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Exploring the effects of N234 and N343 linked glycans to SARS CoV 2 spike protein pocket accessibility using Gaussian accelerated molecular dynamics simulations
Viral suppression among patients in HIV/AIDS care at healthcare facilities in Ethiopia: Same-day antiretroviral initiation
To achieve the 2030 goal of eradicating the HIV epidemic, the Joint United Nations Programme on HIV/AIDS has set 95-95-95 targets: 95% of HIV-infected individuals should know their status, 95% should initiate antiretroviral therapy (ART), and 95% should achieve virologic suppression. In Ethiopia, progress has been made, but challenges remain. This study evaluates same-day ART initiation and its effect viral suppression for patients in HIV/AIDS care in Ethiopia. A cross-sectional study design was used to analyze 332 clinical records of patients who initiated same-day ART between October 1, 2017, and October 30, 2019. A probability simple random sampling technique was used in the selection of the clinical records of patients started on ART. Data were analyzed using Statistical Package for Social Science (SPSS) version 28.0, employing both descriptive and inferential statistical analyses. The results showed that viral suppression rates at 6, 12, and 24 months were 93%, 95%, and 86%, respectively, indicating progress towards the global target of 95% by 2030. This supports the effectiveness of same-day ART initiation in achieving viral suppression. Chi-square test results indicated no significant relationship between gender and suppression status (p = 1.00), age and suppression status (p = 0.876), or WHO stage and suppression status (p = 0.404). However, significant associations were found between resident type and suppression status (p < 0.05), as well as retention in care and suppression status (p < 0.05). No significant association was observed between HIV disclosure status and suppression status (p = 0.072). The results suggest an urgent need for follow-up and monitoring of viral suppression as months on ART increase. Additionally, enhancing viral load testing coverage at 6, 12, and 24 months is crucial to ensure sustained viral suppression.
Middle Meningeal Artery Embolization and Nonacute Subdural Hematoma
MiR-365-3p inhibits lung cancer proliferation and migration via CPT1A-mediated fatty acid oxidation
Abstract The relationship between abnormal lipid acid metabolism and the progression of lung cancer is increasingly evident. Carnitine palmitoyltransferase 1A (CPT1A), a rate-limiting enzyme in fatty acid oxidation, has been implicated in the advancement of various cancers. However, the role of CPT1A in lung cancer and the regulatory mechanisms of microRNAs on CPT1A-mediated fatty acid oxidation remain largely unknown. In our study, we demonstrate that miR-365-3p inhibits CPT1A expression by targeting its 3’-untranslated region in lung cancer cells. The inhibition of CPT1A by miR-365-3p leads to increased lipid droplet accumulation, diminished ATP production, and a decrease in fatty acid oxidation levels. Furthermore, the disruption of fatty acid oxidation attenuates the ability of the miR-365-3p/CPT1A axis to modulate lung cancer cell proliferation and migration both in vitro and in vivo. Clinical data reveal that CPT1A expression is significantly upregulated while miR-365-3p is markedly downregulated. Additionally, there exists a negative correlation between miR-365-3p and CPT1A expression, and both are predictive of clinical outcome in lung cancer patients. Collectively, our findings shed light on the function and mechanistic pathway of the miR-365-3p/CPT1A axis in lung cancer, which might provide a potential therapeutic target for lung cancer.
Prediction and validation of anoikis-related genes in neuropathic pain using machine learning
Background Neuropathic pain (NP) can be induced by a variety of clinical conditions, such as spinal cord injury, lumbar disc herniation (LDH), lumbar spinal stenosis, diabetes, herpes zoster, and spinal cord tumors, and inflammatory stimuli. The pathogenesis of NP is extremely complex. Specifically, in LDH, the herniated nucleus pulposus exerts mechanical pressure on nerve roots, triggering local inflammation and consequent NP. Anoikis, a special form of programmed cell death, is closely related to the progression of NP. In this study, we sought to clarify the molecular characteristics of anoikis-related genes in NP, providing novel insights for the diagnosis and treatment of NP. Methods We screened NP-related genes based on the GSE124272 dataset and obtained 439 anoikis-related genes from the GeneCards database. Through Least Absolute Shrinkage and Selection Operator (LASSO) and Support Vector Machine (SVM) machine learning algorithms, six key hub genes were identified: hepatocyte growth factor (HGF), matrix metalloproteinase 13 (MMP13), c-abl oncogene 1, non-receptor tyrosine kinase (ABL1), elastase neutrophil expressed (ELANE), fatty acid synthase (FASN), and long non-coding RNA (Linc00324). Functional enrichment analyses, including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG), alongside Gene Set Enrichment Analysis (GSEA) and immune infiltration analysis, were performed on these hub genes. Additionally, transcription factors and potential therapeutic drugs were predicted. We also used rats to construct an NP model and validated the analyzed hub genes using hematoxylin and eosin (H&E) staining, real-time polymerase chain reaction (PCR), and Western blotting assays. Results Our data indicated that anoikis-related genes have diagnostic value in NP patients, as confirmed by experimental results. Moreover, this study elucidated the role of these genes in immune infiltration during the pathogenesis of NP and identified potential therapeutic drugs targeting these key genes. Conclusion This study further explores the pathogenesis of NP and provides certain reference value for developing targeted therapeutic strategies, thereby improving NP management.
