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Sökning: WFRF:(Viswanath B.)

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1.
  • Bauer, M., et al. (författare)
  • Solar insolation in springtime influences age of onset of bipolar I disorder
  • 2017
  • Ingår i: Acta Psychiatrica Scandinavica. - 0001-690X. ; 136:6, s. 571-582
  • Forskningsöversikt (refereegranskat)abstract
    • Objective: To confirm prior findings that the larger the maximum monthly increase in solar insolation in springtime, the younger the age of onset of bipolar disorder. Method: Data were collected from 5536 patients at 50 sites in 32 countries on six continents. Onset occurred at 456 locations in 57 countries. Variables included solar insolation, birth-cohort, family history, polarity of first episode and country physician density. Results: There was a significant, inverse association between the maximum monthly increase in solar insolation at the onset location, and the age of onset. This effect was reduced in those without a family history of mood disorders and with a first episode of mania rather than depression. The maximum monthly increase occurred in springtime. The youngest birth-cohort had the youngest age of onset. All prior relationships were confirmed using both the entire sample, and only the youngest birth-cohort (all estimated coefficients P < 0.001). Conclusion: A large increase in springtime solar insolation may impact the onset of bipolar disorder, especially with a family history of mood disorders. Recent societal changes that affect light exposure (LED lighting, mobile devices backlit with LEDs) may influence adaptability to a springtime circadian challenge.
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  • Bauer, Michael, et al. (författare)
  • Association between solar insolation and a history of suicide attempts in bipolar I disorder.
  • 2019
  • Ingår i: Journal of psychiatric research. - 1879-1379. ; 113, s. 1-9
  • Tidskriftsartikel (refereegranskat)abstract
    • In many international studies, rates of completed suicide and suicide attempts have a seasonal pattern that peaks in spring or summer. This exploratory study investigated the association between solar insolation and a history of suicide attempt in patients with bipolar I disorder. Solar insolation is the amount of electromagnetic energy from the Sun striking a surface area on Earth. Data were collected previously from 5536 patients with bipolar I disorder at 50 collection sites in 32 countries at a wide range of latitudes in both hemispheres. Suicide related data were available for 3365 patients from 310 onset locations in 51 countries. 1047 (31.1%) had a history of suicide attempt. There was a significant inverse association between a history of suicide attempt and the ratio of mean winter solar insolation/mean summer solar insolation. This ratio is smallest near the poles where the winter insolation is very small compared to the summer insolation. This ratio is largest near the equator where there is relatively little variation in the insolation over the year. Other variables in the model that were positively associated with suicide attempt were being female, a history of alcohol or substance abuse, and being in a younger birth cohort. Living in a country with a state-sponsored religion decreased the association. (All estimated coefficients p < 0.01). In summary, living in locations with large changes in solar insolation between winter and summer may be associated with increased suicide attempts in patients with bipolar disorder. Further investigation of the impacts of solar insolation on the course of bipolar disorder is needed.
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5.
  • Shi, Leming, et al. (författare)
  • The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models
  • 2010
  • Ingår i: Nature Biotechnology. - Nature Publishing Group. - 1087-0156. ; 28:8, s. 827-838
  • Tidskriftsartikel (refereegranskat)abstract
    • Gene expression data from microarrays are being applied to predict preclinical and clinical endpoints, but the reliability of these predictions has not been established. In the MAQC-II project, 36 independent teams analyzed six microarray data sets to generate predictive models for classifying a sample with respect to one of 13 endpoints indicative of lung or liver toxicity in rodents, or of breast cancer, multiple myeloma or neuroblastoma in humans. In total, &gt;30,000 models were built using many combinations of analytical methods. The teams generated predictive models without knowing the biological meaning of some of the endpoints and, to mimic clinical reality, tested the models on data that had not been used for training. We found that model performance depended largely on the endpoint and team proficiency and that different approaches generated models of similar performance. The conclusions and recommendations from MAQC-II should be useful for regulatory agencies, study committees and independent investigators that evaluate methods for global gene expression analysis.
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