Biology subjects

Abbasi, H.

Publications and source records attributed to Abbasi, H..

9 recordsLinked to original sources

bioRxiv2026

Modeled Oxidative Lesions Remodel the ABCB1 Linker: A Hypothesis for Transporter Regulation

Multidrug resistance mediated by P-glycoprotein (P-gp; ABCB1) remains a major barrier to chemotherapy. Cold atmospheric plasma (CAP) has increased drug responsiveness in resistant cancer models, but the molecular link between plasma-derived oxidative chemistry and ABCB1 regulation remains unresolved. We investigated whether site-specific oxidative lesions remodel the intrinsically disordered linker connecting nucleotide-binding domain 1 to transmembrane domain 2. Native-ensemble exposure analysis identified contrasting oxidation candidates: dynamically exposed Met653 and persistently exposed Trp698. Met653 oxidation to methionine sulfoxide and Trp698 oxidation to kynurenine were examined individually and together using a balanced 2 by 2 molecular-dynamics design with a mechanically tethered linker construct. Analyses integrated global descriptors, residue-resolved mobility, backbone order, native-state occupancies, projected breadth, and conformational switching. Trp698[->]KYN produced the dominant response: all seven global descriptors shifted toward restriction, accompanied by distributed mobility changes, compaction, and increased intramolecular hydrogen bonding. In the radius-of-gyration/end-to-end-distance projection, compact-state occupancy increased from 46.9% to 99.7%, switching decreased from 6.50 to 0.07 transitions per 10 ns, and projected breadth contracted. Met653[->]SME produced weaker, heterogeneous effects, while the double-modified linker remained restricted but showed greater projected exchange than Trp698[->]KYN alone. In this model, Trp698[->]KYN generated a compact, low-exchange projected ensemble in the tethered ABCB1 linker. These findings identify oxidation-site-specific linker remodeling as a candidate molecular intermediate that could influence linker-mediated domain coordination, while requiring experimental validation of lesion formation, transporter activity, and multidrug resistance outcomes.

biophysics↗

bioRxiv2026

CRADLE: A Clinically Robust, Anatomy-Aware Post-Processing Framework for Infant GMA Landmark Tracking in 2D Videos

Accurate pose estimation is central to automated infant General Movements Assessment during the fidgety period, when subtle limb movements, particularly at distal joints inform neurodevelopmental risks. Robust 2D pose tracking from handheld videos remains challenging in real-world settings, where occlusion, rapid motions, and visually ambiguous smaller joints frequently compromise anatomical accuracy. We present CRADLE, a clinically motivated, anatomy-aware post-processing pipeline designed to refine infant 2D movement trajectories across 24-anatomocal landmarks detected by our DeepLabCut-trained model. CRADLE integrates segment-length constraints, velocity-based anomaly detection, anatomically constrained interpolation, and Kalman filtering to correct both large localization failures and subtle persistent joint misplacements without relying primarily on confidence scores. Evaluations against conventional Confidence-Thresholding using Mean Absolute Error (MAE), {Delta}MAE, average Percentage of Correct Keypoints, and net keypoint correction rate showed consistently reduced or preserved error while maintaining accurate trajectories, with the strongest gains achieved at clinically important distal joints. Mean improvements reached up to 5 pixels for some smaller distal landmarks, large-magnitude corrections occurred more often than with Confidence-Thresholding, and well-localised joints remained largely unaffected. Positive net correction rates across metacarpophalangeal and metatarsophalangeal distal-landmarks further confirmed a favourable correction-degradation balance. By improving pose trajectory quality, CRADLE enhances the reliability of downstream movement analysis.

bioengineering↗

bioRxiv2026

Whole-Slide Mapping of Tumor Tissue Fiber Architecture via Computational Scattered Light Imaging

Mapping peritumoral collagen fiber directionality in solid tumors may assist in determining cancer progression and support more personalized prognoses. However, existing microscopy techniques are often limited by a restricted field of view, high cost, or incompatibility with paraffin-treated tissues. Computational scattered light imaging (ComSLI) is a cost-effective whole-slide microscopy technique that reveals fiber orientations independent of sample preparation. Using glioma, colorectal, and head and neck cancer samples, we show for the first time that ComSLI maps fiber orientations in paraffin-treated tumor tissues, visualizes tumor growth pathways and desmoplastic reactions, and allows the study of collagen orientations relative to tumor boundaries.

