Biology subjects

Wu, Y. I.

Publications and source records attributed to Wu, Y. I..

3 recordsLinked to original sources

bioRxiv2025

Decoding memory dysfunction in hippocampal amnesia

The hippocampus reconstructs past experiences by integrating sensory, perceptual, and conceptual information across a cortico-hippocampal autobiographical memory network (AMN). Here, in 18 human participants with amnesia, we decoded the effects of bilateral focal hippocampal damage on distinct autobiographical representations using representational dissimilarity matrices (RDMs). Hippocampal pathology resulted in: (1) impaired generalised episodic memory retrieval RDM model fit in the left angular gyrus; and, (2) reduced distinct episodic memory RDM model fit and trial-by-trial voxel-representational stability in the right angular gyrus, right orbitofrontal cortex, and right inferior frontal gyrus. RDM model fits and mnemonic stability were predicted by total CA23 volumes. Trial-by-trial retrieval stability within the right orbitofrontal cortex and right inferior frontal gyrus predicted autobiographical memory performance, providing the first direct neural correlate between hippocampal dysfunction, altered mnemonic representations, and amnesia. The results demonstrate that hippocampal-mediated amnesia results from impaired mnemonic representational distinctiveness and stability within the AMN.

neuroscience↗

bioRxiv2020

Primary cilia sensitize insulin receptor-mediated negative feedback in pancreatic β cells

Insulin receptors (IR) can localize to the primary cilia of pancreatic {beta} cells. Because primary cilia are known to sensitize or bias the signaling of cell surface receptors, we investigate how ciliary insulin receptors influence glucose-stimulated insulin secretion (GSIS) in {beta} cells by gauging how cytosolic calcium concentration changes in a mouse insulinoma cell line (MIN6). Purified recombinant insulin suppresses calcium elevation in response to glucose in these cells. Interestingly, ciliated cells show attenuated cytosolic calcium elevation compared to cilium-free cells after glucose stimulation even in the absence of exogenous insulin. We observe that ciliary IR is highly phosphorylated, and the phospho-IR density decreases when cells are either treated with an insulin receptor (IR) inhibitor, BMS536924, or ciliary function is disrupted through either IFT88 or BBS1 knockdown. Consistently, the attenuation of calcium elevation in ciliated cells is abrogated when cells are either treated with IR inhibitor or when primary cilia are impaired. We further demonstrate that ciliary IR signaling hyperpolarizes the plasma membrane but has no apparent impact on glucose-induced ATP production. Thus, our results argue that primary cilia sensitize insulin receptor signaling and mediate negative feedback in GSIS in pancreatic {beta} cells.

cell biology↗

bioRxiv2018

baRcodeR with PyTrackDat: Open-source labelling and tracking of biological samples for repeatable science

Repeatable experiments with accurate data collection and reproducible analyses are fundamental to the scientific method but may be difficult to achieve in practice. Several flexible, open-source tools developed for the R and Python coding environments aid the reproducibility of data wrangling and analysis in scientific research. In contrast, analogous tools are generally lacking for earlier stages, such as systematic labelling and processing of field samples with hierarchical structure (e.g. time points of individuals from multiple lines or populations) or curating heterogenous data collected by different researchers over several years. Such tools are critical for modern research given trends toward globally distributed collaborators using higher-throughput technologies. As a step toward improving repeatability of methods for the collection of biological samples, and curation of biological data, we introduce the R package baRcodeR and the PyTrackDat pipeline in Python. The baRcodeR package provides tools for generating biologically informative, hierarchical labels with digitally encoded 2D barcodes that can be printed and scanned using low-cost commercial hardware. The PyTrackDat pipeline integrates with baRcodeR output to build a web interface for sample management and tracking along with data collection and curation. We briefly describe the application of principles from baRcodeR and PyTrackDat in three large research projects, which demonstrate their value to (i) help document sampling methods, (ii) facilitate collaboration and (iii) reduce opportunities for human errors and omissions that could otherwise propagate through downstream data analysis to compromise biological inference.

bioinformatics↗