Potentilla nepalensis belongs to the Rosaceae family, and has numerous therapeutic applications as potent plant-based medicine. Forty phytoconstituents (PCs) from the root and stem through n-hexane (NR and NS) and methanolic (MR and MS) extracts were identified in our earlier studies. However, the PCs affecting human genes and their roles in the body are not disclosed till now. In this study, we employed network pharmacology, molecular docking, molecular dynamics simulations (MDS), and MMGBSA methodologies. SMILES format of PCs from the PubChem used as input to DIGEP-Pred, 764 identified as the inducing genes. Their enrichment studies have shown inducing genes gene ontology descriptions, involved pathways, associated diseases, and drugs. PPI networks constructed in String DB and network topological analysing parameters done in Cytoscape v3.10 revealed three biomarkers, TP53 from MS, NR, and NS induced genes; HSPCB and Nf-kB1 from MR induced genes. From 40 PCs, two PCs 1b (MR) and 2a (MS), showed better binding scores (kcal/mol) with p53 protein of -8.6, and -8.0; three PCs 3a, (NR) 4a and 4c (NS) with HSP protein of -9.6, -8.7, and -8.2. MDS and MMGBSA revealed these complexes are stable without higher deviations with better free energy values. Biomarkers identified in this study, have a prominent role in numerous cancers. Thus, further investigations such as in-vivo and in-vitro should be done to find the molecular functions and interlaying mechanism of the identified biomarkers on numerous cancer cell lines in considering the PCs of P.nepalensis.

Chronic Traumatic Encephalopathy (CTE) is a neurodegenerative disease consistently associated with repetitive traumatic brain injuries (TBIs), which makes multiple professions, such as contact sports athletes, especially susceptible to its onset. There are currently no approved biomarkers to diagnose CTE, thus it can only be confirmed through a post-mortem brain autopsy. Several imaging and cerebrospinal fluid biomarkers have shown promise in the diagnosis. However, blood-based biomarkers can be more easily obtained and quantified, increasing their clinical feasibility and potential for prophylactic use. This article aimed to comprehensively review the studies into potential blood-based biomarkers of CTE, discussing common themes and limitations as well as suggesting future research directions. While the interest in blood-based biomarkers of CTE has recently increased, the research is still in its early stages. The main issue for many proposed biomarkers is their lack of selectivity for CTE. However, several molecules, such as tau phosphorylated on different epitopes, were able to discern CTE from different neurodegenerative diseases. Further, results from studies of exosomal biomarkers suggest that exosomes are a promising source of biomarkers reflective of the internal environment of the brain. Nonetheless, more longitudinal studies combining imaging, neurobehavioral and biochemical approaches are warranted to establish robust biomarkers of CTE.

Early diagnosis and appropriate treatments are crucial to reducing mortality risk in septic patients. Low SOFA scores and current biomarkers may not discern adequately patients that could develop severe organ dysfunction or have an elevated mortality risk. The aim of this prospective observational study is to evaluate the predictive value of the biomarkers midregional proadrenomedullin (MR-proADM), procalcitonin (PCT), C-Reactive Protein (CRP), and lactate for 28-day mortality in patients with sepsis and a SOFA score ≤ 6. 284 patients were included, with a 28-day all-cause mortality of 8.45 % (N=24). Non-survivors were older (p=0.003), required mechanical ventilation (p=0.04) and were ventilated for longer (p=0.02), had a higher APACHE II (p=0.015) and SOFA (p=0.027) scores. Lactate showed the highest predictive ability for all-cause 28-day mortality with an area under the receiver-operating characteristic curve (AUROC) of 0.67 (0.55–0.79). The AUROC for all-cause 28-day mortality in patients with community-acquired infection was 0.69 (0.57–0.84) for SOFA, and 0.70 (0.58–0.82) for MR-proADM. A 2.1 nmol/L cut-off point for this biomarker in this subgroup of patients discerned with 100% sensibility survivors from non-survivors at 28 days. In patients with community acquired sepsis and initial SOFA score ≤ 6, MR-proADM could help identify patients at risk of 28-day mortality.

Renal cell carcinoma (RCC) is the second most common cancer of the urinary system. The current therapeutic strategies are based on partial or total nephrectomy and/or targeted therapies based on immune checkpoint inhibitors to which patients are often refractory. Preventive and screening strategies are not existing and the few available biomarkers for RCC are characterized by the lack of sensitivity, outlining the need of novel noninvasive and sensitive biomarkers for an early diag-nosis and a better disease monitoring. Blood liquid biopsy (LB) is a non- or minimally invasive procedure for a more representative view of tumor heterogeneity than the tissue biopsy, poten-tially allowing real-time monitoring of cancer evolution. Growing interest is focused on the extra-cellular vesicles (EVs) secreted by either healthy or tumoral cells and recovered in a variety of bio-logical matrices, blood included. EVs are involved in cell-to-cell crosstalk transferring their mRNAs, miRNAs, and proteins content. In particular, transferred miRNAs may regulate the tu-morigenesis and proliferation also impacting on resistance to apoptosis, thus representing poten-tial useful biomarkers. Here we present the latest efforts in the identification of circulating miR-NAs in blood samples, focusing on the potential use of EV derived miRNAs as RCC diagnostic, prognostic markers.

The cell stress response is an essential system present in every cell for responding and adapting to extracellular environmental stimulations. A major program for stress response is the heat shock factor (HSF)–heat shock protein (HSP) system that maintains proteostasis in cells and promotes cancer progression. However, less is known about how the cell stress response is regulated by alternative transcription factors. Here, we show that the SCAN domain-containing transcription factors (SCAN-TFs) are involved in repressing the stress response in cancer. SCAND1 and SCAND2 are SCAN-TFs that can hetero-oligomerize with SCAN-zinc finger transcription factors, such as MZF1(ZSCAN6), for accessing DNA and transcriptionally co-repressing target genes. We found that heat stress induced the expression of both SCAND1 and MZF1(ZSCAN6) bound to HSP90 gene promoter regions in prostate cancer cells. SCAND1 and MZF1 blocked the heat shock responsiveness of HSP90 in prostate cancer cells. Gene expression of SCAND2, SCAND1 and MZF1 was negatively correlated with HSP90 expression in patients-derived prostate adenocarcinoma. MZF1 and SCAND2 were more highly expressed in paired normal tissues than in tumor tissues in several cancer types. High expression of SCAND2, SCAND1 and MZF1 correlated with enhanced prognoses of pancreatic cancer and head and neck cancers. Additionally, high expression of SCAND2 was correlated with better prognoses of lung adenocarcinoma and sarcoma. In contrast, high expression of HSP90AA1 correlated with poorer prognoses in several cancer types. These data suggest that the stress-inducible SCAN-TFs can function as a feedback system, suppressing excessive stress response and inhibiting cancers.

Rheumatoid arthritis (RA) is an autoimmune disease in which joints are gradually de-stroyed, and early diagnosis and treatment before joint deformation or destruction is im-portant. The detection of novel RA biomarkers in saliva may facilitate the early detection of RA before the onset of disease. In this study, we conducted a comprehensive proteomic analysis of salivary proteins from RA model mice. Proteins were identified by Western blotting and enzyme-linked immunosorbent assay in serum, saliva, and ankle joints from DBA/1JJmsSlc mice, a model of rheumatoid arthritis. Ankle joints and submandibular glands were hematoxylin and eosin stained and immunostained, and the results were compared with those of control mice. Citrullinated α1 antitrypsin (A1AT, 46 kDa) was commonly detected in saliva, serum, and ankle joints of severe RA model mice, and was confirmed by proteome analysis. Western blotting detected a band corresponding to 46 kDa in serum, saliva and ankle joints, and immunostaining of ankle joints with A1AT an-tibody showed a strong positive signal in the synovium. In DBA/1JJmsSlc mice, not only cyclic citrullinated peptide antibodies but also A1AT may be involved in protein citrulli-nation and contribute to the development and severity of RA.

The most important predictors for outcomes after ischemic stroke, that is, for health deterioration and death, are chronological age and stroke severity; gender, genetics and lifestyle / environmental factors also play a role. Of all these, only the latter can be influenced after the event, even though recurrent stroke may be prevented by antiaggregant/anticoagulant therapy, angioplasty of high-grade stenoses, and treatment of cardiovascular risk factors. Moreover, blood cell composition and protein biomarkers such as C-reactive protein or interleukins in serum are frequently considered as biomarkers of outcome. We surveyed protein biomarkers that were reported to be predictive for outcome after ischemic stroke, specifically considering biomarkers that predict long-term outcome (≥3 months) and that are measured over the first days following the event. We classified the protein biomarkers as immune‑inflammatory, coagulation-related, and adhesion-related biomarkers. Some of these biomarkers are closely related to cellular senescence and, in particular, to the inflammatory processes that can be triggered by senescent cells. Moreover, the processes that underlie inflammation, hypercoagulation and cellular senescence connect stroke to cancer, and biomarkers of cancer-associated thromboembolism, as well as of sarcopenia, overlap strongly with the biomarkers discussed here. Finally, we demonstrate that most of the outcome-predicting protein biomarkers form a close-meshed functional interaction network, suggesting that the outcome after stroke is partially determined by an interplay of molecular processes relating to inflammation, coagulation, cell adhesion and cellular senescence.

Iron (Fe) is a trace element that plays essential roles in various biological processes such as DNA synthesis and repair, as well as cellular energy production, or oxygen transport, and it is currently widely recognized that iron homeostasis is dysregulated in many cancers. Indeed, several iron homeostasis proteins may be responsible for malignant tumor initiation, proliferation, and for metastatic spread of tumors. A large number of studies demonstrated the potential clinical value of turning these deregulated proteins as prognostic and/or predictive biomarkers of malignancy and /or response to anticancer treatments. Additionally, the iron addiction of cancer cells and the importance of iron in ferroptosis cell death signaling pathways prompted the development of therapeutic strategies against advanced stage or resistant cancers. In this review, we selected relevant and promising studies in the field of iron metabolism in cancer research and clinical oncology. Besides, we discuss some co-existing discrepant findings. We will also present and discuss the latest lines of research related to targeting iron, or its regulatory pathways, as potential promising anti-cancer strategies for human therapy. Iron chelators, such as deferoxamine or iron-oxide based nanoparticles, which are already tested in clinical trials, alone or in combination with chemotherapy will also be reported.

Background: Diabetes is among the most prevalent diseases worldwide, of all the affected individuals a significant proportion of the population remains undiagnosed because of a lack of specific symptoms early in this disorder and inadequate diagnostics. Diabetes and its associated sequela, i.e., comorbidity are associated with microvascular and macrovascular complications. As diabetes is characterized by an altered metabolism of key metabolites and regulatory pathways. Metabolic phenotyping can provide us with a better understanding of the unique set of regulatory perturbations that predispose to diabetes and its associated comorbidities. Methodology: The present study utilizes the analytical platform NMR spectroscopy coupled with Random Forest statistical analysis to identify the discriminatory metabolites of diabetes (DB) and diabetes-related comorbidity (DC) along with the healthy control (HC) subjects. A combined and pairwise analysis was performed, between the serum samples of HC (n=50), and DB (n=38), and DC (n=35) individuals to identify the discriminatory metabolites responsible for class separation. The perturbed metabolites were further rigorously validated using t-test, AUROC analysis to examine the statistical significance of the identified metabolites. Results: The DB and DC patients were well discriminated from HC. However, 15 metabolites were found to be significantly perturbed in DC patients compared to DB, the identified panel of metabolites are TCA cycle (succinate, citrate), methylamine metabolism (trimethylamine, methylamine, betaine), -intermediates; energy metabolites (glucose, lactate, pyruvate); and amino acids (valine, arginine, glutamate, methionine, proline and threonine). The metabolites were further used to identify the perturbed metabolic pathway and correlation of metabolites in DC patients. Conclusion: The 1H NMR metabolomics may prove a promising technique to differentiate and predict diabetes and its comorbidities on their onset or progression by determining the altered levels of the metabolites in serum.

At present, there are still no specific therapeutic drugs and appropriate vaccines for Dengue. Therefore, it is very important to explore distinct clinical diagnostic indicators. In this study, we combined differentially expressed genes (DEGs) analysis and weighted co-expression network analysis (WGCNA) to screen a stable and robust biomarker which can be used to distinguish three clinical stages of Dengue and severity of Dengue. CD38 can distinguish excellently Early Acute, Late Acute, Convalescent stages for Dengue patients, and ZNF595 can discriminate DHF from DF in whole acute stages. We also found that three clinical stages can be discriminated based on the fractions of Plasma cells, activated memory CD4+ T cells, and Monocytes. In different clinical stages different immune cells function positively. Negative inhibition of viral replication based on Gene Ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis and Gene set enrichment analysis (GSEA), up-regulated autophagy genes and impairing immune system are potential reasons resulting in dengue hemorrhagic fever (DHF).

Background: Aberrations in endothelial cells, immune and oxidative pathways are associated with atherosclerosis (ATS) and unstable angina (UA). The role of trace elements, minerals, and the endogenous opioid system (EOS) in UA are less well established. Methods: We measured lipid, insulin resistance (IR), and immune, trace element (copper and zinc), mineral (magnesium, calcium), EOS (β-endorphin and mu-opioid receptor (MOR)) and antioxidant (vitamin D3) biomarkers in patients with ATS (n=60) and UA (n=60) and healthy controls (n=58). Results: ATS patients showed increased atherogenic and IR indices, IL-6, IL-10, β-endorphin, copper and magnesium, and lower zinc than healthy controls. Logistic regression showed that UA was significantly discriminated from ATS without UA with an accuracy of 85.5% using calcium, IL-10, β-endorphin, MOR, triglycerides, IR (all positively), and copper and vitamin D3 (inversely). Neural networks showed that UA was discriminated from ATS without UA with an area under the ROC curve of 0.942 using MOR, β-endorphin, calcium, insulin resistance, vitamin D3 and copper as input variables. We found that 50.0% of the variance in IR was explained by the regression on copper, IL-10, IL-6 (all positively), and zinc (inversely), while 32.9% of the variance in the atherogenic index of plasma was explained by copper, IL-10 (both positively), and magnesium (inversely). Conclusion: UA is not only mediated by insulin resistance, atherogenicity, and immune disorders, but also by aberrations in the endogenous opioid system and trace elements as well as lowered antioxidant levels. Copper appears to play a key role in IR and atherogenicity.

Rosavin, a phenylpropanoid in Rhodiola rosea's rhizome, an adaptogen, is known for enhancing the body's response to environmental stress. It significantly affects cellular metabolism in health and many diseases, particularly influencing bone tissue metabolism. In vitro, rosavin inhibits osteoclastogenesis, disrupts F-actin rings formation, and lowers osteoclastogenesis-related gene expression (cathepsin K, CTR, TRAF6, TRAP, MMP-9). It also impedes NFATc1, c-Fos, NF-κB, and MAPK signaling pathways, and blocks phosphorylation processes crucial for bone resorption. Moreover, rosavin promotes osteogenesis, osteoblast differentiation and increases Runx2 and OCN expression. In vivo studies show its effectiveness in enhancing BMD in PMOP mice, re-straining osteoclast maturation, and increasing active osteoblast percentage in bone tissue. It modulates mRNA expressions (increasing EEF2 and decreasing HDAC1, thereby activating os-teoprotective epigenetic mechanisms) and alters various serum markers, including decrease of CTX-1, TRAcp5b, RANKL, M-CSF, TRAP, and increase of ALP and OCN. Additionally, when combined with zinc and probiotics, it reduces pro-osteoporotic MMP-3, IL-6, TNF-α, and en-hances anti-osteoporotic IL-10 and TIMP3 expressions. This paper aims to systematically review rosavin's impact on bone tissue metabolism, exploring its potential in osteoporosis prevention and treatment, and suggesting future research directions.

