Optimism moderates psychophysiological responses to stress in older people with Type 2 diabetes

Optimism is thought to be beneficial for health, and these effects may be mediated through modifications in psychophysiological stress reactivity. Type 2 diabetes (T2D) is associated with reduced cardiovascular responses to stress and heightened cortisol over the day. This study assessed the relationships between optimism, stress responsivity, and daily cortisol output in people with T2D. A total of 140 participants with T2D were exposed to laboratory stress. Heart rate (HR), systolic (SBP), diastolic blood pressure (DBP), and cortisol were measured throughout the session. Cortisol output over the day was also assessed. Optimism and self-reported health were measured using the revised Life Orientation Test and the Short Form Health Survey. Optimism was associated with heightened SBP and DBP stress reactivity (ps  .180). Low optimism was related to poorer self-reported physical and mental health (ps < .01). Optimism could have a protective role in modulating stress-related autonomic and neuroendocrine dysregulation in people with T2D

Factors associated with quality of services for marginalized groups with mental health problems in 14 European countries

This research was financially supported by DG-Sanco (contract: 800197; 2007-2010). The authors would like to thank all of the professionals and services who participated in the PROMO assessment of services. A PhD grant from Fundação para a Ciência e Tecnologia–Portugal (SFRH/BD/66388/2009) to the first author is acknowledged

Protein disulfide-isomerase interacts with a substrate protein at all stages along its folding pathway

In contrast to molecular chaperones that couple protein folding to ATP hydrolysis, protein disulfide-isomerase (PDI) catalyzes protein folding coupled to formation of disulfide bonds (oxidative folding). However, we do not know how PDI distinguishes folded, partly-folded and unfolded protein substrates. As a model intermediate in an oxidative folding pathway, we prepared a two-disulfide mutant of basic pancreatic trypsin inhibitor (BPTI) and showed by NMR that it is partly-folded and highly dynamic. NMR studies show that it binds to PDI at the same site that binds peptide ligands, with rapid binding and dissociation kinetics; surface plasmon resonance shows its interaction with PDI has a Kd of ca. 10−5 M. For comparison, we characterized the interactions of PDI with native BPTI and fully-unfolded BPTI. Interestingly, PDI does bind native BPTI, but binding is quantitatively weaker than with partly-folded and unfolded BPTI. Hence PDI recognizes and binds substrates via permanently or transiently unfolded regions. This is the first study of PDI's interaction with a partly-folded protein, and the first to analyze this folding catalyst's changing interactions with substrates along an oxidative folding pathway. We have identified key features that make PDI an effective catalyst of oxidative protein folding – differential affinity, rapid ligand exchange and conformational flexibility

Operational forecasting of daily summer maximum and minimum temperatures in the Valencia Region

Extreme-temperature events have a great impact on human society. Thus, knowledge of summer temperatures can be very useful both for the general public and for organizations whose workers operate in the open. An accurate forecasting of summer maximum and minimum temperatures could help to predict heatwave conditions and permit the implementation of strategies aimed at minimizing the negative effects that high temperatures have on human health. The objective of this work is to evaluate the skill of the regional atmospheric and modelling system (RAMS) model in determining daily summer maximum and minimum temperatures in the Valencia Region. For this, we have used the real-time configuration of this model currently running at the Centro de Estudios Ambientales de Mediterráneo Foundation. This operational system is run twice a day, and both runs have a 3-day forecast range. To carry out the verification of the model in this work, the information generated by the system has been broken into individual simulation days for a specific daily run of the model. Moreover, we have analysed the summer forecast period from 1 June to 31 August for 2007, 2008, 2009 and 2010. The results indicate good agreement between observed and simulated maximum temperatures, with RMSE in general near 2 °C both for coastal and inland stations. For this parameter, the model shows a negative bias around −1.5 °C in the coast, while the opposite trend is observed inland. In addition, RAMS also shows good results in forecasting minimum temperatures for coastal locations, with bias lower than 1 °C and RMSE below 2 °C. However, the model presents some difficulties for this parameter inland, where bias higher than 3 °C and RMSE of about 4 °C have been found. Besides, there is little difference in both temperatures forecasted within the two daily RAMS cycles and that RAMS is very stable in maintaining the forecast performance at least for three forecast days

