Reinforcing decellularized small intestine submucosa with cellulose acetate nanofibrous and silver nanoparticles as a scaffold for wound healing applications.

BACKGROUND: The formation of chronic wounds accounts for considerable costs in health care systems. Despite the several benefits of decellularized small intestinal submucosa (SIS) as an appropriate scaffold for different tissue regeneration, it has shortcomings such as lack of antibacterial features and inappropriate mechanical properties for skin tissue regeneration. We aimed to examine the efficacy and safety of decellularized SIS scaffold enhanced with cellulose acetate (CA) and silver (Ag) nanoparticles (NPs) for healing full-thickness wounds. METHODS AND RESULTS: The scaffolds were prepared by decellularizing bovine SIS and electrospinning CA/Ag nanoparticles and characterized using a transmission electron microscope (TEM), scanning electron microscope (SEM), tensile testing, and X-ray diffraction. In vivo evaluations were performed using full-thickness excisions covered with sterile gauze as the control group, SIS, SIS/CA, and SIS/CA/Ag scaffolds on the dorsum of twenty male Wistar rats divided into four groups randomly with 21-days follow-up. All in vivo specimens underwent Masson's trichrome (MT) staining for evaluation of collagen deposition, transforming growth factor-ß (TGF-ß) immunohistochemistry (IHC), and Haematoxylin Eosin (H&E) staining. The IHC and MT data were analyzed with the ImageJ tool by measuring the stained area. The TEM results revealed that Ag nanoparticles are successfully incorporated into CA nanofibers. Assessment of scaffolds hydrophilicity demonstrated that the contact angle of SIS/CA/Ag scaffold was the lowest. The in vivo results indicated that the SIS/CA/Ag scaffold had the most significant wound closure. H&E staining of the in vivo specimens showed the formation of epidermal layers in the SIS/CA/Ag group on day 21. The percentage of the stained area of MT and TGF-ß IHC staining's was highest in the SIS/CA/Ag group. CONCLUSION: The decellularized SIS/CA/Ag scaffolds provided the most significant wound closure compared to other groups and caused the formation of epidermal layers and skin appendages. Additionally, the collagen deposition and expression of TGF-ß increased significantly in SIS/CA/Ag group.

Ex vivo anti-senescence activity of N-acetylcysteine in visceral adipose tissue of obese volunteers.

INTRODUCTION: Excessive visceral adiposity is known to drive the onset of metabolic derangements, mostly involving oxidative stress, prolonged inflammation and cellular senescence. N-acetyl cysteine (NAC) is a synthetic form of L-cysteine with potential antioxidant, anti-inflammatory, and anti-senescence properties. This ex-vivo study aimed to determine the effect of NAC on some markers of senescence including ß-galactosidase activity and p16, p53, p21, IL-6 and TNF-α gene expressions in visceral adipose tissue in obese adults. METHODS: This ex-vivo experimental study involved 10 obese participants who were candidates for bariatric surgery. Duplicate biopsies from the abdominal visceral adipose tissue were obtained from the omentum. The biopsies were treated with or without NAC (5 and 10 mM). To evaluate adipose tissue senescence, beta-galactosidase (ß-gal) activity and the expression of P16, P21, P53, IL-6, and TNF-α were determined. ANOVA test was employed to analyze the varying markers of cellular senescence and inflammation between treatment groups. RESULTS: The NAC at concentrations of 5 mM and 10 mM resulted in a noteworthy reduction ß-gal activity compared to the control group (P < 0.001). Additionally, the expression of P16, P21 and IL-6 was significantly reduced following treatment with NAC (5 mM) and NAC (10 mM) compared to the control group (All p<0.001). DISCUSSION/CONCLUSION: Taken together, these data suggest the senotherapeutic effect of NAC, as it effectively reduces the activity of SA-ß-gal and the expression of IL-6, P16, and P21 genes in the visceral adipose tissue of obese individuals.

Predicting drug activity against cancer through genomic profiles and SMILES.

