Effect of resistance exercise contraction mode and protein supplementation on members of the STARS signalling pathway

The striated muscle activator of Rho signalling (STARS) pathway is suggested to provide a link between external stress responses and transcriptional regulation in muscle. However, the sensitivity of STARS signalling to different mechanical stresses has not been investigated. In a comparative study, we examined the regulation of the STARS signalling pathway in response to unilateral resistance exercise performed as either eccentric (ECC) or concentric (CONC) contractions as well as prolonged training; with and without whey protein supplementation. Skeletal muscle STARS, myocardian-related transcription factor-A (MRTF-A) and serum response factor (SRF) mRNA and protein, as well as muscle cross-sectional area and maximal voluntary contraction, were measured. A single-bout of exercise produced increases in STARS and SRF mRNA and decreases in MRTF-A mRNA with both ECC and CONC exercise, but with an enhanced response occurring following ECC exercise. A 31% increase in STARS protein was observed exclusively after CONC exercise (P < 0.001), while pSRF protein levels increased similarly by 48% with both CONC and ECC exercise (P < 0.001). Prolonged ECC and CONC training equally stimulated muscle hypertrophy and produced increases in MRTF-A protein of 125% and 99%, respectively (P < 0.001). No changes occurred for total SRF protein. There was no effect of whey protein supplementation. These results show that resistance exercise provides an acute stimulation of the STARS pathway that is contraction mode dependent. The responses to acute exercise were more pronounced than responses to accumulated training, suggesting that STARS signalling is primarily involved in the initial phase of exercise-induced muscle adaptations.

Regulation of the STARS signaling pathway in response to endurance and resistance exercise and training

The striated muscle activator of Rho signaling (STARS) protein and members of its downstream signaling pathway, including myocardin-related transcription factor-A (MRTF-A) and SRF, are increased in response to prolonged resistance exercise training but also following a single bout of endurance cycling. The aim of the present study was to measure and compare the regulation of STARS, MRTF-A and SRF mRNA and protein following 10 weeks of endurance training (ET) versus resistance training (RT), as well as before and following a single bout of endurance (EE) versus resistance exercise (RE). Following prolonged training, STARS, MRTF-A and SRF mRNA levels were all increased by similar magnitude, irrespective of training type. In the training-habituated state, STARS mRNA increased following a single-bout RE when measured 2.5 and 5 h post-exercise and had returned to resting level by 22 h following exercise. MRTF-A and SRF mRNA levels were decreased by 2.5, 5, and 22 h following a single bout of RE and EE exercise when compared to their respective basal levels, with no significant difference seen between the groups at any of the time points. No changes in protein levels were observed following the two modes of exercise training or a single bout of exercise. This study demonstrates that the stress signals elicited by ET and RT result in a comparable regulation of members of the STARS pathway. In contrast, a single bout of EE and RE, performed in the trained state, elicit different responses. These observations suggest that in the trained state, the acute regulation of the STARS pathway following EE or RE may be responsible for exercise-specific muscle adaptations.

Satellite imagery as a single source of predictor variables for habitat suitability modelling: how Landsat can inform the conservation of a critically endangered lemur

1. Statistical modelling of habitat suitability is an important tool for planning conservation interventions, particularly for areas where species distribution data are expensive or hard to collect. Sometimes however the predictor variables typically used in habitat suitability modelling are themselves difficult to obtain or not meaningful at the geographical extent of the study, as is the case for the Alaotran gentle lemur Hapalemur alaotrensis, a critically endangered lemur confined to the marshes of Lake Alaotra in Madagascar.2. We developed a habitat suitability model where all predictor variables, including vegetation indices and image texture measures at different scales (as surrogates for habitat structure), were derived from Landsat7 satellite imagery. Using relatively few presence records, the maximum entropy (Maxent) approach and AUC were used to assess the performance of candidate predictor variables, for studying the effect of scale, model selection and mapping suitable habitat.3. This study demonstrated the utility of satellite imagery as a single source of predictor variables for a Maxent habitat suitability model at the landscape level, within a restricted geographical extent and with a fine grain, in a case where predictor variables typically used at the macro-scale level (e.g. climatic and topographic) were not applicable.4. In the case of H. alaotrensis, the methodology generated a habitat suitability map to inform conservation management in Lake Alaotra and a replicable protocol to allow rapid updates to habitat suitability maps in the future. The exploration of candidate predictor variables allowed the identification of scales that appear ecologically relevant for the species.5. Synthesis and applications. This study presents a cost-effective combination of maximum entropy habitat suitability modelling and satellite imagery, where all predictor variables are derived solely from Landsat7 images. With a habitat modelling method like Maxent that shows good performance with few presence samples and Landsat images now freely available, the methodology can play an important role in rapid assessments of the status of species at the landscape level in data-poor regions, when typical macro-scale environmental predictors are of little use or difficult to obtain.

