The snow melt from the High Atlas is a critical water resource in Morocco. In spite of its importance, monitoring the spatio-temporal evolution of key snow cover properties like the snow water equivalent remains challenging due to the lack of in situ measurements at high elevation. Since 2015, the Sentinel-2 mission provides high spatial resolution images with a 5 day revisit time, which offers new opportunities to characterize snow cover distribution in mountain regions. Here we present a new data assimilation scheme to estimate the state of the snowpack without in situ data. The model was forced using MERRA-2 data and a particle filter was developed to dynamically reduce the biases in temperature and precipitation using Sentinel-2 observations of the snow cover area. The assimilation scheme was implemented using SnowModel, a distributed energy-balance snowpack model and tested in a pilot catchment in the High Atlas. The study period covers 2015-2016 snow season which corresponds to the first operational year of Sentinel-2A, therefore the full revisit capacity was not yet achieved. Yet, we show that the data assimilation led to a better agreement with independent observations of the snow height at an automatic weather station and the snow cover extent from MODIS. The performance of the data assimilation scheme should benefit from the continuous improvements in MERRA-2 reanalyses and the full revisit capacity of Sentinel-2.

The global threat of COVID-19 has led to the increasing use of metabolomics to study SARS-CoV-2 infection in humans and animals. Despite this, understanding SARS-CoV-2's metabolome during infection remains difficult and incomplete. Here, metabolic responses were characterized from sampled nasal washes collected from an asymptomatic ferret model (n = 20) at different time points before and after the SARS-CoV-2 challenge using an LC-MS-based metabolomics approach. Multivariate analysis of the nasal wash metabolome data resulted in several statistically significant features being observed. Despite no effects of gender or interaction between gender and time on the time course of SARS-CoV-2 infection, 16 metabolites were significantly different at every time point post-infection. Among these altered metabolites, the relative abundance of taurine was elevated post infection which could be an indication of hepatotoxicity, while the accumulation of sialic acids could indicate SARS-CoV-2 invasion. The pathway analysis identified several pathways influenced by SARS-CoV-2 infection. Of these, sugar, glycan, and amino acid metabolisms were the key altered pathways in the upper respiratory channel during infection. These findings provide some new insights into the progression of SARS-CoV-2 infection in ferrets at the metabolic level which could be useful for the development of early clinical diagnosis tools and new or repurposed drug therapies.

The Golden Syrian hamster (Mesocricetus auratus) is now commonly used in preclinical research for the study of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and the assessment of vaccines, drugs and therapeutics. Here we show that hamsters inoculated via the intranasal route with the same infectious virus dose of prototypical SARS-CoV-2 administered in a different volume present with different clinical signs, weight loss and viral shedding, with a reduced volume resulting in reduced severity of disease similar to that obtained by a 500-fold reduction in challenge dose. The tissue burden of virus and the severity of pulmonary pathology were also significantly affected by different challenge inoculum volumes. These findings suggest that direct comparison between the severity of SARS-CoV-2 variants or studies assessing the efficacy of treatments determined by hamster studies cannot be made unless both the challenge dose and inoculation volume are matched when using the intranasal route. Additionally, analysis of sub-genomic and total genomic RNA PCR data demonstrated no link between sub-genomic and live viral titres and that sub-genomic analyses do not provide any information beyond that provided by more sensitive total genomic PCR.

Trypanosoma cruzi infection results in debilitating cardiomyopathy, which is a major cause of mortality and morbidity in the endemic regions of Chagas disease (CD). The pathogenesis of Chagasic cardiomyopathy (CCM) has been intensely studied as a chronic inflammatory disease until recent observations reporting the role of cardio-metabolic dysfunctions. In particular, we demonstrated accumulation of lipid droplets and impaired cardiac lipid metabolism in the hearts of cardiomyopathic mice and patients, and their association with impaired mitochondrial functions and endoplasmic reticulum (ER) stress in CD mice. In the present study, we examined whether treating infected mice with an ER stress inhibitor can modify the pathogenesis of cardiomyopathy during chronic stages of infection. T. cruzi infected mice were treated with an ER stress inhibitor 2-Aminopurine (2AP) during the indeterminate stage and evaluated for cardiac pathophysiology during the subsequent chronic stage. Our study demonstrates that inhibition of ER stress improves cardiac pathology caused by T. cruzi infection by reducing ER stress and downstream signaling of phosphorylated eukaryotic initiation factor (P-elF2α) in the hearts of chronically infected mice. Importantly, cardiac ultrasound imaging showed amelioration of ventricular enlargement, suggesting that inhibition of ER stress may be a valuable strategy to combat the progression of cardiomyopathy in Chagas patients.

A compartmental epidemiological model with seven groups is introduced herein, to account for the dissemination of diseases similar to the Coronavirus disease 2019 (COVID-19). In its simplified version, the model contains ten parameters, four of which relate to characteristics of the virus, whereas another four are transition probabilities between the groups; the last two parameters enable the empirical modelling of the effective transmissibility, associated in this study with the cumulative number of fatalities due to the disease within each country. The application of the model to the fatality data (the main input herein) of five countries (to be specific, of those which had suffered most fatalities by April 30, 2020) enabled the extraction of an estimate for the basic reproduction number $R_0$ for the COVID-19 disease: $R_0=4.91(33)$.

Parkinson’s disease (PD) is one of the most common neurodegenerative diseases. Recent data highlight similarities between neurodegenerative diseases including PD and type 2 diabetes mellitus (T2DM) suggesting a crucial interplay between the gut–brain axis. GLP-1R agonists, known for their use in T2DM treatment, are currently extensively studied as novel PD modifying agents. For this narrative review article, we searched PubMed and Scopus databases for peer-reviewed research, review articles and clinical trials regarding GLP-1R agonists and PD, published in the English language with no time restrictions. We also screened the references of the selected articles for possible additional articles in order to include most of the key recent evidence. Our research was conducted between February 2023 and February 2024. We used the terms “GLP-1”, “GLP-1 receptor”, “GLP-1R agonists”, “PD”, “T2DM”, “insulin”, “neurodegenerative disease”, “glucose”, “animal models”, “clinical trials” in different combinations. Many data on animal models and preclinical studies show that GLP1-R agonists can restore dopamine levels, inhibit dopaminergic loss, attenuate neuronal degeneration and alleviate motor and non-motor features of PD. Evidence from clinical studies are also very promising enhancing the possibility of adding GLP1-R agonists in the current armamentarium of drugs available for PD treatment.

Chronic lymphocytic leukemia (CLL) is characterized by dysfunctional B cells. Immune checkpoint molecules such as cytotoxic T-lymphocyte-associated protein 4 (CTLA-4), and programmed death-1 (PD-1) are upregulated in patients with CLL and may correlate with prognostic markers such as beta-2 microglobulin (B2M). The aim of this study was to evaluate the levels of immune checkpoints on B-cell subsets and to further correlate them with B2M levels in patients with CLL. We recruited 21 patients with CLL and 12 controls. B cell subsets and the levels of immune checkpoint expression were determined using conventional multi-color flowcytometry. Basal levels of B2M in patients with CLL were measured using an Enzyme-linked immunosorbent assay. Patients with CLL had increased levels of activated B cells when compared to the control group, p< 0.001. The expression of PD-1 and CTLA-4 were increased on activated B cells and memory B cells, p< 0.05. There were no associations between B2M levels and the measured immune checkpoints on B cell subsets, after adjusting for sex and age. African patients with CLL express elevated levels of PD-1 and CTLA-4 immune checkpoints on activated and memory B cell subsets. However, there is no correlation between these immune checkpoint expressions and B2M levels.

This study aimed to use remote sensing and GIS to detect changes in surface water and wetlands in the Kumasi Metropolis over a period of 20 years (2002-2022). Landsat images were processed using the QGIS software, and the Maximum Likelihood Algorithm was used to perform supervised classification of land use land cover, while raster calculator aided in detecting wetlands by calculation for NDWI, MNDWI, and AWEI. The results showed that the majority of the landscape in the Kumasi metropolis was made up of built-up areas (79.4%), followed by agricultural lands (13.3%) and wetlands (7.3%). Over the 20-year period, built-up areas had gained 20.7% of the total landscape, while agricultural lands and wetlands had lost 16.7% and 4.0%, respectively. All water index methods recorded an increase in non-water cover and a loss of water cover over the period, with surface water decreasing by 5% and non-water land cover increasing by 5%. The study concludes that there have been significant changes in wetlands and surface water land use and land cover within the Kumasi Metropolis over the past 20 years, and recommends the enforcement of legislation on surface water protection in the area to protect wetlands

Electricity demand forecasting has been a real challenge for power system scheduling in the different levels of the energy sectors. Various computational intelligence techniques and methodologies have been employed in the electricity market for load forecasting; although, scant evidence is available about the feasibility of each of these methods considering the type of data and other potential factors. This work introduces several scientific, technical rationale behind intelligent forecasting methods, based on the work of previous researchers in the field of energy. The fundamental benefits and main drawbacks of the aforementioned methods are discussed in order to depict the efficiency of each approach in various situations. In the end, a proposed hybrid strategy is represented.

The authors previously found a model of universal quantum computation by making use of the coset structure of subgroups of a free group $G$ with relations. A valid subgroup $H$ of index $d$ in $G$ leads to a \lq magic' state $\left|\psi\right\rangle$ in $d$-dimensional Hilbert space that encodes a minimal informationally complete quantum measurement (or MIC), possibly carrying a finite \lq contextual' geometry. In the present work, we choose $G$ as the fundamental group $\pi_1(V)$ of an exotic $4$-manifold $V$, more precisely a \lq small exotic' (space-time) $R^4$ (that is homeomorphic and isometric, but not diffeomorphic to the Euclidean $\mathbb{R}^4$). Our selected example, due to to S. Akbulut and R.~E. Gompf, has two remarkable properties: (a) it shows the occurence of standard contextual geometries such as the Fano plane (at index $7$), Mermin's pentagram (at index $10$), the two-qubit commutation picture $GQ(2,2)$ (at index $15$) as well as the combinatorial Grassmannian Gr$(2,8)$ (at index $28$) , (b) it allows the interpretation of MICs measurements as arising from such exotic (space-time) $R^4$'s. Our new picture relating a topological quantum computing and exotic space-time is also intended to become an approach of \lq quantum gravity'.

The activity and cyclability of Cu-MOF-74 as catalyst was studied for the ligand-free C-O cross-coupling reaction of 4-nitrobenzaldehyde (NB) with phenol (Ph) to form 4-formyldiphenyl ether (FDE). Cu-MOF-74 is characterized by unsaturated copper sites in a highly porous metal-organic framework. The influence of solvent, reaction temperature, NB/Ph ratio, catalyst concentration and basic agent (type and concentration) were evaluated. High conversions were achieved at 120°C, 5 mol% of catalyst, NB/Ph ratio of 1:2, DMF as solvent and 1 equivalent of K2CO3 base. The activity of Cu-MOF-74 material was higher than other ligand-free copper catalytic systems tested in this study. This catalyst was easily separated and reused in five successive runs, achieving a remarkable performance without significant porous framework degradation. The leaching of copper species in the reaction medium was negligible. The O-arylation between NB and Ph took place only in the presence of Cu-MOF-74 material, being negligible without the solid catalyst.

The natural history of COVID-19 caused by SARS-CoV-2 is extremely variable, ranging from asymptomatic infection, to pneumonia, and to complications eventually fatal. We propose here the first model, explaining how the outcome of first, crucial 10-15 days after infection, hangs on the balance between the cumulative dose of viral exposure and the efficacy of the local innate immune response (natural IgA and IgM antibodies, MBL). If SARS-CoV-2 runs the blockade of this innate immunity and spreads from the upper airways to the alveoli in the early phases of the infections, it can replicate with no local resistance, causing pneumonia and releasing high amounts of antigens. The delayed and strong adaptive immune response (high affinity IgM and IgG antibodies) that follows, causes severe inflammation and triggers mediator cascades (complement, coagulation, and cytokine storm) leading to complications often requiring intensive therapy and being, in some patients, fatal. Strenuous exercise and high flow air in the incubation days and early stages of COVID-19, facilitates direct penetration of the virus to the lower airways and the alveoli, without impacting on the airway’s mucosae covered by neutralizing antibodies. This allows the virus to bypass the efficient immune barrier of the upper airways mucosa in young and healthy athletes. In conclusion, whether the virus or the adaptative immune response reach the lungs first, is a crucial factor deciding the fate of the patient. This “quantitative and time-sequence dependent” model has several implications for prevention, diagnosis, and therapy of COVID-19.

The ongoing emergence of SARS-CoV-2 virus variants remains a source of concern because it is accompanied by the potential for increased virulence as well as evasion of immunity. Here we show that, although having an almost identical spike gene sequence as another Omicron variant (BA.5.2.1), a BA.4 isolate lacked all the typical disease characteristics of other isolates seen in the Golden Syrian hamster model despite replicating almost as effectively. Animals infected with BA.4 had similar viral shedding profiles to that seen with BA.5.2.1 (up to day 6 post infection) but they all failed to lose weight or present with any other significant clinical signs. We hypothesize that this lack of detectable signs of disease during infection with BA.4 was due to a small (nine nucleotide) deletion (∆686-694) in the viral genome (ORF1ab) responsible for production of non-structural protein 1 which resulted in the loss of three amino acids (aa 141-143).

This paper describes the formulations for viscoplasticity of metals based on the Chaboche and Delobelle model. The implementations of the viscoplastic models were detailed herein and then implemented via user subroutines for material models (UMAT) in ABAQUS. Two typical metals, i.e., 316 Stainless Steel and Zircaloy-4, were chosen as examples and their viscoplastic behaviors were captured. Numerical simulations are compared to reported experiments to validate the models and the UMAT codes. Typical viscoplastic behaviors of both metals, such as stress relaxation and creep, were captured well against available experiments. We publicize all the data and codes via: https://github.com/XJTU-Zhou-group/ABAQUS_UMAT_316ss_Zr4.

