Biology subjects

Gillespie, T.

Publications and source records attributed to Gillespie, T..

7 recordsLinked to original sources

bioRxiv2026

Mapping California's Urban Forest at Scale: An Error-Adjusted Canopy Time Series for Monitoring Change

Statewide tracking of urban tree canopy change is essential for evaluating progress toward policy targets, but detecting real change requires both high-resolution mapping and rigorous uncertainty estimation. We produced a four-year canopy cover time series for all California census-designated places using 60-cm NAIP aerial imagery and a U-Net deep learning model trained with semi-automated LiDAR-derived labels and manually annotated tiles. Canopy cover and change were estimated using stratified, error-adjusted area estimation, enabling comparisons across years. Statewide canopy cover showed a modest negative trend from 2016 to 2022 (Sens slope: -0.60% per year), but confidence intervals included zero across all groups and climate zones, indicating that trends were not statistically distinguishable from no change. Urban canopy cover was consistently lower than non-urban canopy by approximately six percentage points, and canopy cover was highest in the Northern California Coast and lowest in the Southwest Desert. Residential parcels accounted for 55-56% of canopy within incorporated urban areas across all years, indicating that statewide canopy increase goals will require engagement with private landowners. Error adjustment substantially altered canopy estimates relative to raw pixel-count totals, with direct implications for AB 2251 canopy tracking where baselines and targets drawn from unadjusted maps may not reflect true canopy extent. This open-source workflow is transferable to future NAIP acquisition years and other U.S. states, providing a scalable framework for long-term urban forest monitoring.

ecology↗

bioRxiv2025

Functional synaptic connectivity of engrafted spinal cord neurons with locomotor circuitry in the injured spinal cord

Spinal cord injury (SCI) results in significant neurological deficits, with no currently available curative therapies. Neural progenitor cell (NPC) transplantation has emerged as a promising approach for neural repair, as graft-derived neurons (GDNs) can integrate into the host spinal cord and support axon regeneration. However, the mechanisms underlying functional recovery remain poorly understood. In this study, we investigate the synaptic integration of NPC-derived neurons into locomotor circuits, the projection patterns of distinct neuronal subtypes, and their potential to modulate motor circuit activity. Using transsynaptic tracing in a mouse thoracic contusion SCI model, we found that NPC-derived neurons form synaptic connections with host locomotor circuits, albeit at low frequencies. Furthermore, we mapped the axon projections of V0C and V2a interneurons, revealing distinct termination patterns within host spinal cord laminae. To assess functional integration, we employed chemogenetic activation of GDNs, which induced muscle activity in a subset of transplanted animals. However, NPC transplantation alone did not significantly improve locomotor recovery, highlighting a key challenge in the field. Our findings suggest that while GDNs can integrate into host circuits and modulate motor activity, synaptic connectivity remains a limiting factor in functional recovery. Future studies should focus on enhancing graft-host connectivity and optimizing transplantation strategies to maximize therapeutic benefits for SCI.

neuroscience↗

bioRxiv2024

Pathological microcircuits initiate epileptiform events in patient hippocampal slices

How seizures begin at the level of microscopic neuronal circuits remains unknown. Advancements in high-density CMOS-based microelectrode arrays can be harnessed to study neuronal network activity with unprecedented spatial and temporal resolution. We use high-density electrophysiology recordings to probe the network activity of human hippocampal brain slices from six patients with mesial temporal lobe epilepsy. Two slices from the dentate gyrus exhibited epileptiform activity in the presence of low magnesium media with kainic acid. Both slices exhibit network oscillations indicative of a reciprocally connected circuit, which is unexpected under normal physiological conditions. Future studies may apply this approach to elucidate the network signals that underlie seizure initiation.

neuroscience↗

bioRxiv2021

Brain Data Standards Ontology: A data-driven ontology of transcriptomically defined cell types in the primary motor cortex