Blinatumomab in Standard-Risk B-Cell Acute Lymphoblastic Leukemia in Children
A circular economy based nonlinear corrugated waste management system using Fermatean bipolar hesitant fuzzy logic
Specificity of cranial cutaneous manipulations in modulating autonomic nervous system responses and physiological oscillations: A controlled study
Significant autonomic nervous system responses to a specific osteopathic intervention, the cranial vault hold (CVH), have recently been demonstrated in forehead skin blood volume changes, heart rate, and respiration frequencies. The specificity of the CVH-intervention-related autonomic responses yet requires differentiation. Thus, we compared autonomic responses to CVH with responses to compression of the fourth ventricle (CV4) and to two corresponding SHAM conditions. Analysis of frequencies and amplitudes for changes in skin blood volume and respiration in low (LF; 0.05–0.12 Hz), intermediate (IM; 0.12–0.18 Hz), and high (HF; 0.18–0.4 Hz) frequency bands, and metrics of heartrate variability revealed significant decreases in LF range (from 0.12 to 0.10 Hz), increased LF and decreased IM durations, and increased skin blood volume amplitudes in response to CVH, but no significant skin blood volume responses to any of the control interventions. Ratio changes for respiration and skin blood volume frequencies approximately at 3:1 during CVH, remained unchanged in all other interventions. Heart rate decreased across conditions, indicating an increase in parasympathetic tone. This was also indicated by a significant increase in root mean of squared successive difference following CV4. We incurred that rhythmic response patterns in the LF and IM bands only appeared in CVH. This suggests specific physiological responses to CVH warranting further investigation by studying e.g., responses to CVH in physical or mental health disorders with autonomic involvement.
Xalnesiran with or without an Immunomodulator in Chronic Hepatitis B
Spatial and seasonal accessibility of marine research weather windows in the polish exclusive economic zone
Estimation of maximum lower limb muscle strength from vertical jumps
Determining the one-repetition maximum (1RM) is crucial for organizing training loads, but it also is time-consuming, physically demanding, and poses a risk of injury. Vertical jumps are a less demanding and well-established method to test the ability of the lower limbs to generate great forces over a short time, which may allow for the estimation of 1RM in squatting. The purpose of this study was to develop a model for estimating 1RM back squat from ground reaction forces during vertical jumps. Thirteen healthy participants completed a 1RM back squat test, countermovement jumps, and squat jumps. Five kinematic and kinetic variables (e.g., peak and mean power, relative net impulse, jump height, and peak kinetic energy during various phases) were derived from ground reaction forces collected via a Kistler force plate (1000 Hz). Five out of 5 variables correlated with 1RM in countermovement jump and squat jump (ICC = .96–.98, r = .88–.95, p < .001 and ICC = .97–.99, r = .76–.90, p < .05, respectively). The most accurate stepwise regression model (adjusted R2 = .90, SEE = 13.24 kg, mean error = 7.4% of mean 1RMm, p < .001) estimated 1RM back squat based on peak kinetic energy during countermovement jumps. Estimation errors ranged from 7.4% to 10.7% of mean measured 1RM, with no differences between estimated and measured values (d < 0.01, p = .96–1.00). Estimating 1RM via jump tests may offer a practical alternative to traditional methods, reducing injury risks, testing intervals, and effort. Our study proposes a new possible approach for estimating 1RM back squat from jump forces, providing coaches and sports professionals with a more efficient tool to monitor and adjust training loads.
Highly Pathogenic Avian Influenza A(H5N1) Virus Infections in Humans
Exploring the effectiveness of adaptive randomized sine cosine algorithm in wind integrated scenario based power system optimization with FACTS devices
Immunoinformatic evaluation for the development of a potent multi-epitope vaccine against bacterial vaginosis caused by Gardnerella vaginalis
Background Bacterial vaginosis (BV) is the most common vaginal dysbiosis in fertile women, which is associated with side effects including the risk of premature birth. Gardnerella vaginalis (G. vaginalis) is a facultative anaerobic bacillus known as the main pathogen responsible for BV. In this study, using bioinformatics and immunoinformatics methods, a multi-epitope vaccine with optimal population coverage against BV caused by G. vaginalis was designed. Methods Amino acid sequences of two important virulence factors (Vaginolysin and Sialidase) of G. vaginalis were retrieved from NCBI and UniProt databases. At first, three online servers ABCpred, BCPREDS and LBtope were used to predict linear B-cell epitopes (BCEs) and IEDB server was used for T cells. Then the antigenicity, toxicity, allergenicity were evaluated using bioinformatics tools. After modeling the three-dimensional (3D) structure of the vaccine by Robetta Server, molecular docking and molecular dynamics were performed. Finally, immune simulation and in silico cloning were considered effective for the design of vaccine production strategy. Results In total, six epitopes of BCEs, eight epitopes from CD4+ and seven epitopes from CD8+ were selected. The designed multi-epitope vaccine was non-allergenic and non-toxic and showed high levels of antigenicity and immunogenicity. After the 3D structure was predicted, it was refined and validated, which resulted in an optimized model with a Z-score of -7.4. Molecular docking and molecular dynamics simulation of the designed vaccine revealed stable and strong binding interactions. Finally, the results of vaccine immunity simulation showed a significant increase in immunoglobulins, higher levels of IFN-γ and IL-2. Conclusion According to the findings, the candidate multi-epitope vaccine has stable structural features. It also has the potential to stimulate long-term immunity in the host, but wet-lab validation is needed to justify it.