We demonstrate, for the first time, a highly sensitive detection of 4-methylimidazole (4-MeI), a carcinogenic material, by applying an electric field enhancement technique using a terahertz (THz) metamaterial at the THz region. The THz metamaterials were fabricated with a metal array using an electric-field-coupled inductor-capacitor (ELC) resonator structure, and FDTD simulation showed good agreement with experimental results. We measured the THz spectra of the metamaterials to detect 4-MeI concentrations of 0, 1, 2, 5, 10, 15, and 20 mg/L. The resonance frequency of the metamaterial was shifted by approximately 8 GHz and transmittance at the resonance frequency increased to 2 x 10-3 as the concentration was increased, up to 20 mg/L. Our study provides new insight into application of metamaterials to detect carcinogen using a THz technique.

Cutaneous leishmaniasis (CL) is a neglected tropical disease, which causes severe skin lesions. Due to the lack of effective vaccines, and toxicity or reduced effectiveness of available drugs in addition to complex and prolonged treatments, there is an urgent need to develop alternatives for the treatment for CL with different mechanisms of action. In our effort to search for new promising hits against Leishmania parasites we prepared 18 acyl hydrazone derivatives of thiochroman-4-ones. Compounds were evaluated for their in vitro antileishmanial activity against the intracellular amastigote form of Leishmania panamensis and cytotoxic activity against human monocytes (U-937 ATCC CRL-1593.2). Our results show that derivatization of the thiochroman-4-ones with acyl hydrazones significantly enhances the antileishmanial activity. Among the compounds tested semicarbazone and thiosemicarbazone derivatives of thioflavanone 19 and 20 displayed the highest antileishmanial activities, with EC₅₀ values of 5.4 and 5.1 µM and low cytotoxicities (100.2 and 50.1 µM respectively), resulting in higher indexes of selectivity (IS).

Transition-metal-free synthesis of 4-pyrones via TfOH-promoted nucleophilic addition/cyclization of diynones and water has been developed. This transformation is simple, atom economical and environmentally benign, providing rapid and efficient access to substituted 4-pyrones.

Tyrosine kinase fibroblast growth factor receptor (FGFR), which is aberrant in various cancer types, is a promising target for cancer therapy. Here we reported the design, synthesis, and biological evaluation of a new series of 6-(2,6-dichloro-3,5-dimethoxyphenyl)-4-substituted-1H-indazoles derivatives as potent FGFR inhibitors. Compound 10a was first identified as a potent FGFR1 inhibitor, with good enzymatic inhibition. Further structure-based optimization revealed that compound 13a is the most potent FGFR1 inhibitor in this series with the enzyme inhibitory activity about 30.2 nM of IC50 value.

Transferrin (TF) is a key iron carrier protein. Studies in human cohorts and in cultured adipocytes suggested that decreased transferrin expression and intracellular iron in adipocytes leads to impaired insulin responsiveness and causes differential expression of genes involved in metabolism, insulin action, and obesity. While suggestive, these studies did not definitively prove in an intact organism that altering TF expression in adipocytes is sufficient to affect glucose homeostasis and insulin resistance. In this study we created a mouse model of decreased transferrin expression only in adipocytes (Trf+/-Cre+/-) to test the hypothesis that iron trafficking in adipose tissue is sufficient to affect insulin sensitivity. Area under the glucose curve (AUCg) after intraperitoneal glucose administration was increased in the Trf+/-Cre+/- mice compared to wild type (WT) mice on a normal chow diet, and the mice were slightly heavier (p=0.02 for both). Homeostasis Model of Insulin Resistance (HOMA-IR) values were also significantly higher in the Trf+/- Cre+/- mice (p<0.05). Thus, supporting our hypothesis, analysis of mice with decreased expression of TF restricted to adipocytes showed that a decrease in adipocyte TF is sufficient to affect insulin resistance, weight, and glucose homeostasis.

IL1RA intron 2 86-bp repeat and IL4 intron 3 70-bp repeat are VNTRs that have been associated with various diseases, but their role in obesity is elusive. The objective of this study was to investigate the association of IL1RA and IL4 VNTRs with obesity and adiposity in 315 Malaysian subjects (128 M/187 F; 23 Malays/251 ethnic Chinese/41 ethnic Indians). The allelic distributions of IL1RA and IL4 were significantly different among ethnicities, and the alleles were associated with total body fat (TBF) classes. Individuals with IL1RA I/II genotype or allele II had greater risk of having higher adiposity - even after controlling for ethnicity [Odds Ratio (OR) of I/II genotype = 12.21 (CI = 2.54, 58.79; p = 0.002); II allele = 5.78 (CI = 1.73, 19.29; p = 0.004)]. However, IL4 VNTR B2 allele was only significantly associated with overall adiposity status before adjusting for ethnicity [OR = 1.53 (CI = 1.04, 2.23; p = 0.03)]. TBF was also significantly higher in those with IL1RA II allele compared with I allele (31.79 ± 2.52 vs. 23.51 ± 0.40; p = 0.005). Taken together, IL1RA intron 3 VNTR seems to be a genetic marker for overall adiposity status in Malaysian subjects.

Alzheimer's disease (AD) is characterized by abnormal amyloid beta (Aβ) plaques and hyperphosphorylated tau in the brain. Aβ plaques precede cognitive impairments and can be detected through amyloid-PET or in cerebrospinal fluid (CSF). Assessing the plasma Aβ42/Aβ40 ratio seems promising for non-invasive and cost-effective detection of brain Aβ accumulation. This approach involves some challenges, including the accuracy of blood-based biomarker measurements and the establishment of clear, standardized thresholds to categorize the risk of developing brain amyloid pathology. Plasma Aβ42/Aβ40 ratio was measured in 277 volunteers without dementia, 70 AD patients and 18 non-AD patients using single-molecule array. Patients (n=88) and some volunteers (n=66) were subject to evaluation of amyloid status by CSF Aβ quantification or PET analysis. Thresholds of plasma Aβ42/Aβ40 ratio were determined based on a Gaussian mixture model, a decision tree, and the Youden index. The 0.0472 threshold, the one with the highest sensitivity, was retained for general population without dementia screening, and the 0.0450 threshold was retained for research and clinical trials recruitment, aiming to minimize the need for CSF or PET analyses to identify amyloid-positive individuals. These findings offer a promising step towards a cost-effective method for identifying individuals at risk of developing AD.

Load shifting is one of the demand side management (DSM) strategies to support the efficiency in the electricity grid during the peak hours demand. Load shifting at the appliance level is interesting to review since the appliance usage is one of the main inputs in the load profile analysis. More review studies in load shifting at the appliance level are required as it is a specific issue of load profile research body, and still limited studies are available at this moment. It is also essential to focus on the appliance usage patterns to better understand the impacts and characteristics of the individual appliance. The existing studies in load shifting have applied common structured literature reviews, and our study addresses the transparency of each stage and sub-stage of the selection of the final list studies. The finding shows that efficiency has been achieved in the installed capacity reduction, cost including emission reductions, and peak consumption reduction. The most applied method in the load shifting at the appliance level is by developing the load shifting optimisation algorithms. This work contributes to provide a transparent process of applying a systematicity literature review, where it becomes a source of knowledge and grounded theory. It contributes to a limited and specific research of load shifting at the appliance level by highlighting and discussing the key findings for the readers. In specific, it contributes to improve energy efficiency by presenting the load shifting methods at the appliance level and identifying the controllable and uncontrollable appliances. This detail review study at the appliance level can make valuable contributions to support decision and policy-making by illuminating new dynamic system in load shifting area in specific, and demand side management in general for energy efficiency.

Fluorinated compounds and co-enzymes are being widely researched and employed throughout research community because of their versatile physical, chemical and biological properties. In this work, we synthesized NiS-NiO/S-g-C3N4, a highly effective photocatalyst for C(sp3)-F bond activation and the regeneration of coenzyme (1,4-NADH) employing a new and ecologically acceptable route. The obtained photocatalyst exhibited important photocatalytic properties, such as good solar light harvesting ability, suitability of the optical band-gap, and facilitating efficient charge migrations. As a result, the newly designed NiS-NiO/S-g-C3N4 photocatalyst shows the excellent yield for regenerations of 1,4-NADH (51%). Further, a method of combining C(sp3)-F bond activation with photocatalysis has been demonstrated that represents a very powerful and sustainable approach, that can be a major breakthrough for the field of pharmaceutical.

In this paper I will address Dr. Sonne’s questions about will, agency, choice, consciousness, relevant brain regions, impacts of disorders and their therapeutics, and I will do this by referring to my theory, Dual-brain Psychology, which posits that within most of us there exist two mental agencies with different experiences, wills, choices, and behaviors. Each of these agencies is associated as a trait with one brain hemisphere (either left or right) and its composite regions. One of these agencies is more adversely affected by past traumas and is more immature and more symptomatic while the other is more mature and healthier. The theory has extensive experimental support through 17 peer-reviewed publications with clinical and non-clinical research. I will discuss how this theory relates to the questions that Dr. Sonne presented and will discuss also my published theory on the physical nature of subjective experience and its relation to the brain and how that theory interacts with DBP, and how the 2 theories relate to subjective experience, will, behavior, psychopathology and its treatment.

With data for SARS-CoV-2 and with many countries entering the second wave of contagion required the improvement of the forecasting model, structuring its model to forecast the peak of the first and second contagion wave in Brazil. The Model Estimation for SARS-CoV-2 Peak Contagion (MESPC) was structured, capable of estimating the peak of contagion for SARS-CoV-2 in the first and second waves, as the main objective of this work. Using the MESPC model, it was possible to estimate, with a certain reliability degree, the peak of contagion for the first and second waves in Brazil, with one day difference from the real to the forecast. It is possible to use MESPC to forecast the peak of contagion for several regions, provided that the necessary structure and calibration are respected.

The dynamical equations of the susceptible-infected-recovered/removed (SIR) epidemics model play an important role to predict and/or analyze the temporal evolution of epidemics outbreaks. Crucial input quantities are the time-dependent infection ($a(t)$) and recovery ($\mu (t)$) rates regulating the transitions between the compartments $S\to I$ and $I\to R$, respectively. Accurate analytical approximations for the temporal dependence of the rate of new infections $\dot{J}(t)=a(t)S(t)I(t)$ and the corresponding cumulative fraction of new infections $J(t)=J(t_0)+\int_{t_0}^tdx\dot{J}(x)$ are available in the literature for either stationary infection and recovery rates and for a stationary value of the ratio $k(t)=\mu (t)/a(t)$. Here a new and original accurate analytical approximation is derived for general, arbitrary and different temporal dependencies of the infection and recovery rates which is valid for not too late times after the start of the infection when the cumulative fraction $J(t)\ll 1$ is much less than unity. The comparison of the analytical approximation with the exact numerical solution of the SIR-equations for different illustrative examples proves the accuracy of the analytical approach.

In Tropical Monsoon climates, precipitation exceeds evapotranspiration, leading to increased surface runoff, especially in floodplain regions. The Bhagirathi-Hooghly River in India is the focus of the study, which analyses hydrology, sediment yield, and water balance in this floodplain area. This investigation employs the Soil and Water Assessment Tool (SWAT) model within the ArcGIS environment, using remote sensing data. The study area is divided into 4 sub-basins and 40 Hydrological Response Units (HRUs), with a focus on Land Use/Land Cover (LULC) parameters, soil attributes, and slope characteristics. Calibration (1998-2010) and validation (2011-2018) of river discharge and sediment yield are performed using the SUFI-2 algorithm within SWAT-CUP. The calibration process shows a strong correlation between observed and simulated data points, indicating the model's accuracy. The study reveals a pattern of early-year evapotranspiration followed by increasing rainfall during the monsoon season, leading to heightened surface runoff and sediment yield. Excessive rainfall, therefore, emerges as a pivotal driver of flood incidences within the floodplain. The insights derived from the SWAT model's floodplain data have the potential to inform flood control and sedimentation mitigation strategies. The assimilation of this data can empower local stakeholders and contribute to sustainable livelihoods and improved living conditions, offering guidance for future governmental policies.

Preterm birth (PB) is a leading cause of perinatal morbidity and mortality. PB prediction is per-formed by measuring cervical length, with a detection rate of around 70%. Although it is known that a cytokine-mediated inflammatory process is involved in the pathophysiology of PB, no screening method implemented in clinical practice includes cytokine levels as a predictor varia-ble. Here, we quantified cytokines in cervical-vaginal mucus of pregnant women (18-23.6 weeks of gestation) with high- or low-risk for PB determined by cervical length, collecting relevant obstetric information. IL-2, IL-6, IFN-γ, IL-4, and IL-10 were significantly higher in the high-risk group, while IL-1ra was lower. Two different models for PB prediction were created using the Random Forest machine-learning algorithm: the full model with 12 clinical variables and cyto-kine values, and the adjusted model, including the most significant variables -maternal age, IL-2, and cervical length- (detection rate 66 vs 87%, false positive rate 12 vs 3.33%, false negative rate 28 vs 6.66%, and area under the curve 0.722 vs 0.875, respectively). The adjusted model integrat-ing cytokines showed a detection rate 8 points higher than the gold standard calculator, which may allow us to identify PB risk more accurately and implement strategies for preventive in-terventions

This paper presents a new method for the design of separable denominators 2-D IIR filters with nearly linear phase in the passband. The design method is based on a balanced-realization model reduction technique. The nearly linear-phase 2-D IIR filter is designed using 2-D model reduction from a linear-phase 2-D FIR filter, which serves as the initial filter. The structured controllability and observability Gramians $P^s$ and $Q^s$ serve as the foundation for this technique. These Gramians are block diagonal positive-definite matrices that satisfy 2-D Lyapunov equations. An efficient method is used to compute these Gramians by minimizing the traces of $P^s$ and $Q^s$ under linear matrix inequalities (LMI) constraints. The use of these Gramians ensures that the resulting 2-D IIR filter preserves stability and can be implemented using a separable denominator 2-D filter with fewer coefficients than the original 2-D FIR filter. Numerical examples show that the proposed method compares favorably with existing techniques.

