Examination of adipocere formation in a cold water environment

Adipocere is a late-stage postmortem decomposition product that forms from the lipids present in soft tissue. Its formation in aquatic environments is typically related to the presence of a moist, warm, anaerobic environment, and the effect of decomposer microorganisms. The ideal temperature range for adipocere formation is considered to be 21-45°C and is correlated to the optimal conditions for bacterial growth and enzymatic release. However, adipocere formation has been reported in cooler aquatic environments at considerable depths. This study aimed to investigate the chemical process of adipocere formation in a cold freshwater environment in Lake Ontario, Canada. Porcine tissue was used as a human tissue analogue and submerged at two depths (i.e., 10 and 30 feet) in the trophogenic zone of the lake. Samples were collected at monthly postmortem submersion intervals and analysed using diffuse reflectance infrared Fourier transform spectroscopy to provide a qualitative profile of the lipid degradation and adipocere formation process. Early stage adipocere formation occurred rapidly in the cold water environment and proceeded to intermediate stage adipocere formation by the second month of submersion. However, further adipocere formation was inhibited in the third month of the study when temperatures approached the freezing point. The depth of submergence did not influence the chemical conversion process as similar stages of adipocere formation occurred at both depths investigated. The study demonstrated that adipocere can form rapidly, even on small amounts of soft tissue, which may be representative of dismembered or disarticulated limbs discovered in an aquatic environment. © 2010 Springer-Verlag

Social behavior shapes the chimpanzee pan-microbiome

Animal sociality facilitates the transmission of pathogenic microorganisms among hosts, but the extent to which sociality enables animals’ beneficial microbial associations is poorly understood. The question is critical because microbial communities, particularly those in the gut, are key regulators of host health. We show evidence that chimpanzee social interactions propagate microbial diversity in the gut microbiome both within and between host generations. Frequent social interaction promotes species richness within individual microbiomes as well as homogeneity among the gut community memberships of different chimpanzees. Sampling successive generations across multiple chimpanzee families suggests that infants inherited gut microorganisms primarily through social transmission. These results indicate that social behavior generates a pan-microbiome, preserving microbial diversity across evolutionary time scales and contributing to the evolution of host species–specific gut microbial communities

Qunatification of Metabolites in MR Spectroscopic Imaging using Machine Learning

Magnetic Resonance Spectroscopic Imaging (MRSI) is a clinical imaging modality for measuring tissue metabolite levels in-vivo. An accurate estimation of spectral parameters allows for better assessment of spectral quality and metabolite concentration levels. The current gold standard quantification method is the LCModel - a commercial fitting tool. However, this fails for spectra having poor signal-to-noise ratio (SNR) or a large number of artifacts. This paper introduces a framework based on random forest regression for accurate estimation of the output parameters of a model based analysis of MR spectroscopy data. The goal of our proposed framework is to learn the spectral features from a training set comprising of different variations of both simulated and in-vivo brain spectra and then use this learning for the subsequent metabolite quantification. Experiments involve training and testing on simulated and in-vivo human brain spectra. We estimate parameters such as concentration of metabolites and compare our results with that from the LCModel

The Effect of Map Boundary on Estimates of Landscape Resistance to Animal Movement

BACKGROUND: Artificial boundaries on a map occur when the map extent does not cover the entire area of study; edges on the map do not exist on the ground. These artificial boundaries might bias the results of animal dispersal models by creating artificial barriers to movement for model organisms where there are no barriers for real organisms. Here, we characterize the effects of artificial boundaries on calculations of landscape resistance to movement using circuit theory. We then propose and test a solution to artificially inflated resistance values whereby we place a buffer around the artificial boundary as a substitute for the true, but unknown, habitat. METHODOLOGY/PRINCIPAL FINDINGS: We randomly assigned landscape resistance values to map cells in the buffer in proportion to their occurrence in the known map area. We used circuit theory to estimate landscape resistance to organism movement and gene flow, and compared the output across several scenarios: a habitat-quality map with artificial boundaries and no buffer, a map with a buffer composed of randomized habitat quality data, and a map with a buffer composed of the true habitat quality data. We tested the sensitivity of the randomized buffer to the possibility that the composition of the real but unknown buffer is biased toward high or low quality. We found that artificial boundaries result in an overestimate of landscape resistance. CONCLUSIONS/SIGNIFICANCE: Artificial map boundaries overestimate resistance values. We recommend the use of a buffer composed of randomized habitat data as a solution to this problem. We found that resistance estimated using the randomized buffer did not differ from estimates using the real data, even when the composition of the real data was varied. Our results may be relevant to those interested in employing Circuitscape software in landscape connectivity and landscape genetics studies