cancer biology↗

bioRxiv2026

Application of Explainable AI in Neuroscience: Enhancing Autism Screening

The main challenges in the life of a child with autism are difficulties in communication, behavior, and social interaction. Early diagnosis of this neurodevelopmental disorder improves patient outcomes by enabling more effective, personalized interventions. This diagnosis can sometimes be difficult, especially in very young children. Non-invasive, relatively accessible, and able to reflect neural function in real time, electroencephalography (EEG) shows promise in the detection of Autism spectrum disorders (ASD). However, because EEG data is still difficult for experts to understand, machine learning and artificial intelligence (AI) are beginning to be used in this field as well. In this paper, a ResNet+BiLSTM hybrid deep network was applied and achieved high accuracy in distinguishing individuals with autism from neurotypical subjects. Since AI models typically provide predictions without clear explanations, this study employs explainable AI (XAI) methods such as SHAP (SHapley Additive exPlanations) and LIME (Local Interpretable Model-agnostic Explanations) to clarify their decision-making.Delta, theta, alpha, beta, and gamma waves, as well as ERP components P100, N100, P200, MMN, and P600, were analyzed in the two neurotypical and autistic groups that were compared in this study using EEG recordings. By integrating SHAP and LIME, the system achieved both accurate classification and transparent explanations, pointing to EEG- and ERP-based features as reliable biomarkers for ASD.

neuroscience↗

bioRxiv2025

From Flexibility to Vulnerability: Targeting P-glycoprotein with Cold Atmospheric Plasma-Derived Reactive Species to Overcome Multidrug Resistance

Multidrug resistance (MDR) remains a major obstacle to the efficacy of chemotherapy in cancer treatment. Experimental evidence highlights the pivotal role of drug efflux transporters, such as P-glycoprotein (Pgp), in this phenomenon. Furthermore, studies underscore the significance of linker region flexibility within Pgp in modulating its function. In this study, we propose a novel non-pharmacological strategy to inhibit Pgp activity by targeting the structural flexibility of its linker region. Using molecular dynamics simulations, we investigated the effects of three reactive species generated by cold atmospheric pressure plasma--hydrogen peroxide (HP), nitric oxide (NO), and molecular oxygen (O2)--on the conformational dynamics of the linker. Comprehensive analyses, including conformational entropy, effective spring constants, polymer-like behavior, and hydrogen bonding networks, revealed that these reactive species substantially restrict the structural flexibility of the linker domain. Among them, HP exhibited the most pronounced stiffening effect, primarily driven by stable electrostatic interactions and the formation of strong hydrogen bonds. This reduction in flexibility is likely to hinder the conformational transitions required for drug efflux, thereby locking Pgp in an inactive or impaired state. Our findings not only provide new insights into the structural dynamics of Pgp in response to cold plasma-derived species, but also open up promising avenues for the development of combinatorial therapeutic strategies aimed at overcoming drug resistance.

molecular biology↗

bioRxiv2025

Collagen fibre organisation revealed with computational scattered light imaging and polarimetric second harmonic generation microscopy

Collagen forms dense fibre networks in the human body, with the organisation directly influencing tissue mechanics and function in health and disease. A good understanding of this relation requires proper imaging techniques for visualising the dense collagen network. Previously, computational scattered light imaging was employed as a fast and easy-to-implement technique to retrieve the orientation of multi-directional collagen fibres, but results were not yet validated quantitatively. In this study, we validate the in-plane orientations of collagen fibres determined with computational scattered light imaging by performing comparative measurements with polarimetric second harmonic generation microscopy on rat tendon and bone sections. For rat tendon, sections with and without hematoxylin-and-eosin staining, folded tendon layers, and obliquely cut sections were investigated. Similar fibre orientations were obtained with both techniques in both tissues, with the highest degree of similarity found for in-plane, unidirectional fibres in the tendon sections. The techniques were able to retrieve the orientations of multi-directional crossing collagen fibres in folded rat tendon layers, and results were found to be unaffected by staining. While polarimetric second harmonic generation microscopy provides high resolution and ultrastructural information on collagen, computational scattered light imaging provides large field of view measurements with micrometre resolution.

