Biology subjects

Jenkins, M. W.

Publications and source records attributed to Jenkins, M. W..

5 recordsLinked to original sources

bioRxiv2026

Automated detection of blink reflexes evoked by optogenetic stimulation of TRPV1-expressing corneal nociceptors in transgenic mice

BackgroundConventional rodent models for the study of corneal pain commonly evoke eye blink reflex using methods that indiscriminately activate polymodal nociceptors, mechanoreceptors, and thermoreceptors at temporal resolutions that dont closely match the sub-second timescale of underlying neural dynamics. New methodWe introduce a novel automated behavioral paradigm for detecting blink reflexes in transgenic TRPV1-ChR2-EYFP mice, enabled by cell-type-specific, millisecond-precision optogenetic stimulation of corneal nociceptors (490 nm light). Using multi-feature quantification, we achieve robust automated detection using univariate and multivariate classifiers. ResultsTRPV1-ChR2-EYFP mice exhibited blink reflexes to high-intensity blue light (490 nm, 10 ms pulses) in a threshold-dependent manner (N=3). Blink probability was 77.1 {+/-} 17.1% at high intensity (2.77 mW/mm2) versus 4.2 {+/-} 4.2% at low intensity (0.46 mW/mm2). Red light (638 nm) produced no intensity-dependent change. Noxious air puff evoked blinks in >95% of trials under all conditions. DeepLabCut-based pose estimation extracted six features quantifying the blink reflex, enabling automated detection with [≥]98% accuracy using univariate and multivariate classifiers. Comparison with existing methodsUnlike conventional air puff paradigms, this optogenetic approach enables precise, cell-type-specific stimulation of corneal nociceptors, supporting automated analysis of blink responses at sub-second resolution. ConclusionsThis video tracking behavioral method using machine learning algorithms that accurately classify blink versus no-blink enables high-throughput and observer-independent empirical assessment of blink reflex, suggestive of corneal pain. Moreover, inducing blink reflex in TRPV1-ChR2 mice using high-intensity blue light also demonstrates nociceptive-specific behavioral responses analogous to somatosensory optogenetically-evoked hindpaw pain in the same animal genotype.

neuroscience↗

bioRxiv2026

stMCP: Spatial Transcriptomics with a Model Context Protocol Server

Spatial transcriptomics enables high-resolution mapping of gene expression in intact tissues but remains challenging due to complex computational workflows that limit accessibility and reproducibility. Here, we present a Model Context Protocol (MCP) framework enabling natural language-driven spatial transcriptomics analysis. By executing analytical tools locally, this architecture eliminates the need to upload massive datasets to large language models, bypassing high token costs and mitigating data privacy and training risks. The MCP orchestrator interprets intent, dynamically routes requests, maintains session state, and verifies input integrity to ensure reproducible execution. Benchmarking across biological discovery, orchestration accuracy, token usage, and execution time demonstrates robust performance. This architecture establishes a scalable template for AI-native research by standardizing the interface between models and local analytical engines. Rather than replacing bioinformaticians, this framework empowers biologists to independently and comprehensively explore their data, accelerating hypothesis testing, and unlocking broader biological discoveries.

bioinformatics↗

bioRxiv2025

Automated 3D Segmentation of Human Vagus Nerve Fascicles and Epineurium from Micro-Computed Tomography Images Using Anatomy-Aware Neural Networks

ObjectivePrecise segmentation and quantification of nerve morphology from imaging data are critical for designing effective and selective peripheral nerve stimulation (PNS) therapies. However, prior studies on nerve morphology segmentation suffer from important limitations in both accuracy and efficiency. This study introduces a deep learning approach for robust and automated 3D segmentation of human vagus nerve fascicles and epineurium from high-resolution micro-computed tomography (microCT) images. MethodsWe developed a multi-class 3D U-Net to segment fascicles and epineurium that incorporates a novel anatomy-aware loss function to ensure that predictions respect nerve topology. We trained and tested the network using subject-level five-fold cross-validation with 100 microCT sub-volumes (11.4 m isotropic resolution) from cervical and thoracic vagus nerves stained with phosphotungstic acid from five subjects. We benchmarked the 3D U-Nets performance against a 2D U-Net using both standard and anatomy-specific segmentation metrics. ResultsOur 3D U-Net generated high-quality segmentations (average Dice similarity coefficient: 0.93). Compared to the 2D U-Net, our 3D U-Net yielded significantly better volumetric overlap, boundary delineation, and fascicle-level accuracy. The 3D approach reduced anatomical errors by 2.5-fold, provided more consistent inter-slice boundaries, and improved detection of fascicle splits/merges by nearly 6-fold. SignificanceOur automated 3D segmentation pipeline provides anatomically accurate 3D maps of peripheral neural morphology from microCT data. The automation allows for high throughput, and the substantial improvement in segmentation quality and anatomical fidelity enhances the reliability of morphological analysis, vagal pathway mapping, and the implementation of realistic computational models. These advancements provide a foundation for understanding the functional organization of the vagus and other peripheral nerves and optimizing PNS therapies.

neuroscience↗

bioRxiv2021

Fascicles split or merge every ~560 microns within the human cervical vagus nerve

1Vagus nerve stimulation (VNS) is FDA approved for stroke rehabilitation, epilepsy, and depression; however, the vagus functional anatomy underlying the implant is poorly understood. We used microCT to quantify fascicular structure and neuroanatomy within human cervical vagus nerves. Fascicles split or merged every ~560 m (17.8 {+/-} 6.1 events/cm). The high degree of fascicular splitting and merging in humans may explain the clinical heterogeneity in patient responses.

neuroscience↗

bioRxiv2020

Pocket MUSE: an affordable, versatile and high performance fluorescence microscope using a smartphone

Smartphone microscopes can be effective tools for a broad range of imaging applications. In this manuscript, we demonstrate the first practical implementation of Microscopy with Ultraviolet Surface Excitation (MUSE) in a compact smartphone microscope called Pocket MUSE, resulting in a remarkably effective design. Fabricated with parts from consumer electronics that are readily available at low cost, the small optical module attaches directly over the rear lens in a smartphone and enables high quality multichannel fluorescence microscopy with submicron resolution over a 10X equivalent field of view. In addition to the novel optical configuration, Pocket MUSE is compatible with a series of simple, portable and user-friendly sample preparation strategies that can be directly implemented for various microscopy applications for point-of-care diagnostics, at-home health monitoring, plant biology, STEM education, environmental studies, etc.

bioengineering↗