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Biology subjects

Chen, Y.-K.

Publications and source records attributed to Chen, Y.-K..

5 recordsLinked to original sources

Electrode pooling preserves movement decoding by retaining neural population dynamics

New implantable-electrode fabrication strategies make dense, ultrafine electrode arrays with lower tissue burden increasingly feasible, shifting a key bottleneck for scalable brain-computer interfaces from electrode placement to readout capacity. Electrode pooling, in which multiple electrodes share a readout channel, could relax this bottleneck by combining extracellular signals before acquisition, but it has remained unclear whether such compression preserves the neural population structure needed for behavioral decoding. Here we evaluate this question using software-emulated electrode pooling in mouse sensorimotor cortex during a cue-guided reach-and-grasp task using a high-density microwire array coupled to a CMOS microelectrode-array platform. Pooled recordings retain forelimb kinematic information more effectively than a channel-matched control that discards electrodes. Pooling reduces the separability of electrode-specific spikes and sorted units, indicating a loss of some neuronal detail, but the mixed signals still preserve task-aligned low-dimensional latent dynamics that support decoding. When readout capacity is fixed, this trade-off allows broader electrode coverage to contribute to behaviorally informative population sampling. Together, these results define electrode pooling as a design trade-off for scalable readout, in which some electrode-specific neuronal information is lost but the population dynamics needed for movement decoding remain accessible.

neuroscience↗

OpusTaxa: A Unified Workflow for Taxonomic Profiling, Assembly, and Functional Analysis of Shotgun Metagenomes

Shotgun metagenomics has become a cornerstone of microbiome research, yet the complexity of existing workflows remains a major barrier for life scientists without dedicated bioinformatics support. Manual database setup, detailed sample sheet preparation, and management of software dependencies can make routine analysis difficult and time-consuming. Cross-study comparisons are further hampered by inconsistent processing pipelines, database versions, and profiling strategies, limiting reproducibility and the potential for large-scale meta-analyses. We present OpusTaxa, an open-source Snakemake workflow that provides end-to-end processing of short paired-end shotgun metagenomic data with minimal configuration. Users provide either FASTQ files or Sequence Read Archive accessions; OpusTaxa automatically downloads required databases, performs quality control, removes host reads, and executes taxonomic profiling, metagenome assembly, and functional analysis. All analysis modules can be independently toggled, and per-sample outputs are automatically merged into harmonised, cross-sample tables ready for downstream exploration. Across two public datasets, we demonstrate how OpusTaxa can be used to compare consistency across complementary taxonomic profilers and to estimate microbial load in addition to standard metagenomic workflows. AvailabilityOpusTaxa is freely available at https://github.com/yenkaiC/OpusTaxa. Documentation, test data, and example configurations are included in the repository.

bioinformatics↗

Zinc supplement augments the suppressive effects of repurposed drugs of NF-kappa B inhibitor on ACE2 expression in human lung cell lines in vitro.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes a vast number of infections and fatalities worldwide. As the development and safety validation of effective vaccines are ongoing, drug repurposing is most efficient approach to search FDA approved agents against coronavirus disease 2019 (COVID-19). In the present study, we found that endogenous ACE2 expressions could be detected in H322M and Calu-3 cell lines, as well as their ACE2 mRNA and protein expressions were suppressed by pyrrolidine dithiocarbamate (PDTC), a NF-kappa B inhibitor, in dose- and time-dependent manners. Moreover, N-acetyl-cysteine (NAC) pretreatment reversed PDTC-induced ACE2 suppression, as well as the combined treatment of hydrogen peroxide and knockdown of p50 subunit of NF-kappa B by siRNA reduced ACE2 expression in H322M cells. In addition, anthelmintic drug triclabendazole and antiprotozoal drug emetine, repurposed drugs of NF-kappa B inhibitor, also inhibited ACE2 mRNA and protein expressions in H322M cells. Moreover, zinc supplement augmented the suppressive effects of triclabendazole and emetine on ACE2 suppression in H322M and Calu-3 cells. Taken together, these results indicate that ACE2 expression is modulated by reactive oxygen species (ROS) and NF-kappa B signal in human lung cell lines, and zinc combination with triclabendazole or emetine has the clinical potential for the prevention and treatment of COVID-19.

cell biology↗

Azithromycin Plus Zinc Sulfate Rapidly and Synergistically Suppresses IκBα-Mediated In Vitro Human Airway Cell ACE2 Expression for SARS-CoV-2 Entry

Large-scale efforts have been persistently undertaken for medical prophylaxis and treatment of COVID-19 disasters worldwide. A variety of novel viral spike protein-targeted vaccine preparations have recently been clinically distributed based on accelerated approval. We revisited the early but inconclusive clinical interest in the combination of azithromycin and zinc sulfate repurposing with safety advantages. In vitro proof of concept was provided for rapid and synergistic suppression of ACE2 expression following treatments in human airway cells, Calu-3 and H322M. The two representative ACE2-expressing human airway cells indicate the upper and lower respiratory tracts. Prophylactic and early therapeutic roles of azithromycin combined with zinc are proposed for virus cellular entry prevention potential bridging to effective antibody production.

molecular biology↗

PyBindingCurve, simulation and curve fitting to complex binding systems at equilibrium.

Understanding multicomponent binding interactions in protein-ligand, protein-protein and competition systems is essential for fundamental biology and drug discovery. Hand deriving equations quickly becomes unfeasible when the number of components is increased, and direct analytical solutions only exist to a certain complexity. To address this problem and allow easy access to simulation, plotting and parameter fitting to complex systems at equilibrium, we present the Python package PyBindingCurve. We apply this software to explore homodimer and heterodimer formation culminating in the discovery that under certain conditions, homodimers are easier to break with an inhibitor than heterodimers and may also be more readily depleted. This is a potentially valuable and overlooked phenomenon of great importance to drug discovery. PyBindingCurve may be expanded to operate on any equilibrium binding system and allows definition of custom systems using a simple syntax. PyBindingCurve is available under the MIT license at: https://github.com/stevenshave/pybindingcurve as Python source code accompanied by examples and as an easily installable package within the Python Package Index.

biophysics↗