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AutoMedTS:Automated modeling of physiological time series for surgical suturing action recognition
Get PDFIn laparoscopic surgical training and evaluation, real-time recognition of surgical actions with transparency outputs is crucial for automated, objective, and immediate instructional feedback to support skills improvement. However, we face challenges due to limited dataset sizes and variability in surgical environments. This study presents AutoMedTS, an end-to-end automated machine learning framework customized for medical time-series data, enabling rapid deployment using surgical suturing trajectories collected from both expert and novice surgeons. The proposed method features key improvements including: (i) a novel temperature-scaled Softmax resampling technique effectively addressing severe class imbalance, and (ii) an uncertainty-aware ensemble selection mechanism ensuring robust predictions across surgeons with varying skill levels. Additionally, the approach emphasizes model transparency to meet the high standards of reliability and transparency required in medical applications. Compared to deep learning methods, traditional machine learning models not only facilitate efficient rapid deployment but also offer significant transparency advantages. Experimental results demonstrate that our method provides fast, stable, and reliable real-time surgical action recognition in clinical training environments. Code and data are publicly available at https://github.com/baobingzhang/AutoMedTS.</p
The secondary bile acid, lithocholic acid, inhibits cystic fibrosis transmembrane conductance regulator expression and activity in colonic epithelial cells
Get PDFClassically known for their roles in facilitating lipid digestion and absorption, bile acids are now also appreciated as enterocrine hormones that modulate many aspects of intestinal physiology. We have previously shown lithocholic acid (LCA), a secondary bile acid, to be protective against colonic inflammation. Here, we investigated whether LCA also regulates colonic epithelial fluid and electrolyte transport. T84 cell monolayers were mounted in Ussing chambers for measurements of transepithelial Cl− secretion. CFTR mRNA and protein expression were analyzed by qRT-PCR and Western blotting in T84 cells and human-derived colonic organoids. CFTR promoter activity was assessed using a luciferase promoter/reporter assay in HEK293 cells. Pretreatment of T84 cells with LCA inhibited Cl− secretory responses to the cAMP-dependent agonist, forskolin (FSK), with maximal effects occurring at a concentration of 10 µM after 24 h of treatment. Under these conditions, LCA also inhibited responses to the Ca2+-dependent secretagogues, thapsigargin, and histamine. In nystatin-permeabilized T84 monolayers, LCA reduced FSK-stimulated apical Cl− conductances, an effect that correlated with reduced CFTR Cl− channel expression. Although LCA activated both farnesoid X receptor (FXR) and vitamin D receptor (VDR), its effects on CFTR expression and Cl− conductances were mimicked only by an FXR agonist, GW4064, and not by a VDR agonist, calcitriol. Finally, LCA inhibited CFTR promoter activity in HEK3 cells, but only when FXR was expressed. LCA, at physiologically relevant concentrations, chronically inhibits colonic epithelial Cl− secretion, likely via FXR-induced downregulation of CFTR. These data broaden our knowledge of the regulatory roles of LCA in the colon and highlight its potential as a therapeutic target for intestinal disorders.NEW & NOTEWORTHY This study reveals a previously unrecognized role for lithocholic acid (LCA) in chronically suppressing colonic epithelial chloride secretion. We demonstrate a genomic mechanism of action for LCA that is likely mediated by FXR-induced downregulation of CFTR expression and function. These findings highlight LCA as a key modulator of intestinal fluid and electrolyte transport and underline the therapeutic potential of targeting bile acids and their receptors for the treatment of diarrheal diseases
Boltzmann Sampling for Powersets without an Oracle
Get PDFWe show that powersets over structures with a bounded counting sequence can be sampled efficiently without evaluating the generating function. An algorithm is provided, implemented, and tested. Runtimes are comparable to existing Boltzmann samplers reported in the literature
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