Objective: About a third of schizophrenia patients are treatment-resistant to antipsychotic therapy. No studies established the fingerprints or pathway-phenotypes of treatment-resistant schizophrenia. The present study aimed to delineate the pathway-phenotypes of non-responders (NRTT) and partial responders (PRTT) to treatment using machine learning. Methods: We recruited 115 schizophrenia patients and 43 healthy controls and measured schizophrenia symptom dimensions, neurocognitive tests, plasma CCL11, interleukin-(IL)-6, IL-10, Dickkopf protein 1 (DKK1), high mobility group box-1 protein (HMGB1), κ- and µ-opioid receptors (KOR and MOR, respectively), endomorphin-2 (EM-2), and β-endorphin. Results: Machine learning showed that the NRTT group is a qualitatively distinct class and is significantly discriminated from PRTT with an accuracy of 100% using a neuro-immune-opioid-cognitive (NIOC) pathway-phenotype with as main determinants list learning, controlled word association, and Tower of London test scores, CCL11, IL-6, and EM2. The top-5 symptom domains separating NRTT from PRTT were in descending order: psychomotor retardation, negative symptoms, psychosis, depression, and mannerism. Moreover, a NIOC pathway also discriminated PRTT from healthy controls with an accuracy of 100% while all PRTT and controls were authenticated as belonging to their respective classes. Conclusion: A non-response to treatment with antipsychotics is determined by increased severity of specific symptom profiles coupled with deficits in executive functions, and episodic and semantic memory, and aberrations in neuro-immune and opioid pathways. No patients showed complete remission after treatment indicating that non-remitting in PRTT is attributable to increased HMGB1 and residual deficits in attention, executive functions, and semantic memory.

No studies have examined the immune fingerprint of major neuro-cognitive psychosis (MNP) or deficit schizophrenia using M1 macrophage cytokines in combination with chemokines such as CCL-2 and CCL-11. The present study delineated the neuro-immune fingerprint of MNP/deficit schizophrenia by analyzing plasma levels of IL-1β, sIL-1RA, TNF-α, sTNFR1, sTNFR2, CCL-2 and CCL-11 in MNP (n=120) versus healthy controls (n=54) in association with neurocognitive deficits (as assessed with the Brief Assessment of Cognition in Schizophrenia) and PHEMN (psychotic, hostility, excitation, mannerism and negative) symptoms. All immune biomarkers were significantly higher in MNP than in normal controls. MNP was best predicted by a combination of CCL-11, TNF-α, IL-1β and sIL-1RA which yielded a bootstrapped (n=2000) area under the Receiver Operating Curve of 0.985. Composite scores reflecting M1 macrophage activity and neurotoxic potential including combined effects of CCL-11 plus CCL-2 were significantly increased in MNP. Nevertheless, the effects of increased IL-1β and TNF-α in MNP were attenuated (statistically) by increased sIL-1RA and sTNFR2, two negative immune-regulatory markers. A large part of the variance in PHEM (38.4%-52.6%) and negative (65.8-7439%) symptoms was explained by combinations of immune markers whereby CCL-11 was consistently the most important. The immune markers also explained a large part of the variance in the Mini Mental State examination, list learning, digit sequencing task, category instances, controlled word association, symbol coding and Tower of London. Soft Independent Modeling of Class Analogy performed on the biomarkers showed that the inter-class distance between the models constructed around MNP and controls was 19.3 indicating a good separation. Partial Least Squares analysis showed that 72.7% of the variance in overall phenomenology was explained by the regression on IL-1β, sIL-1RA, CCL-11, TNF-α (all positively) and education (inversely). It is concluded that the combination of the above-mentioned markers defines MNP as a distinct neuro-immune disorder and that those markers in combination explain a large part of the variance in memory and executivive impairments and PHEMN symptoms.

Background: The Apolipoprotein E4 (ApoE4) genotype is strongly associated with Alzheimer’s disease (AD), although the presence of the ApoE4 allele alone is not sufficient to explain AD. The pathophysiology of amnestic mild cognitive impairment (aMCI) remains unclear. This study aims to examine associations between peripheral blood biomarkers coupled with ApoE4 and episodic and semantic memory. Methods: The CERAD battery was completed and various biomarkers were assayed in 60 subjects with aMCI, 60 with AD and 62 healthy controls. Results: Deficits in semantic and episodic memory were significantly predicted by anion gap and bicarbonate, albumin and glucose coupled with Apo E4. Furthermore, these peripheral biomarkers interacted with ApoE to predict greater memory impairments. Conclusions: Peripheral blood biomarkers may interact with pathways related to ApoE4 to predict greater semantic and episodic memory impairments, thus contributing to the pathophysiology of aMCI and AD. Our data suggest that the transition from aMCI to AD could at least in some cases be associated with significant interactions between ApoE4 and those peripheral blood biomarkers.

Direct mass spectrometry-based metabolomics has been widely employed in the last years to characterize metabolic alterations underlying to Alzheimer’s disease development and progression. This high-throughput approach presents a great potential for fast and simultaneous fingerprinting of a vast number of metabolites, which can be applied to multiple biological samples such as serum/plasma, urine, cerebrospinal fluid and tissues. In this review article we present the main advantages and drawbacks of metabolomics based on direct mass spectrometry compared with conventional analytical techniques, and provide a comprehensive revision of the literature on the application of these tools in Alzheimer’s disease research.

Understanding the interplay among organophosphorus flame-retardants (OPFRs), microplastics, and freshwater organisms is crucial for unravelling the dynamics within freshwater environments and foreseeing the potential impacts of organic pollutants and plastic contamination. For that purpose, the present research assessed the exposure impact of 10 mg L–1 flame-retardant alumin-ium diethylphosphinate (ALPI), 10 μg mg–1liver microplastics polyurethane (PU), and the combina-tion of ALPI and PU on the freshwater planarian Girardia tigrina. The exposure of G. tigrina to both ALPI and PU revealed a sequential effect, i.e., a decrease in locomotor activity, while other molecular biomarkers (oxidative stress biomarkers and metabolic response) remained unaffected. Despite this fact, it was possible to observe that the range (min-max) of responses of exposed or-ganisms were altered, in the particular case of electron transport system, cholinesterase activity, glutathione S-transferase, catalase and levels of total glutathione and proteins, showing that the energetic costs for detoxification and antioxidant capacity might be causing less energy allocated for the planarian activity. By examining the physiological, behavioural, and ecological responses of planarians to these pollutants, insights can be gained into broader ecosystem-level effects and inform strategies for mitigating environmental risks associated with OPFRs and microplastic pol-lution in freshwater environments.

There has been significant increase of studies investigating plasma biomarkers of Alzheimer’s and their relationship to cognitive functioning. The impact of ethnicity on this relationship has not been extensively studied. The current research investigated the relationship between the plasma biomarkers of total tau, Aβ40, Aβ42 and NfL and neuropsychological test performance in a bi-ethnic sample of cognitively unimpaired, older community dwelling adults. The 1326 cognitively unimpaired participants drawn from The Health & Aging Brain Study – Health Disparities (HABS-HD) study included 765 Mexican American participants and 860 non-Hispanic White participants with complete plasma biomarkers and neuropsychological testing. Plasma samples were assayed using Simoa technology. Significant differences in concentrations were found for all of the plasma biomarkers. NHWs had significantly higher levels of each of the biomarkers with a lower Aβ42/ Aβ40. With none of the biomarkers related to performance on any of the neuropsychological tests. For MAs, Aβ40 was the only biomarker that was significantly related to neuropsychological test performance. Aβ40 levels were negatively related to performance on Trails A, Trails B and Digit Symbol Substitution. Results suggest that the relationship of these biomarkers to cognitive functioning is impacted by ethnicity and may be domain specific.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) persists throughout the world with over 65 million registered cases of survivors with post-COVID-19 sequelae, also known as LongCOVID-19 (LongC). LongC survivors exhibit various symptoms that span multiple organ systems, including the nervous system. To search for neurological biomarkers of LongC, we investigated the soluble proteins present in the plasma and the proteins associated with plasma neuronal-enriched extracellular vesicles (nEVs) in 33 LongC patients with neurological impairment (nLongC), 12 COVID-19 survivors without any LongC symptoms (Cov), and 28 pre-COVID-19 healthy controls (HC). COVID-19 positive participants were infected from 2020-2022, not hospitalized, and were vaccinated or unvaccinated before infection. IL-1b was significantly increased in both nLongC and Cov and IL-8 elevated in only nLongC. Both brain-derived neurotropic factor and cortisol were significantly elevated in nLongC and Cov compared to HC. nEVs from people with nLongC had significantly elevated protein markers of neuronal dysfunction, including amyloid beta 42, pTau181 and TDP-43. This study shows chronic peripheral inflammation with increased stress after COVID-19 infection. Additionally, differentially expressed nEV neurodegenerative proteins were identified in people recovering from COVID-19 regardless of persistent symptoms.

Contrast-Induced Acute Kidney Injury (CI-AKI) remains a frequent iatrogenic condition since radiological procedures using intra-vascular iodinated contrast media (CM) are being widely administered for diagnostic and therapeutic purposes. Despite the improvement of the medical healthcare system worldwide, CI-AKI is still associated with direct short-term and indirect long-term outcomes including increased morbidity and mortality, specially, in patients under-lying pre-existing renal function impairment, cardiovascular disease or diabetes that could rap-idly progress into Chronic Kidney Disease. Although the RIFLE (Risk, Injury, Failure, Loss, End-Stage Kidney Disease), AKIN (Acute Kidney Injury Network) and KDIGO (Kidney Disease Improving Global Outcomes) clinical criteria and recommendation guidelines are based on tra-ditional “gold standard” biomarkers known as serum creatinine, glomerular filtration rate and urinary output, new reliable serum and urinary biomarkers are still needed for an effective uni-fied diagnostic strategy for AKI. Starting from previous and recent publications on the benefits and limitations of validated biomarkers responding to kidney injury, glomerular filtration and inflammation among others, this review unravels the role of new emerging biomarkers used alone or in combination, as reliable tools for early diagnosis and prognosis of CI-AKI, taking into account patients and procedures-risk factors towards a new clinical perspective.

Mucopolysaccharidosis type IVA (MPS IVA; Morquio A syndrome) is a rare autosomal recessive lysosomal storage disease (LSD) caused by deficiency of a hydrolase enzyme, N-acetylgalactosamine-6-sulfate sulfatase, and characterized clinically by mainly musculoskeletal manifestations. The mechanisms underlying bone involvement in humans are typically explored using invasive techniques such as bone biopsy, which complicates analysis in humans. We compared bone proteomes using DDA and SWATH-MS in wild-type and MPS IVA knockout mice to obtain mechanistic information about the disease. Our findings reveal over 1000 dysregulated proteins in knockout mice, including those implicated in oxidative phosphorylation, oxidative stress (reactive oxygen species), DNA damage, and iron transport, and suggest that lactate dehydrogenase may constitute a useful prognostic and follow-up biomarker. Identifying biomarkers that reflect MPS IVA clinical course, severity, and progression have important implications for disease management.

Background: Estrogen homeostasis is crucial for bladder function, and estrogen deprivation resulting from ovarian removal or ovarian dysfunction may lead to various bladder dysfunctions. However, the specific mechanisms are not fully understood. Methods: We simulated estrogen deprivation using a rat ovariectomy model and supplemented estrogen through subcutaneous injections. The metabolic characteristics of bladder tissue were analyzed using non-targeted metabolomics, followed by bioinformatics analysis to preliminarily reveal the association between estrogen deprivation and bladder function. Results: We successfully established a rat model with estrogen deprivation and, through multivariate analysis and validation, identified several promising biomarkers represented by 3, 5-tetradecadiencarnitine, lysoPC (15:0), and cortisol. Furthermore, we explored estrogen deprivation-related metabolic changes in the bladder primarily characterized by amino acid metabolism imbalance. Conclusions: This study, for the first time, depicted the metabolic profile of bladder resulting from estrogen deprivation, providing an important experimental basis for future research on bladder dysfunctions caused by estrogen deprivation.

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 biomarkers represent a promising future for studying cognitive impairment, particularly in Alzheimer's Disease (AD), as they offer a non-invasive alternative to cerebrospinal fluid tests and have potential as population screening tools. However, the relationships between these biomarkers and specific cognitive functions, as well as their utility in predicting longitudinal cognitive decline, are not yet fully understood. This descriptive review surveys the literature from 2018 to 2023, focusing on the associations between Amyloid-β, Total Tau, Phosphorylated Tau (p-tau), Neurofilament Light (Nfl), and Glial Fibrillary Acidic Protein (GFAP) with cognition. The reviewed studies are heterogeneous, varying in design and population (mixed, cognitively impaired, or unimpaired), and show results that are sometimes conflicting. Generally, cognition positively correlates with Aβ levels, especially when evaluated through the Aβ42/Aβ40 ratio. In contrast, Tau, Nfl, and GFAP levels typically show a negative correlation with cognitive performance. While p-tau measures tend to show stronger associations with cognitive functions than other biomarkers, no single blood marker has emerged as predominantly associated with a specific cognitive domain. These findings add to our understanding of the complex relationship between blood biomarkers and cognitive performance and underscore their potential utility in clinical evaluations of cognition.

Cancer is a complex and heterogeneous disease, influenced by various factors that affect its progression and response to treatment. Although histopathological diagnosis is crucial for identifying and classifying cancer, it may not accurately predict the disease's development and evolution in all cases. To address this limitation, liquid biopsy has emerged as a valuable tool, enabling a more precise and non-invasive analysis of cancer. Liquid biopsy offers the ability to detect tumor DNA fragments, circulating tumor cells, and exosomes released by cancer cells into the bloodstream. Exosomes, in particular, have attracted significant attention in cancer research due to their specific protein composition, which can provide valuable insights into the disease. The protein profile of exosomes often differs from that of normal cells, reflecting the unique molecular characteristics of cancer. Analyzing these proteins can help identify cancer-associated markers that play critical roles in tumor progression, invasion, and metastasis. Ongoing research and clinical validation are essential to advance and effectively utilize protein biomarkers in cancer. Nevertheless, their potential to improve diagnosis and treatment is highly promising. This review discuss several exosome proteins of interest in breast cancer, particularly focusing on studies conducted in mammary tissue and cell lines in humans and experimental animals. Unfortunately, the studies conducted in the canine species are scarce. This emphasis sheds light on the limited research available in this field. Additionally, we present a curated selection of studies that have explored exosomal proteins as potential biomarkers, aiming to achieve the aforementioned benefits in breast cancer diagnosis, prognosis, monitoring, and treatment.

