Integrating resource selection into spatial capture-recapture models for large carnivores

Wildlife managers need reliable methods to estimate large carnivore densities and population trends; yet large carnivores are elusive, difficult to detect, and occur at low densities making traditional approaches intractable. Recent advances in spatial capture-recapture (SCR) models have provided new approaches for monitoring trends in wildlife abundance and these methods are particularly applicable to large carnivores. We applied SCR models in a Bayesian framework to estimate mountain lion densities in the Bitterroot Mountains of west central Montana. We incorporate an existing resource selection function (RSF) as a density co-variate to account for heterogeneity in habitat use across the study area and include data collected from harvested lions. We identify individuals through DNA samples collected by (1) biopsy darting mountain lions detected in systematic surveys of a study area, (2) opportunistically collecting hair and scat samples, and (3) sampling all harvested mountain lions. We included 80 DNA samples collected from 62 individuals in the analysis. Including information on predicted habitat use as a co-variate on the distribution of activity centers reduced the median estimated density by 44% the standard deviation by 7% and the width of 95% credible intervals by 10% as compared to standard SCR models. Within the two management units of interest, we estimated a median mountain lion density of 4.5 mountain lions/100 km2 (95% CI=2.9, 7.7) and 5.2 mountain lions/100 km2 (95% CI=3.4, 9.1). Including harvested individuals (dead recovery) did not create a significant bias in the detection process by introducing individuals that could not be detected after removal. However, the dead recovery component of the model did have a substantial effect on results by increasing sample size. The ability to account for heterogeneity in habitat use provides a useful extension to SCR models, and will enhance the ability of wildlife managers to reliably and economically estimate density of wildlife populations, particularly large carnivores

Florida\u27s Mystery Coral-Killer Identified

An unusual coral disease appeared on the Florida Reef Tract in June 1995. It was distinct in its microbiology, its pattern of tissue degradation, the species susceptible to it, and its regional distribution. Symptoms included a sharp line between healthy and diseased tissue, as occurs with other coral diseases, but the pathogen responsible for the new outbreak seemed more virulent, affected a wider variety of species, and destroyed tissue much more rapidly than these other \u27line\u27 or \u27band\u27 diseases. We have identified the pathogen responsible for this new disease as a new species of Sphingomonas

Genomics of Loa loa, a Wolbachia-free filarial parasite of humans

Loa loa, the African eyeworm, is a major filarial pathogen of humans. Unlike most filariae, Loa loa does not contain the obligate intracellular Wolbachia endosymbiont. We describe the 91.4 Mb genome of Loa loa, and the genome of the related filarial parasite Wuchereria bancrofti, and predict 14,907 Loa loa genes based on microfilarial RNA sequencing. By comparing these genomes to that of another filarial parasite, Brugia malayi, and to several other nematode genomes, we demonstrate synteny among filariae but not with non-parasitic nematodes. The Loa loa genome encodes many immunologically relevant genes, as well as protein kinases targeted by drugs currently approved for humans. Despite lacking Wolbachia, Loa loa shows no new metabolic synthesis or transport capabilities compared to other filariae. These results suggest that the role played by Wolbachia in filarial biology is more subtle than previously thought and reveal marked differences between parasitic and non-parasitic nematodes

Genotypic and phenotypic analyses of a Pseudomonas aeruginosa chronic bronchiectasis isolate reveal differences from cystic fibrosis and laboratory strains

Background Pseudomonas aeruginosa is an environmentally ubiquitous Gram-negative bacterium and important opportunistic human pathogen, causing severe chronic respiratory infections in patients with underlying conditions such as cystic fibrosis (CF) or bronchiectasis. In order to identify mechanisms responsible for adaptation during bronchiectasis infections, a bronchiectasis isolate, PAHM4, was phenotypically and genotypically characterized. Results This strain displays phenotypes that have been associated with chronic respiratory infections in CF including alginate over-production, rough lipopolysaccharide, quorum-sensing deficiency, loss of motility, decreased protease secretion, and hypermutation. Hypermutation is a key adaptation of this bacterium during the course of chronic respiratory infections and analysis indicates that PAHM4 encodes a mutated mutS gene responsible for a ~1,000-fold increase in mutation rate compared to wild-type laboratory strain P. aeruginosa PAO1. Antibiotic resistance profiles and sequence data indicate that this strain acquired numerous mutations associated with increased resistance levels to β-lactams, aminoglycosides, and fluoroquinolones when compared to PAO1. Sequencing of PAHM4 revealed a 6.38 Mbp genome, 5.9 % of which were unrecognized in previously reported P. aeruginosa genome sequences. Transcriptome analysis suggests a general down-regulation of virulence factors, while metabolism of amino acids and lipids is up-regulated when compared to PAO1 and metabolic modeling identified further potential differences between PAO1 and PAHM4. Conclusions This work provides insights into the potential differential adaptation of this bacterium to the lung of patients with bronchiectasis compared to other clinical settings such as cystic fibrosis, findings that should aid the development of disease-appropriate treatment strategies for P. aeruginosa infections

Overweight, obesity, and risk of cardiometabolic multimorbidity: pooled analysis of individual-level data for 120 813 adults from 16 cohort studies from the USA and Europe

Summary Background Although overweight and obesity have been studied in relation to individual cardiometabolic diseases, their association with risk of cardiometabolic multimorbidity is poorly understood. Here we aimed to establish the risk of incident cardiometabolic multimorbidity (ie, at least two from: type 2 diabetes, coronary heart disease, and stroke) in adults who are overweight and obese compared with those who are a healthy weight. Methods We pooled individual-participant data for BMI and incident cardiometabolic multimorbidity from 16 prospective cohort studies from the USA and Europe. Participants included in the analyses were 35 years or older and had data available for BMI at baseline and for type 2 diabetes, coronary heart disease, and stroke at baseline and follow-up. We excluded participants with a diagnosis of diabetes, coronary heart disease, or stroke at or before study baseline. According to WHO recommendations, we classified BMI into categories of healthy (20·0–24·9 kg/m2), overweight (25·0–29·9 kg/m2), class I (mild) obesity (30·0–34·9 kg/m2), and class II and III (severe) obesity (≥35·0 kg/m2). We used an inclusive definition of underweight (Peer reviewe

Sensitization in Transplantation: Assessment of Risk (STAR) 2017 Working Group Meeting Report

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/144684/1/ajt14752_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/144684/2/ajt14752.pd

Intentional creation of carbon-rich dark earth soils in the Amazon

Fertile soil known as Amazonian dark earth is central to the debate over the size and ecological impact of ancient human populations in the Amazon. Dark earth is typically associated with human occupation, but it is uncertain whether it was created intentionally. Dark earth may also be a substantial carbon sink, but its spatial extent and carbon inventory are unknown. We demonstrate spatial and compositional similarities between ancient and modern dark earth and document modern Indigenous practices that enrich soil, which we use to propose a model for the formation of ancient dark earth. This comparison suggests that ancient Amazonians managed soil to improve fertility and increase crop productivity. These practices also sequestered and stored carbon in the soil for centuries, and we show that some ancient sites contain as much carbon as the above-ground rainforest biomass. Our results demonstrate the intentional creation of dark earth and highlight the value of Indigenous knowledge for sustainable rainforest management