Biology subjects

Taha, A.

Publications and source records attributed to Taha, A..

11 recordsLinked to original sources

bioRxiv2026

Concurrent cognitive, behavioral and systemic physiological features mark preclinical Alzheimer's disease

Alzheimer's disease (AD) pathology accumulates years before overt cognitive impairment, yet its multidomain phenotype remains poorly defined. To limit confounding by uncontrolled comorbidities, we assembled a cohort of 644 older adults self-reporting intact cognition, free of systemic or neurological diseases and managed medically for risk factors. Plasma p-tau217 was elevated in 20%, and 93 of these were cognitively unimpaired. This biomarker-defined, risk factor -controlled preclinical AD subgroup showed subtle, concurrent cognitive and behavioral differences, accompanied by modest differences in physiological measures within clinical reference ranges, and alongside higher biomarkers of astrogliosis (GFAP) and neurodegeneration (NfL). Reported modifiable risk factor histories were not associated with p-tau217 when effectively managed. A proof-of-concept AI classifier integrating routine multidomain clinical data improved identification of p-tau217-high individuals relative to cognitive screening alone. These findings indicate preclinical AD is not phenotypically silent at the group level and support multidomain-based screening for biomarker testing and early-detection.

neuroscience↗

bioRxiv2026

AFIDs-Validator: An Open-Access AI-Guided Platform for Learning Anatomical Landmark Placement

Accurate localization of anatomical landmarks is a foundational skill in anatomy and imaging that is often taught informally through expert mentorship, requiring access to data and desktop software. There is no openly accessible, interactive resource that teaches neuroanatomy with quantitative feedback. We present the AFIDs-Validator (validator.afids.io), an open-access, browser-based platform that pairs guided instruction with quantitative assessment. The platform combines (1) a learning mode in which a language-model neuroanatomy tutor operates inside an MRI viewer, giving anatomy-first instruction that responds to the learner's current image slice, orientation, and cursor position; and (2) a validation engine that accepts a learner's landmark file and returns per-landmark Euclidean error against expert-annotated references spanning 21 brain templates. To make the feedback interpretable, we analyzed 15,000 landmark annotations across 132 human subjects and found that landmark difficulty varies fourfold (median error ranged from 0.37 mm at the anterior commissure to 1.50 mm at the temporal horns) with heavy-tailed distributions at every landmark. These distributions are compiled into per-landmark reliability priors, so learners are scored against the empirical spread of trained raters rather than an arbitrary threshold, and difficult landmarks are not mistaken for poor performance. The AFIDs-Validator requires no installation, licensed software, or local data, and all code, reference data, and tutor design are openly released.

scientific communication and education↗

bioRxiv2026

An anatomically distinct dopaminergic cell population of the zona incerta as evidence for the human A13 nucleus

The zona incerta (ZI) is a functionally and molecularly diverse deep brain region increasingly recognized as an integrative hub. The rodent ZI contains the dopaminergic A13 nucleus, with studies supporting a central role in modulating sensorimotor integration, nociception, and confers resilience in models of neurodegeneration; however, to date, no clear human homologue has been identified. Here, we identified a tyrosine hydroxylase-positive subregion in the human ZI consistent with the A13, and refined its borders using ex vivo MRI and histology. We translate these findings to in vivo MRI, demonstrating the A13 is distinguishable from surrounding regions by elevated T1 and T2* values. We further revealed a principal rostral-caudal axis of molecular and structural connectivity variation in the ZI, and identified the A13 as a localized molecular specialization. Altogether, we report a distinct ZI subregion corresponding to the A13 nucleus, providing an anatomical foundation for further mechanistic and translational investigation.

neuroscience↗

bioRxiv2025

Hippocampal grey matter changes across scales in Alzheimer's Disease

Alzheimers disease (AD) is a progressive and debilitating neurodegenerative disease of the central nervous system, characterized by deterioration in cognitive function including extensive memory impairment. The hippocampus, a medial temporal lobe region, is a key orchestrator in the encoding and retrieval of memory and is believed to be one of the first regions to deteriorate in AD. In this work we examined hippocampal macrostructure (specifically gyrification and thickness) and microstructure in Alzheimers disease (AD) and mild cognitive impairment (MCI) relative to healthy aged controls in the Alzheimers Disease Neuroimaging Initiative (ADNI) dataset. We first utilized an iterative training paradigm to adapt an existing deep learning approach for capturing hippocampal topology to elderly individuals as well as individuals with potential hippocampal degeneration. Using this new model, we found notable decreases in both thickness and gyrification in AD and MCI across both the subfields and anterior-posterior axis. Using the diffusion tensor representation derived from diffusion MRI data, we found significant increases in the mean diffusivity across the extent of the hippocampus in AD and MCI, which may be related to a number of changes such as loss of neuronal cells, decreased fiber density, demyelination, and increased presence of CSF. Examining the primary direction of diffusion relative to canonical hippocampal axes, we found distinct diffusion orientation shifts in AD and MCI throughout the anterior-posterior extent of the subiculum and CA1. Specifically, we found a decrease in diffusion oriented tangentially, and an increase in diffusion oriented along the long-axis. This could potentially be related to the known degeneration of the perforant path, which is greatly affected in AD and is a largely tangential oriented pathway. The AD-related changes in diffusion orientations were found to not have significant spatial overlap with AD-related changes in mean diffusivity, suggesting that they may be capturing distinct spatially-localized disease processes. Finally, we showed that the macro- and microstructure of the hippocampus in AD changed less across age relative to MCI and controls. As well, the age-related hippocampal macrostructure changes in MCI appeared indistinguishable from healthy aging.

