CVM Research

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Research continues to be one of the major missions of the College of Veterinary Medicine at Cornell University. As such, its faculty, students, and research scientists produce materials such as posters and datasets that describe or are related to their basic, applied and translational research activities and accomplishments.

This collection includes research outputs that have been submitted voluntarily by faculty, postdoctoral fellows, graduate students, veterinary students, technical personnel, and other research associates. Open access is provided under Creative Commons licenses.

Further information about the College’s research activities can be found at http://www.vet.cornell.edu/research/

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Recent Submissions

Now showing 1 - 10 of 80
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    Chronic Wasting Disease Surveillance Optimization Software (n x 2)
    Hanley, Brenda J.; Mitchell, Corey I.; Them, Cara E.; Walter, W. David; Walsh, Daniel P.,; Jennelle, Christopher S.; Hollingshead, Nicholas A.; Abbott, Rachel C.; Kelly, James D.; Grove, Daniel M.; Williams, David; Christensen, Sonja A.; Ahmed, Md Sohel; Booth, James G.; Guinness, Joseph; Gagne, Roderick B.; DiSalvo, Andrew R.; Fleegle, Jeannine T.; Rosenberry, Christopher S.; Miller, Landon A.; Schuler, Krysten L. (2023-09-22)
    The Chronic Wasting Disease Surveillance Optimization Software (n x 2) computes sampling recommendations for state, tribal, or provincial wildlife management agencies when the goal of the disease surveillance program is to detect chronic wasting disease (CWD) in white-tailed deer (Odocoileus virginianus). Driven by a combinatorial optimization algorithm, the Software pinpoints the number of surveillance points that should be evaluated in each county (or administrative area) to maximize the return-on-investment of sampling to the agency, while staying within the predetermined annual CWD surveillance budget. Agency representatives parameterize their Software with their total annual budget, weightings for specific management objectives, a summary of the historical sampling data, per-deer sampling costs, benefits of first and early detections, risk of spread, and benefits of an ad hoc sampling strategy. Outputs include the set of counties that should be sampled in the upcoming surveillance season. We designed the Software for use in Tennessee, US, but included directions for other states or provinces.
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    Surveillance Benefit Components for Chronic Wasting Disease in White-Tailed Deer
    Them, Cara E.; Mitchell, Corey I.; Hollingshead, Nicholas A.; Abbott, Rachel C.; Hanley, Brenda J.; Ahmed, Md Sohel; Booth, James G.; Jennelle, Chris S.; Hodel, Florian H.; Guinness, Joe; Ballard, Jennifer R.; Riggs, A. J.; Middaugh, Christopher R.; Cunningham, Mark; Clemons, Bambi; Sayler, Katherine; Killmaster, Charlie H.; Harms, Tyler M.; Ruden, Rachel M.; Caudell, Joe; Westrich, Michelle Benavidez; McCallen, Emily; Casey, Christine; O’Brien, Lindsey M.; Trudeau, Jonathan K.; Straka, Kelly; Stewart, Chad; Carstensen, Michelle; McKinley, William T.; Hynes, Kevin P.; Ableman, Ashley; Miller, Lauren A.; Cook, Merril; Myers, Ryan; Shaw, Jonathan; Van de Berg, Sarah; Tonkovich, Michael J.; Nituch, Larissa; Kelly, James D.; Grove, Daniel M.; Storm, Daniel J.; Schuler, Krysten L. (2023-09-22)
    The Surveillance Benefit Components for Chronic Wasting Disease in White-Tailed Deer is multivariable data representing epidemiological, population, ecological, and anthropogenic attributes of chronic wasting disease (CWD) in wild, white-tailed deer (Odocoileus virginianus) in the region of the United States (US) containing the states of Arkansas, Florida, Georgia, Indiana, Iowa, Kentucky, Maryland, Michigan, Minnesota, Mississippi, New York, North Carolina, Ohio, Tennessee, and Wisconsin, and in the region of Canada containing the province of Ontario. The data was made available through state and provincial wildlife agencies in partnership with the Surveillance Optimization Project for Chronic Wasting Disease (SOP4CWD), administered by the Cornell Wildlife Health Lab (CWHL) at Cornell University and Boone and Crockett Quantitative Wildlife Center at Michigan State University. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.
