Virtual screening of plant-derived molecules against zinc-dependent imipenemases in class B metallo-β-lactamases of Acinetobacter baumannii.

Metallo-β-lactamases (MBLs), enzymes of class B, employ zinc ions to degrade β-lactam antibiotics such as penicillins, cephalosporins, carbapenems, and cephamycins. Carbapenem-resistant Acinetobacter baumannii (CRAB) is linked to the existence of carbapenemase enzymes such as oxacillinase and MBL. The most prevalent resistance mechanisms include imipenemases (IMP), verona integron-encoded MBL, and New Delhi MBL-1.

Computational insights into irinotecan's interaction with UBE2I in ovarian and endometrial cancers.

Endometrial and Ovarian cancers are two highly prevalent and fatal reproductive diseases with poor prognoses among women. Elevated estrogen levels in Ovarian Cancer (OC) stimulate the endometrium, causing Endometrial Cancer (EC). Although numerous studies have reported the crucial genes and pathways in this cancer, the pathogenesis of this disease remains unclear.

Unraveling the intricate physiological processes dysregulated in CHD-affected and Dan-Lou tablet-treated individuals.

Coronary heart disease (CHD), a multifactorial cardiovascular condition, arises from the accumulation of atherosclerotic plaque in the coronary arteries, resulting in compromised blood flow to the heart and complications such as angina, myocardial infarction, or heart failure. Addressing global prevalence, risk factors, and genetics is crucial for effective management. The current study aims to identify molecular biomarkers for CHD by scrutinizing the expression patterns of differentially expressed genes (DEGs), utilizing various bioinformatic tools.

Enhancing agency and empowerment in agricultural development projects: A synthesis of mixed methods impact evaluations from the Gender, Agriculture, and Assets Project, Phase 2 (GAAP2).

Development interventions increasingly include women's empowerment and gender equality among their objectives, but evaluating their impact has been stymied by the lack of measures that are comparable across interventions. This paper synthesizes the findings of 11 mixed-methods impact evaluations of agricultural development projects from South Asia and sub-Saharan Africa that were part of the Gender, Agriculture, and Assets Project, Phase 2 (GAAP2). As part of GAAP2, qualitative and quantitative data were used to develop and validate the multidimensional project-level Women's Empowerment in Agriculture Index (pro-WEAI), which was used to assess the impact of GAAP2 projects on women's empowerment.

Identification and Potential Roles of Human MicroRNAs in Ebola Virus Infection and Disease Pathogenesis.

Ebola virus (EBOV) is a highly pathogenic virus that causes a severe illness called Ebola virus disease (EVD). EVD has a high mortality rate and remains a significant threat to public health. Research on EVD pathogenesis has traditionally focused on host transcriptional responses.

Investigating the Impact of First-Line Anti-Tuberculosis Drugs Encapsulated in a Eugenol-Based Nanoemulsion on Human Serum Albumin.

Background: Eugenol exhibits broad-spectrum antibacterial and anti-inflammatory properties. However, cytotoxicity at high concentrations limits the full utilization of eugenol-based drug complexes. Formulations of multidrug-loaded eugenol-based nanoemulsions have reduced cytotoxicity; however, it remains crucial to understand how these eugenol complexes interact with primary human carrier proteins to design and develop therapeutic alternatives.

How Precise are Nanomedicines in Overcoming the Blood-Brain Barrier? A Comprehensive Review of the Literature.

New nanotechnology strategies for enhancing drug delivery in brain disorders have recently received increasing attention from drug designers. The treatment of neurological conditions, including brain tumors, stroke, Parkinson's Disease (PD), and Alzheimer's disease (AD), may be greatly influenced by nanotechnology. Numerous studies on neurodegeneration have demonstrated the effective application of nanomaterials in the treatment of brain illnesses.