neuroscience↗

bioRxiv2024

Folate prevents the autism-related phenotype caused by developmental pyrethroid exposure in prairie voles

Neurodevelopmental disorders (NDDs) have dramatically increased in prevalence to an alarming one in six children, and yet both causes and preventions remain elusive. Recent human epidemiology and animal studies have implicated developmental exposure to pyrethroid pesticides, one of the most common classes of pesticides in the US, as an environmental risk factor for autism and neurodevelopmental disorders. Our previous research has shown that low-dose chronic developmental pyrethroid exposure (DPE) changes folate metabolites in the adult mouse brain. We hypothesize that DPE acts directly on molecular targets in the folate metabolism pathway, and that high-dose maternal folate supplementation can prevent or reduce the biobehavioral effects of DPE. We exposed pregnant prairie vole dams chronically to vehicle or low-dose deltamethrin (3 mg/kg/3 days) with or without high-dose folate supplementation (methylfolate, 5 mg/kg/3 days). The resulting DPE offspring showed broad deficits in five behavioral domains relevant to neurodevelopmental disorders (including the social domain); increased plasma folate concentrations; and increased neural expression of SHMT1, a folate cycle enzyme. Maternal folate supplementation prevented most of the behavioral phenotypes (except for repetitive behaviors) and caused potentially compensatory changes in neural expression of FOLR1 and MTHFR, two folate-related proteins. We conclude that DPE causes neurodevelopmental disorder-relevant behavioral deficits; DPE directly alters aspects of folate metabolism; and preventative interventions targeting folate metabolism are effective in reducing, but not eliminating, the behavioral effects of DPE.

neuroscience↗

bioRxiv2024

Mapping the topographic organization of the human zona incerta using diffusion MRI

The zona incerta (ZI) is a deep brain region originally described by Auguste Forel as an "immensely confusing area about which nothing can be said." Despite the elusive nature of this structure, mounting evidence supports the role of the ZI and surrounding regions across a diverse range of brain functions and as a candidate target for neuromodulatory therapies. Using in vivo diffusion MRI and data-driven connectivity, we identify a topographic organization between the ZI and neocortex. Specifically, our methods identify a rostral-caudal gradient predominantly connecting the frontopolar and ventral prefrontal cortices with the rostral ZI, and the primary sensorimotor cortices with the caudal ZI. Moreover, we demonstrate how clustering and gradient approaches build complementary evidence including facilitating the mapping of a central region of the ZI, connected with the dorsal prefrontal cortex. These results were shown to be replicable across multiple datasets and at the individual subject level, building evidence for the important role of the ZI in mediating frontal lobe-associated tasks, ranging from motor to cognitive to emotional control. Finally, we consider the impact of this topographic organization on the refinement of neuromodulatory targets. These results pave the way for an increasingly detailed understanding of ZI substructures, and considerations for in vivo targeting of the ZI for neuromodulation.

neuroscience↗

bioRxiv2024

It only takes seconds for a human monoclonal autoantibody to inhibit N-methyl-D-aspartate receptors

Transfer of autoantibodies targeting ionotropic N-methyl-D-aspartate receptors in autoimmune encephalitis patients into mice leads to typical disease signs. Long-term effects of the pathogenic antibodies consist of immunoglobulin G-induced crosslinking and receptor internalization. We focused on the direct and immediate impact of a specific pathogenic patient-derived monoclonal autoantibody (immunoglobulin G #003-102) on receptor function. We performed cell-attached recordings in cells transfected with the GluN1 and GluN2A subunit of the N-methyl-D-aspartate receptor. Immunoglobulin G #003-102 binds to the amino-terminal domain of the glycine-binding GluN1 subunit. It reduced simultaneous receptor openings significantly compared to controls at both low and high glutamate and glycine concentrations. Closer examination of our data in 50-second to 2-second intervals revealed, that Immunoglobulin G #003-102 rapidly decreases the number of open receptors. However, antigen-binding fragments of immunoglobulin G #003-102 did not reduce the receptor openings. In conclusion, patient-derived immunoglobulin G #003-102 inhibits N-methyl-D-aspartate receptors rapidly and directly before receptor internalization occurs and the entire immunoglobulin G is necessary for this acute inhibitory effect. This suggests an application of the antigen-binding fragment-like constructs of #003-102 as a potential new treatment strategy for shielding the pathogenic epitopes on the N-methyl-D-aspartate receptors.