Clinical management in neuro-oncology has changed to an integrative approach that incorporates molecular profile alongside histopathology and imaging findings. While the WHO guideline recommends genotyping of informative alterations as a routine clinical practice for central nervous system (CNS) tumors, acquisition of tumor tissue in the CNS is invasive and not always possible. Liquid biopsy is a non-invasive approach that provides the opportunity to capture the complex molecular heterogeneity of the whole tumor through detection of circulating tumor biomarkers in body fluids, such as blood or cerebrospinal fluid. Despite all the advantages, the low abundance of tumor-derived biomarkers, particularly in CNS tumors, as well as their short half-life has limited the application of liquid biopsy in clinical practice. Thus, it is crucial to identify factors that are associated with the presence of these biomarkers and explore possible strategies that can increase the shedding of these tumoral components into biological fluids. In this review, we first describe the clinical applications of liquid biopsy in CNS tumors including its roles in early detection of recurrence and monitoring of treatment response. We then discuss the utilization of imaging in identifying factors that affect the detection of circulating biomarkers as well as how image-guided interventions such as focused ultrasound can help enhance the presence of tumor biomarkers through blood-brain barrier disruption.

Cancer is a common illness with a high mortality. Compared to traditional technologies, biomarkers detection, with low cost and simple operation, has higher sensitivity and faster speed in early screening and prognosis of cancer. Therefore, extensive research has been focused on the development of biosensors and the construction of sensing interfaces. Molybdenum disulfide (MoS2) is a promising two-dimensional (2D) nanomaterial, whose unique adjustable bandgap shows excellent electronic and optical properties in the construction of biosensor interfaces. It not only has the advantages of high catalytic activity and low manufacturing costs, but also can further expand the application of hybrid structures by different functionalization, and is widely used in various biosensors fields. Herein, the application of electrochemical and optical sensing platforms based on MoS2 in the detection of cancer biomarkers was comprehensively reviewed. Firstly, the structure and preparation method of MoS2 were introduced, and its applicable characteristics in the field of biosensors were explored. Secondly, we comprehensively reviewed the recent construction and application of sensing platform based on MoS2 in the field of cancer biomarkers detection in both electrochemical and optical aspects. The prime characteristics and application performances of MoS2 and its composites were emphasized. Additionally, we also involved some other types of biosensors based on MoS2. Finally, we summarized the challenges and development prospects of MoS2 in the application of cancer biomarkers detection, and provided some insights for the application potential of this kind of emerging nano-materials in a broader field.

Non-alcoholic fatty liver disease (NAFLD) is a liver disorder that has become a global health concern due to its increasing prevalence. Currently, there is a need for reliable biomarkers to aid in the diagnosis and prognosis of NAFLD. Extracellular vesicles (EVs) are promising candidates in biomarker discovery, as they carry proteins that reflect the pathophysiological state of the liver. In this review, we developed a list of EV proteins that could be used as diagnostic biomarkers for NAFLD. We employed a multi-step strategy that involved reviewing and comparing various sources of information. Firstly, we reviewed papers that have studied EVs proteins as biomarkers in NAFLD, as well as papers that have studied circulating proteins as biomarkers in NAFLD. To further identify potential candidates, we utilized the EV database Vesiclepedia.org to qualify each protein. Finally, we consulted the Human Protein Atlas to search for candidates' localization, focusing on membrane proteins. By integrating these sources of information, we developed a comprehensive list of potential EVs membrane protein biomarkers that could aid in the diagnosis and monitoring of NAFLD. In conclusion, our multi-step strategy for identifying EV-based protein biomarkers for NAFLD provides a comprehensive approach that can also be applied for other diseases. The protein candidates identified through this approach could have significant implications for the development of non-invasive diagnostic tests for NAFLD and improve the management and treatment of this prevalent liver disorder.

A number of agents, including immune checkpoint inhibitors, have become available for the treatment of hepatocellular carcinoma (HCC). However, the objective response rate of these drugs is currently only 30% to 40%, with a high incidence of side effects. There are also no prac-tical biomarkers to predict their therapeutic effects. Most of the systemic therapies for HCC are performed in general hospitals without research facilities. Such hospitals can perform imaging tests, like CT and MRI, as well as pathological diagnosis using tumor tissue sampling and im-munohistochemical staining. However, analyzing tumor genomic or transcriptomic profiles is difficult because of limitations in facilities, personnel, and cost. Therefore, in this review, we provide an overview of the wide range of research that has been conducted on HCC biomarkers from blood, tissue, or imaging information that can be used practically in general hospitals for predicting the therapeutic effect of systemic therapies before treatment begins. For general hos-pitals that treat HCC patients, we recommend conducting treatment after assessing the state within the tumor tissue as much as possible by collecting blood and tissue samples and per-forming pre- treatment MRI image evaluations.

The COVID-19 pandemic has brought marked changes worldwide to the management of airborne infectious diseases. It sparked the development of the SARS-CoV-2 vaccine and pharmacotherapeutics to prevent infection and increase the survival rate during the acute viral phase and the comorbidities associated with COVID-19. Periodontal disease may increase the morbidity and perhaps the mortality of a COVID-19 infection. However, the molecular interaction between periodontitis and COVID-19 infection remains undetermined. A potential pathogenic co-morbidity may involve periodontal pathogenic release of destructive cytokines in the highly inflamed connective tissue and risk for COVID-19. Additional biomarkers such as C-reactive proteins appear to play a role for risk and pathogenesis of COVID-19. The potential of herpesviruses, especially as it is related to aggressive periodontitis may also be a comorbidity for COVID-19. This paper reviews available evidence on the bidirectional association between periodontitis and COVID-19.

The identification of biomarkers is crucial for cancer diagnosis, understanding the underlying biological mechanisms, and developing targeted therapies. In this study we propose a machine learning approach to predict the outcome and platinum resistance status of ovarian cancer patients using public available gene expression data. Six classical machine learning algorithms are compared on their predictive performance. Those with the highest score are analyzed by their feature importance using the SHAP algorithm. We were able to select multiple genes that were correlating with the outcome and platinum resistance status of the patients and validated those using Kaplan-Meier plots. In comparison to similar approaches the performance of the models were higher and different genes using feature importance analysis were identified. The most promising identified genes that could be used as biomarkers are: TMEFF2, ACSM3, SLC4A1 and ALDH4A1.

Heart failure with preserved ejection fraction (HFpEF) remains a poorly characterized syndrome with many dark aspects related to different patients profile, various associated risk factors and wide aetiologies. It comprises several pathophysiological pathways related to endothelial dysfunction, myocardial fibrosis, extracellular matrix deposition and high inflammatory response. Up to now, it has been described only for clinical appearance and most common associated risk factors without an effective characterization of biological processes responsible for cardiovascular deteriorations. Recent advances in laboratory and metabolomic researches showed that HFpEF appears strictly related to specific cells and molecular mechanisms dysregulation. Some biomarkers are capable to early identify these processes adding new insights into diagnosis and risk stratification. Additionally recent advances on intermediate metabolites reflecting provide relevant information on intrinsic cellular and energetic substrate alterations. The systematic combination of clinical imaging and laboratory data may lead to a precision medicine approach providing prognostic and therapeutic advantages. Current review reports traditional and emerging biomarkers recently investigated in HFpEF setting, and it purpose a new diagnostic approach based on integrative information achieved from risk factors burden, hemodynamic dysfunction and biomarkers signature partnership.

Background: Current strategies in circulating tumor cell (CTC) isolation in pancreatic cancer heavily rely on the EpCAM and cytokeratin cell status. EpCAM is generally not considered as a good marker given its transitory change during Epithelial to Mesenchymal Transition (EMT) or reverse EMT. There is a need to identify other surface markers to capture the complete repertoire of PDAC CTCs. The primary objective of the study is to characterize alternate surface bi-omarkers to EpCAM on CTCs that express low or negligible levels of surface EpCAM in pancre-atic cancer patients. Methods: Flow cytometry and surface mass spectrometry were used to iden-tify proteins expressed on the surface of PDAC CTCs in culture. CTCs were grown under condi-tions of attachment and in co-culture with naïve neutrophils. Putative biomarkers were then validated in GEMMs and patient samples. Results: Surface proteomic profiling of CTCs identi-fied several novel protein biomarkers. ALCAM was identified as a novel robust marker in GEMM models and in patient samples. Conclusions: We identified several novel surface bi-omarkers on CTCs expressed under differing conditions of culture. ALCAM was validated and identified as a novel alternate surface marker on EpCAMlow CTCs.

Glial fibrillary acidic protein (GFAP) is the major intermediate filament III protein of astroglia cells which is upregulated in traumatic brain injury (TBI). Here we reported that GFAP is truncated at both the C- and N-terminals by cytosolic protease calpain to GFAP breakdown products (GBDP) of 46-40K then 38K following pro-necrotic (A23187) and pro-apoptotic (staurosporine) challenges to primary cultured astroglia or neuron-glia mixed cells. In addition, with another pro-apoptotic challenge (EDTA) where caspases are activated but not calpain, GFAP was fragmented internally, generating a C-terminal GBDP of 20 kDa. Following controlled cortical impact in mice, GBDP of 46-40K and 38K were formed from day 3 to 28 post-injury. Purified GFAP protein treated with calpain-1 and -2 generates (i) major N-terminal cleavage sites between A-56 and A-75, and (ii) major C-terminal cleavage sites between T-383 and Q-388, producing a limit fragment of 38K. Caspase-6 treated GFAP was cleaved at D-78, R-79, D-266 and A-267, where GFAP was relatively resistant to caspase-3. We also derived a GBDP-38K N-terminal-specific antibody which only labels injured astroglia cell body in both cultured astroglia and mouse cortex and hippocampus after TBI. As a clinical translation, we observed that CSF samples collected from severe human TBI have elevated levels of GBDP-38K as well as two C-terminally released GFAP peptides (DGEVIKES and DGEVIKE). Thus, in addition to intact GFAP, both the GBDP-38K as well as unique GFAP released C-terminal proteolytic peptides species might have the potential in tracking brain injury progression.

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.

This study aims to systematically review and meta-analyze the nitro-oxidative stress (O&NS)/antioxidant (ANTIOX) ratio in the peripheral blood of people with mild cognitive impairment (MCI). We searched PubMed, Scopus, Google Scholar, and Web of Science for articles published from inception until July 31, 2021. Forty-six studies on 3.798 MCI individuals and 6.063 healthy controls were included. The O&NS/ANTIOX ratio was significantly higher in MCI than in controls with a Standardized Mean Difference (SMD)=0.378 (95% CI: 0.250; 0.506). MCI individuals showed increased lipid peroxidation (SMD=0.774, 95%CI: 4.416; 1.132) and O&NS-associated toxicity (SMD=0.621, CI: 0.377; 0.865) and reduced glutathione (GSH) defenses (SMD=0.725, 95%CI: 0.269; 1.182) as compared with controls. MCI was also accompanied by significantly increased homocysteine (SMD=0.320, CI: 0.059; 0.581), but not protein oxidation, and lowered non-vitamin (SMD=0.347, CI: 0.168; 0.527) and vitamin (SMD=0.564, CI: 0.129; 0.999) antioxidant defenses. The results show that MCI is at least in part due to increased neuro-oxidative toxicity and suggest that treatments targeting lipid peroxidation and the GSH system may be used to treat or prevent MCI.

Ulcerative colitis (UC) is one of the two disorders known as inflammatory bowel diseases (IBD) along with Crohn’s disease (CD), with complex pathogenesis, requiring costly invasive investigations. Objective: to examine the most recent biomarkers proposed for UC diagnosis; to establish the strategy used to make the differential diagnosis between UC and CD relying on these biomarkers, also adding the benefit of finding new non-invasive tools in managing this condition. The search was performed in a single database (Web of Science) using the specific keywords „ulcerative colitis”, „biomarkers” and „diagnosis” for the last five years. Study eligibility criteria: clinical trials on adults and pediatric patients with ulcerative colitis compared with Crohn’s disease. Results: We selected 57 studies, randomized controlled trials (RCTs) and clinical case series (CCS), summarizing the latest most specific biomarkers in diagnosis of UC. Limitations: we considered RCTs and CCS from one database, limited to the search topics. Our findings indicate a important number of potential biomarkers with diagnostic value, which bring the advantage of a non-invasive method to approach this challenging disorder.

The early detection of cutaneous melanoma, a potentially lethal cancer with rising incidence, is key to increase survival and therapeutic adjustment. Especially in stages II-IV biomarkers are urgently needed for adjuvant therapy purposes after resection and for treatment of metastatic patients. We here investigated if fatty acid (FA) and protein composition of small extracellular vesicles (sEV) deriving from plasma of 0-I, II, and III-IV stage melanoma patients (n=38) could reflect disease stage and thus function as biomarker. The subpopulation of sEV expressing CD81 (CD81sEV) was isolated by an ad hoc immune affinity technique from microvesicle-depleted plasma. Biological macromolecules were investigated by gas chromatography and mass spectrometry in CD81sEV. A higher content of FA and a decrease in Saturation Index (C18:0/C18:1), already detectable in early stages, distinguished patients’ from healthy donor CD81sEV. Proteomics (identifier PXD024434) detected an exclusive and significant increase of CD14, PON1, PON3 and APOA5 in stage II and a significant decrease of Rap1b in stage III-IV CD81sEV. The FA and proteomic stage dependent CD81sEV signature strengthens the potential of circulating sEV studies in providing discriminatory information for early diagnosis, prediction of metastatic behavior and follow up of melanoma patients.

Ongoing beta cell death in type 1 diabetes (T1D) can be detected using biomarkers selectively discharged by dying beta cells into plasma. MicroRNA-375 (miR-375) ranks among top biomarkers based on studies in animal models and human islet transplantation. Our objective was to identify additional microRNAs that are co-released with miR-375 proportionate to the amount of beta cell destruction. RT-PCR profiling of 733 microRNAs in a discovery cohort of T1D patients 1 hour before/after islet transplantation indicated increased plasma levels of 22 microRNAs. Sub-selection for beta cell selectivity resulted in 15 microRNAs that were subjected to double-blinded multicenter analysis. This led to identification of 8 microRNAs that were consistently increased during early graft destruction: besides miR-375, these included miR-132/204/410/200a/429/125b, microRNAs with known function and enrichment in beta cells. Their potential clinical translation was investigated in a third independent cohort of 46 transplant patients, by correlating post-transplant microRNA levels to C-peptide levels 2 months later. Only miR-375 and miR-132 had prognostic potential for graft outcome and none of the newly identified microRNAs outperformed miR-375 in multiple regression. In conclusion, this study reveals multiple beta cell-enriched microRNAs that are co-released with miR-375 and can be used as complementary biomarkers of beta cell death.

