Cognitive and behavioral predictors of light therapy use

Objective: Although light therapy is effective in the treatment of seasonal affective disorder (SAD) and other mood disorders, only 53-79% of individuals with SAD meet remission criteria after light therapy. Perhaps more importantly, only 12-41% of individuals with SAD continue to use the treatment even after a previous winter of successful treatment. Method: Participants completed surveys regarding (1) social, cognitive, and behavioral variables used to evaluate treatment adherence for other health-related issues, expectations and credibility of light therapy, (2) a depression symptoms scale, and (3) self-reported light therapy use. Results: Individuals age 18 or older responded (n = 40), all reporting having been diagnosed with a mood disorder for which light therapy is indicated. Social support and self-efficacy scores were predictive of light therapy use (p's<.05). Conclusion: The findings suggest that testing social support and self-efficacy in a diagnosed patient population may identify factors related to the decision to use light therapy. Treatments that impact social support and self-efficacy may improve treatment response to light therapy in SAD. © 2012 Roecklein et al

Human Papillomavirus Risk Perceptions Among Young Adult Sexual Minority Cisgender Women and Nonbinary Individuals Assigned Female at Birth

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/148405/1/psrh12087_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/148405/2/psrh12087.pd

Antiseptics and disinfectants for the treatment of bacterial vaginosis: a systematic review

Background: The study objective was to assess the available data on efficacy and tolerability of antiseptics and disinfectants in treating bacterial vaginosis (BV). Methods: A systematic search was conducted by consulting PubMed (1966-2010), CINAHL (1982-2010), IPA (1970-2010), and the Cochrane CENTRAL databases. Clinical trials were searched for by the generic names of all antiseptics and disinfectants listed in the Anatomical Therapeutic Chemical (ATC) Classification System under the code D08A. Clinical trials were considered eligible if the efficacy of antiseptics and disinfectants in the treatment of BV was assessed in comparison to placebo or standard antibiotic treatment with metronidazole or clindamycin and if diagnosis of BV relied on standard criteria such as Amsel\u27s and Nugent\u27s criteria. Results: A total of 262 articles were found, of which 15 reports on clinical trials were assessed. Of these, four randomised controlled trials (RCTs) were withheld from analysis. Reasons for exclusion were primarily the lack of standard criteria to diagnose BV or to assess cure, and control treatment not involving placebo or standard antibiotic treatment. Risk of bias for the included studies was assessed with the Cochrane Collaboration\u27s tool for assessing risk of bias. Three studies showed non-inferiority of chlorhexidine and polyhexamethylene biguanide compared to metronidazole or clindamycin. One RCT found that a single vaginal douche with hydrogen peroxide was slightly, though significantly less effective than a single oral dose of metronidazole. Conclusion: The use of antiseptics and disinfectants for the treatment of BV has been poorly studied and most studies are somehow methodologically flawed. There is insufficient evidence at present to advocate the use of these agents, although some studies suggest that some antiseptics may have equal efficacy compared to clindamycin or metronidazole. Further study is warranted with special regard to the long-term efficacy and safety of antiseptics and disinfectants for vaginal use

A survey of free software for the design, analysis, modelling, and simulation of an unmanned aerial vehicle

The objective of this paper is to analyze free software for the design, analysis, modelling, and simulation of an unmanned aerial vehicle (UAV). Free software is the best choice when the reduction of production costs is necessary; nevertheless, the quality of free software may vary. This paper probably does not include all of the free software, but tries to describe or mention at least the most interesting programs. The first part of this paper summarizes the essential knowledge about UAVs, including the fundamentals of flight mechanics and aerodynamics, and the structure of a UAV system. The second section generally explains the modelling and simulation of a UAV. In the main section, more than 50 free programs for the design, analysis, modelling, and simulation of a UAV are described. Although the selection of the free software has been focused on small subsonic UAVs, the software can also be used for other categories of aircraft in some cases; e.g. for MAVs and large gliders. The applications with an historical importance are also included. Finally, the results of the analysis are evaluated and discussed—a block diagram of the free software is presented, possible connections between the programs are outlined, and future improvements of the free software are suggested. © 2015, CIMNE, Barcelona, Spain.Internal Grant Agency of Tomas Bata University in Zlin [IGA/FAI/2015/001, IGA/FAI/2014/006

Effect of carbohydrate-protein supplement timing on acute exercise-induced muscle damage

