Increase in circulating endothelial progenitor cells by statin therapy in patients with stable coronary artery disease

Background - Therapeutic neovascularization may constitute an important strategy to salvage tissue from critical ischemia. Circulating bone marrow–derived endothelial progenitor cells (EPCs) were shown to augment the neovascularization of ischemic tissue. In addition to lipid-lowering activity, hydroxymethyl glutaryl coenzyme A reductase inhibitors (statins) reportedly promote the neovascularization of ischemic tissue in normocholesterolemic animals. Methods and Results - Fifteen patients with angiographically documented stable coronary artery disease (CAD) were prospectively treated with 40 mg of atorvastatin per day for 4 weeks. Before and weekly after the initiation of statin therapy, EPCs were isolated from peripheral blood and counted. In addition, the number of hematopoietic precursor cells positive for CD34, CD133, and CD34/kinase insert domain receptor was analyzed. Statin treatment of patients with stable CAD was associated with an '1.5-fold increase in the number of circulating EPCs by 1 week after initiation of treatment; this was followed by sustained increased levels to '3-fold throughout the 4-week study period. Moreover, the number of CD34/kinase insert domain receptor–positive hematopoietic progenitor cells was significantly augmented after 4 weeks of therapy. Atorvastatin treatment increased the further functional activity of EPCs, as assessed by their migratory capacity

Systems approach to microbial pathogenesis: complex patterns emerge from simple interactions

Biological organisms are complex systems and modeling can provide insight into their behavior by the process of recreating it. All elements may not be known of the system under study and thus, hypotheses must be made in order to create an appropriate model. These hypotheses can lead to interesting modeling results and help guide in vitro experiments. However, modeling complexity does not necessarily require complex techniques. By modeling the simplest elements of a biological system and by defining how the elements interact, it is possible to model complex behavior as emergent properties of the system. In this manner, I model simple interactions between biological elements. First, at the lowest level of complexity, is a single molecule such as an RNA. Determining RNA secondary structure is a necessary step to understand how it interacts with other molecules to affect the biological system as a whole. The structure of an RNA is formed through simple interactions between nucleotides. I developed software that aids the process of identifying sites in an RNA where nucleotide-nucleotide or nucleotide-protein binding occurs to predict RNA secondary structure more accurately. The next level of complexity is molecule-molecule interactions that result in the emergence of patterns within an organism, such as phenotypes expressed by a cell. Using agent-based modeling, I model the proteins, RNAs, and enzymes involved in a gene regulatory network that is responsible for the emergence of the competence phenotype in Bacillus subtilis. Competence is stochastically expressed due to the variable expression of genes. My agent-based model identified several possible sources for this variation: dilution events like cell division, inheritance of molecules involved in competence and most importantly, spatial temporal interactions of molecules. And lastly, I model the simple interactions between two organisms, a virus and a host cell, to understand the molecular interactions between host and pathogen that result in the replication and assembly of a virus. In this model, I successfully modeled the self-assembly of BK Virus using an agent-based model that models from transcription to translation to the encapsidation of the BKV genome within a T=7, icosahedral structure all by simple molecule-molecule interactions

Possible Sources of Bias in Primary Care Electronic Health Record Data Use and Reuse

Background - Enormous amounts of data are recorded routinely in health care as part of the care process, primarily for managing individual patient care. There are significant opportunities to use this data for other purposes, many of which would contribute to establishing a learning health system. This is particularly true for data recorded in primary care settings, as in many countries, these are the first place patients turn to for most health problems. Objective - In this paper, we discuss whether data that is recorded routinely as part of the health care process in primary care is actually fit to use for these other purposes, how the original purpose may affect the extent to which the data is fit for another purpose and the mechanisms behind these effects. In doing so, we want to identify possible sources of bias that are relevant for the (re-)use of this type of data. Methods –This discussion paper is based on the authors’ experience as users of electronic health records data, as a general practitioner, health informatics experts, and health services researchers. It is a product of the discussions they had during the TRANSFoRm project, which was funded by the EU and sought to develop, pilot and evaluate a core information architecture for the Learning Health System (LHS) in Europe, based on primary care electronic health records. Results – We first describe the different stages in the processing of EHR data, as well as the different purposes for which this data is used. Given the different data processing steps and purposes, we then discuss the possible mechanisms for each individual data processing step, that can generate biased outcomes. We identified thirteen possible sources of bias. Four of them are related to the organization of a health care system, some are of a more technical nature. Conclusions - There are a substantial number of possible sources of bias, and very little is known about the size and direction of their impact. However, any (re-)user of data that was recorded as part of the health care process (such as researchers and clinicians) should be aware of the associated data collection process and environmental influences that can affect the quality of the data. Our stepwise, actor and purpose oriented approach may help to identify these possible sources of bias. Unless data quality issues are better understood and unless adequate controls are embedded throughout the data lifecycle, data-driven healthcare will not live up to its expectations. We need a data quality research agenda to devise the appropriate instruments needed to assess the magnitude of each of the possible sources of bias, and then start measuring their impact. The possible sources of bias described in this paper serve as a starting point for this research agenda

Access to side-chain carbon information in deuterated solids under fast MAS through non-rotor-synchronized mixing.

