Heterogeneity and molecular landscape of melanoma: implications for targeted therapy.

Uveal cancer (UM) offers a complex molecular landscape characterized by substantial heterogeneity, both on the genetic and epigenetic levels. This heterogeneity plays a critical position in shaping the behavior and response to therapy for this uncommon ocular malignancy. Targeted treatments with gene-specific therapeutic molecules may prove useful in overcoming radiation resistance, however, the diverse molecular makeups of UM call for a patient-specific approach in therapy procedures.

Spectroscopic investigation and structural simulation in human serum albumin with hydroxychloroquine/Silybum marianum and a possible potential COVID-19 drug candidate.

In this study, the interaction between human serum albumin (HSA) and the hydroxychloroquine/Silybum marianum (HCQ/SM) mixture was investigated using various techniques. The observed high binding constant (K) and Stern-Volmer quenching constant (K) indicate a strong binding affinity between the HCQ/SM mixture and HSA. The circular dichroism (CD) analysis revealed that HCQ/SM induced conformational changes in the secondary structure of HSA, leading to a decrease in the α-helical content.

Deciphering the impact of microbial interactions on COPD exacerbation: An in-depth analysis of the lung microbiome.

In microbiome studies, the diversity and types of microbes have been extensively explored; however, the significance of microbial ecology is equally paramount. The comprehension of metabolic interactions among the wide array of microorganisms in the lung microbiota is indispensable for understanding chronic pulmonary disease and for the development of potent treatments. In this investigation, metabolic networks were simulated, and ecological theory was employed to assess the diagnosis of COPD, subsequently suggesting innovative treatment strategies for COPD exacerbation.

Restoring the epigenetic landscape of lung microbiome: potential therapeutic approach for chronic respiratory diseases.

Background: Chronic respiratory diseases, such as chronic obstructive pulmonary disease (COPD) and bronchiectasis, present significant threats to global health. Recent studies have revealed the crucial role of the lung microbiome in the development of these diseases. Pathogens have evolved complex strategies to evade the immune response, with the manipulation of host cellular epigenetic mechanisms playing a pivotal role.

Cohort profile update: Tehran cardiometabolic genetic study.

The Tehran cardiometabolic genetic study (TCGS) is a large population-based cohort study that conducts periodic follow-ups. TCGS has created a comprehensive database comprising 20,367 participants born between 1911 and 2015 selected from four main ongoing studies in a family-based longitudinal framework. The study's primary goal is to identify the potential targets for prevention and intervention for non-communicable diseases that may develop in mid-life and late life.

Parallel molecular alteration between Alzheimer's disease and major depressive disorder in the human brain dorsolateral prefrontal cortex: an insight from gene expression and methylation profile analyses.

Alzheimer's disease (AD) and major depressive disorder (MDD) are comorbid neuropsychiatric disorders that are among the leading causes of long-term disability worldwide. Recent research has indicated the existence of parallel molecular mechanisms between AD and MDD in the dorsolateral prefrontal cortex (DLPFC). However, the premorbid history and molecular mechanisms have not yet been well characterized.

A knowledge-based protein-protein interaction inhibition (KPI) pipeline: an insight from drug repositioning for COVID-19 inhibition.

The inhibition of protein-protein interactions (PPIs) by small molecules is an exciting drug discovery strategy. Here, we aimed to develop a pipeline to identify candidate small molecules to inhibit PPIs. Therefore, KPI, a Knowledge-based Protein-Protein Interaction Inhibition pipeline, was introduced to improve the discovery of PPI inhibitors.

Impact of 5HydroxyMethylCytosine (5hmC) on reverse/direct association of cell-cycle, apoptosis, and extracellular matrix pathways in gastrointestinal cancers.

Background: Aberrant levels of 5-hydroxymethylcytosine (5-hmC) can lead to cancer progression. Identification of 5-hmC-related biological pathways in cancer studies can produce better understanding of gastrointestinal (GI) cancers. We conducted a network-based analysis on 5-hmC levels extracted from circulating free DNAs (cfDNA) in GI cancers including colon, gastric, and pancreatic cancers, and from healthy donors.

Drug repositioning in non-small cell lung cancer (NSCLC) using gene co-expression and drug-gene interaction networks analysis.

Lung cancer is the most common cancer in men and women. This cancer is divided into two main types, namely non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC). Around 85 to 90 percent of lung cancers are NSCLC.

The AGT epistasis pattern proposed a novel role for ZBED9 in regulating blood pressure: Tehran Cardiometabolic genetic study (TCGS).

Introduction: High blood pressure is widely regarded as the most important risk factor for cardiovascular diseases. Epistasis analysis may provide additional insight into the genetic basis of hypertension.

Methods: A nested case-control design was used on 4214 unrelated Tehran Cardiometabolic Genetic Study (TCGS) adults to evaluate 65 SNPs of previously associated genes, including ZBED9, AGT, and TNXB.

Evaluating machine learning-powered classification algorithms which utilize variants in the GCKR gene to predict metabolic syndrome: Tehran Cardio-metabolic Genetics Study.