Dataset of specific variables from the Mums, Dads, Kids study

Dataset for MDK study including screen time and anxiety scores of participants. Also includes demographic characteristics

Meteomap: Generation Of Meteorological Variables For Distributed Physically-Based Hydrological Modeling

Distributed energy and water balance models require time-series surfaces of the meteorological variables involved in hydrological processes. Most of the hydrological GIS-based models apply simple interpolation techniques to extrapolate the point scale values registered at weather stations at a watershed scale. In mountainous areas, where the monitoring network ineffectively covers the complex terrain heterogeneity, simple geostatistical methods for spatial interpolation are not always representative enough, and algorithms that explicitly or implicitly account for the features creating strong local gradients in the meteorological variables must be applied. Originally developed as a meteorological pre-processing tool for a complete hydrological model (WiMMed), MeteoMap has become an independent software. The individual interpolation algorithms used to approximate the spatial distribution of each meteorological variable were carefully selected taking into account both, the specific variable being mapped, and the common lack of input data from Mediterranean mountainous areas. They include corrections with height for both rainfall and temperature (Herrero et al., 2007), and topographic corrections for solar radiation (Aguilar et al., 2010). MeteoMap is a GIS-based freeware upon registration. Input data include weather station records and topographic data and the output consists of tables and maps of the meteorological variables at hourly, daily, predefined rainfall event duration or annual scales. It offers its own pre and post-processing tools, including video outlook, map printing and the possibility of exporting the maps to images or ASCII ArcGIS formats. This study presents the friendly user interface of the software and shows some case studies with applications to hydrological modeling.

Descentralizacion y participacion: dos variables democraticas tensiones y distennsiones en el sector salud, referencias a Brasil y Colombia

Este estudo tem, como tema central, a análise da descentralização e da participação como categorias democratizantes da reforma do Estado, particularmente, na área das políticas de saúde no Brasil e na Colômbia. Foi realizada uma análise teórica de ambas as categorias e de seu impacto na reformulação da relação Estado e sociedade para examinar, no último capítulo, sua conjunção na formulação, implementação e controle das políticas de saúde. Os resultados obtidos permitiram elaborar um marco analítico de gradação dos níveis de descentralização e participação assim como a importância destas na prática de uma gestão de saúde mais democrática.

Price setting and macroeconomic variables: evidence from Brazilian CPI

Esta tese investiga as estratégias de precificação em ambientes macroeconômicos distintos, utilizando uma base de dados única para o IPC da Fundação Getulio Vargas. A base de dados primária consiste em um painel de dados individuais para bens e serviços representando 100% do IPC para o período de 1996 a 2008. Durante este período, diversos eventos produziram uma variabilidade macroeconômica substancial no Brasil: duas crises em países emergentes, uma mudança de regime cambial e monetário, racionamento de energia, uma crise de expectativas eleitorais e um processo de desinflação. Como consequência, a inflação, a incerteza macroeconômica, a taxa de câmbio e o produto exibiram uma variação considerável no período. No primeiro capítulo, nós descrevemos a base de dados e apresentamos as principais estatísticas de price-setting para o Brasil. Em seguida, nos capítulos 2 e 3, nos construímos as séries de tempo destas estatísticas e das estatísticas de promoções, e as relacionamos com as variáveis macroeconômicas utilizando análises de regressões. Os resultados indicam que há uma relação substancial entre as estatísticas de price-setting e o ambiente macroeconômico para a economia brasileira.

A study of the impacts of quantitative easing on the macroeconomics variables

Neste trabalho, propusemos um modelo DSGE que busca responder algumas questões sobre políticas de afrouxamento monetário (Quantitative Easing - QE) recentemente implementadas em resposta à crise de 2008. Desenvolvemos um modelo DSGE com agentes heterogêneos e preferred-habitat nas compras de títulos do governo. Nosso modelo permite o estudo da otimalidade da compra de portfolio (em termos de duration dos títulos) para os bancos centrais quando estão implementando a política. Além disso, a estrutura heterogênea nos permite olhar para distribuição de renda provocada pelas compras de títulos. Nossos resultados preliminares evidenciam o efeito distributivo do QE. No entanto, nosso modelo expandido apresentou alguns problemas de estabilidade.

Optimal two-sided tests for instrumental variables regression with heteroskedastic and autocorrelated errors

This paper considers two-sided tests for the parameter of an endogenous variable in an instrumental variable (IV) model with heteroskedastic and autocorrelated errors. We develop the nite-sample theory of weighted-average power (WAP) tests with normal errors and a known long-run variance. We introduce two weights which are invariant to orthogonal transformations of the instruments; e.g., changing the order in which the instruments appear. While tests using the MM1 weight can be severely biased, optimal tests based on the MM2 weight are naturally two-sided when errors are homoskedastic. We propose two boundary conditions that yield two-sided tests whether errors are homoskedastic or not. The locally unbiased (LU) condition is related to the power around the null hypothesis and is a weaker requirement than unbiasedness. The strongly unbiased (SU) condition is more restrictive than LU, but the associated WAP tests are easier to implement. Several tests are SU in nite samples or asymptotically, including tests robust to weak IV (such as the Anderson-Rubin, score, conditional quasi-likelihood ratio, and I. Andrews' (2015) PI-CLC tests) and two-sided tests which are optimal when the sample size is large and instruments are strong. We refer to the WAP-SU tests based on our weights as MM1-SU and MM2-SU tests. Dropping the restrictive assumptions of normality and known variance, the theory is shown to remain valid at the cost of asymptotic approximations. The MM2-SU test is optimal under the strong IV asymptotics, and outperforms other existing tests under the weak IV asymptotics.