Biology subjects

Huang, L.-Y.

Publications and source records attributed to Huang, L.-Y..

5 recordsLinked to original sources

bioRxiv2026

A large, comprehensive labeled MRI dataset of the human lateral ventricle choroid plexus

The choroid plexus (ChP) is a highly vascularized structure located in the brain ventricles that plays important roles in multiple central nervous system functions. ChP enlargement has been implicated in many neuropsychiatric conditions such as multiple sclerosis, depression, schizophrenia, and Alzheimer's disease. However, limitation in the accuracy of the current segmentation tools highlight the need for more reliable methods to quantify ChP volume in healthy and clinical human populations. The shape and size of the ChP vary drastically from person to person, and currently there are no large ChP datasets which allow comprehensive training of segmentation models. Here we introduce DataPlex, a collection of 700 structural MRI brain images where the lateral ventricle ChP has been manually labeled and checked by expert human raters. DataPlex is balanced and representative across a wide range of scanning parameters, demographics, and clinical profiles, and subject-level information will be available for each labeled image. DataPlex will be open source to support the creation of reliable segmentation tools for the human lateral ventricle ChP.

neuroscience↗

bioRxiv2025

Linage priming and cell type proportioning depends on the interplay between stochastic and deterministic factors

Isogenic cells can break symmetry and adopt different fates, even when exposed to a seemingly identical environment. This deeply conserved phenomenon allows unicellular organisms to pre-empt dynamically changing environments and is central to the evolution of multicellularity. It is thought that cells are primed towards different lineages by cell-cell variation, although the underlying mechanisms are poorly understood. To address this, we exploit the tractability of the social amoeba Dictyostelium discoideum, where cell fate choice also does not depend on spatial cues. We develop and test a model to explain quantitative experimental single cell observations of probabilistic differentiation. The model suggests that cell cycle position affects lineage choice, as previously shown, but that stochastic cell-cell variation also plays a key role. Single cell sequencing reveals genes that exhibit cell type specific expression or genes that affect fate choice exhibit extensive stochastic cell-cell expression variation. Like lineage priming genes in ESCs, they are associated with specific epigenetic modifications, which when perturbed affect their expression and disrupt fate choice. We suggest the integration of stochastic and deterministic inputs represents an adaptive mechanism to increase developmental robustness against perturbations that affect deterministic signals.

developmental biology↗

bioRxiv2020

Identification of bis-benzylisoquinoline alkaloids as SARS-CoV-2 entry inhibitors from a library of natural products in vitro

Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a major public health issue. To screen for antiviral drugs for COVID-19 treatment, we constructed a SARS-CoV-2 spike (S) pseudovirus system using an HIV-1-based lentiviral vector with a luciferase reporter gene to screen 188 small potential antiviral compounds. Using this system, we identified nine compounds, specifically, bis-benzylisoquinoline alkaloids, that potently inhibited SARS-CoV-2 pseudovirus entry, with EC50 values of 0.1-10 M. Mechanistic studies showed that these compounds, reported as calcium channel blockers (CCBs), inhibited Ca2+-mediated membrane fusion and consequently suppressed coronavirus entry. These candidate drugs showed broad-spectrum efficacy against the entry of several coronavirus pseudotypes (SARS-CoV, MERS-CoV, SARS-CoV-2 [S-D614, S-G614, N501Y.V1 and N501Y.V2]) in different cell lines (293T, Calu-3, and A549). Antiviral tests using native SARS-CoV-2 in Vero E6 cells confirmed that four of the drugs (SC9/cepharanthine, SC161/hernandezine, SC171, and SC185/neferine) reduced cytopathic effect and supernatant viral RNA load. Among them, cepharanthine showed the strongest anti-SARS-CoV-2 activity. Collectively, this study offers new lead compounds for coronavirus antiviral drug discovery.

microbiology↗

bioRxiv2020

Methylation-directed Acetylation of Histone H3 Regulates Developmental Sensitivity to Histone Deacetylase Inhibition

BackgroundTreatment of cells with hydroxamate-based lysine deacetylase inhibitors (KDACis) such as Trichostatin A (TSA) can induce biological effects such as differentiation or apoptosis of cancer cells, and a number of related compounds have been approved for clinical use. TSA treatment induces rapid initial acetylation of histone 3 (H3) proteins which are already modified by tri-methylation on lysine 4 (H3K4me3) while acetylation of bulk histones, lacking this mark, is delayed. Sgf29, a subunit of the SAGA acetyltransferase complex, interacts with H3K4me3 via a tandem tudor domain (TTD) and has been proposed to target the acetyltransferase activity to H3K4me3. However the importance of acetylation of this pool of H3 in the biological consequences of KDACi treatment is not known. ResultsWe investigated the role of H3K4me3-directed acetylation in the mechanism of action of TSA on inhibiting development of the eukaryotic social amoeba Dictyostelium discoideum. Loss of H3K4me3 in strains with mutations in the gene encoding Set1 or the histone proteins confers resistance to TSA-induced inhibition of development and delays accumulation of histone acetylation on H3K9 and K14. A candidate orthologue of Sgf29 in Dictyostelium has been identified which specifically recognizes the H3K4me3 modification via its tandem Tudor domain (TTD). Disruption of the gene encoding Sgf29 delayed accumulation of H3K9Ac, abolished targeted H3K4me3-directed H3Ac and led to developmental resistance to TSA, which is dependent on a functional TTD. TSA resistance also results from overexpression of Sgf29. ConclusionPreferential acetylation of H3K4me3 histones, regulated by Sgf29 via its TTD, is important in developmental sensitivity to TSA. Levels of H3K4me3 or Sgf29 will provide useful biomarkers for sensitivity to this class of chemotherapeutic drug.

pharmacology and toxicology↗

bioRxiv2020

Accurate Diagnosis of Colorectal Cancer Based on Histopathology Images Using Artificial Intelligence

BackgroundAccurate and robust pathological image analysis for colorectal cancer (CRC) diagnosis is time-consuming and knowledge-intensive, but is essential for CRC patients treatment. The current heavy workload of pathologists in clinics/hospitals may easily lead to unconscious misdiagnosis of CRC based on their daily image analyses. MethodsBased on a state-of-the-art transfer-learned deep convolutional neural network in artificial intelligence (AI), we proposed a novel patch aggregation strategy for clinic CRC prediction/diagnosis using weakly labeled pathological whole slide image (WSI) patches. This approach was trained and validated using an unprecedented and enormously large number of 170,099 patches, >14,680 WSIs, from >9,631 subjects that covered diverse and representative clinical cases from multi-independent-sources across China, U.S., and Germany. ResultsOur innovative AI tool was consistently nearly perfectly agreed with (average Kappa-statistic 0.896) and even often better than most of the experienced expert pathologists when tested in diagnosing CRC WSIs from multi-centers. The average area under the receiver operating characteristics curve (AUC) of AI was greater than that of the pathologists (0.981 vs 0.970) and achieved the best performance among the application of other AI methods to CRC diagnosis. Our AI-generated heatmap highlights the image regions of cancer tissue/cells. ConclusionsThis first-ever generalizable AI system can handle large amounts of WSIs consistently and robustly without potential bias due to fatigue commonly experienced by clinical pathologists. Hence, it will drastically alleviate the heavy clinical burden of daily pathology diagnosis, and improve the treatment for CRC patients. This tool is generalizable to other cancer diagnosis based on image recognition.

pathology↗