Large-scale single-cell omics profiling is revolutionising our understanding of cell types in complex organs like the brain, where it is being used to define a complete catalogue of cell types, something that traditional methods struggle with due to the diversity and complexity of the brain. But this poses a problem. How do we organise such a catalogue - providing a standard way to refer to the cell types discovered, linking their classification and properties to supporting data? Cell ontologies provide a solution to recording definitions, classifications, and properties of cell types and provide standard identifiers for annotation, but they currently do not support the data driven cell type definitions and classifications needed for multi-modal single cell omics profiling. Here we describe the construction and application of a semi-automated, data-linked extension to the Cell Ontology that represents cell types in the Primary Motor Cortex of humans, mice and marmosets. The methods and resulting ontology are designed to be scalable and applicable to similar whole brain atlases currently in preparation.

neuroscience↗

bioRxiv2021

The SPARC DRC: Building a resource for the autonomic nervous system community

The Data and Resource Center (DRC) of the NIH-funded SPARC program is developing databases, connectivity maps and simulation tools for the mammalian autonomic nervous system. The experimental data and mathematical models supplied to the DRC by the SPARC consortium are curated, annotated and semantically linked via a single knowledgebase. A data portal has been developed that allows discovery of data and models both via semantic search and via an interface that includes Google Map-like 2D flatmaps for displaying connectivity, and 3D anatomical organ scaffolds that provide a common coordinate framework for cross-species comparisons. We discuss examples that illustrate the data pipeline, which includes data upload, curation, segmentation (for image data), registration against the flatmaps and scaffolds, and finally display via the web portal, including the link to freely available online computational facilities that will enable neuromodulation hypotheses to be investigated by the autonomic neuroscience community and device manufacturers.

neuroscience↗

bioRxiv2020

Bacterial flagella disrupt host cell membranes and interact with cytoskeletal components

Bacterial flagella have many established roles beyond swimming motility. Despite clear evidence of flagella-dependent adherence, the specificity of ligands and mechanisms of binding are still debated. In this study, the molecular basis of E. coli O157:H7 and S. Typhimurium flagella binding to epithelial cell cultures was investigated. Flagella interactions with host cell surfaces were intimate and crossed cellular boundaries as demarcated by actin and membrane labelling. SEM revealed flagella disappearing into cellular surfaces and TEM of S. Typhiumurium indicated host membrane deformation and disruption in proximity to flagella. Motor mutants of E. coli O157:H7 and S. Typhimurium caused reduced haemolysis compared to wild-type, indicating that membrane disruption was in part due to flagella rotation. Flagella from E. coli O157 (H7), EPEC O127 (H6), and S. Typhimurium (P1 & P2 flagella) were shown to bind to purified intracellular components of the actin cytoskeleton and directly increase in vitro actin polymerisation rates.

microbiology↗

bioRxiv2017

Advancing A Science For Sustaining Health: Establishing A Model Health District in Madagascar

ObjectiveWe demonstrate a replicable model health district for Madagascar. The governments of many low-income countries have adopted health policies that follow international standards, and yet there are four hundred million people without basic access to primary care. Closing this global health delivery gap is typically framed as an issue of scale-up, accomplished primarily through integrating international donor funds with broad-based health system strengthening (HSS) efforts. However, there is no established process by which healthcare systems measure improvements at the point of service and how those, in turn, impact population health. There is no gold standard, equivalent to randomized trials of individual-level interventions, for health systems research. Here, we present a framework for a model district in Madagascar where national policies are implemented along with additional health system interventions to allow for bottom-up adaptation.\n\nSettingThe intervention takes place in a government district in Madagascar, which includes 1 district hospital, 20 primary care health centers, and a network of community health workers.\n\nInterventionThe program simultaneously strengthens the WHOs six building blocks of HSS at all levels of the health system within a government district and pioneers a data platform that includes 1) strengthening the districts health management information systems; 2) monitoring and evaluation dashboards; and 3) a longitudinal cohort demographic and health study of over 1,500 households, with a true baseline in intervention and comparison groups.\n\nConclusionThe integrated intervention and data platform allows for the evaluation of system output indicators as well as population-level impact indicators, such as mortality rates. It thus supports field-based implementation and policy research to fill the know-do gap, while providing the foundation for a new science of sustaining health.\n\nData Sharing StatementData can be made available upon request by emailing research@pivotworks.org.

epidemiology↗