neuroscience↗

bioRxiv2023

Optimal evaluation of energy yield and driving force in microbial metabolic pathway variants

This work presents a methodology to evaluate the bioenergetic feasibility of alternative metabolic pathways for a given microbial conversion, optimising their energy yield and driving forces as a function of the concentration of metabolic intermediates. The tool, based on thermodynamic principles and multi-objective optimisation, accounts for pathway variants in terms of different electron carriers, as well as energy conservation (proton translocating) reactions within the pathway. The method also accommodates other constraints, some of them non-linear, such as the balance of conserved moieties. The approach involves the transformation of the maximum energy yield problem into a multi-objective linear optimisation problem which is then subsequently solved using the epsilon-constraint method, highlighting the trade-off between yield and rate in metabolic reactions. The methodology is applied to analyse several pathway alternatives occurring during propionate oxidation in anaerobic fermentation processes, as well as to the reverse TCA cycle pathway occurring during autotrophic microbial CO2 fixation. The results obtained using the developed methodology match previously reported literature, and bring about insights into the studied pathways.

systems biology↗

bioRxiv2022

Magnetic resonance imaging datasets with anatomical fiducials for quality control and registration

Tools available for reproducible, quantitative assessment of brain correspondence have been limited. We previously validated the anatomical fiducial (AFID) placement protocol for point-based assessment of image registration with millimetric (mm) accuracy. In this data descriptor, we release curated AFID placements for some of the most commonly used structural magnetic resonance imaging templates and datasets. The release of our accurate placements allows for rapid quality control of image registration, teaching neuroanatomy, and clinical applications such as disease diagnosis and surgical targeting. We release placements on individual subjects from four datasets (n = 132 subjects for a total of 15,232 fiducials) and more than 10 brain templates (4,288 fiducials), compiling over 300 human rater hours of annotation. We also validate human rater accuracy of released placements to be within 1-2 mm (using a total of 50,336 Euclidean distances), consistent with prior studies. Our data is compliant with the Brain Imaging Data Structure (BIDS) allowing for facile incorporation into modern neuroimaging analysis pipelines. Data is accessible on GitHub (https://github.com/afids/afids-data).

neuroscience↗

bioRxiv2022

Amyloid-beta biomarkers in Braak stages and their predictive relationships with cognitive impairment: Support vector machine and deep learning approaches

Amyloid-beta (A{beta}) and tau tangles are hallmarks of Alzheimers disease. A{beta} distributions in the tau-defined Braak staging regions and their multivariate predictive relationships with mild cognitive impairment (MCI) are not known. In this study, we used PiB PET data from 60 participants (33 with MCI and 27 healthy controls (HC)), quantified A{beta} as distribution volume ratio (DVR) in Braak regions, and compared between MCI and controls to test the hypothesis that DVR alters with declining cognition. We found elevated DVR in participants with MCI, especially in the spatial distribution of Braak stages III-IV and V-VII, while an alteration in Braak stage I-II was near the statistical significance. DVR markers correlated with cognitive status, especially in Braak stages III-IV and VI-V. To evaluate whether these markers are predictive of cognitive dysfunction, we designed support vector machine and artificial neural network models. These methods showed predictive multivariate relationships between A{beta} makers of Braak regions and cognitive impairment. Overall, these results highlight the importance of computer-aided research efforts for understanding AD pathophysiology.

neuroscience↗

bioRxiv2020

Application of the Anatomical Fiducials Framework to a Clinical Dataset of Patients with Parkinsons Disease

Establishing spatial correspondence between subject and template images is necessary in neuroimaging research and clinical applications such as brain mapping and stereotactic neurosurgery. Our anatomical fiducials (AFIDs) framework has recently been validated to serve as a quantitative measure of image registration based on salient anatomical features. In this study, we sought to apply the AFIDs protocol to the clinic, focusing on structural magnetic resonance images obtained from patients with Parkinsons Disease (PD). We confirmed AFIDs could be placed to millimetric accuracy in the PD dataset with results comparable to those in normal control subjects. We evaluated subject-to-template registration using this framework by aligning the clinical scans to standard template space using a robust open preprocessing workflow. We found that registration errors measured using AFIDs were higher than previously reported, suggesting the need for optimization of image processing pipelines for clinical grade datasets. Finally, we examined the utility of using point-to-point distances between AFIDs as a morphometric biomarker of PD, finding evidence of reduced distances between AFIDs that circumscribe regions known to be affected in PD including the substantia nigra. Overall, we provide evidence that AFIDs can be successfully applied in a clinical setting and utilized to provide localized and quantitative measures of registration error. AFIDs provide clinicians and researchers with a common, open framework for quality control and validation of spatial correspondence and the location of anatomical structures, facilitating aggregation of imaging datasets and comparisons between various neurological conditions.

neuroscience↗