Biology subjects

Chen, H.-A.

Publications and source records attributed to Chen, H.-A..

8 recordsLinked to original sources

bioRxiv2025

An immunocompetent murine model of virus-elicited liver fibrosis and hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the third deadliest cancer worldwide. Over 75% of HCC cases are associated with chronic viral infections. Mechanistic studies and preclinical therapeutic development for virus-associated HCC have been limited by a paucity of small animal models of chronic hepatotropic virus infection that faithfully recapitulate human disease. Here we demonstrate the induction of chronic hepatitis, progressive liver fibrosis, and HCC in immunocompetent laboratory mice upon chronic viral infection with Norway rat hepacivirus (NrHV) - a virus closely related to hepatitis C virus (HCV). NrHV-elicited tumors resemble HCV-associated tumors and liver transcriptome analyses reveal numerous similarities between chronic NrHV and HCV. These findings establish an experimentally tractable, physiologically relevant, and immunocompetent mouse model of virus-elicited progressive liver fibrosis and oncogenesis.

pathology↗

bioRxiv2025

YOTO (You Only Think Once): A Human EEG Dataset for Multisensory Perception and Mental Imagery

The YOTO (You Only Think Once) dataset presents a human electroencephalography (EEG) resource for exploring multisensory perception and mental imagery. The study enrolled 26 participants who performed tasks involving both unimodal and multimodal stimuli. Researchers collected high-resolution EEG signals at a 1000 Hz sampling rate to capture high-temporal-resolution neural activity related to internal mental representations. The protocol incorporated visual, auditory, and combined cues to investigate the integration of multiple sensory modalities, and participants provided self-reported vividness ratings that indicate subjective perceptual strength. Technical validation involved event-related potentials (ERPs) and power spectral density (PSD) analyses, which demonstrated the reliability of the data and confirmed distinct neural responses across stimuli. This dataset aims to foster studies on neural decoding, perception, and cognitive modeling, and it is publicly accessible for researchers who seek to advance multimodal mental imagery research and related applications.

neuroscience↗

bioRxiv2025

Functional relevance of CASP16 nucleic acid predictions as evaluated by structure providers

Accurate biomolecular structure prediction enables the prediction of mutational effects, the speculation of function based on predicted structural homology, the analysis of ligand binding modes, experimental model building and many other applications. Such algorithms to predict essential functional and structural features remain out of reach for biomolecular. Here, we report quantitative and qualitative evaluation of nucleic acid structures for the CASP16 blind prediction challenge by 12 of the experimental groups who provided nucleic acid targets. Blind predictions accurately model secondary structure and some aspects of tertiary structure, including reasonable global folds for some complex RNAs, however, predictions often lack accuracy in the regions of highest functional importance. All models have inaccuracies in non-canonical regions where, e.g., the nucleic-acid backbone bends or a base forms a non-standard hydrogen bond. These bends and non-canonical interactions are integral to form functionally important regions such as RNA enzymatic active sites. Additionally, the modeling of conserved and functional interfaces between nucleic acids and ligands, proteins, or other nucleic acids remains poor. For some targets, the experimental structures may not represent the only structure the biomolecular complex occupies in solution or in its functional life-cycle, posing a future challenge for the community.

biophysics↗

bioRxiv2024

Innovative platelet-derived extracellular vesicle drug delivery system for the treatment of corneal neovascularization

Platelet-derived extracellular vesicles (PEVs) have drawn attention due to their multifunctionality, ease of procurement, and abundant supply from clinical-grade platelet concentrates. PEVs can be easily endocytosed owing to their lipid bilayer membrane and nanosized structure, thereby increasing the bioavailability and functionality of their therapeutic effects. PEVs also possess multiple trophic factors that make them effective therapeutic agents. Since nanomedicine offers advantages over traditional therapies for eye diseases by overcoming physical ocular barriers, PEVs combined with an anti-angiogenic agent, kaempferol (KM), were evaluated for their ability to inhibit abnormal vessel formation in the cornea. Characterization of the nanoparticles indicated successful preparation of KM- loaded PEVs (PEV-KM) with a mean diameter of [~]160 nm and an encapsulation efficiency of [~]61%. PEV-KM was efficiently internalized into human vascular endothelial cells, resulting in inhibited function, evidenced by lower wound closure rates, reduced tube formation capacity, and downregulation of angiogenesis-related gene expression. Moreover, prolonged ocular retention was observed followed by topical application of PEV and PEV-KM in mouse eyes. In an alkali-burned corneal neovascularization (CoNV) mouse model, PEV (1%) was found to reduce vessel formation in the injured cornea. PEV with KM (1% PEV with KM 6 {micro}g/mL) showed an even stronger effect in suppressing CoNV and reducing the expression of proangiogenic and inflammatory cytokines. Together, our data suggests that topical administration of PEVs or in combination with KM (PEV-KM) is a promising therapeutic for managing CoNV.

