360 research outputs found

    Evaluation of thermal pattern distributions in racehorse saddles using infrared thermography

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    The impact of a rider’s and saddle’s mass on saddle thermal pattern distribution was evalu ated using infrared thermography (IRT). Eighteen racehorses were ridden by four riders with their own saddle. Images of the saddle panels were captured at each of six thermographic examinations. On each image, six regions of interest (ROIs) were marked on the saddle panels. The mean temperature for each ROI was extracted. To evaluate the influence of load on saddle fit, 4 indicators were used: ΔTmax (difference between the mean temperature of the warmest and coolest ROI); standard deviation of the mean temperature of the six ROIs; right/left; bridging/rocking and front/back thermal pattern indicator. Incorrect saddle fit was found in 25 measurements (23.1%) with ΔTmax greater than 2˚C. The relationships between rider and saddle fit as well as saddle fit and horse were significant (p<0.001). An average ΔTmax in rider A was significantly higher than in other riders (p<0.001). The right/left thermal pattern differed significantly from the optimal value for riders A and B; while the bridging/rocking thermal pattern differed significantly from this value for riders A, C and D (p<0.05). Front saddle thermal pattern was most frequent for rider A (41.5%), whereas back saddle thermal pattern was most frequent for rider C (85.7%). Measurement of the mean temperature in 6 ROIs on saddle panels after training was helpful in assessing the influence of rider and saddle mass on saddle fit. IRT offered a non-invasive, rapid and simple method for assessing load on thermal pattern distribution in race saddles.info:eu-repo/semantics/publishedVersio

    Spatial partial identity model reveals low densities of leopard and spotted hyaena in a miombo woodland

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    Decline in global carnivore populations has led to increased demand for assessment of carnivore densities in understudied habitats. Spatial capture–recapture (SCR) is used increasingly to estimate species densities, where individuals are often identified from their unique pelage patterns. However, uncertainty in bilateral individual identification can lead to the omission of capture data and reduce the precision of results. The recent development of the two-flank spatial partial identity model (SPIM) offers a cost-effective approach, which can reduce uncertainty in individual identity assignment and provide robust density estimates. We conducted camera trap surveys annually between 2016 and 2018 in Kasungu National Park, Malawi, a primary miombo woodland and a habitat lacking baseline data on carnivore densities. We used SPIM to estimate density for leopard (Panthera pardus) and spotted hyaena (Crocuta crocuta) and compared estimates with conventional SCR methods. Density estimates were low across survey years, when compared to estimates from sub-Saharan Africa, for both leopard (1.9±0.19 sd adults/100km2) and spotted hyaena (1.15±0.42 sd adults/100km2). Estimates from SPIM improved precision compared with analytical alternatives. Lion (Panthera leo) and wild dog (Lycaon pictus) were absent from the 2016 survey, but lone dispersers were recorded in 2017 and 2018, and both species appear limited to transient individuals from within the wider transfrontier conservation area. Low densities may reflect low carrying capacity in miombo woodlands or be a result of reduced prey availability from intensive poaching. We provide the first leopard density estimates from Malawi and a miombo woodland habitat, whilst demonstrating that SPIM is beneficial for density estimation in surveys where only one camera trap per location is deployed. The low density of large carnivores requires urgent management to reduce the loss of the carnivore guild in Kasungu National Park and across the wider transfrontier landscape

    Peak positions and shapes in neutron pair correlation functions from powders of highly anisotropic crystals

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    The effect of the powder average on the peak shapes and positions in neutron pair distribution functions of polycrystalline materials is examined. It is shown that for highly anisotropic crystals, the powder average leads to shifts in peak positions and to non-Gaussian peak shapes. The peak shifts can be as large as several percent of the lattice spacing

    Fibrinogen, viscosity, and white blood cell count are major risk factors for ischemic heart disease. The Caerphilly and Speedwell collaborative heart disease studies.

