Biology subjects

Lai, H.-Y.

Publications and source records attributed to Lai, H.-Y..

10 recordsLinked to original sources

bioRxiv2026

Functional Ultrasound Characterization of Spatiotemporal Cerebral Hemodynamic Responses Evoked by Whisker Stimulation

Functional ultrasound imaging (fUS) measures task-associated changes in cerebral blood volume (CBV) with fine spatial sampling and rapid acquisition, supporting functional mapping and brain-signal decoding. As an indirect measure of neural activity, fUS-CBV signals are shaped by neurovascular coupling and vascular dynamics, which influence the spatial and temporal stimulus information available for decoding. Consequently, the functional distinctions accessible in fUS-CBV signals require characterization under controlled experimental conditions. Here, controlled whisker stimulation in awake, head-fixed mice was used to characterize these decoding-relevant response properties. Whisker identity and number, stimulation duration, and inter-stimulus interval were systematically varied. All-whisker stimulation produced contralaterally dominant responses in the primary somatosensory barrel field and ventral posteromedial thalamic nucleus. Different whisker inputs were associated with distinguishable cortical response distributions, while stimulation involving more whiskers produced broader representative activation patterns. Across durations of 0.5 s to10 s, brief stimulation generated measurable stimulus-associated signals, and response magnitude, persistence, and spatial distribution varied with stimulus duration. For paired 2-s stimuli, trial-level separability was already high at the shortest tested 1-s gap, corresponding to a 3-s onset-to-onset spacing, and reached 100% at gaps of 3 s or longer. Building on the experimentally characterized spatiotemporal response properties of fUS-CBV signals, a proof-of-concept modeling and decoding framework was developed, comprising cross-animal spatial prediction, classification of short versus long stimulation from S1BF {Delta}CBV time courses with known stimulus onset, and modeling of paired-event separability. Together, the results show that fUS-CBV signals retain structured spatial and temporal information about controlled sensory input after neurovascular transformation. These measured response properties characterize the spatiotemporal boundaries within which neural activity can be reliably distinguished using fUS-CBV signals, providing constraints for the development of fUS-based decoding models and the design of stimulation paradigms suitable for reliable fUS decoding.

neuroscience↗

bioRxiv2026

The SEA-AD DREAM Challenge: Community benchmarking human and AI agent solutions for Alzheimer's disease neuropathology prediction from single-nucleus transcriptomics

Single-nucleus transcriptomic atlases offer an unprecedented opportunity to connect cellular molecular states with Alzheimer's disease (AD) neuropathology, but whether these profiles encode reproducible, predictive information about pathological burden remains unclear. We present the SEA-AD DREAM Challenge, an open, international, model-to-data competition built on the Seattle Alzheimer's Disease Brain Cell Atlas to predict Alzheimer's disease neuropathological severity from single-nucleus RNA-sequencing data. Participants developed containerized models to predict categorical neuropathological staging, including overall Alzheimer's disease neuropathologic change, Braak stage, Thal phase, and CERAD score, as well as quantitative amyloid-{beta} and phospho-tau burden measured by 6E10 and AT8 immunohistochemistry. Across 17 eligible teams from 15 countries, the crowdsourcing framework enabled systematic comparison of diverse computational approaches and surfaced a broad landscape of modeling strategies and candidate predictive features. Top-performing methods achieved near-perfect prediction of categorical staging, with the best submission reaching a quadratic weighted kappa of 1.0 for the Overall AD Neuropathological Change score (ADNC), and competitive prediction of quantitative pathological burden in held-out data, with a best concordance correlation coefficient of 0.48. Post hoc perturbation analyses revealed that top categorical-stage predictions relied heavily on donor-level metadata-driven signals rather than transcriptomic features, whereas quantitative pathology prediction was more robust and supported by transcriptomic and cell-type-associated features with potential biological relevance to AD progression. The challenge also introduced the first AI Agent Track in a DREAM Challenge, providing an early benchmark for autonomous and human-guided agentic model development in single-cell neuroscience. This work demonstrates that single-nucleus transcriptomes encode substantial information about Alzheimer's disease pathology, establishes a reproducible benchmark for molecular neuropathology prediction, and highlights critical principles for designing privacy-preserving, leakage-aware community challenges using deeply phenotyped human brain data.

neuroscience↗

bioRxiv2026

Multiregional single-cell profiling reveals shared and specialized cellular vulnerability in Alzheimer's disease

