Adjustment of sex allocation to co-foundress number and kinship under local mate competition : an inclusive-fitness analysis

AG is supported by a Natural Environment Research Council Independent Research Fellowship (NE/K009524/1) and a European Research Council Consolidator Grant (771387).Hamilton’s theory of local mate competition (LMC) describes how competition between male relatives for mating opportunities favours a female‐biased parental investment. LMC theory has been extended in many ways to explore a range of genetic and life‐history influences on sex allocation strategies, including showing that increasing genetic homogeneity within mating groups should favour greater female bias. However, there has been no quantitative theoretical prediction as to how females should facultatively adjust their sex allocation in response to co‐foundress number and kinship. This shortfall has been highlighted recently by the finding that sex ratios produced by sub‐social parasitoid wasps in the family Bethylidae are affected by the number of co‐foundresses and by whether these are sisters or unrelated females. Here we close this gap in LMC theory by taking an inclusive‐fitness approach to derive explicit theoretical predictions for this scenario. We find that, in line with the recent empirical results, females should adopt a more female‐biased sex allocation when their co‐foundresses are less numerous and are their sisters. Our model appears to predict somewhat more female bias than is observed empirically; we discuss a number of possible model extensions that would improve realism and that would be expected to result in a closer quantitative fit with experimental data.Publisher PDFPeer reviewe

Improving coordination through information continuity: a framework for translational research

BACKGROUND There is good evidence that coordination can have beneficial impacts on patient care and outcomes but the mechanisms by which coordination is to be achieved are poorly understood and rarely identified in relevant policies. One approach suggests that continuity of information is a key element but research is yet to provide guidance on how to optimise coordination through improving continuity in healthcare settings. DISCUSSION In this paper we report on the development of a conceptual framework of information continuity in care coordination. We drew on evidence from systematic reviews of coordination and empirical studies on information use in integrated care models to develop the framework. It identifies the architecture, processes and scope of practices that evidence suggests is required to support information continuity in a population based approach to care coordination. The framework offers value to policy makers and practitioners as a map that identifies the multi-level elements of an integrated system capable of driving better coordination. Testing of the framework in different settings could aid our understanding of information continuity as a mechanism for linking coordination strategies that operate at different levels of the health system and enable synthesis of findings for informing policy and practice.This study was supported by a grant from the Ian Potter Foundation to the Menzies Centre for Health Policy. The Australian Primary Health Care Research Institute is supported by a grant from the Australian Government Department of Health and Ageing

Management factors associated with seropositivity to Lawsonia intracellularis in US swine herds.

abstract: This study was conducted to determine risk factors for Lawsonia intracellularis seropositivity in the breeding and grower-finisher units of US farrowing-to-finishing swine herds. Serum was collected from 15 breeding females and 15 grower-finisher pigs per herd in 184 farrow-to-finish herds, a subset of 405 herds in the National Animal Health Monitoring System (NAHMS) Swine 1995 Study that examined management, health and productivity in herds with at least 300 finisher pigs. Sera were tested by indirect fluorescent antibody test for L. intracellularis. Test results were linked with NAHMS questionnaire data and a logistic regression model of management factors associated with L. intracellularis serological status was developed. Separate models were used for breeding and grower-finisher units. Risk factors for seropositive breeding units were L intracellularis-seropositive status of the grower-finisher unit, use of a continuous system of management for the farrowing unit and a young parity structure (<75% multiparous sows). Risk factors for seropositive grower-finisher units were L. intracellularis-seropositive status of the breeding unit, the number of pigs entering the grower-finisher stage, raising pigs on concrete slats, and intensive management compared with raising pigs on outdoor lots. Use of all in-all out management in the farrowing house and an older parity structure in the sow herd were associated with a lower risk of L. intracellularis seropositivity in the breeding unit, and slatted concrete flooring in grower-finisher houses was associated with a greater risk. Alteration of these management factors might improve control of L. intracellularis infection in farrowing-to-finishing herds

Farm-level returns and costs of yellow catfish (Pelteobagrus fulvidraco) aquaculture in Guangdong and Zhejiang provinces, China

AbstractFreshwater aquaculture in China is expanding and intensifying as this country experiences rapid economic growth, and understanding farm-level profitability is necessary if farmers are to make reasonable decisions about their production plans. We conducted a survey of yellow catfish farmers in 2014 in Guangdong and Zhejiang provinces in order to estimate farm-level profitability of pond aquaculture. We selected representative prefectures from the 2 provinces as study areas and used convenience sampling. Eighty-seven farmers were interviewed between April and May 2014 and the questionnaire collected detailed information on: (1) farmers’ demographics (age, gender, education, training, and experience); (2) production inputs (land, labor, fingerlings, feed, chemicals, machinery, and other miscellaneous costs); and (3) outputs (weight and revenue of harvested fish). Responses of 61 farmers included in the data analysis were post-stratified into 3 categories of farm size (<1.47ha, 1.47–3.67ha, and >3.67ha). We calculated production cost components, returns, and returns-costs ratios by farm size in each province. The overall returns-costs ratio was 1.31 in Guangdong and 1.17 in Zhejiang. Farmers in Guangdong invested more in land and machinery and had higher percentages of labor costs and chemical expenditures, but achieved better returns-costs ratios than farmers in Zhejiang. Higher land rent might be associated with greater yields of yellow catfish in Guangdong, which were almost twice those of Zhejiang