Effectiveness of a stepped primary care smoking cessation intervention (ISTAPS study): design of a cluster randomised trial

Background: There is a considerable body of evidence on the effectiveness of specific interventions in individuals who wish to quit smoking. However, there are no large-scale studies testing the whole range of interventions currently recommended for helping people to give up smoking; specifically those interventions that include motivational interviews for individuals who are not interested in quitting smoking in the immediate to short term. Furthermore, many of the published studies were undertaken in specialized units or by a small group of motivated primary care centres. The objective of the study is to evaluate the effectiveness of a stepped smoking cessation intervention based on a trans-theoretical model of change, applied to an extensive group of Primary Care Centres (PCC). ethods/Design: Cluster randomised clinical trial. Unit of randomization: basic unit of care consisting of a family physician and a nurse, both of whom care for the same population (aprox. 2000 people). Intention to treat analysis. Study population: Smokers (n = 3024) aged 14 to 75 years consulting for any reason to PCC and who provided written informed consent to participate in the trial. Intervention: 6-month implementation of recommendations of a Clinical Practice Guideline which includes brief motivational interviews for smokers at the precontemplation - contemplation stage, brief intervention for smokers in preparation-action who do not want help, intensive intervention with pharmacotherapy for smokers in preparation-action who want help, and reinforcing intervention in the maintenance stage. Control group: usual care. Outcome measures: Self-reported abstinence confirmed by exhaled air carbon monoxide concentration of ≤ 10 parts per million. Points of assessment: end of intervention period and 1 and 2 years post-intervention; continuous abstinence rate for 1 year; change in smoking cessation stage; health status measured by SF-36. Discussion: The application of a stepped intervention based on the stages of a change model is possible under real and diverse clinical practice conditions, and improves the smoking cessation success rate in smokers, besides of their intention or not to give up smoking at baseline

Disrupted Small-World Brain Networks in Moderate Alzheimer's Disease: A Resting-State fMRI Study

The small-world organization has been hypothesized to reflect a balance between local processing and global integration in the human brain. Previous multimodal imaging studies have consistently demonstrated that the topological architecture of the brain network is disrupted in Alzheimer's disease (AD). However, these studies have reported inconsistent results regarding the topological properties of brain alterations in AD. One potential explanation for these inconsistent results lies with the diverse homogeneity and distinct progressive stages of the AD involved in these studies, which are thought to be critical factors that might affect the results. We investigated the topological properties of brain functional networks derived from resting functional magnetic resonance imaging (fMRI) of carefully selected moderate AD patients and normal controls (NCs). Our results showed that the topological properties were found to be disrupted in AD patients, which showing increased local efficiency but decreased global efficiency. We found that the altered brain regions are mainly located in the default mode network, the temporal lobe and certain subcortical regions that are closely associated with the neuropathological changes in AD. Of note, our exploratory study revealed that the ApoE genotype modulates brain network properties, especially in AD patients

The rate of cellular hydrogen peroxide removal shows dependency on GSH: Mathematical insight into in vivo H2O2 and GPx concentrations

Although its concentration is generally not known, glutathione peroxidase-1 (GPx-1) is a key enzyme in the removal of hydrogen peroxide (H2O2) in biological systems. Extrapolating from kinetic results obtained in vitro using dilute, homogenous buffered solutions, it is generally accepted that the rate of elimination of H2O2 in vivo by GPx is independent of glutathione concentration (GSH). To examine this doctrine, a mathematical analysis of a kinetic model for the removal of H2O2 by GPx was undertaken to determine how the reaction species (H2O2, GSH, and GPx-1) influence the rate of removal of H2O2. Using both the traditional kinetic rate law approximation (classical model) and the generalized kinetic expression, the results show that the rate of removal of H2O2 increases with initial GPxr, as expected, but is a function of both GPxr and GSH when the initial GPxr is less than H2O2. This simulation is supported by the biological observations of Li et al.. Using genetically altered human glioma cells in in vitro cell culture and in an in vivo tumour model, they inferred that the rate of removal of H2O2 was a direct function of GPx activity × GSH (effective GPx activity). The predicted cellular average GPxr and H2O2 for their study are approximately GPxr ≤ 1 μm and H2O2 ≈ 5 μm based on available rate constants and an estimation of GSH. It was also found that results from the accepted kinetic rate law approximation significantly deviated from those obtained from the more generalized model in many cases that may be of physiological importance