SARS-CoV-2 attachment and entry inside mammalian cells is mainly mediated by human angiotensin-converting enzyme 2 (ACE2) and its interaction with spike protein. However, it is well known that spike protein also interacts with other molecules like glycosaminoglycans (GAG), e.g., heparan sulfate (HS) or Enoxaparin (EX), which are linear, anionically charged polysaccharides known for their biological activities. The mode of action of these two polysaccharides is to bind spike protein to block the interaction with ACE2 receptors. This study aimed to assess a model capable of confirming the activity of these GAGs in both the wild-type strain of SARS-CoV-2 and its variants, such as the highly variable BA.2.86. This was achieved by combining in silico modeling with in vitro determination using BacMam technology. The results showed the antiviral activity of HS and EX both in vitro and through the in-silico analysis, reconciling conflicting findings from recent studies on the cellular entry of SARS-CoV-2. In conclusion, it is possible to highlight the ability of these molecules to circumvent the high variability of SARS-CoV-2, providing valuable insights into intervention strategies targeting cell entry mechanisms and establishing a safe in vitro model.

The COVID-19 pandemic caused by the SARS-CoV-2 virus has inflicted significant mortality and morbidity worldwide. Continuous virus mutations have led to the emergence of new variants. The Omicron BA.1 sub-lineage prevailed as the dominant variant globally at the beginning of 2022 but was subsequently replaced by BA.2 in numerous countries. Wastewater-based epidemiology (WBE) offers an efficient tool for capturing viral shedding from infected individuals, enabling early detection of potential pandemic outbreaks without relying solely on community cooperation and clinical testing resources. This study integrated RT-qPCR assays for detecting general SARS-CoV-2 and its variants levels in wastewater into a modified triple susceptible-infected-recovered-susceptible (SIRS) model. The emergence of the Omicron-BA.1 variant was observed, replacing the presence of its predecessor, the Delta variant. Comparative analysis between the wastewater data and the modified SIRS model effectively described the BA.1 and subsequent BA.2 waves, with the decline of the Delta variant aligning with its diminished presence below the detection threshold in wastewater. This study demonstrates the potential of WBE as a valuable tool for future pandemics. Furthermore, by analyzing the sensitivity of different variants to model parameters, we are able to deduce real-life values of cross-variant immunity probabilities, emphasizing the asymmetry in their strength.

Exacerbated inflammatory responses are a hallmark of severe coronavirus disease 2019 (COVID-19). Zileuton (Zi) is a selective inhibitor of 5-lipoxygenase, an enzyme involved in the production of several inflammatory/pro-resolving lipid mediators. Herein, we investigated the effect of Zi treatment in a severe acute respiratory syndrome (SARS) model. Mouse hepatitis virus (MHV)3-infected mice treated with Zi significantly improved the clinical score, weight loss, cardiopulmonary function, and survival rates compared with infected untreated animals. The protection observed in Zi-treated mice was associated with a lower inflammatory score, reduced dendritic cell-producing tumor necrosis factor (TNF), and increased neutrophil-producing interleukin (IL)-10 in the lungs 3 days after infection (dpi). At 5 dpi, the lungs of treated mice showed an increase in Th2-, Treg CD4+-, and Treg CD8+-producing IL-10 and reduced Th1 infiltrating cells. Furthermore, similar results were found upon Zi treatment after SARS-CoV2 infection in transgenic mice expressing the human angiotensin I-converting enzyme 2 (ACE2) receptor driven by the cytokeratin-18 (K18) gene promoter (K18-hACE2), significantly improving the clinical score, weight loss, and lung inflammatory score compared with untreated animals. Our data suggest that Zi protects against developing severe lung disease during SARS induced by betacoronavirus without affecting the host’s capacity to deal with infection.

In this paper, we present an extended version of the Hadi-Vencheh model for multiple criteria ABC inventory classification. The proposed model is a nonlinear weighted product model (WPM) which determines a common set of weights for all the items. Our proposed nonlinear WPM incorporates multiple criteria with different measure units, without converting the performance of each inventory item in terms of each criterion into a normalized attribute value, thereby providing an improvement over the model proposed by Hadi-Vencheh. Our study mainly includes various criteria for ABC classification, and demonstrates an efficient algorithm for solving nonlinear programming problems in which the feasible solution set does not have to be convex. The algorithm presented in this study improves the solution efficiency of the Canonical Coordinates Method (CCM) algorithm substantially when applied to large scale, nonlinear programming problems. The modified algorithm was tested to compare our proposed model results to the results derived using the Hadi-Vencheh model and demonstrate the algorithm's efficacy. The practical implications of the study are to develop an efficient nonlinear optimization solver by optimizing the quality of existing solutions, thus improving time and space efficiency.

Vaccine-induced immune thrombotic thrombocytopenia (VITT) is a rare but severe adverse event that was first observed during the global vaccination campaign against SARS-CoV-2 infection, specifically in those receiving adenoviral vector-based vaccines for Coronavirus disease 2019 (COVID-19). VITT develops 4 to 42 days post-vaccination and is characterized by the development of platelet-activating anti-platelet factor 4 (PF4) antibodies, leading to thrombocytopenia and thrombosis at unusual sites. The rise in awareness and subsequent prompt recognition of VITT was paramount in reducing mortality. Moreover, as vaccination campaigns around the world continue, a better understanding of VITT not only has important clinical implications but is also crucial for future vaccine development. In this review, we summarize the clinical features, pathophysiology, and incidence rates of VITT as well as highlight other anti-PF4 antibody-mediated disorders of growing clinical significance.

Background Candida auris is an emerging multidrug-resistant fungal pathogen that represents a serious threat to healthcare settings currently. Objective: Its objective was to determine the prevalence of C. auris in the hospital since its initial detection in late 2019. Methods: Using an adapted risk assessment tool, we reviewed the charts. and medical files of all suspected? and confirmed cases of C. auris cases reported at King Khalid University Hospital, Riyadh between November 2019 and December 2022. Anonymized data were retrieved in a pre-established datasheet and analyzed to determine the epidemiological characteristics of C. auris infection in our facility. We established our initial prevalence by age, gender, risk factors, and according to sampling source. Results: Of the 53 confirmed cases positive for C. auris during the study period, 33 (62%) were males. Their ages ranged between 15 and 98; most positive cases occurred in 50 and above. Only one of the confirmed cases was hospital-acquired. All patients had at least one risk factor, and Urine samples yielded the greatest number of positive cases while admission to healthcare facilities constituted the highest risk in our study. Conclusion: Establishing a local prevalence could serve as our baseline/benchmark to compare with regional and international benchmarks.

The theory of heterogeneous nucleation was initially developed as a part of condensed matter physics and later it was used as an important engineering tool to design metallurgical processes. The success leads to wide applications of the theory in metallurgical practice. For example, engineering heterogeneous nucleation in ductile iron has been used to reduce shrinkage defects, suppress cementite formation, and modify size and shape of micro-structural constituencies. This demonstrates how theoretical knowledge could benefit industry practice. This overview aims to summarize the authors’ published studies in co-authorship with colleagues and students, which covered different aspects of engineering heterogeneous nucleation in multiphase cast alloys. Several approaches for engineering heterogeneous nucleation using thermodynamic simulation and practical methods for improving efficiency of nucleation using co-precipitation technique and a local transient melt supersaturation were suggested. Automated Scanning Electron Microscopy Energy-Dispersive-X-ray (SEM/EDX) analysis and a high-resolution Transmission Electron Microscopy (TEM) were used to verify simulation predictions. Practical examples of controlling micro-porosity shrinkage in cast irons with spheroidal graphite are presented to illustrate the power of engineering heterogenous nucleation. The authors appreciate the great efforts that the co-authors have made on the original, overviewed articles here.

On April 17, 2019, a coach with tourists from Germany crashed in Madeira requiring repatriation by the German Air Force. The Advance Trauma Life Support (ATLS) concept was the central component of patient care. Data in Madeira were collected through a structured interview. The analysis of the Aeromedical Evacuation was based on intensive care transport records. In Germany all available were reviewed for data collection. Quality of life (HRQoL) was evaluated by the 12-item Short-Form Health Survey (SF-12). Twenty-eight prehospital patients were transported to the Level III Trauma Center in Funchal (Madeira). Five operative procedures were performed. Fifteen patients were eligible for Aeromedical Evacuation (AE). In the second hospital phase in Germany in total 82 radiological images and nine operations were performed. Hospital stay lasted 11 days (median, IQR 10–18). Median Follow-up (14 of 15 patients) was 16 months (IQR 16–21). 80% (8 out of 10) showed an increased risk for post-traumatic stress disorder (PTSD). Six key findings were identified in this study: divergent injury classification, impact of AE mission on health status, lack of communication, need of PTSD prophylaxis, patient identification, media coverage. Those findings may improve AE missions in the future e.g. required after armed conflicts.

One of the models that could be used to understand the adoption of vaccine uptake is the Health Belief Model (HBM). The aim of this study is to assess the role of HBM constructs and perceived health status (PHS) on vaccination status of individuals and to understand the role of socio-demographic variables on HBM scoring. A comparative cross-sectional telephone survey was conducted among 1,325 vaccinated (60.0%) and non-vaccinated (40.0%) vaccinated individuals aged 40 years and above in July 2021 in Punjab province, Pakistan. A higher level of education was the strongest predictor of positive HBM. All constructs of HBM, PHS and cues-to-action were significant predictors of COVID-19 vaccination uptake with perceived benefits as the strongest predictor. In order to expand the vaccination coverage, doubled pronged interventions utilizing both ICT and human resources should be designed that address each barrier perceived by individuals and understandably communicate the benefits of COVID-19 vaccine to the broader population.

Cinnamate 4-hydroxylase (C4H) is a cytochrome P450-dependent monooxygenase enzyme that catalyzes a key step in phenylpropanoid metabolism in plants. However, there is very limited information on the function of C4H in medicinal plants. In the present study, the C4H gene from the Ferula pseudalliacea genome (named FpC4H) was cloned and characterized. In addition, the expression levels of FpC4H in the roots, stems, leaves, flowers and seeds were investigated via real-time PCR. FpC4H showed the most similarity with C4H proteins from Daucus carota. The results predicted that FpC4H, as well as its orthologs, is an unstable and hydrophilic protein. A high genetic distance was observed between FpC4H and C4H from monocots based on evolutionary analysis. Moreover, a variable region related to the variable function of C4H was detected in conserved domain region of C4H proteins. Protein structure analysis revealed that isoleucine and leucine residues are frequently present in the binding region of FpC4H, and two ion binding regions, cysteine258 and asparagine217, were identified in the 3D structure of FpC4H. Expression analysis revealed that the FpC4H gene is expressed in all organs of F. pseudallicea. A low expression level of FpC4H was recorded in leaves, and a high expression level was observed in flower tissues. Based on the expression profile, FpC4H seems to be linked to a high content of phenolic compounds in flowers.

Chat generative pre-trained transformer (ChatGPT) is a developed language model and a subgroup of artificial intelligence (AI) which has demonstrated noticeable innovation in interactions between computer models and human studies. The release of ChatGPT in November 2022 attracted over 100 million users in a short time. It has unlimited applications in different fields of studies such as technology and science. ChatGPT utilizes deep learning and internet text to produce responses that resemble human language, although their accuracy is not always guaranteed. ChatGPT and GPT-4 can make a huge revolution in biology, medical, dental research, and health care. However, it's important to acknowledge the limitations of ChatGPT such as limitation in accessing the latest data. ChatGPT has generated both excitement and concern regarding its potential misuse. Its utilization in scientific publications has sparked debates and prompted the development of policies to govern the use of it. Although ChatGPT has certain limitations, it could impact on many different fields of study. There are challenges associated with using ChatGPT in the field of laboratory medicine and biology, particularly in the interpretation of test results. In this article, we review some of the applications of ChatGPT and GPT-4 in biology, dental and medical studies, and concerns about ChatGPT. Despite ChatGPT's conversational abilities are impressive, there are important considerations regarding its use in different fields of research and academic public.

A study has been carried out on Ta and Nb recovery by liquid-liquid extraction process using 4-methylacetophenone (4-MAcPh) as organic phase. The 4-MAcPh was compared to methylisobutylketone (MIBK) with respect to extraction efficiencies (kD values) at different concentrations of H2SO4 in the aqueous phase. The results showed a similar extraction of Nb for both solvents. However, for Ta extraction efficiency is increased by a factor of 1.3 for 4-MAcPh. In addition, the MIBK solubilized completely after 6 mol L-1 of H2SO4 against only a loss of 0.14 to 4% for 4-MAcPh between 6 and 9 mol L-1 of H2SO4. The potential of 4-MAcPh has also been studied to selectively recover Ta from a model capacitor waste solution. The results showed a selectivity for Ta in the presence of impurities such as Fe, Ni, Mn. The 4-MAcPh also presents the advantage of having physicochemical properties adapted to its use in liquid-liquid extraction technologies such as mixer-settlers.

