Predicting suicide attempts and suicide deaths among adolescents following outpatient visits

BACKGROUND: Few studies report on machine learning models for suicide risk prediction in adolescents and their utility in identifying those in need of further evaluation. This study examined whether a model trained and validated using data from all age groups works as well for adolescents or whether it could be improved. METHODS: We used healthcare data for 1.4 million specialty mental health and primary care outpatient visits among 256,823 adolescents across 7 health systems. The prediction target was 90-day risk of suicide attempt following a visit. We used logistic regression with least absolute shrinkage and selection operator (LASSO) and generalized estimating equations (GEE) to predict risk. We compared performance of three models: an existing model, a recalibrated version of that model, and a newly-learned model. Models were compared using area under the receiver operating curve (AUC), sensitivity, specificity, positive predictive value and negative predictive value. RESULTS: The AUC produced by the existing model for specialty mental health visits estimated in adolescents alone (0.796; [0.789, 0.802]) was not significantly different than the AUC of the recalibrated existing model (0.794; [0.787, 0.80]) or the newly-learned model (0.795; [0.789, 0.801]). Predicted risk following primary care visits was also similar: existing (0.855; [0.844, 0.866]), recalibrated (0.85 [0.839, 0.862]), newly-learned (0.842, [0.829, 0.854]). LIMITATIONS: The models did not incorporate non-healthcare risk factors. The models relied on ICD9-CM codes for diagnoses and outcome measurement. CONCLUSIONS: Prediction models already in operational use by health systems can be reliably employed for identifying adolescents in need of further evaluation

Attitudes and Performance: An Analysis of Russian Workers

This paper investigates the relationship between locus of control and performance among Russian employees, using survey data collected at 28 workplaces in 2002 in Taganrog and at 47 workplaces in 2003 in Ekaterinburg. We develop a measure that allows us to categorize the Russian employees participating in our survey as exhibiting an internal or external locus of control. We then assess the extent to which there are significant differences between “internals” and “externals” in work-related attitudes that may affect performance. In particular, we focus on (1) attitudes about outcomes associated with hard work, (2) level of job satisfaction, (3) expectation of receiving a desired reward, and (4) loyalty to and involvement with one’s organization. In each case we identify where gender and generational differences emerge. Our main objective is to determine whether Russian employees who exhibit an internal locus of control perform better than employees with an external locus of control. Our performance measures include earnings, expected promotions, and assessments of the quantity and quality of work in comparison to others at the same organization doing a similar job. Controlling for a variety of worker characteristics, we find that (1) individuals who exhibit an internal locus of control perform better, but this result is not always statistically significant; (2) even among “internals,” women earn significantly less than men and have a much lower expectation of promotion; (3) even among “internals,” experience with unemployment has a negative influence on performance.http://deepblue.lib.umich.edu/bitstream/2027.42/40144/3/wp758.pd

The Use of Mosquito Nets and the Prevalence of Plasmodium falciparum Infection in Rural South Central Somalia

BACKGROUND: There have been resurgent efforts in Africa to estimate the public health impact of malaria control interventions such as insecticide treated nets (ITNs) following substantial investments in scaling-up coverage in the last five years. Little is known, however, on the effectiveness of ITN in areas of Africa that support low transmission. This hinders the accurate estimation of impact of ITN use on disease burden and its cost-effectiveness in low transmission settings. METHODS AND PRINCIPAL FINDINGS: Using a stratified two-stage cluster sample design, four cross-sectional studies were undertaken between March-June 2007 across three livelihood groups in an area of low intensity malaria transmission in South Central Somalia. Information on bed net use; age; and sex of all participants were recorded. A finger prick blood sample was taken from participants to examine for parasitaemia. Mantel-Haenzel methods were used to measure the effect of net use on parasitaemia adjusting for livelihood; age; and sex. A total of 10,587 individuals of all ages were seen of which 10,359 provided full information. Overall net use and parasite prevalence were 12.4% and 15.7% respectively. Age-specific protective effectiveness (PE) of bed net ranged from 39% among <5 years to 72% among 5-14 years old. Overall PE of bed nets was 54% (95% confidence interval 44%-63%) after adjusting for livelihood; sex; and age. CONCLUSIONS AND SIGNIFICANCE: Bed nets confer high protection against parasite infection in South Central Somalia. In such areas where baseline transmission is low, however, the absolute reductions in parasitaemia due to wide-scale net use will be relatively small raising questions on the cost-effectiveness of covering millions of people living in such settings in Africa with nets. Further understanding of the progress of disease upon infection against the cost of averting its consequent burden in low transmission areas of Africa is therefore required

