Biology subjects

Cohen, J. A.

Publications and source records attributed to Cohen, J. A..

4 recordsLinked to original sources

bioRxiv2026

No Strings Attached: Predicting Tricuspid Valve Deformation Without In Vivo Chordal Geometry

Predictive biomechanical models of the tricuspid valve require accurate representation of the chordae tendineae, yet subject-specific chordal geometry is difficult to reconstruct from non-invasive imaging. Here, we adopt a framework for generating functionally equivalent synthetic chordae without prior knowledge of in vivo chordal attachments. To this end, we first adapt an anatomy-informed hyperelastic shape-matching method that establishes correspondence between end-diastolic and end-systolic leaflet configurations using chordal-mimicking forces, a rigid contact template, and a Gaussian-smoothed locally corrective pressure field. We then generate synthetic chordal insertion sites using zone-based rejection sampling and calibrate the unloaded length of each chord by combining reaction forces with the chordal stress-stretch relationship. The framework was evaluated using Texas TriValve 1.1, a high-fidelity finite element model of a human tricuspid valve validated against beating-heart echocardiography. We found that shape matching reproduced the target end-systolic geometry with a mean inter-surface distance of 0.29 {+/-} 0.35 mm. Moreover, synthetic chordal insertions faithfully reproduce end-systolic leaflet deformations. We subsequently examined synthetic chordal configurations containing 202, 225, and 450 insertions, informed by measurements from eight explanted human tricuspid valves. Here, increasing insertion number reduced mean inter-surface distance from 0.63 {+/-} 0.52 mm to 0.49 {+/-} 0.44 mm and reduced contact area errors from 3.52% to 0.59%. Across all configurations, mean maximum principal stretch errors in leaflet belly regions remained below 2.4%, while areal strain errors ranged from 0.34% to 10.01%. These results demonstrate that anatomically informed shape matching coupled with stress-based chordal calibration can reproduce tricuspid valve closure without explicit subject-specific chordal geometry. This framework provides a foundation for generating synthetic subvalvular anatomy for future imaging-derived, predictive tricuspid valve models.

bioengineering↗

bioRxiv2026

Multi-model Segmentation and Morphometric Quantification of Cerebral Amyloid Angiopathy in Alzheimer's Disease Whole Slide Histopathology Images

IntroductionCerebral amyloid angiopathy (CAA) is characterized by amyloid-beta deposition in cortical and leptomeningeal vessels and associated with cognitive impairment and hemorrhage. Current neuropathological assessments rely on semiquantitative grading and lack vessel-level resolution and scalability. Existing computational pathology approaches also fail to capture individual vessel morphology and spatial amyloid distribution across whole-slide images (WSIs). To address this gap, we developed a deep learning framework for reproducible, quantitative analysis of CAA in WSIs. MethodsWe analyzed 20 postmortem brain tissue sections from the frontal (n = 10) and occipital cortices (n = 10) of 10 individuals with Alzheimers disease pathology obtained from the University of Pittsburgh Alzheimers Disease Research Center, which served as the internal development cohort. An independent external cohort consisted of 10 sections (5 frontal and 5 occipital samples) from 5 individuals obtained from the University of Kentucky Alzheimers Disease Research Center. We trained and compared three semantic segmentation architectures, a standard U-Net, a dual-attention residual U-Net (DA-ResUNet), and a Swin Transformer-based U-Net (Swin-UNet), using the internal development cohort with slide-level five-fold cross-validation. All models were evaluated on the independent external cohort to assess generalization under domain shift. Based on segmentation performance and computational efficiency, we selected one architecture to generate whole-slide composite segmentation masks for vessel walls, amyloid deposits, and tissue compartments. These masks were subsequently used for deterministic vessel detection, morphometric measurements, and quantification of vascular and perivascular amyloid features through post-processing analysis. ResultsAll three architectures achieved high segmentation accuracy on the internal cohort, with Dice scores above 90% across vessel walls, amyloid deposits, gray matter, and leptomeninges. The Swin-UNet showed marginally higher performance for vessel segmentation, whereas the DA-ResUNet provided more balanced accuracy and computational efficiency and was selected for downstream analysis. External cohort evaluation demonstrated robust generalization, with attention-enhanced models outperforming the standard U-Net under domain shift. Using the selected model, the pipeline reliably detected valid vessels, excluded non-vascular artifacts, and enabled deterministic extraction of vessel morphometry, vascular and perivascular amyloid burden, and identification of circumferential CAA involvement at the vessel level. DiscussionThis framework provides a scalable, interpretable solution for vessel-level CAA analysis, supporting robust geometric and spatial characterization of cerebrovascular pathology and enabling future integration with clinical and genetic studies. Beyond CAA, the modular design allows extension to other vascular pathologies, including arteriolosclerosis, in WSIs, facilitating broader investigation of cerebrovascular disease mechanisms.

pathology↗

bioRxiv2025

The T-cell receptor repertoire of wild mice

Wild animals live in a pathogen-rich environment, and are normally infected with a wide range of micro- and macro-parasites. Wild animals T cells are central to the effectiveness of their adaptive immune response in ameliorating the effect of these infections. Here we have investigated the T-cell receptor (TCR) repertoire of wild mice to investigate how it varies in animals of different ages and sex, and from different sites. We sequenced the TCR alpha and beta chains of CD4+ and CD8+ T-cells of 65 wild Mus musculus domesticus from two UK sites. We analysed repertoire richness and diversity finding that wild mice have large TCR repertoires. Repertoire richness, which measures the breadth of the repertoire, was not significantly affected by mouse age or sex, suggesting that wild mice maintain the capacity to respond to novel antigens throughout their lives. In contrast, repertoire diversity (measured by Shannons index) was affected by a mouse sex-by-age interaction. This low diversity, coupled with constant richness, points to older mice having comparatively more highly abundant clones in their repertoires, perhaps due to chronic exposure to persistent pathogens in their environment. These findings provide a novel description of the wild mouse TCR, revealing an immune system that balances maintaining a broad response capacity with developing strong, lasting responses to infections in the natural environment.

immunology↗

bioRxiv2024

Effects of host heterogeneity on epidemiological dynamics are mediated by how host infectiousness is determined

Host heterogeneities in susceptibility and infectiousness can affect parasite transmission, but standard analyses typically consider a limited range of epidemiological scenarios. We propose two contrasting phenomenological scenarios that capture a wide range of processes by which host infectiousness is determined, and explore how these scenarios affect the impact of host heterogeneities on parasite transmission. Specifically, we contrast Recipient dependence (RD), where a hosts infectiousness is a fixed characteristic of the recipient host being infected, with Donor dependence (DD), where a hosts infectiousness is determined by the donor host that infected them. Contrasting Susceptible-Infected models of these two phenomenological scenarios show that under RD, R0 is driven by population-level covariance between susceptibility and infectiousness, but for DD scenarios it is driven by the maximum infectiousness present in the population. Our results show that these different scenarios, which capture different ways by which host infectiousness is determined, should be considered explicitly when exploring the consequences of host heterogeneity on transmission.

ecology↗