bioengineering↗

bioRxiv2024

Uncovering microstructural architecture from histology

Mapping the brains fiber network is crucial for understanding its function and malfunction, but resolving nerve trajectories over large fields of view is challenging. Here, we show that computational scattered light imaging (ComSLI) can map fiber networks in histology independent of sample preparation, also in formalin-fixed paraffin-embedded (FFPE) tissues including whole human brain sections. We showcase this method in new and archived, animal and human brain sections, for different sample preparations (in paraffin, deparaffinized, various stains, unstained fresh-frozen). We convert microscopic orientations to microstructure-informed fiber orientation distributions (FODs). Adapting tractography tools from diffusion magnetic resonance imaging (dMRI), we trace axonal trajectories revealing white and gray matter connectivity. These allow us to identify altered microstructure or deficient tracts in demyelinating or neurodegenerating pathology, and to show key advantages over dMRI, polarization microscopy, and structure tensor analysis. Finally, we map fibers in non-brain tissues, including muscle, bone, and blood vessels, unveiling the tissues function. Our cost-effective, versatile approach enables micron-resolution studies of intricate fiber networks across tissues, species, diseases, and sample preparations, offering new dimensions to neuroscientific and biomedical research.

pathology↗

bioRxiv2023

Conserved features of eye movement related eardrum oscillations (EMREOs) across humans and monkeys

Auditory and visual information involve different coordinate systems, with auditory spatial cues anchored to the head and visual spatial cues anchored to the eyes. Information about eye movements is therefore critical for reconciling visual and auditory spatial signals. The recent discovery of eye movement-related eardrum oscillations (EMREOs) suggests that this process could begin as early as the auditory periphery. How this reconciliation might happen remains poorly understood. Because humans and monkeys both have mobile eyes and therefore both must perform this shift of reference frames, comparison of the EMREO across species can provide insights to shared and therefore important parameters of the signal. Here we show that rhesus monkeys, like humans, have a consistent, significant EMREO signal that carries parametric information about eye displacement as well as onset times of eye movements. The dependence of the EMREO on the horizontal displacement of the eye is its most consistent feature, and is shared across behavioral tasks, subjects, and species. Differences chiefly involve the waveform frequency (higher in monkeys than in humans) and patterns of individual variation (more prominent in monkeys than humans), and the waveform of the EMREO when factors due to horizontal and vertical eye displacements were controlled for.

neuroscience↗

bioRxiv2022

Deep-Learning for Automated Markerless Tracking of Infants General Movements

The presence of abnormal infant General Movements (GMs) is a strong predictor of progressive neurodevelopmental disorders, including cerebral palsy (CP). Automation of the assessment will overcome scalability barriers that limit its delivery to at-risk individuals. Here, we report a robust markerless pose-estimation scheme, based on advanced deep-learning technology, to track infant movements in consumer mobile device video recordings. Two deep neural network models, namely Efficientnet-b6 and resnet152, were trained on manually annotated data across twelve anatomical locations (3 per limb) in 12 videos from 6 full-term infants (mean age = 17.33 (SD 2.9) wks, 4 male, 2 female), using the DeepLabCut framework. K-fold cross-validation indicates the generalization capability of the deep-nets for GM tracking on out-of-domain data with an overall performance of 95.52% (SD 2.43) from the best performing model (Efficientnet-b6) across all infants (performance range: 84.32- 99.24% across all anatomical locations). The paper further introduces an automatic, unsupervised strategy for performance evaluation on extensive out-of-domain recordings through a fusion of likelihoods from a Kalman filter and the deep-net. Findings indicate the possibility of establishing an automated GM tracking platform, as a suitable alternative to, or support for, the current observational protocols for early diagnosis of neurodevelopmental disorders in early infancy.

bioengineering↗