Resting-State Multi-Spectrum Functional Connectivity Networks for Identification of MCI Patients

In this paper, a high-dimensional pattern classification framework, based on functional associations between brain regions during resting-state, is proposed to accurately identify MCI individuals from subjects who experience normal aging. The proposed technique employs multi-spectrum networks to characterize the complex yet subtle blood oxygenation level dependent (BOLD) signal changes caused by pathological attacks. The utilization of multi-spectrum networks in identifying MCI individuals is motivated by the inherent frequency-specific properties of BOLD spectrum. It is believed that frequency specific information extracted from different spectra may delineate the complex yet subtle variations of BOLD signals more effectively. In the proposed technique, regional mean time series of each region-of-interest (ROI) is band-pass filtered ( Hz) before it is decomposed into five frequency sub-bands. Five connectivity networks are constructed, one from each frequency sub-band. Clustering coefficient of each ROI in relation to the other ROIs are extracted as features for classification. Classification accuracy was evaluated via leave-one-out cross-validation to ensure generalization of performance. The classification accuracy obtained by this approach is 86.5%, which is an increase of at least 18.9% from the conventional full-spectrum methods. A cross-validation estimation of the generalization performance shows an area of 0.863 under the receiver operating characteristic (ROC) curve, indicating good diagnostic power. It was also found that, based on the selected features, portions of the prefrontal cortex, orbitofrontal cortex, temporal lobe, and parietal lobe regions provided the most discriminant information for classification, in line with results reported in previous studies. Analysis on individual frequency sub-bands demonstrated that different sub-bands contribute differently to classification, providing extra evidence regarding frequency-specific distribution of BOLD signals. Our MCI classification framework, which allows accurate early detection of functional brain abnormalities, makes an important positive contribution to the treatment management of potential AD patients

Variability in the performance of preventive services and in the degree of control of identified health problems: A primary care study protocol

Background: Preventive activities carried out in primary care have important variability that makes necessary to know which factors have an impact in order to establish future strategies for improvement. The present study has three objectives: 1) To describe the variability in the implementation of 7 preventive services (screening for smoking status, alcohol abuse, hypertension, hypercholesterolemia, obesity, influenza and tetanus immunization) and to determine their related factors; 2) To describe the degree of control of 5 identified health problems (smoking, alcohol abuse, hypertension, hypercholesterolemia and obesity); 3) To calculate intraclass correlation coefficients. Design: Multi-centered cross-sectional study of a randomised sample of primary health care teams from 3 regions of Spain designed to analyse variability and related factors of 7 selected preventive services in years 2006 and 2007. At the end of 2008, we will perform a cross-sectional study of a cohort of patients attended in 2006 or 2007 to asses the degree of control of 5 identified health problems. All subjects older than16 years assigned to a randomised sample of 22 computerized primary health care teams and attended during the study period are included in each region providing a sample with more than 850.000 subjects. The main outcome measures will be implementation of 7 preventive services and control of 5 identified health problems. Furthermore, there will be 3 levels of data collection: 1) Patient level (age, gender, morbidity, preventive services, attendance); 2) Health-care professional level (professional characteristics, years working at the team, workload); 3) Team level (characteristics, electronic clinical record system). Data will be transferred from electronic clinical records to a central database with prior encryption and dissociation of subject, professional and team identity. Global and regional analysis will be performed including standard analysis for primary health care teams and health-care professional level. Linear and logistic regression multilevel analysis adjusted for individual and cluster variables will also be performed. Variability in the number of preventive services implemented will be calculated with Poisson multilevel models. Team and health-care professional will be considered random effects. Intraclass correlation coefficients, standard error and variance components for the different outcome measures will be calculated