This review explores the transformative impact of sensor technologies in early disease detection. It highlights recent advancements in nanotechnology-based sensors, particularly focusing on their applications in identifying disease biomarkers at early stages. The integration of these sensors with artificial intelligence for predictive analytics in healthcare is also discussed. Applications in cancer, infectious diseases, and chronic disease management underscore their diverse utility. Challenges in sensor technology adoption and future directions, including multiplexed sensors and wearable devices, are examined. This review underscores sensors' potential in enhancing disease management and patient outcomes.

Herpesvirus is a prevalent pathogen that primarily infects human epithelial cells and has the ability to reside in neurons. In the field of otolaryngology, herpesvirus infection primarily leads to hearing loss and vestibular neuritis, and is considered the primary hypothesis regarding the pathogenesis of vestibular neuritis. In this review, we provide a summary of the effects of herpes virus on cellular processes in both host cells and immune cells, with a focus on HSV-1 as illus-trative examples.

Energy demand has exponentially increased with the increase in the world population and ur-banization. Renewable energy is clean, renewable, and environmentally friendly. Hydrogen production through Proton Exchange Membrane (PEM) electrolyzer is an efficient way to produce renewable energy. The efficiency and energy consumption of the PEM electrolyzer depends on the feed water quality. In this report, we study the effect of pH, TDS, and conductivity on hydrogen production as well as energy consumption during the process. pH values (3, 7, 9), TDS values (300ppm, 600ppm, 900ppm), and conductivity values (30mS/cm, 70mS/cm, 100mS/cm) were studied to understand and optimize the hydrogen production using PEM electrolyzer. The in-vestigations showed that hydrogen production is significantly affected by pH, total dissolved solids, and conductivity, and the best levels of each variable were identified by extensive testing. The findings show both the scientific significance of proton exchange electrolysis in meeting the growing energy demands of society as well as the importance of knowing the influence that di-verse conditions have on the creation of hydrogen. Our research, in general, contributes to the expanding body of scientific knowledge on the topic of the effective production of hydrogen and offers useful insights for the continuation of investigation in this field.

The article is aimed at a brief comparison and analysis of the results of queries to IEEE Xplore and the leading abstract databases Scopus and Web of Science to identify research trends. Some errors in the Author Keywords in Web of Science have been revealed. Therefore, a more detailed analysis was conducted by comparing different types of key terms for IEEE Xplore and Scopus platforms only. I used IEEE Access journal metadata as indexed on both platforms. The sample match for IEEE Xplore and Scopus was achieved by comparing DOI. The IEEE Xplore metadata contains more types of key terms, which provides an advantage in analyzing research trends. Using NSPEC Controlled Terms from expert-compiled vocabulary provides a more stable data, which gives an advantage when considering the change of terms over time. Apriori, an algorithm for finding association rules, has been used to compare co-occurrence of terms for a more detailed description of sample subjects on both platforms. VOSviewer was used to analyze trends in scientific research based on IEEE Xplore data. The 2011-2021 ten-year period was divided into two sub-intervals for comparing the occurrence of Author Keywords, IEEE Terms, and NSPEC Controlled Terms. Using the IEEE conference proceedings bibliometric data, I illustrated the importance of context in estimating the rate of growth of publishing activity on a topic of interest.

Intravitreal injection is the gold standard therapeutic option for posterior segment pathologies, and long-lasting release is necessary to avoid reinjections. There is no effective intravitreal treatment for glaucoma or other optic neuropathies in daily practice, nor is there a non-invasive method to monitor drug levels in the vitreous. Here we show that a glaucoma treatment combining a hypotensive and neuroprotective intravitreal formulation (IF) of brimonidine-Laponite (BRI/LAP) can be monitored non-invasively using vitreous imaging captured with optical coherence tomography (OCT) over 24 weeks of follow-up. Qualitative and quantitative characterization was achieved by analysing the changes in vitreous (VIT) signal intensity, expressed as a ratio of retinal pigment epithelium (RPE) intensity. Vitreous hyperreflective aggregates mixed in the vitreous and tended to settle on the retinal surface. Relative intensity and aggregate size progressively decreased over 24 weeks in treated rat eyes as the BRI/LAP IF degraded. VIT/RPE relative intensity and total aggregate area correlated with brimonidine levels measured in the eye. The OCT-derived VIT/RPE relative intensity may be a useful and objective marker for non-invasive monitoring of BRI/LAP IF.

Acute coronary syndrome (ACS) is a life-threatening condition that requires a prompt diagnosis and therapeutic intervention. Although serum troponin T and creatinine kinase-MB (CK-MB) are established biomarkers for ACS, it may take several hours to reach diagnostic values for ACS. In this study, we attempted to explore novel biomarkers for ACS with higher sensitivity than that of troponin T and CK-MB. The metabolomic profiles of 18 patients with ACS upon hospital arrival and those of the age-matched control (HC) group consisted of 24 healthy volunteers were analyzed using liquid chromatography-time-of-flight mass spectrometry. Volcano plots showed 24 metabolites whose concentrations differed significantly between the ACS and HC groups. Using these data, we developed a multiple logistic regression model for the ACS diagnosis, in which lysine, isocitrate, and tryptophan were selected as minimum-independent metabolites. The area under the receiver operating characteristic curve value for discriminating ACS from HC was 1.00 (95% confidence interval [CI]: 1.00-1.00). In contrast, those for troponin T and CK-MB were 0.917 (95% confidence interval [CI]: 0.812-1.00) and 0.988 (95% CI: 0.966-1.00), respectively. This study showed the potential of combining three plasma metabolites to discriminate ACS from HC with a higher sensitivity than that of troponin T and CK-MB.

Lung cancer remains the leading cause of cancer-related mortality worldwide. The main issue is the absence of a screening test available in clinical practice; the identification of non-invasive biomarkers is thus an urgent clinical necessity. Currently, low-dose computed tomography (LD-CT) demonstrates a 20% reduction of lung cancer mortality. However, it is not particularly suitable for clinical practice because of the costs, radiation, and the false positive rate. Several studies have therefore focused on research into biomarkers in body fluids. Despite the power of certain molecules to distinguish lung cancer patients from healthy subjects, no biomarker has yet been shown to significantly and reliably influence clinical decisions or to be translated from the laboratory to clinical practice. We performed an overview of the peer-reviewed biomedical literature published in the last 10 years on the research regarding biomarkers for the early diagnosis of lung cancer via a comprehensive analysis of the reviews published this past year. Our main aim was to bring to light the limitations and strengths of the research already conducted. Furthermore, future prospectives have been explored, bearing in mind the management of clinical trials and their integration into clinical practice.

Blood-based circulating cell free DNA(cfDNA) detection offers a non-invasive and easily accessible way for early cancer detection. Despite the extensive utility of cfDNA, there are still many challenges to develop the clinical biomarkers. For example, cfDNA with genetic alterations often compose a small portion of the DNA circulating in plasma, which can be confounded by cfDNA contributed by normal cells. Therefore, filtering out the potential false-positive cfDNA mutations from health population will be important for the cancer-based biomarkers. Additionally, many low-frequency genetic alterations are easily overlooked in small amount of cfDNA-based cancer test. We hypothesize that, the combination of diverse types of cancer studies on cfDNA can provide us a new insight to identify low-frequency genetic variant across cancer types for early clinical detection of cancers. By building a standardized computational pipeline for 1358 cfDNA samples across seven cancer types, we prioritize 129 shard genetic variants in the major cancer types. Further functional analysis of the 129 variants found that they are mainly enriched in ribosome pathways such as cotranslational protein targeting to membrane, some of which are tumor suppressor, oncogene and related to cancer initiation. In summary, our integrative analysis revealed the important roles of ribosome proteins as the common biomarkers in early cancer diagnosis.

Background: The ongoing outbreak of Coronavirus Disease 2019 (COVID-19) represents a major threat to human health, which impairs the functionality of several organs. One of the hardest challenges in the fight against COVID-19 is the development of wide-scale, effective, and rapid laboratory tests to control disease severity, progression, and possible sudden worsening. Monitoring patients in real-time is indeed highly demanded in this pandemic era when physicians need reliable and quantitative tools to prioritize patients’ access to intensive care departments. In this regard, salivary biomarkers are extremely promising, as they allow for a fast and non-invasive specimens’ collection, which can be repeated multiple times. Methods: We compare salivary levels of immunoglobulin A subclasses (IgA1 and IgA2) and free-light chains (FLC k and λ) in a cohort of 29 SARS-CoV-2 patients and 21 healthy subjects. Results: We found that each biomarkers differs significantly between the two groups, with p-values ranging from 10-8 to 10-4. The performance ranking of these markers, shows that λFLC level (p=1.4e-8) is the best-suited candidate to discriminate the two groups, with an accuracy of 0.94 (0.87-1.00 95% CI), a precision of 0.91 (0.81-1.00 95% CI), a sensitivity of 1.00 (0.96-1.00 95% CI) and a specificity of 0.86 (0.70-1.00 95% CI). Conclusion: These results suggest λFLC as an ideal indicator of patient conditions. This is more strengthened in consideration that λFLC half-life (approximately 6 hours) is significantly shorter than the IgA one (21 days): thus λFLC appears displaying the potential to effectively monitor patients fluctuation in real-time.

Neurodegenerative diseases are multifactorial, initiated by a series of the causative complex which develops into a certain clinical picture. The pathogenesis and disease course vary from patient to patient. Thus, it should be likewise to the treatment. Peripheral biomarkers are to play a central role for tailoring a personalized therapeutic plan for patients who suffered from neurodegenerative diseases such as Alzheimer’s diseases, Parkinson’s disease, and multiple sclerosis, among others. Nevertheless, the use of biomarkers in clinical practice is still underappreciated and data presented in biomarker research for clinical use is still uncompelling, compared to abundant data available for drug research and development. So is the case with kynurenines (KYNs) and the kynurenine pathway (KP) enzymes which have been associated with a wide range of diseases including cancer, autoimmune diseases, inflammatory diseases, neurologic diseases, and psychiatric disorders. This review article discusses current knowledge of the KP alteration observed in the central nervous system as well as the periphery, its involvement in pathogenesis and disease progression, and emerging evidence of roles of microbiota to the gut-brain axis, searching for practical peripheral biomarkers which ensure personalized treatment plans for neurodegenerative diseases.

Background: Meniere's disease (MD) has been recently linked to gluten assumption. Approximately 75% of MD patients show positive skin test to food and about 50% of the positive responses are specific to the gliadin acid extract fraction. Aim of this study was to investigate the humoral immune responses to wheat antigens and related autoantigens in MD patients. Methods. We assessed the reactivity of sera from 28 patients with definite MD and 100 healthy controls against a repertoire of 51 antigens usually associated with immune reaction to gluten. Results. MD patients showed an increase of anti-wheat IgA, anti-cerebellar peptide IgA and anti-glutamic acid decarboxylase (GAD) 65 IgM compared to healthy controls. In particular, the increase of anti-wheat IgA and GAD 65 IgM has been confirmed in a subgroup of MD patients symptomatically responding to a gluten free diet (GFD). Conclusion. In MD patients, an increase of the antibody production against gluten biomarkers was observed; in particular, anti-wheat IgA seems to be associated to clinical response to GFD.

Besides the increase in global energy demand, access to clean energy, reduction in greenhouse gas emissions caused by conventional power generation sources, energy security, and availability of electricity in remote villages in emerging nations are some of the factors that foster the use of renewable energy sources (RESs) in generating electricity. One of the aims of initiating microgrids (MGs) is to maximize the benefits of RES and alleviate the associated grid integration issues. Microgrids are made up of RES connected to electrical loads within clearly delineated electrical limits that operate as individual controllable units on the electrical network. It can operate in-dependently as well as in connection with the grid. The paper presents an overview of microgrids and investigates the system's performance when connected to and disconnected from the grid. Furthermore, in both modes of operation, the functioning and behavior of system components such as the bidirectional DC-DC converter and energy storage system (ESS) were evaluated. The architecture of the proposed microgrid consists of a small hydropower plant, a wind farm, and a battery energy storage system (BESS). The microgrid under investigation is modeled and simu-lated using MATLAB and Simulink.

Background: Systemic lupus erythematosus (SLE) is characterized by inflammation and cardiovascular complications. Our study aimed to investigate subclinical and early indicators of systolic myocardial dysfunction in SLE patients using advanced echocardiographic methods and biomarkers. Methods: In this cross-sectional study, we enrolled 102 SLE patients without known cardiac impairment and 51 healthy controls. Demographics, disease characteristics, laboratory results, disease activity (SLEDAI) and organ damage (SDI) indices were recorded. Left ventricular global longitudinal strain (GLS) and myocardial work indices were assessed by utilizing speckle tracking echocardiography. In addition, high sensitivity C-reactive protein (hsCRP), high sensitivity troponin (hsTn) and N-terminal-pro B-type natriuretic peptide (NT-proBNP) levels were measured in blood samples. Results: In comparison to controls, SLE patients had significantly higher GLS (-19.94±2.71%vs-21.15±1.55%, p<0.001) and global wasted work (GWW) (94±71mmHg%vs71±49 mmHg%, p=0.025). Notably, NT-proBNP and hsTn were threefold and twofold higher in SLE group compared to control group, respectively (p<0.001). Within SLE cohort, patients with at least moderate disease activity (SLEDAI≥4) both biomarkers were significantly elevated than those with low disease activity (SLEDAI<4). Conclusion: Advanced echocardiographic parameters combined with specific biomarkers have a promising role in detecting systolic dysfunction at an early phase in SLE patients, potentially enabling timely interventions to mitigate cardiovascular risk.

Extracellular vesicle-derived microRNAs (EV-miRNAs) are promising circulating biomarkers for chronic liver disease. In this study, we explored the potential significance of plasma EV-miRNAs in non-hepatitis B-, non-hepatitis C-related HCC (NBNC-HCC). We compared plasma EV-miRNA profiles between NBNC-HCC and control groups including non-alcoholic fatty liver disease (NAFLD) and healthy controls using NanoString method. The differentially expressed EV-miRNAs were validated in another set of plasma samples by qRT-PCR. A total of 66 significantly differentially expressed EV-miRNAs between the HCC and control groups were identified in the discovery set. In the validation cohort including plasma samples of 70 NBNC-HCC, 70 NAFLD and 35 healthy controls, 5 plasma EV-miRNAs were significantly elevated in HCC, which included miR-19-3p, miR-16-5p, miR-223-3p, miR-30d-5p, and miR-451a. These miRNAs were found to participate in several cancer-related signaling pathways based on bioinformatic analysis. Among them, EV-miR-19-3p exhibited the best diagnostic performance and displayed a high sensitivity for detecting AFP-negative HCC and early-stage HCC. In multivariate analysis, high EV-miR-19-3p level was demonstrated as an independently unfavorable predictor of overall survival in patients with NBNC-HCC. In conclusion, our data have indicated for the first time that EV-miR-19-3p could serve as a novel circulating biomarker for the diagnosis and prognosis of NBNC-HCC.

People with diabetic foot frequently exhibit poor gait and balance. However, there is no review to inform digital biomarkers of poor gait and balance related to diabetic foot, measurable by wearables outside traditional gait laboratories. Such information could assist in designing remote patient monitoring platform to track changes in gait and balance dysfunction among people with diabetic foot for timely referral and intervention. Accordingly, we conducted a web-based review using PubMed. Our search was limited to human subjects and English-written papers published in peer-reviewed journals. We identified 20 papers in this review. We found preliminary evidence of digital biomarkers of gait and balance dysfunction in people with diabetic foot, measured by wearables, such as slow gait speed, large gait variability, unstable gait initiation, and large body sway. However, due to heterogeneities in included papers in terms of study design, movement tasks, and small sample size, more studies are recommended to confirm this preliminary evidence. Additionally, based on our review, we recommend establishing appropriate strategies to successfully implement wearable-based assessment into clinical practice for diabetic foot care.

