Late-adolescent risk factors for suicide and self-harm in middle-aged men: explorative prospective population-based study

BackgroundRecent reports show alarmingly high rates of suicide in middle-aged men, yet there are few long-term prospective studies that focus on suicidal behaviour in men in this age group.AimsTo prospectively explore associations of potential risk factors at age 18 with suicide and self-harm in middle-aged men.MethodA population-based Swedish longitudinal cohort study of male conscripts with no history of self-harm at enlistment in 1968–1989 (n= 987 583). Conscription examinations included measures of cognitive performance, stress resilience, psychiatric diagnoses, body mass index (BMI), cardiovascular fitness and muscle strength. Suicides and self-harm at age 45–65 years were identified in the National Hospital Register and Swedish Cause of Death Register. Risks were calculated using Cox proportional hazards models.ResultsLow stress resilience (cause-specific hazard ratio CHR = 2.31, 95% CI 1.95–2.74), low cognitive ability (CHR = 2.01, 95% CI 1.71–2.37) as well as psychiatric disorders and low cardiovascular fitness in late adolescence were associated with increased risk for suicide in middle-aged men. Similar risk estimates were obtained for self-harm. In addition, high and low BMI as well as low muscle strength were associated with increased risk of self-harm. Associations also remained significant after exclusion of men with self-harm before age 45.ConclusionsThis prospective study provides life-course perspective support that psychological and physical characteristics in late adolescence may have long-lasting consequences for suicidal behaviour in middle-aged men, a very large population at heightened risk of suicide

Detecting Bacteria on Wounds with Hyperspectral Imaging in Fluorescence Mode

Chronic non-healing wounds represent an increasing problem. In order to enable physicians and nurses to make evidence based decisions on wound treatment, the professional societies call for supporting tools to be offered to physicians. Oxygen supply, bacteria colonization and other parameters influence the healing process. So far, these parameters cannot be monitored in an objective and routinely manner. Existing methods like the microbiological analysis of wound swabs, mean a great deal of effort and partly a long delay. In this paper 42 fluorescence images from 42 patients with diabetic foot ulcer, recorded with a hyperspectral imaging system (TIVITA®), converted for fluorescence imaging, were analysed. Beside the fluorescence images, information about the bacterial colonization is available from microbiological analysis of wound swabs. After preprocessing, principal component analysis, PCA, is used for data analysis with a 405 nm excitation wavelength, the emission wavelength range 510 - 745 nm is used for analysis. After dividing the data into a training and a test dataset it could be shown, that bacteria are detectable in the wound area. A quantification in bacterial colonization counts (BCC) was not in the focus of the research in this study stage

Applications and data analysis of next-generation sequencing

Over the past 6 years, next-generation sequencing (NGS) has been established as a valuable high-throughput method for research in molecular genetics and has successfully been employed in the identification of rare and common genetic variations. Although the high expectations regarding the discovery of new diagnostic targets and an overall reduction of cost have been achieved, technological challenges in instrument handling, robustness of the chemistry, and data analysis need to be overcome. Each workflow and sequencing platform have their particular problems and caveats, which need to be addressed. Regarding NGS, there is a variety of different enrichment methods, sequencing devices, or technologies as well as a multitude of analyzing software products available. In this manuscript, the authors focus on challenges in data analysis when employing different target enrichment methods and the best applications for each of the

Diagnostic applications of next generation sequencing: working towards quality standards

Over the past 6 years, next generation sequencing (NGS) has been established as a valuable high-throughput method for research in molecular genetics and has successfully been employed in the identification of rare and common genetic variations. All major NGS technology companies providing commercially available instruments (Roche 454, Illumina, Life Technologies) have recently marketed bench top sequencing instruments with lower throughput and shorter run times, thereby broadening the applications of NGS and opening the technology to the potential use for clinical diagnostics. Although the high expectations regarding the discovery of new diagnostic targets and an overall reduction of cost have been achieved, technological challenges in instrument handling, robustness of the chemistry and data analysis need to be overcome. To facilitate the implementation of NGS as a routine method in molecular diagnostics, consistent quality standards need to be developed. Here the authors give an overview of the current standards in protocols and workflows and discuss possible approaches to define quality criteria for NGS in molecular genetic diagnostics

Network Neighbors of Drug Targets Contribute to Drug Side-Effect Similarity

In pharmacology, it is essential to identify the molecular mechanisms of drug action in order to understand adverse side effects. These adverse side effects have been used to infer whether two drugs share a target protein. However, side-effect similarity of drugs could also be caused by their target proteins being close in a molecular network, which as such could cause similar downstream effects. In this study, we investigated the proportion of side-effect similarities that is due to targets that are close in the network compared to shared drug targets. We found that only a minor fraction of side-effect similarities (5.8 %) are caused by drugs targeting proteins close in the network, compared to side-effect similarities caused by overlapping drug targets (64%). Moreover, these targets that cause similar side effects are more often in a linear part of the network, having two or less interactions, than drug targets in general. Based on the examples, we gained novel insight into the molecular mechanisms of side effects associated with several drug targets. Looking forward, such analyses will be extremely useful in the process of drug development to better understand adverse side effects