bioengineering↗

bioRxiv2023

SiamEEGNet: Siamese Neural Network-Based EEG Decoding for Drowsiness Detection

Recent advancements in deep-learning have significantly enhanced EEG-based drowsiness detection. However, most existing methods overlook the importance of relative changes in EEG signals compared to a baseline, a fundamental aspect in conventional EEG analysis including event-related potential and time-frequency spectrograms. We herein introduce SiamEEGNet, a Siamese neural network architecture designed to capture relative changes between EEG data from the baseline and a time window of interest. Our results demonstrate that SiamEEGNet is capable of robustly learning from high-variability data across multiple sessions/subjects and outperforms existing model architectures in cross-subject scenarios. Furthermore, the models interpretability associates with previous findings of drowsiness-related EEG correlates. The promising performance of SiamEEGNet highlights its potential for practical applications in EEG-based drowsiness detection. We have made the source codes available at http://github.com/CECNL/SiamEEGNet.

neuroscience↗

bioRxiv2022

Epigenetic plasticity cooperates with emergent cell-cell interactions to drive neoplastic tissue remodeling in the pancreas

The response to tumor-initiating inflammatory and genetic insults can vary amongst morphologically indistinguishable cells, suggesting yet uncharacterized roles for epigenetic plasticity during early neoplasia. To investigate the origins and impact of such plasticity, we perform single-cell analyses on normal, inflamed, pre-malignant and malignant tissues in autochthonous models of pancreatic cancer. We reproducibly identify heterogeneous cell-states that are primed for diverse late-emerging neoplastic fates and link these to chromatin remodeling at cell-cell communication loci. Using a new inference approach, we reveal signaling gene modules and tissue-level crosstalk, including a neoplasia-driving feedback loop between discrete epithelial and immune cell populations that we validate by genetic perturbation in mice. Our results uncover a neoplasia-specific tissue remodeling program that may be exploited for pancreas cancer interception. One-Sentence SummarySingle-cell analysis reveals that enhanced epigenetic plasticity drives pro-neoplastic crosstalk in early pancreatic cancer.

cancer biology↗

bioRxiv2022

Somatic mouse models of gastric cancer reveal genotype-specific features of metastatic disease

Metastatic gastric carcinoma is a highly lethal cancer that responds poorly to conventional and molecularly targeted therapies. Despite its clinical relevance, the mechanisms underlying the behavior and therapeutic response of this disease are poorly understood owing, in part, to a paucity of tractable models that faithfully recapitulate different subtypes of the human disease. To close this gap, we developed methods to somatically introduce different oncogenic lesions directly into the stomach epithelium and show that genotypic configurations observed in patients produce metastatic gastric cancers that recapitulate the histological, molecular, and clinical features of all non-viral molecular subtypes of the human disease. Applying this platform to both wild-type and immune-deficient mice revealed previously unappreciated links between the genotype, organotropism and immune surveillance of metastatic cells that produced distinct patterns of metastasis that were mirrored in patients. Our results establish and credential a highly portable platform for producing autochthonous cancer models with flexible genotypes and host backgrounds, which can unravel mechanisms of gastric tumorigenesis or test new therapeutic concepts aimed at improving outcomes in gastric cancer patients.

cancer biology↗

bioRxiv2022

Senescence rewires microenvironment sensing to facilitate anti-tumor immunity

Cellular senescence involves a stable cell cycle arrest coupled to a secretory program that, in some instances, stimulates the immune clearance of senescent cells. Using an immune competent tumor model in which senescence triggers CD8 T cell-mediated tumor rejection, we show that senescence also remodels cell surface proteome to alter how they sense environmental factors, as exemplified by Type II interferon gamma (IFN-{gamma}). Compared to proliferating cells, senescent cells upregulate IFN-{gamma} receptor, become hypersensitized to microenvironmental IFN-{gamma}, and more robustly induce antigen presenting machinery -effects also recapitulated in human tumor cells treated with senescence-inducing drugs. Disruption of the IFN-{gamma} sensing by senescent cells blunts their immune-mediated clearance without disabling their characteristic secretory program or immune cell recruitment. Our results demonstrate that senescent cells have an enhanced ability to both send and receive environmental signals, and imply that each process is required for their effective immune surveillance. SIGNIFICANCEOur work identifies a novel interplay between tissue remodeling and tissue sensing programs that can be engaged by senescence in advanced cancers to render tumor cells more visible to the adaptive immune system. This new facet of senescence establishes reciprocal heterotypic signaling interactions that can be induced therapeutically to enhance anti-tumor immunity.

cancer biology↗