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    Wildlife Disease Hazard Software Version 2
    Them, Cara E.; Hanley, Brenda J.; Mitchell, Corey I.; Abbott, Rachel C.; Hollingshead, Nicholas A.; Schuler, Krysten L. (2023-08-21)
    The Wildlife Disease Hazard Software Version 2 depicts US counties in which anthropogenic activities enhance the risk of CWD introduction and pinpoints how cervid demographic parameters influence the spread of CWD. We packaged the software using examples from the states of Tennessee and New York. We included for each example state the (redacted) hazard and (redacted) demographic data from white-tailed deer (Odocoileus virginianus). The software can be adapted for use in other geographical entities such as province or Tribal nation. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.
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    Raptor Health V4: Software to assess the population-scale impact of mortality in raptors
    Hanley, Brenda; Dhondt, André; Forzán, María; Bunting, Elizabeth M.; Pokras, Mark A.; Hynes, Kevin P.; Dominquez-Villegas, Ernesto; Schuler, Krysten L. (2023-08-18)
    The Raptor Health V4 software allows wildlife professionals to use a mathematical model and 17-sequential years of nesting or breeding adult count data to examine the localized population-scale impacts to raptor populations arising from one or more source of observed mortality. The mathematical model is the closed-system Lefkovitch matrix, where closed-system is defined to be no gains or losses to the population from dispersal. The software allows the user to input demographic parameters as well as time series data (counts of nesting pairs and counts of mortalities) to produce comparative demographic quantities between a population with and without the source of mortality, including the annual and bi-annual abundances of hatchlings, non-breeders, and breeders, growth rates (long-term, transient, cumulative, and stochastic), stable stage distributions, reproductive values, and dominant elasticities. The software automatically generates non-parametric (Kruskal-Wallis) statistical tests to compare differences in median growth rates between populations with and without the source of mortality, as well as quantifies the bias introduced through the use of the algorithm as an estimator. Default values in the software depict parameters of bald eagles (Haliaeetus leucocephalus) and eagle nesting and mortality data collected by biologists at the New York State Department of Environmental Conservation (NYSDEC).
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    Habitat Risk Version 2 Software
    Hanley, Brenda; Mitchell, Corey I.; Walter, W. David; Them, Cara E.; Kelly, James D.; Abbott, Rachel C.; Hollingshead, Nicholas A.; Miller, Landon A.; Schuler, Krysten L. (2023-08-18)
    The Habitat Risk Version 2 Software, hereafter “Habitat Risk V2”, leverages a previously published Bayesian hierarchical model framework with opportunistic (hunter-harvest) wildlife surveillance disease testing data and publicly available geospatial (raster) data to estimate the geographical risk that a hunter will harvest a white-tailed deer (Odocoileus virginianus) that tests positive for chronic wasting disease (CWD) in a small “study area” portion of the state. The three-part R scripts of Habitat Risk V2: 1) prepare the surveillance (testing) and geospatial (raster) data for model inclusion, 2) parameterize and estimate coefficient values for twenty five predetermined candidate model structures (Table 1), 3) select the model structure with the lowest Deviance Information Criterion (DIC) given the data, 4) gather diagnostic plots for the user to verify modeling assumptions have been met, and then 5) display the results of the best model in geographical and tabular context via an interactive user interface (UI). UI capabilities include interactive and downloadable maps of estimated risk (and associated error), a map of disease data overlaid onto spatial covariates, and detailed statistical information about the best model and the model selection process. The three R scripts must be run in sequence, as the data outputs of one become the data inputs of the next. The Habitat Risk V2 requires testing data in the state of interest to 1) contain locations of each deer in exact latitude/longitude coordinates, and 2) contain least one record that is CWD positive for each age/sex segment (adult male, adult female, yearling male, yearling female, fawn male, fawn female). The software will not work on datasets containing all CWD negative deer. We packaged Habitat Risk V2 using examples from Tennessee and New York. This packet does not furnish the real disease testing data necessary to run Habitat Risk V2. The Habitat Risk V2 software is adaptable for use in other areas with positive CWD samples. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the United States Government.