Background: Clozapine (CLZ) use is precarious due to its neurological, cardiovascular, and hematological side effects; however, it is the gold standard in therapy-resistant schizophrenia (TRS) in adults and is underused. Objective: to examine the most recent CLZ data on (a) side effects concerning (b) recent pharmacological mechanisms, (c) therapy benefits, and (d) the particularities of the COVID-19 pandemic. Data sources: a search was performed in two databases (PubMed and Web of Science) using the specific keywords "clozapine" and "schizophrenia," "side effects," "agranulocytosis," "TRS," or "bipolar affective disorder (BAF)" for the last ten years. Study eligibility criteria: clinical trials on adults with acute symptoms of schizophrenia or related disorders. Results: We selected 37 studies, randomized controlled trials (RCTs), and clinical case series (CCS), centered on six main topics in the search area: (a) CLZ in schizophrenia, (b) CLZ in bipolar disorder, (c) side effects during the clozapine therapy, (d) CLZ in pregnancy, (e) CLZ in early-onset schizophrenia, and (f) CLZ therapy and COVID-19 infection. Limitations: We considered RCTs and CCS from two databases, limited to the search topics. Conclusions and implications of key findings: (a) Clozapine doses should be personalized for each patient based on pharmacogenetics testing when available; the genetic vulnerability postulates predictors of adverse reactions' severity; patients with a lower genetic risk could have less frequent hematological monitoring; (b) CLZ-associated risk of pulmonary embolism imposes prophylactic measures for venous thromboembolism; (c) convulsive episodes are not an indication for stopping treatment; the plasma concentration of clozapine is a better side effect predictor than the dosage; (d) COVID-19 infection may enhance clozapine toxicity, generating an increased risk of pneumonia. Therapy must be continued with proper monitoring of the white blood count, and the clozapine dose decreased by half until three days after the fever breaks; psychiatrists and healthcare providers must act together. Background: Clozapine (CLZ) use is precarious due to its neurological, cardiovascular, and hematological side effects; however, it is the gold standard in therapy-resistant schizophrenia (TRS) in adults and is underused. Objective: to examine the most recent CLZ data on (a) side effects concerning (b) recent pharmacological mechanisms, (c) therapy benefits, and (d) the particularities of the COVID-19 pandemic. Data sources: a search was performed in two databases (PubMed and Web of Science) using the specific keywords "clozapine" and "schizophrenia," "side effects," "agranulocytosis," "TRS," or "bipolar affective disorder (BAF)" for the last ten years. Study eligibility criteria: clinical trials on adults with acute symptoms of schizophrenia or related disorders. Results: We selected 37 studies, randomized controlled trials (RCTs), and clinical case series (CCS), centered on six main topics in the search area: (a) CLZ in schizophrenia, (b) CLZ in bipolar disorder, (c) side effects during the clozapine therapy, (d) CLZ in pregnancy, (e) CLZ in early-onset schizophrenia, and (f) CLZ therapy and COVID-19 infection. Limitations: We considered RCTs and CCS from two databases, limited to the search topics. Conclusions and implications of key findings: (a) Clozapine doses should be personalized for each patient based on pharmacogenetics testing when available; the genetic vulnerability postulates predictors of adverse reactions' severity; patients with a lower genetic risk could have less frequent hematological monitoring; (b) CLZ-associated risk of pulmonary embolism imposes prophylactic measures for venous thromboembolism; (c) convulsive episodes are not an indication for stopping treatment; the plasma concentration of clozapine is a better side effect predictor than the dosage; (d) COVID-19 infection may enhance clozapine toxicity, generating an increased risk of pneumonia. Therapy must be continued with proper monitoring of the white blood count, and the clozapine dose decreased by half until three days after the fever breaks; psychiatrists and healthcare providers must act together.

The goal of newborn screening is to improve health outcomes by identifying and treating affected newborns. This manuscript provides an overview of a data tool to facilitate the longitudinal collection of health information on newborns diagnosed with a condition through NBS. The Newborn Screening Translational Research Network (NBSTRN) developed the Longitudinal Pediatric Data Resource (LPDR) to capture, store, analyze, visualize, and share genomic and phenotypic data over the lifespan of NBS identified newborns to facilitate understanding of genetic disease, and to assess the impact of early identification and treatment. NBSTRN developed a consensus-based process using clinical care experts to create, maintain, and evolve question and answer sets organized into common data elements (CDEs). The LPDR contains 24,172 core and disease-specific CDEs for 118 rare genetic diseases, and the CDEs are being made available through the NIH CDE Repository. The number of CDEs for each condition average of 2,200 with a range from 69 to 7,944. The LPDR is used by state NBS programs, clinical researchers, and community-based organizations. Case level, de-identified data sets are available for secondary research and data mining. The development of the LPDR for longitudinal data gathering, sharing, and analysis supports research and facilitates the translation of new discoveries into clinical practice.

Our investigations show that electrochemical corrosion of copper is faster than electrochemical corrosion of aluminium at temperatures below 100oC. Literature data analysis shows that the Al atoms diffuse faster than the Cu atoms at temperatures higher than 475oC, Al rich intermetallic compounds (IMCs) are formed faster in the Cu-Al system, and the Kirkendall plane shifts toward Al side. Electrochemical corrosion occurs due to electric current and due to diffusion. An electronic devise working time, for example, depends on initial copper cover thickness on aluminium wire, connected to the electronic devise, temperature, and volume and dislocation pipe diffusion coefficients, so copper, iron, and aluminium electrochemical corrosion rates are investigated experimentally at room temperature and at temperature 100oC. Intrinsic diffusivities ratios of copper and aluminium at different temperatures and diffusion activation energies in the Cu-Al system are calculated by proposed here methods using literature experimental data. Dislocation pipe and volume diffusion activation energies of pure iron are calculated separately by earlier proposed method using literature experimental data. Aluminium dissolved into NaCl solution as the Al3+ ions at room temperature and at temperature 100oC, iron dissolved into NaCl solution as the Fe2+ (not Fe3+) ions at room temperature and at temperature 100oC, copper dissolved into NaCl solution as the Cu+ ions at room temperature and as the Cu+ and the Cu2+ ions at temperature 100oC. It is founded experimentally that copper corrosion is higher than aluminium corrosion, and ratio of electrochemical corrosion rates, kCu/kAl>1, decreases with temperature increasing, although iron electrochemical corrosion rate doesn’t depend on temperature below 100oC. It is obvious, because melting point of iron is more higher then melting point of copper or aluminium. It is calculated that copper electrochemical corrosion rate is approximately equal to aluminium electrochemical corrosion at temperature about 300oC, so copper can dissolve into NaCl solution mostly as the Cu2+ ions at temperature about 300oC. Ratio of intrinsic diffusivities, DCu/DAl <1, increases with temperature increasing, and intrinsic diffusivity of aluminium could be approximately equal to intrinsic diffusivity of copper at temperature about 460oC.

Graft injury affects over 50% of liver transplant (LT) recipients, but non-invasive biomarkers to diagnose and guide treatment are currently limited. We aimed to develop a biomarker of graft injury by integrating serum metabolomic profiles with clinical variables. Serum from 55 LT recipients with biopsy confirmed metabolic-dysfunction associated steatohepatitis (MASH), T-cell mediated rejection (TCMR) and biliary complications was collected and processed using a combination of LC-MS/MS assay. The metabolomic profiles were integrated with clinical information using a multi-class Machine Learning (ML) classifier. The efficacy of the model was assessed through the evaluation of the Out-of-Bag (OOB) error estimate. Our ML model yielded an overall accuracy of 79.66% with an OOB estimate of the error rate at 19.75%. The model exhibited a maximum ability to distinguish MASH, with an OOB error estimate of 7.4% compared to 22.2% for biliary and 29.6% for TCMR. The metabolites serine and serotonin emerged as the topmost predictors. When predicting binary outcomes using 3 models: Biliary (biliary vs. rest), MASH (MASH vs. rest) and TCMR (TCMR vs. rest), the AUCs were 0.882, 0.972 and 0.96 respectively. Our ML tool integrating serum metabolites with clinical variables shows promise as a non-invasive, multi-class serum biomarker of graft pathology.

Introduction: Advanced glycation end-products (AGEs) may play a relevant role as inducers in the chronic inflammatory pathway present in immune-mediated diseases, such as systemic lupus erythematosus (SLE). AGEs concentrations have been associated, with discrepant results to date, with some parameters such as disease activity or accrual damage, suggesting their potential usefulness as biomarkers of the disease. Objectives: To confirm differences in AGEs levels measured by cutaneous autofluorescence between SLE patients and healthy controls (HC) and study their correlation with various disease parameters. Methods: Cross-sectional study, where AGEs levels were measured by skin autofluorescence, and SLE patients’ data were compared with those of sex- and age-matched HC in a 1:3 proportion through a multiple linear regression model. Correlations of AGEs levels with demographic and clinical data were analyzed through ANOVA tests. Both analyses were adjusted for confounders. Results: AGEs levels in SLE patients were significantly higher than in HC (p<0.001). We found statistically significant positive correlation with SLE disease activity index (SLEDAI) and damage index (SDI), physician and patient global assessment, C-reactive protein, leukocyturia, complement C4, IL6 and oral ulcers. We also found a negative statistically significant correlation with current positivity of anti-nuclear and anti-Ro60 antibodies. Conclusions: AGEs seem to have a role in LES pathophysiology, becoming a new management and prognosis biomarker in this disease. The association with specific antibodies and disease manifestations may indicate a specific clinical phenotype related to higher AGEs levels.

Urolithiasis is an increasingly common clinical problem worldwide. The formation of stones is a combination of metabolic status, environmental factors, family history and many other aspects. It’s important to find new ways to quickly detect and assess urolithiasis because it causes sudden, severe pain and often comes back. One way to do this is by exploring new biomarkers. Current advances in proteomic studies provide a great opportunity for breakthroughs in this field. The study focuses on protein biomarkers and their connection to kidney damage and inflammation during urolithiasis.

Background: The incidence of prostate cancer (PC) has been risen annually. Despite the diagnosis is made mainly with non-metastatic PC, mortality is explained by the metastatic disease (mPC). Without a doubt there is an intermediate scenario in which patients have no mPC but will have initiated a metastatic cascade through an epithelial-mesenchymal transition. There is indeed a need for more and better tools to predict what patients will progress in the future to non-localized clinical disease or already have micrometastatic disease, and therefore, will clinically progress after primary treatment. Biomarkers for predicting mPC are still under development; there are few studies and not much evidence of their usefulness. Summary: This review is focused on tissue-based genomic biomarkers (TBGB) for predicting metastatic disease. We developed four main research questions that will attempt to answer according to the current evidence. Why is important to predict metastatic disease? Which tests are available to predict metastatic disease? What impact should there be on clinical guidelines and clinical practice in predicting metastatic disease? What are current prostate cancer treatments? Key Messages: Knowing useful predict tools could help determine which patients may need multimodal or adjuvant treatment even with a localized disease, and in consequence, what patients do not need more than a single modality of treatment. The importance of predicting metastasis is fundamental, given that once metastasis is diagnosed, the quality of life (QoL) and survival drop dramatically.

Metabolic-associated fatty liver disease (MAFLD) and diabetic kidney disease (DKD) share various pathophysiological factors, and epidemiological evidence suggests that these two diseases are associated. Albuminuria and the estimated glomerular filtration rate, which are conventional biomarkers of DKD, are reportedly associated with the risk or severity of MAFLD. Recently, novel DKD biomarkers reflecting renal tubular injury have been introduced to complement conventional DKD markers. In this article, we looked at previous studies that showed an association between MAFLD and DKD and also reviewed the significance of DKD biomarkers as predictive risk factors for MAFLD.

In this study, novel biomarkers in Blood Mononuclear Cells (PBMCs) of Hepatocellular Carcinoma (HCC) patients were identified through microarray data analysis. The problem that prompted the study was the lack of reliable biomarkers for early diagnosis and monitoring of HCC. The purpose of this study was to discover potential biomarkers in PBMCs of HCC patients that can be used for early diagnosis and monitoring of the disease. The main hypothesis was that there are genes that are overexpressed in PBMC of HCC patients compared to healthy individuals. The results showed that genes HBB, WBP2, HBA2, and HBA1 were overexpressed in PBMCs of HCC patients. Additionally, nine genes were found to be upregulated in HCC patients and had a relation between KEGG pathways of RA, suggesting a link between the two diseases. These genes are TLR4, IL1B, CXCL5, IL11, HLA-DQA1, HLA-DRA, LBT, ATP6V1B2 and ATP6V1C1. The Gene ontology analysis revealed biological processes used in the process of how these genes play a role in development of HCC. In conclusion, this study identified potential biomarkers in PBMC of HCC patients that can aid in early diagnosis and monitoring of the disease. The findings of this study have important implications for improving the clinical management of HCC patients.

In the era of nanotechnology, researchers are implementing point to care service to cancer patients to detect malignancy beforehand and to reduce the mortality rate of cancers. Cancer is known to be the most fatal disease among all other diseases and the survivability from cancer is quite impossible if the stage of the cancer is an advanced level. Though the early detection of cancer can increase the chances of survival with a double fold. Biosensor is a part of nanotechnology which is capable to provide point to care service in the field of medicine. With the rising number of cancer occurrences being identified around the world and the increasing number of deaths because of the identification of advanced cancer, biosensors can play a significant part in the early detection of cancer. New molecular methods, including as genomic and proteomic approaches, are increasingly being used to study patient molecular profiles. When such diagnosis method is paired with bioinformatics tools, they generate new data that can be used to discover new disease biomarkers. Finding precise and sensitive indicators that are corelated to a specific disease, as with many other diseases, can be challenging. Furthermore, the concentration of biomarkers in biological fluids varies according to illness states and phases. Peptides, proteins, up or down regulated expression of gene markers, and gene alternation are all examples of molecular markers that are commonly used to diagnose cancer. In this article, we have highlighted six different deadliest cancers such as Ovarian, Breast, Prostrate, Lung, Colorectal and Liver cancer. The article contains distinct types of biomarkers which are normally found in these kinds of cancer and generally used as a potential diagnostic target in the medicine field. The article mainly summarized the application of different types of biosensors devices in the detection of the mostly found biomarkers in the above cancer types.

Background/Aim: Patients with uterine sarcoma comprise 2%–5% of all patients with uterine malignancies; however, the morbidity of uterine sarcoma is low compared with that of other gynecological cancers. For many cases, malignant uterine tumors are diagnosed during follow-up of benign uterine leiomyoma. Of the uterine sarcomas, rhabdomyosarcoma is considered a mixed tumor containing components of epithelial cells and mesenchymal cells. Therefore, the onset of primary uterine rhabdomyosarcoma during follow-up of uterine leiomyoma is extremely rare. Rhabdomyosarcoma is a relatively common malignant tumor in children, but rhabdomyosarcoma in adults is extremely rare, accounting for approximately 3% of all patients with soft tissue sarcoma. Rhabdomyosarcoma in children is highly sensitive to chemotherapy and radiation therapy; however, the response to chemotherapy and radiation therapy in adult rhabdomyosarcoma is low and survival in adult rhabdomyosarcoma with metastatic lesions to other organs is approximately 14 months. We experienced a case of polymorphic rhabdomyosarcoma during the follow-up of a uterine leiomyoma. Materials and Methods: We examined the oncological properties of uterine rhabdomyosarcoma in adults using molecular pathological techniques on tissue excised from patients with uterine leiomyoma. Result: A differential diagnosis was made for this case by molecular pathology, which included candidate biomarkers for uterine smooth muscle tumors. The oncological nature of uterine rhabdomyosarcoma was found to be similar to the oncological properties of uterine leiomyosarcoma. However, in uterine rhabdomyosarcoma, LMP2/1i-positive cells were clearly observed. Conclusion: It is expected that establishing a diagnostic and treatment method targeting characteristics of mesenchymal tumor cells will lead to the treatment of malignant tumors with a low risk of recurrence and metastasis.

