Number of amyloid formations in negative control runs.

CWD-negative control obex, retropharyngeal lymph node (RPLN), recto-anal mucosal-associated lymphatic tissue (RAMALT), sclera, and ear tissue were tested numerous times. Each data represents the number of replicates (out of eight) in a RT-QuIC run that indicated amyloid formation and their respective time to thresholds (h) in parentheses. The average time to thresholds in all negative tissues exceed average time to thresholds of their CWD-positive counterparts. Ear skin had the highest number of replicates turn on, although the average number of amyloid formation incidents was 0.12 (below 1/8). (TIF)</p

Assay results from white-tailed deer.

Assay results from white-tailed deer.</p

endptdat

Part 2 - data for multinomial partitioning when an end point occurs with prior prediction probabilities to account for uncertainty, data are pipe delimited

Number of replicates that indicated amyloid formation for all available tissues of 30 collared white-tailed deer.

Obex, retropharyngeal lymph node (RPLN), recto-anal mucosal-associated lymphatic tissue (RAMALT), sclera, ear, and belly skin tissue were analyzed with RT-QuIC in technical replicates of eight. (TIF)</p

Disagreement between postmortem immunohistochemistry (IHC) and real-time quaking-induced conversion (RT-QuIC) results.

Disagreement between postmortem immunohistochemistry (IHC) and real-time quaking-induced conversion (RT-QuIC) results.</p

Median time to threshold of 20 white-tailed deer ears and belly skin samples determined to be CWD-positive by the real-time quaking-induced conversion (RT-QuIC) assay.

Time to threshold was determined by the time at which fluorescent signal reaches 10× the standard deviation of the threshold (defined by the average of fluorescent readings of cycles 3–13). The median values correspond with the real-time quaking-induced conversion (RT-QuIC) assay results from Fig 1(A) and 1(B). (TIF)</p

Spearman rank correlation coefficients between tissues.

Coefficients highlighted in blue indicate statistically significant (p (TIF)</p

Real-time quaking-induced conversion (RT-QuIC) analysis of ear and belly skin tissue sampled from CWD-positive white-tailed deer.

Box plots indicate the median with a horizontal red line, second and third quartiles with the box, and first and fourth quartiles with the whiskers. Statistical outliers are indicated by red crosses. Controls are known CWD-positive and negative obex run at 10−3 dilutions. The horizontal black line at 40 h indicates the end time of the assay. (A) Ear time to threshold results from samples at dilutions of 10−2. (B) Belly skin results from tissue samples at 10−2 dilutions.</p

Data_Sheet_1_A call to action: Standardizing white-tailed deer harvest data in the Midwestern United States and implications for quantitative analysis and disease management.pdf

Recreational hunting has been the dominant game management and conservation mechanism in the United States for the past century. However, there are numerous modern-day issues that reduce the viability and efficacy of hunting-based management, such as fewer hunters, overabundant wildlife populations, limited access, and emerging infectious diseases in wildlife. Quantifying the drivers of recreational harvest by hunters could inform potential management actions to address these issues, but this is seldom comprehensively accomplished because data collection practices limit some analytical applications (e.g., differing spatial scales of harvest regulations and harvest data). Additionally, managing large-scale issues, such as infectious diseases, requires collaborations across management agencies, which is challenging or impossible if data are not standardized. Here we discuss modern issues with the prevailing wildlife management framework in the United States from an analytical point of view with a case study of white-tailed deer (Odocoileus virginianus) in the Midwest. We have four aims: (1) describe the interrelated processes that comprise hunting and suggest improvements to current data collections systems, (2) summarize data collection systems employed by state wildlife management agencies in the Midwestern United States and discuss potential for large-scale data standardization, (3) assess how aims 1 and 2 influence managing infectious diseases in hunted wildlife, and (4) suggest actionable steps to help guide data collection standards and management practices. To achieve these goals, Wisconsin Department of Natural Resources disseminated a questionnaire to state wildlife agencies (Illinois, Indiana, Iowa, Kentucky, Michigan, Minnesota, Missouri, Ohio, Wisconsin), and we report and compare their harvest management structures, data collection practices, and responses to chronic wasting disease. We hope our “call to action” encourages re-evaluation, coordination, and improvement of harvest and management data collection practices with the goal of improving the analytical potential of these data. A deeper understanding of the strengths and deficiencies of our current management systems in relation to harvest and management data collection methods could benefit the future development of comprehensive and collaborative management and research initiatives (e.g., adaptive management) for wildlife and their diseases.</p

Highest dilution of detectable seeding activity of each ear sample location site of the seven CWD-positive deer.

Color saturations indicate the lowest detectable dilution where amyloid seeding activity was present in at least four of the eight technical replicates. None of the sites (Fig 2) were significantly different in lowest dilutions. (TIF)</p