Biology subjects

Wang, H.-T.

Publications and source records attributed to Wang, H.-T..

13 recordsLinked to original sources

bioRxiv2025

Resting-state functional MRI derivatives: A dataset derived from the The Comprehensive Assessment of Neurodegeneration and Dementia Study

Resting-state functional connectivity (RSFC) holds promise for the detection and characterisation of dementia. The Comprehensive Assessment of Neurodegeneration and Dementia (COMPASS-ND) Study, by the Canadian Consortium on Neurodegeneration in Aging (CCNA), provides a unique resource to study deeply phenotyped neurodegenerative conditions. We present RSFC derivatives for 784 participants (data release 7 of the cohort) who were either cognitively unimpaired or diagnosed primarily with Alzheimers disease (AD), mixed dementia (AD with a vascular component), mild cognitive impairment (MCI), vascular MCI, frontotemporal dementia, Parkinsons disease with or without MCI or dementia, Lewy body disease or subjective cognitive impairment. Functional MRI scans were preprocessed using fMRIPrep, and time-series and whole-brain connectomes generated using three atlases at multiple resolutions, denoised using seven different techniques. High-motion artifacts were managed using a liberal quality control threshold appropriate for an older clinical population, resulting in data from 680 participants. These derivatives are made available to the research community to accelerate research on RSFC biomarkers of neurodegenerative disease, reducing duplication of effort, saving computational resources, and improving standardisation across studies.

neuroscience↗

bioRxiv2025

Biochemical and structural characterization of glycosyltransferase family 61 proteins reveal a key determinant of sugar donor specificity

Xylan, the most abundant non-cellulosic polymer in plant cell walls, is structurally diverse, especially in grasses where it is heavily substituted with arabinofuranose and further modified by various residues. Common substitutions across species include glucuronic and 4-O-methyl-glucuronic acid. Arabinose and xylose sidechains are synthesized by glycosyltransferase family 61 (GT61) proteins, many of which remain uncharacterized in plants, with limited structural and mechanistic understanding. In this study, we identified two novel GT61 enzymes in Sorghum bicolor, functioning as xylan arabinosyltransferase (SbXAT) and xylan xylosyltransferase (SbXXT). We resolved the crystal structure of SbXAT, which exhibits a GT-B fold with two Rossmann-like domains linked by a cleft that accommodates the catalytic site. Structural comparison with a predicted SbXXT model revealed a substrate-binding residue critical for sugar donor specificity, validated through site-directed mutagenesis and enzymatic assays. These findings enhance understanding of xylan biosynthesis and provide a foundation for engineering glycosyltransferases and predicting their functions.

biochemistry↗

bioRxiv2025

Integrated metagenome-resolved profiling of the resistome, virulome, and mobilome in the gut microbiota of wild birds

Wild birds, with their extensive geographic distributions and high mobility, are increasingly recognized as important players in the dissemination of antimicrobial resistance. Their gut microbiota, shaped by exposure to diverse environments, may act as both reservoirs and vectors of antibiotic resistance genes (ARGs), virulence factor genes (VFGs), and mobile genetic elements (MGEs). In this study, we reconstructed 2,516 high-quality metagenome-assembled genomes (MAGs) from 718 gut metagenomes of wild birds to comprehensively profile their resistome and virulome. We identified 5,596 ARG-encoding proteins across 389 distinct ARG types, with multidrug resistance emerging as the most dominant category. Escherichia coli was the principal carrier of ARGs, and genes conferring resistance to elfamycin antibiotics via target alteration were notably widespread--indicating persistent antibiotic selection pressures in avian habitats. Co-occurrence analyses revealed extensive genetic linkage between ARGs, VFGs, and MGEs. Critically, we detected 25 ARG-MGE co-localization events within 5-kilobase genomic regions, highlighting a strong potential for horizontal gene transfer and accelerated resistance dissemination within microbial communities. Of particular concern was the detection of the tetX1 gene--conferring resistance to tigecycline, a last-resort antibiotic--in the gut microbiota of Chroicocephalus ridibundus and Cygnus cygnus. This finding strongly implicates anthropogenic pollution in the spread of clinically relevant ARGs into wildlife and emphasizes the risk of environmental transmission to other hosts, including humans. These results underscore the critical ecological role of wild birds in the global antimicrobial resistance network. As both reservoirs and potential vectors of ARGs, they represent a significant but under-monitored interface between environmental and clinical resistance pathways. Enhanced surveillance and mitigation strategies targeting wildlife are urgently needed to curb the environmental propagation of antimicrobial resistance.