Comparative Analysis of Machine Learning Algorithms Evaluating the Single Nucleotide Polymorphisms of Metabolizing Enzymes with Clinical Outcomes Following Intravenous Paracetamol in Preterm Neonates with Patent Ductus Arteriosus.

Aims: Pharmacogenomics has been identified to play a crucial role in determining drug response. The present study aimed to identify significant genetic predictor variables influencing the therapeutic effect of paracetamol for new indications in preterm neonates.

Background: Paracetamol has recently been preferred as a first-line drug for managing Patent Ductus Arteriosus (PDA) in preterm neonates.

Microplastic interactions in the agroecosystems: methodological advances and limitations in quantifying microplastics from agricultural soil.

The instantaneous growth of the world population is intensifying the pressure on the agricultural sector. On the other hand, the critical climate changes and increasing load of pollutants in the soil are imposing formidable challenges on agroecosystems, affecting productivity and quality of the crops. Microplastics are among the most prevalent pollutants that have already invaded all terrestrial and aquatic zones.

Mechanistic Insights into the Binding of Boar Salivary Pheromones and Putative Molecule with Receptor Proteins: A Comparative Computational Approach.

Precise estrus detection in sows is pivotal in increasing the productivity within the pork industry. Sows in estrus exhibit exclusive behaviors when exposed to either a live boar or the steroid pheromones androstenone and androstenol. Recently, a study employing solid-phase microextraction-gas chromatography-mass spectrometry has identified a novel salivary molecule in boars, known as quinoline.

Identification of Potential Inhibitors Targeting GTPase-Kirsten RAt Sarcoma Virus (K-Ras) Driven Cancers via E-Pharmacophore-Based Virtual Screening and Drug Repurposing Approach.

Background: Mutations in the gene are among the most frequent genetic alterations in various cancers, and inhibiting RAS signaling has shown promising results in treating solid tumors. However, finding effective drugs that can bind to the RAS protein remains challenging. This drove us to explore new compounds that could inhibit tumor growth, particularly in cancers that harbor K-Ras mutations.

Evaluation of Supervised Machine Learning Algorithms and Computational Structural Validation of Single Nucleotide Polymorphisms Related to Acute Liver Injury with Paracetamol.

Aims: To identify single nucleotide polymorphisms (SNPs) of paracetamol-metabolizing enzymes that can predict acute liver injury.

Background: Paracetamol is a commonly administered analgesic/antipyretic in critically ill and chronic renal failure patients and several SNPs influence the therapeutic and toxic effects.

Objective: To evaluate the role of machine learning algorithms (MLAs) and bioinformatics tools to delineate the predictor SNPs as well as to understand their molecular dynamics.

Deepfakes and scientific knowledge dissemination.

Science misinformation on topics ranging from climate change to vaccines have significant public policy repercussions. Artificial intelligence-based methods of altering videos and photos (deepfakes) lower the barriers to the mass creation and dissemination of realistic, manipulated digital content. The risk of exposure to deepfakes among education stakeholders has increased as learners and educators rely on videos to obtain and share information.

Airway and Oral microbiome profiling of SARS-CoV-2 infected asthma and non-asthma cases revealing alterations-A pulmonary microbial investigation.

New evidence strongly discloses the pathogenesis of host-associated microbiomes in respiratory diseases. The microbiome dysbiosis modulates the lung's behavior and deteriorates the respiratory system's effective functioning. Several exogenous and environmental factors influence the development of asthma and chronic lung disease.

Machine learning in photosynthesis: Prospects on sustainable crop development.

Improving photosynthesis is a promising avenue to increase food security. Studying photosynthetic traits with the aim to improve efficiency has been one of many strategies to increase crop yield but analyzing large data sets presents an ongoing challenge. Machine learning (ML) represents a ubiquitous tool that can provide a more elaborate data analysis.

Computational Structural Validation of Mutations and Evaluation of Machine Learning Algorithms in Predicting the Therapeutic Outcomes of Warfarin.