Background: Hepatocellular carcinoma (HCC) is one of most common cancers with a high mortality rate. HBV/HCV infection is an important risk factor to trigger HCC. Therefore, developing serum biomarkers for early diagnosis is crucial to prolong survival in HCC patients. Methods: An antibody array technology was utilized to detect serum from 20 HBV-related HCC patients, 20 chronic hepatitis B patients and 20 normal population, whose results were further validated by ELISA. Results: Both antibody array and ELISA showed that ten growth factors (SCF R, GDF-15, HGF, FGF-4, IGFBP-1, PIGF, GH, GDNF, BDNF and IGF-1) were significantly differential in HCC patients when compared to the non-HCC population. Among these growth factors, the levels of SCF R, GDF-15, HGF, GH and IGF-1 showed significant correlation with hepatitis B and its severity, indicating that these growth factors may promote HCC progression by an HBV-specific mechanism. A therapy targeting these growth factors in hepatitis B patients may help to prevent the development of HCC. FGF4 and GH were found, for the first time, to be upregulated in HCC, suggesting that these two growth factors may serve as novel serum biomarkers for the early diagnosis of HCC. Conclusion: The combined detection of all the differential growth factors may improve the diagnostic accuracy of HCC.

Background. The aim of this study is to examine whether biomarkers of the immune-inflammatory response (IRS) and endogenous opioid (EOS) systems are associated with affective symptoms in schizophrenia. Methods. We recruited 115 schizophrenia patients and 43 healthy controls and assessed the Hamilton Depression (HDRS) and Anxiety (HAM-A) rating Scale scores as well as serum levels of interleukin (IL)-6, IL-10, eotaxin (CCL11), high mobility group box 1 (HMGB1), Dickkopf-related protein 1 (DKK1), and mu (MOR) and kappa (KOR) opioid receptors.Results. The HDRS and HAM-A scores are significantly and positively correlated with a) psychosis, hostility, excitation, mannerism, negative symptoms, psychomotor retardation, and formal thought disorders; and b) lowered scores on semantic and episodic memory, executive functions, and attention tests as measured with the Brief Assessment of Cognition in Psychiatry. Both HDRS and HAM-A are significantly increased in non-responders to treatment as compared with partial responders. Both affective scores are strongly associated with latent vectors extracted from all symptoms, reflecting overall severity of psychosis (OSOS), and neurocognitive test scores, reflecting a generalized cognitive decline (G-CoDe). The HDRS score was strongly and positively associated with IL-6, HMGB1, KOR, and MOR levels, and the HAM-A score with IL-6, IL-10, CCL11, HMGB1, KOR, and MOR levels. A single latent trait may be extracted from OSOS, G-CoDe, and the HDRS and HAMA scores, and this latent vector score is strongly predicted by HMGB1, MOR, and DKK1.Conclusion. Immune-inflammatory and EOS pathways contribute to the phenome of schizophrenia, which comprises OSOS, affective, and physiosomatic symptoms, and G-CoDe.

Purpose: To investigate the alterations in nitro-oxidative stress (OS) and antioxidant status in adolescents with metabolic syndrome (MetS) and whether these alterations occur independently from effects of overweight or obesity.Methods: Blood was collected in 47 adolescents with MetS and 94 adolescents without MetS as assessed with the International Diabetes Federation criteria. The International Obesity Task Force (IOTF) criteria were used to classify the subjects into those with overweight or obesity. We measured nitro-oxidative biomarkers including nitric oxide metabolites (NOx), lipid hydroperoxides (LOOH), and malondialdehyde (MDA), and antioxidant biomarkers, i.e. total radical-trapping antioxidant parameter (TRAP), paraoxonase (PON)-1 activity, thiol (SH-) groups, as well as tumor necrosis factor-α, glucose, insulin, triglycerides, uric acid and high-density lipoprotein cholesterol (HDL-C).Results: Logistic regression analysis showed that increased MDA and NOx and a lowered TRAP/uric acid ratio were associated with MetS. Machine learning including soft independent modeling of class analogy (SIMCA) showed that the top-3 most important features of MetS were increased glucose and MDA and lowered HDL-C. Support vector machine using MDA, glucose, insulin, HDL-C, triglycerides and body mass index as input variables yielded a 10-fold cross-validated accuracy of 89.8% when discriminating MetS from controls. The association between MetS and increased MDA was independent from the effects of overweight-obesity. glucose, insulin, triglycerides and HDL-C.Conclusion: In adolescents, increased MDA formation is a key component of MetS, indicating that increased production of reactive oxygen species with consequent lipid peroxidation and aldehyde formation participate in the development of MetS.

Measurements of copper and zinc in transfusion-dependent thalassemia (TDT) show contradictory results.Aim of the study: To examine serum levels of these minerals in TDT in relation to iron overload indices and erythron variables. Methods: This study recruited 60 children with TDT and 30 healthy children aged 3-12 years old.Results: Zinc was significantly higher in TDT children than in control children, whilst copper and the copper to zinc ratio were significantly lowered in TDT. Serum zinc was significantly associated with the number of blood transfusions and iron overload variables (including serum iron and TS%) and negatively with erythron variables (including hemoglobin, mean corpuscular volume, mean corpuscular hemoglobin). Serum copper was significantly and negatively associated with the same iron overload and erythron variables. The copper to zinc ratio was significantly correlated with iron, TS%, ferritin, hemoglobin, mean corpuscular volume, and mean corpuscular hemoglobin. Albumin levels were significantly higher in TDT children than in control children. Conclusion: Our results suggest that the increase in zinc in children with TDT may be explained by iron loading anemia and hemolysis and the consequent shedding of high amounts of intracellular zinc into the plasma. Increased albumin levels and treatment with Desferral may further contribute towards higher zinc levels in TDT. We suggest that the elevations in zinc in TDT are a compensatory mechanism protecting against infection, inflammation, and oxidative stress. Previous proposals for prophylactic use of zinc supplements in TDT may not be warranted.

The progression of the recent COVID-19 pandemic surprised political authorities as well as scientists. The possibility to design powerful strategies for health care and preserving economic and social activities strongly relies on the capacity to monitor correctly the virus spreading and the immune response in the symptomatic and asymptomatic population. The available data relative to the first pandemic months indicate that the test reliability was progressively improved but also that the extremely variable methodologies used in the diagnostic studies generated data that are often not comparable. This condition prevents a simple metadata analysis for the identification of reliable diagnostics guidelines. Nevertheless, there are converging evidences that combinations of complementary approaches may enable more precise identification of virus infection. Furthermore, it appears that the similarities between SARS-CoV2 and the related types SARS-CoV1 and MERS that caused outbreaks in the last 20 years can be exploited to infer some information for which no direct evidence is still available

Background: Physiosomatic symptoms are an important part of schizophrenia phenomenology. The aim of this study is to examine the biomarker, neurocognitive and symptomatic correlates of physiosomatic symptoms in schizophrenia. Methods: We recruited 115 schizophrenia patients and 43 healthy controls and measured the Fibromyalgia and Chronic Fatigue Syndrome Rating (FF) scale, schizophrenia symptom dimensions, and the Brief Assessment of Cognition in Schizophrenia. We measured neuro-immune markers including plasma CCL11 (eotaxin), interleukin-(IL)-6, IL-10, Dickkopf protein 1 (DKK1), high mobility group box 1 protein (HMGB1) and endogenous opioid system (EOS) markers including κ-opioid receptor (KOR), µ-opioid receptor (MOR), endomorphin-2 (EM2) and β-endorphin. Results: Patients with an increased FF score display increased ratings of psychosis, hostility, excitement, formal though disorders, psychomotor retardation and negative symptoms as compared with patients with lower FF scores. A large part of the variance in the FF score (55.1%) is explained by the regression on digit sequencing task, token motor task, list learning, IL-10, age (all inversely) and IL-6 (positively). Neural network analysis shows that the top-6 predictors of the FF score are (in descending order): IL-6, HMGB1, education, MOR, KOR and IL-10. We found that 45.1% of the variance in a latent vector extracted from cognitive test scores, schizophrenia symptoms and the FF score was explained by HMGB-1, MOR, EM2, DKK1, and CCL11. Conclusions: FF symptoms are an integral part of the phenome of schizophrenia. Neurotoxic immune and neurodegenerative pathways and to a lesser extent the EOS appear to drive FF symptoms in schizophrenia.

In the modern world, the problem of antibiotic therapy is acute. Despite the diversity of existing antibiotic drugs, their efficacy decreases as new, resistant forms of pathogenic microorganisms emerge. It is extremely difficult to control such processes and even more difficult to treat severe bacterial infections. In such situations, an individual approach to each patient is required and physicians need parameters to estimate the efficacy of antibiotic therapy. This review discusses the significance of monitoring the content of antibiotics in the blood for this purpose, in combination with the content of inflammatory markers, such as C-reactive protein and procalcitonin. The basic principles of antibiotic therapy, and factors in the resistance of microorganisms to antibiotics, are examined. Approaches to assess the efficacy of antibiotic therapy, as well as methods to detect antibiotics and inflammatory markers in the blood of patients, and comparative assessment of their capabilities and limitations, are described.

Background and Objectives: Knee osteoarthritis (KOA) is a degenerative disease that is targeting continuously people of different ages, but especially the elderly population, the number of which tends to increase continuously at the global level. Apart from age, excess weight can influence the evolution of the disease, with obesity being associated with a weak inflammation stage, and an imbalance between pro-inflammatory and anti-inflammatory cytokines. The present work aimed to identify specific biomarkers alike ACRP-30, IL-10, TNF-α, and IL-6 in synovial fluid and correlate them with patients’ clinical data. Materials and Methods: 24 subjects with KOA and over 50 years of age are involved in the present study. All patients performed a supine X-ray at the target knee. Ultrasound was performed using an ESAOTE MyLab Omega (ESAOTE Spa, Italy) ultrasound device and a 6-19 MHz linear array transducer. Results: The obtained results highlighted a significant correlation between age and adiponectin level (p=0.0451, r=-0.412). Also, the IL-10 values are lower in cases where the intensity of the pain is more pronounced (p=0.0405, r=-0.421). In addition, analyzing the data by gender, it was observed that in the case of males, stiffness is more related to age (p=0.0079, r=0.7993), compared to women (p=0.0203, r=0.6223). In the case of women, the progression of the disease tends to increase more intensively total WOMAC score’s values (p=0.00031, r=0.8342), compared with men (p=0.0289, r=7013). Regarding interleukins and BMI, significant correlations were observed only in the case of men. Conclusions: A significant correlation between age and adiponectin, and adiponectin and IL-6, suggests that advanced age may contribute to adiponectin reduction. Comparing men with women, it was observed that men's age is more related to rigidity, and IL-6 and IL-10 are directly correlated to BMI and women seem to be more sensitive to pain and stiffness.

SARS-CoV-2 is the Coronavirus responsible for the COVID-19 pandemic. Even though we are no more in a pandemic situation, people are getting infected some of them needing hospitalization, and a few of them die. Methods: We did a retrospective study including 445 patients who accessed the Emergency Section of Policlinico Umberto I, Rome, Italy, where they had routine blood exams. In this study, we concentrated on the complete blood count, creatinine, and azotemia. The data was analyzed using ANOVA, Spearman correlation, and ROC analysis. They were divided into four groups based on their outcome: (1) the emergency group (patients with mild forms who were quickly discharged); (2) the hospital ward group (patients who after admission to the emergency section were hospitalized in a COVID-19 ward); (3) the intensive care unit (ICU) group (patients that after the admission in the emergency section required intensive assistance); (4) the deceased group (patients that after the admission in the emergency section had a fatal outcome). Results: We found significant changes for creatinine, azotemia, hematocrit, mean corpuscular hemoglobin concentration, basophils, monocytes, red blood cell distribution width, hemoglobin, hematocrit, and red blood cell numbers by ANOVA according to their outcomes, particularly for the deceased group. Also, we found outcome correlations for eosinophils, hemoglobin, hematocrit, mean corpuscular hemoglobin concentration, lymphocyte, neutrophil, platelet, and red blood cell number and red blood cell distribution width. Conclusions: This study discloses an association between “classical” routine blood biomarkers and the severity of outcomes in Omicron patients.

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.

Cancer, a globally prevalent and often deadly disease, holds promise for improved treatment through the integration of innovative medical technologies and interdisciplinary collaborations. Despite advancements, current cancer therapies lack a specific focus on addressing recurrence and targeting cancer stem cells (CSCs), known contributors to relapse. In this study, we utilized three types of cancer cells and generated three types of CSCs derived from them to conduct proteomic analysis and identified shared cell surface biomarkers as potential targets for a comprehensive treatment strategy. The selected biomarkers underwent evaluation through shRNA treatment, revealing contrasting functions in cancer and CSCs. Knocking down the identified protein showed promising results in regulating epithelial-mesenchymal transition (EMT) and stemness via the ERK signaling pathway. This led to a reduction in resistance to anticancer agents, ultimately enhancing the overall anticancer effects. Additionally, the biomarker's significance in clinical patient outcomes was confirmed using bioinformatics. Our study suggests a novel cancer treatment strategy that addresses existing limitations in current anticancer therapies.

Prostate cancer (PC) is a common malignancy of elderly men, characterized by great heterogeneity in its clinical course, ranging from an indolent to a highly aggressive disease. The aggressive variant prostate cancer (AVPC) clinically shows an atypical pattern of disease progression, similar to that of small cell PC (SCPC), and also shares the chemo-responsiveness of SCPC. The term AVPC does not describe a specific histologic subtype of PC but rather the group of tumors that, irrespective of morphology, show an aggressive clinical course, dictated by androgen receptor (AR) indifference. AR indifference represents an adaptive response to androgen deprivation therapy (ADT), driven by epithelial plasticity, an inherent ability of tumor cells to adapt to their environment by changing their phenotypic characteristics in a bi-directional way. The molecular profile of AVPC entails combined alterations in tumor suppressor genes retinoblastoma protein 1 (RB1), tumor protein 53 (TP53) and phosphatase and tensin homolog (PTEN). The understanding of the biologic heterogeneity of castration-resistant PC (CRPC) and the need to identify the subset of patients that would potentially benefit from specific therapies necessitate the development of prognostic and predictive biomarkers. This review aims to discuss the possible pathophysiologic mechanisms of AVPC development and the potential use of emerging tissue-based biomarkers in clinical practice.

