Biology subjects

Cinar, O.

Publications and source records attributed to Cinar, O..

3 recordsLinked to original sources

bioRxiv2026

User-friendly transcriptomic data analysis with ArrayAnalysis

Transcriptomic profiling has become a cornerstone of modern biomedical research. To make transcriptomic analyses accessible to a broader scientific community, specifically including researchers with limited bioinformatics expertise, we introduced ArrayAnalysis in 2013 as a user-friendly web-based application for microarray data analysis. We now present a major update (https://arrayanalysis.org), introducing a strongly interactive platform that facilitates the dedicated exploration and analysis of both microarray and RNA-seq data, and allows for the generation of publication-ready outputs. Users can perform key analysis steps, including data pre-processing and quality control, differential expression analysis, and gene set analysis, via a sequential, interactive workflow. At each step, the application provides interactive visualizations accompanied by information pages to support interpretation. Users can dynamically adjust figure layouts and colour palettes and export figures as vector graphics and high-resolution raster images. For non-expert users, ArrayAnalysis offers step-by-step guidance to support correct usage and facilitate learning, while for experienced bioinformaticians, it provides a streamlined and flexible workflow ideal for large-scale analyses requiring efficient and consistent processing. ArrayAnalysis is available both as a web application and for local deployment as a desktop application, Docker image, or R package, making it suitable for diverse computational environments, user groups, and analytical purposes. Together, ArrayAnalysis empowers a broad community of biomedical researchers to unlock the full potential of transcriptomic data. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=96 SRC="FIGDIR/small/738193v1_ufig1.gif" ALT="Figure 1"> View larger version (39K): org.highwire.dtl.DTLVardef@1072123org.highwire.dtl.DTLVardef@11095e0org.highwire.dtl.DTLVardef@1dfaee7org.highwire.dtl.DTLVardef@53d31e_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2024

Boosting Proteasome Activity: A Novel Mechanism of NMDAR Blockers Against Neurodegeneration

NMDAR antagonists, such as memantine and ketamine, have shown efficacy in treating neurodegenerative diseases and major depression. The mechanism by which these drugs correct the aforementioned diseases is still unknown. Our study reveals that these antagonists significantly enhance 20S proteasome activity, crucial for degrading intrinsically disordered, oxidatively damaged, or misfolded proteins, factors pivotal in neurodegenerative diseases like Alzheimers and Parkinsons. In a mouse model, ketamine administration notably altered brain synaptic protein profiles within two hours, downregulating proteins linked to neurodegenerative conditions. Furthermore, the altered proteins exhibited enrichment in terms related to plasticity and potentiation, including retrograde endocannabinoid signaling--a pivotal pathway in both short- and long-term plasticity that may elucidate the long-lasting effects of ketamine in major depression. Via the ubiquitin-independent 20S proteasome pathway (UIPS), these drugs maintain cellular protein homeostasis, crucial as proteasome activity declines with age leading to protein aggregation and disease symptoms. The elucidation of the mechanistic pathways underlying the therapeutic effects of NMDAR antagonists holds promise for developing new treatment strategies for brain diseases, including schizophrenia, Alzheimers, and Parkinsons.

neuroscience↗

bioRxiv2019

Interaction between polygenic liability for schizophrenia and childhood adversity influences daily-life emotional dysregulation and psychosis proneness

BackgroundThe earliest stages of the pluripotent psychopathology on the pathway to psychotic disorders is represented by emotional dysregulation and subtle psychosis expression, which can be measured using the Ecological Momentary Assessment (EMA). However, it is not clear to what degree common genetic and environmental risk factors for psychosis contribute to variation in these early expressions of psychopathology.\n\nMethodsIn this largest ever EMA study of a general population twin cohort including 593 adolescents and young adults between the ages of 15 and 35 years, we tested whether polygenic risk score for schizophrenia (PRS-S) interacts with childhood adversity (the Childhood Trauma Questionnaire score) and daily-life stressors to influence momentary mental state domains (negative affect, positive affect, and subtle psychosis expression) and stress-sensitivity measures.\n\nResultsBoth childhood adversity and daily-life stressors were associated with increased negative affect, decreased positive affect, and increased subtle psychosis expression, while PRS-S was only associated with increased positive affect. No gene-environment correlation was detected. We have provided novel evidence for interaction effects between PRS-S and childhood adversity to influence momentary mental states [negative affect (b = 0.07, 95% CI 0.01 to 0.13, P = 0.013), positive affect (b = -0.05, 95% CI -0.10 to -0.00, P = 0.043), and subtle psychosis expression (b = 0.11, 95% CI 0.03 to 0.19, P = 0.007)] and stress-sensitivity measures.\n\nConclusionExposure to childhood adversities, particularly in individuals with high PRS-S, is pleiotropically associated with emotional dysregulation and psychosis proneness.

genomics↗