Developmental Stability: A Major Role for Cyclin G in Drosophila melanogaster

Morphological consistency in metazoans is remarkable given the pervasive occurrence of genetic variation, environmental effects, and developmental noise. Developmental stability, the ability to reduce developmental noise, is a fundamental property of multicellular organisms, yet its genetic bases remains elusive. Imperfect bilateral symmetry, or fluctuating asymmetry, is commonly used to estimate developmental stability. We observed that Drosophila melanogaster overexpressing Cyclin G (CycG) exhibit wing asymmetry clearly detectable by sight. Quantification of wing size and shape using geometric morphometrics reveals that this asymmetry is a genuine—but extreme—fluctuating asymmetry. Overexpression of CycG indeed leads to a 40-fold increase of wing fluctuating asymmetry, which is an unprecedented effect, for any organ and in any animal model, either in wild populations or mutants. This asymmetry effect is not restricted to wings, since femur length is affected as well. Inactivating CycG by RNAi also induces fluctuating asymmetry but to a lesser extent. Investigating the cellular bases of the phenotypic effects of CycG deregulation, we found that misregulation of cell size is predominant in asymmetric flies. In particular, the tight negative correlation between cell size and cell number observed in wild-type flies is impaired when CycG is upregulated. Our results highlight the role of CycG in the control of developmental stability in D. melanogaster. Furthermore, they show that wing developmental stability is normally ensured via compensatory processes between cell growth and cell proliferation. We discuss the possible role of CycG as a hub in a genetic network that controls developmental stability

In silico Experimentation of Glioma Microenvironment Development and Anti-tumor Therapy

Tumor cells do not develop in isolation, but co-evolve with stromal cells and tumor-associated immune cells in a tumor microenvironment mediated by an array of soluble factors, forming a complex intercellular signaling network. Herein, we report an unbiased, generic model to integrate prior biochemical data and the constructed brain tumor microenvironment in silico as characterized by an intercellular signaling network comprising 5 types of cells, 15 cytokines, and 69 signaling pathways. The results show that glioma develops through three distinct phases: pre-tumor, rapid expansion, and saturation. We designed a microglia depletion therapy and observed significant benefit for virtual patients treated at the early stages but strikingly no therapeutic efficacy at all when therapy was given at a slightly later stage. Cytokine combination therapy exhibits more focused and enhanced therapeutic response even when microglia depletion therapy already fails. It was further revealed that the optimal combination depends on the molecular profile of individual patients, suggesting the need for patient stratification and personalized treatment. These results, obtained solely by observing the in silico dynamics of the glioma microenvironment with no fitting to experimental/clinical data, reflect many characteristics of human glioma development and imply new venues for treating tumors via selective targeting of microenvironmental components

Transcriptional diversity during lineage commitment of human blood progenitors.

Blood cells derive from hematopoietic stem cells through stepwise fating events. To characterize gene expression programs driving lineage choice, we sequenced RNA from eight primary human hematopoietic progenitor populations representing the major myeloid commitment stages and the main lymphoid stage. We identified extensive cell type-specific expression changes: 6711 genes and 10,724 transcripts, enriched in non-protein-coding elements at early stages of differentiation. In addition, we found 7881 novel splice junctions and 2301 differentially used alternative splicing events, enriched in genes involved in regulatory processes. We demonstrated experimentally cell-specific isoform usage, identifying nuclear factor I/B (NFIB) as a regulator of megakaryocyte maturation-the platelet precursor. Our data highlight the complexity of fating events in closely related progenitor populations, the understanding of which is essential for the advancement of transplantation and regenerative medicine.The work described in this article was primarily supported by the European Commission Seventh Framework Program through the BLUEPRINT grant with code HEALTH-F5-2011-282510 (D.H., F.B., G.C., J.H.A.M., K.D., L.C., M.F., S.C., S.F., and S.P.G.). Research in the Ouwehand laboratory is further supported by program grants from the National Institute for Health Research (NIHR, www.nihr.ac.uk; to A.A., M.K., P.P., S.B.G.J., S.N., and W.H.O.) and the British Heart Foundation under nos. RP-PG-0310-1002 and RG/09/12/28096 (www.bhf.org.uk; to A.R. and W.J.A.). K.F. and M.K. were supported by Marie Curie funding from the NETSIM FP7 program funded by the European Commission. The laboratory receives funding from the NHS Blood and Transplant for facilities. The Cambridge BioResource (www.cambridgebioresource.org.uk), the Cell Phenotyping Hub, and the Cambridge Translational GenOmics laboratory (www.catgo.org.uk) are supported by an NIHR grant to the Cambridge NIHR Biomedical Research Centre (BRC). The BRIDGE-Bleeding and Platelet Disorders Consortium is supported by the NIHR BioResource—Rare Diseases (http://bioresource.nihr.ac.uk/; to E.T., N.F., and Whole Exome Sequencing effort). Research in the Soranzo laboratory (L.V., N.S., and S. Watt) is further supported by the Wellcome Trust (Grant Codes WT098051 and WT091310) and the EU FP7 EPIGENESYS initiative (Grant Code 257082). Research in the Cvejic laboratory (A. Cvejic and C.L.) is funded by the Cancer Research UK under grant no. C45041/A14953. S.J.S. is funded by NIHR. M.E.F. is supported by a British Heart Foundation Clinical Research Training Fellowship, no. FS/12/27/29405. E.B.-M. is supported by a Wellcome Trust grant, no. 084183/Z/07/Z. Research in the Laffan laboratory is supported by Imperial College BRC. F.A.C., C.L., and S. Westbury are supported by Medical Research Council Clinical Training Fellowships, and T.B. by a British Society of Haematology/NHS Blood and Transplant grant. R.J.R. is a Principal Research Fellow of the Wellcome Trust, grant no. 082961/Z/07/Z. Research in the Flicek laboratory is also supported by the Wellcome Trust (grant no. 095908) and EMBL. Research in the Bertone laboratory is supported by EMBL. K.F. and C.v.G. are supported by FWO-Vlaanderen through grant G.0B17.13N. P.F. is a compensated member of the Omicia Inc. Scientific Advisory Board. This study made use of data generated by the UK10K Consortium, derived from samples from the Cohorts arm of the project.This is the author’s version of the work. It is posted here by permission of the AAAS for personal use, not for redistribution. The definitive version was published in Science on 26/9/14 in volume 345, number 6204, DOI: 10.1126/science.1251033. This version will be under embargo until the 26th of March 2015

