Troponin release following endurance exercise: is inflammation the cause? a cardiovascular magnetic resonance study

Background: The aetiology and clinical significance of troponin release following endurance exercise is unclear but may be due to transient myocardial inflammation. Cardiovascular magnetic resonance (CMR) affords us the opportunity to evaluate the presence of myocardial inflammation and focal fibrosis and is the ideal imaging modality to study this hypothesis. We sought to correlate the relationship between acute bouts of ultra endurance exercise leading to cardiac biomarkers elevation and the presence of myocardial inflammation and fibrosis using CMR.Methods: 17 recreation athletes (33.5 +/- 6.5 years) were studied before and after a marathon run with troponin, NTproBNP, and CMR. Specific imaging parameters to look for inflammation included T2 weighted images, and T1 weighted spin-echo images before and after an intravenous gadolinium-DTPA to detect myocardial hyperemia secondary to inflammation. Late gadolinium imaging was performed (LGE) to detect any focal regions of replacement fibrosis.Results: Eleven of the 17 participant had elevations of TnI above levels of cut off for myocardial infarction 6 hrs after the marathon (0.075 +/- 0.02, p = 0.007). Left ventricular volumes were reduced post marathon and a small increase in ejection fraction was noted (64 +/- 1% pre, 67 +/- 1.2% post, P = 0.014). Right ventricular volumes, stroke volume, and ejection fraction were unchanged post marathon. No athlete fulfilled criteria for myocardial inflammation based on current criteria. No regions of focal fibrosis were seen in any of the participants.Conclusion: Exercise induced cardiac biomarker release is not associated with any functional changes by CMR or any detectable myocardial inflammation or fibrosis

Evidence for methane and ammonia in the coma of comet P/Halley

Methane and ammonia abundances in the coma of Halley are derived from Giotto IMS data using an Eulerian model of chemical and physical processes inside the contact surface to simulate Giotto HIS ion mass spectral data for mass-to-charge ratios (m/q) from 15 to 19. The ratio m/q = 19/18 as a function of distance from the nucleus is not reproduced by a model for a pure water coma. It is necessary to include the presence of NH_3 , and uniquely NH_3 , in coma gases in order to explain the data. A ratio of production rates Q(NH_3)/Q(H20) = 0.01-Q.02 results in model values approximating the Giotto data. Methane is identified as the most probable source of the distinct peak at m/q = 15. The observations are fit best with Q(CH_4)/Q(H_20) = 0.02. The chemical composition of the comet nucleus implied by these production rate ratios is unlike that of the outer planets. On the other hand, there are also significant differences from observations of gas phase interstellar material

Development and Validation of an Anodic Stripping Voltammetric Method for Determination of Zn2+ Ions in Brain Microdialysate Samples

An easy, rapid, and sensitive anodic stripping voltammetric method with a controlled growth mercury drop electrode has been developed and validated for the determination of Zn2+ ions in brain microdialysate samples obtained from rats. The considered level of the zinc concentration in the dialysate was 0.5–6 ppb. In the investigated method, the stripping step was carried out by using a differential pulse potential-time voltammetric excitation signal. The optimal experimental conditions as well as the instrumental and accumulation parameters and supporting electrolyte composition were investigated. The optimized method was validated for precision, linearity, and accuracy. Mean recovery 82–110% was achieved, the precision expressed by CV not greater than 7.6% and the linearity given by correlation coefficient not lower than 0.9988. The limit of detection was 0.1 ppb. No interferences were observed. Due to high linearity, precision, and sensitivity, the developed method may be successfully applied in the determination of zinc ions in microdialysate brain samples. The results obtained for the first time demonstrate detailed characteristics of the determination of zinc in the brain microdialysate fluid by the ASV method. It may be applied in a wide range of physiological and pharmacological studies which focus on very low zinc concentration/alteration in various compartments of the organisms

Automated Discovery of Food Webs from Ecological Data Using Logic-Based Machine Learning

