Biology subjects

Shuaib, A.

Publications and source records attributed to Shuaib, A..

3 recordsLinked to original sources

bioRxiv2026

A semi-automated pipeline for quantitation of Pax7+, myonuclei, and cross-sectional area by fiber type

Manual analysis of skeletal muscle cross-sections is time-consuming and subject to error and user bias. To overcome these limitations, we developed and validated a semi-automated, quantitative, and reproducible image-analysis pipeline specifically tailored to quantify Pax7+ satellite cells, myonuclei, and cross-sectional area by fiber type. The workflow combines FIJI/ImageJ-based image preprocessing with CellProfiler, Cellpose, and a custom Python script to process and analyze immunohistological images of muscle tissue cross-sections. Outcomes include Pax7+ satellite cells and myonuclei quantified per fiber by fiber type, along with cross-sectional area, perimeter, and fiber type classification. This semi-automated approach provides a robust and efficient platform for high-throughput analysis of muscle tissue cross-sections from large datasets. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=141 SRC="FIGDIR/small/729866v1_ufig1.gif" ALT="Figure 1"> View larger version (44K): org.highwire.dtl.DTLVardef@e85bfdorg.highwire.dtl.DTLVardef@ef75e0org.highwire.dtl.DTLVardef@123e461org.highwire.dtl.DTLVardef@166a304_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2025

A semi-automated pipeline for morphological analysis of myonuclei along single muscle fibers

Manual quantitation of skeletal muscle myonuclear number, spatial orientation, and morphology is time-consuming and subject to error and bias. To overcome these limitations, we developed and validated a semi-automated, quantitative, and reproducible image-analysis pipeline. The workflow combines FIJI-based preprocessing with custom Python scripts to process immunohistological images of individual muscle fibers, enabling high-resolution and scalable quantification of nuclei. Analyses incorporate morphometric parameters including nuclear position, shape, and three-dimensional orientation, as well as centroid-to-skeleton distance and nearest-neighbor relationships to capture spatial patterns of myonuclear organization along the fiber. Outputs include per-fiber and biopsy-level summaries integrated with Imaris metrics. This semi-automated approach provides a robust and efficient platform for high-throughput analysis of myonuclear number and structural features across large single fiber datasets.

cell biology↗

bioRxiv2020

Cognitive and Motor Correlates of Grey and White Matter Pathology in Parkinsons Disease

IntroductionPrevious studies have found associations between grey matter atrophy and white matter hyperintensities (WMH) of vascular origin with cognitive and motor deficits in Parkinsons disease (PD). Here we investigate these relationships in a sample of PD patients and age-matched healthy controls. MethodsData included 50 PD patients and 45 age-matched controls with T1-weighted and FLAIR scans at baseline, 18-months, and 36-months follow-up. Deformation-based morphometry was used to measure grey matter atrophy. SNIPE (Scoring by Nonlocal Image Patch Estimator) was used to measure Alzheimers disease-like textural patterns in the hippocampi. WMHs were segmented using T1-weighted and FLAIR images. The relationship between MRI features and clinical scores was assessed using mixed-effects models. The motor subscore of the Unified Parkinsons Disease Rating Scale (UPDRSIII), number of steps in a walking trial, and Dementia Rating Scale (DRS) were used respectively as measures of motor function, gait, and cognition. ResultsSubstantia nigra atrophy was significantly associated with motor deficits, with a greater impact in PDs (p<0.05). Hippocampal SNIPE scores were associated with cognitve decline in both PD and controls (p<0.01). WMH burden was significantly associated with cognitive decline and increased motor deficits in the PD group, and gait deficits in both PD and controls (p<0.03). ConclusionWhile substantia nigra atrophy and WMH burden were significantly associated with additional motor deficits, WMH burden and hippocampal atrophy were associated with cognitive deficits in PD patients. These results suggest an additive contribution of both grey and white matter damage to the motor and cognitive deficits in PD.

neuroscience↗