Due to the constant increase in cancer rates, the disease has become a leading cause of death worldwide, enhancing the need for its detection and treatment. In the era of personalized medicine, the main goal is to incorporate individual variability in order to choose more precisely which therapy and prevention strategies suit each person. However, predicting the sensitivity of tumors to anticancer treatments remains a challenge. In this work, we propose two deep neural network models to predict the impact of anticancer drugs in tumors through the half-maximal inhibitory concentration (IC50). These models join biological and chemical data to apprehend relevant features of the genetic profile and the drug compounds, respectively. In order to predict the drug response in cancer cell lines, this study employed different DL methods, resorting to Recurrent Neural Networks (RNNs) and Convolutional Neural Networks (CNNs). In the first stage, two autoencoders were pre-trained with high-dimensional gene expression and mutation data of tumors. Afterward, this genetic background is transferred to the prediction models that return the IC50 value that portrays the potency of a substance in inhibiting a cancer cell line. When comparing RSEM Expected counts and TPM as methods for displaying gene expression data, RSEM has been shown to perform better in deep models and CNNs model can obtain better insight in these types of data. Moreover, the obtained results reflect the effectiveness of the extracted deep representations in the prediction of the IC50 value that portrays the potency of a substance in inhibiting a tumor, achieving a performance of a mean squared error of 1.06 and surpassing previous state-of-the-art models.

Using Cu2O/ZnO as Two-Dimensional Hole/Electron Transport Nanolayers in Unleaded FASnI3 Perovskite Solar Cells.

A Pb-free FASnI3 perovskite solar cell improved by using Cu2O/ZnO as two-dimensional-based hole/electron transport nanolayers has been proposed and studied by using a SCAPS-1D solar simulator. To calibrate our study, at first, an FTO/ZnO/MAPbI3/Cu2O/Au multilayer device was simulated, and the numerical results (including a conversion efficiency of 6.06%, an open circuit potential of 0.76 V, a fill factor parameter of 64.91%, and a short circuit electric current density of 12.26 mA/cm2) were compared with the experimental results in the literature. Then, the conversion efficiency of the proposed FASnI3-based solar cell was found to improve to 7.83%. The depth profile energy levels, charge carrier concentrations, recombination rate of electron/hole pair, and the FASnI3 thickness-dependent solar cell efficiency were studied and compared with the results obtained for the MAPbI3-containing device (as a benchmark). Interestingly, the FASnI3 material required to obtain an optimized solar cell is one-half of the material required for an optimized MAPbI3-based device, with a thickness of 200 nm. These results indicate that developing more environmentally friendly perovskite solar cells is possible if suitable electron/hole transport layers are selected along with the upcoming Pb-free perovskite absorber layers.

Efficient performance of InP and InP/ZnS quantum dots for photocatalytic degradation of toxic aquatic pollutants.

In recent years, the growing concern over the presence of toxic aquatic pollutants has prompted intensive research into effective and environmentally friendly remediation methods. Photocatalysis using semiconductor quantum dots (QDs) has developed as a promising technology for pollutant degradation. Among various QD materials, indium phosphide (InP) and its hybrid with zinc sulfide (ZnS) have gained considerable attention due to their unique optical and photocatalytic properties. Herein, InP and InP/ZnS QDs were employed for the removal of dyes (crystal violet, and congo red), polyaromatic hydrocarbons (pyrene, naphthalene, and phenanthrene), and pesticides (deltamethrin) in the presence of visible light. The degradation efficiencies of crystal violet (CV) and congo red (CR) were 74.54% and 88.12% with InP, and 84.53% and 91.78% with InP/ZnS, respectively, within 50 min of reaction. The InP/ZnS showed efficient performance for the removal of polyaromatic hydrocarbons (PAHs). For example, the removal percentage for naphthalene, phenanthrene, and pyrene was 99.8%, 99.6%, and 88.97% after the photocatalytic reaction. However, the removal percentage of InP/ZnS for pesticide deltamethrin was 90.2% after 90 min light irradiation. Additionally, advanced characterization techniques including UV-visible spectrophotometer (UV-Vis), photoluminescence (PL), X-ray diffractometer (XRD), energy-dispersive spectrometer (EDS) elemental mapping, transmission electron microscopy (TEM), and thermogravimetric analysis (TGA) were used to analyze the crystal structure, morphology, and purity of the fabricated materials in detail. The particle size results obtained from TEM are in the range of 2.28-4.60 nm. Both materials (InP and InP/ZnS) exhibited a spherical morphology, displaying distinct lattice fringes. XRD results of InP depicted lattice planes (111), (220), and (311) in good agreement with cubic geometry. Furthermore, the addition of dopants was discovered to enhance the thermal stability of the fabricated material. In addition, QDs exhibited efficacy in the breakdown of PAHs. The analysis of their fragmentation suggests that the primary mechanism for PAHs degradation is the phthalic acid pathway.