Aim: The study aimed to identify the key pharmacogenetic variable influencing the therapeutic outcomes of warfarin using machine learning algorithms and bioinformatics tools.

Background: Warfarin, a commonly used anticoagulant drug, is influenced by cytochrome P450 (CYP) enzymes, particularly . MLAs have been identified to have great potential in personalized therapy.

Machine learning algorithms and computational validation of single-nucleotide polymorphisms of antioxidant enzymes and oxidative stress markers in neonates.

To evaluate machine learning algorithms (MLAs) for predicting factors (oxidative stress biomarkers [OSBs] and single-nucleotide polymorphism of the antioxidant enzymes) for respiratory distress syndrome (RDS) and significant alterations in the liver functions (SALVs). MLAs were applied for predicting the RDS and SALV (with OSB and single-nucleotide polymorphisms in the antioxidant enzymes) with area under the curve (AUC) as the accuracy measure. The C5.

Unraveling the Dysbiosis of Vaginal Microbiome to Understand Cervical Cancer Disease Etiology-An Explainable AI Approach.

Microbial Dysbiosis is associated with the etiology and pathogenesis of diseases. The studies on the vaginal microbiome in cervical cancer are essential to discern the cause and effect of the condition. The present study characterizes the microbial pathogenesis involved in developing cervical cancer.

Integrated gene network analysis sheds light on understanding the progression of Osteosarcoma.

Introduction: Osteosarcoma is a rare disorder among cancer, but the most frequently occurring among sarcomas in children and adolescents. It has been reported to possess the relapsing capability as well as accompanying collateral adverse effects which hinder the development process of an effective treatment plan. Using networks of omics data to identify cancer biomarkers could revolutionize the field in understanding the cancer.

The impact of human papilloma virus on human reproductive health and the effect on male infertility: An updated review.

It is believed that human papilloma virus infection (HPV), which is caused by the DNA virus, is the most prominent factor contributing to sexually transmitted disease (STD) in the world, with males having a prevalence rate of 3.5%-45% while that women are 2%-44%. Infertility is a rising problem on a global basis, affecting anywhere from 10% to 30% of couples who have reached reproductive age.

At Risk Safety Behaviors of the Perioperative Nursing Team: A Direct Observational Study.

Background: The operating room setting has unique workforce hazards and extremely high ergonomic demands due to patient lifting/positioning requirements, long periods of standing, and the heavy equipment and supplies that are needed for surgical procedures. Despite worker safety policies, injuries among registered nurses are increasing. Most of the research on the ergonomic safety of nurses is conducted utilizing survey methodology, which may not provide accurate data.

Non-coding RNAs in human health and disease: potential function as biomarkers and therapeutic targets.

Human diseases have been a critical threat from the beginning of human history. Knowing the origin, course of action and treatment of any disease state is essential. A microscopic approach to the molecular field is a more coherent and accurate way to explore the mechanism, progression, and therapy with the introduction and evolution of technology than a macroscopic approach.

Effects of the pathological E200K mutation on human prion protein: A computational screening and molecular dynamics approach.

The human prion protein gene (PRNP) is mapped to the short arm of chromosome 20 (20pter-12). Prion disease is associated with mutations in the prion protein-encoding gene sequence. Earlier studies found that the mutation G127V in the PRNP increases protein stability.

An integrated investigation of structural and pathway alteration caused by PIK3CA and TP53 mutations identified in cfDNA of metastatic breast cancer.

In peripheral blood, cell-free DNA (cfDNA) contains circulating tumor DNA (ctDNA), which indicates molecular abnormalities in metastatic breast tumor tissue. The sequencing of cfDNA of Metastatic Breast Cancer (MBC) patients allows assessment of therapy response and noninvasive treatment. In the proposed study, clinically significant alterations in PIK3CA and TP53 genes associated with MBC resulting in a missense substitution of His1047Arg and Arg282Trp from an next-generation sequencing-based multi-gene panel were reported in a cfDNA of a patient with MBC.