Rapid Visual Screening (RVS) is a procedure that estimates structural scores for buildings and prioritize their retrofit and upgrade requirements. Despite the speed and simplicity of RVS, many of the collected parameters are non-commensurable and include subjectivity due to visual observations. It might cause uncertainties in the evaluation, which emphasizes the use of a fuzzy-based method. This study aims to propose a novel RVS methodology based on the interval type-2 fuzzy logic system (IT2FLS) to set the priority of vulnerable building to undergo detailed assessment while covering uncertainties and minimizing their effects during evaluation. The proposed method estimates the vulnerability of a building, in terms of Visual Damage Index, considering the number of stories, age of building, plan irregularity, vertical irregularity, building quality, and peak ground velocity, as inputs with a single output variable. Applicability of the proposed method has been investigated using a post-earthquake damage database of 28 reinforced concrete buildings from the Bingöl earthquake in Turkey.

The enzyme N-acetylgalactosamine-4-sulfatase (Arylsulfatase B; ARSB) was originally identified as a lysosomal enzyme which was deficient in Mucopolysaccharidosis VI (MPS VI; Maroteaux-Lamy Syndrome). Newly directed attention to the impact of ARSB in human pathobiology indicates a broader, more pervasive effect, encompassing roles as a tumor suppressor, transcriptional mediator, redox switch, and regulator of intracellular and extracellular-cell signaling. By controlling the degradation of chondroitin 4-sulfate and dermatan sulfate by removal or failure to remove the 4-sulfate residue at the non-reducing end of the sulfated glycosaminoglycan chain, ARSB modifies the binding or release of critical molecules into the cell milieu. These molecules, such as galectin-3 and SHP-2, in turn, influence crucial cellular processes and events which determine cell fate. Identification of ARSB at the cell membrane and in the nucleus expands perception of the potential impact of decline in ARSB activity. Regulation of availability of sulfate from chondroitin 4-sulfate and dermatan sulfate may also affect sulfate assimilation and production of vital molecules, including glutathione and cysteine. Increased attention to ARSB in mammalian cells may help to integrate and deepen our understanding of diverse biological phenomenon and to approach human diseases with new insights.

Immune checkpoint inhibition therapy (ICIT) is an emerging field in oncology especially opening new horizons to chemotherapy refractory patients. This paper provides deep insight into immune related adverse events (irAEs) posing a major challenge and drawback to ICIT, and presents right management strategies for very complex complications. Moreover, for the first time in literature, a non-linear mathematical model is introduced to measure the ICIT success rate and to decide about the optimum ICIT duration. Furthermore, a strategy is presented to overcome or to delay the progression after initial good response in a subset of patients.

The study investigated the application of Wastewater-Based Epidemiology (WBE) as a tool for monitoring SARS-CoV-2 prevalence in a city in Northern Italy from October 2021 to May 2023. Starting from a widely applied deterministic model, this study proposed a variation to take into account population characteristics and virus biodegradation in the sewer network. The model calculated virus loads and corresponding COVID-19 cases over time in different areas of the city and was validated with healthcare data while considering viral mutations, vaccinations, and testing variability. The correlation between the predicted and reported cases was high across the three waves that occurred in the considered period, demonstrating the model’s capacity to predict relevant fluctuations in the number of cases. Population characteristics did not substantially influence the predicted and reported infection rates. Conversely, biodegradation significantly reduced the virus load reaching the wastewater treatment plant, resulting in a 30% reduction in the total virus load produced in the study area. This approach can be applied for comparing virus load values across cities with varying population demographics and sewer network structures, enhancing the comparability of WBE data for effective surveillance and intervention strategies.

Background: Classical Hodgkin's lymphoma (cHL) is a lymph node disease, however, extranodal involvement is present in about 10% of affected individuals. Various forms of direct central nervous system (CNS) involvement have been reported, including intracranial, epidural, leptomeningeal, and intramedullary spinal cord cHL (Table 1). We hereby describe the clinical presentation, work up, and outcomes of two distinctive cases of cHL with intracranial extra-axial spread in patients receiving novel combination and traditional chemotherapy. Methods: This case series (n=2) was conducted following the CARE guidelines. Institutional review board (IRB) approved protocol #24-015 for HIPPA waiver of subjects in our retrospective study. Results: Patients with cHL exhibiting CNS symptoms or relapse refractory cases benefit from neuroimaging and excluding infectious etiologies. Suspicious lesions include iso- to hypointensity on T1 weighted and iso- to hyperintensity on T2 MR scans. Diagnosis is confirmed with biopsy. Treatment with A-AVD has shown more benefit than traditional ABVD chemotherapy. There has been shown progression free survival with nivolumab-AVD (N-AVD) over brentuximab-AVD (B-AVD). Conclusion: cHL with CNS involvement is rare and requires comprehensive workup to exclude infectious and other malignancies. Diagnosis relies on neuroimaging and subsequent brain biopsy. Treatment with novel N-AVD has shown greater PFS in patients with advanced cHL.

Footprints are powerful indicators for evaluating the impact of the bioeconomy of a country on environmental goods, domestically and abroad. In this study, we apply a hybrid approach combining a Multi-Regional Input-Output model and land use modelling to compute the agricultural land footprint (aLF). Furthermore, we added information on land-use change to the analysis and allocated land conversion to specific commodities. The German case study shows that the aLF abroad is larger by a factor of 2.5 to 3 than the aLF in Germany. In 2005 and 2010, conversion of natural and semi-natural land-cover types abroad allocated to Germany due to import increases was 2.5 times higher than the global average. Import increases to Germany slowed down in 2015 and 2020, reducing land conversion attributed to the German bioeconomy to the global average. The case study shows that the applied land footprint provides clear and meaningful information for policymakers and other stakeholders. The presented methodological approach can be applied to other countries and regions covered in the underlying database EXIOBASE. It can be adapted, also for an assessment of other ecosystem functions, such as water or soil fertility.

Biofilm-mediated infection is a major cause of bone prosthesis failure. The lack of molecules able to act in biofilms has driven research aimed at identifying new anti-biofilm agents via chemical screens. However, to be able to accommodate a large number of compounds, the testing conditions of these screenings end up being typically far from the clinical scenario. In this study, we assess the potential applicability of three anti-biofilm compounds (based on natural compounds) as part of implanted medical devices by testing them on in vitro systems that more faithfully resemble the clinical scenario. To that end, we used a competition model based on the co-culture of SaOS-2 mammalian cells and Staphylococcus aureus (collection and clinical strains) on a titanium surface. Additionally, we studied whether these derivatives of natural compounds enhance the previously proven protective effect of pre-incubating the titanium surface with SaOS-2 cells. Out of the three tested leads, one showed the highest potential, and can be regarded as a promising agent for incorporation into bone implants. This study emphasizes and demonstrates the importance of using meaningful experimental models, where potential antimicrobials ought to be tested for protection of biomaterials in translational applications.

Cerebral ischemic stroke is one of the leading causes of death and disability worldwide. 2’-fucosyllactose (2’-FL), a human milk oligosaccharide, has anti-inflammatory effects and plays a protective role in arterial thrombosis, but its role in ischemic stroke remains unclear. This study aimed to investigate the neuroprotective effects of 2’-FL and its potential mechanisms in a mouse model of ischemic stroke. The administration of 2’-FL led to a reduction in the size of cerebral infarct and reactive oxygen species (ROS)-related products in the brain of MCAO mice. Further, 2’-FL promotes the recovery of neurological deficits and motor function in neurological scores and behavior tests. Biochemical studies showed that 2’-FL reduced upregulated IL-10 and downregu-lated TNF-α. Additionally,2’-FL enhanced M2-type microglial polar2’-FL upregulated IL-10 and downregulated TNF-α ization at 7 days after MCAO, with an increase in IL-4 levels and STAT6 activation at 3 days after MCAO. Our data showed that 2’-FL reduced the neurological symptoms of ischemic stroke and ROS accumulation in the brain through IL-4/STAT6-dependent M2-type mi-croglial polarization in MCAO mice. These results demonstrate that 2’-FL is a potentially effective therapeutic agent for ischemic stroke.

A single Cancer immunotherapy has ushered in a transformative era in oncology, bringing forth unprecedented promise and opportunities. However, even with its significant breakthroughs, the domain faces the continual issue of treatment resistance. Such resistance not only restricts the broad effectiveness of these pioneering treatments but also highlights the imperative need for further research. Delving into the complex world of cancer immunotherapy resistance, we identify a range of mechanisms, from primary and secondary resistance to the notable effects of genetic and epigenetic variables, and the pivotal importance of the tumor microenvironment (TME). Additionally, we emphasize the need for innovative strategies to mitigate this resistance, including combination treatments, customized immune checkpoints, and instantaneous monitoring. By advocating for these cutting-edge methods, we foresee a direction that incorporates personalized healthcare, enhanced treatment options, and a steadfast dedication to the welfare of patients. Through a comprehensive and diverse approach, we aim to address the hurdles posed by resistance, elevating cancer immunotherapy as a symbol of hope for patients worldwide.

The field of mitochondrial genomics has advanced rapidly and revolutionized disciplines from molecular anthropology, population genetics, to medical/oncogenetics. However, mtDNA next-generation sequencing (NGS) analysis for matrilineal haplotyping and phylogeographic inference remains hindered by the lack of a consolidated, mitogenome database and efficient bioinformatics pipeline. To address this, we developed a customized human mitogenome database (hMITO DB) embedded in a CLC Genomics workflow for read mapping, variant analysis, haplotyping, and geo-mapping. The database was constructed from 4,286 mitogenomes. The macro-haplogroup (A to Z) distribution and representative phylogenetic tree were found consistent with published literature. The hMITO DB automated workflow was tested using mtDNA-NGS sequences derived from Pap smears and cervical cancer cell lines. The auto-generated read mapping, variants track, and table of haplotypes and geo-origins were completed in 15 min for 47 samples. The mtDNA workflow proved to be a rapid, efficient and accurate means of sequence analysis for translational mitogenomics.

We successfully fabricated Ag@Cu2O core-shell decorated on reduced graphene oxide (rGO) nanocomposites (ACRN) by a simple and convenient in situ substitution method. The properties of these ACRN with heterostructure layers were characterized by scanning and transmission electron microscopies and absorption spectroscopy. We used p-nitrophenol (4-NP) as a probe molecule to determine the chemical catalytic activity of the ACRN. Upon introduction of rGO, a high electron transfer efficiency was achieved; thus, the catalytic activity was improved significantly. Therefore, the ACRN exhibited significantly improved catalytic activity for the reduction of 4-NP and showed the high application value in the removal of toxic and harmful substances from water. In addition, the fabricated ACRN was used for the reduction of organic dyes and explosive pollutants to generate nontoxic products. Furthermore, the high charge redistribution and transfer among Ag, Cu2O and rGO in the ACRN induced the high catalytic reduction of organic pollutants, indicating the excellent potential of these materials for applications in water pollution treatment.

Various 4-aminotetrahydropyridinylidene salts were treated with aldehydes in alkaline medium. Their conversion to 5-substituted -hydroxyketones in a one-step reaction succeeded only with an aliphatic aldehyde. Instead, aromatic aldehydes gave 5-substituted -aminoketones or a single -diketone. The new compounds were characterized by spectroscopic methods and a single crystal structure analysis. Some of them showed anticancer and antibacterial properties.

A newly synthesized upper rim azocalix[4]arene, namely, 5,11,17,23-tetra[(4-ethylacetoxyphenyl) (azo)]calix[4]arene, CA-AZ was fully characterized and its chromogenic and selective properties for anions are reported. The receptor is selective for the fluoride anion and its mode of interaction in solution is discussed. The kinetics of the complexation process was found to be very fast as reflected in the immediate color change observed with a naked eye resulting from the receptor-anion interaction. Emphasis is made about the relevance in selecting a solvent in which the formulation of the process is representative of the events taking place in the solution. The composition of the fluoride complex investigated by UV/VIS spectrophotometry, conductance measurements and titration calorimetry was 1:1 and the thermodynamics of complexation was determined. The fluoride complex salt was isolated, and a detailed investigation was carried out to assess its ability to remove CO₂ from the air. Recycling of the complex was easily achieved. Final conclusions are given.

Excess hepatic lipid accumulation is the hallmark of non-alcoholic fatty liver disease (NAFLD), for which no medication is currently approved. However, Glucagon-Like Peptide-1 Receptor Ag-onists (GLP-1RAs), already approved for treating type 2 diabetes, have lately emerged as possible treatments. Herein we aimed to investigate how the GLP-1RA Exendin-4 (Ex-4) affects the mi-croRNA (miRNAs) expression profile using an in vitro model of steatosis. Total RNA, including miRNAs, was isolated from untreated, steatotic, and Ex-4-treated steatotic cells and used for probing a panel of 799 highly curated miRNAs using NanoString technology. Enrichment path-way analysis was used to find the signaling pathways and cellular functions associated with the differentially expressed miRNAs. Our data shows that Ex-4 reversed the expression of a set of miRNAs. Functional enrichment analysis highlighted many relevant signaling pathways and cellular functions enriched in the differentially expressed miRNAs, including hepatic fibrosis, in-sulin receptor, PPAR, Wnt/β-Catenin, VEGF, and mTOR receptor signaling pathways, fibrosis of the liver, cirrhosis of the liver, proliferation of hepatic stellate cells, diabetes mellitus, glucose metabolism disorder and proliferation of liver cells. Our findings suggest that miRNAs may play essential roles in the processes driving steatosis reduction in response to GLP-1R agonists, which warrants further functional investigations.