ZIF-8 Nanoparticle: A Valuable Tool for Improving Gene Delivery in Sperm-Mediated Gene Transfer.

Metal-organic frameworks (MOFs) are porous materials with unique characteristics that make them well-suited for drug delivery and gene therapy applications. Among the MOFs, zeolitic imidazolate framework-8 (ZIF-8) has emerged as a promising candidate for delivering exogenous DNA into cells. However, the potential of ZIF-8 as a vector for sperm-mediated gene transfer (SMGT) has not yet been thoroughly explored.This investigation aimed to explore the potential of ZIF-8 as a vector for enhancing genetic transfer and transgenesis rates by delivering exogenous DNA into sperm cells. To test this hypothesis, we employed ZIF-8 to deliver a plasmid expressing green fluorescent protein (GFP) into mouse sperm cells and evaluated the efficiency of DNA uptake. Our findings demonstrate that ZIF-8 can efficiently load and deliver exogenous DNA into mouse sperm cells, increasing GFP expression in vitro. These results suggest that ZIF-8 is a valuable tool for enhancing genetic transfer in SMGT, with important implications for developing genetically modified animals for research and commercial purposes. Additionally, our study highlights the potential of ZIF-8 as a novel class of vectors for gene delivery in reproductive biology.Overall, our study provides a foundation for further research into using ZIF-8 and other MOFs as gene delivery systems in reproductive biology and underscores the potential of these materials as promising vectors for gene therapy and drug delivery.

Effects of treadmill training on myelin proteomic markers and cerebellum morphology in a rat model of cuprizone-induced toxic demyelination.

BACKGROUND: Multiple sclerosis (MS) is the most common demyelinating disease of the central nervous system (CNS). If demyelination is persistent, it will result in irreversible axonal injury and loss. The purpose of the current study was to investigate the effects of treadmill training on myelin proteomic markers and cerebellum morphology in a rat model of cuprizone-induced toxic demyelination. METHODS: Thirty male rats were randomly assigned to five groups (n = 6 per group), consisting of a healthy control group (Control), a cuprizone (CPZ) group, and three exercise training groups: exercise training before and during the CPZ administration (EX-CPZ-EX), exercise training before the CPZ administration (EX-CPZ), and exercise training during the CPZ administration (CPZ-EX). A rat model of CPZ-induced toxic demyelination consisted of feeding the rats cuprizone pellets (0.2%) for 6 weeks. All exercise groups performed a treadmill training protocol 5 days/week for 6 weeks. Levels of Myelin proteolipid protein (PLP), Myelin oligodendrocyte glycoprotein (MOG), axonal injury in the cerebellar tissue, and volume, weight, and length of the cerebellum were determined. RESULTS: Results indicated a significant decrease in PLP and MOG in the CPZ groups compared to the Control group (****p < 0.0001). There was a significant increase in PLP and MOG and a significant decrease in axonal injury in the EX-CPZ-EX group as compared to other CPZ groups (****p < 0.0001), and CPZ-MS and CPZ-EX were not significantly different from one another. However, there were no significant differences between the groups for the volume, weight, or length of the cerebellum. CONCLUSION: Treadmill training improved myelin sheath structural proteins and axonal injury in cerebellar tissue in a rat model of CPZ-induced toxic demyelination.

The impact of sleeve gastrectomy on polycystic ovarian syndrome: a single-center 1-year cohort study.

