Publications by authors named "N A Vaidya"

The evidence supporting the presence of individual brain structure correlates of the externalizing spectrum (EXT) is sparse and mixed. To date, large-sample studies of brain-EXT relations have mainly found null to very small effects by focusing exclusively on either EXT-related personality traits (e.g.

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Unhealthy eating, a risk factor for eating disorders (EDs) and obesity, often coexists with emotional and behavioral problems; however, the underlying neurobiological mechanisms are poorly understood. Analyzing data from the longitudinal IMAGEN adolescent cohort, we investigated associations between eating behaviors, genetic predispositions for high body mass index (BMI) using polygenic scores (PGSs), and trajectories (ages 14-23 years) of ED-related psychopathology and brain maturation. Clustering analyses at age 23 years ( = 996) identified 3 eating groups: restrictive, emotional/uncontrolled and healthy eaters.

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Background: Atypical teratoid rhabdoid tumor (ATRT) is the most common malignant brain tumor in infants, and more than 60% of children with ATRT die from their tumor. ATRT is associated with mutational inactivation/deletion of , a member of the SWI/SNF chromatin remodeling complex, suggesting that epigenetic events play a critical role in tumor development and progression. Moreover, disruption of SWI/SNF allows unopposed activity of epigenetic repressors, which contribute to tumorigenicity.

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Black band disease (BBD) is one of the most prevalent diseases causing significant destruction of coral reefs. Coral reefs acquire this deadly disease from bacteria in the microbiome community, the composition of which is highly affected by the environmental temperature. While previous studies have provided valuable insights into various aspects of BBD, the temperature-dependent microbiome composition has not been considered in existing BBD models.

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Article Synopsis
  • The study utilized machine learning models to identify reliable diagnostic markers for eating disorders, major depressive disorder, and alcohol use disorder, targeting young adults aged 18-25.
  • The classification models showed high accuracy rates (AUC-ROC ranging from 0.80 to 0.92) even without considering body mass index and highlighted shared predictors like neuroticism and hopelessness.
  • Additionally, the models were moderately successful in predicting future symptoms related to eating disorders, depression, and alcohol use in a longitudinal sample of adolescents, indicating the potential for improved diagnosis and risk assessment in mental health.
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