microbiology↗

bioRxiv2024

Peptide Information Compression Technology (PICT): A New Frontier in Therapeutic Peptide Discovery

Therapeutic peptides hold tremendous market potential, yet the discovery methods for active peptides lag considerably behind those for small molecules and biological macromolecule drugs. Due to their respective limitations, traditional peptide compound synthesis and display libraries fail to meet the growing demands of the peptide drug market. Here, we introduce a novel Peptide Information Compression Technology (PICT) and, based on this technology, a large-scale physical peptide library and its accompanying high-throughput screening (HTS) platform. By screening for inhibitors of TSLP/TSLPR/IL7R and antagonists of MC3R at both the molecular and cellular levels, we have identified active molecules in the single-digital micromolar and nanomolar ranges, respectively. This demonstrates the immense application value of Peptide Information Compression Technology in the efficient discovery of peptide drugs.

molecular biology↗

bioRxiv2024

Du-IN-v2: Unleashing the Power of Vector Quantization for Decoding Cognitive States from Intracranial Neural Signals

While invasive brain-computer interfaces have shown promise for high-performance speech decoding under medical use, the potential of intracranial stereoElectroEn-cephaloGraphy (sEEG), which causes less damage to patients, remains underex-plored. With the rapid progress in representation learning, leveraging abundant pure recordings to further enhance speech decoding becomes increasingly attractive. However, some popular methods pre-train temporal models based on brain-level tokens, overlooking the brains desynchronization nature; others pre-train spatial-temporal models based on channel-level tokens, yet fail to evaluate them on more challenging tasks, e.g., speech decoding, which demands intricate processing in specific brain regions. To tackle these issues, we introduce a general pre-training framework for speech decoding - Du-IN-v2, which can extract contextual embeddings based on region-level tokens through discrete codex-guided mask modeling. To further push its limits, we propose Decoupling Product Quantization (DPQ), where different codexes are designed to extract different parts of brain dynamics. Our model achieves SOTA performance on both the 61-word classification task and the 49-syllable sequence classification task, surpassing all baselines. Model comparison and ablation studies reveal that our design choices, including (i) temporal modeling based on region-level tokens by utilizing 1D depthwise convolution to fuse channels in vSMC and STG regions and (ii) self-supervision by discrete decoupling codex-guided mask modeling, significantly contribute to these performances. Collectively, our approach, inspired by neuroscience findings, capitalizing on region-level representations from specific brain regions, is suitable for invasive brain modeling. It marks a promising neuro-inspired AI approach in BCI.

bioengineering↗

bioRxiv2024

Telomere-to-telomere sheep genome assembly reveals new variants associated with wool fineness trait

Ongoing efforts to improve sheep reference genome assemblies still leave many gaps and incomplete regions, resulting in a few common failures and errors in sheep genomic studies. Here, we report a complete, gap-free telomere-to-telomere (T2T) genome of a ram (T2T-sheep1.0) with a size of 2.85 Gb, including all autosomes and chromosomes X and Y. It adds 220.05 Mb of previously unresolved regions (PURs) and 754 new genes to the most updated reference assembly, ARS-UI_Ramb_v3.0, and contains four types of repeat units (SatI, SatII, SatIII, and CenY) in the centromeric regions. T2T-sheep1.0 exhibits a base accuracy of >99.999%, corrects several structural errors in previous reference assemblies, and improves structural variant (SV) detection in repetitive sequences. We identified 192,265 SVs, including 16,885 new SVs in the PURs, from the PacBio long-read sequences of 18 global representative sheep. With the whole-genome short-read sequences of 810 wild and domestic sheep representing 158 global populations and seven wild species, the use of T2T-sheep1.0 as the reference genome has improved population genetic analysis based on [~]133.31 million SNPs and 1,265,266 SVs, including 2,664,979 novel SNPs and 196,471 novel SVs. T2T-sheep1.0 improves selective tests by detecting several novel genes and variants, including those associated with domestication (e.g., ABCC4) and selection for the wool fineness trait (e.g., FOXQ1) in tandemly duplicated regions.