Background: Metabolic syndrome (MetS) is a prevalent multifactorial disorder that can increase the risk of developing diabetes, cardiovascular diseases, and cancer. We aimed to compare different machine learning classification methods in predicting metabolic syndrome status as well as identifying influential genetic or environmental risk factors.

Methods: This candidate gene study was conducted on 4756 eligible participants from the Tehran Cardio-metabolic Genetic study (TCGS).

Computer Gaming and Physiological Changes in the Brain: An Insight from QEEG Complexity Analysis.

To compare the pattern of brain waves in video game addicts and normal individuals, a case-control study was carried out on both. Thirty participants were recruited from 14 to 20 years old males from two gaming centers. Twenty healthy participants were gathered from different schools in Tehran using the available sampling method.

High-throughput analysis of the interactions between viral proteins and host cell RNAs.

RNA-protein interactions of a virus play a major role in the replication of RNA viruses. The replication and transcription of these viruses take place in the cytoplasm of the host cell; hence, there is a probability for the host RNA-viral protein and viral RNA-host protein interactions. The current study applies a high-throughput computational approach, including feature extraction and machine learning methods, to predict the affinity of protein sequences of ten viruses to three categories of RNA sequences.

Revealing transcriptional and post-transcriptional regulatory mechanisms of γ-glutamyl transferase and keratin isoforms as novel cooperative biomarkers in low-grade glioma and glioblastoma multiforme.

Gamma-glutamyltransferase (GGT) and keratins (KRT) are key factors in regulating tumor progression rely on emerging evidence. However, the prognostic values of GGT and KRT isoforms and their regulation patterns at transcriptional and post-transcriptional levels have been rarely studied. In this study, we aimed to identify cooperative prognostic biomarker signature conducted by GGT and KRT genes for overall survival prediction and discrimination in patients with low-grade glioma (LGG) and glioblastoma multiforme (GBM).

Interplay between SARS-CoV-2 and human long non-coding RNAs.

The long non-coding RNAs (lncRNAs) play a critical regulatory role in the host response to the viral infection. However, little is understood about the transcriptome architecture, especially lncRNAs pattern during the SARS-CoV-2 infection. In the present study, using publicly available RNA sequencing data of bronchoalveolar lavage fluid (BALF) and peripheral blood mononuclear cells (PBMC) samples from COVID-19 patients and healthy individuals, three interesting findings highlighted: (a) More than half of the interactions between lncRNAs-PCGs of BALF samples established by three trans-acting lncRNAs (HOTAIRM1, PVT1 and AL392172.

In silico design of novel aptamers utilizing a hybrid method of machine learning and genetic algorithm.

Aptamers can be regarded as efficient substitutes for monoclonal antibodies in many diagnostic and therapeutic applications. Due to the tedious and prohibitive nature of SELEX (systematic evolution of ligands by exponential enrichment), the in silico methods have been developed to improve the enrichment processes rate. However, the majority of these methods did not show any effort in designing novel aptamers.

SARS-CoV-2 infection susceptibility influenced by ACE2 genetic polymorphisms: insights from Tehran Cardio-Metabolic Genetic Study.

The genetic variations among individuals are one of the notable factors determining disease severity and drug response. Nowadays, COVID-19 pandemic has been adversely affecting many aspects of human life. We used the Tehran Cardio-Metabolic Genetic Study (TCGS) data that is an ongoing genetic study including the whole-genome sequencing of 1200 individuals and chip genotyping of more than 15,000 participants.

The Stabilizing Mechanism of Immobilized Metagenomic Xylanases on Bio-Based Hydrogels to Improve Utilization Performance: Computational and Functional Perspectives.

While polysaccharide-based superabsorbent hydrogels (SHs) have attracted increasing interest as proficient carriers in the enzyme immobilization, the nature of the favored interactions between the SHs and enzymes is still unclear. Herein, a combined experimental and computational study was employed to investigate the dominant parameters affecting on the stabilization of two metagenomic xylanases on the SHs. The thermostable enzymes (PersiXyn3 and PersiXyn4) with similar domains were screened, cloned, expressed, and purified from cattle rumen metagenome.

RPINBASE: An online toolbox to extract features for predicting RNA-protein interactions.

Feature extraction is one of the most important preprocessing steps in predicting the interactions between RNAs and proteins by applying machine learning approaches. Despite many efforts in this area, still, no suitable structural feature extraction tool has been designed. Therefore, an online toolbox, named RPINBASE which can be applied to different scopes of biological applications, is introduced in this paper.

Peptide LIQ Promotes Cell Protection against Zinc-Induced Cytotoxicity through Microtubule Stabilization.

Stability of the microtubule protein (MTP) network required for its physiological functions is disrupted in the course of neurodegenerative disorders. Thus, the design of novel therapeutic approaches for microtubule stabilization is a focus of intensive study. Dynamin-related protein-1 (Drp1) is a guanosine triphosphatase (GTPase), which plays a prevailing role in mitochondrial fission.