Alzheimers disease (AD) is defined and staged by the stereotyped, progressive accumulation of amyloid-beta (A{beta}) plaques and hyperphosphorylated tau (pTau) tangles across brain regions. These regions differ substantially in their architecture and function but share largely conserved cellular composition, with some regional specialization. As pathology accumulates, specific neurons are lost and non-neuronal cells shift toward disease-associated states, but whether the cell types affected in any one region are the same across the others has remained unclear. Here we extended the Seattle Alzheimers Disease Brain Cell Atlas (SEA-AD) to ten neo- and allocortical regions spanning the cortical arc of canonical AD staging, profiling approximately seven million nuclei from 84 donors with single-nucleus RNA-seq, ATAC-seq, and Multiome alongside quantitative neuropathology and whole-genome sequencing. Nuclei were mapped to an expanded BRAIN Initiative reference taxonomy of 207 cell types, and a hierarchical pseudo-progression framework derived continuous, donor-level measures of AD pathological burden within each region and across the brain by jointly modeling A{beta} and pTau. Cellular changes were both highly selective and strikingly consistent: only [~]30% of cell types shifted in relative abundance, but those that did changed in a coherent direction across regions. Specific subsets of Sst, Lamp5, Vip, Sncg, and Pvalb inhibitory interneurons and myelinating oligodendrocytes were lost earliest in preclinical donors with minimal pathology, alongside initial emergence of AD-associated microglia; loss of L2/3 and selected deep-layer excitatory types, sharper microglial increases, and reactive astrocyte emergence followed in later-stage donors. Regionally specialized populations were also vulnerable, including expected allocortical types and, unexpectedly, primary visual cortex (V1C)-specialized layer 4 (L4 IT) excitatory neurons and intermixed Sst and Pvalb interneurons. Key changes replicated across three independent cohorts encompassing over 700 additional donors. We examined two complementary vulnerable populations in mechanistic detail: regionally specialized V1C L4 IT neurons lost late despite being widely considered resilient, and pan-cortical Sst interneurons lost earliest in disease. Applying a multi-agentic AI workflow that constructed literature-grounded hypotheses from differential expression to L4 IT neurons nominated hyperexcitability, mediated in part by high NMDA receptor expression, as a convergent vulnerability phenotype. Vulnerable Sst interneurons converged on hyperexcitability through partly distinct pathways, and were enriched for expression of AD GWAS-prioritized genes, linking their vulnerability to the genetic architecture of AD. These data, available at SEA-AD.org, provide a multiregional framework for the community to explore the molecular and cellular changes of AD progression.

neuroscience↗

bioRxiv2026

Aberrant cortical subcortical somatosensory network organization is associated with impaired tactile-motion perception in akinetic-rigid Parkinson's disease

BackgroundParkinsons disease (PD) is associated with somatosensory dysfunction, yet higher-order tactile-motion processing and its neural basis remain poorly understood. Here, we combined psychophysical assessment of tactile-motion perception with resting-state functional MRI (rs-fMRI) to investigate how altered sensorimotor network organization relates to tactile perceptual deficits in akinetic-rigid dominant PD (PDAR). MethodsForty-six participants (25 PDAR and 21 healthy controls, HCs) underwent clinical evaluation and resting-state functional MRI scanning. A subset of participants (15 PDAR and 15 HCs) additionally completed a tactile-motion perception task assessing directional bias and speed sensitivity. ROI-to-ROI functional connectivity analyses were performed within a customized 26-node sensorimotor and cortico-basal ganglia-thalamo-cortical (CBGTC) network. ResultsCompared with HCs, PDAR patients exhibited significantly altered tactile-motion perception, including greater directional bias (p = 0.047) and reduced sensitivity to dynamic tactile speed (p < 0.001), reflecting diminished sensitivity to mid-to-high speeds. Resting-state functional connectivity analyses revealed widespread reductions in connectivity within cortical somatosensory regions (Areas 1, 2, 3a, 3b, 5), particularly between primary somatosensory and motor cortices. In contrast, increased connectivity was observed between basal ganglia-thalamic structures and cortical sensorimotor regions, including thalamus-M1 and GPi-sensorimotor connections (all p-FDR < 0.05). ConclusionsThese findings demonstrate a dual pattern of sensorimotor network reorganization in PDAR, characterized by disrupted cortical somatosensory integration alongside enhanced subcortical-cortical coupling. The present study provides evidence that higher-order tactile-motion dysfunction in PD is associated with large-scale abnormalities in distributed sensorimotor networks and highlights the somatosensory system as a potential target for future therapeutic intervention.