We demonstrate the accessibility of aliphatic 13C side chain chemical shift sets for solid-state NMR despite perdeuteration and fast MAS using isotropic, non-rotor-synchronized 13C-13C mixing. Combined with amide proton detection, we unambiguously and sensitively detect whole side chain to backbone correlations for two proteins using around 1 mg of sample

Nutritional risk index is a better predictor of early mortality than conventional nutritional markers after transcatheter aortic valve replacement: A prospective cohort study

Background: Nutritional risk index (NRI) has been shown to better predict survival than body mass index (BMI) or albumin after several cardiovascular interventions. Under assessment herein is whether NRI can have higher predictive value than conventional parameters for short-term survival after transcatheter aortic valve replacement (TAVR).Methods: A prospective cohort study was performed. In-hospital, 1-month and 3-month survival was evaluated. Since most patients undergoing TAVR are over 65, the NRI definition for a geriatric population (GNRI) was used. The impact of baseline BMI, albumin levels, and GNRI on in-hospital and short-term survival was assessed.Results: One hundred fifty two patients aged 82 ± 5.4 were included. In-hospital, 1-month, and 3-month mortality was 5.3%, 5.9%, and 9.2%, respectively. Mean GNRI was 112.7 ± 11.9, and was significantly lower in patients who died in-hospital (101.0 ± 8.8 vs. 113.3 ± 11.7), at 30 days (103.4 ± 10.9 vs. 113.3 ± 11.7), and at 90 days (104.0 ± 9.6 vs. 113.6 ± 11.8) than in survivors (all, p < 0.05). Three-month mortality in patients with no nutritional risk was 6.8% (9/132) vs. 25% (5/20) in patients with malnutrition (p = 0.022). In univariate analysis, GNRI predicted in-hospital, 30-day, and 90-day mortality (all, p < 0.05). Predictive value remained significant after adjusting for age, EuroSCORE II, and STS-Score (p < 0.05). Based on receiver operating curves, GNRI (AUC: 0.73) showed a betterdiscrimination for 3-month mortality than albumin (0.69), weight (0.67) or BMI (0.62). The optimal cut-off value was 109.8.Conclusions: The geriatric nutritional risk index predicts short-term mortality after TAVR and has a higher discriminating ability than other commonly used nutritional variables. It is a simple parameter that identifies those patients who could benefit from pre-procedural nutritional therapy

Conservative and disruptive modes of adolescent change in human brain functional connectivity

Adolescent changes in human brain function are not entirely understood. Here, we used multiecho functional MRI (fMRI) to measure developmental change in functional connectivity (FC) of resting-state oscillations between pairs of 330 cortical regions and 16 subcortical regions in 298 healthy adolescents scanned 520 times. Participants were aged 14 to 26 y and were scanned on 1 to 3 occasions at least 6 mo apart. We found 2 distinct modes of age-related change in FC: “conservative” and “disruptive.” Conservative development was characteristic of primary cortex, which was strongly connected at 14 y and became even more connected in the period from 14 to 26 y. Disruptive development was characteristic of association cortex and subcortical regions, where connectivity was remodeled: connections that were weak at 14 y became stronger during adolescence, and connections that were strong at 14 y became weaker. These modes of development were quantified using the maturational index (MI), estimated as Spearman’s correlation between edgewise baseline FC (at 14 y, FC14) and adolescent change in FC (ΔFC14−26), at each region. Disruptive systems (with negative MI) were activated by social cognition and autobiographical memory tasks in prior fMRI data and significantly colocated with prior maps of aerobic glycolysis (AG), AG-related gene expression, postnatal cortical surface expansion, and adolescent shrinkage of cortical thickness. The presence of these 2 modes of development was robust to numerous sensitivity analyses. We conclude that human brain organization is disrupted during adolescence by remodeling of FC between association cortical and subcortical areas

Indications and trends of caesarean birth delivery in the current practice scenario

Background: Objective of current study was to analyze incidence, indications and trends of cesarean birth delivery in our environment.Methods: A prospective study of the cesarean sections performed at V.S. general teaching hospital in Ahmedabad from January 2008 to December 2013Results: Out of 28,411 total deliveries, 11629 women underwent CS. Each year the CS rate, above 40%, was relatively constant. 72.46% patients were within 20-29 years of age group. 39% patients were from middle to higher socio-economic class. CS in emergency patient was consistently more than 50% and in registered patient around 40%. Maternal indications for CS were twice common to fetal indications. Previous CS and fetal distress were the commonest among maternal and fetal indications respectively. Overall maternal morbidity in CS ranged from 8-10%, commonest being blood transfusion and wound infection. Neonatal morbidity was less than half and neonatal mortality was almost one third in comparison to normal delivery. Rising CS trend was noted in patients with previous CS, fetal distress, oligohydramnios and failed induction. Gradual but constant decline in CS rate was noted among emergency patients, patient with CPD, obstructed labor and PROM.Conclusions: Although to some extent higher CS rate is justifiable due to remarkable reduction in neonatal mortality and morbidity in high risk patients; the CS rate in our environment is still three times higher than WHO recommendation. In controlled environment with experienced staff, careful selection of patients for normal delivery among patients with previous CS, breech presentation and scientific induction of labor may satisfy our concern for mother and newborn safety while keeping the CS rate low