Background/Aims: Screening for gestational diabetes mellitus (GDM) are currently done at 24 - 28 weeks of conception, missing out on the most vulnerable period of organogenesis and thus preventing clinicians from starting treatments until the late second or third trimester. MicroRNAs (miR) are small non-coding RNA molecules that could aid in detecting or predicting GDM through establishing a novel non-invasive prenatal testing (NIPT) tool. The objective of this study was to summarize the most recent updates on plasma microRNAs as GDM diagnostic biomarkers. Methods: Between April and June 2021, a PubMed literature search was undertaken to review recent articles on human plasma miR associated with GDM. Animal studies and papers that are written in languages other than English were excluded. Only plasma miRNAs were used to avoid coagulation biases. Results: A total of 31 miRNAs were found significantly upregulated in the plasma samples of patients with GDM. It was found mainly during the 2nd or 3rd trimester except for miR-223 and miR-23a that were upregulated at 9 – 11 weeks of gestation. Conclusion: Though extensive prospective cohort studies are required, miR-223 and miR-23a should be considered the most promising to develop a successful NIPT tool because they were found to be upregulated earliest, during the first trimester.

KLHL genes and the related KBTBD genes encode components of the Cullin-E3 ubiquitin ligase complex and typically target tissue-specific proteins for degradation, thereby affecting differentiation, homeostasis, metabolism, cell signaling, and the oxidative stress response. Despite their importance in normal cell function and in disease (KLHL40, KLHL41, KBTBD13, KEAP1, and ENC1), previous studies that examined epigenetic factors affecting transcription were predominantly limited to promoter DNA methylation. Using diverse tissue and cell culture whole-genome profiles, we examined 17 KLHL or KBTBD genes preferentially expressed in skeletal muscle or brain to identify tissue-specific enhancer and promoter chromatin, open chromatin (DNaseI hypersensitivity), and DNA hypomethylation. Sixteen of the 17 genes displayed muscle- or brain-specific enhancer chromatin in their gene bodies, and most exhibited specific intergenic enhancer chromatin as well. Seven genes were embedded in a super-enhancer. The enhancer chromatin regions typically displayed foci of DNA hypomethylation at peaks of open chromatin. In addition, we found evidence that gene neighbors (HHATL and FBXO32) of KLHL40 and KLHL38 harbor enhancer chromatin that likely upregulates the adjacent KLHL gene. Many KLHL/KBTBD genes had tissue-specific promoter chromatin at their 5’ ends, but surprisingly, two (KBTBD11 and KLHL31) had constitutively unmethylated promoter chromatin in their 3’ exons that overlaps a retrotransposed KLHL gene. Our findings demonstrate the importance of expanding epigenetic analyses beyond the 5’ ends of genes in studies of normal and abnormal gene regulation.

Background and objectives: Unrestricted kinematic alignment total knee arthroplasty (KA-TKA) with a soft tissue respecting technique (STRT) is a soft tissue-dependent tibial resection entailing restoration of the original soft tissue tension using ligamentotaxis after resurfacing the femur, based on the concept of restoring the native or pre-osteoarthritis alignment in each patient. However, there is no consensus on the indications of unrestricted KA-TKA with STRT. We modified the STRT, followed by investigation of the effects of surgery on the postoperative hip-knee-ankle angle (HKAA). Materials and Methods: We retrospectively analyzed the clinical background data, including the preoperative and postoperative HKAA, of 87 patients who underwent unrestricted KA-TKA with the modified STRT. Univariate and multivariate analyses were performed to determine the factors affecting the postoperative HKAA. A receiver operating characteristic (ROC) curve was plot-ted to investigate the change in the cut-off values of preoperative HKAA with respect to the safe zone of the postoperative HKAA. We generated two regression models, the linear regression model and generalized additive model (GAM) using machine learning, to predict the postopera-tive HKAA. Results: Univariate and multivariate analyses revealed the preoperative HKAA as the factor most relevant to the postoperative HKAA. ROC analysis revealed that the preoperative HKAA exhibited high predictive utility, with a cut-off value of -10°, when the safe range of postoperative HKAA was set at ± 5°. The GAM was the superior machine learning model, indicating a non-linear association between the preoperative and postoperative HKAA. Patients with preoperative HKAAs ranging from -18° to 4° were more likely to fall within the ± 5° safe range of the postoperative HKAA. Conclusions: The preoperative HKAA influences the postoperative HKAA in unrestricted KA-TKA with the modified STRT. Machine learning using the GAM may contribute to the selection of patients eligible for the surgical approach.

One of the important research directions in the field of photovoltaics is integration with construction. The integration of solar cell systems with a building can reduce installation costs and help optimize the used space. One of the interesting types of cells is dye-sensitized solar cells. In addition to their interesting properties, they also have aesthetic value. In the classic arrangement, they are constructed using glass with a transparent conductive layer (TCL). This article describes replacing a classic glass counter electrode with an electrode based on a ceramic tile and nickel foil. This solution makes it possible to expand their construction applications. The advantage of this solution is full integration with construction while simultaneously generating electricity. A dye-sensitized solar cell was built layer-by-layer on ceramic tile and nickel foil. An atomization method was used to deposit fluorine-doped tin oxide, and then a screen printing method was used to deposit a platinum layer. The electrical parameters of the manufactured DSSCs with and without a counter electrode tile were characterized by measuring their current-voltage characteristics under standard AM 1.5 radiation. A dye-sensitized solar cell integrated with ceramic tiles and nickel foil was produced and displayed an efficiency of over 4%.

Abstract: The promise of regenerative medicine and tissue engineering is founded on the ability to regenerate diseased or damaged tissues and organs into functional tissues and organs or the creation of new tissues and organs altogether. In theory, all damaged and diseased tissues and organs can be regenerated or created using different configurations and combinations of extracellular matrix, cells and inductive biomolecules. Currently, regenerative medicine and tissue engineering can allow the improvement of patients’ quality of life through availing novel treatment options. Tissues and organs have a specific ECM, with specific proteins and factors released by cells residing within the local microenvironment. The coupling of regenerative medicine and tissue engineering field with 3D printing is revolutionizing the treatment of patients in a huge way. 3D bioprinting allows the proper placement of cells and ECMs, allowing the recapitulation of native microenvironments of tissues and organs. 3D bioprinting utilizes different bioinks made up of different formulations of ECM/biomaterials, biomolecules and even cells. The choice of the bioink used during 3D bioprinting is very important as properties such as printability, compatibility and physical strength influence the final construct printed. The extracellular matrix (ECM) provides both physical and mechanical microenvironment needed by cells to survive and proliferate. Decellularized ECM bioink contains biochemical cues from the original native ECM and also the right proportions of ECM proteins. Different techniques and characterization methods are used to derive bioinks from several tissues and organs and to evaluate their quality. This review discusses the uses of decellularized ECM bioinks and argues that they represent the most biomimetic bioinks available. In addition, we briefly discuss some polymer-based bioinks utilized in 3D bioprinting.

Objective. To evaluate serum neuronal and inflammatory biomarkers in asphyctic newborns treated with hypothermia alone or hypothermia plus melatonin, and whether biomarkers correlate with neurodevelopmental outcomes. Design. This is a pilot multicentre, randomised, controlled, double blind clinical trial. Neuronal glial fibrillary acidic protein (GFAP), granulocyte-macrophage colony-stimulating factor (GM-CSF), and inflammatory cytokines (interleukin (IL)-1, IL-2, IL-7 and IL-13) were measured in serum samples at hospital admission (T0), 24 hours (T1), 72 hours (T2) and 7-10 days of age (T3). Neurodevelopmental outcomes (Bayley Scales of Infant and Toddler Development-III scales, Gross Motor Function Classification System (GMFCS) and the Tardieu scale) were performed at 6 and 18 months. Setting: Level 3 neonatal intensive care unit. Patients and interventions: 25 newborns were recruited. The treated patients received a daily dose of intravenous melatonin, 5 mg per kg body weight, for 3 days. Results. After adjusting the data for severity, in the group treated with melatonin, there is a decrease in plasma levels of GM-CSF, IL-2 and IL-13 at T1 compared to placebo, as well as, at T2, in GM-CSF concentrations, as well as IL-7 and IL-13 at T3. Evolutionarily, we found a significant decrease in GM-CSF concentrations in the treatment group compared to placebo, with no differences for the rest of the biomarkers. It is noteworthy that the sustained decrease in GM-CSF and inflammatory cytokines IL-2, IL-7 and IL-13 correlated with better neurodevelopmental outcomes at 6 and 18 months. Conclusions. In neonates with hypoxic-ischemic encephalopathy, the addition of iv melatonin to hypothermia therapy affects the plasma concentration of biomarkers in the first week of life, with a high correlation with long-term neurological prognosis.

Background: Alongside their long-term effects - post-concussion syndrome (PCS) - mild traumatic brain injuries (mTBI) are significant public health concerns. Currently, there is a lack of reliable biomarkers for diagnosing and monitoring mTBI and PCS. Exosomes are small extracellular vesicles secreted by cells that have recently emerged as a potential source of biomarkers for mTBI and PCS due to their ability to cross the blood-brain barrier and reflect the pathophysiology of brain injury. This study aimed to investigate the role of salivary exosomal biomarkers in mTBI and PCS. Methods: A systematic review using the PRISMA guidelines was conducted, and studies were selected based on their relevance to the topic. Results: Studies have shown that exosomal tau, phosphorylated tau (p-tau), amyloid beta (Aβ), and microRNAs (miRNAs) are potential biomarkers for mTBI and PCS. Specifically, elevated levels of exosomal tau and p-tau have been associated with mTBI and PCS, as well as with repetitive mTBI. Dysregulated exosomal miRNAs have also been observed in individuals with mTBI and PCS. Additionally, exosomal Prion cellular protein (PRPc), coagulation factor XIII (XIIIa), synaptogyrin-3, IL-6, and aquaporins have been identified as promising biomarkers for mTBI and PCS. Conclusion: Salivary exosomal biomarkers have the potential to serve as non-invasive and easily accessible diagnostic and prognostic tools for mTBI and PCS. Further studies are needed to validate these biomarkers and to develop standardized protocols for their use in clinical settings. Salivary exosomal biomarkers can improve the diagnosis, monitoring, and treatment of mTBI and PCS, leading to improved patient outcomes.

Objectives: This study aimed to assess the impact of a predictive model for detecting extracapsular extension on pathology (pECE+) on biochemical recurrence-free survival (BCRFS) within 4 years after robotic-assisted radical prostatectomy (RARP). Methods: Retrospective data analysis from a single center between 2015 to 2022. Variables under consideration included prostate-specific antigen (PSA) levels, patient age, prostate volume, MRI semantic features and Gleason score (GS). We also assessed the influence of pECE+ and positive surgical margins on BCRFS. using the Kaplan-Meier survival function and Cox regression model were assessed. Additionally, we analyzed the MRI features on BCR (biochemical recurrence) in low/intermediate risk patients. Results: 177 participants with a follow-up exceeding 6 months post-RARP were included. The 1-year, 2-year, and 4-year risks of BCR after curative prostatectomy were 5%, 13%, and 21%, respectively. The survival analysis showed that adverse MRI features as macroscopic ECE on MRI (mECE+), capsular disruption, high tumor capsular contact length (TCCL), GS≥8, positive surgical margins (PSM), and pECE+ on pathology were risk factors for BCR. In low/intermediate-risk patients (pECE- and GS &lt;(4+4)) the presence of adverse MRI features, has been shown to increase the risk of BCR. Conclusions: The study highlights the importance of incorporating predictive MRI features for detecting extracapsular extension pre-surgery in influencing early outcomes and clinical decision-making; mECE+, TCCL, capsular disruption, and GS≥8 based on pre-surgical biopsy were independent prognostic factors for early BCR. The presence of adverse features on MRI can assist in identifying low/intermediate-risk patients who would benefit from closer monitoring.

Demonstrating biosimilarity entails comprehensive analytical evaluations, clinical pharmacolo-gy profiling, and efficacy testing for at least one medical indication in patients. These require-ments are stipulated by the U.S. Biologics Price Competition and Innovation Act (BPCIA). The costliest element—efficacy testing—can be waived if other compliance benchmarks are satisfied, including comparing functional pharmacodynamic (PD) biomarkers, even when they do not di-rectly correlate with clinical outcomes. Most biological drugs, such as monoclonal antibodies (mAbs), lack identifiable PD biomarkers. The FDA has employed various 'omics' technologies to identify potential PD biomarkers, including proteomics, glycomics, transcriptomics, genomics, epigenomics, and metabolomics. Although these efforts provide a robust scientific basis for estab-lishing biosimilarity, they are neither practical nor necessarily superior to existing functional biomarkers, such as receptor binding and mode-of-action outcomes. As we report for the first time, these functional biomarkers can effectively serve as PD indicators for all FDA-licensed bio-logical drugs. We recommend that the FDA consider officially listing these functional biomarkers to expedite and reduce the cost of biosimilar development, thereby increasing the accessibility of biological drugs. PD surrogates, like the receptor binding and pharmacokinetic profiles, are more robust and offer a rational solution to finding PD markers to compare for establishing biosimi-larity.

Single-cell RNA sequencing (scRNA-seq) technology has significantly advanced our understanding of the diversity of cells and how this diversity is implicated in diseases. Yet, translating these findings across various scRNA-seq datasets poses challenges due to technical variability and dataset-specific biases. To overcome this, we present a novel approach that employs both an LLM-based framework and explainable machine learning to facilitate generalization across single-cell datasets and identify gene signatures to capture disease-driven transcriptional changes. Our approach uses scBERT, which harnesses shared transcriptomic features among cell types to establish consistent cell-type annotations across multiple scRNA-seq datasets. Additionally, we employ a symbolic regression algorithm to pinpoint highly relevant yet minimally redundant models and features for inferring a cell type’s disease state based on its transcriptomic profile. We ascertain the versatility of these cell-specific gene signatures across datasets, showcasing their resilience as molecular markers to pinpoint and characterize disease-associated cell types. Validation is carried out using four publicly available scRNA-seq datasets from both healthy individuals and those suffering from ulcerative colitis (UC). This demonstrates our approach’s efficacy in bridging disparities specific to different datasets, fostering comparative analyses. Notably, the simplicity and symbolic nature of the retrieved gene signatures facilitate their interpretability, allowing us to elucidate underlying molecular disease mechanisms using these models.

Background and Objective: Although whole body-electromyostimulation (WB-EMS) has been shown to favorably improve body composition in several research studies, it has not been confirmed how it affects adipose tissue-derived biomarkers and circumferences of the abdomen and thighs. Materials and Methods: Twenty participants of obese elderly women were randomly classified into an EMS group (EMSG; n = 10) or a non-EMS group (CON; n = 10). The WB-EMS suits used in this study enabled the simultaneous activation of 8 muscle groups with selectable intensities for each phase. Stimulation frequency was selected at 85 Hz, impulse-width at 350 μ seconds, and impulse-rise as a rectangular application. Impulse duration was 6 seconds with a 4-second break between impulses. The EMS sessions were combined with aerobic dancing 3 times a week for 12 weeks. Both groups received the same program; however, the CON did not receive electrical stimuli. Biomarkers and body composition including circumferences of the abdomen and thighs were measured on Week 0 and Week 12. Results: Compared with the CON, 1) a significant effect of the EMS-intervention concerning decreased body weight (p = 0.032) and increased basal metabolic rate (p = 0.029) were evident. The thigh subcutaneous fat and total fat of EMSG were not significantly changed, but those of CON were significantly increased after 12 weeks. 2) The biomarkers of CON either increased or showed no change, although the interleukin (IL)-6 was significantly (p = 0.028) decreased in EMSG. Specifically, C-reactive protein (CRP; p = 0.005) and alpha-fetoprotein (p = 0.050) of CON were significantly increased after 12 weeks. In addition, the IL-6 (p = 0.034), CRP (p = 0.001), carcinoembryonic antigen (p = 0.017), and low density lipoprotein (p = 0.005) of EMSG were lower than those of CON in the end of experiment. 3) Conclusions: The results indicate that EMS intervention improved body composition and reduced negative biomarkers, thus highlighting its effectiveness.

