Identification of proteins' expression pathway and the effective miRNAs for the treatment of human papillomavirus-induced cervical cancer: in-silico analyses-experimental research.

Introduction: Cervical cancer is the fourth most common cancer in women. The risk factors for cervical cancer include human papillomavirus (HPV) infection, age, smoking, number of pregnancies, use of oral contraceptives, and diet. However, long-term HPV infection appears to be the main risk factor for developing cervical cancer.

From Multiple Sclerosis to Organ-Specific Autoimmune Disorders: Insights into the Molecular and Clinical Implications of Comorbidity.

Multiple sclerosis (MS) is a complex autoimmune disorder that affects the central nervous system. Although the pathological mechanisms of MS have been extensively studied, its association with other autoimmune diseases, known as comorbidities, remains unclear. In this comprehensive review article, we aim to clarify the cellular and molecular relationship between MS and the incidence of organ-specific autoimmune comorbidities by summarizing former studies.

Complement protein expression changes in various conditions of breast cancer: in-silico analyses-experimental research.

Introduction: Breast cancer is the most prevalent cancer diagnosed in females worldwide. The known biomarkers are insufficient to understand the actual prognosis of breast cancer, and identifying new biomarkers is desirable and valuable data to improve the patient's survival. Many inflammatory biomarkers, such as the complement system, can be regarded as prognostic values and as potent inflammatory mediators; complement proteins have a critical role in tumorigenesis.

Prediction of immune molecules activity during burn wound healing among elderly patients: in-silico analyses: experimental research.

Introduction: Burn injuries lead to dysregulation of immune molecules, impacting cellular and humoral immune pathways. This study aims to determine the prediction of immune molecule activity during burn wound healing among elderly patients.

Methods: The current study utilized the Gene Expression Omnibus (GEO) database to extract the proper gene set.

Decoding common genetic alterations between Barrett's esophagus and esophageal adenocarcinoma: A bioinformatics analysis.

Background: Esophageal adenocarcinoma (EAC) is a common cancer with a poor prognosis in advanced stages. Therefore, early EAC diagnosis and treatment have gained attention in recent decades. It has been found that various pathological changes, particularly Barrett's Esophagus (BE), can occur in the esophageal tissue before the development of EAC.

Identification of a valuable gene network for the diagnosis and treatment of non-obstructive azoospermia: in-silico analyses - experimental research.

Introduction: Non-obstructive azoospermia (NOA) is an etiology of infertility in men. NOA may have various classifications; however, hypogonadotropic hypogonadism can be regarded as a class of NOA associated with genetic factors. Former studies have shown that noncoding RNA (ncRNA) plays an essential role in NOA incidence, but few studies have been performed on the NOA-related ncRNA interaction network.

SARS-CoV-2 helicase might interfere with cellular nonsense-mediated RNA decay: insights from a bioinformatics study.

Background: Viruses employ diverse strategies to interfere with host defense mechanisms, including the production of proteins that mimic or resemble host proteins. This study aimed to analyze the similarities between SARS-CoV-2 and human proteins, investigate their impact on virus-host interactions, and elucidate underlying mechanisms.

Results: Comparing the proteins of SARS-CoV-2 with human and mammalian proteins revealed sequence and structural similarities between viral helicase with human UPF1.

Risk predictions of hospital-acquired pressure injury in the intensive care unit based on a machine learning algorithm.

Pressure injury (PI), or local damage to soft tissues and skin caused by prolonged pressure, remains controversial in the medical world. Patients in intensive care units (ICUs) were frequently reported to suffer PIs, with a heavy burden on their life and expenditures. Machine learning (ML) is a Section of artificial intelligence (AI) that has emerged in nursing practice and is increasingly used for diagnosis, complications, prognosis, and recurrence prediction.

Long non‑coding RNA LINC00460 contributes as a potential prognostic biomarker through its oncogenic role with ANXA2 in colorectal polyps.

Background: Long intergenic non-coding RNA 460 (LINC00460) as a potential oncogene and Annexin A2 (ANXA2) as a promoter in different cancer progression processes was considered. A significant relationship between the LINC00460 and ANXA2 has been recently discovered in colorectal cancer (CRC). Therefore, defining molecular biomarkers accompanied by lesion histopathologic features can be a suggestive prognostic biomarker in precancerous polyps.

SARS-CoV-2 spike protein displays sequence similarities with paramyxovirus surface proteins; a bioinformatics study.

Recent emergence of SARS-CoV-2 and associated COVID-19 pandemic have posed a great challenge for the scientific community. In this study, we performed bioinformatic analyses on SARS-CoV-2 protein sequences, trying to unravel potential molecular similarities between this newly emerged pathogen with non-coronavirus ssRNA viruses. Comparing the proteins of SARS-CoV-2 with non-coronavirus positive and negative strand ssRNA viruses revealed multiple sequence similarities between SARS-CoV-2 and non-coronaviruses, including similarities between RNA-dependent RNA-polymerases and helicases (two highly-conserved proteins).