Gene expression signatures of morphologically normal breast tissue identify basal-like tumors

INTRODUCTION: The role of the cellular microenvironment in breast tumorigenesis has become an important research area. However, little is known about gene expression in histologically normal tissue adjacent to breast tumor, if this is influenced by the tumor, and how this compares with non-tumor-bearing breast tissue. METHODS: To address this, we have generated gene expression profiles of morphologically normal epithelial and stromal tissue, isolated using laser capture microdissection, from patients with breast cancer or undergoing breast reduction mammoplasty (n = 44). RESULTS: Based on this data, we determined that morphologically normal epithelium and stroma exhibited distinct expression profiles, but molecular signatures that distinguished breast reduction tissue from tumor-adjacent normal tissue were absent. Stroma isolated from morphologically normal ducts adjacent to tumor tissue contained two distinct expression profiles that correlated with stromal cellularity, and shared similarities with soft tissue tumors with favorable outcome. Adjacent normal epithelium and stroma from breast cancer patients showed no significant association between expression profiles and standard clinical characteristics, but did cluster ER/PR/HER2-negative breast cancers with basal-like subtype expression profiles with poor prognosis. CONCLUSION: Our data reveal that morphologically normal tissue adjacent to breast carcinomas has not undergone significant gene expression changes when compared to breast reduction tissue, and provide an important gene expression dataset for comparative studies of tumor expression profiles

Predicting the Electron Requirement for Carbon Fixation in Seas and Oceans

Marine phytoplankton account for about 50% of all global net primary productivity (NPP). Active fluorometry, mainly Fast Repetition Rate fluorometry (FRRf), has been advocated as means of providing high resolution estimates of NPP. However, not measuring CO2-fixation directly, FRRf instead provides photosynthetic quantum efficiency estimates from which electron transfer rates (ETR) and ultimately CO2-fixation rates can be derived. Consequently, conversions of ETRs to CO2-fixation requires knowledge of the electron requirement for carbon fixation (Φe,C, ETR/CO2 uptake rate) and its dependence on environmental gradients. Such knowledge is critical for large scale implementation of active fluorescence to better characterise CO2-uptake. Here we examine the variability of experimentally determined Φe,C values in relation to key environmental variables with the aim of developing new working algorithms for the calculation of Φe,C from environmental variables. Coincident FRRf and 14C-uptake and environmental data from 14 studies covering 12 marine regions were analysed via a meta-analytical, non-parametric, multivariate approach. Combining all studies, Φe,C varied between 1.15 and 54.2 mol e- (mol C)-1 with a mean of 10.9±6.91 mol e- mol C)-1. Although variability of Φe,C was related to environmental gradients at global scales, region-specific analyses provided far improved predictive capability. However, use of regional Φe,C algorithms requires objective means of defining regions of interest, which remains challenging. Considering individual studies and specific small-scale regions, temperature, nutrient and light availability were correlated with Φe,C albeit to varying degrees and depending on the study/region and the composition of the extant phytoplankton community. At the level of large biogeographic regions and distinct water masses, Φe,C was related to nutrient availability, chlorophyll, as well as temperature and/or salinity in most regions, while light availability was also important in Baltic Sea and shelf waters. The novel Φe,C algorithms provide a major step forward for widespread fluorometry-based NPP estimates and highlight the need for further studying the natural variability of Φe,C to verify and develop algorithms with improved accuracy. © 2013 Lawrenz et al

Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans

Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same regio