Predicting suicides after outpatient mental health visits in the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS).

The 2013 US Veterans Administration/Department of Defense Clinical Practice Guidelines (VA/DoD CPG) require comprehensive suicide risk assessments for VA/DoD patients with mental disorders but provide minimal guidance on how to carry out these assessments. Given that clinician-based assessments are not known to be strong predictors of suicide, we investigated whether a precision medicine model using administrative data after outpatient mental health specialty visits could be developed to predict suicides among outpatients. We focused on male nondeployed Regular US Army soldiers because they account for the vast majority of such suicides. Four machine learning classifiers (naive Bayes, random forests, support vector regression and elastic net penalized regression) were explored. Of the Army suicides in 2004-2009, 41.5% occurred among 12.0% of soldiers seen as outpatient by mental health specialists, with risk especially high within 26 weeks of visits. An elastic net classifier with 10-14 predictors optimized sensitivity (45.6% of suicide deaths occurring after the 15% of visits with highest predicted risk). Good model stability was found for a model using 2004-2007 data to predict 2008-2009 suicides, although stability decreased in a model using 2008-2009 data to predict 2010-2012 suicides. The 5% of visits with highest risk included only 0.1% of soldiers (1047.1 suicides/100 000 person-years in the 5 weeks after the visit). This is a high enough concentration of risk to have implications for targeting preventive interventions. An even better model might be developed in the future by including the enriched information on clinician-evaluated suicide risk mandated by the VA/DoD CPG to be recorded

The re-emergence of natural products for drug discovery in the genomics era

Natural products have been a rich source of compounds for drug discovery. However, their use has diminished in the past two decades, in part because of technical barriers to screening natural products in high-throughput assays against molecular targets. Here, we review strategies for natural product screening that harness the recent technical advances that have reduced these barriers. We also assess the use of genomic and metabolomic approaches to augment traditional methods of studying natural products, and highlight recent examples of natural products in antimicrobial drug discovery and as inhibitors of protein-protein interactions. The growing appreciation of functional assays and phenotypic screens may further contribute to a revival of interest in natural products for drug discovery

A tree without leaves

The puzzle presented by the famous stumps of Gilboa, New York, finds a solution in the discovery of two fossil specimens that allow the entire structure of these early trees to be reconstructed

Functional characterization of a 28-Kilobase Catabolic Island from Pseudomonas sp. Strain M1 involved in biotransformation of β-Myrcene and related plant-derived volatiles

Pseudomonas sp. strain M1 is able to mineralize highly hydrophobic and recalcitrant compounds, such as benzene, phenol, and their methylated/halogenated derivatives, as well as the backbone of several monoterpenes. The ability to use such a spectrum of compounds as the sole carbon source is, most probably, associated with a genetic background evolved under different environmental constraints. The outstanding performance of strain M1 regarding β-myrcene catabolism was elucidated in this work, with a focus on the biocatalytical potential of the β-myrcene-associated core code, comprised in a 28-kb genomic island (GI), predicted to be organized in 8 transcriptional units. Functional characterization of this locus with promoter probes and analytical approaches validated the genetic organization predictedin silicoand associated the β-myrcene-induced promoter activity to the production of β-myrcene derivatives. Notably, by using a whole-genome mutagenesis strategy, different genotypes of the 28-kb GI were generated, resulting in the identification of a novel putative β-myrcene hydroxylase, responsible for the initial oxidation of β-myrcene into myrcen-8-ol, and a sensor-like regulatory protein, whose inactivation abolished themyr + trait of M1 cells. Moreover, it was demonstrated that the range of monoterpene substrates of the M1 enzymatic repertoire, besides β-myrcene, also includes other acyclic (e.g., β-linalool) and cyclic [e.g.,R-(+)-limonene and (-)-β-pinene] molecules. Our findings are the cornerstone for following metabolic engineering approaches and hint at a major role of the 28-kb GI in the biotransformation of a broad monoterpene backbone spectrum for its future biotechnological applications.IMPORTANCEInformation regarding microbial systems able to biotransform monoterpenes, especially β-myrcene, is limited and focused mainly on nonsystematic metabolite identification. Complete and detailed knowledge at the genetic, protein, metabolite, and regulatory levels is essential in order to set a model organism or a catabolic system as a biotechnology tool. Moreover, molecular characterization of reported systems is scarce, almost nonexistent, limiting advances in the development of optimized cell factories with strategies based on the new generation of metabolic engineering platforms. This study provides new insights into the intricate molecular functionalities associated with β-myrcene catabolism inPseudomonas, envisaging the production of a molecular knowledge base about the underlying catalytic and regulatory mechanisms of plant-derived volatile catabolic pathways.Vectors from the Standard European Vector Architecture (SEVA) library and pBAM1 used in this work were kindly provided by Victor de Lorenzo (CNB-CSIC, Madrid, Spain). This work was supported by the strategic program UID/BIA/04050/2013 (POCI-01- 0145-FEDER-007569) funded by national funds through the FCT I.P. and by the ERDF through the COMPETE2020-Programa Operacional Competitividade e Internacionalização (POCI) and through a Ph.D. grant (grant SFRH/BD/76894/2011) to P.S.-C.info:eu-repo/semantics/publishedVersio

Decision tree supported substructure prediction of metabolites from GC-MS profiles