<p>Abstract</p> <p>Purpose</p> <p>To determine if timing of a supplement would have an effect on muscle damage, function and soreness.</p> <p>Methods</p> <p>Twenty-seven untrained men (21 ± 3 yrs) were given a supplement before or after exercise. Subjects were randomly assigned to a pre exercise (n = 9), received carbohydrate/protein drink before exercise and placebo after, a post exercise (n = 9), received placebo before exercise and carbohydrate/protein drink after, or a control group (n = 9), received placebo before and after exercise. Subjects performed 50 eccentric quadriceps contractions on an isokinetic dynamometer. Tests for creatine kinase (CK), maximal voluntary contraction (MVC) and muscle soreness were recorded before exercise and at six, 24, 48, 72, and 96 h post exercise. Repeated measures ANOVA were used to analyze data.</p> <p>Results</p> <p>There were no group by time interactions however, CK significantly increased for all groups when compared to pre exercise (101 ± 43 U/L) reaching a peak at 48 h (661 ± 1178 U/L). MVC was significantly reduced at 24 h by 31.4 ± 14.0%. Muscle soreness was also significantly increased from pre exercise peaking at 48 h.</p> <p>Conclusion</p> <p>Eccentric exercise caused significant muscle damage, loss of strength, and soreness; however timing of ingestion of carbohydrate/protein supplement had no effect.</p

Pancreatic Transcription Factors Containing Protein Transduction Domains Drive Mouse Embryonic Stem Cells towards Endocrine Pancreas

Protein transduction domains (PTDs), such as the HIV1-TAT peptide, have been previously used to promote the uptake of proteins into a range of cell types, including stem cells. Here we generated pancreatic transcription factors containing PTD sequences and administered these to endoderm enriched mouse embryonic stem (ES) cells under conditions that were designed to mimic the pattern of expression of these factors in the developing pancreas. The ES cells were first cultured as embryoid bodies and treated with Activin A and Bone morphogenetic protein 4 (BMP4) to promote formation of definitive endoderm. Cells were subsequently plated as a monolayer and treated with different combinations of the modified recombinant transcription factors Pdx1 and MafA. The results demonstrate that each transcription factor was efficiently taken up by the cells, where they were localized in the nuclei. RT-qPCR was used to measure the expression levels of pancreatic markers. After the addition of Pdx1 alone for a period of five days, followed by the combination of Pdx1 and TAT-MafA in a second phase, up-regulation of insulin 1, insulin 2, Pdx1, Glut2, Pax4 and Nkx6.1 was observed. As assessed by immunocytochemistry, double positive insulin and Pdx1 cells were detected in the differentiated cultures. Although the pattern of pancreatic markers expression in these cultures was comparable to that of a mouse transformed β-cell line (MIN-6) and human islets, the expression levels of insulin observed in the differentiated ES cell cultures were several orders of magnitude lower. This suggests that, although PTD-TFs may prove useful in studying the role of exogenous TFs in the differentiation of ES cells towards islets and other pancreatic lineages, the amount of insulin generated is well below that required for therapeutically useful cells

Clustering of metabolic syndrome components in a Middle Eastern diabetic and non-diabetic population

<p>Abstract</p> <p>Background</p> <p>Metabolic syndrome (MetS) encompasses a cluster of coronary heart disease and diabetes mellitus risk factors. In this study, we aimed to elucidate the factors underlying the clustering of MetS components in diabetic and non-diabetic individuals.</p> <p>Methods</p> <p>Factor analysis was performed on 2978 (1652 non-diabetic and 1326 diabetic) participants. Entering waist circumference, homeostasis model assessment of insulin resistance (HOMA-IR), triglycerides, high-density lipoprotein-cholesterol (HDL-C) and systolic blood pressure (SBP), we performed exploratory factor analysis in diabetic and non-diabetic individuals separately. The analysis was repeated after replacing triglycerides and HDL-C with triglycerides to HDL-C ratio (triglycerides/HDL-C). MetS was defined by either adult treatment panel III (ATPIII), international diabetes federation (IDF) criteria, or by the modified form of IDF using waist circumference cut-off points for Iranian population.</p> <p>Results</p> <p>The selection of triglycerides and HDL-C as two distinct variables led to identifying two factors explaining 61.3% and 55.4% of the total variance in non-diabetic and diabetic participants, respectively. In both diabetic and non-diabetic subjects, waist circumference, HOMA-IR and SBP loaded on factor 1. Factor 2 was mainly determined by triglycerides and HDL-C. Factor 1 and 2 were directly and inversely associated with MetS, respectively. When triglycerides and HDL-C were replaced by triglycerides/HDL-C, one factor was extracted, which explained 47.6% and 38.8% of the total variance in non-diabetic and diabetic participants, respectively.</p> <p>Conclusion</p> <p>This study confirms that in both diabetic and non-diabetic participants the concept of a single underlying factor representing MetS is plausible.</p

Pathogen-induced hatching and population-specific life-history response to water-borne cues in brown trout (Salmo trutta)