BACKGROUND AND AIM: Obesity is one of the risk factors for polycystic ovarian syndrome (PCOS), and weight loss is the mainstay of treatment. This study investigates the effects of sleeve gastrectomy on clinical and paraclinical signs and symptoms of PCOS patients referred to a tertiary hospital. METHODS: Female patients with a definite diagnosis of PCOS and body mass index (BMI) > 40 kg/m2 who were candidates for sleeve gastrectomy were enrolled in this cohort study and followed for 1 year postoperatively. Clinical signs and symptoms of PCOS, sonographic examination, and laboratory hormonal assessments were assessed preoperatively and 1 year following surgery. RESULTS: Fifty patients enrolled in the study. The mean age of patients was 31.69 ± 9.54 years. The mean BMI before and after the surgery was 44.28 ± 3.03 and 29.37 ± 2.41 kg/m2, respectively. Oligomenorrhea was improved in 66% of patients. According to the sonographic criteria, PCOS was improved in 74% of patients. After a year post-operation, while the mean serum levels of the follicular stimulating hormone (FSH), testosterone, and dehydroepiandrostenedione have improved significantly in all patients (p < 0.001 in all), the significant decrease in serum luteinizing hormone (LH), LH/ FSH ratio, and estrogen was only noted in patients with improved clinical response (p < 0.05, p < 0.001, and p < 0.001 respectively). CONCLUSION: Weight loss and improvements in hyperandrogenism following sleeve gastrectomy result in clinical and paraclinical improvement of PCOS signs and symptoms, including oligomenorrhea and ovulation induction.

Chronic constipation and acute small bowel obstruction due to small bowel encapsulation: A case report.

Key Clinical Message: Peritoneal encapsulation is most of the time asymptomatic and is found incidentally, but when symptomatic it usually presents with bowel obstruction. CT scan is a gold standard for the diagnosis of bowel encapsulation. Abstract: Congenital peritoneal encapsulation (CPE), abdominal cocoon syndrome (ACS), and sclerosing encapsulating peritonitis (SEP) are syndromes in which the small bowel is encapsulated. Small bowel encapsulation is usually asymptomatic and rarely presents with small bowel obstruction. In this article, we report a 65-year-old man who presented to our hospital with signs and symptoms of small bowel obstruction. He underwent an urgent operation, and small bowel encapsulation was diagnosed. One year after the surgery, all symptoms improved.

Gallbladder agenesis and choledochogastric fistula in patient with history of cholangitis: A case report.

Background: Gallbladder agenesis is a biliary tract related congenital malformation with an incidence of 10-65 per 100,000 and associated with other congenital abnormalities. GA is usually asymptomatic, but sometimes patients become symptomatic. The most usual symptoms are jaundice, abdominal pain in the right upper quadrant, nausea and vomiting. We reported a case of GA and choledochogastric fistula in a patient with history of cholangitis. Case Presentation: A 70-year-old man presented to Emergency Department of Modarres Hospital with jaundice, fever, right upper quadrant abdominal pain, nausea and vomiting. Clinical examination and lab test demonstrated cholangitis. He underwent ultrasonography, abdominopelvic CT scan and ERCP. ERCP revealed a CBD fistula. Due to recurrent symptoms, he underwent operation and hepaticojejunostomy was done. Conclusion: In our knowledge, the case of GA and choledochogastric fistula is rare. Furthermore, this type of abnormalities rarely presented with cholangitis, so probable anatomical malformation of the biliary tract should always be considered as a differential diagnosis in patients with biliary disease signs and symptoms.

Effects of electron transport layer type on the performance of Pb-free Cs2AgBiBr6 double perovskites: a SCAPS-1D solar simulator-based study.

Recently, due to the superior stability and lower risk of toxicity, the development of Pb-free halide double perovskite materials has revived excellent interest. In this work, Pb-free perovskite solar cells (PSCs) with ITO/ETL/Cs2AgBiBr6/Cu2O/Au multilayer structures with Cs2AgBiBr6 double perovskite as the solar light absorber layer, some electron transport layers (ETLs) and Cu2O as a hole transport layer have been introduced. Then, the effects of various thicknesses of the absorber layer and also ETL materials, like ZnO, C60, CdS, SnO2, phenyl-C61-butyric acid methyl ester (PCBM), and TiO2, on the device performance (including photoelectronic conversion efficiency (PCE), fill factor (FF%), short circuit current density (Jsc), and open-circuit voltage (VOC)) were examined with the help of a solar cell simulator (SCAPS-1D). It is noteworthy that, in the case of all ETL materials, the optimal thickness of the absorber layer was determined to be 400 nm. Then, the maximum PCE values of 20.08%, 17.63%, 14.07%, 12.11%, 14.94%, and 18.83% were obtained for the solar cells containing ZnO, C60, CdS, SnO2, PCBM, and TiO2 as the ETL, respectively. These results show that designing/developing Pb-free halide double perovskite devices having comparable PCEs with the Pb-based PSCs is feasible, provided that proper/compatible materials will be used in the multilayer structure of the next generations of solar cells.