CD44 has been known as a marker of tumor initiating cells, and plays pro-tumorigenic functions in many cancers. The splicing variants play critical roles in malignant progression of cancers by promoting the stemness, cancer cell invasion or metastasis, and resistance to chemo- and radiotherapy. To understand each CD44 variant (CD44v) function is essential to know the property of cancers and establishment of the therapy. However, the function of the variant 4-encoded region has not to be elucidated. Therefore, specific monoclonal antibodies (mAbs) against the variant 4 are indispensable for basic research, tumor diagnosis, and therapy. In this study, we established anti-CD44 variant 4 (CD44v4) monoclonal antibodies (mAbs) by immunizing mice with a peptide containing the variant 4-encoded region. We next performed flow cytometry, western blotting, and immunohistochemistry to characterized them. One of the established clones (C₄₄Mab-108; IgG₁, kappa) reacted with CD44v3-10-overexpressed Chinese hamster ovary-K1 cells (CHO/CD44v3-10). The K_D of C₄₄Mab-108 for CHO/CD44 v3-10 was 3.4 × 10⁻⁷ M. In western blot analysis, C₄₄Mab-108 detected CD44v3-10 in the lysate of CHO/CD44v3-10 cells. Furthermore, C₄₄Mab-108 stained formalin-fixed paraffin-embedded oral squamous carcinoma tissues in immunohistochemistry. These results indicated that C₄₄Mab-108 is useful to detect CD44v4 in various applications.

Endoplasmic reticulum (ER) stress perturbs cell homeostasis and induces the unfolded protein response (UPR). In breast cancer, this process is activated by oestrogen deprivation and is associated with tamoxifen resistance. We present evidence that the transcription factor SOX2 and the long noncoding RNA SOX2 overlapping transcript (SOX2OT) are up-regulated in oestrogen receptor-positive (ER+) breast cancer and in response to oestrogen deprivation. We examined the effect of the UPR on SOX2 and SOX2OT expression, and the effect of SOX2OT on UPR pathways in breast cancer cell lines. The induction of the UPR by thapsigargin or glucose deprivation up-regulates SOX2OT expression. This up-regulation is also shown with the anti-oestrogen 4OH-tamoxifen and mTOR inhibitor everolimus in ER + breast cancer cells that are sensitive to oestrogen deprivation or everolimus treatment. SOX2OT overexpression decreased BiP and PERK expression. This effect of SOX2OT overexpression was confirmed on BiP and PERK pathway by q-PCR. Our results show that a long noncoding RNA regulates the UPR and evince a new function of SOX2OT as a participant of ER stress reprogramming of breast cancer cells.

Exposure to psychosocial stress is a risk factor for cardiovascular disease, including vascular aging, angiogenesis, and atherosclerosis-based cardiovascular disease (ACVD). Dipeptidyl peptidase-4 (DPP-4) is a complex enzyme (also called CD26) that acts as a membrane-anchored cell surface exopeptidase. DPP4 is upregulated in metabolic and inflammatory cardiovascular disorders. The widespread expression of DPP4 macrophages and immune cells and the noncatalytic function of DPP4 (also called CD26) as a signaling and binding protein across a wide range of species suggest a teleological role for DPP4 in inflammation and immune response. DPP-4 exhibits many physiological and pharmacological functions by regulating its extremely abundant substrates [e.g., stromal cell-derived factor-1α/ C-X-C chemokine receptor type-4, glucagon-like peptide-1 (GLP-1), etc.]. Over last ten year, emerging data demonstrated unexpected roles for GLP-1 and DPP-4 in extracellular and intracellular signaling, immune activation, inflammation, oxidative stress production, cell apoptosis, insulin resistance, and lipid metabolism,. This mini review has focuses on recent novel findings in this field, highlighting an imbalance between GLP-1 and DPP4 as a potential therapeutic molecular target in treatments of chronic psychological stress-related atherosclerotic cardiovascular disease in humans and animals.

The toxic effects of 4-octylphenol (4-OP) have been studied in species such as mouse and fish; however, the toxic effects of 4-OP in male specific niche cells has not been researched. In this study, we investigated the molecular mechanism of toxicity of 4-OP in mouse TM4 Sertoli cells. TM4 cells were treated with four concentrations (0, 10, 30, and 50 µM/mL) of 4-OP at time points 24, 48, and 72 h. Cell viability and apoptosis assay was conducted following exposure. 4-OP significantly decreased cell viability in a concentration- and time-dependent manner, and increased apoptosis. Quantitative PCR analysis showed that Bad, Bax, and Bak mRNA expression levels were higher in exposed cells than in the control, but Bcl-2 expression was decreased. Western blotting revealed that 4-OP induced activities of caspase-3 and phosphorylation of Bad in a concentration- and time-dependent manner. Additionally, cytochrome C protein did not colocalize with mitochondria marker dye by 24 h. Cytochrome c protein expression increased in a time-dependent manner with 50 µM/mL. These results suggest that 4-OP induces mitochondria-mediated apoptosis by regulation of Bcl-2 family proteins and caspase-3 activation in male Sertoli cells.

In the present study, we have systematically examined the clinical significance of Nectin-4 (encoded by the PVRL-4 gene), a marker for breast cancer stem cells (CSCs), in cancer metastasis and angiogenesis using a variety of human specimens, including invasive duct carcinoma (IDC) with multiple grades, several types of primary tumors to local and distant relapses, lymph node metastases and circulating tumor cells (CTCs). Nectin-4 was overexpressed in more than 92% of samples with 65.2% Nectin-4 positive cells. The level of expression was increased with increasing tumor grade (GI-III) and size (T1-4) of IDC specimens. More induction of Nectin-4 was noted in relapsed samples from a variety of tumors (colon, tongue, liver, kidney, ovary, buccal mucosa) in comparison to primary tumors, while paired adjacent normal tissues do not express any Nectin-4. A high expression of Nectin-4 along with other representative markers in CTCs and lymph node metastasis was also observed in cancer specimens. An increased level of Nectin-4 along with representative metastatic (CD-44, Sca1, ALDH1, Nanog) and angiogenic (Ang-I, Ang-II, VEGF) markers was noted in metastatic tumors (local and distant) in comparison to primary tumors that were correlated with different grades of tumor progression. In addition, greater expression of Nectin-4 was observed in secondary tumors (distant metastasis, e.g., breast to liver or stomach to gallbladder) in comparison to primary tumors. Nectin-4 was overexpressed at all stages of metastasis and angiogenesis, thus appearing to play a major role in tumor relapse through the PI3K-Akt-NFκβ pathway.

In this work, the solar light-induced redox photoactivity of the ZnO semiconductor material was used to prepare at room temperature CuxO-ZnO composite catalysts with a control of the chemical state of the copper oxide phase. The preparation of Cu2(I)O-ZnO and Cu(II)O-ZnO composite catalysts was achieved by using Cu(acac)2 in THF-water and Cu(NO3)2 in water as metallic precursor, respectively. Prior to the implementation of the photo-assisted synthesis method, the most efficient photoactive ZnO material was selected among different ZnO materials prepared by the low temperature polyol method and through the precipitation method with carbonates and carbamates as precipitation agent, by taking the photocatalytic degradation of the 4-chlorophenol compound in water under simulated solar light as model reaction. The ZnO support materials were characterized by XRD, BET, TGA, SEM and TEM, and the synthesis method was strongly influencing their photoactivity in terms of 4-chlorophenol degradation and of total organic carbon removal. The most photoactive ZnO material was prepared by precipitation with carbonates and calcined at 300°C, and was taking advantage of a high specific surface area and a small mean crystallite size for achieving a complete 4-chlorophenol mineralization within 70 min of reaction, with a minimum Zn2+ released to the solution due to surface photocorrosion. Beside thermal catalysis applications, this work opened a new route for the facile synthesis of Cu2O-ZnO heterojunction photocatalysts, that could take advantage under solar light of the heterojunction built between the p-type semi-conductor Cu2O with direct visible light band gap and the ZnO semiconductor phase.

Miscarriage due to blastocyst implantation failure occurs in up to two-thirds of all miscarriage cases in human. The calcium ion has been shown to be involved in many cellular signal transduction pathways as well as in the regulation of cell adhesion, which is necessary for the embryo implantation process. Exposure to endocrine-disrupting chemicals (EDs) during early gestation results in disruption of intrauterine implantation and uterine reception, leading to implantation failure. In this study, ovarian estrogen (E2), bisphenol A (BPA), or 4-tert-octylphenol (OP), with or without ICI 182,780 (ICI) were injected subcutaneously from gestation day 1 to gestation day 3 post-coitus. The expression levels of the calcium transport genes were assessed in maternal uteri and implantation sites. The number of implantation sites was significantly low in the OP group, and implantation sites were absent in the E2 and EDs+ICI groups. There were different calcium transient transport channel expression levels in uterus and implantation site samples. The levels of TRPV5 and TRPV6 gene expression were significantly increased by EDs with/without ICI treatment in uterus. Whereas, TRPV5 and TRPV6 gene expression were significantly lower in implantation sites samples. NCX1 and PMCA1 mRNA levels were significantly decreased by OP and BPA in the implantation site samples. Compared to vehicle treatment in uterus, both the MUC1 mRNA and protein levels were markedly high in all but the BPA group. Taken together, these results suggest that both BPA and OP can impair embryo implantation through alteration of calcium transport gene expressions and by affecting uterine receptivity.

This paper surveys estimates of the transmission features of the novel coronavirus, and then proposes a model to address sample-selection bias in estimated determinants of infection. Containment assumptions of the infection forecasting models depend on assumed effects of policies and self-regulating behavior. In the commons dilemma of the pandemic, the perceived ‘low risks’ of unregulated marginal choices do not reflect the full social cost, implying non-pharmaceutical interventions (NPI) to reduce mortality can enhance social welfare. As more economic activity renews with liftings of restrictive NPI (RNPI), a critical question concerns the ability of milder NPI (MNPI) and voluntary precautions to mitigate the risk of greater infections and deaths while also limiting the pandemic’s economic damage and its social costs. Ineffective NPI could lead to continued COVID-19 waves and new types of crises, worsened expectations and delayed economic recoveries. From the central range of surveyed estimates of transmission and alternative herd-immunity-threshold estimates, a ‘worst-case’ virus guidepost suggests eventual deaths of around 25 to 41 million worldwide and 1.1 to 1.7 million in the U.S. needed to reach herd immunity with no vaccine or treatment. The most optimistic study surveyed (theoretical model from a non-reviewed preprint study) combined with the low end of the range of the estimated mortality rate suggests 6 to 9 million deaths worldwide and 250 to 370 thousand in the U.S. to reach herd immunity. Successes in the mix of NPI, treatments, and vaccine can limit the eventual global death toll of the virus. Improved estimation models for forecasting and decision making may assist in better targeting the local timings and mix of NPI. Diagnostic tests for the virus have been largely limited to symptomatic cases, causing possible sample selection bias. A recursive bivariate probit model of infection and testing is proposed along with several possible applications from cross-section or panel-data estimation. Multiple potential explanatory variables, data sources, and estimation needs are specified and discussed.

We study the μ-μ45-T phase diagram of the 2+1-dimensional Gross-Neveu model, where μ denotes the ordinary chemical potential, μ45 the chiral chemical potential and T the temperature. We use the mean-field approximation and two different lattice regularizations with naive chiral fermions. An inhomogeneous phase at finite lattice spacing is found for one of the two regularizations. Our results suggest that there is no inhomogeneous phase in the continuum limit. We show that a chiral chemical potential is equivalent to an isospin chemical potential. Thus, all results presented in this work can also be interpreted in the context of isospin imbalance.

: The cyber-physical gap (CPG) is the difference between the 'real' state of the world and the way the system perceives it. This discrepancy often stems from the limitations of sensing and data collection technologies and capabilities, and is an inevitable issue in any cyber-physical system (CPS). Ignoring or misrepresenting such limitations during system modeling, specification, design, and analysis can potentially result in systemic misconceptions, disrupted functionality and performance, system failure, severe damage, and potential detrimental impacts on the system and its environment. We propose CPG-Aware Modeling & Engineering (CPGAME), a conceptual model-based approach for capturing, explaining, and mitigating the CPG, on top of and in sync with the conventional system model, and as an inherent systems engineering activity. This approach enhances the systems engineer’s ability to cope with CPGs, mitigate them by design, and prevent erroneous decisions, actions, and hazardous implications. CPGAME is a generic, conceptual approach, specified and demonstrated with Object Process Methodology (OPM). OPM is a holistic conceptual modeling paradigm for multidisciplinary, complex, dynamic systems, which is also ISO-19450. We analyze the 1979 Three Miles Island 2 nuclear accident as a prime example of the disastrous consequences of unmitigated CPGs in complex systems.

Early-season crop-type data are required for a variety of agricultural monitoring and decision-making applications. The early season in this study referred to the prophase and middle of a growth season. Early-season detection of crop types remains challenging because of limited discriminative features, especially for landscapes that are characterized by complex cropping patterns. In fact, different remote-sensing satellites can increase the frequency of data acquisition, which can provide more information in the early season. Moreover, optical and radar sensors have different degrees of sensitivity to crop parameters. Therefore, the integration and application of two types of multitemporal data are of great significance to improve the accuracy and timeliness of crop type detection.In deep learning (DL), convolutional neural network (CNN) and recurrent neural network (RNN) models have great potential for temporal feature extraction. Compared with RNNs, CNNs usually have fewer parameters and are more conducive to determining early-season detection dates of different crop types, which requires a lot of training because of the need to model on different dates. Nevertheless, revisit dates and temporal intervals of different satellites are usually different, resulting in different data acquisition time series; these data cannot be directly used as input for the same convolutional layer. To address this challenge, a Dual-1DCNN was bulit based on the CNN model in this study. Moreover, an incremental training method was used to attain the network on each data acquisition date and obtained the best detection date for each crop type in the early season. A case study for Hengshui City in China was conducted using time series of Sentinel-1A (S1A) and Sentinel-2 (S2). To verify this method, classical methods support vector machine (SVM) and random forest (RF) were implemented. The results demonstrated the following: (1) the Dual-1DCNN extracted discriminative features from S1A and S2 time series at the early season by producing the highest overall accuracy (OA: 87.23%); (2) for summer maize, cotton, and common yam rhizome, the Dual-1DCNN achieved F1 values of 92.39%, 87.71%, and 84.38%, respectively, at the early season (moreover, the early seasons were almost 40, 70, and 80 days before the end of the growth seasons, respectively). These findings suggested that the Dual-1DCNN is promising for the accurate and timely detection of crop types.