Comparison of machine learning algorithms for the prediction of five-year survival in oral squamous cell carcinoma

BACKGROUND/AIM Machine learning analyses of cancer outcomes for oral cancer remain sparse compared to other types of cancer like breast or lung. The purpose of the present study was to compare the performance of machine learning algorithms in the prediction of global, recurrence-free five-year survival in oral cancer patients based on clinical and histopathological data.METHODS Data were gathered retrospectively from 416 patients with oral squamous cell carcinoma. The data set was divided into training and test data set (75:25 split). Training performance of five machine learning algorithms (Logistic regression, K-nearest neighbours, Naïve Bayes, Decision tree and Random forest classifiers) for prediction was assessed by k-fold cross-validation. Variables used in the machine learning models were age, sex, pain symptoms, grade of lesion, lymphovascular invasion, extracapsular extension, perineural invasion, bone invasion and type of treatment. Variable importance was assessed and model performance on the testing data was assessed using receiver operating characteristic curves, accuracy, sensitivity, specificity and F1 score.RESULTS The best performing model was the Decision tree classifier, followed by the Logistic Regression model (accuracy 76% and 60%, respectively). The Naïve Bayes model did not display any predictive value with 0% specificity.CONCLUSIONS Machine learning presents a promising and accessible toolset for improving prediction of oral cancer outcomes. Our findings add to a growing body of evidence that Decision tree models are useful in models in predicting OSCC outcomes. We would advise that future similar studies explore a variety of machine learning models including Logistic regression to help evaluate model performance.</p

Seasonal variation and impact of waste-water lagoons as larval habitat on the population dynamics of Culicoides sonorensis (Diptera:Ceratpogonidae) at two dairy farms in northern California.

The Sacramento (northern Central) Valley of California (CA) has a hot Mediterranean climate and a diverse ecological landscape that is impacted extensively by human activities, which include the intensive farming of crops and livestock. Waste-water ponds, marshes, and irrigated fields associated with these agricultural activities provide abundant larval habitats for C. sonorensis midges, in addition to those sites that exist in the natural environment. Within this region, C. sonorensis is an important vector of bluetongue (BTV) and related viruses that adversely affect the international trade and movement of livestock, the economics of livestock production, and animal welfare. To characterize the seasonal dynamics of immature and adult C. sonorensis populations, abundance was monitored intensively on two dairy farms in the Sacramento Valley from August 2012- to July 2013. Adults were sampled every two weeks for 52 weeks by trapping (CDC style traps without light and baited with dry-ice) along N-S and E-W transects on each farm. One farm had large operational waste-water lagoons, whereas the lagoon on the other farm was drained and remained dry during the study. Spring emergence and seasonal abundance of adult C. sonorensis on both farms coincided with rising vernal temperature. Paradoxically, the abundance of midges on the farm without a functioning waste-water lagoon was increased as compared to abundance on the farm with a waste-water lagoon system, indicating that this infrastructure may not serve as the sole, or even the primary larval habitat. Adult midges disappeared from both farms from late November until May; however, low numbers of parous female midges were detected in traps set during daylight in the inter-seasonal winter period. This latter finding is especially critical as it provides a potential mechanism for the "overwintering" of BTV in temperate regions such as northern CA. Precise documentation of temporal changes in the annual abundance and dispersal of Culicoides midges is essential for the creation of models to predict BTV infection of livestock and to develop sound abatement strategies

New insights into the reliability of automatic dynamic methods for oral bioaccessibility testing: a case study for BGS102 soil

Dynamic flow-through extraction is attracting a great deal of attention for real-time monitoring of the bioaccessible fraction of metal species in environmental solid substrates compared to its batchwise manual counterparts. There is however a lack of studies on the harmonization and validation of in vitro dynamic methods for physiologically based extraction tests against in vivo bioavailability methods. This work is aimed at evaluating the reliability of dynamic flow-through extraction methods for estimation of oral bioaccessible fractions of Cu, Zn, Pb, Ni, Cr, and As under worst-case extraction conditions in the gastric compartment based on the BGS102 guidance soil using the in vivo validated Unified BARGE (UBM) test, commonly performed under batchwise mode. Good overall agreement between batch and dynamic UBM results was obtained for the tested elements, except for Pb, as a consequence of the slow leaching kinetics identified with the dynamic method and the contribution of readsorption phenomena in the course of the gastric digestion. Metal-soil phase associations and their relationship with gastric bioaccessible fractions were elucidated using the so-called Chemometric Identification of Substrates and Element Distributions method based on sequential extraction with a variety of chemicals of increasing acidity as applied to both static and dynamic bioaccessibility data