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    BACKGROUND Recent studies have suggested that hemostatic factors and white blood cell count are predictive of ischemic heart disease (IHD). The relations of fibrinogen, viscosity, and white blood cell count to the incidence of IHD in the Caerphilly and Speedwell prospective studies are described. METHODS AND RESULTS The two studies have a common core protocol and are based on a combined cohort of 4,860 middle-aged men from the general population. The first follow-up was at a nearly constant interval of 5.1 years in Caerphilly and 3.2 years in Speedwell; 251 major IHD events had occurred. Age-adjusted relative odds of IHD for men in the top 20% of the distribution compared with the bottom 20% were 4.1 (95% confidence interval, 2.6-6.5) for fibrinogen, 4.5 (95% confidence interval, 2.8-7.4) for viscosity, and 3.2 (95% confidence interval, 2.0-4.9) for white blood cell count. Associations with IHD were similar in men who had never smoked, exsmokers, and current smokers, and the results suggest that at least part of the effect of smoking on IHD is mediated through fibrinogen, viscosity, and white blood cell count. Multivariate analysis shows that white blood cell count is an independent risk factor for IHD as is either fibrinogen or viscosity, or possibly both. Jointly, these three variables significantly improve the fit of a logistic regression model containing all the main conventional risk factors. Further, a model including age, smoking habits, fibrinogen, viscosity, and white blood cell count predicts IHD as well as one in which the three hemostatic/rheological variables are replaced by total cholesterol, diastolic pressure, and body mass index. CONCLUSION Jointly, fibrinogen, viscosity, and white blood cell count are important risk factors for IHD

    Dental microwear texture analysis of Homo sapiens sapiens: foragers, farmers, and pastoralists

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    Objectives. The current study seeks to determine if a sample of foragers, farmers, and pastoralists can be distinguished by their dental microwear texture signatures. Materials and Methods. The study included a sample of 719 individuals from 51 archaeological sites (450 farmers, 192 foragers, 77 pastoralists). All were over age 12 and sexes were pooled. Using a Sensofar® white-light confocal profiler we collected dental microwear texture analysis (DMTA) data from a single first or second molar from each individual. We leveled and cleaned data clouds following standard procedures and analyzed the data with Sfrax® and Toothfrax® software. The DMTA variables were complexity and anisotropy. Statistics included ANOVA with partial eta squared and Hedges's g. We also performed a follow-up K-means cluster analysis. Results. We found significant differences between foragers and farmers and pastoralists for complexity and anisotropy, with foragers having greater complexity than either the farmers or the pastoralists. The farmers and pastoralists had greater anisotropy than the foragers. The Old World foragers had significantly higher anisotropy values than New World foragers. Old and New World farmers did not differ. Among the Old World farmers, those dating from the Neolithic through the Late Bronze Age had higher complexity values than those from the Iron Age through the medieval period. The cluster analysis discerned foragers and farmers but also indicated similarity between hard food foragers and hard food farmers. Discussion. Our findings reaffirm that DMTA is capable of distinguishing human diets. We found that foragers and farmers, in particular, differ in their microwear signatures across the globe. There are some exceptions, but nothing that would be unexpected given the range of human diets and food preparation techniques. This study indicates that in general DMTA is an efficacious means of paleodietary reconstruction in humans

    The Association of C-Reactive Protein and CRP Genotype with Coronary Heart Disease: Findings from Five Studies with 4,610 Cases amongst 18,637 Participants

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    Background: It is unclear whether C-reactive protein (CRP) is causally related to coronary heart disease (CHD). Genetic variants that are known to be associated with CRP levels can be used to provide causal inference of the effect of CRP on CHD. Our objective was to examine the association between CRP genetic variant +1444C>T (rs1130864) and CHD risk in the largest study to date of this association.Methods and Results: We estimated the association of CRP genetic variant +1444C>T (rs1130864) with CRP levels and with CHD in five studies and then pooled these analyses (N= 18,637 participants amongst whom there were 4,610 cases). CRP was associated with potential confounding factors (socioeconomic position, physical activity, smoking and body mass) whereas genotype (rs1130864) was not associated with these confounders. The pooled odds ratio of CHD per doubling of circulating CRP level after adjustment for age and sex was 1.13 (95% CI: 1.06, 1.21), and after further adjustment for confounding factors it was 1.07 (95% CI: 1.02, 1.13). Genotype (rs1130864) was associated with circulating CRP; the pooled ratio of geometric means of CRP level among individuals with the TT genotype compared to those with the CT/CC genotype was 1.21 (95% CI: 1.15, 1.28) and the pooled ratio of geometric means of CRP level per additional T allele was 1.14 (95% CI: 1.11, 1.18), with no strong evidence in either analyses of between study heterogeneity (I-2 = 0%, p>0.9 for both analyses). There was no association of genotype (rs1130864) with CHD: pooled odds ratio 1.01 (95% CI: 0.88, 1.16) comparing individuals with TT genotype to those with CT/CC genotype and 0.96 (95% CI: 0.90, 1.03) per additional T allele (I-2<7.5%, p. 0.6 for both meta-analyses). An instrumental variables analysis (in which the proportion of CRP levels explained by rs1130864 was related to CHD) suggested that circulating CRP was not associated with CHD: the odds ratio for a doubling of CRP level was 1.04 (95% CI: 0.61, 1.80).Conclusions: We found no association of a genetic variant, which is known to be related to CRP levels, (rs1130864) and having CHD. These findings do not support a causal association between circulating CRP and CHD risk, but very large, extended, genetic association studies would be required to rule this out

