Epidemiology and Impact of Abdominal Oblique Injuries in Major and Minor League Baseball.

BACKGROUND: Oblique injuries are known to be a common cause of time out of play for professional baseball players, and prior work has suggested that injury rates may be on the rise in Major League Baseball (MLB). PURPOSE: To better understand the current incidence of oblique injuries, determine their impact based on time out of play, and to identify common injury patterns that may guide future injury prevention programs. STUDY DESIGN: Descriptive epidemiological study. METHODS: Using the MLB Health and Injury Tracking System, all oblique injuries that resulted in time out of play in MLB and Minor League Baseball (MiLB) during the 2011 to 2015 seasons were identified. Player demographics such as age, position/role, and handedness were included. Injury-specific factors analyzed included the following: date of injury, timing during season, days missed, mechanism, side, treatment, and reinjury status. RESULTS: A total of 996 oblique injuries occurred in 259 (26%) MLB and 737 (74%) MiLB players. Although the injury rate was steady in MiLB, the MLB injury rate declined (P = .037). A total of 22,064 days were missed at a mean rate of 4413 days per season and 22.2 days per injury. The majority of these occurred during batting (n = 455, 46%) or pitching (n = 348, 35%), with pitchers losing 5 days more per injury than batters (P \u3c .001). The leading side was injured in 77% of cases and took 5 days longer to recover from than trailing side injuries (P = .009). Seventy-nine (7.9%) players received either a corticosteroid or platelet-rich plasma injection, and the mean recovery time was 11 days longer compared with those who did not receive an injection (P \u3c .001). CONCLUSION: Although the rate of abdominal oblique injuries is on the decline in MLB, this is not the case for MiLB, and these injuries continue to represent a significant source of time out of play in professional baseball. The vast majority of injuries occur on the lead side, and these injuries result in the greatest amount time out of play. The benefit of injections for the treatment of oblique injuries remains unknown

Emerging climate-driven disturbance processes: Widespread mortality associated with snow-to-rain transitions across 10° of latitude and half the range of a climate-threatened conifer

Climate change is causing rapid changes to forest disturbance regimes worldwide. While the consequences of climate change for existing disturbance processes, like fires, are relatively well studied, emerging drivers of disturbance such as snow loss and subsequent mortality are much less documented. As the climate warms, a transition from winter snow to rain in high latitudes will cause significant changes in environmental conditions such as soil temperatures, historically buffered by snow cover. The Pacific coast of North America is an excellent test case, as mean winter temperatures are currently at the snow–rain threshold and have been warming for approximately 100 years post-Little Ice Age. Increased mortality in a widespread tree species in the region has been linked to warmer winters and snow loss. Here, we present the first high-resolution range map of this climate-sensitive species, Callitropsis nootkatensis (yellow-cedar), and document the magnitude and location of observed mortality across Canada and the United States. Snow cover loss related mortality spans approximately 10° latitude (half the native range of the species) and 7% of the overall species range and appears linked to this snow–rain transition across its range. Mortality is commonly >70% of basal area in affected areas, and more common where mean winter temperatures is at or above the snow–rain threshold (>0 °C mean winter temperature). Approximately 50% of areas with a currently suitable climate for the species (< 2 °C) are expected to warm beyond that threshold by the late 21st century. Regardless of climate change scenario, little of the range which is expected to remain suitable in the future (e.g., a climatic refugia) is in currently protected landscapes (<1–9%). These results are the first documentation of this type of emerging climate disturbance and highlight the difficulties of anticipating novel disturbance processes when planning for conservation and management.Ye

Glioma cells on the run – the migratory transcriptome of 10 human glioma cell lines

<p>Abstract</p> <p>Background</p> <p>Glioblastoma multiforme (GBM) is the most common primary intracranial tumor and despite recent advances in treatment regimens, prognosis for affected patients remains poor. Active cell migration and invasion of GBM cells ultimately lead to ubiquitous tumor recurrence and patient death.</p> <p>To further understand the genetic mechanisms underlying the ability of glioma cells to migrate, we compared the matched transcriptional profiles of migratory and stationary populations of human glioma cells. Using a monolayer radial migration assay, motile and stationary cell populations from seven human long term glioma cell lines and three primary GBM cultures were isolated and prepared for expression analysis.</p> <p>Results</p> <p>Gene expression signatures of stationary and migratory populations across all cell lines were identified using a pattern recognition approach that integrates <it>a priori </it>knowledge with expression data. Principal component analysis (PCA) revealed two discriminating patterns between migrating and stationary glioma cells: i) global down-regulation and ii) global up-regulation profiles that were used in a proband-based rule function implemented in GABRIEL to find subsets of genes having similar expression patterns. Genes with up-regulation pattern in migrating glioma cells were found to be overexpressed in 75% of human GBM biopsy specimens compared to normal brain. A 22 gene signature capable of classifying glioma cultures based on their migration rate was developed. Fidelity of this discovery algorithm was assessed by validation of the invasion candidate gene, connective tissue growth factor (CTGF). siRNA mediated knockdown yielded reduced <it>in vitro </it>migration and <it>ex vivo </it>invasion; immunohistochemistry on glioma invasion tissue microarray confirmed up-regulation of CTGF in invasive glioma cells.</p> <p>Conclusion</p> <p>Gene expression profiling of migratory glioma cells induced to disperse <it>in vitro </it>affords discovery of genomic signatures; selected candidates were validated clinically at the transcriptional and translational levels as well as through functional assays thereby underscoring the fidelity of the discovery algorithm.</p

