Evaluation of predictive models to determine total morbidity outcome of feedlot cattle based on cohort-level feed delivery data during the first 15 days on feed.

Changes in feeding behavior and intake have been used to predict the onset of bovine respiratory disease in individual animals but have not been applied to cohort-level data. Correctly identifying high morbidity cohorts of cattle early in the feeding period could facilitate the administration of interventions to improve health and economic outcomes. The study objective was to determine the ability of feed delivery data from the first 15 days of feed to predict total feeding period morbidity. Data consisted of 518 cohorts (10 feedlots, 56,796 animals) of cattle of varying sex, age, arrival weight, and arrival time of year over a 2-year period. Overall cohort-level morbidity was classified into high (≥15% total morbidity) or low categories with 18.5% of cohorts having high morbidity. Five predictive models (advanced perceptron, decision forest, logistic regression, neural network, and boosted decision tree) were created to predict overall morbidity given cattle characteristics at arrival and feeding characteristics from the first 15 days. The dataset was split into training and testing subsets (75% and 25% of original, respectively), stratified by the outcome of interest. Predictive models were generated in Microsoft Azure using the training set and overall predictive performance was evaluated using the testing set. Performance in the testing set (n = 130) was measured based on final accuracy, sensitivity (Sn, the ability to accurately detect high morbidity cohorts), and specificity (Sp, the ability to accurately detect low morbidity cohorts). The decision forest had the highest Sp (97%) with the greatest ability to accurately identify low morbidity lots (103 of 106 identified correctly), but this model had low Sn (33%). The logistic regression and neural network had similar Sn (both 63%) and Sp (69% and 72%, respectively) with the best ability to correctly identify high morbidity cohorts (15 of 24 correctly identified). Predictor variables with the greatest importance in the predictive models included percent change in feed delivery between days and 4-day moving averages. The most frequent variable with a high level of importance among models was the percent change in feed delivered from d 2 to 3 after arrival. In conclusion, feed delivery data during the first 15 days on feed was a significant predictor of total cohort-level morbidity over the entire feeding period with changes in feed delivery providing important information.

Dynamical Defects in Rotating Magnetic Skyrmion Lattices.

The chiral magnet Cu_{2}OSeO_{3} hosts a Skyrmion lattice that may be equivalently described as a superposition of plane waves or a lattice of particlelike topological objects. A thermal gradient may break up the Skyrmion lattice and induce rotating domains, raising the question of which of these scenarios better describes the violent dynamics at the domain boundaries. Here, we show that in an inhomogeneous temperature gradient caused by illumination in a Lorentz transmission electron microscope different parts of the Skyrmion lattice can be set into motion with different angular velocities. Tracking the time dependence, we show that the constant rearrangement of domain walls is governed by dynamic 5-7 defects arranging into lines. An analysis of the associated defect density is described by Frank's equation and agrees well with classical 2D Monte Carlo simulations. Fluctuations of boundaries show a surgelike rearrangement of Skyrmion clusters driven by defect rearrangement consistent with simulations treating Skyrmions as point particles. Our findings underline the particle character of the Skyrmion.

Temporal control of i-motif switch lifetimes for autonomous operation of transient DNA nanostructures.

Functional DNA nanotechnology creates increasingly complex behaviors useful for sensing, actuation or computation, as enabled via the integration of dynamic and responsive structural DNA motifs. However, temporally controlled and dynamic DNA structures with programmable lifetimes, that are able to operate autonomously and self-revert to the starting state are challenging to achieve due to tedious and very system-specific sequence design. Here, we present a straightforward concept to program transient lifetimes into DNA duplexes based on the pH-sensitive DNA i-motif switch. We integrate the i-motif switch with an internal, non-linear pH-resetting function using a rationally designed chemical reaction framework, by which the switch autonomously undergoes a complete "off-on-off"-cycle without the use of additional external triggers. The lifetime of the activated "on"-state (i.e. the hybridized state) can be systematically programmed over several hours. The system can be readily implemented into hybrid DNA structures on larger length scales. Focusing on autonomous materials, we demonstrate temporal control of transient fluorescence signals and temporary aggregation of gold nanoparticles.

The tomato Mi-1 gene confers resistance to both root-knot nematodes and potato aphids.

Mi-1, a Lycopersicon peruvianum gene conferring resistance to the agricultural pests, root-knot nematodes, and introgressed into tomato, has been cloned using a selective restriction fragment amplification based strategy. Complementation analysis of a susceptible tomato line with a 100 kb cosmid array yielded a single cosmid clone capable of conferring resistance both to the root-knot nematode Meloidogyne incognita and to an unrelated pathogen, the potato aphid Macrosiphum euphorbiae. This resistance was stable. The Mi-1 gene encodes a protein sharing structural features with the nucleotide-binding site leucine-rich repeat-containing type of plant resistance genes.

Performance reporting of health care delivery systems: will it make the grade?

Recently, federal governments, state governments, and private sector groups have begun initiatives that would report the performance of health plans in key areas. United HealthCare Corporation's experience in developing and publicly releasing "report cards" for 15 of its health plans may prove useful as other efforts go forward. There are both advantages and challenges to producing a report card in terms of resource investment, directing health plans toward performance improvement, and the ability for both purchasers and policy makers to understand and make use of results. These and other issues will be important to consider as other segments of the health care industry, particularly providers, focus on reporting performance measures.

Quality screening and management using claims data in a managed care setting.

Quality screening and management (QSM), developed by United HealthCare Corporation for its own health plans but applicable to other settings, analyzes health care provided to an enrolled population using claims and administrative data supplemented, when necessary, with medical record review. For selected topics/conditions, QSM compares the care received by patients to that recommended by established practice guidelines and also reports and describes quality through incidence rates, condition-specific process and outcome measures, occurrence of adverse events, and use of preventive services. Results of the analyses are linked to appropriate quality management actions and are used to identify strategies for improvement. Data permit health plans to make performance comparisons on individual indicators and longitudinal comparisons on the effectiveness of quality improvement initiatives.

Findings from the Medicaid Competition Demonstrations: a guide for states.

The Medicaid Competition Demonstrations were initiated in 1983-84 in six States (California, Florida, Minnesota, Missouri, New Jersey, and New York). State experiences in implementing the demonstrations are presented in this article. Although problems of enrolling Medicaid recipients in prepaid plans or with primary care case managers under these demonstrations proved challenging to States, lessons were learned in three key areas: program design and administration, health plan and provider relations, and beneficiary acceptance. Therefore, States considering similar programs in the future could benefit from these findings.