Calving Difficulty in Beef Cattle: Part I

Calving difficulty (dystocia) can increase calf losses, cow mortality, and veterinary and labor costs, as well as delay return to estrus, and lower conception rates. In two studies at the U.S. Meat Animal Research Center (MARC), Clay Center, Nebraska, calf losses within 24 hours of birth averaged 4 percent for those born with little or no assistance compared to 16 percent for those requiring assistance. Calf mortality increased by a 0.35 percent per pound increase in birth weight. In a Hereford herd at the U.S. Livestock and Range Research Station. Miles City, Montana, 57 percent of all calf losses were reported to be due to dystocia

Calving Difficulty in Beef Cattle: Part II

Many cattlemen believe reducing dietary energy during late pregnancy will decrease fetal size resulting in improved calving ease, whereas increasing energy will increase fetal size leading to a higher incidence of dystocia. Generally speaking, research has shown that lowering the energy allowance will decrease birth weight but will not significantly reduce dystocia. At MARC, Hereford and Angus 2-year-old heifers were fed three levels of energy (10.8, 13.7 or 17 .0 lb TDN/head/day) for 90 days prior to calving. Increasing the level of dietary energy resulted in increased birth weight but not increased dystocia; in fact, the incidence of calving difficulty was lower in the medium and high energy groups than in the low energy group

An application of conditional logistic regression and multifactor dimensionality reduction for detecting gene-gene Interactions on risk of myocardial infarction: The importance of model validation

BACKGROUND: To examine interactions among the angiotensin converting enzyme (ACE) insertion/deletion, plasminogen activator inhibitor-1 (PAI-1) 4G/5G, and tissue plasminogen activator (t-PA) insertion/deletion gene polymorphisms on risk of myocardial infarction using data from 343 matched case-control pairs from the Physicians Health Study. We examined the data using both conditional logistic regression and the multifactor dimensionality reduction (MDR) method. One advantage of the MDR method is that it provides an internal prediction error for validation. We summarize our use of this internal prediction error for model validation. RESULTS: The overall results for the two methods were consistent, with both suggesting an interaction between the ACE I/D and PAI-1 4G/5G polymorphisms. However, using ten-fold cross validation, the 46% prediction error for the final MDR model was not significantly lower than that expected by chance. CONCLUSIONS: The significant interaction initially observed does not validate and may represent a type I error. As data-driven analytic methods continue to be developed and used to examine complex genetic interactions, it will become increasingly important to stress model validation in order to ensure that significant effects represent true relationships rather than chance findings

How Safe is Our Product – Beef? Do We Have a Story to Tell?

Americans are vitally concerned about the safety of their food supply. Agriculture is likewise concerned about the safety of its products. In fact, the agricultural community agrees that, along with the environment, diet/health, and animal welfare, food safety is a major issue as we approach the 21st century. Confidence in our food supply was eroded by the alar/apples and cyanide/grapes calamities in February and March of 1989. As the Food Marketing Institute (FMI) survey data in Table 1 illustrate, public confidence in food safety, once shaken, is slow to rebuild

Feeding steers for show /

Fact sheet 5000- for beef manual.At head of title: Michigan beef production.Caption title.Mode of access: Internet.CARLI Last Copy Program

Swine buildings and equipment : a catalog of plans /

At head of title: Farming know-how, guidelines to better family farming.Caption title.Mode of access: Internet.CARLI Last Copy Program

Data from: Data sharing through an NIH central database repository: a cross-sectional survey of BioLINCC users

Objective To characterise experiences using clinical research data shared through the National Institutes of Health (NIH)'s Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC) clinical research data repository, along with data recipients’ perceptions of the value, importance and challenges with using BioLINCC data. Design and setting Cross-sectional web-based survey. Participants All investigators who requested and received access to clinical research data from BioLINCC between 2007 and 2014. Main outcome measures Reasons for BioLINCC data request, research project plans, interactions with original study investigators, BioLINCC experience and other project details. Results There were 536 investigators who requested and received access to clinical research data from BioLINCC between 2007 and 2014. Of 441 potential respondents, 195 completed the survey (response rate=44%); 89% (n=174) requested data for an independent study, 17% (n=33) for pilot/preliminary analysis. Commonly cited reasons for requesting data through BioLINCC were feasibility of collecting data of similar size and scope (n=122) and insufficient financial resources for primary data collection (n=76). For 95% of respondents (n=186), a primary research objective was to complete new research, as opposed to replicate prior analyses. Prior to requesting data from BioLINCC, 18% (n=36) of respondents had contacted the original study investigators to obtain data, whereas 24% (n=47) had done so to request collaboration. Nearly all (n=176; 90%) respondents found the data to be suitable for their proposed project; among those who found the data unsuitable (n=19; 10%), cited reasons were data too complicated to use (n=5) and data poorly organised (n=5). Half (n=98) of respondents had completed their proposed projects, of which 67% (n=66) have been published. Conclusions Investigators were primarily using clinical research data from BioLINCC for independent research, making use of data that would otherwise have not been feasible to collect

Dryad BioLINCC Survey Data 16-09-01

This is the deidentified data from the 2015 cross-sectional survey of investigators who requested and received access to clinical research data from BioLINCC between 2007 and 2014