Wearable devices have become ubiquitous, collecting rich temporal data that offers valuable insights into human activities, health monitoring, and behavior analysis. Leveraging this data, researchers have developed innovative approaches to classify and predict time-based patterns and events in human life. Time-based techniques allow the capture of intricate temporal dependencies, which is the nature of the data coming from wearable devices. This paper focuses on predicting well-being factors, such as stress, anxiety, positive and negative affect, on the Tesserae dataset collected from office workers. We examine the performance of different methodologies, including deep learning architectures, LSTM, ensemble techniques, Random Forest (RF) and XGBoost and compare their performances for time-based and non-time-based versions. In time-based versions, we investigate the effect of previous records of well-being factors on the upcoming ones. The overall results show that time-based LSTM performs the best among conventional (non-time-based) RF, XGBoost, and LSTM. The performance even increases when we consider a more extended previous period, in this case, 3 past-days rather than 1 past-day to predict the next day. Furthermore, we explore the corresponding biomarkers for each well-being factor using feature ranking. The obtained rankings are compatible with the psychological literature. In this work, we validated them based on device measurements rather than subjective survey responses.

Background: In this study, we aimed to evaluate the effect of s-FLT-1 and PlGF concentrations in women in the first trimester of pregnancy on the pulsatility index of the ductus venosus and the right and left uterine arteries. Methods: A total of 108 pregnant women in their first trimester were included in the study, with 87 assigned to the experimental group and 21 to the control group. Ultrasound examination were performed to measure the uterine artery pulsatility index, resistance index, ductus venosus pulsatility index, and blood sampling levels of biomarkers such as b-HCG; PAPP-A; s-FLT-1 and PlGF. Results: There was a significant negative relationship between PAPP-A concentration and the risk of fetal growth restriction, and a significant negative relationship between PlGF concentration and the risk of preeclampsia and fetal growth restriction in women in their first trimester of pregnancy. There was also a significant positive relationship between sFLT-1/PLGF ratio and the risk of developing preeclampsia. No significant relationships were found between the concentrations of biomarkers beta-HCG, PAPP-A, sFLT-1, PlGF, and any of the parameters PIUARt, PIUALt, Mean uterine arteries, and DVPI. Summary: In conclusion, this study did not find conclusive evidence to support the hypothesis that beta-HCG, PAPP-A, s-FLT-1, and PlGF concentrations in women in the first trimester of pregnancy have a significant effect on the Pulsatility Index of the ductus venosus and the Right and left Uterine Arteries. Further research is needed to investigate these potential associations.

Plants produce specific structures constituting a barrier hindering penetration of pathogens, while they also produce substances inhibiting pathogen growth . These compounds are secondary metabolites, such as phenolics, terpenoids, sesquiterpenoids, resins, tannins and alkaloids. Bioactive compounds are secendary metabolities from trees and shrubs are used in medicine, herbal medicine and cosmetology. To date fruits and flowers of exotic trees and shrubs have been primarily used as sources of bioactive compounds. In turn, search for new sources of bioactive compounds is currently focused on native plant species due to its availability. Application of such raw material needs to be based on knowledge of their chemical composition, particularly health-promoting or therapeutic compounds. Research conducted to date on European trees and shrubs has been scarce. This paper presents results of literature studies conducted to systematise knowledge on bioactive compounds found in trees and shrubs native to central Europe. The aim of this review providing available information on the subject is to indicate gaps in the present knowledge.

Abstract: The aim of this study is to emphasize on the clinical uses of amniotic membrane (AM) in multiple ocular disorders. AM possesses many properties including promotion of epithelialization, anti-fibrotic, anti-apoptotic, anti-angiogenic properties. Epithelial wound healing on the eye surface is promoted due to several epidermal and keratocyte growth factors as well as by its anti-inflammatory and anti-scarring effects due to interleukin-10, interleukin-1 receptor antagonists and inhibition of transforming growth factor- beta (TGF-β) signal transduction by AM in the corneal and conjunctival fibroblasts respectively. It plays a crucial role by functioning as a substitute of basement membrane (BM) and as a temporary graft material. It is not only being used as an eye graft but also its extract can be used as an eye drop for corneal and external eye diseases. So its proper preparation, preservation and clinical application can bring a revolutionary change in the treatment of different ocular disorders.

Abstract Antibacterial activities can be improved using mixed ligands. Mixed ligands involved in this research are sodium sulfadiazine (Na-sfz) and dithiocarbamate (ai-dtc). One-pot synthesis was used to synthesize ligand of aniline dithiocarbamate (ai-dtc) and the corresponding coordination compounds of [VO(sfz)(ai-dtc)] and [Zn(sfz)(ai-dtc)]. Crystals of ai-dtc, which grew from the solution when refrigerated after five days, were diffracted with technique of single crystal x-ray crystallography to reveal the structure. Other characterization techniques involving physicochemical parameters, FT-IR, UV-Vis and NMR (1H NMR and 13C NMR) were carried out on ligands of ai-dtc, sfz and corresponding coordination compounds. Differences in results of FT-IR, UV-Vis and NMR between ligands and their respective metal ions confirmed the coordination. The in vitro antibacterial studies showed that the ligands (not the metal complexes) had modest activity against Gram negative bacteria: Staphylococcus aureus, whereas, the coordination compounds had modest activities against the Gram negative bacteria: Escherichia coli and Pseudomonas aeruginosa.

Neurodegenerative diseases that include Alzheimer's disease (AD), amyotrophic lateral sclerosis (ALS), Parkinson's disease (PD), Huntington's disease (HD), and multiple sclerosis (MS), arise due to numerous causes like protein accumulation and autoimmunity, characterized by neurologic depletion which lead to incapacity in normal physiological function such as thinking and movement in these patients. Glial cells perform a critical role in protective neuronal function; in the case of neuroinflammation, glial cell dysfunction can promote the development of neurodegenerative diseases. MiRNA participates in gene regulation and plays a vital role in many biological processes in the body; in the central nervous system (CNS), it can play an essential part in neural maturation and differentiation. In neurodegenerative diseases, miRNA dysregulation occurs, enhancing the development of these diseases. In this review, we discuss neurodegenerative diseases (Alzheimer's disease (AD), Parkinson's disease (PD), amyotrophic lateral sclerosis (ALS), and multiple sclerosis (MS)) and how miRNA is preserved as a diagnostic biomarker or therapeutic agent in these disorders. Finally, we highlighted miRNA as therapy.

Lung cancer is one of the leading causes of cancer-related mortality globally. Pulmonary nodules are one of the risk factors and their discovery rate has been increasing. Based on the nodule size and growth rate, their malignancy propensity is determined; however, it is very challenging to distinguish between benign and cancerous nodules. Many tumour-associated antigens (TAA) have been studied as blood biomarkers for lung cancer, most commonly the Cytokeratin 19 fragment (CYFRA 21-1), squamous cell carcinoma antigen (SCC Ag), carbohydrate antigen (CA19-9) and carcinoembryonic antigen (CEA). Due to their low sensitivity, TAAs are not recommended as tools for the early detection of lung cancer. However, cancer testis antigens (CTAs) are highly specific for carcinomas but their expression is more commonly associated with advanced stages of cancer and poor prognosis. Despite the fact that TAAs may provide useful insights for the diagnosis and prognosis of early lung cancer, their potential to do so has yet to be demonstrated.

Background: Early diagnosis of acute brain injury (ABI) is critical for patients on venoarterial extracorporeal membrane oxygenation (VA-ECMO) to guide anticoagulation strategy; however, neurological assessment in ECMO is often limited by patient sedation. Methods: In this pilot study of adults from June 2018 to May 2019, plasma samples of glial fibrillary acidic protein (GFAP), neurofilament light chain (NFL), and Tau were collected daily after VA-ECMO cannulation and measured using a multiplex platform. Primary outcomes were the occurrence of ABI, assessed clinically, and neurologic outcome, assessed by modified Rankin Scale (mRS). Results: Of 20 consented patients (median age=48.5 years; 55% female), 8 (40%) had ABI and 15 (75%) had unfavorable neurologic outcomes at discharge. 10 (50%) patients were centrally cannulated. The median duration on ECMO was 4.5 days (IQR: 2.5-9.5). Peak GFAP, NFL, and Tau levels were higher in patients with ABI vs. without (AUC = 0.77; 0.85; 0.57, respectively) and in patients with unfavorable vs. favorable neurologic outcomes (AUC = 0.64; 0.59; 0.73, respectively). GFAP elevated first, NFL elevated to the highest degree, and Tau showed limited change regardless of ABI. Conclusion: Plasma biomarkers may facilitate early detection of ABIs in VA-ECMO where neurological exam is limited and assist timely clinical decision-making.

We investigated the diagnostic capacity of selected circulating biomarkers (CBMs) for the early detection of bone metastasis (BMets) in patients with pancreatic neuroendocrine neoplasms (PanNENs). 115 patients with PanNENs and 40 controls were enrolled. We measured the serum levels of ferritin, cytokeratin 18 (CY18), CA19-9, CA125, AFP, CEA, and beta-2 microglobulin (B2M). 8 PanNENs patients developed BMets, and 107 remained BMets-free. We observed a significantly higher level of CA125 and CY18 in BM-PanNENs patients vs. non-BM-PanNENs patients (p = 0.01 and p = 0.04, respectively). CA125, CY18, and B2M area under receiver operator characteristic (AUROC) analyses differentiated BM-PanNENs from non-BM-PanNENs patients; CA125 area under the curve (AUC) 0.77, p < 0.01; CY18 AUC data were 0.72, p = 0.03, and B2M AUC 0.67, p = 0.02. Based on CBMs metrics in both subgroups, we reached a sensitivity/specificity for CA125 of 75/76%; for CY18 of 75/69%, for B2M of 100/50%, for CA125 and CY18 combination 93/90%, respectively. The useful CBMs for BM-PanNENs patients detection were CA125, CY18, and B2M. They seem to have the diagnostic capacity as a fair single biomarker and CA125&CY18 combination panel for the detection of BMets.

Transfer RNA fragments (tRFs) have gene silencing effects similarly to miRNAs, can be sorted into extracellular vesicles (EVs) and are emerging as potential circulating biomarkers for cancer diagnosis. We aimed at analyzing the expression of tRFs in gastric cancer (GC) and understanding their potential as biomarkers. We explored miRNA datasets from gastric tumors and normal adjacent tissues (NAT) from TCGA repository, and proprietary 3D-cultured GC cell lines and corresponding EVs, in order to identify differentially represented tRFs using MINTmap and R/Bioconductor packages. Selected tRFs were validated in patient-derived EVs. We found 613 Differentially Expressed (DE)-tRFs in the TCGA dataset, of which 19 were concomitantly upregulated in TCGA gastric tumors and present in 3D-cells and EVs, but barely expressed in NAT. Moreover, 20 tRFs were expressed in 3D-cells and EVs and downregulated in TCGA gastric tumors. Of these 39 DE-tRFs, 9 tRFs were also detected in patient-derived EVs. Interestingly, the targets of these 9 tRFs affect neutrophil activation and degranulation, cadherin binding, focal adhesion and cell-substrate junction, highlighting these pathways as major targets of EV-mediated crosstalk with the tumor microenvironment. Furthermore, as they are present in four distinct GC datasets and can be detected even in low quality patient-EV derived samples, they hold promise as GC biomarkers. By repurposing already available NGS data, we could identify and cross-validate a set of tRFs holding potential as GC diagnosis biomarkers.

Suicide is defined as the action of harming oneself with the intention of dying. It is estimated that worldwide one suicide occurs every 40 seconds, making it a major health problem. Studies in families have suggested that suicide has a genetic component, around the world studies have been carried out in search of genetic variants associated with suicidal behavior, these variants could be useful as potential biomarkers to identify people at risk of suicide. In this area in Mexico, some studies of variants in genes related to neurotransmission and other important pathways have been carried out and a possible association of variants located in genes has been suggested: SLC6A4, SAT-1, TPH-2, ANKK1, GSHR, SCARA50, RGS10, STK33, COMT, and FKBP5. This systematic review shows the genetic studies on the Mexican population. This article contributes by compiling the existing information on genetic variants and genes associated with suicidal behavior, said variants in the future could be used as potential biomarkers to identify people at risk of suicide.

Soybean is a highly nutritious legume grown globally as a food and feed crop. An examination of a collection of 10 cultivated and 6 wild Korean soybean varieties showed that there is phenotypic variability notable in different soybeans. Therefore, to develop a list of biomarker candidates useful for growing soybeans of better quality and quantity, the genes of 16 Korean soybean varieties were compared with those of the reference Glycine max var. Williams 82. The comparison was made through gene sequencing to facilitate selection of nsSNPs. The objective of the study was to find out the structural and functional variations caused by nsSNPs and discuss whether the collection of Korean soybean varieties qualifies as biomarkers based on their phenotypic traits. Analysis of the data collected was done using four software: SIFT, Polyphen, PANTHER, and I-mutant 2.0, which are designed to detect the rate of functional and structural variations caused by the nsSNPs in cultivated and wild soybean varieties. Genotypic information obtained in the analysis was used to develop a core collection of biomarkers based on whether nsSNP content was found in more than half of the 16 samples. Therefore, the list of biomarker candidates developed from this study showed that Korean soybean could provide valuable information needed in both future crop genetic research and identification of biomarkers.

The musculoskeletal system consisting of bones and muscles have been recognized as endocrine organs secreting hormones that are involved in regulating metabolic and inflammatory pathways. Obesity and type 2 diabetes (T2D) are associated with several musculoskeletal system complications. We hypothesized that an interaction exists between adipomyokines namely, irisin and METRNL, and various bone markers in individuals with obesity and T2D. A total of 228 individuals were enrolled in this study, including 124 non-diabetic and 104 T2D. A Multiplex assay was used to assess the level of various bone markers namely Osteoactivin, Syndecan, osteoprotegerin (OPG) and osteonectin/SPARC. Our data shows elevated levels of Osteoactivin, Syndecan, OPG and SPARC in T2D as compared to non-T2D individuals (p ≤ 0.05). Using Spearman’s correlation, irisin was positively correlated only with Osteoactivin and OPG (p &lt; 0.05). Similarly, a positive association was observed between METRNL and Osteoactivin (p &lt; 0.05). The strong positive association shown in our study between irisin, METRNL and various bone markers emphasises the strong interaction between these organs. This suggests that a dysregulation in the functional interaction between these molecules could play a possible role in the development of bone and muscle related complications that are associated with obesity and T2D.

ABSTRACT: Recurrent glioblastoma (rGBM) is a highly aggressive form of brain cancer that poses a significant challenge for treatment in neurooncology, and the survival status of patients after relapse usually means rapid deterioration, and also the leading cause of death among patients. In recent years, immunotherapy has emerged as a promising strategy for the treatment of recurrent glioblastoma by stimulate the body's immune system to recognize and attack cancer cells , which could be used as a in combination with other treatments such as surgery, radiation, and chemotherapy to improve outcomes for patients with recurrent glioblastoma, This therapy combines several key methods such as the use of monoclonal antibodies, chimeric antigen receptor T cell (CAR-T) therapy, checkpoint inhibitors, oncolytic viral therapy cancer vaccines, and combination strategies. In this review, we mainly document the latest immunotherapies for the treatment of glioblastoma and focus on the rGBM especially.