Artificial intelligence for prediction of biological activities and generation of molecular hits using stereochemical information.

In this work, we develop a method for generating targeted hit compounds by applying deep reinforcement learning and attention mechanisms to predict binding affinity against a biological target while considering stereochemical information. The novelty of this work is a deep model Predictor that can establish the relationship between chemical structures and their corresponding [Formula: see text] values. We thoroughly study the effect of different molecular descriptors such as ECFP4, ECFP6, SMILES and RDKFingerprint. Also, we demonstrated the importance of attention mechanisms to capture long-range dependencies in molecular sequences. Due to the importance of stereochemical information for the binding mechanism, this information was employed both in the prediction and generation processes. To identify the most promising hits, we apply the self-adaptive multi-objective optimization strategy. Moreover, to ensure the existence of stereochemical information, we consider all the possible enumerated stereoisomers to provide the most appropriate 3D structures. We evaluated this approach against the Ubiquitin-Specific Protease 7 (USP7) by generating putative inhibitors for this target. The predictor with SMILES notations as descriptor plus bidirectional recurrent neural network using attention mechanism has the best performance. Additionally, our methodology identify the regions of the generated molecules that are important for the interaction with the receptor's active site. Also, the obtained results demonstrate that it is possible to discover synthesizable molecules with high biological affinity for the target, containing the indication of their optimal stereochemical conformation.

Enhancing reinforcement learning for de novo molecular design applying self-attention mechanisms.

The drug discovery process can be significantly improved by applying deep reinforcement learning (RL) methods that learn to generate compounds with desired pharmacological properties. Nevertheless, RL-based methods typically condense the evaluation of sampled compounds into a single scalar value, making it difficult for the generative agent to learn the optimal policy. This work combines self-attention mechanisms and RL to generate promising molecules. The idea is to evaluate the relative significance of each atom and functional group in their interaction with the target, and to utilize this information for optimizing the Generator. Therefore, the framework for de novo drug design is composed of a Generator that samples new compounds combined with a Transformer-encoder and a biological affinity Predictor that evaluate the generated structures. Moreover, it takes the advantage of the knowledge encapsulated in the Transformer's attention weights to evaluate each token individually. We compared the performance of two output prediction strategies for the Transformer: standard and masked language model (MLM). The results show that the MLM Transformer is more effective in optimizing the Generator compared with the state-of-the-art works. Additionally, the evaluation models identified the most important regions of each molecule for the biological interaction with the target. As a case study, we generated synthesizable hit compounds that can be putative inhibitors of the enzyme ubiquitin-specific protein 7 (USP7).

Effects of N-acetylcysteine on aging cell and obesity complications in obese adults: a randomized, double-blind clinical trial.

Background: We decided to conduct this study with the aim of investigating the effects of N-Acetylcysteine (NAC) on obesity complications and senescence of visceral adipose tissue in obese adults. Methods and analysis: The present study was conducted as a randomized clinical trial (RCT) (Clinical trial registry number: IRCT20220727055563N1) on 40 obese adults candidates for bariatric surgery, who were randomly assigned to receive 600 mg of NAC (n = 20) or placebo as a control (n = 20) for 4 weeks. During bariatric surgery, visceral adipose tissue was used to examine gene expression and senescence cells using SA-ß-gal. Results: Our findings showed that intervention with NAC significantly reduces SA-ß-gal activity (as a marker of senescence) and expression of p16 and interleukin 6 (IL-6) genes in the visceral adipose tissue compared to placebo in obese adults for 4 weeks. In addition, our findings showed the potential and beneficial effect of NAC administration on reducing the levels of inflammatory factors including IL-6 and high-sensitivity C-reactive protein (hs-CRP), as well as the level of fasting blood sugar (FBS), homeostatic model assessment of insulin resistance (HOMA-IR), and insulin compared to placebo after adjusting for confounders. No significant effect was indicated on anthropometric factors and lipid profile. Conclusion: Findings showed that NAC, in addition to having a potential beneficial effect on reducing some of the complications caused by obesity, seems to have synolytic/senomorphic potential as well. Clinical trial registration: [https://clinicaltrials.gov/], identifier [IRCT20220727055563N1].