genomics↗

bioRxiv2024

Mapping patterns of thought onto brain activity during movie-watching

Movie-watching is a central aspect of our lives and an important paradigm for understanding the brain mechanisms behind cognition as it occurs in daily life. Contemporary views of ongoing thought argue that the ability to make sense of events in the here and now depend on the neural processing of incoming sensory information by auditory and visual cortex, which are kept in check by systems in association cortex. However, we currently lack an understanding of how patterns of ongoing thoughts map onto the different brain systems when we watch a film, partly because methods of sampling experience disrupt the dynamics of brain activity and the experience of movie-watching. Our study established a novel method for mapping thought patterns onto the brain activity that occurs at different moments of a film, which does not disrupt the time course of brain activity or the movie-watching experience. We found moments when experience sampling highlighted engagement with multi-sensory features of the film or highlighted thoughts with episodic features, regions of sensory cortex were more active and subsequent memory for events in the movie was better--on the other hand, periods of intrusive distraction emerged when activity in regions of association cortex within the frontoparietal system was reduced. These results highlight the critical role sensory systems play in the multi- modal experience of movie-watching and provide evidence for the role of association cortex in reducing distraction when we watch films. Significance statementStates like movie-watching provide a window into the brain mechanisms behind cognition in daily life. However, we know relatively little about the mapping between brain activity during movies and associated thought patterns because of difficulties in measuring cognition without disrupting how brain activity naturally unfolds. We establish a novel method to link different experiential states to brain activity during movie-watching with minimal interruptions to viewers or disruptions to brain dynamics. We found states of sensory engagement occur in moments of films when activity in visual and auditory cortex are high. In contrast, states of distraction are reduced when activity in frontoparietal regions is high. Our study, therefore, establishes both sensory and association cortex as core features of the movie-watching experience.

neuroscience↗

bioRxiv2023

Experience sampling reveals the role that covert goal states play in task-relevant behavior.

Cognitive neuroscience has gained insight into covert states using experience sampling. Traditionally, this approach has focused on off-task states, however, task-relevant states are also maintained via covert processes. Our study examined whether experience sampling can also provide insights into covert goal-relevant states that support task performance. To address this question, we developed a neural state-space, using dimensions of brain function variation, that allows neural correlates of overt and covert states to be examined in a common analytic space. We use this to describe brain activity during task performance, its relation to covert states identified via experience sampling, and links between individual variation in overt and covert states and task performance. Our study established activity patterns within association cortex emphasizing the fronto-parietal network both during target detection and a covert state of deliberate task focus which was associated with better task performance. In contrast, periods of vigilance and a covert off-task state were both linked to activity patterns emphasizing the default mode network. Our study shows experience sampling can not only describe covert states that are unrelated to the task at hand, but can also be used to highlight the role fronto-parietal regions play in the maintenance of covert task-relevant states.

neuroscience↗

bioRxiv2023

A reproducible benchmark of resting-state fMRI denoising strategies using fMRIPrep and Nilearn

Reducing contributions from non-neuronal sources is a crucial step in functional magnetic resonance imaging (fMRI) connectivity analyses. Many viable strategies for denoising fMRI are used in the literature, and practitioners rely on denoising benchmarks for guidance in the selection of an appropriate choice for their study. However, fMRI denoising software is an ever-evolving field, and the benchmarks can quickly become obsolete as the techniques or implementations change. In this work, we present a denoising benchmark featuring a range of denoising strategies, datasets and evaluation metrics for connectivity analyses, based on the popular fMRIprep software. The benchmark is implemented in a fully reproducible framework, where the provided research objects enable readers to reproduce or modify core computations, as well as the figures of the article using the Jupyter Book project and the Neurolibre reproducible preprint server (https://neurolibre.org/). We demonstrate how such a reproducible benchmark can be used for continuous evaluation of research software, by comparing two versions of the fMRIprep software package. The majority of benchmark results were consistent with prior literature. Scrubbing, a technique which excludes time points with excessive motion, combined with global signal regression, is generally effective at noise removal. Scrubbing however disrupts the continuous sampling of brain images and is incompatible with some statistical analyses, e.g. auto-regressive modeling. In this case, a simple strategy using motion parameters, average activity in select brain compartments, and global signal regression should be preferred. Importantly, we found that certain denoising strategies behave inconsistently across datasets and/or versions of fMRIPrep, or had a different behavior than in previously published benchmarks. This work will hopefully provide useful guidelines for the fMRIprep users community, and highlight the importance of continuous evaluation of research methods. Our reproducible benchmark infrastructure will facilitate such continuous evaluation in the future, and may also be applied broadly to different tools or even research fields.

neuroscience↗

bioRxiv2020

Structure of the Xylan O-Acetyltransferase AtXOAT1 Reveals Molecular Insight into Polysaccharide Acetylation in Plants

