Parasite infections in a social carnivore: Evidence of their fitness consequences and factors modulating infection load

There are substantial individual differences in parasite composition and infection load in wildlife populations. Few studies have investigated the factors shaping this heterogeneity in large wild mammals or the impact of parasite infections on Darwinian fitness, particularly in juveniles. A host's parasite composition and infection load can be shaped by factors that determine contact with infective parasite stages and those that determine the host's resistance to infection, such as abiotic and social environmental factors, and age. Host–parasite interactions and synergies between coinfecting parasites may also be important. We test predictions derived from these different processes to investigate factors shaping infection loads (fecal egg/oocyte load) of two energetically costly gastrointestinal parasites: the hookworm Ancylostoma and the intracellular Cystoisospora, in juvenile spotted hyenas (Crocuta crocuta) in the Serengeti National Park, in Tanzania. We also assess whether parasite infections curtail survival to adulthood and longevity. Ancylostoma and Cystoisospora infection loads declined as the number of adult clan members increased, a result consistent with an encounter‐reduction effect whereby adults reduced encounters between juveniles and infective larvae, but were not affected by the number of juveniles in a clan. Infection loads decreased with age, possibly because active immune responses to infection improved with age. Differences in parasite load between clans possibly indicate variation in abiotic environmental factors between clan den sites. The survival of juveniles (<365 days old) to adulthood decreased with Ancylostoma load, increased with age, and was modulated by maternal social status. High‐ranking individuals with low Ancylostoma loads had a higher survivorship during the first 4 years of life than high‐ranking individuals with high Ancylostoma loads. These findings suggest that high infection loads with energetically costly parasites such as hookworms during early life can have negative fitness consequences

Analysis of time-to-event for observational studies: Guidance to the use of intensity models

This paper provides guidance for researchers with some mathematical background on the conduct of time-to-event analysis in observational studies based on intensity (hazard) models. Discussions of basic concepts like time axis, event definition and censoring are given. Hazard models are introduced, with special emphasis on the Cox proportional hazards regression model. We provide check lists that may be useful both when fitting the model and assessing its goodness of fit and when interpreting the results. Special attention is paid to how to avoid problems with immortal time bias by introducing time-dependent covariates. We discuss prediction based on hazard models and difficulties when attempting to draw proper causal conclusions from such models. Finally, we present a series of examples where the methods and check lists are exemplified. Computational details and implementation using the freely available R software are documented in Supplementary Material. The paper was prepared as part of the STRATOS initiative.Comment: 28 pages, 12 figures. For associated Supplementary material, see http://publicifsv.sund.ku.dk/~pka/STRATOSTG8

Hepatic retransplantation in cholestatic liver disease: Impact of the interval to retransplantation on survival and resource utilization

The aim of our study was to quantitatively assess the impact of hepatic retransplantation on patient and graft survival and resource utilization. We studied patients undergoing hepatic retransplantation among 447 transplant recipients with primary biliary cirrhosis (PBC) and primary sclerosing cholangitis (PSC) at 3 transplantation centers. Cox proportional hazards regression analysis was used for survival analysis. Measures of resource utilization included the duration of hospitalization, length of stay in the intensive care unit, and the duration of transplantation surgery. Forty-six (10.3%) patients received 2 or more grafts during the follow-up period (median, 2.8 years). Patients who underwent retransplantation had a 3.8-fold increase in the risk of death compared with those without retransplantation (P < .01). Retransplantation after an interval of greater than 30 days from the primary graft was associated with a 6.7-fold increase in the risk of death (P < .01). The survival following retransplantations performed 30 days or earlier was similar to primary transplantations. Resource utilization was higher in patients who underwent multiple consecutive transplantations, even after adjustment for the number of grafts during the hospitalization. Among cholestatic liver disease patients, poor survival following hepatic retransplantation is attributed to late retransplantations, namely those performed more than 30 days after the initial transplantation. While efforts must be made to improve the outcome following retransplantation, a more critical evaluation may be warranted for late retransplantation candidates

Relation of vertebral deformities to bone density, structure, and strength.