Speeding Up Entanglement Generation by Proximity to Higher-Order Exceptional Points.

Entanglement is a key resource for quantum information technologies ranging from quantum sensing to quantum computing. Conventionally, the entanglement between two coupled qubits is established at the timescale of the inverse of the coupling strength. In this Letter, we study two weakly coupled non-Hermitian qubits and observe entanglement generation at a significantly shorter timescale by proximity to a higher-order exceptional point. We establish a non-Hermitian perturbation theory based on constructing a biorthogonal complete basis and further identify the optimal condition to obtain the maximally entangled state. Our study of speeding up entanglement generation in non-Hermitian quantum systems opens new avenues for harnessing coherent nonunitary dissipation for quantum technologies.

COVID-19: A novel holistic systems biology approach to predict its molecular mechanisms (in vitro) and repurpose drugs.

PURPOSE: COVID-19 strangely kills some youth with no history of physical weakness, and in addition to the lungs, it may even directly harm other organs. Its complex mechanism has led to the loss of any significantly effective drug, and some patients with severe forms still die daily. Common methods for identifying disease mechanisms and drug design are often time-consuming or reductionist. Here, we use a novel holistic systems biology approach to predict its molecular mechanisms (in vitro), significant molecular relations with SARS, and repurpose drugs. METHODS: We have utilized its relative phylogenic similarity to SARS. Using the available omics data for SARS and the fewer data for COVID-19 to decode the mechanisms and their significant relations, We applied the Cytoscape analyzer, MCODE, STRING, and DAVID tools to predict the topographically crucial molecules, clusters, protein interaction mappings, and functional analysis. We also applied a novel approach to identify the significant relations between the two infections using the Fischer exact test for MCODE clusters. We then constructed and analyzed a drug-gene network using PharmGKB and DrugBank (retrieved using the dgidb). RESULTS: Some of the shared identified crucial molecules, BPs and pathways included Kaposi sarcoma-associated herpesvirus infection, Influenza A, and NOD-like receptor signaling pathways. Besides, our identified crucial molecules specific to host response against SARS-CoV-2 included FGA, BMP4, PRPF40A, and IFI16. CONCLUSION: We also introduced seven new repurposed candidate drugs based on the drug-gene network analysis for the identified crucial molecules. Therefore, we suggest that our newly recommended repurposed drugs be further investigated in Vitro and in Vivo against COVID-19.

FSM-DDTR: End-to-end feedback strategy for multi-objective De Novo drug design using transformers.

The design of compounds that target specific biological functions with relevant selectivity is critical in the context of drug discovery, especially due to the polypharmacological nature of most existing drug molecules. In recent years, in silico-based methods combined with deep learning have shown promising results in the de novo drug design challenge, leading to potential leads for biologically interesting targets. However, several of these methods overlook the importance of certain properties, such as validity rate and target selectivity, or simplify the generative process by neglecting the multi-objective nature of the pharmacological space. In this study, we propose a multi-objective Transformer-based architecture to generate drug candidates with desired molecular properties and increased selectivity toward a specific biological target. The framework consists of a Transformer-Decoder Generator that generates novel and valid compounds in the SMILES format notation, a Transformer-Encoder Predictor that estimates the binding affinity toward the biological target, and a feedback loop combined with a multi-objective optimization strategy to rank the generated molecules and condition the generating distribution around the targeted properties. The results demonstrate that the proposed architecture can generate novel and synthesizable small compounds with desired pharmacological properties toward a biologically relevant target. The unbiased Transformer-based Generator achieved superior performance in the novelty rate (97.38%) and comparable performance in terms of internal diversity, uniqueness, and validity against state-of-the-art baselines. The optimization of the unbiased Transformer-based Generator resulted in the generation of molecules exhibiting high binding affinity toward the Adenosine A2A Receptor (AA2AR) and possessing desirable physicochemical properties, where 99.36% of the generated molecules follow Lipinski's rule of five. Furthermore, the implementation of a feedback strategy, in conjunction with a multi-objective algorithm, effectively shifted the distribution of the generated molecules toward optimal values of molecular weight, molecular lipophilicity, topological polar surface area, synthetic accessibility score, and quantitative estimate of drug-likeness, without the necessity of prior training sets comprising molecules endowed with pharmacological properties of interest. Overall, this research study validates the applicability of a Transformer-based architecture in the context of drug design, capable of exploring the vast chemical representation space to generate novel molecules with improved pharmacological properties and target selectivity. The data and source code used in this study are available at: https://github.com/larngroup/FSM-DDTR.

