Biology subjects

Lin, M.-K.

Publications and source records attributed to Lin, M.-K..

3 recordsLinked to original sources

bioRxiv2026

Noninvasive Focal Gene Delivery of Functional Neural Actuators to the Primate Spinal Cord using Focused Ultrasound

Pathologies of the spinal cord -- from degenerative diseases to chronic pain -- represent a substantial global health burden. Although surgical and pharmacological treatments for spinal cord pathologies have advanced considerably, therapies capable of addressing the cellular mechanisms underlying these conditions remain limited. Viral gene therapies present a compelling alternative, allowing for delivery of therapeutic genes that directly target the pathological processes in specific cell-types. Effective viral delivery to the spinal cord, however, remains constrained by a fundamental tradeoff between procedural invasiveness and spatial precision. As such, there remains a need for clinically tractable methods -- that are both noninvasive and focal -- to deliver gene therapeutics across the restrictive vascular boundaries of the blood-spinal cord barrier (BSCB). Here, we demonstrate noninvasive, focal disruption of the BSCB and delivery of systemically administered chemogenetic gene payloads to the cervical and thoracic spinal cord in marmoset nonhuman primates (Callithrix jacchus) using focused ultrasound (FUS). Through systematic testing of ultrasonic pressures and central frequencies, we establish a FUS parameter set optimized for robust, spatially constrained molecular delivery across the marmoset BSCB. Using these optimized parameters, we show that FUS BSCB disruption permitted focal penetrance of systemically administered viral vectors for transduction of both fluorescent transgenes and excitatory chemogenetics within targeted spinal segments. Positron emission tomography (PET) imaging following chemogenetic actuation revealed significantly increased metabolic demand within the targeted region of the spinal cord, demonstrating in vivo evidence of functional transgene expression. Behavioral and histopathological assessments demonstrated preserved neurological function and tissue integrity, supporting the safety of FUS BSCB disruption and viral delivery in nonhuman primates. To facilitate broad application of this platform for noninvasive delivery of receptor-based gene therapeutics in marmosets, we generated an ultra-high-resolution (74 m) multimodal MRI/CT spinal cord template for precise targeting and anatomical localization. We also provide open-access engineering drawings and CAD files for our M-FRAME system (Marmoset Fixation and Reorientation Apparatus for Multimodal Experiments), enabling precise and repeatable spinal targeting without surgical fixation. Together, these results establish FUS-mediated BSCB disruption as a safe and effective approach for noninvasive, focal gene delivery to the primate spinal cord.

neuroscience↗

bioRxiv2024

An Open Access Resource for Marmoset Neuroscientific Apparatus

The use of the common marmoset (Callithrix jacchus) for neuroscientific inquiry has grown precipitously over the past two decades. Despite windfalls of grant support from funding initiatives in North America, Europe, and Asia to model human brain diseases in the marmoset, marmoset- specific apparatus are of sparse availability from commercial vendors and thus are often developed and reside within individual laboratories. Through our collective research efforts, we have designed and vetted myriad designs for awake or anesthetized magnetic resonance imaging (MRI), positron emission tomography (PET), computed tomography (CT), as well as focused ultrasound (FUS), electrophysiology, optical imaging, surgery, and behavior in marmosets across the age- span. This resource makes these designs openly available, reducing the burden of de novo development across the marmoset field. The computer-aided-design (CAD) files are publicly available through the Marmoset Brain Connectome (MBC) resource (https://www.marmosetbrainconnectome.org/apparatus/) and include dozens of downloadable CAD assemblies, software and online calculators for marmoset neuroscience. In addition, we make available a variety of vetted touchscreen and task-based fMRI code and stimuli. Here, we highlight the online interface and the development and validation of a few yet unpublished resources: Software to automatically extract the head morphology of a marmoset from a CT and produce a 3D printable helmet for awake neuroimaging, and the design and validation of 8-channel and 14- channel receive arrays for imaging deep structures during anatomical and functional MRI.

bioengineering↗

bioRxiv2020

Semantic segmentation of microscopic neuroanatomical data by combining topological priors with encoder-decoder deep networks

Understanding of neuronal circuitry at cellular resolution within the brain has relied on tract tracing methods which involve careful observation and interpretation by experienced neuroscientists. With recent developments in imaging and digitization, this approach is no longer feasible with the large scale (terabyte to petabyte range) images. Machine learning based techniques, using deep networks, provide an efficient alternative to the problem. However, these methods rely on very large volumes of annotated images for training and have error rates that are too high for scientific data analysis, and thus requires a significant volume of human-in-the-loop proofreading. Here we introduce a hybrid architecture combining prior structure in the form of topological data analysis methods, based on discrete Morse theory, with the best-in-class deep-net architectures for the neuronal connectivity analysis. We show significant performance gains using our hybrid architecture on detection of topological structure (e.g. connectivity of neuronal processes and local intensity maxima on axons corresponding to synaptic swellings) with precision/recall close to 90% compared with human observers. We have adapted our architecture to a high performance pipeline capable of semantic segmentation of light microscopic whole-brain image data into a hierarchy of neuronal compartments. We expect that the hybrid architecture incorporating discrete Morse techniques into deep nets will generalize to other data domains.

neuroscience↗