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    Surveillance Optimization Project for Chronic Wasting Disease dataset for Ohio, US, 2019-2021
    Ohio Department of Natural Resources, Division of Wildlife (2023-05-09)
    This dataset contains one file containing data from the Ohio Department of Natural Resources, Division of Wildlife shared with the Cornell Wildlife Health Lab (CWHL) at Cornell University for the purpose of the Surveillance Optimization Project for Chronic Wasting Disease (SOP4CWD). Professionals at the source facility have provided written permission for professionals at the CWHL to post this open data to this persistent eCommons repository. OHDNR_WTD_surveillance_2021.csv This datafile constitutes records in standardized form depicting the results of chronic wasting disease (CWD) testing of white-tailed deer (Odocoileus virginianus) in Ohio, US for hunting seasons from 2018-19 to 2020-21, as completed by wildlife health diagnosticians at (or in partnership with) the Ohio Department of Natural Resources, Division of Wildlife.
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    Data from: Recombinant production of a diffusible signal factor inhibits Salmonella invasion and animal carriage
    Rather, Mudasir Ali; Chowdhury, Rimi; Bitar, Paulina Pavinski; Altier, Craig (2023)
    These files contain data along with associated output from instrumentation supporting all results reported in Rather, et al. In Rather, et al., we found: The complex chemical environment of the intestine is defined largely by the metabolic products of the resident microbiota. Enteric pathogens, elegantly evolved to thrive in the gut, use these chemical products as signals to recognize specific niches and to promote their survival and virulence. Our previous work has shown that a specific class of quorum-sensing molecules found within the gut, termed diffusible signal factors (DSF), signals the repression of Salmonella tissue invasion, thus defining a means by which this pathogen recognizes its location and modulates virulence to optimize its survival. Here we determined whether the recombinant production of a DSF could reduce Salmonella virulence in vitro and in vivo. We found that the most potent repressor of Salmonella invasion, cis-2-hexadecenoic acid (c2-HDA), could be recombinantly produced in E. coli by the addition of a single exogenous gene encoding a fatty acid enoyl-CoA dehydratase/thioesterase, and that co-culture of the recombinant strain with Salmonella potently inhibited tissue invasion by repressing Salmonella genes required for this essential virulence function. Using the well characterized E. coli Nissle 1917 strain and a chicken infection model, we found that the recombinant DSF-producing strain could be stably maintained in the large intestine. Further, challenge studies demonstrated that this recombinant organism could significantly reduce Salmonella colonization of the cecum, the site of carriage in this animal species. These findings thus describe a plausible means by which Salmonella virulence may be affected in animals by in situ chemical manipulation of functions essential for colonization and virulence.
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    Surveillance Optimization Project for Chronic Wasting Disease dataset for Wisconsin, US, 1999-2021
    Wisconsin Department of Natural Resources (2023-03-28)
    This dataset contains five files containing data from the Wisconsin Department of Natural Resources shared with the Cornell Wildlife Health Lab (CWHL) at Cornell University for the purpose of the Surveillance Optimization Project for Chronic Wasting Disease (SOP4CWD). Professionals at the source facility have provided written permission for professionals at the CWHL to post this open data to this persistent eCommons repository. WIDNR_WTD_surveillance_2021.csv: This datafile constitutes records in standardized form depicting the results of chronic wasting disease (CWD) testing of white-tailed deer (Odocoileus virginianus) in Wisconsin, US for hunting seasons from 1999-2000 to 2020-21, as completed by wildlife health diagnosticians at (or in partnership with) the Wisconsin Department of Natural Resources. WIDNR_WTD_harvest_2020.csv: This datafile constitutes the total number of white-tailed deer (Odocoileus virginianus) legally harvested by hunters by county in Wisconsin, US for hunting seasons from 2014-15 to 2019-20, as recorded by the Wisconsin Department of Natural Resources. WIDNR_WTD_density_2020.csv: This datafile constitutes the density of white-tailed deer (Odocoileus virginianus) by county in Wisconsin, US at the beginning of the 2019-20 hunting season, as recorded by the Wisconsin Department of Natural Resources. WIDNR_processors_2021.csv: This datafile constitutes the total number wild cervid meat processors and taxidermists by county in Wisconsin, US for the year 2021, as recorded by the Wisconsin Department of Natural Resources. WIDNR_cervid_facilities_2021.csv: This datafile constitutes the total number of captive cervid facilities by county in Wisconsin, US for the year 2021, as recorded by the Wisconsin Department of Natural Resources.