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.

: Inflammation may mediate the association of mitral valve prolapse (MVP) with ventricular scarring and arrhythmia. The purpose of this study is to investigate the association of neutrophil- and platelet-to-lymphocyte ratios (NLR, PLR) with ventricular arrhythmia in MVP. Clinical and demographic data were extracted from electronic medical records for all patients aged 18-90 years with MVP on echocardiography between 2016-19 at our institution. We studied 65 patients who had a differential blood count within six months prior to ambulatory ECG (A- ECG) (medi-an age [IQR] 70 [61-77] years; 62% female; 12% African American). Patients with surgery or in-fection within six months prior to CBC were excluded. Complex or frequent ventricular ectopy (cfVE) was defined as the presence of two or more premature ventricular contractions (PVCs) on a 10-second ECG tracing or greater than 1% PVC burden or NSVT on ambulatory ECG monitoring. Logistic and bivariate regression was used to analyze clinical, electrocardiographic and echo-cardiographic factors associated with NLR and PLR. Factors associated with higher NLR were congestive heart failure (p=0.005), male sex (p=0.01), age (p=0.003), and bileaflet MVP (p=0.04). NLR was associated with higher absolute PVC burden (rs=0.28, p=0.03) and cfVE (median NLR [IQR] 3.0 [1.6 – 6.3]) with cfVE versus (2.4 [1.4-3.4], p=0.04) without cfVE. An NLR of 5.6 yielded 50% sensitivity and 90% specificity for PVC burden >1% (AUC 0.69). No significant association was found between PLR and PVC burden or cfVE. NLR is associated with PVC burden and com-plex ventricular ectopy in MVP, suggesting that inflammation is a significant factor in the patho-genesis of ventricular arrhythmia in this condition.

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.

Abatacept (CTLA4-Ig) – a monoclonal antibody which restricts T cell activation – is an effective treatment for rheumatoid arthritis (RA). Herein, we aimed to investigate for biomarkers of response to abatacept. We performed a detailed immunological profiling of CTLA4-treated RA patients’ peripheral blood (PB) cells and sera using flow cytometry and proteomics analysis, respectively. At 6 months of treatment, 34.5% of patients attained clinical response. Notably, baseline levels of Th1 and myeloid cell populations were significantly elevated in PB of responders compared to non-responders (P-value<0.05). Additionally, proteomics analysis revealed 10 amongst 303 molecules which were associated with clinical responses. Should the present data be confirmed in a larger cohort could be of clinical value.

This narrative review aims to clarify the role of tertiary lymphoid structures in breast cancer. We examine their development, composition, prognostic value and current ways of recognising them. A comprehensive literature review was performed using PubMed/Medline, Scopus and EMBASE databases. A significant area of interest in breast cancer research involves targeting immune checkpoint molecules, particularly in the triple-negative subtype, where treatment options remain limited. However, existing biomarkers have limitations in accurately predicting treatment response.  In this context, tertiary lymphoid structures (TLS) emerge as a prognostic biomarker and also as a promising predictive marker for response. TLS are ectopic lymphoid formations or neo-organogenesis that can develop after prolonged exposure to inflammatory signals mediated by chemokines and cytokines. Their presence is inversely correlated with estrogen receptor (ER) and/or progesterone receptor (PR) expression, but positively associated with a higher pathologic complete response rate and improved overall  survival. In certain scenarios, TLS-positive tumors were associated with improved outcomes regardless of the presence of PDL-1 (programmed cell death ligand 1) expression or and TILs (tumor-infiltrating lymphocytes).

Ustekinumab, a new anti-interleukin-12/23 antibody, is an effective treatment for ulcerative colitis; however, data regarding predictive factors of its efficacy are limited. This study aimed to identify biomarkers that can predict the long-term outcome of ustekinumab treatment. We retrospectively reviewed the records of patients with active ulcerative colitis treated with ustekinumab at our hospital from June 2020 to January 2023. We divided patients into non-remission and remission groups, and examined whether baseline biomarkers, including C-reactive protein-to-lymphocyte ratio, and early treatment response could predict clinical remission at week 48 of ustekinumab treatment. Of the 33 patients included in the study, 21 (63.6%) were in clinical remission at week 48 of ustekinumab treatment. The baseline C-reactive protein-to-lymphocyte ratio value was identified as an independent prognostic factor for clinical remission at week 48 (odds ratio: 10, 95% confidence interval: 1.6–62.4, p=0.014), with the cutoff value of 3.353 showing excellent prognostic performance (sensitivity: 71.4%, specificity: 83.3%). Furthermore, the clinical response at week 4 (p=0.009) and that at week 8 (p=0.005) were significantly associated with clinical remission at week 48. The baseline C-reactive protein-to-lymphocyte ratio value and early treatment response are useful biomarkers to predict the long-term efficacy of ustekinumab treatment.

The SARS-CoV-2 infection is a cause of hypoxemic acute respiratory failure, leading to frequent intensive care unit (ICU) admission. Due to invasive organ support and immunosuppressive therapies, these patients are prone to nosocomial infections. Our aim was to assess the value of daily measurements of C-reactive protein (CRP) and Procalcitonin (PCT) in the early identification of ICU-acquired infections in COVID-19 patients Methods: We undertook a prospective observational cohort study (12 months). All adult me-chanically-ventilated patients admitted for ≥ 72 hours to the ICU with COVID-19 pneumonia were divided into an infected group (n=35) and a non-infected group (n=83). Day 0 was considered as the day of the diagnosis of infection (infected group) and day 10 of ICU stay (non-infected group). The kinetics of CRP and PCT were assessed from day -10 to day 10 and evaluated using a general linear model, univariate, repeated-measures analysis. Results: 118 patients (mean age 63 years, 74% males) were eligible for the analysis. The groups did not differ in patients' age, gender, CRP, and PCT serum levels at ICU admission. However, the infected group encompassed patients with a higher severity (SOFA score at ICU admission, p=0.009) and a higher 28-day mortality (p<0.001). Before D0, CRP kinetics showed a significant increase in infected patients, whereas in noninfected it remained almost unchanged (p<0.001), while PCT kinetics did not appear to retain diagnostic value to predict superinfection in COVID-19 patients (p=0.593). Conclusion: COVID-19 patients who develop ICU-acquired infections exhibited different biomarker kinetics before the diagnosis of those infections. Daily CRP monitoring and the recognition of the CRP kinetics could be useful in the prediction of ICU-acquired infections.

In order to provide a new direction for the diagnosis and treatment of gastric cancer, the differentially expressed blood-based miRNAs in gastric carcinoma were obtained and analyzed from the datasets GSE113486, GSE112264 and GSE113740 by the SangerBox, the miRNA - target genes prediction, GO and KEGG functional enrichment analyses with DAVID 6.8, and the STRING database with Cytoscape, respectively. The correlation between the key miRNAs expression and the prognosis and diagnostic value of gastric cancer patients were detected by survival prognosis and ROC curve. QRT-PCR was used to detect the possible key miRNAs expression in human blood species. The dataset GSE108307 which shows the miRNAs affected by H. pylori infection was analyzed by GEO2R. The expression level of CagA and the clinically used gastric cancer markers were detected in human blood species for contrast. Five key blood-based miRNAs were determined, including hsa-miR-124-3p, hsa-miR-125a-3p, hsa-miR-29b-3p, hsa-miR-4276, and hsa-miR-575.The detection in human blood species as well as the cross analysis with H. pylori infection and clinically used markers expression suggested the importance and efficacy of the specific miRNAs in the early diagnosis and monitoring of gastric carcinoma. The study identified potential novel blood miRNA biomarkers of gastric cancer by bioinformatics and human blood species detection, which may give a new possibility of the important biomarkers for the diagnosis and prognosis of gastric cancer.

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.

It has been previously shown that aldehyde dehydrogenase (ALDH) family member ALDH1A1 has a significant association with acute myeloid leukemia (AML) patient risk group classification, and that AML cells lacking ALDH1A1 expression can be readily killed by chemotherapy. In the past, however, a redundancy between the activities of subgroup members of the ALDH family has hampered conclusive evidence for addressing the role of specific ALDH genes. We here describe the bioinformatics evaluation of all nineteen member genes of the ALDH family as prospective actionable targets for the development of methods aimed to improve AML treatment. We implicate ALDH1A1 in the development of recurrent AML, and we show that from the nineteen members of the ALDH family, ALDH1A1 and ALDH2 have the strongest association with AML patient risk group classification. Furthermore, we discover that the sum of the expression values for RNA from the genes ALDH1A1 and ALDH2 has a stronger association with AML patient risk group classification and survival than either one gene alone. In conclusion, we identify ALDH1A1 and ALDH2 as prospective actionable targets for the treatment of AML in high risk patients. Substances that inhibit both enzymatic activities can constitute potentially effective pharmaceutics.

Male infertility (MI) involves various endogenous and exogenous facts. These include oxidative stress (OS), which is known to alter several physiological pathways and it is estimated to be present at high levels in up to 80 % of infertile men. That is why since the late 20th Century, the relationship between OS and MI has been widely studied. New terms have emerged, such as Male Oxidative Stress Infertility (MOSI), which is proposed as a new category to define infertile men with high OS levels. Another important term is MOXI: Male, Antioxidants, and Infertility. Such term refers to the hypothesis that antioxidants could improve male fertility without the use of assisted reproductive technology. However, there is no evidence-based antioxidant treatments that directly improve seminal parameters or birth ratio. In this regard, there is controversy about their use. While certain scientists argue against their use due to the lack of results, others support this use because of their safety profile and low price. Some uncertainties related to the use of antioxidants for treating MI are their questionable efficacy or the difficulties to know their correct dosage. In addition, the lack of quality methods for OS detection can lead to an excessive antioxidant supplementation, resulting in “reductive stress”. Another important problem is that, although the inflammatory process is interdependent and closely linked to OS, it is usually ignored. To solve these uncertainties, new trends have recently emerged. These include the use of molecules with anti-inflammatory and antioxidant potential, and which are also able to specifically target the reproductive tissue; as well as the use of new methods that allow for reliable quantification of OS and a quality diagnosis. This review aims to elucidate the main uncertainties about MOXI and to outline the latest trends in research to achieve effective therapies with clinically relevant outcomes.

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.

Amyotrophic lateral sclerosis (ALS) is a severe and incurable neurodegenerative disease, char-acterized by the progressive death of motor neurons, leading to paralysis and death. It is a rare disease distinguished by high patient-to-patient heterogeneity, making its study arduous and complex. Extracellular vesicles (EVs) emerged as an important player in ALS development. Thus, ALS phenotype-expressing cells can spread their abnormal bioactive cargos through the secretion of EVs, even at far distant tissues. Importantly, due to their nature and composition, EVs’ formation and cargo can be exploited for the better comprehension of this elusive disease and identification of novel biomarkers, as well as for potential therapeutic applications, such as those based on stem cell-derived exosomes. This review highlights the recent advances in the identification of the role of EVs in ALS etiopathology and how EVs can be promising new approaches for therapeutic strategies.

Long non-coding RNAs (LncRNAs) are mRNA-like molecules that do not encode for proteins and that are longer than 200 nucleotides. LncRNAs play important biological roles in normal cell physiology and organism development. Therefore, deregulation of their activities is involved in disease processes such as cancer. Lung cancer is the leading cause of cancer-related deaths due to late stage at diagnosis, distant metastasis, and high rates of therapeutic failure. LncRNAs are emerging as important molecules in lung cancer for their oncogenic or tumor suppressive functions. LncRNAs are highly stable in circulation, presenting an opportunity for use as non-invasive and early-stage cancer diagnostic tools. Here, we summarize latest works providing in vivo evidence available for LncRNAs role in cancer development, therapy-induced resistance, and their potential as biomarkers for diagnosis and prognosis, with a focus on lung cancer. Additionally, we discuss current therapeutic approaches to target LncRNAs. The evidence discussed here strongly suggests that investigation of LncRNAs in lung cancer in addition to protein-coding genes will provide a holistic view of molecular mechanisms of cancer initiation, development, and progression, and could open a new avenue for cancer treatment.

Abstract: Advanced high-grade serous ovarian carcinoma is a serious malignant neoplasm with a late diagnosis and high mortality rate. Even when treated with standard therapy, such as surgery followed by carboplatin and paclitaxel chemotherapy, the prognosis remains unfavorable. Im-munotherapy is a treatment alternative that requires further study. Therefore, we aimed to evaluate the expression of the immunotherapy markers: PD-1, PD-L1, CD8, MSI (MLH1, MSH2, MSH6, and PMS2), and p53 in the paraffin samples of high-grade serous ovarian carcinoma. A retrospective study of 28 southern Brazilian patients with advanced serous ovarian carcinoma (EC III or IV) was conducted between 2009 and 2020. The expression of these proteins was evaluated using im-munohistochemistry, and the results were correlated with the patients' clinicopathological data. At diagnosis, the mean age was 61 years, and the most common clinical stage (60%) was EC III. Among the cases, 84.6% exhibited p53 overexpression, 14.8% had MSI, 92.0% were sensitive to platinum, and more than 50.0% relapsed after treatment. Patients with MSI had a lower CD8/PD-1 ratio and more relapses (p=0.03). In conclusion, analysis of immunotherapeutic markers in paraf-fin-embedded samples of advanced serous ovarian carcinoma is feasible and may assist in prog-nosis.