It is very difficult to accurately divide farmland and woodland in Gaofen 2 (GF-2) remote sensing image, because their single plant coverage is very small, and their spectra are very similar. The ratio of spatial resolution and one plant’s coverage area must be fully taken into account when designing the Convolutional Neural Network structure for extracting them from GF-2 image. We establish a Convolutional Encode Neural Networks model (CENN), The first layer has two sets of convolution kernels to learn the characteristics of farmland and woodland respectively, while the second layer is the encoder to encode the characteristics by transfer function, which can map the results to the corresponding category number. In the training stage, samples of farmland, woodland, and other categories are categorically used to train CENN, as soon as training is accomplished, CENN would acquire enough ability to accurately extract farmland and woodland from remote sensing images. The final extraction result is obtained by implementing per-pixel segmentation of images used to train the CENN. CENN is compared and analyzed with others such as Deep Belief Network (DBN), Full Convolutional Network (FCN), Deeplab Model. The results of experiments show that CENN can more accurately mine the characteristics of farmland and woodland, and it achieves its goal of extracting farmland and woodland with high precision from GF-2 images.

Lodging is a common problem in maize production that seriously impacts yield, quality, and the capacity for mechanical harvesting. Evaluation of site-specific lodging risks requires establishment of a method for multi-year monitoring. In this study, spectral images collected by the Sentinel-2 satellite were processed to obtain three types of data: gray-level co-occurrence matrix texture (GLCM), vegetation indices (VIs), and spectral reflectance (SR). Lodging classification models were then established with Random Forest (RF) using each of the three data types separately (the GLCM, VI, and SR models) and in combination (SR+VI model, SR+GLCM model, VI+GLCM mod-el, and SR+VI+GLCM model). By gradually removing features with low importance scores from the SR+VI+GLCM model and analyzing the changes in the overall accuracy (OA), the optimal set of predictive variables was identified and used to construct the optimal model. A model built us-ing data from a single timepoint in 2021 was tested on data collected at a similar timepoint in 2019 and vice versa to assess interannual model generalizability. The results of this study demon-strate that for monitoring maize lodging, models constructed with a single feature type, the GLCM model had significantly lower accuracy compared to the VI and SR models. During certain growth stages, the model constructed with combined features had significantly higher accuracy in monitoring maize lodging compared to models constructed with a single feature. During the pro-cess of selecting the optimal predictive variables, it was found that the accuracy of the model did not increase as the number of predictive variables increased. The results show that the positive and negative validation models had an accuracy of 96.55% and 95.18%, with kappa values of 0.93 and 0.83, respectively. This indicates that the model has strong generality for the same repro-ductive stage between years. This study provides a detailed method for large-scale maize lodging monitoring, allowing for identification of optimal planting practices to reduce the probability of lodging and ultimately improving regional maize yield and quality.

Metabolomics profiling for accurate and reliable quantification of organic acids that carry a carboxylic acid functional group in complex biological samples, remains a major analytical challenge in clinical chemistry research. Several procedural barriers associated with quantification of clinically important carboxylic containing metabolites (CCMs) including spontaneous decarboxylation during ionization, poor chromatographic resolution, and retention on a reverse-phase column, limit the sensitivity, specificity, and reproducibility of multiple-reaction monitoring (MRM) based LC-MS assay development. We report a targeted metabolomics-based analytical method for the quantification of CCMs using phenylenediamine derivatization. Accurate and sensitive quantification of CCMs is successfully demonstrated in an array of biological matrices. Recovery of metabolites from different matrices (plasma, serum, urine, saliva, tissues, and cell extracts), ranged from 90% to 105%, with all the CVs ≤ 10%. The method showed linearity over a broad dynamic range from 0.1 ng/mL to 10 µg/mL with linear regression coefficients of 0.99 for most of the metabolites tested herein, that covers broad-based applicability with the analysis of biological samples. In most cases the LODs were as low as 0.01 ng/mL. The phenylenediamine-based derivatization of carboxyl acid library consisting of more than 70 endogenous metabolites was constructed for metabolite identification, which spanned more than 40 biological pathways. The library included a wide-variety of structurally variant CCMs such as amino acids/conjugates, short to medium chain organic acids, di/tri-carboxylic acids/conjugates, fatty acids and some ring-containing CCMs. We compared the CCMs profiles of pancreatic cancer cells with normal pancreatic epithelial cells to test and validate the biological utility of this method. The comparative profiling between cancerous and normal cells resulted in the identification of potential biomarkers in pancreatic cancer, and their correlation with several key metabolic pathways such as central carbon energy metabolism, protein metabolism, including TCA cycle, glycolysis, Gln-Glu pathway, and biosynthesis of amino acids and unsaturated fatty acids was established. The method, described herein, for the first time enables the sensitive and highly specific quantification of CCMs on small sample size with high reproducibility in a high throughput manner. Given the biological and functional significance of this class of metabolites, this mass spectrometry based targeted quantitative assay, fills an important gap and is likely to support a wide range of applications for basic, clinical, and translational research.

The reactivity of 3,5-di-(pyridin-4-yl)-1,2,4-thiadiazole (L1) with 1,4-diiodotetrafluorobenzene (1,4-DITFB) was explored and the halogen-bonded 1:1 co-crystal (1) was successfully isolated and structurally characterized.

We describe the development and validation of a HPLC-MS/MS method to assess the pharmacokinetics and tumour distribution of fenretinide, a synthetic retinoid chemically related to all-trans-retinoic acid, after administration of a novel oral nanoformulation of fenretinide, called bionanofenretinide (BNF). BNF was developed to overcome the major limitation of fenretinide: its poor aqueous solubility and bioavailability due to its hydrophobic nature. The method proved to be reproducible, precise, and highly accurate for the measurement of the drug and the mains metabolites. The lower limit of quantification resulted 1 ng/mL. The curve range of 1-500 ng/mL and 50-2000 ng/mL, for plasma and tumor homogenate respectively, was appropriate for the analysis, as demonstrated by the accuracy between 96.8% and 102.4% for plasma and 96.6-102.3% for tumor. The inter-days precision and accuracy determined on quality controls at 3 different levels were in ranges of 6.9%-7.5% and 99.3-101.0% and 0.96-1.91% and 102.3-105.8% for plasma and tumour, respectively.

The prevalent pathogens associated with bovine uterine infections are bacteria that appear to increase the host's susceptibility to secondary infections with other bacteria or viruses, among which BoHV-4 is the most frequently found. In this work, the study of the pathways of apoptosis induction was carried out on an experimental model of primary culture of endometrial cells, in order to know the implication of BoHV-4 and the presence of bacterial LPS in the pathogenesis of the bovine reproductive tract. For this, different staining techniques and molecular analysis by RT-PCR were used. The results obtained allowed us to conclude that the level of cell death observed in the proposed primary culture is directly related to the time of viral infection and the presence of LPS in BoHV-4 infection. The apoptosis indices in cells infected with BoHV-4, BoHV-4 + LPS presented a maximum that correlates with the appearance of the cytopathic effect, and the maximum viral titers in the model studied. However, morphological, biochemical and molecular changes were evident during both early and late stages of apoptosis. These findings provide information on the factors that may influence the pathogenesis of BoHV-4 and help to better understand the mechanisms involved in virus infection.

The emergence of resistance to first-line antimalarial drugs calls for development of new therapies for drug-resistant malaria. The efficacy of quinoline-based antimalarial drugs has prompted the development of novel quinolines. A panel of 4-aminoquinoline hydrazone analogues were tested on Plasmodium falciparum strains: IC50 values after a 48-hour cycle ranged from 0.60 - 49 µM, while the 72-hour cycle ranged from 26-219 nM on the multi-drug resistant K1 strain. Time-course assays were carried out to define the activity of the lead compounds which inhibited over 50 % growth in 24 hours and 90% growth in 72 hours. Cytotoxicity assays with HepG2 cells showed IC50 values of 0.87-11.1 M, whereas in MDBK cells IC50 values ranged from 1.66-11.7 M. High selectivity indices were observed for the lead compounds screened at 72 hours on P. falciparum. Analyses of stage-specificity revealed that the ring stage of the parasite life cycle were most affected. Based on antimalarial efficacy and in vitro safety profiles, lead compound 4-(2-benzylidenehydrazinyl)-6-methoxy-2-methylquinoline 2 was progressed to drug combination studies for the detection of synergism, with a combinatory index of 0.599 at IC90 for the combination of with artemether, indicating a synergistic antimalarial activity. Compound 2 was screened on different strains of P. falciparum (3D7, Dd2) which maintained similar activity to K1, suggesting no cross-resistance between multi-drug resistance and sensitive parasite strains. In vivo analysis with 2 showed suppression of parasitaemia with P. yoelii NL treated mice (20 mg/kg and 5 mg/kg).

Cytokines secreted by individual immune cells regulate tissue regeneration and allow communication between various cell types. Cytokines bind to cognate receptors and trigger the healing process. Determining the orchestration of cytokine interactions with their receptors on their cellular targets is essential to fully understand the process of inflammation and tissue regeneration. To this end, we have investigated the interactions of Interleukin-4 cytokine (IL-4)/Interleukin-4 cytokine receptor (IL-4R) and Interleukin-10 cytokine (IL-10)/Interleukin-10 cytokine receptor (IL-10R) using in situ Proximity Ligation Assays in a regenerative model of skin, muscle and lung tissues in the mini-pig. The pattern of protein-protein interactions was distinct for the two cytokines. IL-4 bound predominantly to receptors on macrophages and endothelial cells around the blood vessels while the target cells of IL-10 were mainly receptors on muscle cells. Our results show that in situ studies of cytokine-receptor interactions can provide unravel the fine details of the mechanism of action of cytokines.

There is an urgent need to better understand the mechanisms involved in scar formation in brain. It is well known that astrocytes are critically engaged in this process. Here we analyze in-cipient scar formation one week after a discrete ischemic insult to the cerebral cortex. We show that the infarct border zone is characterized by pronounced changes in the organization and subcellular localization of the major astrocytic protein AQP4. Specifically there is a loss of AQP4 from astrocytic endfoot membranes that anchor astrocytes to pericapillary basal laminae and a disassembly of the supramolecular AQP4 complexes that normally abound in these membranes. This disassembly may be mechanistically coupled to a downregulation of the newly discovered AQP4 isoform AQP4ex. AQP4 has adhesive properties and is assumed to facilitate astrocyte mo-bility by permitting rapid volume changes at the leading edges of migrating astrocytes. Thus, the present findings provide new insight in the molecular basis of incipient scar formation.

Bacterial infections are world-wide problem and resistant bacteria is increasing globally that lead to treatments failure. Thus, it is important to find new techniques that are effective for the treatment antibiotic-resistant microorganisms. Green medicine used for the medication of different bacterial infection. Therefore , the study aimed to evaluate the immunomodulatory activity of essential fatty acid semi carbazide (EFASC) compounds extracted from flaxseed to eradicate resistance pathogens . Crud extracts of Linum usitatissimum was extracted by hexane for extraction of EFASC. The results of LD₅₀ appear that a live suspension of E.coli was 0.49×10⁷ ,while HK E.coli was 10⁸ , 125 mg /ml were the optimum dose in stimulate immune response of EFASC which gave maximum dose of total WBC , Neutrophil and Monocyte count. The immunomodulatory activity appear that E.coli + EFASC released moderate levels of IL-4 . HK E.coli release higher IL-4 lead to increase the hypersensitivity and hyper responses of immune system. HK + EFASC immunogen revealed moderate increased in IL-12 mean level 0.99 pg /ml, HK bacteria recorded 1.49 pg/ml, while the mean of EFASC revealed no significant different compare with control. An effective protection was observed in immunized groups with HK E.coli and EFASC challenged with 100 of LD50 of a live E.coli.

To cope the high glycemic variability (GV) is crucial in the management of multiple daily insulin (MDI) in diabetes. We compared the effect of low dose metformin 750mg/d adding vildagliptin 100mg/d (DPP4+LMET) or the high dose metformin 1500mg/d (HMET), in type 2 diabetes (T2D) with MDI, evaluating GV by continuous glucose monitoring (CGM). Single center, open-label, 12 weeks - 2 period crossover design. Twenty T2D with inadequately controlled (7.0% <HbA1c ≦9.0%) with MDI + LMET were enrolled. Primary endpoints were GV and hypoglycemia derived from CGM performed after each 12 weeks treatment periods. There was no significant difference in HbA1c, body weight changes, total daily dose of insulin. DPP4+LMET compared to the HMET, significantly reduced the calculated GV value, mean (7.15±1.3 vs 7.82±1.6, p<0.05), standard deviation (1.78±0.55 vs 2.27±1.11, p=0.03), continuous overlapping net glycemic action (6.44±1.28 vs 7.12±1.69, p<0.05), J-Index (26.7±11.0 vs 34.9±19.8, p<0.05), high blood glucose index (3.01±1.96 vs. 6.73±4.85, p=0.02), and mean amplitude of glycemic excursions (4.53±1.35 vs 5.50±2.34, p=0.03). The GV metrics with hypoglycemia and nocturnal hypoglycemia were not significantly different. DPP4+LMET decreased GV associated with hyperglycemia. Adding DPP4 inhibitor to the lower dose of metformin is an alternative approach to the stable GV in MDI.