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    Surveillance Optimization Project for Chronic Wasting Disease dataset for Tennessee, US, 2015-2021
    Tennessee Wildlife Resources Agency (2023-03-28)
    This dataset contains four files containing data from the Tennessee Wildlife Resources Agency shared with the Cornell Wildlife Health Lab (CWHL) at Cornell University for the purpose of the Surveillance Optimization Project for Chronic Wasting Disease (SOP4CWD). Professionals at the source facility have provided written permission for professionals at the CWHL to post this open data to this persistent eCommons repository. TWRA_WTD_surveillance_2021.csv: This datafile constitutes records in standardized form depicting the results of chronic wasting disease (CWD) testing of white-tailed deer (Odocoileus virginianus) in Tennessee, US for hunting seasons from 2015-16 to 2020-21, as completed by wildlife health diagnosticians at (or in partnership with) the Tennessee Wildlife Resources Agency. TWRA_WTD_harvest_2020.csv: This datafile constitutes the total number of white-tailed deer (Odocoileus virginianus) legally harvested by hunters by county in Tennessee, US for the 2019-20 hunting season, as recorded by the Tennessee Wildlife Resources Agency. TWRA_processors_2022.csv: This datafile constitutes the total number wild cervid meat processors and taxidermists by county in Tennessee, US for hunting seasons from 2018-19 to 2021-22, as recorded by the Tennessee Wildlife Resources Agency. TWRA_cervid_facilities_2021.csv: This datafile constitutes the total number of captive cervid facilities by county in Tennessee, US for the year 2021, as recorded by the Tennessee Wildlife Resources Agency.
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    Surveillance Optimization Project for Chronic Wasting Disease dataset for Ontario, Canada, 2017-2020
    Ontario Ministry of Natural Resources and Forestry (2023-03-28)
    This dataset contains four files containing data from the Ontario Ministry of Natural Resources and Forestry shared with the Cornell Wildlife Health Lab (CWHL) at Cornell University for the purpose of the Surveillance Optimization Project for Chronic Wasting Disease (SOP4CWD). Professionals at the source facility have provided written permission for professionals at the CWHL to post this open data to this persistent eCommons repository. OMNRF_WTD_surveillance_2020.csv: This datafile constitutes records in standardized form depicting the results of chronic wasting disease (CWD) testing of white-tailed deer (Odocoileus virginianus) in Ontario, Canada for hunting seasons from 2017-18 to 2019-20, as completed by wildlife health diagnosticians at (or in partnership with) the Ontario Ministry of Natural Resources and Forestry. OMNRF_WTD_harvest_2020.csv: This data constitutes the estimated total number of white-tailed deer (Odocoileus virginianus) legally harvested by hunters by county in Ontario, Canada for hunting seasons from 2017-18 to 2019-20, as recorded by the Ontario Ministry of Natural Resources and Forestry. OMNRF_processors_2020.csv: This data constitutes the estimated total number taxidermists and cervid meat processors by county in Ontario, Canada for hunting season 2019-20, as recorded by the Ontario Ministry of Natural Resources and Forestry. OMNRF_cervid_facilities_2020.csv: This data constitutes the estimated total number of captive cervid facilities by county in Ontario, Canada for the year 2020, as recorded by the Ontario Ministry of Natural Resources and Forestry.