Surgeons are increasingly faced with a challenging, ageing and frail patient population. A significant absence of biomarkers to stratify outcomes of patients undergoing emergency laparotomy exists. Inflammageing describes a state of chronic inflammation associated with ageing and frailty and may predict worse outcomes. This retrospective observational study evaluated pre-morbid inflammatory markers in the prognostication of elderly patients undergoing emergency laparotomy. Patients aged ≥65 years undergoing surgery between 01/04/2017 – 01/04/2022 were identified. Pre-admission and acute C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), total white cell count (WCC), neutrophil count (NC) and lymphocyte count (LC) data points were captured. Pre-operative risk stratification scores and postoperative outcomes were recorded using the National Emergency Laparotomy Audit (NELA) database. A cohort of 196 patients was included: 57.7% were female, median age of 74.5 years. High-risk (NELA risk of mortality ≥5%) and frail (clinical frailty scale ≥4) patients experienced a significantly longer hospital and critical care stay (p<0.05). Pre-admission ESR ≥16 and LC ≥4.1 were significantly associated with a longer critical care stay (p<0.05), however, no statistical significance was observed with CRP, WCC and NC in predicting adverse outcomes. We found an elevated pre-morbid ESR and LC identifies a potential inflammageing cohort that demonstrate worse outcomes following emergency laparotomy. The prognostication of elderly surgical patients remains a challenge and represents an area of research deserving of future attention.

Viral infections cause metabolic dysregulation in the infected organism. The present study used metabolomics techniques and machine learning algorithms to retrospectively analyze the alter-ations of a broad panel of metabolites in the serum and urine of a cohort of 126 patients hospi-talized with COVID-19. Results were compared with those of 50 healthy subjects and 45 COVID-19 negative patients but with bacterial infectious diseases. Metabolites were analyzed by gas chro-matography coupled to quadrupole time-of-flight mass spectrometry. The main metabolites al-tered in the sera of COVID-19 patients were those of pentose glucuronate interconversion, ascorbate and fructose metabolism, nucleotide sugars, and nucleotide and amino acid metabolism. Alterations in serum maltose, mannonic acid, xylitol, or glyceric acid metabolites segregated positive patients from the control group with high diagnostic accuracy, while succinic acid seg-regated positive patients from those with other disparate infectious diseases. Increased lauric acid concentrations were associated with severity of infection and death. Urine analyses could not discriminate between groups. Targeted metabolomics and machine learning algorithms facilitated the exploration of the metabolic alterations underlying COVID-19 infection, and to identify po-tential biomarkers for the diagnosis and prognosis of the disease.

Alzheimer’s disease is the most common neurodegenerative disease and affects persons of all races, ethnic groups, and sexes. The disease is characterized by neuronal loss leading to cognitive decline and memory loss. There is no cure and the effectiveness of existing treatments is limited and depends on the time of diagnosis. The long prodromal period, during which patients’ ability to live a normal life is not affected despite neuronal loss, often leads to a delayed diagnosis because it can be mistaken for normal aging of the brain. In order to make a substantial impact on AD patients, early diagnosis may provide a greater therapeutic window for future therapies to slow AD-associated neurodegeneration. Current gold standards for disease detection include magnetic resonance imaging and positron emission tomography scans, which visualize amyloid β and phosphorylated tau depositions and aggregates. Liquid biopsies, already an active field of research in precision oncology, are hypothesized to provide early disease detection through minimally or non-invasive sample collection techniques. Liquid biopsies in Alzheimer’s disease have been studied in cerebrospinal fluid, blood, ocular, oral, and olfactory fluids. However, most of the focus has been on blood and cerebrospinal fluid due to biomarker specificity and sensitivity attributed to the effects of the blood-brain barrier and inter-laboratory variation during sample collection. Many studies have identified amyloid β and phosphorylated tau levels as putative biomarkers, however, advances in next-generation sequencing-based liquid biopsy methods have led to significant interest in identifying nucleic acids species associated with Alzheimer’s disease from liquid tissues. Differences in cell-free RNAs and DNAs have been described as potential biomarkers for AD and hold the potential to affect disease diagnosis, treatment, and future research avenues.

Glioblastoma (GBM) is a very aggressive malignant brain tumor with the vast majority of patients surviving less than 12 months (Short-term survivors [STS]). Only around 2% of patients survive more than 36 months (Long-term survivors [LTS]). Studying these extreme survival groups might help in better understanding GBM biology. This work aims at exploring application of machine learning methods in predicting survival groups(STS, LTS). We used age and gene expression profiles belonging to 249 samples from publicly available datasets. 10 Machine learning methods have been implemented and compared for their performances. Hyperparameter tuned random forest model performed best with accuracy of 80% (AUC of 74% and F1_score of 85%). The performance of this model is validated on external test data of 16 samples. The model predicted the true survival group for 15 samples achieving an accuracy of 93.75%. This classification model is deployed as a web tool GlioSurvML. The top 1500 features which retained classification efficiency (Accuracy of 80%, AUC of 74%) were studied for enriched pathways and disease-causal biomarker associations using the HumanPSD^TM database. We identified 199 genes as possible biomarkers of GBM and/or similar diseases (like Glioma, astrocytoma, and others). 57 of these genes are shown to be differentially expressed across survival groups and/or have impact on survival. This work demonstrates the application of machine learning methods in predicting survival groups of GBM.

This single-blind and cross-sectional study evaluated the role of Rho-kinase (ROCK) as a biomarker of the cardiovascular remodelling process assessed by echocardiography in competitive long-distance runners (LDR) during the training period before a marathon race. Thirty-six healthy male LDR (37.0±5.3 years; 174.0±7.0 height; BMI: 23.8±2.8; VO2-peak: 56.5±7.3 mL·kg-1·min-1) were separated into two groups according to previous training level: high-training (HT, n=16) ≥100 km·week-1 and low-training (LT, n=20) ≥70 and &lt;100 km·week-1. Also, twenty-one healthy nonactive subjects were included as a control group (CTR). A transthoracic echocardiography was performed and ROCK activity levels in circulating leukocytes were measured at rest (48-hr without exercising) the week before the race. HT group showed higher left ventricular mass index (LVMi) and left atrial volume index (LAVi) than other groups (p&lt;0.05, for both), also higher levels of ROCK activity were found in LDR (HT=6.17±1.41 vs CTR=1.64±0.66 (p&lt;0.01); vs LT=2.74±0.84; (p&lt;0.05)). In LDR a direct correlation between ROCK activity levels and LVMi (r=0.83; p&lt;0.001), and LAVi (r=0.70; p&lt;0.001) were found. In conclusion, in male competitive long-distance runners, the load of exercise implicated in marathon training is associated with ROCK activity levels and the left cardiac remodelling process assessed by echocardiography.

Background. COVID-19 patients suffer from hypercoagulation and activated immune-inflammatory pathways. This study was performed to assay serum complement C3 and C4, and thromboxane A2 (TxA2) and prostacyclin (PGI2) in association with chest CT scan anomalies (CCTAs) and peripheral oxygen saturation (SpO2) Methods. Serum levels of C3, C4, TxA2, and PGI2 were measured by ELISA and albumin, calcium, and magnesium by spectrophotometric method in 60 COVID-19 patients and 30 controls. Results. C3 and C4 are significantly decreased and TxA2 and PGI2 significantly increased in COVID-19 patients as compared with controls. Neural networks showed that a combination of C3, albumin, and TxA2 yielded a predictive accuracy of 100% in detecting COVID-19 patients. SpO2 was significantly decreased in COVID-19 patients and was inversely associated with TxA2 and PGI2, and positively with C3, C4, albumin, and calcium. CCTAs were accompanied by lower SpO2 and albumin, and increased PGI2 levels. Patients with positive IgG results show significantly higher SpO2, TxA2, PGI2, and C4 levels than IgG negative patients. Conclusion. Hypoalbuminemia, which is strongly associated with lung lesions and lowered peripheral oxygen saturation, is characterized by increased TxA2, suggesting that interactions between immune-inflammatory pathways and platelet hyperactivity participate in the pathophysiology of COVID-19 and consequently may play a role in enhanced risk of hypercoagulability and venous thromboembolism. These mechanisms are aggravated by lowered calcium and magnesium levels.

Cervical cancer (CC) is the most common cancer in women worldwide and is almost always associated with repeated infections by human papillomavirus (HPV). Screening by traditional tests combined with biomarker identification techniques for low- or high-grade injuries, are becoming increasingly important in diagnosis and prognosis, avoiding countless deaths. This article explores existing literature on the main serum biomarkers and the identification of biomarkers associated with the oncogenesis of HPV expression in the identification of pre-cancerous lesions and of CC for an effective treatment, with reduction of recurrence, as well as we explain strategies for the development of biomarkers based on DNA, proteins and other markers. We also describe how markers of chromosomal instability host DNA, promoting hypo- or hypermethylation of DNA, as well as polymorphisms and epigenetic events in the p53 gene. Finally, we discuss changes in gene expression using cDNA microarray techniques and changes in the expression of proteins and markers identified through mass spectrometry.

Prostate cancer (Pca) is a highly heterogeneous disease and the second more common tumor in males. Molecular and genetic profiles have been used to identify subtypes and guide therapeutic intervention. However, roughly 26% of primary Pca are driven by unknown molecular lesions. We use Principal Component Analysis (PCA) and custom RNAseq-data normalization to identify a gene expression signature which segregates primary PRAD from normal tissues. This Core-Expression Signature (PRAD-CES) includes 33 genes and accounts for 39% of data complexity along the PC1-cancer axis. The PRAD-CES is populated by protein-coding (AMACR, TP63, HPN) and RNA-genes (PCA3, ARLN1) sparsely found in previous studies, validated/predicted biomarkers (HOXC6, TDRD1, DLX1), and/or cancer drivers (PCA3, ARLN1, PCAT-14). Of note, the PRAD-CES also comprises six over-expressed LncRNAs without previous Pca association, four of them potentially modulating driver’s genes TMPRSS2, PRUNE2 and AMACR. Overall, our PCA capture 57% of data complexity within PC1-3. GO enrichment and correlation analysis involving major clinical features (i.e., Gleason Score, AR Score, TMPRSS2-ERG fusion and Tumor Cellularity) suggest that PC2 and PC3 gene signatures might describe more aggressive and inflammation-prone transitional forms of PRAD. Of note, surfaced genes may entail novel prognostic biomarkers and molecular alterations to intervene. Particularly, our work uncovered RNA genes with appealing implications on Pca biology and progression.

Adjuvant chemotherapy is currently used in all patients with resected pancreatic cancer who are able to begin treatment within 3 months after surgery. Since the recent publication of the PRODIGE 24 trial results, modified FOLFIRINOX has become the standard-of-care in the non-Asian population with localized pancreatic adenocarcinoma following surgery. Nevertheless, there is still a risk of toxicity, and feasibility may be limited in heavily pre-treated patients. In more frail patients, gemcitabine-based chemotherapy remains a suitable option, for example gemcitabine or 5FU in monotherapy. In Asia, although S1-based chemotherapy is the standard of care it is not readily available outside Asia and data are lacking in non-Asiatic patients. In patients in whom resection is not initially possible, intensified schemes such as FOLFIRINOX or Gemcitabine-Nabpaclitaxel have been confirmed as options to enhance the response rate and resectability, promoting research in adjuvant therapy. In particular, should oncologists prescribe adjuvant treatment after a long sequence of chemotherapy +/- chemoradiotherapy and surgery? Should oncologists consider the response rate, the R0 resection rate alone, or the initial chemotherapy regimen? And finally, should they take into consideration the duration of the entire sequence, or the presence of limited toxicities of induction treatment? The aim of this review is to summarize adjuvant management of resected pancreatic cancer and to raise current and future concerns, especially the need for biomarkers and the best holistic care for patients.

Atopic dermatitis (AD) is a protease-modulated chronic disorder with heterogenous clinical manifestations which may lead to an imprecise diagnosis. So far, there are no diagnostic protease tests for AD. We explored the gingival crevicular fluid (GCF) protease profile of periodontally-healthy individuals with moderate/severe AD compared to healthy controls. An exploratory case-control study was conducted. Matching AD patients (n=6) and controls (n=6) were enrolled at the International Center for Clinical Studies, Santiago, Chile. Complete dermatological and periodontal evaluations (involving the collection of GCF samples) were made. The levels of 35 proteases were analyzed using a human protease antibody array. The GCF levels of zinc-binding ADAM8, ADAM9, MMP8 and Neprilysin/CD10, aspartyl-binding Cathepsin E, and serin-binding Protein convertase9 and uPA/Urokinase proteases were lower in moderate/severe AD patients compared to controls (p<0.05). No inter-group differences in the levels of the other 28 proteases were found. MMP8, Cathepsin E and ADAM9 were the biomarkers with the highest sensitivity and specificity regarding the detection of AD (p < 0.05). The area under receiver operating characteristic (ROC) curve for MMP-8+ADAMP-9 was 0.90. In conclusion, differences in the protease profile between AD and control patients associated with MMP8, Cathepsin E and ADAM9. MMP8, ADAM9 and Cathepsin E may be useful as combined diagnostic and therapeutic biomarkers of moderate/severe AD.

Transfusion dependent thalassemia (TDT) patients are treated with continued blood transfusions and show a higher prevalence of depression. TDT with consequent iron overload and inflammation is associated with increased severity of depressive symptoms in TDT children.Aim of the study: To construct a pathway-phenotype which combines iron overload and neuro-immune biomarkers with depressive symptom subdomains in TDT children.Methods: We measured iron status parameters (iron, ferritin, transferrin saturation percentage) and inflammatory (interleukin-1β and tumour necrosis factor-α) biomarkers in TDT (n=111) and healthy (n=53) children and analyzed the results using machine learning.Results: Cluster analysis separated TDT children with depression from those without depression and revealed two depressive subgroups one with low self-esteem and another with increased social-irritability scores. Exploratory factor analysis validated four depressive symptom dimensions as reliable constructs, namely key depressive, physiosomatic, lowered self-esteem and social-irritability dimensions. Partial Least Squares showed that 73.0% of the variance in a latent vector extracted from those four clinical subdomains, immune-inflammatory and iron overload biomarkers was explained by exposure variables including the number of blood transfusions and hospitalizations and use of deferoxamine. The exposure data, iron and immune biomarkers, and symptom subdomains are reflective manifestations of a single latent trait, which shows internal consistency reliability and predictive relevance.Conclusions: The nomological network combining exposure, pathways and behavioral phenome manifestations provides an index of overall severity and disease risk and, therefore, constitutes a new drug target, indicating that iron overload and immune activation should be targeted to treat depression due to TDT.