Acetylation of biomolecules is gaining increased attention due to both the abundance and importance of this modification across all kingdoms of life. Xylans are a major component of plant cell walls and are the third most abundant biopolymer in Nature. O-Acetyl moieties are the dominant backbone substituents of glucuronoxylan in dicots and play a major role in the polymer-polymer interactions that are crucial for proper wall architecture and normal plant development. Here, we describe the biochemical, structural, and mechanistic characterization of Arabidopsis thaliana xylan O-acetyltransferase 1 (AtXOAT1), a member of the plant-specific Trichome Birefrigence Like (TBL) family that catalyzes the 2-O-acetylation of xylan. A multipronged approach involving X-ray crystallography, biochemical analyses, mutagenesis, and molecular simulations show that XOAT1 catalyzes xylan acetylation through formation of an acyl-enzyme intermediate by a double displacement bi-bi mechanism involving a Ser-His-Asp catalytic triad and unconventionally employs an arginine residue in formation of an oxyanion hole.

biochemistry↗

bioRxiv2019

Neurocognitive patterns dissociating semantic processing from executive control are linked to more detailed off-task mental time travel

1Features of ongoing experience are common across individuals and cultures. However, certain people express specific patterns to a greater extent than others. The current psychological theory assumes that individual differences in thought patterns occur because different types of experience depend on differences in associated neurocognitive mechanisms. Consequently, individual variation in the underlying neurocognitive architecture is hypothesised to determine the ease with which certain thought patterns are generated or maintained. Our study (N=178) tested this hypothesis using multivariate pattern analysis to infer shared variance among measures of cognitive function and neural organisation and examined whether these hidden structures explain reports of the patterns of on-going thoughts people experienced in the lab. We found that relatively better performance on tasks requiring primarily semantic knowledge, rather than executive control, was linked to a neural functional organisation that was associated, via meta-analysis, with task labels related to semantic associations (sentence processing, reading and verbal semantics). Variability of this functional mode predicted significant individual variation in the types of thoughts that individuals experienced in the laboratory: Neurocognitive patterns linked to better performance at tasks that required guidance from semantic representation, rather than those dependent on executive control, were associated with patterns of thought characterised by greater subjective detail and a focus on time periods other than the here and now. These relationships were consistent across different days and did not vary with task condition, indicating they are relatively stable features of an individuals cognitive profile. Together these data confirm that individual variation in aspects of ongoing experience can be inferred from hidden neurocognitive architecture and demonstrate that performance trade-offs between executive control and long term semantic knowledge are linked to a persons tendency to imagine situations that transcend the here and now.

neuroscience↗

bioRxiv2019

Hello, is that me you are looking for? A re-examination of the role of the DMN in off-task thought

Neural activity within the default mode network (DMN) is widely assumed to relate to processing during off-task states, however it remains unclear whether this association emerges from a shared role in self or social cognition. In the current study, we examine the possibility that the role of the DMN in ongoing thought emerges from contributions to specific features of off-task experience such as self-relevant or social content. A group of participants described their experiences while performing a laboratory task over a period of days. In a different session, neural activity was measured while participants performed self/other judgements. Despite the prominence of social and personal content in off-task reports, there was no association with neural activity during off-task trait adjective judgements. Instead, during both self and other judgements we found recruitment of caudal posterior cingulate cortex - a core DMN hub - was above baseline for individuals whose laboratory experiences were characterised as detailed. These data provide little support for a role of the DMN in self or other content in the off-task state and instead suggest a role in how on-going thought is represented.

neuroscience↗

bioRxiv2017

Scaffolding imagination: A role for medial frontal cortex in the expression of off-task thought

We often think about people, places and events that are outside of our immediate environment. Although prior studies have explored how we can reduce the occurrence of these experiences, the neurocognitive process through which they are produced are less understood. The current study builds on developmental and evolutionary evidence that language helps organise and express our thoughts. Behaviorally, we found the occurrence of task unrelated thought (TUT) in easy situations was associated with thinking in words. Using experience sampling data, in combination with online measures of neural function, we established that activity in a region of anterior cingulate cortex / medial-prefrontal cortex (mPFC) tracked with changes in the expression of TUT. This region is at the intersection of two mPFC clusters identified through their association with variation in aspects of spontaneous thought: thinking in words (dorsal) and mental time travel (ventral). Finally, using meta-analytic decoding we confirmed the dorsal/ventral distinction within mPFC corresponding to a functional difference between domains linked to language and meaning and those linked to memory and scene construction. This evidence suggests a role for mPFC in the expression of TUT that may emerge from interactions with distributed neural signals reflecting processes such as language and memory.

animal behavior and cognition↗