Hatching is an important niche shift, and embryos in a wide range of taxa can either accelerate or delay this life-history switch in order to avoid stage-specific risks. Such behavior can occur in response to stress itself and to chemical cues that allow anticipation of stress. We studied the genetic organization of this phenotypic plasticity and tested whether there are differences among populations and across environments in order to learn more about the evolutionary potential of stress-induced hatching. As a study species, we chose the brown trout (Salmo trutta; Salmonidae). Gametes were collected from five natural populations (within one river network) and used for full-factorial in vitro fertilizations. The resulting embryos were either directly infected with Pseudomonas fluorescens or were exposed to waterborne cues from P. fluorescens-infected conspecifics. We found that direct inoculation with P. fluorescens increased embryonic mortality and induced hatching in all host populations. Exposure to waterborne cues revealed population-specific responses. We found significant additive genetic variation for hatching time, and genetic variation in trait plasticity. In conclusion, hatching is induced in response to infection and can be affected by waterborne cues of infection, but populations and families differ in their reaction to the latter

The Shark Assemblage at French Frigate Shoals Atoll, Hawai‘i: Species Composition, Abundance and Habitat Use

Empirical data on the abundance and habitat preferences of coral reef top predators are needed to evaluate their ecological impacts and guide management decisions. We used longline surveys to quantify the shark assemblage at French Frigate Shoals (FFS) atoll from May to August 2009. Fishing effort consisted of 189 longline sets totaling 6,862 hook hours of soak time. A total of 221 sharks from 7 species were captured, among which Galapagos (Carcharhinus galapagensis, 36.2%), gray reef (Carcharhinus amblyrhynchos, 25.8%) and tiger (Galeocerdo cuvier, 20.4%) sharks were numerically dominant. A lack of blacktip reef sharks (Carcharhinus melanopterus) distinguished the FFS shark assemblage from those at many other atolls in the Indo-Pacific. Compared to prior underwater visual survey estimates, longline methods more accurately represented species abundance and composition for the majority of shark species. Sharks were significantly less abundant in the shallow lagoon than adjacent habitats. Recaptures of Galapagos sharks provided the first empirical estimate of population size for any Galapagos shark population. The overall recapture rate was 5.4%. Multiple closed population models were evaluated, with Chao Mh ranking best in model performance and yielding a population estimate of 668 sharks with 95% confidence intervals ranging from 289–1720. Low shark abundance in the shallow lagoon habitats suggests removal of a small number of sharks from the immediate vicinity of lagoonal islets may reduce short-term predation on endangered monk seal (Monachus schauinslandi) pups, but considerable fishing effort would be required to catch even a small number of sharks. Additional data on long-term movements and habitat use of sharks at FFS are required to better assess the likely ecological impacts of shark culling

A comparison of machine learning algorithms for chemical toxicity classification using a simulated multi-scale data model

<p>Abstract</p> <p>Background</p> <p>Bioactivity profiling using high-throughput <it>in vitro </it>assays can reduce the cost and time required for toxicological screening of environmental chemicals and can also reduce the need for animal testing. Several public efforts are aimed at discovering patterns or classifiers in high-dimensional bioactivity space that predict tissue, organ or whole animal toxicological endpoints. Supervised machine learning is a powerful approach to discover combinatorial relationships in complex <it>in vitro/in vivo </it>datasets. We present a novel model to simulate complex chemical-toxicology data sets and use this model to evaluate the relative performance of different machine learning (ML) methods.</p> <p>Results</p> <p>The classification performance of Artificial Neural Networks (ANN), K-Nearest Neighbors (KNN), Linear Discriminant Analysis (LDA), Naïve Bayes (NB), Recursive Partitioning and Regression Trees (RPART), and Support Vector Machines (SVM) in the presence and absence of filter-based feature selection was analyzed using K-way cross-validation testing and independent validation on simulated <it>in vitro </it>assay data sets with varying levels of model complexity, number of irrelevant features and measurement noise. While the prediction accuracy of all ML methods decreased as non-causal (irrelevant) features were added, some ML methods performed better than others. In the limit of using a large number of features, ANN and SVM were always in the top performing set of methods while RPART and KNN (k = 5) were always in the poorest performing set. The addition of measurement noise and irrelevant features decreased the classification accuracy of all ML methods, with LDA suffering the greatest performance degradation. LDA performance is especially sensitive to the use of feature selection. Filter-based feature selection generally improved performance, most strikingly for LDA.</p> <p>Conclusion</p> <p>We have developed a novel simulation model to evaluate machine learning methods for the analysis of data sets in which in vitro bioassay data is being used to predict in vivo chemical toxicology. From our analysis, we can recommend that several ML methods, most notably SVM and ANN, are good candidates for use in real world applications in this area.</p