Gas chromatography coupled to mass spectrometry (GC-MS) is one of the most widespread routine technologies applied to the large scale screening and discovery of novel metabolic biomarkers. However, currently the majority of mass spectral tags (MSTs) remains unidentified due to the lack of authenticated pure reference substances required for compound identification by GC-MS. Here, we accessed the information on reference compounds stored in the Golm Metabolome Database (GMD) to apply supervised machine learning approaches to the classification and identification of unidentified MSTs without relying on library searches. Non-annotated MSTs with mass spectral and retention index (RI) information together with data of already identified metabolites and reference substances have been archived in the GMD. Structural feature extraction was applied to sub-divide the metabolite space contained in the GMD and to define the prediction target classes. Decision tree (DT)-based prediction of the most frequent substructures based on mass spectral features and RI information is demonstrated to result in highly sensitive and specific detections of sub-structures contained in the compounds. The underlying set of DTs can be inspected by the user and are made available for batch processing via SOAP (Simple Object Access Protocol)-based web services. The GMD mass spectral library with the integrated DTs is freely accessible for non-commercial use at http://gmd.mpimp-golm.mpg.de/. All matching and structure search functionalities are available as SOAP-based web services. A XML + HTTP interface, which follows Representational State Transfer (REST) principles, facilitates read-only access to data base entities

Sex-biased islet β cell dysfunction is caused by the MODY MAFA S64F variant by inducing premature aging and senescence in males.

A heterozygous missense mutation of the islet β cell-enriched MAFA transcription factor (p.Ser64Phe [S64F]) is found in patients with adult-onset β cell dysfunction (diabetes or insulinomatosis), with men more prone to diabetes than women. This mutation engenders increased stability to the unstable MAFA protein. Here, we develop a S64F MafA mouse model to determine how β cell function is affected and find sex-dependent phenotypes. Heterozygous mutant males (MafAS64F/+) display impaired glucose tolerance, while females are slightly hypoglycemic with improved blood glucose clearance. Only MafAS64F/+ males show transiently higher MafA protein levels preceding glucose intolerance and sex-dependent changes to genes involved in Ca2+ signaling, DNA damage, aging, and senescence. MAFAS64F production in male human β cells also accelerate cellular senescence and increase senescence-associated secretory proteins compared to cells expressing MAFAWT. These results implicate a conserved mechanism of accelerated islet aging and senescence in promoting diabetes in MAFAS64F carriers in a sex-biased manner

MDCT and Gd-EOB-DTPA Enhanced MRI Findings of Adrenal Adenoma Arising from an Ectopic Adrenal Gland within the Liver: Radiologic-Pathologic Correlation

We report a case of an adenoma arising from an ectopic adrenal gland mimicking a hepatocellular carcinoma in a heavy alcohol abuser. A MDCT showed a 2.7 low-attenuating nodule in segment VII of the liver through all CT phases. Compared to a precontrast image, however, a subtle enhancement was noted on the arterial phase CT image. On T1 weighted in- and opposed-phase MR images, an abundant fat component within the lesion was seen. Dynamic contrast-enhanced MR images after administration of gadolinium ethoxybenzyl diethylenetriaminepentaacetic acid (Gd-EOB-DTPA) more clearly depicted hypervascularity and wash-out of the lesion on arterial and portal phases, respectively. On delayed hepatobiliary phase MR images, obtained 20 minutes after Gd-EOB-DTPA administration, subtle uptake or retention of the contrast agent by the lesion was suspected. A tumorectomy was performed and adrenal adenoma from an ectopic adrenal gland within the liver was confirmed

Clinical Pharmacogenetics Implementation Consortium (CPIC) Guideline for Pharmacogenetics-Guided Warfarin Dosing: 2017 Update

This document is an update to the 2011 Clinical Pharmacogenetics Implementation Consortium (CPIC) guideline for CYP2C9 and VKORC1 genotypes and warfarin dosing. Evidence from the published literature is presented for CYP2C9, VKORC1, CYP4F2, and rs12777823 genotype-guided warfarin dosing to achieve a target international normalized ratio of 2-3 when clinical genotype results are available. In addition, this updated guideline incorporates recommendations for adult and pediatric patients that are specific to continental ancestry

Identifying metabolites by integrating metabolome databases with mass spectrometry cheminformatics.

Novel metabolites distinct from canonical pathways can be identified through the integration of three cheminformatics tools: BinVestigate, which queries the BinBase gas chromatography-mass spectrometry (GC-MS) metabolome database to match unknowns with biological metadata across over 110,000 samples; MS-DIAL 2.0, a software tool for chromatographic deconvolution of high-resolution GC-MS or liquid chromatography-mass spectrometry (LC-MS); and MS-FINDER 2.0, a structure-elucidation program that uses a combination of 14 metabolome databases in addition to an enzyme promiscuity library. We showcase our workflow by annotating N-methyl-uridine monophosphate (UMP), lysomonogalactosyl-monopalmitin, N-methylalanine, and two propofol derivatives

Serotonin tranporter methylation and response to cognitive behaviour therapy in children with anxiety disorders

Anxiety disorders that are the most commonly occurring psychiatric disorders in childhood, are associated with a range of social and educational impairments and often continue into adulthood. Cognitive behaviour therapy (CBT) is an effective treatment option for the majority of cases, although up to 35-45% of children do not achieve remission. Recent research suggests that some genetic variants may be associated with a more beneficial response to psychological therapy. Epigenetic mechanisms such as DNA methylation work at the interface between genetic and environmental influences. Furthermore, epigenetic alterations at the serotonin transporter (SERT) promoter region have been associated with environmental influences such as stressful life experiences. In this study, we measured DNA methylation upstream of SERT in 116 children with an anxiety disorder, before and after receiving CBT. Change during treatment in percentage DNA methylation was significantly different in treatment responders vs nonresponders. This effect was driven by one CpG site in particular, at which responders increased in methylation, whereas nonresponders showed a decrease in DNA methylation. This is the first study to demonstrate differences in SERT methylation change in association with response to a purely psychological therapy. These findings confirm that biological changes occur alongside changes in symptomatology following a psychological therapy such as CBT