neuroscience↗

bioRxiv2026

scVIP: personalized modeling of single-cell transcriptomes for developmental and disease phenotypes

Single-cell transcriptomics resolves cellular heterogeneity within individuals, but connecting molecular states to individual-level phenotypes requires frameworks that explicitly bridge these scales. We present scVIP, a generative model that links gene expression, cell-type composition, and phenotypic measurements within a single probabilistic model, which enables accurate phenotype prediction and interpretable trajectory inference. A cell-type-aware multi-instance learning architecture learns donor embeddings that capture progression while localizing phenotype-associated signals to specific cell populations. Applied across four settings, scVIP accurately predicts cortical developmental age (Pearson r = 0.95), characterizes Huntingtons disease progression (concordance correlation coefficient = 0.90), integrates two Alzheimers disease cohorts recovering disease-relevant microglial and astrocytic programs, and distinguishes healthy from ACPA-positive individuals and non-progressors from early RA individuals, identifying inflammatory T cell programs associated with disease. scVIP enables principled analysis of how cellular states collectively shape organism-level phenotypes across development and disease.

bioinformatics↗

bioRxiv2026

The Caudate Nucleus Exhibits Distinct Pathology and Cell Type-Specific Responses Across Alzheimer's Disease

A{beta} presence in the caudate nucleus (Ca) partially defines Thal stage III in Alzheimers disease (AD), but little is known about ADs cellular impact on the region. Leveraging a public basal ganglia taxonomy of cellular populations, we generated a cellular resolution atlas of AD-associated pathological changes in Ca. Unlike cortex, we found that Ca AD pathology is dominated by two key features: phosphorylated tau (pTau)-containing neuropil threads enriched near oligodendrocytes in white matter tracts and amyloid-{beta} diffuse plaques enriched in gray matter. Although AD pathology in affected cortical regions results in neuronal loss, we find no AD-driven reductions in neuron proportions in Ca. However, there were observable changes in multiple cellular populations. Protoplasmic astrocytes and FLT1+/IL1B+ microglia increased in abundance with global pTau levels. We also observe gene expression changes in fast-spiking PTHLH-PVALB interneurons indicative of disrupted signaling pathways and altered intrinsic physiological properties. This work provides a cellular-resolution framework for understanding AD pathology in Ca.

neuroscience↗

bioRxiv2023

Comprehensive Assessment of Ischemic Stroke in Nonhuman Primates: Neuroimaging, Behavioral, and Serum Proteomic Analysis

Ischemic strokes, prevalence and impactful, underscore the necessity of advanced research models closely resembling human physiology. O integrating n ur study in nonhuman primates (NHPs) offers a comprehensive exploration of ischemic stroke, integrating neuroimaging data, behavioral outcomes, and serum proteomics to elucidate the complex interplay of factors involved in stroke pathophysiology. We observed a consistent pattern in infarct volume, peaking at 1-month post-middle cerebral artery occlusion (MCAO) and stabilizing thereafter. This trend was closely correlated with notable changes in motor function and working memory performance. Using diffusion tensor imaging (DTI), we detected significant alterations in fractional anisotropy (FA) and mean diffusivity (MD) values, indicative of microstructural changes in the brain. These findings were strongly correlated with the observed neurological and cognitive deficits, highlighting the sensitivity of DTI metrics in stroke assessment. Behaviorally, the monkeys exhibited a reliance on their unaffected limb for compensatory movements, a response commonly observed in stroke impairment. This adaptation, alongside the consistent findings in DTI metrics, suggests a substantial impact of stroke on motor function and spatial perception. Proteomic analysis through MS/MS functional enrichment revealed two distinct groups of proteins with significant changes post-MCAO. Notably, MMP9, THBS1, MB, PFN1, and YWHAZ emerged as potential biomarkers and therapeutic targets in ischemic stroke. Our findings underscore the complex nature of stroke and the potential of an integrated approach, combining neuroimaging, behavioral studies, and proteomics, for advancing our understanding and treatment of this condition.

neuroscience↗

bioRxiv2023

Unveiling interactions of spatial-temporal information in tactile motion perception