Precision power quality control in grid-integrated microgrid via matrix pencil technique
Microsoft claims quantum-computing breakthrough — but some physicists are sceptical
Validation and adaptation of the Arabic version of health-related quality of life with six domains (HRQ-6D): A factor and Rasch analyses study
Background Health-related quality of life (HRQOL) provides a complete picture of patients’ overall health status and should be evaluated in all patients encountered. To accurately assess patients’ HRQOL a comprehensive validated tool is necessary. Therefore, the present study aimed to validate the Arabic version of the Health-Related Quality of Life with Six Domains (Ar-HRQ-6D) scale. Methods This cross-sectional study utilized an online questionnaire targeting adult Jordanians and implemented several validation steps to ensure the adequacy of the Ar-HRQ-6D. These steps included the application of the forward-backward translation technique, assessment of the content and face validity of the questionnaire, evaluation of internal consistency, validation of the construct through confirmatory factor analysis (CFA) and Rasch analysis, and assessment of the questionnaire’s predictive capabilities. Results A total of 808 participants (63% female) completed the Ar-HRQ-6D. Confirmatory Factor Analysis (CFA) supported the suitability of the original three-factor model for the present study data, yielding acceptable model fit indices (χ²/df = 4.1, SRMR = 0.03, RMSEA = 0.06, CFI = 0.99, GFI = 0.96, CIF = 0.98, and TLI = 0.97) and factor loadings ranging from 0.63 to 0.86. Cronbach’s alpha for the three factors ranged from 0.81 to 0.90, confirming the high reliability of the questionnaire. Rasch analysis further validated the person and item separation reliability for the three factors. Additionally, all items of the Ar-HRQ-6D fell within the acceptable infit and outfit ranges. All thresholds were appropriately ordered, ranging from -5.27 to 2.86. Significant differences were observed in the median Ar-HRQ-6D scores across the various health status categories (p < 0.001), with the healthy category showing significantly higher median scores than the other categories. These findings confirm the predictive validity of the Ar-HRQ-6D. Conclusion The study confirmed the reliability, validity, and predictive accuracy of the Arabic version of the Ar-HRQ-6D. This tool is suitable for assessing patients’ HRQOL across various medical settings.
T1-weighted MRI-based brain tumor classification using hybrid deep learning models
Identification of potential biomarkers for lung cancer using integrated bioinformatics and machine learning approaches
Lung cancer is one of the most common cancer and the leading cause of cancer-related death worldwide. Early detection of lung cancer can help reduce the death rate; therefore, the identification of potential biomarkers is crucial. Thus, this study aimed to identify potential biomarkers for lung cancer by integrating bioinformatics analysis and machine learning (ML)-based approaches. Data were normalized using the robust multiarray average method and batch effect were corrected using the ComBat method. Differentially expressed genes were identified by the LIMMA approach and carcinoma-associated genes were selected using Enrichr, based on the DisGeNET database. Protein-protein interaction (PPI) network analysis was performed using STRING, and the PPI network was visualized using Cytoscape. The core hub genes were identified by overlapping genes obtained from degree, betweenness, closeness, and MNC. Moreover, the MCODE plugin for Cytoscape was used to perform module analysis, and optimal modules were selected based on MCODE scores along with their associated genes. Subsequently, Boruta-based ML approach was utilized to identify the important genes. Consequently, the core genes were identified by the overlapping genes obtained from PPI networks, module analysis, and ML-based approach. The prognostic and discriminative power analysis of the core genes was assessed through survival and ROC analysis. We extracted five datasets from USA cohort and three datasets from Taiwan cohort and performed same experimental protocols to determine potential biomarkers. Four genes (LPL, CLDN18, EDNRB, MME) were identified from USA cohort, while three genes (DNRB, MME, ROBO4) were from Taiwan cohort. Finally, two biomarkers (EDNRB and MME) were identified by intersecting genes, obtained from USA and Taiwan cohorts. The proposed biomarkers can significantly improve patient outcomes by enabling earlier detection, precise diagnosis, and tailored treatment, ultimately contributing to better survival rates and quality of life for patients.