Optimal assignment methods for ligand-based virtual screening

<p>Abstract</p> <p>Background</p> <p>Ligand-based virtual screening experiments are an important task in the early drug discovery stage. An ambitious aim in each experiment is to disclose active structures based on new scaffolds. To perform these "scaffold-hoppings" for individual problems and targets, a plethora of different similarity methods based on diverse techniques were published in the last years. The optimal assignment approach on molecular graphs, a successful method in the field of quantitative structure-activity relationships, has not been tested as a ligand-based virtual screening method so far.</p> <p>Results</p> <p>We evaluated two already published and two new optimal assignment methods on various data sets. To emphasize the "scaffold-hopping" ability, we used the information of chemotype clustering analyses in our evaluation metrics. Comparisons with literature results show an improved early recognition performance and comparable results over the complete data set. A new method based on two different assignment steps shows an increased "scaffold-hopping" behavior together with a good early recognition performance.</p> <p>Conclusion</p> <p>The presented methods show a good combination of chemotype discovery and enrichment of active structures. Additionally, the optimal assignment on molecular graphs has the advantage to investigate and interpret the mappings, allowing precise modifications of internal parameters of the similarity measure for specific targets. All methods have low computation times which make them applicable to screen large data sets.</p

Synergetic Effects of Granulocyte-Colony Stimulating Factor and Cognitive Training on Spatial Learning and Survival of Newborn Hippocampal Neurons

Granulocyte-Colony Stimulating Factor (G-CSF) is an endogenous hematopoietic growth factor known for its role in the proliferation and differentiation of cells of the myeloic lineage. Only recently its significance in the CNS has been uncovered. G-CSF attenuates apoptosis and controls proliferation and differentiation of neural stem cells. G-CSF activates upstream kinases of the cAMP response element binding protein (CREB), which is thought to facilitate the survival of neuronal precursors and to recruit new neurons into the dentate gyrus. CREB is also essential for spatial long-term memory formation. To assess the role and the potential of this factor on learning and memory-formation we systemically administered G-CSF in rats engaged in spatial learning in an eight-arm radial maze. G-CSF significantly improved spatial learning and increased in combination with cognitive training the survival of newborn neurons in the hippocampus as measured by bromodeoxyuridine and doublecortin immunohistochemistry. Additionally, G-CSF improved re-acquisition of spatial information after 26 days. These findings support the hypothesis that G-CSF can enhance learning and memory formation. Due to its easy applicability and its history as a well-tolerated hematological drug, the use of G-CSF opens up new neurological treatment opportunities in conditions where learning and memory-formation deficits occur

Identification of 12 new susceptibility loci for different histotypes of epithelial ovarian cancer.

To identify common alleles associated with different histotypes of epithelial ovarian cancer (EOC), we pooled data from multiple genome-wide genotyping projects totaling 25,509 EOC cases and 40,941 controls. We identified nine new susceptibility loci for different EOC histotypes: six for serous EOC histotypes (3q28, 4q32.3, 8q21.11, 10q24.33, 18q11.2 and 22q12.1), two for mucinous EOC (3q22.3 and 9q31.1) and one for endometrioid EOC (5q12.3). We then performed meta-analysis on the results for high-grade serous ovarian cancer with the results from analysis of 31,448 BRCA1 and BRCA2 mutation carriers, including 3,887 mutation carriers with EOC. This identified three additional susceptibility loci at 2q13, 8q24.1 and 12q24.31. Integrated analyses of genes and regulatory biofeatures at each locus predicted candidate susceptibility genes, including OBFC1, a new candidate susceptibility gene for low-grade and borderline serous EOC

Metabolic profiling identifies trehalose as an abundant and diurnally fluctuating metabolite in the microalga Ostreococcus tauri

© 2017, The Author(s).Introduction: The picoeukaryotic alga Ostreococcus tauri (Chlorophyta) belongs to the widespread group of marine prasinophytes. Despite its ecological importance, little is known about the metabolism of this alga. Objectives: In this work, changes in the metabolome were quantified when O. tauri was grown under alternating cycles of 12 h light and 12 h darkness. Methods: Algal metabolism was analyzed by gas chromatography-mass spectrometry. Using fluorescence-activated cell sorting, the bacteria associated with O. tauri were depleted to below 0.1% of total cells at the time of metabolic profiling. Results: Of 111 metabolites quantified over light–dark cycles, 20 (18%) showed clear diurnal variations. The strongest fluctuations were found for trehalose. With an intracellular concentration of 1.6 mM in the dark, this disaccharide was six times more abundant at night than during the day. This fluctuation pattern of trehalose may be a consequence of starch degradation or of the synchronized cell cycle. On the other hand, maltose (and also sucrose) was below the detection limit (~10 μM). Accumulation of glycine in the light is in agreement with the presence of a classical glycolate pathway of photorespiration. We also provide evidence for the presence of fatty acid methyl and ethyl esters in O. tauri. Conclusions: This study shows how the metabolism of O. tauri adapts to day and night and gives new insights into the configuration of the carbon metabolism. In addition, several less common metabolites were identified