The present short communication aimed to determine the effects of vegetable cultivation on health. We conducted a qualitative study using responses to an open-ended question that was part of a survey on regional differences on vegetable intake. Participants in this study were residents of Gunma Prefecture, Japan, and were aged between 20–74 years. In the questionnaire, we asked: “Aside from increasing vegetable intake, how does vegetable cultivation affect your health?” We were able to categorize the answers into six subcategories related to physical health, mental health, and social well-being.

A B S T R A C T Genital herpes disease is caused mainly by herpes simplex virus type 2 (HSV-2), which is sexually transmitted with a high prevalence in both developed and developing countries. No vaccine is currently available against genital herpes. In this study, we introduced and expressed two genes encoding HSV-2 glycoprotein D (gD) and VP16 protein and a GFP marker gene (control) in tobacco seedlings. Positive plant infection was assessed through characteristic tobacco mosaic virus disease symptoms on leaves and by monitoring the fluorescence emitted by the expressed GFP protein. Expression of the HSV-gD2 and VP16 antigens was verified by RT-PCR, ELISA and Western blot. As a proof of concept, the immunogenicity and the protection ability of the plant produced gD antigen was tested in a mouse model of genital herpes and compared to gD antigen produced in a mammalian expression system. This showed that the plant-gD preparation, when used in combination with a CpG oligodeoxynucleotide as adjuvant, was highly immunogenic and capable of inducing complete immunity to lethal vaginal HSV-2 challenge in mice. Thus, the data presented here may have implications for the development of a production system for highly immunogenic plant-based HSV-2 vaccine antigens.

Long COVID (LC) encompasses a constellation of long-term symptoms experienced by at least 10% of people after the initial SARS-CoV-2 infection, and so far has affected about 65 million people. The etiology of LC remains unclear; however, many pathophysiological pathways may be involved, including viral persistence; chronic, low grade inflammatory response; immune dysregulation and defective immune response; reactivation of latent viruses; autoimmunity; persistent endothelial dysfunction and coagulopathy; gut dysbiosis; hormonal dysregulation, mitochondrial dysfunction; and autonomic nervous system dysfunction. There are no specific tests for the diagnosis of LC, and clinical features including laboratory findings and biomarkers may not specifically relate to LC. Therefore, it is of paramount importance to develop and validate biomarkers that can be employed for the prediction, diagnosis and prognosis of LC and its therapeutic response. Promising candidate biomarkers that are found in some patients are markers of systemic inflammation including acute phase proteins, cytokines and chemokines; biomarkers reflecting SARS-CoV-2 persistence, reactivation of herpesviruses and immune dysregulation; biomarkers of endotheliopathy, coagulation and fibrinolysis; microbiota alterations; diverse proteins and metabolites; hormonal and metabolic biomarkers; as well as cerebrospinal fluid biomarkers. At present, there are only two reviews summarizing relevant biomarkers; however, they do not cover the entire umbrella of current biomarkers or their link to etiopathogenetic mechanisms, and the diagnostic work-up in a comprehensive manner. Herein, we aim to appraise and synopsize the available evidence on the typical laboratory manifestations and candidate biomarkers of LC, their classification based on main LC symptomatology in the frame of the epidemiological and pathogenetic aspects of the syndrome, and furthermore assess limitations and challenges as well as potential implications in candidate therapeutic interventions.

The present study was aimed to evaluate the levels of oxidative stress markers in breast diseases by measuring the 8-hydoxy-2-deoxyguanosine (8-OHdG), vitamin A, vitamin C, vitamin E and total antioxidant status (TAS) alterations in relation to cell proliferation activity and disease progression. Significant increases in the level of oxidative damage marker 8-OHdG and cell proliferation activity were observed in breast carcinoma patients in comparison to benign and normal controls, which were accompanied by significant decrease in non enzymatic antioxidants and TAS concentrations. 8-OHdG and cell proliferation level were negatively correlated with non enzymatic antioxidants viz., Vitamin A, Vitamin C, vitamin E level and total antioxidant activity. Altered levels of biomarkers of oxidative stress and cell proliferation activity amongst the malignant, benign and controls suggest a correlation of increased oxidative stress and cell proliferation activity in the progression of disease in breast carcinoma patients. Among the oxidative stress markers and cell proliferation index, decreased level of vitamin A, vitamin C, vitamin E, TAS and increased level of 8-OHdG, cell proliferation index emerged as best predicted biomarkers for subjects with malignancy and benign breast disease.

Pancreatic cancer (PC) is the most lethal type of cancer, it has the lowest 5-year survival rate among all other types of cancers. More than half of PC cases are diagnosed at an advanced stage due to PC’s insidious and non-specific symptoms. Surgery remains the most efficacious treatment option currently available, but only 10-20% of PC cases are resectable upon diagnosis. As of now, the sole biomarker approved by the United States Food and Drug Administration (US-FDA) for PC is carbohydrate antigen 19-9 (CA19-9); however, its use is limited use for early diagnosis. An in-creasing number of studies have investigated a combination of biomarkers. Lately, there has been considerable interest in the application of a liquid biopsy, including the utilization of microRNAs (miRNAs), circulating tumor DNA (ctDNA), and circulating tumor cells (CTCs). Screening for PC is indicated for high-risk patients; studies on new diagnostic models combined with biomarkers for early detection have also shown promising results for the ability of these models and biomarkers to aid clinicians in deciding on whether to start screening. This review seeks to provide a concise overview of the advancements in existing biomarkers and explore novel strategies for the early detection of PC.

Ischemic heart disease is the leading cause of mortality worldwide. There is evidence of the participation of Aβ in thrombosis and clinical manifestations of acute coronary syndromes. In this study, we investigated the correlation of Aβ peptides with myocardial injury and inflammation biomarkers in acute coronary syndrome. This is a single-center, cross-sectional, observational, and correlation study that included 65 patients within the first 12 hours after symptom onset (chest pain, shoulder pain, or chest discomfort) with ST-elevation and non-ST elevation myocardial infarction who were admitted in the Coronary Care Unit, biochemical parameters of Aβ peptides levels were evaluated. Our results show that NSTEMI patients had a higher prevalence of hypertension, diabetes, smoking, and prior myocardial infarction when compared to STEMI patients. We observed a higher level of Aβ-42 in NSTEMI, but no difference in Aβ-40 levels. We also found a correlation between age and NT-proBNP with both Aβ peptides (Aβ-40, Aβ-42) in both groups. In this analysis, NSTEMI patients had higher prevalence of cardiovascular risk factors. Considering the toxic properties of Aβ-42 in coronary endothelial cells and cardiomyocytes, this peptide may be useful in risk stratification scores in patients with NSTEMI.

(1) Background: Neonatal early-onset sepsis (EOS) is associated with important mortality and morbidity. The aims of this study were to evaluate the association between serum biomarkers with early onset neonatal sepsis in a cohort of patients with prolonged rupture of membranes (PROM), and to calculate their diagnostic accuracy. (2) Methods: A retrospective cohort study was conducted on 1355 newborns with PROM admitted between January 2017 and March 2020, who were divided in two groups: group A, with PROM ≥ 18 hours and group B, with PROM < 18 hours. Both groups were further split into subgroups: proven sepsis, probable sepsis and no sepsis. Descriptive statistics, ANOVA analysis, and a Random Effects Generalized Least Squares (GLS) regression were used to evaluate the data. (3) Results: The statistically significant predictors of neonatal sepsis were the high white blood cells count from the first (p = 0.005) and third day (p = 0.028), and high CRP values from the first day (p = 0.004). Procalcitonin (area under the curve - AUC = 0.78) and CRP (AUC = 0.76) measured on the first day had the best predictive performance for early onset neonatal sepsis. (4) Conclusions: Further studies are needed to explore other bi-omarkers of sepsis in both pregnant women and newborns to better predict EOS.

Objective: Obstructive sleep apnea syndrome (OSAS) is a common sleep disorder that is caused by the reduction or cessation of airflow in the upper airway. Irisin, retinol-binding protein-4 (RBP-4), and adiponectin are the three significant factors in the metabolic process of the human body. The objective of this study was to investigate whether plasma irisin, RBP-4, and adiponectin levels are associated with the severity of OSAS. Methods: According to inclusion and exclusion criteria, 125 patients with OSAS and 46 healthy, gender matched controls were included to the study. The patients were classified according to the apnea hypopnea index (AHI) as 14 mild cases (5<AHI<15), 23 moderate OSAS cases (15<AHI<30) and 88 severe OSAS cases (AHI>30). The plasma irisin, RBP-4 and adiponectin levels were measured and compared between groups. Results: RBP-4 levels were higher in severe OSAS compared to moderate (p<0.05) and mild (p<0.001) OSAS groups, irisin levels were significantly lower compared to moderate (p<0.05) and mild (p<0.001) OSAS groups. There was a negative correlation between irisin and RBP-4 (r=-0.379; p<0.001) and AHI (r=-0.834; p<0.001) and a positive correlation with minimum oxygen saturation (MOS) (r=0.341; p<0.001) in the patient group. In the patient group, there was a negative correlation between adiponectin and BMI (r=-0.682; p<0.001), RBP-4 (r=-0.292; p<0.01) and AHI (r=-0.179; p<0.05) and a positive correlation with MOS (r=0.397; p<0.001). In the patient group, there was a positive correlation between RBP-4 and BMI (r=0.406; p<0.001) and AHI (r=0.473; p<0.001) and a negative correlation with MOS (r=-0.805; p<0.001). As a predictor of OSAS, adiponectin showed the highest specificity (84.8%) and RBP-4 the highest sensitivity (92.0%). Conclusion: The results of the present study demonstrated that the severity of OSAS causes more metabolic problems, including decreased plasma irisin and adiponectin levels and an increased plasma RBP-4 level. As a result, patients with an AHI score greater than thirty should be closely monitored for metabolic and cardiovascular abnormalities.

Cellular senescence is characterized by permanent proliferation and migration arrest, senescence-associated secretory phenotype (SASP), and oxidative stress. Senescent vascular smooth muscle cells (VSMCs) contribute to cardiovascular diseases and atherosclerotic plaque instability. To establish and characterize a model of replicative senescence (RS), human aortic VSMCs were serially passaged to represent different stages of RS such as young proliferating cells and old/senescent non-proliferating cells. More than 50% of old cells stained positive for the senescence-associated β-galactosidase compared to 20% of young cells. Old cells have a slower proliferation rate, a migratory activity reduced by 50%, but increased levels of TP53 and of cell cycle inhibitors p21/p16 expression, and accumulate in the G1 phase. Old cells showed a flattened appearance and enlarged and regular nuclei, and downregulation of the expression of LMNB1 and HMGB1. Old cells showed also an increased expression of SASP molecules (IL1β, IL6, IL8, and MMP3). Moreover, among a set of 12 manually selected long non-coding RNAs (lncRNAs), we detected significant upregulation of PURPL and NEAT1. We observed also increased levels of RRAD mRNA. The detection of novel molecular markers of senescence, such as RRAD, PURPL, and NEAT1, could be helpful for future studies on potential anti-aging factors.

Objective: A study was made of the salivary levels of adenosine deaminase (ADA), ferritin (FRR) and total proteins in healthy individuals and in patients with oral potentially malignant disorders (OPMD), assessing the potential role of saliva as a diagnostic tool. Methods: A total of 91 subjects participated in the study, divided into two groups: 59 patients with OPMD (oral leukoplakia or oral lichen planus )and 32 healthy controls with measurements being made of salivary ADA, ferritin (FRR) and total proteins (TP). Results: There were no significant differences in salivary ADA between the OPMD group and the controls (p=0.934), though the levels of both FRR and TP were significantly higher in the OPMD group (p=0.001). Patients with oral lichen planus showed significant differences in terms of FRR (p=0.009) and TP (p=0.003). Conclusions: The promising findings of this study suggest a potential role for FRR and TP in the salivary diagnosis of OPMD. In addition, saliva appears to be a reliable tool offering an interesting alternative for the screening of large populations.

Recent reports suggest that dysregulation of lipid metabolism is a key feature of the most invasive cancers. To identify potential biomarkers of tumor aggressiveness, we compared the proteomes of two experimental models of malignant mesothelioma in rats exhibiting different invasive properties. Quantitative changes between the most invasive, M5-T1, versus the least invasive, F4-T2, first led to a list of 424 proteins. A second step, cross-comparing this list with 433 proteins distinguishing invasive vs non-invasive tumors, led to identifying 88 proteins that specifically increased and 157 that decreased, respectively, characterizing the most aggressive M5-T1 tumor. Among the 15 mitochondrial proteins found in these lists, the very long-chain specific acyl-CoA dehydrogenase, encoded by the Acadvl gene and involved in fatty acid beta oxidation, appeared to play an important role in the metabolic reprogramming of the tumor microenvironment. Immunohistochemical staining of tumor sections confirmed increased expression of Acadvl in the M5-T1 tumor. Finally, the dramatic increase and decrease, observed in 25 and 17 proteins, respectively, suggested the existence of a strong link between mitochondrial events and modifications of the extracellular matrix, immune cell components or other subcellular compartments. These findings highlight some important aspects of the tumor microenvironment changes linked to aggressiveness.

Ascending aorta aneurysm (AsAA) is a complex disease, currently defined an inflammatory disease. In the sporadic form, AsAA has, indeed, a complex physiopathology with a strong inflammatory basis, significantly modulated by genetic variants in innate/inflammatory genes, acting as independent risk factors and as largely evidenced in our recent studies performed during the last 10 years. Based on these premises, here, we want to revise the impact of reactive oxygen species (ROS) and oxidative stress on AsAA pathophysiology and consequently on the onset and progression of sporadic AsAA. This might consent to add other important pieces in the intricate puzzle of the pathophysiology of this disease with the translational aim to identify biomarkers and targets to apply in the complex management of AsAA, by facilitating the AsAA diagnosis currently based only on imaging evaluations, and the treatment exclusively founded on surgery approaches.

Vitamin D plays an important role in maintaining healthy mineralized skeleton. It is also consid-ered an immunomodulatory agent that regulate the innate and adaptive immune systems. Multi-ple observational studies have demonstrated the association between low level of serum 25-hydroxyvitamin D [25(OH)D] and presence and severity of several rheumatic diseases, such as rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), spondyloarthropathies and oste-oarthritis (OA). Nevertheless, the specific benefits of vitamin D supplement for treatment and prevention of rheumatic diseases are less accepted as the results from randomized clinical trials are inconsistent, although some conceivable benefits of vitamin D for improvement of disease ac-tivity of RA, SLE and OA have been demonstrated in meta-analyses. It is also possible that some individuals might benefit from vitamin D differently from others since inter-individual difference in responsiveness to vitamin D supplementation has been observed in genomic studies. Although the optimal level of serum 25(OH)D is still debatable, it is advisable it is advisable that patients with rheumatic diseases should maintain serum 25(OH)D level at least 30 ng/mL (75 nmol/L) to prevent osteomalacia, secondary osteoporosis and fracture, and possibly 40 – 60 ng/mL (100 – 150 nmol/L) to achieve maximal benefit from vitamin D for immune health and overall health.

In May of 2022, millions of U.S. parents faced uncertainty in safely feeding their infants due to the infant formula shortage. Methods: An anonymous, electronic, cross-sectional, retrospective survey was used. Results: U.S. parents (n =187) whose infants were 10.2 weeks old during the short-age completed the survey. Eighty-one percent of parents switched formulas during the shortage, 87% switched because they could not find the formula they typically used, 34% switched 3-5 times, 29% of parents visited ≥ 4 stores/24 hours and 26% of parents traveled >20 miles/24 hours to purchase formula. Use of infant formula increased (p< 0.01); in infants requiring specialty for-mula, use of intact cow’s milk formula increased (p < 0.05) and use of premature infant formulas decreased (p < 0.05). Infants relying on specialty formulas experienced at least one undesirable outcome compared with non-specialty users. Parents used social media, relatives/friends, and healthcare providers for support during the shortage, but their helpfulness scores were suboptimal. Parents reported needs for greater infant formula availability, free prenatal lactation education and postpartum lactation support. Conclusions: Government, regulatory and healthcare policy oversight are needed to protect the infant feeding system, including more commercially available products, access to banked donor milk and lactation support.