Cartilage regeneration requires a balance of anabolic and catabolic processes. This study examined the susceptibility of fibromodulin (FMOD) and lumican (LUM) to degradation by MMP-13, ADAMTS-4 and ADAMTS-5, the three major degradative proteinases in articular cartilage in osteoarthritis (OA). Immunolocalisation of FMOD and LUM in foot sections of developmental cartilages demonstrated prominent localisations in metatarsal and phalangeal foetal rudiment cartilages and growth plate. An MMP-13 neoepitope antibody (TsYG11) demonstrated localisation of MMP-13 cleaved FMOD in the hypertrophic chondrocytes of the metatarsal growth plate. FMOD was more prominently localised in the superficial cartilage of normal and fibrillated zones in OA cartilage, TsYG11 positive FMOD was located deeper in the cartilage samples. Ab TsYG11 also identified FMOD fragmentation in Western blots of extracts of normal and fibrillated cartilage and total knee replacement OA cartilage. The C-terminal anti-FMOD used in this study (PR-184) failed to identify FMOD fragmentation due to C terminal processing, an equivalent Ab to the C-terminus of LUM (pAb PR-353) identified 3 prominent LUM fragments in OA human knee cartilages. In-vitro digestion of human knee cartilage with MMP-13, ADAMTS-4 and ADAMTS-5 generated equivalently sized FMOD fragments of 54, 45 and 32kDa to those in blots of OA cartilage, LUM was not less susceptible to fragmention in in-vitro digestions however Ab PR-353 detected N-terminally processed LUM fragments of 39, 38 and 22 kDa in 65-80 year old OA knee cartilage. FMOD and LUM were differentially processed during in-vitro digestions with MMP-13, ADAMTS-4 and ADAMTS-5 with FMOD susceptible to degradation by MMP-13, ADAMTS-4 and to a lesser extent ADAMTS-5 however LUM was less susceptible to fragmentation. FMOD was processed by MMP-13 in metatarsal and phalangeal foetal rudiment developmental cartilages and growth plate indicating a role in skeletogenesis.

Herein, two title compounds, N-Benzoyl-N’-4-cyanophenyl thiourea (I) and N-(4-nitrobenzoyl)-N’-4-cyanophenyl thiourea (II) were synthesized in high yield, via aroyl isocyanate and 4-aminobenzonitrile. The structure of the prepared compounds was characterized by elementary analysis and FT-IR, ¹H, ¹³C NMR spectroscopic methods. Cyclic voltammetric (CV) experiments were performed with glassy carbon electrode. The reduction potential values of different functional group such as nitro, cyano in title compounds were investigated using CV curves.

Renal cell carcinoma (RCC) is the most common kidney cancer, accounting for approximately 80–90 % of all primary kidney cancer. Treatment for patients with advanced RCC remains unsatisfactory. Rare cancer stem cells (CSCs) are proposed to be responsible for failure of current treatment. Here, we investigate the effects of CBFA2T2 on CSCs regulation in RCC, as well as to elucidate the possible mechanisms. We showed that CBFA2T2 expression can significantly predict the survival of RCC patients. Functional assays showed that knocking-down of CBFA2T2 can inhibit cell migration and invasion in 786-O and A-498 cells in vitro, and reduce ALDH^high CSCs populations. Furthermore, CBFA2T2 expression is necessary for sphere-forming ability and cancer stem cells marker expression in RCC cell lines. Collectively, our data suggest that CBFA2T2 expression correlates with aggressive characteristics of RCC and CBFA2T2 is required for maintenance of “stemness” through regulation of stem cells factors, thereby highlighting CBFA2T2 as a potential therapeutic target for RCC treatment.

We review consequences for the radiation and dark sectors of the cosmological model arising from the postulate that the CMB is governed by an SU(2) rather than a U(1) gauge principle. We also speculate on the possibility of actively assisted structure formation due to the de-percolation of lump-like configurations of condensed ultralight axions with a Peccei-Quinn scale comparable to the Planck mass. The chiral-anomaly induced potential of the axion condensate receives contributions from SU(2)/SU(3) Yang-Mills factors of hierarchically separated scales which act in a screened (reduced) way in confining phases.

The coronavirus disease 2019 (COVID-19) is the fastest transmittable virus caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The detection of COVID-19 using artificial intelligence techniques and especially deep learning will help to detect this virus in early stages which will reflect in increasing the opportunities of fast recovery of patients worldwide. This will lead to release the pressure off the healthcare system around the world. In this research, classical data augmentation techniques along with CGAN based on a deep transfer learning model for COVID-19 detection in chest CT scan images will be presented. The limited benchmark datasets for covid-19 especially in chest CT images is the main motivation of this research. The main idea is to collect all the possible images for covid-19 that exists until the very writing of this research and use the classical data augmentations along with CGAN to generate more images to help in the detection of the COVID-19. In this study, five different deep convolutional neural network-based models (AlexNet, VGGNet16, VGGNet19, GoogleNet, and ResNet50) have been selected for the investigation to detect the coronavirus infected patient using chest CT radiographs digital images. The classical data augmentations along with CGAN improve the performance of classification in all selected deep transfer models. The Outcomes show that ResNet50 is the most appropriate deep learning model to detect the COVID-19 from limited chest CT dataset using the classical data augmentation with testing accuracy of 82.91%.

The coronavirus (covid-19) pandemic is putting healthcare systems across the world under unprecedented and increasing pressure according to the World Health Organization (WHO). With the advances in computer algorithms and especially Artificial Intelligence, the detection of this type of virus in the early stages will help in fast recovery and help in releasing the pressure off healthcare systems. In this paper, a GAN with deep transfer learning for coronavirus detection in chest x-ray images is presented. The lack of benchmark datasets for covid-19 especially in chest x-rays images is the main motivation of this research. The main idea is to collect all the possible images for covid-19 that exists until the writing of this research and use the GAN network to generate more images to help in the detection of the virus from the available x-rays images with the highest accuracy possible. The dataset used in this research was collected from different sources and it is available for researchers to download and use it. The number of images in the collected dataset is 307 images for four different types of classes. The classes are the covid-19, normal, pneumonia bacterial, and pneumonia virus. The dataset is divided into 90% for the GAN and the training and the validation phase, while 10% used in the testing phase. The GAN helps in generating more images from the original dataset to be 30 times larger than the originally collected dataset. The GAN also help in overcoming the overfitting problem and made the proposed model more robust. Three deep transfer models are selected in this research for investigation. The models are the Alexnet, Googlenet, and Restnet18. Those models are selected based on their small number of layers on their architectures, which will reflect in reducing the complexity of the models and the consumed memory and time. Using a combination of GAN and deep transfer models prove it is efficiency according to validation, testing accuracy, and performance measurements such as precision, recall, and F1 score. Three case scenarios are tested through the paper, the first scenario which includes 4 classes from the dataset, while the second scenario includes 3 classes and the third scenario includes 2 classes. All the scenarios include the covid-19 class as it is the main target of this research to be detected. In the first scenario, the Googlenet is selected to be the main deep transfer model as it achieves 80.6% in testing accuracy. In the second scenario, the Alexnet is selected to be the main deep transfer model as it achieves 85.2% in testing accuracy, while in the third scenario which includes 2 classes(covid-19, and normal), Googlenet is selected to be the main deep transfer model as it achieves 100% in testing accuracy and 99.9% in the validation accuracy. All the performance measurement strengthen the obtained results through the research. Finally, this research may be considered one of the first trails to use GAN and deep transfer models together to help in detecting coronaviruses (covid-19) within the absence of a benchmark dataset around the world, especially in x-rays chest images.

Overhydration (OH) is a common medical problem found in patients with kidney or heart failure, but still a specific marker has not been found. Clinicians today use bioimpedance spectroscopy (BIS), ultrasound (US) markers of fluid overload or markers of heart and kidney function like NT-pro-BNP, GFR or creatinine levels. New serum markers such as Ca-125, Galectin-3 (Gal-3), Adrenomedullin (AMD) and Urocortin-2 (UCN-2), are being researched with promising results. The need to discover a more precise marker of overhydration is dire mainly because physical examination is extremely imprecise. Signs and symptoms of fluid overload like edema or gradual increase of body mass are not always present, especially in patients with chronic kidney disease. This review paper summarizes actual knowledge of a patient's hydration status estimation focusing especially on kidney diseases.

C-type lectin CD209/DC-SIGN and CD209L/L-SIGN proteins are distinct cell adhesion and pathogen recognition receptors that mediate cellular interactions and recognize a wide range of pathogens including, viruses such as SARS, SARS-CoV-2, bacteria, fungi and parasites. Pathogens exploit CD209L family proteins to promote infection and evade the immune recognition system. CD209L and CD209 are widely expressed in SARS-CoV-2 target organs and can contribute to infection and pathogenesis. CD209L family receptors are highly susceptible to alternative splicing and genomic polymorphism, which may influence virus tropism and transmission in vivo. The carbohydrate-recognition domain (CRD) and the neck/repeat region represent the key features of CD209L family proteins that are also central to facilitating cellular ligand interactions and pathogen recognition. While, the neck/repeat region is involved in oligomeric dimerization, the CRD recognizes the mannose containing structures present on specific glycoproteins such as those found on the SARS-CoV-2 spike protein. Considering the role of CD209L and related proteins in diverse pathogen recognition, this review article discusses the recent advances in the cellular and biochemical characterization of CD209 and CD209L and their roles in viral uptake, which has important implications in understanding the host-pathogen interaction, the viral pathobiology and driving vaccine development of SARS-CoV-2.

The abundant mechanical vibration energy in bridge road environment can be converted into electric energy by using the piezoelectric energy harvest technology, which could be an efficient way to provide energy required by the wireless sensor network in the bridge condition monitoring system. An autonomous energy harvesting system has been designed based on cantilever beams for sensing and acquiring the bridge vibration energy. After the analysis of the dynamic properties of the piezoelectric cantilever beam in the energy conversion, three kinds of interface circuits were compared through simulation and experimental results. It was shown that the VD interface circuit has less power loss. Furthermore, the proposed closed loop control method based on the VD circuit was simple, adaptive, and self-powered, which is suitable for the road energy harvesting application. Finally, the energy harvesting system based on VD circuit was realized with harvested power of around 0.8mW.

Human sepsis is one of the leading cause of death worldwide and is known to be a harmful damaging host inflammatory condition, primarily caused by endotoxin released by gram-negative bacteria. Despite antibiotics administration being widely used to treat disease, effective targeted therapeutic strategies for the sepsis are still lacking. Here, we demonstrate that CM1, a derivative of natural polyphenol chrysin, exerts anti-inflammatory activity by inducing the ubiquitin-editing protein TNFAIP3 and NAD-dependent deacetylase sirtuin 1 (SIRT1). We found that CM1 attenuated Toll-like receptor 4 (TLR4)-induced the generation of inflammatory cytokines by inhibiting the extracellular-signal-regulated kinase (ERK)/MAPK and nuclear factor kappa B (NF-κB) signaling pathway. In addition, the treatment of macrophages with CM1 induced the expression of TNFAIP3 and SIRT1 in TLR4-stimulated primary macrophages, however the anti-inflammatory properties of CM1 was disappeared by siRNA silencing of TNFAPI3 or by the genetic and pharmacologic inhibition of SIRT1. Importantly, intravenously administration of CM1 resulted in the decreased susceptibility to endotoxin-induced sepsis, leading to inhibition of the generation of proinflammatory cytokines and neutrophils infiltration into lung than control mice. Collectively, these findings suggest that CM1 has the potential to be a treatment candidate for diverse inflammatory diseases including sepsis.

Oncostatin M (OSM), an inflammatory cytokine belonging to interleukin-6 superfamily, is recognized as an essential factor secreted by osteal macrophages to orchestrate bone remodelling. Osteoprotegerin (OPG) produced by osteoblasts regulates osteoclastogenesis. We previously demonstrated that bone morphogenetic protein-4 (BMP-4) stimulates OPG synthesis in osteoblast-like MC3T3-E1 cells, and that SMAD1/5/8(9), p38 mitogen-activated protein kinase (MAPK), and p70 S6 kinase positively regulates the OPG synthesis. The present study is aimed to investigate the effect of OSM on BMP-4-stimulated OPG synthesis in osteoblasts. OSM suppressed the release and the mRNA expression of OPG upregulated by BMP-4 in MC3T3-E1 cells.  Neither the BMP-4-induced phosphorylation of SMAD1/5/9 nor that of p38 MAPK affected by OSM. On the other hand, the BMP-4-stimulated phosphorylation of p70 S6 kinase was considerably suppressed by OSM. These results strongly suggest that OSM suppresses the BMP-4-stimulated OPG synthesis via inhibition of the p70 S6 kinase-mediated pathway in osteoblasts.