Because they are not reliably discriminated by areal bone mineral density (aBMD) measurements, it is unclear whether minimal vertebral deformities represent early osteoporotic fractures. To address this, we compared 90 postmenopausal women with no deformity (controls) with 142 women with one or more semiquantitative grade 1 (mild) deformities and 51 women with any grade 2-3 (moderate/severe) deformities. aBMD was measured by dual-energy X-ray absorptiometry (DXA), lumbar spine volumetric bone mineral density (vBMD) and geometry by quantitative computed tomography (QCT), bone microstructure by high-resolution peripheral QCT at the radius (HRpQCT), and vertebral compressive strength and load-to-strength ratio by finite-element analysis (FEA) of lumbar spine QCT images. Compared with controls, women with grade 1 deformities had significantly worse values for many bone density, structure, and strength parameters, although deficits all were much worse for the women with grade 2-3 deformities. Likewise, these skeletal parameters were more strongly associated with moderate to severe than with mild deformities by age-adjusted logistic regression. Nonetheless, grade 1 vertebral deformities were significantly associated with four of the five main variable categories assessed: bone density (lumbar spine vBMD), bone geometry (vertebral apparent cortical thickness), bone strength (overall vertebral compressive strength by FEA), and load-to-strength ratio (45-degree forward bending ÷ vertebral compressive strength). Thus significantly impaired bone density, structure, and strength compared with controls indicate that many grade 1 deformities do represent early osteoporotic fractures, with corresponding implications for clinical decision making

Spatial normalization improves the quality of genotype calling for Affymetrix SNP 6.0 arrays

<p>Abstract</p> <p>Background</p> <p>Microarray measurements are susceptible to a variety of experimental artifacts, some of which give rise to systematic biases that are spatially dependent in a unique way on each chip. It is likely that such artifacts affect many SNP arrays, but the normalization methods used in currently available genotyping algorithms make no attempt at spatial bias correction. Here, we propose an effective single-chip spatial bias removal procedure for Affymetrix 6.0 SNP arrays or platforms with similar design features. This procedure deals with both extreme and subtle biases and is intended to be applied before standard genotype calling algorithms.</p> <p>Results</p> <p>Application of the spatial bias adjustments on HapMap samples resulted in higher genotype call rates with equal or even better accuracy for thousands of SNPs. Consequently the normalization procedure is expected to lead to more meaningful biological inferences and could be valuable for genome-wide SNP analysis.</p> <p>Conclusions</p> <p>Spatial normalization can potentially rescue thousands of SNPs in a genetic study at the small cost of computational time. The approach is implemented in R and available from the authors upon request.</p

Interplay between topography, fog and vegetation in the central South Arabian mountains revealed using a novel Landsat fog detection technique

In the central South Arabian mountains of Yemen and Oman, monsoon fog interception by the endemic cloud forest is essential for ecosystem functions and services. Yet, we know little about the local factors affecting fog distributions and their cumulative effects on vegetation. To examine these relationships, we developed a novel method of high-resolution fog detection using Landsat data, and validated the results using occurrence records of eight moisture-sensitive plant species. Regression tree analysis was then used to examine the topographic factors influencing fog distributions and the topoclimatic factors influencing satellite-derived vegetation greenness. We find that topography affects fog distributions. Specifically, steep windward slopes obstruct the inland movement of fog, resulting in heterogenous fog densities and hotspots of fog interception. We find that fog distributions explain patterns of vegetation greenness, and overall, that greenness increases with fog density. The layer of fog density describes patterns of vegetation greenness more accurately than topographic variables alone, and thus, we propose that regional vegetation patterns more closely follow a fog gradient, than an altitudinal gradient as previously supposed. The layer of fog density will enable an improved understanding of how species and communities, many of which are endemic, range-restricted, and in decline, respond to local variability in topoclimatic conditions