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Given the critical role of human papillomavirus (HPV) in the cause of cervical cancer and other malignancies, there is a need for innovative approaches to preventing this infection. It has been shown that immunoinformatics is an important strategy in computational vaccinology. It is used to design new multi-epitope vaccines against different types of HPV and subsequent cervical cancer. This paper reviews the scope of the entire computational pipeline of HPV vaccine design, starting from data analysis at the genomic and proteomic levels and continuing to epitope predictions of the innate and adaptive immune systems. The search strategy was based on investigating original articles published in “Google Scholar" and “PubMed" from 2015 to 2023-2024. The terms "Immunoinformatics", "Bioinformatics", "Human papillomavirus (HPV)", "Vaccine design", "In silico vaccine design", "Multi-epitope vaccine design", "Vaccinology" and "HPV vaccine" were used to for this purpose. We discussed various essential tools involved in the computational design of the vaccine process, e.g., sequence analysis, epitope prediction, conservancy analysis, tertiary structure modeling, refinement, molecular docking, molecular dynamics (MD) simulation, and in silico cloning. This review article describes immunoinformatics methods that facilitate the design of a multi-epitope vaccine against HPV. However, this pipeline can also be used to design novel chimeric vaccines for other pathogens. [ABSTRACT FROM AUTHOR]

Objective: The prevalence of neurological disorders often varies by sex, with conditions such as Alzheimer’s disease and autism spectrum disorder (ASD) demonstrating notable differences in incidence. The aim of this study is to understand the molecular basis for these divergences in order to facilitate the creation of sex-specific therapeutic strategies. Materials and Methods: This study is a bioinformatic analysis of publicly available RNA sequencing datasets involving autism patients. The study utilized RNA sequencing data from postmortem human brains’ prefrontal cortex, including 38 neurotypical controls and 34 individuals with ASD. The sequencing data was obtained from previously published papers, and we downloaded the raw data from SRA. We investigated the molecular basis of sex-biased presentation in ASD through comprehensive transcriptomic analysis. Results: Comparative analysis of gene expression between male and female subjects, both autistic and unaffected, was conducted, using a significance level of ≤0.01. In autistic individuals, 136 genes demonstrated differential expression between sexes, predominantly upregulated in males, indicating a bias in male gene expression. Among these, 12 genes were identified as risk factors in the SFARI dataset. While most sex-biased genes were autosomal, expression differences on sex chromosomes were also observed in neurotypical subjects. Notable genes included TCF7L2, collagen family genes, and solute carrier family genes. In ASD males, extracellular matrix (ECM) organization emerged as a significant pathway, while immune-related processes were prominent in unaffected individuals. Conclusion: Our study highlights the impact of the ECM pathway in ASD, with notable differences between sexes, particularly in males. MIR424 shows promise as a potential biomarker for ASD in males. Recognizing the importance of sex differences in ASD transcriptomic research is crucial, as these variances provide insights into the disorder’s pathophysiology and may guide the development of more personalized treatments for both sexes. [ABSTRACT FROM AUTHOR]

Objective: This paper aimed to investigate the PI3K/Akt/mTOR signal-pathway regulator factor-related lncRNA signatures (PAM-SRFLncSigs), associated with regulators of the indicated signaling pathway in patients with lung adenocarcinoma (LUAD) undergoing immunotherapy. Materials and Methods: In this retrospective study, we employed univariate Cox, multivariate Cox, and least absolute shrinkage and selection operator (LASSO) regression analyses to identify prognostically relevant long non-coding RNAs (lncRNAs), construct prognostic models, and perform Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Subsequently, immunoassay and chemotherapy drug screening were conducted. Finally, the prognostic model was validated using the Imvigor210 cohort, and tumor stem cells were analyzed. Results: We identified seven prognosis-related lncRNAs (AC084757.3, AC010999.2, LINC02802, AC026979.2, AC024896.1, LINC00941 and LINC01312). We also developed prognostic models to predict survival in patients with LUAD. KEGG enrichment analysis confirmed association of LUAD with the PI3K/Akt/mTOR signaling pathway. In the analysis of immune function pathways, we discovered three good prognostic pathways (Cytolytic_activity, Inflammation-promoting, T_cell_co-inhibition) in LUAD. Additionally, we screened 73 oncology chemotherapy drugs using the "pRRophetic" algorithm. Conclusion: Identification of seven lncRNAs linked to regulators of the PI3K/Akt/mTOR signaling pathway provided valuable insights into predicting the prognosis of LUAD, understanding the immune microenvironment and optimizing immunotherapy strategies. [ABSTRACT FROM AUTHOR]

This article, published in Cell Journal, explores the relationship between salivary alkaline phosphatase enzyme activity and the concentrations of salivary calcium and phosphate ions. The authors found that the affiliation of the second author was missed during the formatting of the paper and have provided a correction. The article is open-access and has been published under the terms of the Creative Commons Attribution Non-Commercial 3.0 license. [Extracted from the article]

This document is a correction notice for an article titled "Effects of Streptozotocin Induced Diabetes on One-Carbon Cycle and Sperm Function" published in Cell Journal. The correction states that the affiliation of authors and the two corresponding authors were accidentally omitted during the formatting of the paper. The authors apologize for any inconvenience caused. The article is open-access and has been published under the Creative Commons Attribution Non-Commercial 3.0 license. [Extracted from the article]