Objectives: 1) to demonstrate the anti-inflammatory and anabolic effect of Ozone by determining in serum samples the biochemical levels of IL-6 and IGF-1 in knee osteoarthritis (OA) patients in a real world in Rehabilitation Setting; 2) to evaluate clinical effectiveness by Visual Analog Scale (VAS) and WOMAC scale, and biochemical effect by C-reactive protein (CRP), uric acid and erythrocyte sedimentation rate (ESR). Material and methods: 65 patients with knee OA Kellgren Lawrence (KL) grade 2 or more were analyzed in a retrospective observational study. The study run from January 2018 to September 2021. Inclusion criteria: a) patients 18 years or older; b) with knee OA KL 2º or more; c) biochemical analysis before-and-after treatment; d) pain more than 3 on VAS. Exclusion Criteria: a) previous knee surgery; b) favism; c) pregnancy; d) any other disease that originates lack of collaboration for infiltration. Primary Outcome variables: a) IL-6; b) IGF-1 in diabetes mellitus (DM)/obese and non-DM/non-obese patients; both before-and-after Ozone treatment. Secondary Outcome variables: a) CRP, b) ESR, c) uric acid, d) VAS pain, e) WOMAC pain, function and stiffness. Ozone protocol consisted of 4 sessions (once a week) of an intra-articular infiltration of 20 mL (20µg/mL concentration) of a gas mixture of Oxygen-Ozone 95-5% (produced by Ozone generator Ozonosan-α Plus ®). For biochemical evaluation, SNIBE MAGLUMI ™ IL-6 (CLIA) and SNIBE MAGLUMI ™ IGF-1 (CLIA) kits were used. CRP and uric acid were analyzed by Abbott Alinity c kit; and ESR was evaluated by DIESSE VES MATIC CUBE 30. Results: There is a linear correlation between age and OA severity. IL-6 decreased both in DM and non-DM patients and in all OA KL grades (from 2.7 to 1.59 pg/mL). IGF-1 decreased in total group (OA + DM + obesity) from 112.09 to 107.19 ng/mL. When only knee OA patients were analyzed, Ozone improved IGF-1 levels (from 100.17 to 102.03 ng/mL). Ozone decreased CRP, ESR, uric acid, and improved VAS pain, WOMAC pain, function and stiffness (p<0.05). Conclusions: Ozone is a valid option for the management of knee osteoarthritis in real world Rehabilitation Setting, because of its anti-inflammatory, metabolic and anabolic properties. Ozone downregulates pro-inflammatory IL-6 cytokine. Ozone has a metabolic/hypoglycemic effect on obese/diabetic knee osteoarthritis patients by reducing IGF-1. Ozone has an anabolic effect on non-diabetic/non-obese patients by improving IGF-1. Ozone reduces other biomarkers of inflammation (CRP, ESR and uric acid) and improves, pain, function and quality of life.

The concept and policies of multiple early cancer detection (MCED) have gained significant attention from governments worldwide in recent years. In the era of burgeoning artificial intelligence (AI) technology, the integration of MCED with AI has become a prevailing trend, giving rise to a plethora of MCED AI products. However, due to the heterogeneity of both the detection targets and the AI technologies, the overall diversity of MCED AI products remains considerable. The types of detection targets encompass protein biomarkers, cell-free DNA, or combinations of these biomarkers. In the development of AI models, different model training approaches are employed, including datasets of case-control researches or real-world cancer screening datasets. Various validation techniques, such as cross-validation, location-wise validation, and time-wise validation are used. All of the factors show significant impacts on the predictive efficacy of MCED AIs. After the completion of AI model development, deploying the MCED AIs in clinical practice presents numerous challenges, including presenting the predictive reports, identifying the potential locations and types of tumor, and addressing cancer-related information such as clinical follow-up and treatment. This study reviews several mature MCED AI products currently available in the market, detecting their composing factors from serum biomarkers detection, MCED AIs training/validation, and the clinical application. The review illuminates the challenges encountered by existing MCED AI products across these stages, offering insights into the continued development and obstacles within the field of MCED AI.

The study explored the correlation between serum biomarkers and hepatocellular carcinoma detection in various fishing groups, utilizing a descriptive and experimental approach in Bangladesh. The study identified fishers often consume tobacco, polluted drinking water, and lack sufficient sunlight, all of which are extremely detrimental to their health. Fishermen who mostly fish at night and spend little time on the water during the daytime hours do not get enough sunlight, nor do they get enough vitamin D. An increased risk of liver cancer was found to be directly and strongly correlated with insufficient serum levels of vitamin D. In addition, a negligent lifestyle, a lack of awareness about hepatitis, and inadequate nutritional assistance have significantly increased their risk. Our results contribute to the information on HCC assessment and evaluation by clarifying the relevance of serum vitamin D, alpha-fetoprotein (AFP), creatinine (Cr), and hemoglobin A1C (HbA1c) in distinguishing between categories and sexes. According to the study, the combination of AFP, Vitamin-D, and Cr (AFP+Vit-D+Cr) has a high predictive value, which improves diagnosis and offers a reliable instrument for identifying liver cancer.

Breast cancer (BC) is the second leading cause of death in the United States in women. 1 in 8 women in their lifetime has a risk of developing breast cancer. With advances in omics technology, more data is available for diagnosis, treatment, and prognosis. The help of Machine Learning algorithms, a subdomain of Artificial Intelligence, would allow for a better clinical support tool. Machine Learning could be the key to answering a complex problem in BC. The methodology of this research question involves collecting and finding data such as RNA-Seq datasets, selecting and training appropriate machine learning algorithms, and evaluating the performance of the algorithms in predicting BC prognosis. Also, the study explores and tries to identify the most relevant genes and pathways through feature selection extraction and dimensionality reduction techniques. After applying feature extraction, the top 10 genes were extracted using the Univariate Feature Selection (UFS) method, precisely the SelectKBest technique. After employing different machine learning algorithms, such as Networks, Random Forest, Linear SVM, Logistic Regression, and Quadratic Discriminant Analysis (QDA), we found QDA was the best model in classifying the RNA-seq dataset with a 96% accuracy rate and 94% ROC AUC. This study suggests that AK2 and CD68 have a positive correlation with each other, and it could potentially be a biomarker and therapeutic target for BC.

Immunological aging type definition requires establishing reference intervals from the distribution of immunosenescence biomarkers conditional on age. For 1,605 individuals (18–97 years), we determined the comprehensive IMMmune Age indeX IMMAX from flow cytometry-based blood cell sub-populations, and identified age-specific centiles by fitting generalized additive models for location, scale and shape. The centiles were uncorrelated with age, and facilitated the categorization of individuals as immunologically slow or fast aging types. Using its 50th percentile as reference, we rescaled IMMAX to equivalent years-of-life (EYOL), and computed the immunological age gap as difference between EYOL and chronological age. Applied to preliminary baseline and follow-up measurements from 53 participants of the Dortmund Vital Study (Clinical-Trials.gov Identifier: NCT05155397), the averaged changes in IMMAX and EYOL conformed to the 5-year follow-up period, whereas no significant changes occurred concerning IMMAX centiles and age gap. This suggested that the participants immunologically adapted to aging, and kept their relative positions within the cohort. Sex was non-significant. Methodical comparisons indicated that future confirmatory analyses with the completed follow-up examinations could rely on percentile curves estimated by simple linear quantile regression, while the selection of the immunosenescence biomarker will greatly influence the outcome, with IMMAX representing the preferable choice.

Due to the lack of a diagnostic tumor marker (TM), the diagnosis of pancreatic neuroendocrine neoplasia (PNEN) is usually delayed, and a large part of patients present with regional (RM) and distant metastases (DM). The project aimed to assess the serum TM levels in PNEN and their relationships with disease extent and grade. One hundred fifteen patients with PNEN and 40 healthy subjects (HS) were enrolled. Most of the PNEN were well-differentiated (93.04%) and non-functional (93.91%). Beta-2 microglobulin (BMG), carbohydrate antigen 19-9 (CA19-9), carcinoembryonic antigen (CEA), cytokeratin 18 (CY18), and ferritin concentrations in PNEN patients were significantly higher than in HS (p &lt; 0.01). The highest area under the curve (AUC) ≥ 0.7 for differentiating PNEN patients from HS had CY18, CA19-9, and ferritin (p &lt; 0.001). PNEN disease was localized (LD) in 63 patients, 8 had RM, and 44 exhibited DM. Patients with metastatic PNEN (RM, DM) also showed significantly higher levels of CY18, CA125, and CEA than those without metastases (p &lt; 0.05). In conclusion, CY18, CA19-9, and ferritin were serum biomarkers that fair diagnosed PNEN disease. Elevated CY18, CA125, and CEA levels correlated with clinical stages (RM, DM) and elevated CY18, CA125 with high grade (G3) of disease.

Background: There is an increasing interest in the role of EEG in neurorehabilitation. We primarily aimed to identify the knowledge base through highly influential studies. Our secondary aims were to imprint the relevant thematic hotspots, research trends, and social networks within the scientific community. Methods: We performed an electronic search in Scopus looking for studies reporting on rehabilitation in patients with neurological disabilities. The most influential papers outlined the knowledge base, while a word co-occurrence analysis imprinted the research hotspots. Likewise, co-citation analyses highlighted collaboration networks between Universities, authors, and countries. The results were presented in summary tables, burst detection plots, and geospatial maps. Finally, a content review based on the top-20 most cited articles completed our study. Results: Our current bibliometric study was based on 874 records from 420 sources. There was a vivid research interest in EEG use for neurorehabilitation, with an annual growth rate as high as 14.3%. The most influential paper was the study titled "Brain-computer interfaces, a review" by Nicolas-Alfonso LF and Gomez-Gill J, with 997 citations, followed by "Brain-computer interfaces in neurological rehabilitation" by Daly J. and Wolpaw JR (708 citations). The USA, Italy, and Germany were among the most productive countries. The research hotspots shifted with time from the use of “functional magnetic imaging” to EEG-based “brain-machine interface”, “motor imagery”, and “deep learning”. Conclusions: EEG constitutes the most significant input in brain-computer interfaces (BCI) and can be successfully used in the neurorehabilitation of patients with stroke, amyotrophic lateral sclerosis, and traumatic brain and spinal injury. EEG-based BCI facilitates training, communication, and control of wheelchair and exoskeletons. However, research is limited to specific scientific groups from developed countries. Evidence is expected to change with the broader availability of BCI and improvement in EEG filtering algorithms.

Quantitative biomarkers derived from positron-emission tomography/computed tomography (PET/CT) have been suggested as prognostic variables in immune-checkpoint inhibitor (ICI) treated non-small cell lung cancer (NSCLC). As such data for first-line ICI therapy and especially for chemotherapy-ICI combinations are still scarce, we retrospectively evaluated baseline 18F-FDG-PET/CT of 85 consecutive patients receiving first-line pembrolizumab with chemotherapy (n=70) or as monotherapy (n=15). Maximum and mean standardized uptake value, metabolic tumor volume (MTV), total lesion glycolysis and bone marrow-/ spleen to liver ratio (BLR/SLR) were calculated. Kaplan-Meier analyses and Cox-regression models were used to assess progression-free/overall survival (PFS/OS) and their determinant variables. Multivariate selection for PFS/OS revealed MTV as most relevant PET/CT biomarker (p<0.001). Median PFS/OS were significantly longer in patients with MTV≤70mL versus >70mL (PFS: 10 months (M; 95% confidence interval 4-16) vs. 4M (3-5), p=0.001; OS: not reached vs. 10M (5-15), p=0.004). Disease control rate was 81% vs. 53% for MTV≤/>70mL (p=0.007). BLR ≤1.06 versus >1.06 was associated with better outcomes (PFS: 8M (4-13) vs. 4M (3-6), p=0.034; OS: 19M (12-/) vs. 6M (4-12), p=0.005). In patients with MTV>70mL, concomitant BLR≤1.06 indicated a better prognosis. Higher MTV is associated with inferior PFS/OS in first-line ICI treated NSCLC, with BLR allowing additional risk stratification.

The use of biomarkers to measure immune responses in serum is crucial for understanding population-level exposure and susceptibility to human pathogens. Advances in sample collection, multiplex testing, and computational modeling are transforming serosurveillance into a powerful tool for public health program design and response to infectious threats. In July 2018, 70 scientists from 20 countries met to perform a landscape analysis of approaches that support an integrated serosurveillance platform, including the consideration of issues for successful implementation. Here, we summarize the group’s insights and proposed roadmap for implementation, including objectives, technical requirements, ethical issues, logistical considerations, and monitoring and evaluation.

The objective of this study was to evaluate biomarkers of heat stress (HS) from automatic milking system (AMS), the relationships between measurements of temperature-humidity index (THI) and reticulorumen ph and temperature and some automatic milking systems parameters in dairy cows (rumination time (RT), milk traits, body weight (BW) and consumption of concentrate (CC)) during summer period. The experiment was carried out on a dairy farm at 54.9587408, 23.784146. Lithuanian Black and White dairy cows (n=365) were selected. The cows were milked with Lely Astronaut® A3 milking robots with free traffic. The rations were calculated to meet physiological requirements of the animals. Daily milk yield, rumination time, body weight, milk fat and protein ratio were collected from the Lely T4C management program for analysis. The pH and temperature of the contents of cow reticulorumen were measured using specific smaX-tec boluses manufactured for animal care. The daily humidity and air temperature in the farm zone were obtained from the adjacent weather station (2 km away). According this study during HS, the higher THI had positive correlation with ML, which show tendencies to increase risk of mastitis, and decrease CC, RT, BW, MY, reticulorumen ph and F/P. Some biomarkers of HS can be milk yield, milk lactose, somatic cell count, concentrate conception, rumination time, body weight, reticulorumen ph and milk fat – protein ratio. We can recommend to monitoring these parameters in the herd management program to identify possibility of heat stress.

1) Background: One of the most common cancer that affects men worldwide and North American men is prostate cancer. Gleason score is a pathological grading system to examine the potential aggressiveness of the disease in the prostate tissue. The advancement in computing and next-generation sequencing technology now allow us to study the genomic profiles of patients in association with their different Gleason score more accurately and effectively. 2) Methods: In this study, we used a novel machine learning method to analyze gene expression of prostate tumors with different Gleason scores, and identify potential genetic biomarkers for each Gleason group. We obtained a publicly-available RNA-Seq dataset of a cohort of 104 prostate cancer patients from the National Center for Biotechnology Information’s (NCBI) Gene Expression Omnibus (GEO) repository, and categorized patients based on their Gleason scores to create a hierarchy of disease progression. A hierarchical model with standard classifiers in different Gleason groups, also known as nodes, was developed to identify and predict nodes based on their mRNA or gene expression. In each node, patient samples were analyzed via class imbalance and hybrid feature selection techniques to build the prediction model. The outcome from analysis of each node is a set of genes that can differentiate each Gleason group from the remaining groups. To validate the proposed method, the set of identified genes are used to classify a second dataset of 499 prostate cancer patients collected from cBioportal [1]. 3) Results: The overall accuracy of applying this novel method to the first dataset was 93.3%, and further validated to 87% accuracy using the second dataset. This method also identified genes that were not previously reported as potential biomarkers for specific Gleason groups. In particular, PIAS3 was identified as a potential biomarker for Gleason score 4+3=7, and UBE2V2 for Gleason score 6. 4) Insight: Previous reports show that the genes predicted by this newly proposed method strongly correlate with prostate cancer development and progression. Furthermore, pathway analysis shows that both PIAS3 and UBE2V2 share similar protein interaction pathways, the JAK/STAT signaling process.