Introduction: Lowered thiol or sulfhydryl (-SH) groups and glutathione (GSH) metabolism may be associated with prostate cancer (PCa) and benign prostatic hyperplasia (BPH). The main objectives of this study were to systematically review and meta-analyze the evidence on the associations among -SH groups, GSH, GSH peroxidase (GPx), GSH reductase (GR) and GSH transferase (GST) and PCa/BPH. Methods: Four electronic databases were searched for studies that reported -SH and GSH variables in PCa/BPH and healthy controls (HC) and the data were meta-analyzed by calculating Hedges’s g with 95% confidence intervals. Results: Twenty studies were included in this meta-analysis including 800 PCa and 791 BPH patients and 592 HC. Total -SH (g=-1.750, -2.341/-1.159), GPx (g=-0.789, -1.234/-0.344), GSH (g=-2.219, -4.132/-0.305), and the combination of -SH, GPx, and GSH (g=-1.271, -1.271/-0.800) were significantly lower in PCa patients than in HC. -SH (g=-1.752, -3.123/-0.381) and the combination of -SH, GPx, and GSH (g=-0.813, -1.298/-0.327) were significantly lower in BPH patients than in HC. GPx was significantly lower in PCa than in BPH patients (g=-0.455, -0.896/-0.014). Heterogeneity levels were very high, but Egger’s test showed that none of the biomarkers showed significant publication bias. Conclusion: Thiol/GPx antioxidant defenses are significantly attenuated in patients with PCa while patients with BPH occupy an intermediate risk group position between PCa patients and HC. Those results suggest that reduced thiol-related antioxidant mechanisms play a crucial role in prostatic disorders, especially in PCa. Future research should examine whether thiols/GPx antioxidants are associated with the onset of PCa/BHP.

Background: There is now evidence that schizophrenia and deficit schizophrenia are neuro-immune conditions and that oxidative stress toxicity (OSTOX) may play a pathophysiological role. Aims of the study: To compare OSTOX biomarkers and antioxidant (ANTIOX) defenses in deficit versus non-deficit schizophrenia. Methods: We examined lipid hydroperoxides (LOOH), malondialdehyde (MDA), advanced oxidation protein products (AOPP), sulfhydryl (-SH) groups, paraoxonase 1 (PON1) activity and PON1 Q192R genotypes, total radical-trapping antioxidant parameter (TRAP) as well as immune biomarkers in patients with deficit (n=40) and non-deficit (n=40) schizophrenia and healthy controls (n=40). Results: Deficit schizophrenia is characterized by significantly increased levels of AOPP and lowered -SH, and PON1 activity, while no changes in the OSTOX/ANTIOX biomarkers were found in non-deficit schizophrenia. An increased OSTOX/ANTIOX ratio was significantly associated with deficit versus non-deficit schizophrenia (Odds ratio=3.15, p<0.001). Partial least squares analysis showed that 47.6% of the variance in a latent vector extracted from psychosis, excitation, hostility, mannerism, negative symptoms, psychomotor retardation, formal thought disorders, and neurocognitive test scores was explained by LOOH+AOPP, PON1 genotype + activity, CCL11, tumor necrosis factor (TNF)-α, IgA responses to neurotoxic tryptophan catabolites (TRYCATs), whereas -SH groups and IgM responses to MDA showed indirect effects mediated by OSTOX and neuro-immune biomarkers. Discussion: Our findings indicate that with increasing overall severity of schizophrenia, neuro-immune and neuro-oxidative (especially protein oxidation indicating chlorinative stress) toxicities become more prominent and together with lowered antioxidant defenses and impairments in innate immunity-associated resilience against neurotoxic processes shape a distinct nosological entity, namely deficit schizophrenia.

Introduction: Increased oxidative stress, including elevated homocysteine (Hcy) plasma levels, and lowered levels of antioxidants participate in the pathophysiology and progression of chronic kidney disease (CKD). Paraoxonase (PON)1 activity and folic acid are antioxidants which play a role in Hcy metabolism. However, there are no data whether, in CKD, treatment with folic acid improves glomerular filtration rate (GFR) through effects on PON1 activity and Hcy concentrations. Methods: In the current study, we determined PON1 genotypes and activity, Hcy and estimated GFR (eGFR) both before and after treatment with folic acid (5 mg/d) versus no treatment during three consecutive months in 113 outpatients with CKD classified into stages 4, 3b and 3a. Results: PON1 CMPAase and AREase activities were significantly lower in patients allocated to CKD stage 4 as compared with stages 3b and 3a. Treatment with folic acid significantly improved eGFR and increased levels of CMPAase and AREase in patients allocated to classes 4 and 3b, but not 3a. The improvement of eGFR was associated with increased CMPAase and AREase activities, while the latter were associated with increased levels of folic acid. Treatment with folic acid significantly reduced plasma Hcy levels and the Hcy/PON1 activity ratio. The effects of folic acid increasing PON1 activities were not mediated by changes in Hcy. Discussion: Treatment of CKD patients in early/intermediate stages of CKD patients improves oxidative stress by rebalancing the prooxidant (Hcy) / antioxidant (PON1 activities) ratio. Treatment with folic acid significantly improves eGFR and these effects are mediated via increased PON1 activities. Treatment with folic acid in phase G3b and G4 may reduce renal disease progression by enhancing antioxidant defenses.

Objective: To examine the associations between menstruation features and symptoms and hormone-immune-metabolic biomarkers. Methods: Forty-one women completed questionnaires assessing characteristic menstruation symptoms, duration of menstrual cycle and number of pads used/day and completed the Daily Record of Severity of Problems (DRSP) during the consecutive days of their menstrual cycle. Menses-related symptoms (MsRS) were computed from the sum of 10 pre- and post-menses symptoms and the menstruation blood and duration index (MBDI) was computed based on the daily number of pads and duration of menses. We assayed serum levels of various biomarkers at days 7, 14, 21, and 28 of the subjects’ menstrual cycle. Results: MBDI was significantly associated with a) MsRS including low abdominal cramps, and gastro-intestinal (GI) and pain symptoms (positively); b) plasma levels of haptoglobin (Hp), CCL5, insulin growth factor (IGF)-1, and plasminogen activator inhibitor (PAI)1 (all positively); and c) estradiol and paraoxonase (PON)1 arylesterase activity (both inversely). MsRS were significantly predicted by CCL5 and IGF-1 (both positively) and progesterone (inversely). Low-abdominal cramps, and gastro-intestinal and pain symptoms were associated with lower progesterone levels. The MBDI+MsRS score was significantly predicted by the cumulative effects of (in descending order of importance): Hp, IGF-1, PON1 arylesterase, estradiol and PAI. Conclusion: Menstruation-related features including estimated blood loss, duration of menses, cramps, pain and GI symptoms are associated with hormone-immune-metabolic biomarkers, which mechanistically may explain those features. Women with an increased MBDI+MsRS index ≥ 0.666 percentile may be considered to have menstruation-related distress, including dysmenorrhea symptoms.

Objective: A previous study showed that schizophrenia is accompanied by lowered levels of trace/metal elements including cesium. There are no data whether changes in cesium, rubidium and rhenium are associated with activated immune-inflammatory pathways, cognitive impairments, and the symptomatology of schizophrenia. Methods: This study measured cesium, rubidium, and rhenium, cognitive impairments (using the Brief Assessment of Cognition in Schizophrenia) and the cytokines/chemokines interleukin (IL)-1β, tumor necrosis factor (TNF)-α, and CCL11 (eotaxin) in 120 schizophrenia patients and 54 healthy controls. Severity of illness was assessed using the Brief Psychiatric Rating Scale (BPRS), the Scale for the Assessment of Negative Symptoms (SANS), the Fibromyalgia and Chronic Fatigue Syndrome Rating (FF) Scale and the Hamilton Depression Rating Scale (HAM-D). Results: Serum cesium was significantly lower in schizophrenia patients as compared with controls. Serum cesium was significantly and inversely associated with CCL11 and TNF-α, but not IL-1β. Moreover, there were significant inverse associations between serum cesium levels and the BPRS, FF, HAM-D and SANS scores and positive correlations between cesium and neurocognitive probe results including the Tower of London, Symbol Coding, Controlled Word Association, Category Instances, Digit Sequencing Task, and List Learning tests. Conclusion: The results suggest that lowered serum cesium levels may play a role in the pathophysiology of SCZ, specific symptom domains including negative, depressive and fatigue symptoms, neurocognitive impairments (spatial working, episodic and semantic memory and executive functions) and neuro-immune pathways as well.

Exosomes are nano-sized extracellular vesicles excreted by mammalian cells that circulate freely in the bloodstream of living organisms. Exosomes have a lipid bilayer that encloses genetic material used in intracellular communication (e.g., double-stranded DNA, micro-RNAs, and messenger RNA). Recent evidence suggests that dysregulation of this genetic content within exosomes has a major role in tumor progression and in the surrounding microenvironment. Motivated by this discovery, we focused here on using exosomal biomarkers as a diagnostic and prognostic tool for cancer. In this review, we discuss recently discovered exosome-derived proteomic and genetic biomarkers used in cancer diagnosis and prognosis. Although several genetic biomarkers have been validated for their diagnostic values, proteomic biomarkers are still being actively pursued. We discuss both commercial technologies and emerging technologies for exosome isolation and analysis.

The proteomic profile of extracellular vesicles (EVs) has been of increasing interest, particularly in understanding cancer growth, drug resistance, and metastatic behavior. Emerging data suggests that cancer-derived EVs may carry an array of oncogenic cargo, including certain integrin proteins that may, in turn, promote cell detachment, migration, and selection of future metastatic sites. We previously reported a large comparison of secreted vesicle protein cargo across sixty diverse human cancer cell lines. Here, we analyze the distinct integrin profiles of these cancer EVs. We further demonstrate the enrichment of integrin receptors in breast cancer EVs compared to vesicles secreted from benign breast epithelial cells. Total EV integrin levels, including the quantity of integrins α2, αv, β4, and β5 correlate with breast tumor stage. In particular, integrin α2 also largely reflects progenitor cell expression, highlighting the utility of this integrin protein as a potential circulating biomarker of primary tumors. This study provides preliminary evidence of the value of vesicle-associated integrin proteins in cancer diagnosis and prediction of tumor stage. Differential expression of integrins across cancer cells, and selective packaging of integrins into EVs may contribute to further understanding the development and progression of tumor growth and metastasis across a variety of cancer types.

Psychiatric disorders share the same pattern of longitudinal evolution and have courses that tend to be chronic and recurrent. These aspects of chronicity and longitudinal evolution of psychiatric disorders are currently studied under the neuroprogression framework. Interestingly, considering the plasticity of the brain, it is necessary to emphasize the bidirectional nature of neuroprogression. We review evidence highlighting alterations of the brain associated with the longitudinal evolution of psychiatric disorders from the framework of neuroplastic adaptation to pathology. This new framework highlights that substantial plasticity and remodelling may occur beyond the classic neuroprogressive framework, which is characterized only by loss of grey matter volume, decreased brain connectivity, and chronic inflammation. We also integrate the brain economy concept in the neuroplastic adaptation to pathology framework, emphasizing that to preserve its economy, i.e., function, the brain learns how to cope with the disease by adapting its architecture. This approach can disentangle both the specific pathophysiology of psychiatric symptoms and the adaptation to pathology, thus offering a new framework for both diagnosis and treatment.

Early detection of neurological conditions is critical for timely diagnosis and treatment. Identifying cellular-level changes is essential for implementing therapeutic interventions prior to symptomatic disease onset. However, monitoring brain tissue directly through biopsies is invasive and high-risk. Bodily fluids such as blood or cerebrospinal fluid contain information in many forms, including proteins and nucleic acids. Particularly, cell-free DNA (cfDNA) has potential as a versatile neurological biomarker. Yet, our knowledge of cfDNA released by brain tissue and how cfDNA changes in response to deleterious events within the brain is incomplete. Mapping changes in cfDNA to specific cellular events is difficult in vivo, where many tissues contribute to circulating cfDNA. Organoids are tractable systems for examining specific changes consistently in a human background. However, few studies have investigated cfDNA released from organoids. Here, we examined cfDNA isolated from cerebral organoids. We found that cerebral organoids release quantities of cfDNA sufficient for downstream analysis with droplet-digital PCR and whole-genome sequencing. Further, gene ontology analysis of genes aligning with sequenced cfDNA fragments revealed association with terms related to neurodevelopment and autism spectrum disorder. We conclude that cerebral organoids hold promise as tools for the discovery of cfDNA biomarkers related to neurodevelopmental and neurological disorders.

Analysing the human body by direct observation can lead to misinterpretation of underlying trends, whereas in vitro organ models facilitate their understanding. Likewise, in vitro organ models serve as valuable tools for assessing the toxicity of compounds. However, none of the existing models had the features we considered critical for toxicity assessment, so we developed an in vitro liver model for toxicity assessment. We used four different types of primary liver cells: Hepatic sinusoidal endothelial cells, hepatic stellate cells, Kupffer cells and hepatocytes. We cultured them in different combinations of composition and volume of cell medium, hepatocyte proportion of total cells, and addition of extracellular matrix. We added rifampicin, ibuprofen and 5-fluorouracil to this model and observed the microanatomy and physiology changes for a week with preclinical and clinical instruments. Among the different model configurations, we selected the feature combination of the in vitro model that had similar biomarker values to those measured by the clinical instruments used in clinical diagnostics. When we exposed the selected model configuration to rifampicin, ibuprofen and 5-fluorouracil, the viability of Kupffer cells and liver sinusoidal endothelial cells was significantly lower than in the untreated samples. In contrast, we observed negligible viability of hepatocytes compared to the untreated samples. We have built an in vitro liver model that resembles the liver microenvironment and we have analysed it with clinical instrumentation to facilitate the data translation. In this sense, we have established that Kupffer and LSEC cells are suitable candidates for the search for clinical diagnostic markers of liver function.

Cell-culture meat is a novel concept to replace traditional meat produced from animals, and to satisfy rising food demands due to the world population growth. It is still a young field and requires to solve technical issues including cell sources and types, efficient culture for large scale production, taste and texture for customer satisfaction. The current review summarized traditional beef meat production and evaluation methods for customer satisfaction. In particular, serum biomarkers for beef meat evaluation are discussed, which can be applicated for cell-culture meat production.