The intricate interplay of spatial and temporal information in tactile-motion perception remains elusive. Despite strides in decoding neural signals for direction, speed and texture in tactile perception, nuanced interactions persist as challenges. Addressing this, we investigated direction and speed tactile perception, exploring the intricate spatial-temporal dynamics. Psychophysical experiments manipulated direction and speed parameters using a laboratory-designed fingerpad ball-stimulator. A pivotal discovery includes quadrant-dependent anisotropic distortion in perceived motion direction, expanding the well-known notion of a specific preferred orientation. Spatial features primarily influence inherent responses, while temporal features impact stimulus-specific responses, shedding light on dynamic directional perception. The introduction of a psychometric function improved the modeling of tactile-motion speed perception, incorporating both linear and nonlinear components for a more accurate representation. This study provides intriguing insights into the neural mechanisms in tactile-motion perception, with potential applications for somatosensation in brain-machine interfaces. TeaserThis study unveils the intricate interplay of perceiving tactile motion, shedding light on the mysteries of tactile sensations.

neuroscience↗

bioRxiv2023

Interactions with a phage gene underlie costs of a β-lactamase

The fitness cost of an antibiotic resistance gene (ARG) can differ across host strains creating refuges that allow maintenance of an ARG in the absence of direct selection for its resistance phenotype. Despite the importance of such ARG-host interactions for predicting ARG dynamics, the basis of ARG fitness costs and their variability between hosts are not well understood. We determined the genetic basis of a host-dependent cost of a {beta}-lactamase, blaTEM-116*, that conferred a significant cost in one Escherichia coli strain but was close to neutral in 11 other Escherichia spp. strains. Selection of a blaTEM-116* encoding plasmid in the strain in which it initially had a high cost resulted in rapid and parallel compensation to that cost through mutations in a P1 phage gene, relAP1. When the wildtype relAP1 gene was added to a strain in which it was not present and in which blaTEM-116* was neutral, it caused the ARG to become costly. Thus, relAP1 is both necessary and sufficient to explain blaTEM-116* costs in at least some host backgrounds. To our knowledge, these findings represent the first demonstrated case of the cost of an ARG being influenced by a genetic interaction with a phage gene. The interaction between a phage gene and a plasmid-borne ARG highlights the complexity of selective forces determining the maintenance and spread of ARGs, and, by extension, encoding phage and plasmids, in natural bacterial communities.

evolutionary biology↗

bioRxiv2023

Costs of antibiotic resistance genes depend on host strain and environment and can influence community composition

Antibiotic resistance genes (ARGs) is a major contributor to increasing levels of antibiotic resistance in clinical and agricultural settings. ARGs are strongly selected in environments containing corresponding antibiotics, but it is less clear how ARGs are maintained in environments where antibiotic selection might be weak or sporadic. In particular, few studies have directly estimated the effect of ARGs on host fitness in the absence of direct selection. To the extent that ARGs impose costs, it is not clear if these are fixed or might depend on the host strain, perhaps marking some ARG-host combinations as low-cost reservoirs that can act to maintain ARGs in the absence of antibiotic selection. We quantified the fitness effects of six ARGs in each of 11 diverse Escherichia spp. strains in two environments. While three ARGs (blaTEM-116, cat, and dfrA5, encoding resistance to {beta}-lactam antibiotics, chloramphenicol, and trimethoprim, respectively) imposed an overall cost, all ARGs had an effect in at least one host strain, reflecting a significant ARG effect-by-strain interaction effect. A simulation model predicts that these interactions cause the ecological success of ARGs to depend on available host strains, and, to a lesser extent, for successful host strains to depend on the ARGs present in a community. Together, these results indicate the importance of considering ARG effects over different host strains, especially the potential of reservoir strains that allow resistance to persist in the absence of direct selection, in efforts to understand resistance dynamics. ImportanceAntibiotic resistance is a major and increasing public health concern. Resistance occurs through a variety of mechanisms but commonly involves bacterial strains acquiring antibiotic resistance genes (ARGs) encoded by mobile elements. It is obvious and well-documented that ARGs will be selected in bacteria that are exposed to the antibiotics they confer resistance to. ARGs can also confer costs to bacteria--in environments that do not contain antibiotics, these costs can lead to the loss of ARGs. We show that ARG costs can be significant and that they depend on the host bacterial strain and the environment in which strains are grown. This dependence creates host-environment refuges for many ARGs, allowing them to be maintained in the absence of direct selection.

microbiology↗