Background: Macrophage inflammatory protein-1 alpha (MIP-1α) and C-reactive protein (CRP) are pro-inflammatory biomarkers that quantify clinical and subclinical inflammation in cardiac ischemia in cardiac inflammation and disease. Adiponectin is an anti-inflammatory marker associated with good health. The susceptibility of periodontitis patients to cardiovascular events needs to be evaluated. Objective: This study aims to assess the levels of biomarkers in periodontitis patients with and without acute myocardial infarction (AMI) compared to controls. Material and methods: Pro-inflammatory and anti-inflammatory analytes were examined by collecting unstimulated saliva from three groups (n = 20/each): healthy individuals, individuals with stage III periodontitis, and post-myocardial infarction patients with stage III periodontitis. The samples were collected within 48 hours of AMI. Results: Adiponectin levels were significantly lower in patients with periodontitis with and without AMI compared to controls, while CRP and MIP-1α were significantly higher in patients with periodontitis with and without AMI compared to controls. The highest titers for MIP-1α and CRP were detected among patients with periodontitis with and AMI. Conclusion: Our study provides evidence of the association between periodontitis and salivary analytes that occur in tandem with cardiovascular disease. The lower levels of Adiponectin and higher levels of CRP and MIP-1α in patients with periodontitis indicate that this condition is a potential risk factor for cardiovascular disease. The findings emphasize the importance of early detection and intervention for periodontitis patients to prevent cardiovascular events.

Alzheimer’s disease (AD) is an irreversible neurodegenerative disease characterized by progressive cognitive decline. The two cardinal neuropathological hallmarks of AD include buildup of cerebral β amyloid (Aβ) plaques and neurofibrillary tangles of hyperphosphorylated tau. The current disease-modifying treatments are still not effective enough to lower the rate of cognitive decline. The paucity of early detection and disease progression biomarkers also seems to present a major obstacle to AD drug development. The current established readouts based on expression levels of amyloid beta, tau and phospho tau have shown many discrepancies in patient samples when linked to disease progression. There is an urgent need to identify diagnostic and disease progression biomarkers from blood, CSF or other biofluids that can facilitate early detection of the disease and provide pharmacodynamic readouts for new drugs being tested in clinical trials. Advances in proteomic approaches using state-of-the-art mass spectrometry, are now being increasingly applied to study AD disease mechanisms, identify drug targets and novel disease biomarkers. In this report, we describe applications of the quantitative proteomic approaches for understanding AD pathophysiology, summarize the current knowledge gained from proteomic investigations of AD and discuss development and validation of new predictive and diagnostic disease biomarkers.

The paper focuses on the application of a multilevel, integrative and territorial approach to the protection of cultural heritage through planning instruments in Serbia. It points out the problems of the sectoral approach and discusses international recommendations that can be integrated into the planning methodology. The case study is the area of Djerdap National Park, which has an already established international and national importance. The research suggests that the cultural heritage in the area, with the exception of the Roman limes, is still recognized at the level of individual localities. The study emphasizes the importance of aligning all levels of governance to safeguard the whole spatial entity rather than focusing solely on its particular areas. The interna-tional and national importance of the planning area contributes to the strengthening of awareness of heritage and its institutional protection. However, the vitality of the area, which is key to its sustainable development, comes from the local level. Planning documents contribute to the inte-gration of local values and local communities into development programs and projects.

Abstract: Sustainable use of Native American heritage places is viewed in this analysis as serving to preserve their traditional purposes and sustain the cultural landscapes that give them heritage meaning. The research is about the potential impacts of heritage tourism to selected Native American places at Arches National Park, Canyonlands National Park, and Hovenweep National Monument. The impacts of tourists to a heritage place must be understood as having both potential effects on the place itself and on an integrated cultural landscape. Impacts to one place potentially change other places- functions in a Native American landscape and the integrity of the landscape itself. The analysis is based on 696 interviews with representatives from nine tribes and pueblos, who in addition to defining the cultural meaning of places, officially made 349 heritage management recommendations. The U.S. National Park Service interprets Natives American resources and then brings millions of tourists to these through museums, brochures, outdoor displays, and ranger-guided tours. Native American ethnographic study participants argued that tourist education and regulation can increase the sustainability of Native American places in a park and can help protect related places beyond the park.

A large body of evidence has linked unhealthy eating patterns with an alarming increase in obesity and chronic disease worldwide. However, existing methods of assessing dietary intake in nutritional epidemiology rely on food frequency questionnaires or dietary records that are prone to bias and selective reporting. Herein, metabolic phenotyping was performed on 42 healthy participants from the Diet and Gene Intervention (DIGEST) pilot study, a parallel two-arm randomized clinical trial that provided complete diets to all participants. Matching urine and plasma specimens were collected at baseline and following 2 weeks of provision of either a Prudent or Western diet with a weight-maintaining menu plan designed by a dietician. Targeted and nontargeted metabolite profiling was conducted using three complementary analytical platforms, where 80 plasma metabolites and 84 creatinine-normalized urinary metabolites were reliably measured (CV < 30%) in the majority of participants (> 75%) after implementing a rigorous data workflow for metabolite authentication with stringent quality control. We classified a panel of metabolites with distinctive trajectories following 2 weeks of food provisions when using complementary univariate and multivariate statistical models. Unknown metabolites associated with contrasting dietary patterns were identified with high resolution MS/MS and/or co-elution after spiking with authentic standards. Overall, 3-methylhistidine and proline betaine concentrations increased consistently after participants were assigned a Prudent diet (q< 0.05) in both plasma and urine samples with a corresponding decrease in the Western diet group. Similarly, creatinine-normalized urinary imidazole propionate, hydroxypipecolic acid, dihydroxybenzoic acid, and enterolactone glucuronide, as well as plasma ketoleucine and ketovaline increased with a Prudent diet (p< 0.05) after adjustments for age, sex and BMI. In contrast, plasma myristic acid, linoelaidic acid, linoleic acid, a-linoleic acid, pentadecanoic acid, alanine, proline, carnitine and deoxycarnitine, as well as urinary acesulfame K increased among participants following a Western diet. Most metabolites were also correlated (r > ±0.30, p< 0.05) to changes in average intake of specific nutrients from self-reported diet records reflecting good adherence to assigned food provisions. Our study revealed robust biomarkers sensitive to short-term changes in habitual diet for accurate monitoring of healthy eating patterns in free-living populations, which is required for validating evidence-based public health policies for chronic disease prevention.

Abstract: Letter migrations between words in reading aloud (e.g., reading "cane love" as "lane love" or "lane cove") are known to result from a deficit in the visual-orthographic analysis and characterize attentional dyslexia. In spontaneous speech, individuals with impairment in the phonological output buffer may show migrations of phonemes between words. The purpose of this study was to examine whether migrations between words in reading aloud can also result from a deficit in the phonological output buffer, to explore the characteristics of migrations resulting from orthographic input and from phonological output deficits, and to examine methods to distinguish these two sources. Using tasks of reading aloud of 92-182 word pairs, we identified 18 adults and adolescents with developmental dyslexia who made between-word letter migrations in reading aloud, significantly more than age-matched controls (372 adults and 26 7th-graders). To distinguish between orthographic-input and phonological-output sources for these migrations, we administered a test assessing orthographic-input without spoken-output (written-semantic-decision on 140 migratable word pairs) and a test of repetition of 36 auditorily-presented migratable word pairs, assessing spoken output without orthographic-input (and word span tests). These tests indicated that the migrations of ten of the participants with dyslexia resulted from an orthographic-input deficit, and for the other eight participants, migrations resulted from a phonological-output deficit. We identified several differences between the two types of between-word errors: first, whereas the individuals with attentional dyslexia made omissions of a letter that appeared in the same position in the two words, the phonological output buffer group did not make such omissions. In addition, the groups differed in the origin of migration: orthographic input migrations involve letters that are orthographically adjacent, whereas phonological output migrations involve phonemes that have just been spoken or that are prepared together in the phonological buffer for production. This was manifested in that migrations from the line below and from two lines above occurred only in the orthographic input deficit group, and migrations occurred from a word vertically close to the target in the orthographic input group but from a word that has just been spoken (placed diagonally to the target) in the phonological output group. This study thus indicates that between-word migrations in reading-aloud can result not only from attentional dyslexia, but also from a phonological output buffer deficit, and offers ways to distinguish between the two.

Ocean big data is the scientific practice of using big data technology in the marine field. Data from satellites, manned spacecraft, space stations, airship, unmanned aerial vehicles, shore-based radar and observation stations, exploration platforms, buoys, underwater gliders, submersibles, and submarine observation networks are seamlessly combined into the ocean’s big data. Increasing numbers of scholars have tried to fully analyze the ocean’s big data. To explore the key research technology knowledge graphs related to ocean big data, articles between 1990 and 2020 were collected from the “Web of Science”. By comparing bibliometric software and using the visualization software Cite-Space, the pivotal literature related to ocean big data, as well as countries, institutions, categories, and keywords, were visualized and recognized. Journal co-citation analysis networks can help determine the national distribution of core journals. Co-citation analysis networks for documents show authors who are influential at key technical levels. Key co-occurrence analysis network keywords can determine research hot spots and research frontiers. The three supporting elements of marine big data research are shown in the co-citation network. These elements are author, institution, and country. By examining the co-occurrence of keywords, the key technology research directions for future marine big data were determined.

Background: Tumor microenvironment (TME) plays a crucial role in virtually every aspect of tumorigenesis of glioblastoma multiforme (GBM). The dysfunctional TME promotes drug resistance, disease recurrence and distant metastasis. Recent evidence indicates that exosomes released by stromal cells within TME may promote oncogenic phenotypes via transferring signaling molecules such as cytokines, proteins and microRNAs. Results: In this study, clinical GBM samples were collected and analyzed. We found that GBM-associated macrophages (GAMs) secreted exosomes which were enriched with oncomiR-21. Co-culture of GAMs (and GAM derived exosomes) and GBM cell lines resulted in the increased GBM cells’ resistance against temozolomide (TMZ) by upregulating pro-survival gene, PDCD4 and stemness markers Sox2, STAT3, Nestin and miR-21-5p and increased M2 cytokines, IL-6 and TGF-β1 secreted by GBM cells, promoting the M2 polarization of GAMs. Subsequently, pacritinib treatment suppressed GBM tumorigenesis and stemness; more importantly, pacritinib-treated GBM cells showed markedly reduced ability to secret M2 cytokines and reduced miR-21 enriched exosomes secreted by GAMs. Pacritinib-mediated effects were accompanied by a reduction of oncomiR miR-21-5p, by which tumor suppressor PDCD4 was targeted. We subsequently established a patient-derived xenograft models where mice bore patient GBM and GAMs. The treatment of pacritinib, and the combination of pacritinib/TMZ appeared to significantly reduce tumorigenesis of GBM/GAM PDX mice, overcome TMZ-resistance, and M2 polarization of GAMs. Conclusion: In summation, we showed that potential of pacritinib alone or in combination with TMZ for suppressing GBM tumorigenesis via modulating STAT3/miR-21/PDCD4 signaling. Further investigations are warranted for adopting pacritinib for the treatment of TMZ-resistant GBM in the clinical settings.

Glycosidic linkage analysis was conducted on the unfractionated polysaccharides in the alcohol-insoluble residues (AIRs) prepared from six red seaweeds (Gracilariopsis sp., Prionitis sp., Mastocarpus papillatus, Callophyllis sp., Mazzaella splendens, and Palmaria palmata) using GC-MS/FID analysis of partially methylated alditol acetates (PMAAs). The cell walls of P. palmata primarily contained mixed-linkage xylans and small amounts of sulfated galactans and cellulose. In contrast, the unfractionated polysaccharides of the other five species were rich in galactans displaying diverse 3,6-anhydro-galactose and galactose linkages with varied sulfation patterns. Different levels of cellulose were also observed. This glycosidic linkage method offers advantages for cellulose analysis over traditional monosaccharide analysis that is known for underrepresenting glucose in crystalline cellulose. Relative linkage compositions calculated from GC-MS and GC-FID measurements showed that anhydro sugar linkages generated more response in the latter detection method. This improved linkage workflow presents a useful tool for studying polysaccharide structural variations across red seaweed species. Furthermore, for the first time, relative linkage compositions from GC-MS and GC-FID measurements, along with normalized FID and total ion current (TIC) chromatograms without peak assignments, were analyzed using principal component analysis (PCA) as a proof-of-concept demonstration of the technique's potential to differentiate various red seaweed species.

Background: Educating college students about the importance of good sleep habits could lead to the adoption of healthier sleep routines, including sufficient sleep duration and sleep quality. The current pre-post study examines the impact of completing a sleep education program called “Sleep 101” on (1) sleep hygiene practices, (2) sleep quality, and (3) weekday and weekend sleep behaviors among college students. “Sleep 101” is an interactive online course developed to educate college students about the importance of sleep by addressing basic sleep physiology, the impact of sleep on mood, academic and physical performance, the interactions between sleep and various substances, and common sleep disorders. Methods: 338 college students were recruited from a midsized public university in the US and invited to participate in “Sleep 101”, of which 25 participants completed the baseline and post-intervention questionnaire. The Sleep Hygiene Index (SHI) was utilized to evaluate sleep hygiene practices, while standard questions were employed to assess weekday and weekend sleep behaviors and overall sleep quality. Results: Those who completed the study demonstrated a significant increase in weekday sleep duration and were less likely to engage in negative prior bedtime activities. In addition, 40% of those who completed baseline and post-intervention assessments noticed improvements in their sleep quality. Conclusion: These findings suggest that a brief online program is beneficial in improving sleep behaviors among college and could be a scalable approach to addressing current sleep issues and preventing future sleep problems in college students.

The profile of secondary metabolites occurring in apple cuticular layer is not only characteristic for particular apple cultivar, but also dynamically reflects various external factors in growing environment. In this study, the possibility to authenticate apple samples based on analysis of their cuticular layer extracts was investigated. Ultra-high-performance liquid chromatography coupled to high resolution tandem mass spectrometry (UHPLC-HRMS/MS) was employed for obtaining metabolomic fingerprints. In total, 274 authentic apple samples, four cultivars harvested within the seasons 2020 to 2022 in the Czech Republic and Poland were analysed. The generated complex data processed by univariate and multivariate statistical methods enabled to build classification models for discrimination of apple cultivars as well as their geographical origin. The models showed very good performance in differentiation of Czech and Polish samples for three of four cultivars: ‘Gala’, ‘Golden Delicious’ and ‘Idared’, moreover, the validity of the models was verified over harvest seasons. The diagnostic markers, besides metabolites of triterpene biosynthetic pathway, mainly represented wax esters. ‘Jonagold’, which is known to be susceptible to mutations, was the only cultivar for which the unambiguous classification of geographical origin was not possible.

The temporary immersion system bioreactor named GreenTray®[2], [3]presents advantages over the existing ones. Firstly, there is no need to use forceps to move the shoots or plantlets in or out of the recipient, neither the use of scalpel to divide them. Secondly, the basis of the shoot can remain in the GreenTray® and can sprout again in several cycles of growth. These two characteristics reduce the costs in the process of micropropagation. Besides, shoots or plantlets development is enhanced by the aeration of the recipient, thus enriching with CO2 the recipient atmosphere. The chapter describes and provides images and values of interest in (1) the micropropagation process of some commercial Prunus or Pyrus rootstocks; (2) the plantlet growth under autotrophic conditions; and (2) the inoculation of plants with pathogens that reproduce in vitro the symptoms observed in vivo, using the GreenTray® bioreactor.