Chronic kidney disease patients treated by hemodialysis present a high cardio-vascular morbidity and mortality. There is an imperative need for novel biomarkers in identifying and to offer possible therapeutically intervention in these patients. We performed a prospective observational cohort study on 77 patients in the period October 2021 – October 2023. We measured serum plasma levels of Interleukin 1-Beta, Galectin 3, human suppression of tumorigenicity factor 2, bone morphogenetic protein 2 and fibroblastic growth factor 23 at the inclusion. We evaluated the correlations of these biomarkers with cardiac function and structure evaluated by echocardiography. Mean age was 61.02 (±11.81) years, 45 (56.2%) males and with a dialysis vintage of 4.95 (2.4-7.8) years. Median ejection fraction was 51 (43-54 %) and more than two thirds of the patients presented valvular calcifications. Overall mortality was 22%. Interleukin 1-Beta correlated positively with ejection fraction and global longitudinal strain and negatively with left atrium diameter and left ventricle tele systolic diameter. Galectin 3 values negatively correlated with aortic valve fibrosis and mitral valve calcifications and human suppression tumorigenity factor 2 negatively correlated with mitral valve calcifications. Some of these novel biomarkers could be used to better asses the cardio-vascular disease in patients on maintenance hemodialysis.

Introduction: Substance-induced psychotic disorder (SIPD) is a mental health condition linked to the use of a psychotropic substance whose pathogenesis has not been totally clarified. The present retrospective observational study has the objective to identify differences in clinical features and peripheral biomarkers in SIPD patients according to the main substance of abuse.Methods: A total sample of 218 patients was divided in 3 groups according to the type of consumed substance: alcohol, cannabis and psychostimulants. The 3 groups were compared for continuous variables by one-way analyses of variance (ANOVAs) and for qualitative variables by χ² tests. After removing alcohol-induced psychotic disorder group, the same analyses were repeated. Statistically significant variables from these latter analyses were included in a binary logistic regression model to confirm their reliability as predictors for cannabis- or psychostimulants-induced psychotic disorders. Results: Psychotic cannabis abusers were younger (p<0.01) and had an earlier age at onset (p<0.01). On the contrary, alcohol consumers resulted to have a longer duration of illness (p<0.01), more previous hospitalizations (p=0.04), more frequent medical comorbidity (p<0.01), higher mean Modified Sad Person Scale scores (p<0.01). Finally, psychostimulant abusers had more frequently a lifetime history of poly-substance use disorders (p<0.01). Binary logistic regression revealed that higher mean Brief Psychiatric Rating Scale scores (p<0.01) higher sodium (p=0.012) and haemoglobin(p=0.040) plasma levels were predictors of cannabis misuse in SIPD patients.Conclusions: Different clinical factors and biochemical parameters con be associated to SIPD according to the main substance of abuse, thus requiring a specific management by clinicians.

Anastomotic Leakage (AL) remains the main cause of post-esophagectomy morbidity and mortality. Early detection can avoid sepsis and reduce morbidity and mortality. This study evaluates the diagnostic accuracy of the NUn-score and its components as early detectors of AL. This single centre observational cohort study included all esophagectomies from 2010-2020. C-reactive Protein (CRP), Albumin (Alb) and White cell count (WCC) were analyzed and Nun-scores calculated. Area under the curves (AUC) were used to assess their predictive accuracy. Seventy-four of the 668 patients (11%) developed an AL. CRP and the NUn-score proved to be good diagnostic accuracy tests on POD2 (CRP AUC:0,859; Nun-score AUC:0,869) and POD4 (CRP AUC:0,924; Nun-score AUC:0,948). A 182mg/L CRP cut-off on POD4 yielded a 87% sensitivity, 88% specificity, a negative predictive value (NPV) of 98% and a positive predictive value (PPV) of 47,7%. A Nun score cut-off&gt;10 resulted in 92% sensitivity, 95% specificity, 99% NPV and 68% PPV. Albumin and WCC have limited value in the detection of post-esophagectomy AL. Elevated CRP and a high NUn score on POD4 provide a high accuracy to predict AL after esophageal cancer surgery. Their high negative predictive value allows to select patients who can safely proceed with enhanced recovery protocols.

The aim of the present study, was to evaluate the wild freshwater fish health status using a vast array of biomarkers as predictive factor of pollutant exposure. European eel (Anguilla anguilla) and Brown trout (Salmo trutta fario), resident in rivers with different degree of pollution in the South of Italy (Picentino river with good environmental quality and Tusciano river with low environmental quality), were examined using biometric parameters, histopathological and immunohistochemical biomarkers to evaluate the health status and a possible correlation with the water quality. Several alterations identified in the liver positively correlated with water and soil pollutants were: hemorrhage (P≤0.05), cytoplasmic vacuolization (P≤ 0.01), hemosiderosis (P≤0.05), irregular arrangement of hepatocytes (P≤ 0.01), lipid accumulation (P≤0.05), necrosis (P≤ 0.01), cellular hyperplasia (P≤0.05), leukocyte infiltration (P≤ 0.01) and melanomacrophages centers (MMC) (P≤ 0.01). In the spleen, only hemosiderosis correlated with water and soil pollutants (P≤ 0.05). The inflammatory biomarker tumor necrosis factor α (TNFα) and ciclooxigenase 2 (COX2) responded to the environmental pollution, as well as the oxidative stress biomarkers superoxide dismutase (SOD) and 8-Hydroxy-2'-deoxyguanosine (8-OHdG). Erythrocytic nuclear abnormalities and erythrocytic cellular abnormalities were found significantly higher in the blood of both Europen eel (P&lt;0.0001) and Brown trout (P &lt;0.001) in the Tusciano river with respect to the Picentino river. Taken together, these results outline the need to increase the number of suitable biomarkers to assess fish health and reinforce the importance to employ additional biomarkers in biomonitoring programs which can be applied to evaluate the water quality and environmental risk assessment around the world

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.

Abstract: Sarcopenia poses a significant challenge to public health and can severely impact the quality of life of aging populations. Despite extensive efforts to study muscle degeneration using traditional animal models, there is still a lack of effective diagnostic tools, precise biomarkers, and treatments for sarcopenia. Zebrafish models have emerged as powerful tools in biomedical research, providing unique insights into age-related muscle disorders like sarcopenia. The advantages of using zebrafish models include their rapid growth outside of the embryo, optical transparency during early developmental stages, high reproductive potential, ease of husbandry, compact size, and genetic tractability. By deepening our understanding of the molecular processes underlying sarcopenia, we may develop novel diagnostic tools and effective treatments that can improve the lives of aging individuals affected by this condition. This review aims to explore the unique advantages of zebrafish as a model for sarcopenia research, highlight recent breakthroughs, outline potential avenues for future investigations, and emphasize the distinctive contributions that zebrafish models offer. Our research endeavors to contribute significantly to addressing the urgent need for practical solutions to the impact of sarcopenia on aging populations, ultimately striving to enhance the quality of life for individuals affected by this condition.

Genome-based testing in oncology is a rapidly expanding area of health care which is the basis of the emerging area of precision medicine. Efficient and considered adoption of novel genomic medicine testing is hampered in Canada by the fragmented nature of health care oversight as well as by lack of clear and transparent processes to support rapid evaluation, assessment and implementation of genomic tests. This article provides an overview of some key barriers and proposes approaches to addressing these challenges as a potential pathway to developing a national approach to genomic medicine in oncology.

Introduction: The identification of some prognostic markers in head and neck cancers (HNC) is necessary for the stratification of the therapeutic approach with benefits in increasing treatment response rates and limiting the toxic side effects of treatments. Neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR) and pallets-to-lymphocyte ratio (PLR) are currently validated as cheap and accessible biomarkers in different types of solid tumors. The purpose of the study was to evaluate the possible biomarker value of NLR, PLR and MLR recorded pre-treatment (radiotherapy/chemotherapy) for prognostic purposes in HNC. Materials and methods: The study included 190 patients with HNC included in the oncology record in the oncology outpatient clinic of the Craiova County Emergency Hospital starting from January 2002 and deceased until December 2022. Among them, 40 patients treated multimodally in the Clinic were included in the study of Oncology of the Craiova County Emergency Hospital for which the pre-treatment value (chemotherapy/radiotherapy) of NLR, PLR and MLR could be calculated. Overall survival (OS) values were correlated with NLR, PLR and MLR. Results: Median values for NLR, PLR and MLR were 6.15 (1.24-69), 200.79 (61.3- 1775.0) and 0.53 (0.12-5.5) respectively. In the study, the mean values for NLR, PLR and MLR of 2.88, 142.97 and 0.36 respectively were obtained. Median OS in the study group was 11 months (1-120). Although a negative Pearson`s correlation, the relationship between your variables was only weak, values R =.07, p=.67; R=.02, p=.31 and R=07, p=.62 being related with NLR, PLR and MLR respectively correlation with overall survival (OS). The median values of NLR, PLR and MLR were calculated (1.53, 90.32 and 0.18 respectively) for HNC cases with pre-treatment values of NLR <2 and for HNC cases with NLR values ≥6 (23.5, 232.78 and 0.79 respectively). Median OS for cases with NLR<2 and NLR≥6 were 17.4 and 13 months, respectively. Conclusions: The negative correlations of NLR, PLR and MLR with OS reported in the study are in accordance with the data reported in the literature for locally advanced recurrent and metastatic HNSCC cases. The comparative analysis of the data in the group with NLR<2 and NLR≥6 highlights an advantage of 4.4 months in median OS in favor of the group with low values of NLR. Being cheap and accessible, these markers could change the therapeutic approach even in centers with limited resources. The role of borderline NLR values as a prognostic factor in HNSCC must also be defined. PLR and MLR are less evaluated as biomarkers but the study demonstrates their potential to be used as prognostic biomarkers, it remains to be clarified if their inclusion in multivariable models along with NLR would bring a benefit

The aim of our study was to assess the relationship between the concentration/activity of salivary stress biomarkers (cortisol, α-amylase) and the psychological profile of patients with oral lichen planus (OLP) and primary burning mouth syndrome (BMS). A total of 160 subjects participated in this cross-sectional study: 60 patients with OLP; 60 patients with primary BMS; 40 control subjects. Unstimulated whole saliva (UWS) was collected between 9 and 10 am. Salivary biomarkers were analyzed by enzyme-linked immunosorbent assay (ELISA). Psychological assessment was evaluated with the Depression, Anxiety, and Stress Scale (DASS-21). Patients with primary BMS had higher salivary cortisol concentrations and α-amylase activity (0.52 vs. 0.44 µg/dl; 160531 vs. 145804 U/L) compared with patients with OLP. Patients with primary BMS had statistically significantly higher scores for depression, anxiety, and stress compared with patients with OLP and control subjects (p <0.001, Kruskal-Wallis test). There was a strong positive correlation between anxiety and depression, stress and depression, stress and anxiety in patients with OLP and BMS (p <0.001 and p <0.001, respectively). There was a good positive correlation between symptom intensity (pain/burning) and psychological profile (depression, anxiety, stress) in patients with primary BMS (r=0.373, p=0.003; r=0.515, p <0.001; r=0.365, p= 0.004, respectively). Patients with BMS show a stronger association with mental disorders compared to patients with OLP. However, an interdisciplinary psychoneuroimmunological approach is equally important in both patient groups (OLP and BMS), regardless of whether mental disorders are the cause or the consequence.

Despite the available literature on traumatic brain injury (TBI) biomarkers elsewhere, data are limited or non-existent in sub-Saharan Africa (SSA). The aim of the study was to analyse associations in acute TBI between admission serum biomarker concentrations and TBI severity, CT-scan findings and outcome as well as explore the influence of concurrent Toxoplasma gondii infection. Concentrations of serum biomarkers (GFAP, NFL Tau, UCH-L1, and S100B) were measured and Toxoplasma gondii detected in samples obtained <24 hours post-injury. The GOSE was used to evaluate 6 months outcome. All biomarkers levels increased with severity of TBI, but this increase was significant only for NFL (P=0.01). GFAP values significantly increased (P=0.026) in those with unfavorable outcome. Tau levels were higher in those who died (P=0.017). GFAP and NFL were sensitive to CT-scan pathology (p values respectively 0.004 and 0.002). S100B levels were higher (P<0.001) in TBI patients seropositive to Toxoplasma gondii. NFL was found to be sensitive to TBI severity while NFL and GFAP were predictive of CT intracranial abnormalities. Increased levels of GFAP and Tau were associated with poorer outcomes 6 months after TBI. S100B levels were significantly higher in T. gondii seropositive TBI patients.

Biomarkers have become an important tool in the diagnosis and management of cardio renal syndromes (CRS), a complex condition characterized by dysfunction in both the cardiovascular and renal systems. These biomarkers can help identify the presence and severity of CRS, predict its progression and outcomes, and facilitate personalized treatment options. Several biomarkers, including natriuretic peptides, troponins, and inflammatory markers, have been extensively studied in CRS and have shown promising results in improving diagnosis and prognosis. In addition, emerging biomarkers such as kidney injury molecule-1 and neutrophil gelatinase-associated lipocalin offer potential for early detection and intervention of CRS. However, the use of biomarkers in CRS is still in its infancy, and further research is needed to establish their utility in routine clinical practice. This review highlights the role of biomarkers in the diagnosis, prognosis, and management of CRS and discusses their potential as valuable clinical tools for personalized medicine in the future.

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.

Background: Digital clinical measures collected via various digital sensing technologies such as smartphones, smartwatches, wearables, ingestible, and implantable are increasingly used by individuals and clinicians to capture health outcomes or behavioral and physiological characteristics of individuals. Time series classification (TSC) is very commonly used in modeling digital clinical measures. While deep learning models for TSC are very common and powerful, there exist some fundamental challenges. This review presents non-deep learning models commonly used for time series classification in biomedical applications that achieve high performance. Objective: We performed a systematic review to characterize the techniques used in time series classification of digital clinical measures throughout all stages of data processing and model building. Methods: We conducted a literature search on PubMed, and the Institute of Electrical and Electronics Engineers (IEEE), Web of Science, and SCOPUS databases using a range of search terms to retrieve peer-reviewed articles reporting academic research on digital clinical measures in the five year period between June 2016 and June 2021. We identified and categorized research studies based on the types of classification algorithms and sensor input types. Results: We found 452 papers in total from four different databases: PubMed, IEEE, Web of Science Database, and SCOPUS. After removing duplicates and irrelevant papers, 135 articles remained for detailed review and data extraction. Among these, engineered features using time series methods that were subsequently fed into widely-used machine learning classifiers was the most commonly used technique and also most frequently achieved the best performance metrics (77 out of 135 articles). Statistical modeling (24 out of 135 articles) algorithms were the second most common and also second best classification technique. Wavelet-based classification models (8 out of 135 articles) were also common. Electroencephalogram (29 out of 135 articles) was the most common data type used as an input. Accuracy was the most commonly reported performance metric, with 67.65% of articles reporting on accuracy. In this review paper, we provide summaries of signal pre-processing methods, feature engineering and selection methods, time series models, as well as model interpretations. Importantly, we found that about 50% of the papers only report one performance metric, which may result in a skewed view of overall performance. Conclusion: While high time series classification performance has been achieved in digital clinical, physiological, or biomedical measures, no standard benchmark datasets, modeling methods, or reporting methodology exist. There is no single widely used method for time series model development or feature interpretation– many different methods have proven successful.