Down-regulation of estrogen receptor-alpha and rearranged during transfection tyrosine kinase is associated with withaferin a-induced apoptosis in MCF-7 breast cancer cells

<p>Abstract</p> <p>Background</p> <p>Withaferin A (WA), a naturally occurring withanolide, induces apoptosis in both estrogen-responsive MCF-7 and estrogen-independent MDA-MB-231 breast cancer cell lines with higher sensitivity in MCF-7 cells, but the underlying mechanisms are not well defined. The purpose of this study was to determine the anti-cancer effects of WA in MCF-7 breast cancer cells and explore alterations in estrogen receptor alpha (ERα) and its associated molecules <it>in vitro </it>as novel mechanisms of WA action.</p> <p>Methods</p> <p>The effects of WA on MCF-7 viability and proliferation were evaluated by 3-(4, 5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium (MTS) assay and trypan blue exclusion assays. Apoptosis was evaluated by Annexin V-fluorescein isothiocyanate (FITC)/propidium iodide (PI) flow cytometry and Western blot analysis of poly (ADP-ribose) polymerase (PARP) cleavage. Cell cycle effects were analyzed by PI flow cytometry. Western blotting was also conducted to examine alterations in the expression of ERα and pathways that are associated with ERα function.</p> <p>Results</p> <p>WA resulted in growth inhibition and decreased viability in MCF-7 cells with an IC50 of 576 nM for 72 h. It also caused a dose- and time-dependent apoptosis and G2/M cell cycle arrest. WA-induced apoptosis was associated with down-regulation of ERα, REarranged during Transfection (RET) tyrosine kinase, and heat shock factor-1 (HSF1), as well as up-regulation of phosphorylated p38 mitogen-activated protein kinase (phospho-p38 MAPK), p53 and p21 protein expression. Co-treatment with protein synthesis inhibitor cycloheximide or proteasome inhibitor MG132 revealed that depletion of ERα by WA is post-translational, due to proteasome-dependent ERα degradation.</p> <p>Conclusions</p> <p>Taken together, down-regulation of ERα, RET, HSF1 and up-regulation of phospho-p38 MAPK, p53, p21 are involved in the pro-apoptotic and growth-inhibitory effects of WA in MCF-7 breast cancer cells <it>in vitro</it>. Down-regulation of ERα protein levels by WA is caused by proteasome-dependent ERα degradation.</p

Random-phase approximation and its applications in computational chemistry and materials science

The random-phase approximation (RPA) as an approach for computing the electronic correlation energy is reviewed. After a brief account of its basic concept and historical development, the paper is devoted to the theoretical formulations of RPA, and its applications to realistic systems. With several illustrating applications, we discuss the implications of RPA for computational chemistry and materials science. The computational cost of RPA is also addressed which is critical for its widespread use in future applications. In addition, current correction schemes going beyond RPA and directions of further development will be discussed.Comment: 25 pages, 11 figures, published online in J. Mater. Sci. (2012

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

Published by Elsevier Ltd. This is an Open Access article under the CC BY license.Background 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

Biological Process Linkage Networks

BACKGROUND. The traditional approach to studying complex biological networks is based on the identification of interactions between internal components of signaling or metabolic pathways. By comparison, little is known about interactions between higher order biological systems, such as biological pathways and processes. We propose a methodology for gleaning patterns of interactions between biological processes by analyzing protein-protein interactions, transcriptional co-expression and genetic interactions. At the heart of the methodology are the concept of Linked Processes and the resultant network of biological processes, the Process Linkage Network (PLN). RESULTS. We construct, catalogue, and analyze different types of PLNs derived from different data sources and different species. When applied to the Gene Ontology, many of the resulting links connect processes that are distant from each other in the hierarchy, even though the connection makes eminent sense biologically. Some others, however, carry an element of surprise and may reflect mechanisms that are unique to the organism under investigation. In this aspect our method complements the link structure between processes inherent in the Gene Ontology, which by its very nature is species-independent. As a practical application of the linkage of processes we demonstrate that it can be effectively used in protein function prediction, having the power to increase both the coverage and the accuracy of predictions, when carefully integrated into prediction methods. CONCLUSIONS. Our approach constitutes a promising new direction towards understanding the higher levels of organization of the cell as a system which should help current efforts to re-engineer ontologies and improve our ability to predict which proteins are involved in specific biological processes.Lynn and William Frankel Center for Computer Science; the Paul Ivanier center for robotics research and production; National Science Foundation (ITR-048715); National Human Genome Research Institute (1R33HG002850-01A1, R01 HG003367-01A1); National Institute of Health (U54 LM008748