Cognitive and behavioral predictors of light therapy use

Objective: Although light therapy is effective in the treatment of seasonal affective disorder (SAD) and other mood disorders, only 53-79% of individuals with SAD meet remission criteria after light therapy. Perhaps more importantly, only 12-41% of individuals with SAD continue to use the treatment even after a previous winter of successful treatment. Method: Participants completed surveys regarding (1) social, cognitive, and behavioral variables used to evaluate treatment adherence for other health-related issues, expectations and credibility of light therapy, (2) a depression symptoms scale, and (3) self-reported light therapy use. Results: Individuals age 18 or older responded (n = 40), all reporting having been diagnosed with a mood disorder for which light therapy is indicated. Social support and self-efficacy scores were predictive of light therapy use (p's<.05). Conclusion: The findings suggest that testing social support and self-efficacy in a diagnosed patient population may identify factors related to the decision to use light therapy. Treatments that impact social support and self-efficacy may improve treatment response to light therapy in SAD. © 2012 Roecklein et al

Genome-wide association study meta-analysis for quantitative ultrasound parameters of bone identifies five novel loci for broadband ultrasound attenuation.

Osteoporosis is a common and debilitating bone disease that is characterised by low bone mineral density, typically assessed using dual-energy X-ray absorptiometry. Quantitative ultrasound (QUS), commonly utilising the two parameters velocity of sound (VOS) and broadband ultrasound attenuation (BUA), is an alternative technology used to assess bone properties at peripheral skeletal sites. The genetic influence on the bone qualities assessed by QUS remains an under-studied area. We performed a comprehensive GWAS including low-frequency variants (MAF ≥0.005) for BUA and VOS using a discovery population of individuals with whole-genome sequence (WGS) data from the UK10K project (n=1,268). These results were then meta-analysed with those from two deeply imputed GWAS replication cohorts (n=1,610 and 13,749). In the gender-combined analysis, we identified eight loci associated with BUA and five with VOS at the genome-wide significance level, including three novel loci for BUA at 8p23.1 (PPP1R3B), 11q23.1 (LOC387810) and 22q11.21 (SEPT5) (P = 2.4 × 10-8-1.6 × 10-9). Gene-based association testing in the gender-combined dataset revealed eight loci associated with BUA and seven with VOS at the genome-wide significance level, with one novel locus for BUA at FAM167A (8p23.1) (P = 1.4 × 10-6). An additional novel locus for BUA was seen in the male-specific analysis at DEFB103B (8p23.1) (P = 1.8 × 10-6). Fracture analysis revealed significant associations between variation at the WNT16 and RSPO3 loci and fracture risk (P = 0.004 and 4.0 × 10-4 respectively). In conclusion, by performing a large GWAS meta-analysis for QUS parameters of bone using a combination of WGS and deeply imputed genotype data, we have identified five novel genetic loci associated with BUA

Cellular responses of Candida albicans to phagocytosis and the extracellular activities of neutrophils are critical to counteract carbohydrate starvation, oxidative and nitrosative stress

Acknowledgments We thank Alexander Johnson (yhb1D/D), Karl Kuchler (sodD/D mutants), Janet Quinn (hog1D/D, hog1/cap1D/D, trx1D/D) and Peter Staib (ssu1D/D) for providing mutant strains. We acknowledge helpful discussions with our colleagues from the Microbial Pathogenicity Mechanisms Department, Fungal Septomics and the Microbial Biochemistry and Physiology Research Group at the Hans Kno¨ll Institute (HKI), specially Ilse D. Jacobsen, Duncan Wilson, Sascha Brunke, Lydia Kasper, Franziska Gerwien, Sea´na Duggan, Katrin Haupt, Kerstin Hu¨nniger, and Matthias Brock, as well as from our partners in the FINSysB Network. Author Contributions Conceived and designed the experiments: PM HW IMB AJPB OK BH. Performed the experiments: PM CD HW. Analyzed the data: PM HW IMB AJPB OK BH. Wrote the paper: PM HW OK AJPB BH.Peer reviewedPublisher PD