Background: Myometrial invasion (MI) is a parameter currently used in transvaginal ultrasound (TVS) in endometrial cancer (EC) to determine local staging, however, without molecular diagnostics, it is insufficient for selection of high-risk cases, i.e., those with a high risk of lymph node metastases (LNM). Methods: One hundred sixteen consecutive EC patients, who had received 2D transvaginal ultrasound examinations in their preoperative workup and final histopathology results as a reference standard, were included in this prospective study. Univariate and multivariate logistic models of analyzed TVS biomarkers (tumor [T] size, T area [AREA], T volume [SPE-VOL], MI, T-free distance to serosa [TFD], endo-myometrial irregularity, [EMIR], cervical stromal involvement, CSI) were evaluated to assess the relative accuracy of the possible LNM predictors. To avoid a potential bias in assuming linear relations between LNM and continuous predictors, spline functions were applied. Calculations were made in R with the use of libraries splines, glmulti, and pROC. Results: LNM was found in 20 out of 116 (17%) patients. In univariate analysis, only uMI, EMIR, uCSI and uTFD were significant predictors of LNM. Accuracy was 0.707 (AUC 0.684, 95% CI 0.568-0.801) for uMI (p<0.01), 0.672 (AUC 0.664, 95% CI 0.547-0.781) for EMIR (p<0.01), 0.776 (AUC 0.647, 95% CI 0.529-0.765) for uCSI (p<0.01), and 0.638 (AUC 0.683, 95% CI 0.563-0.803) for uTFD (p<0.05). The cut-off value for uTFD was 5.2 mm. However, AREA and VOL revealed significant relation by non-linear analysis as well. Among all possible multivariate models, the one comprising interactions of splines of uTFD with uMI and splines of SPE-VOL with uCSI showed most usefulness. Accuracy was 0.802 (AUC 0.791, 95% CI 0.673-0.91) Conclusions: A combination of uTFD for patients with uMI>50%, and SPE-VOL for patients with uCSI, allows for the most accurate prediction of LNM in EC, rather than uMI alone.

Early disease detection in livestock allows for target treatment decreasing antibiotics use and allow advancements in precision veterinary medicine. MicroRNA (miRNA) -driven signaling cascades play a crucial role in the context of farm animal disease diagnostics and prediction, and their proper understanding remains a challenge. In livestock farm animals, only a small number of miRNAs have been fully validated with respect to disease conditions and physiological or behavioral traits. Low abundance of miRNAs in blood and bodily fluids, along with a small number of nucleotides, makes detection and discrimination tedious and challenging task in. miRNAs usually are homologous, owing to which detection specificity becomes next to impossible when screening for multiple miRNAs in the same analyte sample. Hence, a concurrent, multiplexing, approach becomes crucial for the development of on-farm point-of-care based detection systems. Comprehensive screening methods demand broad dynamic range and enhanced specificity. For on-farm handheld platform development, the ability to screen for multiple varieties of miRNA is essential. In this review paper, I provide an overview of the recent developments of miRNA sensing and the current bottlenecks in the realization of the sensors for detecting miRNAS as target analyte for various livestock disease detection applications. Due to the nascent stages of this research, the possibilities of exploiting miRNAs as a biomarker opens up ways to move from reactive to predictive possibilities in diseases detection in the modern digital livestock farming.

The combination of statistical learning technologies with large databases of psychophysiological data has appropriately generated enthusiastic interest in future clinical applicability. It is argued here that this enthusiasm should be tempered with the understanding that significant obstacles must be overcome before the systematic introduction of psychophysiological measures into neuropsychiatric practice becomes possible. The nonspecificity of psychophysiological measures complicates their use in diagnosis. Low test-retest reliability complicates use in longitudinal assessment, and quantitative psychophysiological measures can normalize in response to placebo intervention. Ten cautionary observations are introduced and, in some instances, possible directions for remediation are suggested.

The tryptophan catabolite (TRYCAT) pathway is implicated in the pathophysiology of schizophrenia (SCZ) since the rate-limiting enzyme indoleamine-dioxygenase (IDO) may be induced by inflammatory and oxidative stress mediators. This systematic review searched PubMed, Web of Science, and Google Scholar for papers published from inception until August 2021 and meta-analyzed the association between SCZ and TRYCATs in the central nervous system (CNS) and peripheral blood. We included 61 studies comprising 2813 patients and 2948 healthy controls. In the CNS we found a significant (p<0.001) increase in the kynurenine/tryptophan (KYN/TRP) (standardized mean difference, SMD=0.769, 95% confidence interval, CI: 0.456; 1.082) and kynurenic acid (KA)/KYN+TRP (SMD=0.697, CI:0.478-0.917) ratios, KA (SMD=0.646, CI: 0.422; 0.909) and KYN (SMD=1.238; CI: 0.590; 1.886), while the 3OH-kynurenine (3HK) + KYN-3-monooxygenase (KMO)/KYN ratio was significantly reduced (SMD=-1.089, CI: -1.682; -0.496). There were significant differences between KYN/TRP, (KYN+KA)/TRP, (3HK+KMO)/KYN, KA, and KYN levels among the CNS and peripheral blood, and among serum and plasma KYN. The only useful peripheral marker of CNS TRYCATs findings was the increased KYN/TRP ratio in serum (SMD=0.211, CI: 0.056; 0.366, p=0.007), but not in plasma. There was no significant increase in a neurotoxic composite score based on KYN, 3HK, and picolinic, xanthurenic, and quinolinic acid. SCZ is accompanied by increased IDO activity in the CNS and serum, and reduced KMO activity and a shift towards KA production in the CNS. This CNS TRYCATs profile indicates neuroprotective, negative immunoregulatory and anti-inflammatory effects. Peripheral blood levels of TRYCATs are dissociated from CNS findings except for a modest increase in serum IDO activity.

We performed a comprehensive analysis of angiosarcoma (AS) genomic biomarkers and their associations with the site of origin. We aimed to describe the genomic landscape of AS in a cohort of 143 cases of AS profiled by Caris Life Sciences. Data of Next Generation Sequencing (NGS) with a 592 gene panel was available for the entire cohort. Fifty-three cases had data of Whole Exome Sequencing (WES) which we used to study the microenvironment phenotype. Immuno-therapy (IO) response biomarkers: Tumor Mutation Burden (TMB), Microsatellite Instability (MSI) and PD-L1 status were included. IO-response markers were present in 36.4% of the cohort and in 65% of head and neck AS (H/N-AS) (p<0.0001). H/N-AS cases had predominantly muta-tions in TP53 (50.0%, p=0.0004), POT1 (40.5%, p<0.0001) and ARID1A (33.3%, p=0.5875). In breast AS, leading alterations were MYC amplification (63.3%, p<0.0001), HRAS (16.1%, p=0.0377), and PI3KCA (16.1%, p=0.2352). A microenvironment with a high immune signature, associated with better response to IO, was present in 13% of the cases. This signature was evenly distributed among different primary sites. We found that the molecular biology for AS varies significantly according to the primary site. Our findings can facilitate the design and optimiza-tion of therapeutic strategies for AS to overcome resistance to IO and targeted therapies.

Hepatitis B virus (HBV) infection remains a global public problem despite the availability of effective vaccine. In the past decades, nonalcoholic fatty liver disease (NAFLD) has surpassed HBV as the most common cause of chronic liver disease worldwide. The prevalence of concomitant chronic hepatitis B (CHB) and NAFLD, thus, reaches endemic in geographic regions where both conditions are common. Patients with CHB and NAFLD are at increased risk of liver disease progression to cirrhosis and hepatocellular carcinoma. Due to complexity of the pathogenesis, accurate diagnosis of NAFLD in CHB patients can be challenging. Liver biopsy is considered the gold standard for diagnosing and determining the disease severity, but it is an invasive procedure with potential complications. There is a growing body of literatures on the application of novel noninvasive serum biomarkers and advanced radiological modalities to diagnose and evaluate NAFLD, but most have not been adequately validated especially for patients with CHB. Currently, there is no approved therapy for NAFLD though many new agents are in different phases of development. This review provides a summary of the epidemiology, clinical features, diagnosis and management of the NAFLD and highlights the unmet needs in the areas of CHB and NAFLD coexistence.

Background: Hypertension, atherogenicity and insulin resistance are major risk factors of cardiovascular disorder (CVD), which shows a strong comorbidity with major depression (MDD) and bipolar disorder (BD). Activated oxidative and nitrosative stress (O&NS), inflammatory pathways, and increased atherogenicity are shared pathways underpinning CVD and mood disorders. Methods: The current study examined the effects of lipid hydroperoxides (LOOH), superoxide dismutase (SOD), nitric oxide metabolites (NOx), advanced oxidation protein products (AOPP), and malondialdehyde (MDA) on systolic (SBP) and diastolic (DBP) blood pressure in 96 mood disordered patients and 60 healthy controls. Results: A large part of the variance in SBP (31.6%) was explained by the regression on a z unit-weighted composite score (based on LOOH, AOPP, SOD, NOx) reflecting nitro-oxidative stress toxicity (NOSTOX), coupled with highly sensitive C-reactive protein, body weight and use of antihypertensives. Increased DBP was best predicted (23.8%) by body mass index and NOSTOX. The most important O&NS biomarkers predicting an increased SBP were in descending order of significance: LOOH, AOPP and SOD. Higher levels of the atherogenic index of plasma, HOMA2 insulin resistance index and basal thyroid-stimulating hormone also contributed to increased SBP independently from NOSTOX. Although there were no significant changes in SBP/DBP in mood disorders, the associations between NOSTOX and blood pressure were significant in patients with mood disorders but not in healthy controls. Conclusions: Activated O&NS pathways including increased lipid peroxidation and protein oxidation, which indicates hypochlorous stress, are the most important predictors of an increased BP, especially in patients with mood disorders.

Non-Alcoholic Fatty Liver Disease (NAFLD) is a term that covers a range of hepatic disorders involving fat deposits in the liver. NAFLD begins with simple steatosis and progresses into non-alcoholic steatohepatitis (NASH) characterised by inflammation, fibrosis, apoptosis, oxidative stress, lipid peroxidation, mitochondrial dysfunction and release of adipokines and pro-inflammatory cytokines. Oxidative stress and antioxidants are known to play a vital role in the pathogenesis and severity of NAFLD/NASH. A number of oxidative stress and antioxidant markers are employed in the assessment of the pathological state and progression of the disease. In this article, we review several biomarkers of oxidative stress and antioxidants that have been measured at clinical and experimental levels. The levels/ activity in various models reviewed are also included. Also included is a comprehensive description of oxidative stress, sources and contribution to the pathogenesis of NAFLD/NASH

Oral cancer represents a significant global public health challenge, contributing substantially to cancer incidence and mortality. Despite established risk factors such as tobacco use and alcohol consumption, early detection remains crucial for effective treatment. This study introduces a novel approach using a transistor-based biosensor system for detecting the P90 (CIP2A) protein. We have tested the presence of CIP2A in human leukoplakia samples that can rise into oral squamous cell carcinoma. The method employs commercially available glucose test strips functionalized with P90 antibodies, providing high sensitivity and a low limit of detection, which is five orders lower than commercial ELISA kits. A specially designed printed circuit board (PCB) facilitates accurate measurements, and the device's performance is optimized through characteristic tests. Human sample testing validates the biosensor's effectiveness in distinguishing samples after cell lysis. This study contributes to advancing accurate and cost-effective diagnostic approaches for oral pre-cancer and cancer tissues.

Wilms tumor (WT), the most prevalent type of renal cancer in children, exhibits overall survival rates exceeding 90%. However, chemotherapy resistance, which occurs in approximately 10% of WT cases, is a major challenge for the treatment of WT, particularly for advanced-stage patients. In this study, we aimed to discover potential mutation markers and drug targets associated with chemotherapy resistance in advanced stage WT. We performed exome sequencing to detect somatic mutations and molecular targets in 43 WT samples, comprising 26 advanced stage WTs, of which 7 cases are chemotherapy-resistant. Our analysis revealed four genes (ALPK2, C16orf96, PRKDC, and SVIL) that correlated with chemotherapy resistance and reduced disease-free survival in ad-vanced-stage WT. Additionally, we identified driver mutations in 55 genes within the chemo-therapy-resistant group, including 14 druggable cancer driver genes. Based on the mutation profile of the resistant WT samples, we propose potential therapeutic strategies involving platinum-based agents, PARP inhibitors, and antibiotic/antineoplastic agents. Our findings provide insights into the genetic landscape of WT and offer potential avenues for targeted treatment, particularly for patients with chemotherapy resistance.

We have been encouraging practicing gynecologists to adopt molecular diagnostics tests, PCR, and cancer biomarkers, as an alternative enabled by these platforms to traditional Papanicolaou and colposcopy tests, respectively. An aliquot of liquid-based cytology was used for the molecular test [high-risk HPV types, (HR HPV)], another for the PAP test and still one more for the p16/Ki67 dual stain cytology. A total of 4,499 laboratory samples were evaluated, and we found that 25.1% of low-grade samples and 47.9% of high-grade samples after PAP testing had a negative HR HPV-PCR result. In those cases, reported as Pap-negative, 22.1% got a positive HR HPV-PCR result. Dual staining with the p16/Ki67 biomarkers in samples was positive for HR HPV, and 31.7% were also positive for these markers. Of the PCR results positive for any of these high-risk HPV subtypes, n 68.3% we did not to find evidence for the presence of cancerous cells, highlighting the importance of performing dual staining with p16/Ki67 after PCR, to avoid unnecessary colposcopies. Encountered challenges are a deep-rooted social reluctance in Mexico to abandon traditional Pap smears and the opinion of many specialists, we still believe that colposcopy continues to be a preferred procedure over dual staining protocol.