    Systematically missing confounders in individual participant data meta-analysis of observational cohort studies.

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    One difficulty in performing meta-analyses of observational cohort studies is that the availability of confounders may vary between cohorts, so that some cohorts provide fully adjusted analyses while others only provide partially adjusted analyses. Commonly, analyses of the association between an exposure and disease either are restricted to cohorts with full confounder information, or use all cohorts but do not fully adjust for confounding. We propose using a bivariate random-effects meta-analysis model to use information from all available cohorts while still adjusting for all the potential confounders. Our method uses both the fully adjusted and the partially adjusted estimated effects in the cohorts with full confounder information, together with an estimate of their within-cohort correlation. The method is applied to estimate the association between fibrinogen level and coronary heart disease incidence using data from 154,012 participants in 31 cohort

    Effects of body size on estimation of mammalian area requirements.

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    Accurately quantifying species' area requirements is a prerequisite for effective area-based conservation. This typically involves collecting tracking data on species of interest and then conducting home range analyses. Problematically, autocorrelation in tracking data can result in space needs being severely underestimated. Based on the previous work, we hypothesized the magnitude of underestimation varies with body mass, a relationship that could have serious conservation implications. To evaluate this hypothesis for terrestrial mammals, we estimated home-range areas with global positioning system (GPS) locations from 757 individuals across 61 globally distributed mammalian species with body masses ranging from 0.4 to 4000 kg. We then applied blockcross validation to quantify bias in empirical home range estimates. Area requirements of mammals 1, meaning the scaling of the relationship changedsubstantially at the upper end of the mass spectrum

    New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk.

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    Levels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, fasting insulin and indices of beta-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 nondiabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with fasting glucose and HOMA-B and two loci associated with fasting insulin and HOMA-IR. These include nine loci newly associated with fasting glucose (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and C2CD4B) and one influencing fasting insulin and HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 with type 2 diabetes. Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify type 2 diabetes risk loci, as well as loci containing gene variants that are associated with a modest elevation in glucose levels but are not associated with overt diabetes

    Progressive Focal Gray Matter Volume Loss in a Former High School Football Player: A Possible Magnetic Resonance Imaging Volumetric Signature for Chronic Traumatic Encephalopathy

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    Here a case is presented of a 51-year-old former high school football player with multiple concussions, including one episode with loss of consciousness. The patient experienced 6 years of cognitive and mood decline, and his wife corroborated increasing memory loss, attentional difficulties, and depressed mood without suicidal ideation. He had been unable to maintain full-time employment because of progressive decline. Based on his presentation, he had been previously diagnosed with attention deficit hyperactivity disorder and bipolar disorder, type II. Neuropsychological tests indicated domain-specific cognitive impairment, and longitudinal volumetric magnetic resonance imaging (MRI) of the brain showed progressive brainstem, diencephalic, and frontal lobe atrophy. This regional volume loss correlated with the increased signal seen on tau and amyloid imaging (FDDNP-PET scan) of a separate case of suspected chronic traumatic encephalopathy (CTE). Visual assessment of the MRI also showed evidence of old petechial hemorrhages in the frontal and temporal-parietal lobe white matter. This case raises the possibility of distinct quantitative and visual brain MRI findings in suspected CTE
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