Biology subjects

Snyder, P.

Publications and source records attributed to Snyder, P..

4 recordsLinked to original sources

bioRxiv2024

Wild Florida Mottled Ducks demonstrate strong heterogeneity in their humoral innate immune response

The Florida Mottled Duck (Anas fulvigula fulvigula) is a unique subspecies of waterfowl whose range is limited to peninsular Florida, USA. As an endemic species, Florida Mottled Ducks face numerous conservation stressors, such as habitat conversion and hybridization with non-native Mallards (Anas platyrhynchos). In addition to these numerous stressors, Mottled Ducks are also contending with emerging and/or geographically expanding waterborne pathogens such as Vibrio spp., due to the effects of climate change. However, even given their conservation needs, little is known with respect to the health, physiology and the immunity of wild Mottled Ducks in Florida. Given this lack of data, we performed health assessments of Mottled Ducks in the Central Florida area. Specifically, we examined the humoral innate immune system, i.e., plasma, of Mottled Ducks in response to a common, but extraneous pathogen, Escherichia coli strain ATCC number 8739. We utilized a bactericidal assay (BKA) commonly used in eco-immunology, to provide insight into the bactericidal capacities of captured Florida Mottled Ducks. We statistically tested the BKA capacity of 23 Mottled Ducks in response to age and whole blood lead levels (Pb). We found that there was no statistically significant relationship between the covariates we measured and Mottled Duck BKA capacity against E. coli. However, the variability we observed in the BKA capacity of this subspecies warrants further research into additional physiological and ecological covariates coupled with potential immune stressors that Florida Mottled Ducks may be contending with.

ecology↗

bioRxiv2020

Single cell tracking based on Voronoi partition via stable matching

Live-cell imaging is an important technique to study cell migration and proliferation as well as image-based profiling of drug perturbations over time. To gain biological insights from live-cell imaging data, it is necessary to identify individual cells, follow them over time and extract quantitative information. However, since often biological experiment does not allow the high temporal resolution to reduce excessive levels of illumination or minimize unnecessary oversampling to monitor long-term dynamics, it is still a challenging task to obtain good tracking results with coarsely sampled imaging data. To address this problem, we consider cell tracking problem as "stable matching problem" and propose a robust tracking method based on Voronoi partition which adapts parameters that need to be set according to the spatio-temporal characteristics of live cell imaging data such as cell population and migration. We demonstrate the performance improvement provided by the proposed method using numerical simulations and compare its performance with proximity-based tracking and nearest neighbor-based tracking.

systems biology↗

bioRxiv2020

Crowdsourcing digital health measures to predict Parkinson's disease severity: the Parkinson's Disease Digital Biomarker DREAM Challenge

Mobile health, the collection of data using wearables and sensors, is a rapidly growing field in health research with many applications. Deriving validated measures of disease and severity that can be used clinically or as outcome measures in clinical trials, referred to as digital biomarkers, has proven difficult. In part due to the complicated analytical approaches necessary to develop these metrics. Here we describe the use of crowdsourcing to specifically evaluate and benchmark features derived from accelerometer and gyroscope data in two different datasets to predict the presence of Parkinsons Disease (PD) and severity of three PD symptoms: tremor, dyskinesia and bradykinesia. Forty teams from around the world submitted features, and achieved drastically improved predictive performance for PD status (best AUROC=0.87), as well as tremor (best AUPR=0.75), dyskinesia (best AUPR=0.48) and bradykinesia (best AUPR=0.95) severity.

bioengineering↗

bioRxiv2019

Meta-analysis of the human brain transcriptome identifies heterogeneity across human AD coexpression modules robust to sample collection and methodological approach

Alzheimers disease (AD) is a complex and heterogenous brain disease that affects multiple inter-related biological processes. This complexity contributes, in part, to existing difficulties in the identification of successful disease-modifying therapeutic strategies. To address this, systems approaches are being used to characterize AD-related disruption in molecular state. To evaluate the consistency across these molecular models, a consensus atlas of the human brain transcriptome was developed through coexpression meta-analysis across the AMP-AD consortium. Consensus analysis was performed across five coexpression methods used to analyze RNA-seq data collected from 2114 samples across 7 brain regions and 3 research studies. From this analysis, five consensus clusters were identified that described the major sources of AD-related alterations in transcriptional state that were consistent across studies, methods, and samples. AD genetic associations, previously studied AD-related biological processes, and AD targets under active investigation were enriched in only three of these five clusters. The remaining two clusters demonstrated strong heterogeneity between males and females in AD-related expression that was consistently observed across studies. AD transcriptional modules identified by systems analysis of individual AMP-AD teams were all represented in one of these five consensus clusters except ROS/MAP-identified Module 109, which was specific for genes that showed the strongest association with changes in AD-related gene expression across consensus clusters. The other two AMP-AD transcriptional analyses reported modules that were enriched in one of the two sex-specific Consensus Clusters. The fifth cluster has not been previously identified and was enriched for genes related to proteostasis. This study provides an atlas to map across biological inquiries of AD with the goal of supporting an expansion in AD target discovery efforts.

systems biology↗