The risk and control of Salmonella outbreaks in calf-raising operations: a mathematical modeling approach

Salmonellosis in calves has economic and welfare implications, and serves as a potential source of human infections. Our objectives were to assess the risk of Salmonella spread following its introduction into a herd of pre-weaned calves and to evaluate the efficacy of control strategies to prevent and control outbreaks. To meet these objectives, we developed a model of Salmonella transmission within a pre-weaned group of calves based on a well documented outbreak of salmonellosis in a calf-raising operation and other literature. Intervention scenarios were evaluated in both deterministic and stochastic versions of the model. While the basic reproduction number (R0) was estimated to be 2.4, simulation analysis showed that more than 60% of the invasions failed after the introduction of a single index case. With repeated introduction of index cases, the probability of Salmonella spread was close to 1, and the tested control strategies were insufficient to prevent transmission within the group. The most effective strategies to control ongoing outbreaks were to completely close the rearing operation to incoming calves, to increase the proportion of admitted calves that were immunized (\u3e75%), and to assign personnel and equipment to groups of calves

Zebrafish models in neuropsychopharmacology and CNS drug discovery

Despite the high prevalence of neuropsychiatric disorders, their aetiology and molecular mechanisms remain poorly understood. The zebrafish (Danio rerio) is increasingly utilized as a powerful animal model in neuropharmacology research and in vivo drug screening. Collectively, this makes zebrafish a useful tool for drug discovery and the identification of disordered molecular pathways. Here, we discuss zebrafish models of selected human neuropsychiatric disorders and drug-induced phenotypes. As well as covering a broad range of brain disorders (from anxiety and psychoses to neurodegeneration), we also summarize recent developments in zebrafish genetics and small molecule screening, which markedly enhance the disease modelling and the discovery of novel drug targets. © 2017 The British Pharmacological SocietyThe study was coordinated through the International Zebrafish Neuroscience Research Consortium (ZNRC), and this collaboration was funded by St. Petersburg State University, Ural Federal University and Guangdong Ocean University. A.V.K. is the Chair of ZNRC, and his research is supported by the Russian Foundation for Basic Research (RFBR) grant 16-04-00851

The Digital Road to Scientific Knowledge Diffusion; A Faster, Better Way to Scientific Progress?

With the United States federal government spending billions annually for research and development, ways to increase the productivity of that research can have a significant return on investment. The process by which science knowledge is spread is called diffusion. It is therefore important to better understand and measure the benefits of this diffusion of knowledge. In particular, it is important to understand whether advances in Internet searching can speed up the diffusion of scientific knowledge and accelerate scientific progress despite the fact that the vast majority of scientific information resources continue to be held in deep web databases that many search engines cannot fully access. To address the complexity of the search issue, the term global discovery is used for the act of searching across heterogeneous environments and distant communities. This article discusses these issues and describes research being conducted by the Office of Scientific and Technical Information (OSTI)

Linking disease epidemiology and livestock productivity: the case of bovine respiratory disease in France

Concerns are growing over the impact of livestock farming on environment and public health. The livestock industry is faced with the double constraint of limiting its use of natural resources and antimicrobials while ensuring its economic sustainability. In this context, reliable methods are needed to evaluate the effect of the prevention of endemic animal diseases on the productivity of livestock production systems. In this study, an epidemiological and productivity model was used to link changes in Bovine Respiratory Disease (BRD) incidence with the productivity of the beef and dairy cattle sectors in France. Cattle production parameters significantly affected by BRD were selected through literature review. Previous field study results and national cattle performance estimates were used to infer growth performances, mortality rates and carcass quality in the cattle affected and not affected by BRD. A steady-state deterministic herd production model was used to predict the productivity of the dairy and beef sector and their defined compartments (breeding-fattening, feedlot young bulls, and feedlot veal) in case of BRD incidence reduction by 20%, 50% or 100%. Results suggested that BRD should be controlled at a priority in beef breeding farms as eradication of BRD in beef calves would increase the whole beef sector’s productivity by 4.7–5.5% while eradication in other production stages would result in lower productivity gain in their respective sectors. However, the analysis performed at compartment level showed that, in both the beef and dairy sector, young bull and veal feedlot enterprises derive more economic benefits from BRD eradication for their own compartment (increase in productivity of 8.7–12.8% for beef young bulls) than the breeding farms (increase in productivity of 5.1–6% for beef calves), which may limit the investments in BRD control

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

An investigation of the effects of lipid-lowering medications: genome-wide linkage analysis of lipids in the HyperGEN study

BACKGROUND: Use of anti-hyperlipidemic medications compromises genetic analysis because of altered lipid profiles. We propose an empirical method to adjust lipid levels for medication effects so that the adjusted lipid values substitute the unmedicated lipid values in the genetic analysis. RESULTS: Published clinical trials were reviewed for HMG-CoA reductase inhibitors and fibric acid derivatives as mono-drug therapy. HMG-CoA reductase inhibitors showed similar effects in African Americans (AA) and non-African Americans (non-AA) for lowering total cholesterol (TC, -50.7 mg/dl), LDL cholesterol (LDL-C, -48.1 mg/dl), and triglycerides (TG, -19.7 mg/dl). Their effect on increasing HDL cholesterol (HDL-C) in AA (+0.4 mg/dl) was lower than in Non-AA (+2.3 mg/dl). The effects of fibric acid derivatives were estimated as -46.1 mg/dl for TC, -40.1 mg/dl for LDL-C, and +5.9 mg/dl for HDL-C in non-AA. The corresponding effects in AA were less extreme (-20.1 mg/dl, -11.4 mg/dl, and +3.1 mg/dl). Similar effect for TG (59.0 mg/dl) was shown in AA and non-AA. The above estimated effects were applied to a multipoint variance components linkage analysis on the lipid levels in 2,403 Whites and 2,214 AA in the HyperGEN study. The familial effects did vary depending on whether the lipids were adjusted for medication use. For example, the heritabilities increased after medication adjustment for TC and LDL-C, but did not change significantly for HDL-C and TG. CONCLUSION: Ethnicity-specific medication adjustments using our empirical method can be employed in epidemiological and genetic analysis of lipids.National Heart, Lung, and Blood Institute (HL554471, HL54472, HL54473, HL54495, HL54496, HL54497, HL54509, HL54515

Epitaxial Growth and Processing of Compound Semiconductors

Contains an introduction and reports on six research projects.Defense Advanced Research Projects Agency/U.S. Navy - Office of Naval Research University Research Initiative Subcontract N00014-92-J-1893Joint Services Electronics Program Grant DAAH04-95-1-0038National Center for Integrated Photonics Technology Contract 542-381National Science Foundation Grant DMR 92-02957MIT Lincoln Laboratory Contract BX-6085National Center for Integrated Photonics Technology Subcontract 542-383U.S. Air Force - Office of Scientific Research Grant F49620-96-1-0126U.S. Navy - Office of Naval Research Grant N00014-91-J-1956National Science Foundation Grant DMR 94-0033

A classification system for argumentation schemes

This paper explains the importance of classifying argumentation schemes, and outlines how schemes are being used in current research in artificial intelligence and computational linguistics on argument mining. It provides a survey of the literature on scheme classification. What are so far generally taken to represent a set of the most widely useful defeasible argumentation schemes are surveyed and explained systematically, including some that are difficult to classify. A new classification system covering these centrally important schemes is built