Protective role of natural and semi-synthetic tocopherols on TNFα-induced ros production and ICAM-1 and Cl-2 expression in ht29 intestinal epithelial cells

Vitamin E, a fat-soluble compound, possesses both antioxidant and non-antioxidant properties. In this study we evaluated, in intestinal HT29 cells, the role of natural tocopherols, α-Toc and δ-Toc, and two semi-synthetic derivatives, namely bis-δ-Toc sulfide (δ-Toc)2S and bis-δ-Toc disulfide (δ-Toc)2S2, on TNFα-induced oxidative stress, and intercellular adhesion molecule-1 (ICAM-1) and claudin-2 (Cl-2) expression. The role of tocopherols was compared to that of N-acetylcysteine (NAC), an antioxidant precursor of glutathione synthesis. The results show that all tocopherol containing derivatives used, prevented TNFα-induced oxidative stress and the increase of ICAM-1 and Cl-2 expression, and that (δ-Toc)2S and (δ-Toc)2S2 are more effective than δ-Toc and α-Toc. The beneficial effects demonstrated were due to tocopherol antioxidant properties, but suppression of TNFα-induced Cl-2 expression seems not only to be related with antioxidant ability. Indeed, while ICAM-1 expression is strongly related to the intracellular redox state, Cl-2 expression is TNFα-up-regulated by both redox and non-redox dependent mechanisms. Since ICAM-1 and Cl-2 increase intestinal bowel diseases, and cause excessive recruitment of immune cells and alteration of the intestinal barrier, natural and, above all, semi-synthetic tocopherols may have a potential role as a therapeutic support against intestinal chronic inflammation, in which TNFα represents an important proinflammatory mediator

State-Based Markers of Disordered Eating Symptom Severity

Recent work using naturalistic, repeated, ambulatory assessment approaches have uncovered a range of within-person mood- and body image-related dynamics (such as fluctuation of mood and body dissatisfaction) that can prospectively predict eating disorder behaviors (e.g., a binge episode following an increase in negative mood). The prognostic significance of these state-based dynamics for predicting trait-level eating disorder severity, however, remains largely unexplored. The present study uses within-person relationships among state levels of negative mood, body image, and dieting as predictors of baseline, trait-level eating pathology, captured prior to a period of state-based data capture. Two-hundred and sixty women from the general population completed baseline measures of trait eating pathology and demographics, followed by a 7 to 10-day ecological momentary assessment phase comprising items measuring state body dissatisfaction, negative mood, upward appearance comparisons, and dietary restraint administered 6 times daily. Regression-based analyses showed that, in combination, state-based dynamics accounted for 34-43% variance explained in trait eating pathology, contingent on eating disorder symptom severity. Present findings highlight the viability of within-person, state-based dynamics as predictors of baseline trait-level disordered eating severity. Longitudinal testing is needed to determine whether these dynamics account for changes in disordered eating over time

High-Throughput SHAPE Analysis Reveals Structures in HIV-1 Genomic RNA Strongly Conserved across Distinct Biological States

Replication and pathogenesis of the human immunodeficiency virus (HIV) is tightly linked to the structure of its RNA genome, but genome structure in infectious virions is poorly understood. We invent high-throughput SHAPE (selective 2′-hydroxyl acylation analyzed by primer extension) technology, which uses many of the same tools as DNA sequencing, to quantify RNA backbone flexibility at single-nucleotide resolution and from which robust structural information can be immediately derived. We analyze the structure of HIV-1 genomic RNA in four biologically instructive states, including the authentic viral genome inside native particles. Remarkably, given the large number of plausible local structures, the first 10% of the HIV-1 genome exists in a single, predominant conformation in all four states. We also discover that noncoding regions functioning in a regulatory role have significantly lower (p-value < 0.0001) SHAPE reactivities, and hence more structure, than do viral coding regions that function as the template for protein synthesis. By directly monitoring protein binding inside virions, we identify the RNA recognition motif for the viral nucleocapsid protein. Seven structurally homologous binding sites occur in a well-defined domain in the genome, consistent with a role in directing specific packaging of genomic RNA into nascent virions. In addition, we identify two distinct motifs that are targets for the duplex destabilizing activity of this same protein. The nucleocapsid protein destabilizes local HIV-1 RNA structure in ways likely to facilitate initial movement both of the retroviral reverse transcriptase from its tRNA primer and of the ribosome in coding regions. Each of the three nucleocapsid interaction motifs falls in a specific genome domain, indicating that local protein interactions can be organized by the long-range architecture of an RNA. High-throughput SHAPE reveals a comprehensive view of HIV-1 RNA genome structure, and further application of this technology will make possible newly informative analysis of any RNA in a cellular transcriptome