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Peripheral DNA Methylation of Cortisol- and Serotonin-Related Genes Predicts Hippocampal Volume in a Pediatric Population.
Biol Psychiatry Glob Open Sci
March 2025
Department of Psychology, Arizona State University, Tempe, Arizona.
Background: Hippocampal volume increases throughout early development and is an important indicator of cognitive abilities and mental health. However, hippocampal development is highly vulnerable to exposures during development, as seen by smaller hippocampal volume and differential epigenetic programming in genes implicated in mental health. However, few studies have investigated hippocampal volume in relation to the peripheral epigenome across development, and even less is known about potential genetic moderators.
View Article and Find Full Text PDFIdentification of novel cytoskeleton protein involved in spermatogenic cells and sertoli cells of non-obstructive azoospermia based on microarray and bioinformatics analysis.
BMC Med Genomics
January 2025
Department of Surgery, Faculty of General of Medicine, Koya University, Koya, Kurdistan Region - F.R., KOY45, Iraq.
Background: During mammalian spermatogenesis, the cytoskeleton system plays a significant role in morphological changes. Male infertility such as non-obstructive azoospermia (NOA) might be explained by studies of the cytoskeletal system during spermatogenesis.
Methods: The cytoskeleton, scaffold, and actin-binding genes were analyzed by microarray and bioinformatics (771 spermatogenic cellsgenes and 774 Sertoli cell genes).
Exploring the mechanism and drug candidates of alveolar echinococcosis affecting liver fibrosis through analysis of existing microarray data.
Acta Trop
January 2025
Department of Department of Anesthesiology, the First Affiliated Hospital of Xinjiang Medical University, No. 137, South Liyushan Road, Xinshi District, Urumqi, Xinjiang, 830054, China; Xinjiang Perioperative Organ Protection Laboratory, No. 137, South Liyushan Road, Xinshi District, Urumqi, Xinjiang, 830054, China. Electronic address:
Echinococcosis, a zoonotic disease, significantly impacts the liver, with alveolar echinococcosis (AE) often leading to liver fibrosis and, in severe cases, cirrhosis. However, the molecular mechanisms by which AE infection promotes liver fibrosis remain incompletely understood. This study utilized bioinformatic analysis of existing microarray data to explore the shared mechanisms between AE and liver fibrosis and to identify potential therapeutic drug candidates.
View Article and Find Full Text PDFDigital Profiling of Immune Biomarkers in Breast Cancer: Relation to Anthracycline Benefit.
Mod Pathol
January 2025
Interdisciplinary Oncology, University of British Columbia, Vancouver, BC, Canada; MAPcore, University of British Columbia, Vancouver, BC, Canada. Electronic address:
Assessment of the tumor immune microenvironment can be used as a prognostic tool for improved survival and as a predictive biomarker for treatment benefit, particularly from immune modulating treatments including cytotoxic chemotherapy. Using Digital Spatial Profiling (DSP), we studied the tumor immune microenvironment of 522 breast cancer cases by quantifying 35 immune biomarkers on tissue microarrays from the MA.5 phase III clinical trial.
View Article and Find Full Text PDFPredicting the Progression from Asymptomatic to Symptomatic Multiple Myeloma and Stage Classification Using Gene Expression Data.
Cancers (Basel)
January 2025
Bioinformatics Department, The Cyprus Institute of Neurology & Genetics, 6 Iroon Avenue, Ayios Dometios, 2371 Nicosia, Cyprus.
Background: The accurate staging of multiple myeloma (MM) is essential for optimizing treatment strategies, while predicting the progression of asymptomatic patients, also referred to as monoclonal gammopathy of undetermined significance (MGUS), to symptomatic MM remains a significant challenge due to limited data. This study aimed to develop machine learning models to enhance MM staging accuracy and stratify asymptomatic patients by their risk of progression.
Methods: We utilized gene expression microarray datasets to develop machine learning models, combined with various data transformations.
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