(1) Background: The aim of this study was to analyze the relationship between the serum levels of soluble transferrin receptor (sTfR) and interleukin 4 (IL-4), and disease activity and organ mani-festations in SLE patients. (2) Methods: We studied 200 SLE patients and 50 controls. We analyzed disease activity, organ involvement, serum sTfR, IL-4, and interleukin-6 (IL-6) levels, and antinu-clear and antiphospholipid antibody profiles. (3) Results: The median serum levels of sTfR (p>0.000001) and IL-4 (p<0.00001) were higher in the study group than in the controls. SLE patients, compared to the controls, had significantly lower HGB levels (p<0.0001), a lower iron concentration (p=0.008), a lower value of total iron-binding capacity (TIBC) (p=0.03), and lower counts of RBC (p=0.004), HCT (p=0.0004), PLT (p=0.04), neutrophil (p=0.04), and lymphocyte (p<0.0001). Serum sTfR levels were negatively correlated with lymphocyte (p=0.0005), HGB (p=0.0001) and HCT (p=0.008), and positively correlated with IL-4 (p=0.01). Elevated serum sTfR >2.14 mg/dL was associated with an increased risk of myocardial infarction (OR: 10.6 95 CI 2.71–464.78; p=0.001), ischemic heart disease (OR: 3.25 95 CI 1.02–10.40; p=0.04), lung manifestations (OR: 4.48 95 CI 1.44–13.94; p=0.01), and hematological manifestations (OR: 2.07 95 CI 1.13–3.79; p=0.01), and with a reduced risk of neuropsychiatric manifestations (OR: 0.42 95 CI 0.22–0.80; p=0.008). Serum IL-4 was negatively correlated with CRP (p=0.003), and elevated serum IL-4 levels > 0.17 mg/l were associated with a reduced risk of mucocutaneous manifestations (OR: 0.48 95 CI 0.26–0.90; p=0.02). (4) Conclusions: In SLE patients, elevated serum levels of sTfR were associated with an increased risk of cardiovascular, pulmonary, and hematological manifestations, and with a decreased risk of neuropsychiatric manifestations. In contrast, elevated serum IL-4 levels were associated with a decreased risk of mucocutaneous manifestations.

CD44 is a type I transmembrane glycoprotein, and possesses various isoforms which are largely classified into CD44 standard and CD44 variant (CD44v) isoforms. Some variant-encoded regions play critical roles in tumor progression. However, the function of CD44 variant 4 (CD44v4)-encoded region has not been fully understood. Using peptide immunization, we developed an anti-CD44v4 mAb, C₄₄Mab-108, which is useful for flow cytometry, western blotting, and immunohistochemistry. In this study, we determined the critical epitope of C₄₄Mab-108 by enzyme-linked immunosorbent assay (ELISA). We used the alanine (or glycine)-substituted peptides of the CD44v4-encoded region (amino acids 271-290 of human CD44v3-10), and found that C₄₄Mab-108 did not recognize the alanine-substituted peptides of D280A and W281A. Furthermore, these peptides could not inhibit the recognition of C₄₄Mab-108 in flow cytometry and immunohistochemistry. The results indicate that the critical binding epitope of C₄₄Mab-108 includes Asp280 and Trp281 of CD44v3-10.

Novel effluent treatment solutions for dangerous organic pollutants are crucial worldwide. In recent years, chemical reduction using noble metal-based nanocatalysts and NaBH4, a reducing agent, has become common practice for eliminating organic contaminants from aquatic environments. We suggest a straightforward approach to synthesizing magnetic cellulose nanocrystals (CNC) modified with magnetite (Fe3O4) and silver nanoparticles (Ag NPs) as a catalyst for organic contamination removal. Especially, Ag NPs were decorated on the CNC surface without reducing agents or stabilizers by reducing AgNO3. XRD, FE-SEM, TEM, EDX, VSM, BET, and zeta potential tests characterized the Ag/Fe3O4/CNC nanocomposite. The nanocomposite's catalytic activity was tested by eliminating 4-nitrophenol (4-NP) and organic dyes methylene blue (MB) and methyl orange (MO) in an aqueous solution at 25 oC. The Ag/Fe3O4/CNC nanocomposite reduced 4-NP and decolored these hazardous organic dyes in short time (2 to 5 min) using a tiny amount of catalyst (2.5 mg for 4-NP and 15 mg for MO and MB). The magnetic catalyst was removed and reused three times without losing catalytic activity. This work shows that the Ag/Fe3O4/CNC nanocomposite can chemically reduce harmful pollutants in effluent for environmental applications.

SMARCA4-deficient non-small cell lung cancer (NSCLC) is a more recently recognized subset of NSCLC. We describe the 18F-fluorodeoxyglucose (FDG) PET/CT findings in a rare case of SMARCA4-deficient NSCLC and response to therapy. A 45-year-old male patient with a history of heavy smoking (10 years) underwent an 18F-fluorodeoxyglucose (FDG) PET/CT dynamic (chest) + static (whole-body) scan for diagnosis and pre-treatment staging. 18F-FDG PET/CT showed an FDG-avid mass in the upper lobe of the left lung (SUVmax of 22.4) and FDG-avid lymph nodes (LN) in the left pulmonary hilar region (SUVmax of 5.7). In addition, there are multiple metastases throughout the body, including distant LNs, adrenal glands, bone, and brain. Pathological findings confirmed SMARCA-4 deficient NSCLC. After 4 cycles of chemotherapy and immune checkpoint inhibitors（ICI）, the patient underwent again an 18F-FDG PET/CT scan (including dynamic scan) for efficacy evaluation. We report cases that deepen the understanding of the 18F-FDG PET/CT presentation of SMARCA4-deficient NSCLC as well as dynamic imaging features and parametric characteristics.

As the echoes of ChatGPT's remarkable success continue to permeate the AI community, its formidable successor, GPT-4, has emerged, showing off a wealth of novel features. In this concise paper, we elucidate the capabilities of GPT-4 and conduct a comparative analysis with its predecessor, ChatGPT, offering insights into their relative strengths and advancements in the rapidly evolving field of generative AI. We also present a comprehensive summary of the major performance results reported by OpenAI on GPT-4 across various Natural Language Processing (NLP) tasks. We place great emphasis on the innovative advancements offered by GPT-4 in comparison to its predecessors. Our focus is on highlighting its remarkable performance while also mentioning its limitations. The purpose of this paper is to deliver a succinct understanding of the new features and performance benchmarks of GPT-4.

It was the aim of this study to compare the ratio of salbutamol and its major metabolite salbutamol-4’-O-sulfate as well as the quantity excreted renally after oral and inhalative administration. Additionally, the excretion pattern after application of racemic salbutamol opposed to the pure enantiomer levosalbutamol was evaluated. For quantitation of the sulfonated metabolite of salbutamol, reference material was synthesized and characterized by NMR and HRMS. Urine samples were analyzed by ultrahigh performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS). Salbutamol is mainly metabolized by sulfotransferase 1A3 (SULT1A3), which is most abundantly found in the jejunum. A high first pass effect occurs upon oral administration, which leads to a higher amount of salbutamol-4’-O-sulfate in urine compared to unchanged salbutamol excreted within the first hour post administration. Thus, when administered orally, the proportion of metabolite to total salbutamol was higher than for inhalative administration in the early urinary excretion. Levosalbutamol is the favored enantiomer of SULT1A3 and therefore metabolized at a higher rate whereas racemic salbutamol shows a reduced proportion between metabolite and parent compound. The amount of sulfoconjugate was found higher than that of the parent compound for all urine samples except for those excreted in the first hour after inhalative administration.

CRISPR-Cas allows us to introduce desired genome editing, including mutations, epitopes, and deletions with unprecedented efficiency. The development of CRISPR-Cas has progressed to such an extent that it is now applicable in various fields with the help of model organisms. C. elegans is one of the pioneering animals in which numerous CRISPR-Cas strategies have been rapidly es-tablished over the past decade. Ironically, the emergence of numerous methods makes the right choice of method difficult. Choosing an appropriate selection or screening approach is the first step in planning a genome modification. This report summarizes the key features and applications of CRISPR-Cas methods using C. elegans and illustrates key strategies. Our overview of significant advances in CRISPR-Cas will help readers to understand current advances in genome editing and navigate various methods of CRISPR-Cas genome editing.

Different types of engineered cardiac constructs are being developed nowadays by many research groups. However, the immunological properties of such artificial tissues are not yet clearly understood. Previously, we have studied microfiber scaffolds carrying iPSC-derived cardiomyocytes. In this work, we evaluated the ability of these tissue-engineered constructs to activate the expression of CD28 and CTLA-4 proteins in T-lymphocytes which are early markers of the immune response. For this purpose electrospun PLA nanofibrous scaffolds were seeded with human iPSCs-CM and cultivated for 2 weeks. After, allogeneic mononuclear cells were co-cultured during 48 hours with 3 groups of samples that were tissue-engineered constructs, pure culture of cardiomyocytes and bare scaffolds followed by analysis of CD28/CTLA-4 expression on T-lymphocytes via flow cytometry. PLA scaffolds and concanavalin A (positive control) stimulation statistically significantly increased CD28 expression on CD4+ cells (up to 61.3% and 66.3%) and on CD8+ cells (up to 17.8% and 21.7%). CD28/CTLA-4 expression didn’t increase during co-cultivation of T-lymphocytes with cardiac engineered constructs and iPSC-CM monolayers. Thus, iPSCs-CM in monolayers and on PLA nanofibrous scaffolds didn’t cause T-cell activation, which allows us to expect that such cardiac constructs are not a cause of rejection after implantation.

Multiple myeloma (MM) is characterized by the malignant proliferation of monoclonal plasma cells in the bone marrow with an elevation in monoclonal paraprotein, renal impairment, hypercalcemia, lytic bony lesions, and anemia. Immune cells and associated cytokines play a significant role in MM growth, progression, and dissemination. While some cytokines and their clinical significance are well described in MM biology, others remain relatively unknown. The aim of the present study was to assess the impact of pretreatment serum levels of 27 selected cytokines on progression-free survival (PFS) and overall survival (OS) in MM patients before first-line therapy with bortezomib-based regimens. Serum cytokine levels were assayed with a Bio-Rad Bio-Plex Pro Human Cytokine 27-Plex Assay on the MAGPIX Multiplex Reader and the Bio-Plex® 200 System (Bio-Rad) including IL-1β, IL-1Ra, IL-2, IL-4, IL-5, IL-6, IL-7, IL-8, IL-9, IL-10, IL-12, IL-13, IL-15, IL-17, Eotaxin, FGF, G-CSF, GM-CSF, IFN-γ, IP-10, MCP-1, MIP-1α, MIP-1β, PDGF-BB, RANTES, TNF-α, and VEGF. A total of 61 MM patients were examined. Most patients received a bortezomib, cyclophosphamide and dexamethasone (VCD) chemotherapy regimen. In the final multivariate model, IL-13 cytokine level (HR 0.1411, 95% CI: 0.0240-0.8291, p = 0.0302), and ASCT (HR 0.3722, 95% CI: 0.1826-0.7585, p=0.0065) significantly impacted PFS. Furthermore, ASCT (HR 0.142, 95% CI: 0.046-0.438, p=0.0007), presence of bone disease at diagnosis (HR 3.826, 95% CI: 1.471-9.949, p=0.0059) and two cytokine levels- IL-1Ra (HR 1.017, 95% CI: 1.004-1.030, p= 0.0091) and IL-4 (HR 0.161, 95% CI: 0.037-0.698, p = 0.0147) were independent predictors of OS. Three clusters of MM patients were identified with different cytokine profiles. In conclusion, serum pretreatment levels of IL-13 and IL-4 are predictors of better PFS and OS, respectively, whereas IL-1Ra pretreatment levels negatively impact OS in MM patients treated with bortezomib-based chemotherapy. Cytokine signature profile may have a potential influence on the outcome of patients treated with bortezomib.

Immune checkpoint inhibitors (ICIs) have obtained durable responses in many cancers, making it possible to foresee their potential in improving the health of cancer patients. However, immunotherapies are limited at the moment to a minority of patients and there is a need for a better understanding of the basic molecular mechanisms and functions of pivotal immune regulatory molecules. Immune checkpoint cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) and regulatory T (Treg) cells play pivotal roles in hindering the anticancer immunity. Treg cells suppress antigen-presenting cells (APCs) by depleting immune stimulating cytokines, producing immunosuppressive cytokines and constitutively expressing CTLA-4. CTLA-4 molecules bind with higher affinity to CD80 and CD86 than CD28 and act as competitive inhibitors of CD28 in APCs. The purpose of this review is to summarize state-of-the-art understanding of the molecular mechanisms underlining CTLA-4 immune regulation and the correlation of ICI response with CTLA-4 expression in Treg cells from preclinical and clinical studies for possibly improving CTLA-4-based immunotherapies, while highlighting the knowledge gap.

Malignant gliomas are heterogeneous neoplasms. Glioma stem-like cells (GSCs) are undifferentiated and self-renewing cells that develop and maintain these tumors. These cells are the main population that resist current therapies. Genomic and epigenomic analyses has identified various molecular subtypes. Bone morphogenetic protein 4 (BMP4) reduces the number of GSCs through differentiation and induction of apoptosis, thus increasing therapeutic sensitivity. However, the short half-life of BMP4 impedes its clinical application. We have previously reviewed BMP4 signaling in central nervous system development and glioma tumorigenesis and its’ potential as a treatment target in human gliomas. Recent advances in understanding both adult and pediatric malignant gliomas highlight critical roles of BMP4 signaling pathways in the regulation of tumor biology, and indicate its’ potential as a therapeutic molecule. Furthermore, significant progress has been made on synthesizing BMP4 biocompatible delivery materials, which can bind to and markedly extend BMP4 half-life. Here, we review current research associated with BMP4 in brain tumors, especially in pediatric malignant gliomas. We also summarize BMP4 delivery strategies, with a focus on biocompatible BMP4 binding peptide amphiphile nanostructures as promising novel delivery platforms for treatment of these devastating tumors.

Binderless zeolite macrostructures in the form of ZK-4 microspheres were prepared using anion exchange resin beads as shape directing macrotemplates. The particles were synthesized under hydrothermal conditions at different temperatures and treatment times. The influence of the different synthesis parameters was investigated by X-ray diffraction, scanning electron microscopy, fluorescence X, nitrogen adsorption measurements and ²⁹Si solid NMR. Fully crystalline spheres similar in size and shape to the original resin beads were obtained by a hydrothermal treatment at the highest temperatures (150 - 180 °C) for a short treatment time of 24 h. The synthesized microspheres showed to be promising in the molecular decontamination of Volatile Organic Compounds (VOCs).