Antimicrobial resistance (AMR) is one of the threats to our world according to the World Health Organization (WHO). Resistance is an evolutionary dynamic process where host-associated microbes have to adapt to their stressful environments. AMR could be classified according to the mechanism of resistance or the biome where resistance takes place. Antibiotics are one of the stresses that lead to resistance through antibiotic resistance genes (ARGs). The resistome could be defined as the collection of all ARGs in an organism’s genome or metagenome. Currently, there is a growing body of evidence

Non-Structural Protein 6 (NSP6) has a protecting role for SARS-CoV-2 replication by inhibiting the expansion of autophagosomes inside the cell. NSP6 is involved in the endoplasmic reticulum stress response by binding to Sigma receptor 1 (SR1). Nevertheless, NSP6 crystal structure is not solved yet. Therefore, NSP6 is considered a challenging target in Structure-Based Drug Discovery. Herein, we utilized the high quality NSP6 model built by AlphaFold in our study. Targeting a putative NSP6 binding site is believed to inhibit the SR1-NSP6 protein-protein interactions. Three databases were

Type 2 diabetes mellitus (T2D) remains a critical health concern, particularly in its early disease stages such as prediabetes. Understanding these early stages is paramount for improving patient outcomes. Multiomics data integration tools offer promise in unraveling the underlying mechanisms of T2D. The advent of high-throughput technology and the increasing availability of multiomics data has led to the development of several statistical and network-based integration methods. However, the performance of such methods varies, requiring their output evaluation in an unbiased manner. Here, we

Biomedical research and pharmaceutical development have been profoundly impacted by genomics in recent years, with researchers gaining new understanding of the genetic pathways underlying disease and opening up new opportunities for the creation of targeted therapeutic interventions. Without a comprehensive grasp of the genetic mechanisms at play, medication discovery approaches in the past often relied on trial and error, targeting particular symptoms or pathways. However, the advent of genomics has changed the game. Scientific advances in high-throughput DNA sequencing have allowed

Background: Hepatocellular carcinoma (HCC) is the most common primary liver cancer. Chronic hepatitis and liver cirrhosis lead to accumulation of genetic alterations driving HCC pathogenesis. This study is designed to explore genomic landscape of HCC in Egyptian patients by whole exome sequencing. Methods: Whole exome sequencing using Ion Torrent was done on 13 HCC patients, who underwent surgical intervention (7 patients underwent living donor liver transplantation (LDLT) and 6 patients had surgical resection}. Results: Mutational signature was mostly S1, S5, S6, and S12 in HCC. Analysis of

Tables 2, 3, and 6, as shown in the original publication, were modified to black and white during the typesetting process. Following the publication, the authors requested that the tables be reverted to their original-colored versions, as the colors in the heatmap indicate the number of pathogenic variants present in genes. Green indicates the smallest number, and red indicates the highest number. The colored tables are as follows: Heatmap for pathogenic variants in highly mutated genes in HCC samples Heatmap for pathogenic variants in highly mutated genes in Non-HCC samples Heatmap showing

Future always starts now; we simply do not know that! COVID-19 has triggered a new phase of human evolution! It disrupted every aspect of our life. It created new norms for everything, from education to supply chains to employment to healthcare to economy to personal hygiene! We are still in the middle of the pandemic, and the impact on both economic and social levels is not clear yet, and its severity would depend on how long the pandemic would endure. Based on that the paper outlines the disruptions prior to the virus outbreak and acted as a double-edged sword, such as the infodemic

This paper proposes Parallelized Linear Time-Variant Acceleration Coefficients and Inertial Weight of Particle Swarm Optimization algorithm (PLTVACIW-PSO). Its designed has introduced the benefits of Parallel computing into the combined power of TVAC (Time-Variant Acceleration Coefficients) and IW (Inertial Weight). Proposed algorithm has been tested against linear, non-linear, traditional, and multiswarm based optimization algorithms. An experimental study is performed in two stages to assess the proposed PLTVACIW-PSO. Phase I uses 12 recognized Standard Benchmarks methods to evaluate the

There are many water resources like rivers, seas, rains, and groundwater, which can be used in different sectors such as agricultural, domestic, and industrial uses. Therefore, different wastewater effluents with different properties are produced depending on their source. Industrial wastewater is one of the most harmful effluents due to the presence of toxic pollutants such as heavy metals, dyes, and other toxic substances. Usually, water is used in different industries for different internal processes, and then the resulting wastewater is discharged without treatment into the water resources

Adulteration of vinegar to gain economic benefit has become a common practice in recent years. RP-HPLC strategies were proposed for the assurance of the concentration of acetic acid, rare organic acids (tartaric, malic, lactic and citric), and acetaldehyde in Egyptian vinegar samples. The flow rate was 0.5 mL/min using UV detection at 210 and 365 nm for organic acid and acetaldehyde, respectively. The linearity was 0.05-0.60 g/100 mL for acetic acid, 0.01-0.12 g/100 mL for citric, malic, and tartaric acids, 0.005-0.060 g/100 mL for lactic acid, and 0.02-0.16 mg/L for acetaldehyde with r2 > 0