EFL learners' engagement in online learning context: development and validation of potential measurement inventory.

Research has proved learner engagement is a strong predictor of academic achievement, especially in the online learning environment. The lack of any reliable and valid instrument to measure this construct in the context of online education made the researchers of the current study develop and validate a potential measurement inventory to assess EFL learners' engagement in the online learning environment. For this purpose, a comprehensive review of the related literature and careful investigation of the existing instruments were carried out to find the theoretical constructs for learner engagement which led to the development of a 56-item Likert scale questionnaire. The newly developed questionnaire was piloted with 560 female and male EFL university students selected based on nonprobability convenience sampling. The results of the factor analysis indicated the reduction of items to 48 loaded on three main components, namely behavioral engagement (15 items), emotional engagement (16 items), and cognitive engagement (17 items). The results also revealed that the newly developed questionnaire enjoyed a reliability index of 0.925. The findings of the current study will undoubtedly help teaching practitioners assess EFL learners' engagement in the online learning context and make principled decisions when it comes to learners' engagement.

A comparison between bilateral and unilateral thyroid eye disease.

PURPOSE: To compare characteristics of unilateral vs. bilateral thyroid eye disease (TED). METHODS: This retrospective analytical cross-sectional study was conducted on patients with TED who were evaluated at an academic referral center over a 6-year period. We compared demographics, activity (clinical activity score) and severity (EUGOGO classification) of TED, thyroid disease duration, TED duration, the time interval between thyroid and eye involvement, thyroid function status, and clinical signs between bilateral and unilateral TED. RESULTS: Three hundred eighty-three patients including 213 females (55.6%), who had a mean age of 40.23 ± 13.72 years, were enrolled. Active TED was seen in 8.8% of bilateral and none of unilateral cases (P = 0.04). Bilateral TED patients had more severe disease (P = 0.001). The distribution of hyperthyroidism, hypothyroidism, and euthyroidism was significantly different between unilateral and bilateral groups (P = 0.001). Abnormal ocular motility was present in 26.3% versus 2.3% of bilateral and unilateral ones, respectively (P = 0.001). Proptosis was more prevalent in bilateral than unilateral cases (P = 0.001). We did not observe any statistically significant difference between the two groups in others variables. CONCLUSION: Bilateral TED patients present with more severity, activity, movement abnormality, proptosis, and hyperthyroidism.

Deciphering crucial genes in multiple sclerosis pathogenesis and drug repurposing: A systems biology approach.

This study employed systems biology and high-throughput technologies to analyze complex molecular components of MS pathophysiology, combining data from multiple omics sources to identify potential biomarkers and propose therapeutic targets and repurposed drugs for MS treatment. This study analyzed GEO microarray datasets and MS proteomics data using geWorkbench, CTD, and COREMINE to identify differentially expressed genes associated with MS disease. Protein-protein interaction networks were constructed using Cytoscape and its plugins, and functional enrichment analysis was performed to identify crucial molecules. A drug-gene interaction network was also created using DGIdb to propose medications. This study identified 592 differentially expressed genes (DEGs) associated with MS disease using GEO, proteomics, and text-mining datasets. 37 DEGs were found to be important by topographical network studies, and 6 were identified as the most significant for MS pathophysiology. Additionally, we proposed six drugs that target these key genes. Crucial molecules identified in this study were dysregulated in MS and likely play a key role in the disease mechanism, warranting further research. Additionally, we proposed repurposing certain FDA-approved drugs for MS treatment. Our in silico results were supported by previous experimental research on some of the target genes and drugs. SIGNIFICANCE: As the long-lasting investigations continue to discover new pathological territories in neurodegeneration, here we apply a systems biology approach to determine multiple sclerosis's molecular and pathophysiological origin and identify multiple sclerosis crucial genes that contribute to candidating new biomarkers and proposing new medications.