Networks of trophic links (food webs) are used to describe and understand mechanistic routes for translocation of energy (biomass) between species. However, a relatively low proportion of ecosystems have been studied using food web approaches due to difficulties in making observations on large numbers of species. In this paper we demonstrate that Machine Learning of food webs, using a logic-based approach called A/ILP, can generate plausible and testable food webs from field sample data. Our example data come from a national-scale Vortis suction sampling of invertebrates from arable fields in Great Britain. We found that 45 invertebrate species or taxa, representing approximately 25% of the sample and about 74% of the invertebrate individuals included in the learning, were hypothesized to be linked. As might be expected, detritivore Collembola were consistently the most important prey. Generalist and omnivorous carabid beetles were hypothesized to be the dominant predators of the system. We were, however, surprised by the importance of carabid larvae suggested by the machine learning as predators of a wide variety of prey. High probability links were hypothesized for widespread, potentially destabilizing, intra-guild predation; predictions that could be experimentally tested. Many of the high probability links in the model have already been observed or suggested for this system, supporting our contention that A/ILP learning can produce plausible food webs from sample data, independent of our preconceptions about “who eats whom.” Well-characterised links in the literature correspond with links ascribed with high probability through A/ILP. We believe that this very general Machine Learning approach has great power and could be used to extend and test our current theories of agricultural ecosystem dynamics and function. In particular, we believe it could be used to support the development of a wider theory of ecosystem responses to environmental change

Domain Altering SNPs in the Human Proteome and Their Impact on Signaling Pathways

Single nucleotide polymorphisms (SNPs) constitute an important mode of genetic variations observed in the human genome. A small fraction of SNPs, about four thousand out of the ten million, has been associated with genetic disorders and complex diseases. The present study focuses on SNPs that fall on protein domains, 3D structures that facilitate connectivity of proteins in cell signaling and metabolic pathways. We scanned the human proteome using the PROSITE web tool and identified proteins with SNP containing domains. We showed that SNPs that fall on protein domains are highly statistically enriched among SNPs linked to hereditary disorders and complex diseases. Proteins whose domains are dramatically altered by the presence of an SNP are even more likely to be present among proteins linked to hereditary disorders. Proteins with domain-altering SNPs comprise highly connected nodes in cellular pathways such as the focal adhesion, the axon guidance pathway and the autoimmune disease pathways. Statistical enrichment of domain/motif signatures in interacting protein pairs indicates extensive loss of connectivity of cell signaling pathways due to domain-altering SNPs, potentially leading to hereditary disorders

Utilisation of an operative difficulty grading scale for laparoscopic cholecystectomy

Background A reliable system for grading operative difficulty of laparoscopic cholecystectomy would standardise description of findings and reporting of outcomes. The aim of this study was to validate a difficulty grading system (Nassar scale), testing its applicability and consistency in two large prospective datasets. Methods Patient and disease-related variables and 30-day outcomes were identified in two prospective cholecystectomy databases: the multi-centre prospective cohort of 8820 patients from the recent CholeS Study and the single-surgeon series containing 4089 patients. Operative data and patient outcomes were correlated with Nassar operative difficultly scale, using Kendall’s tau for dichotomous variables, or Jonckheere–Terpstra tests for continuous variables. A ROC curve analysis was performed, to quantify the predictive accuracy of the scale for each outcome, with continuous outcomes dichotomised, prior to analysis. Results A higher operative difficulty grade was consistently associated with worse outcomes for the patients in both the reference and CholeS cohorts. The median length of stay increased from 0 to 4 days, and the 30-day complication rate from 7.6 to 24.4% as the difficulty grade increased from 1 to 4/5 (both p < 0.001). In the CholeS cohort, a higher difficulty grade was found to be most strongly associated with conversion to open and 30-day mortality (AUROC = 0.903, 0.822, respectively). On multivariable analysis, the Nassar operative difficultly scale was found to be a significant independent predictor of operative duration, conversion to open surgery, 30-day complications and 30-day reintervention (all p < 0.001). Conclusion We have shown that an operative difficulty scale can standardise the description of operative findings by multiple grades of surgeons to facilitate audit, training assessment and research. It provides a tool for reporting operative findings, disease severity and technical difficulty and can be utilised in future research to reliably compare outcomes according to case mix and intra-operative difficulty

Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015

SummaryBackground The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 provides an up-to-date synthesis of the evidence for risk factor exposure and the attributable burden of disease. By providing national and subnational assessments spanning the past 25 years, this study can inform debates on the importance of addressing risks in context. Methods We used the comparative risk assessment framework developed for previous iterations of the Global Burden of Disease Study to estimate attributable deaths, disability-adjusted life-years (DALYs), and trends in exposure by age group, sex, year, and geography for 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2015. This study included 388 risk-outcome pairs that met World Cancer Research Fund-defined criteria for convincing or probable evidence. We extracted relative risk and exposure estimates from randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. We developed a metric that allows comparisons of exposure across risk factors—the summary exposure value. Using the counterfactual scenario of theoretical minimum risk level, we estimated the portion of deaths and DALYs that could be attributed to a given risk. We decomposed trends in attributable burden into contributions from population growth, population age structure, risk exposure, and risk-deleted cause-specific DALY rates. We characterised risk exposure in relation to a Socio-demographic Index (SDI). Findings Between 1990 and 2015, global exposure to unsafe sanitation, household air pollution, childhood underweight, childhood stunting, and smoking each decreased by more than 25%. Global exposure for several occupational risks, high body-mass index (BMI), and drug use increased by more than 25% over the same period. All risks jointly evaluated in 2015 accounted for 57·8% (95% CI 56·6–58·8) of global deaths and 41·2% (39·8–42·8) of DALYs. In 2015, the ten largest contributors to global DALYs among Level 3 risks were high systolic blood pressure (211·8 million [192·7 million to 231·1 million] global DALYs), smoking (148·6 million [134·2 million to 163·1 million]), high fasting plasma glucose (143·1 million [125·1 million to 163·5 million]), high BMI (120·1 million [83·8 million to 158·4 million]), childhood undernutrition (113·3 million [103·9 million to 123·4 million]), ambient particulate matter (103·1 million [90·8 million to 115·1 million]), high total cholesterol (88·7 million [74·6 million to 105·7 million]), household air pollution (85·6 million [66·7 million to 106·1 million]), alcohol use (85·0 million [77·2 million to 93·0 million]), and diets high in sodium (83·0 million [49·3 million to 127·5 million]). From 1990 to 2015, attributable DALYs declined for micronutrient deficiencies, childhood undernutrition, unsafe sanitation and water, and household air pollution; reductions in risk-deleted DALY rates rather than reductions in exposure drove these declines. Rising exposure contributed to notable increases in attributable DALYs from high BMI, high fasting plasma glucose, occupational carcinogens, and drug use. Environmental risks and childhood undernutrition declined steadily with SDI; low physical activity, high BMI, and high fasting plasma glucose increased with SDI. In 119 countries, metabolic risks, such as high BMI and fasting plasma glucose, contributed the most attributable DALYs in 2015. Regionally, smoking still ranked among the leading five risk factors for attributable DALYs in 109 countries; childhood underweight and unsafe sex remained primary drivers of early death and disability in much of sub-Saharan Africa. Interpretation Declines in some key environmental risks have contributed to declines in critical infectious diseases. Some risks appear to be invariant to SDI. Increasing risks, including high BMI, high fasting plasma glucose, drug use, and some occupational exposures, contribute to rising burden from some conditions, but also provide opportunities for intervention. Some highly preventable risks, such as smoking, remain major causes of attributable DALYs, even as exposure is declining. Public policy makers need to pay attention to the risks that are increasingly major contributors to global burden. Funding Bill & Melinda Gates Foundation