The promise of generative AI for suicide prevention in India
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A network outcome analysis of psychological risk factors driving suicide risk in emergency department patients
Different theories of suicide propose somewhat different psychological factors that lead to suicidal thoughts and behaviors. For example, Beck’s theory highlights hopelessness, while the interpersonal–psychological theory of suicide emphasizes burdensomeness, lack of belonging and fearlessness about death. Surprisingly, few studies have tested which theoretically proposed psychological factors are most predictive of suicidal thoughts and behaviors. We used network outcome analysis to disentangle the effects of these constructs in predicting suicidal ideation, suicide plans and attempts. Participants were 1,412 patients presenting to an emergency department with psychiatric complaints, with follow-up assessments one month and six months (n = 938) later. Here we showed that different psychological factors predicted different parts of the continuum of suicidal thoughts and behaviors. Lack of belongingness was most predictive of suicidal ideation (partial correlation (pcor) = 0.14), acquired capability for death (that is, fearlessness of death) was most predictive of suicide planning (pcor = 0.08), and hopelessness was most predictive of suicide attempts (pcor = 0.12). Individuals’ explicit associations with death (that is, death = me) prospectively predicted all three outcomes (pcor = 0.13–0.23). The occurrence of suicidal thoughts and behaviors is best predicted using constructs from several different theories of suicide. Future theoretical and empirical work should integrate components of existing theories.
Childhood trauma cortisol and immune cell glucocorticoid transcript levels are associated with increased risk for suicidality in adolescence
Rising adolescent suicide rates present a growing unmet need. Childhood trauma (CT) has been associated with altered cortisol dynamics and immune cell glucocorticoid reactivity, yet their additive longer-term contributions to later suicide outcomes are less clear. The current study compared CT scores, resting salivary free cortisol and mononuclear cell gene expression levels of the nuclear receptor, subfamily 3, member 1 (NR3C1) coding the glucocorticoid receptor, and its co-chaperons FKBP prolyl isomerase 5 (FKBP5) and KIT Ligand (KITLG), between a cohort of adolescents presenting with a suicidal crisis requiring hospital treatment, and matched healthy controls. Childhood trauma scores and glucocorticoid measures were significantly altered among suicidal adolescents, and CT scores correlated with mononuclear cell glucocorticoid transcripts. Both CT scores and glucocorticoid measures explained substantial additive portions of the variance in adolescent suicidality. Long-term perturbations in cortisol dynamics and immune cell glucocorticoid response elements denote dysregulated immune stress reactivity, and may possess value in prediction and point to modifiable-risk factors in prevention of clinically significant suicidality during the brittle period of adolescence, years after childhood trauma exposure.
Application of decision analytic modelling to cardiovascular disease prevention in Sub-Saharan Africa: a systematic review
This systematic review sought to examine the application of decision analytic models (DAMs) to evaluate cardiovascular disease (CVD) prevention interventions in sub-Saharan Africa (SSA), a region that has experienced an increasing CVD burden in the last two decades.
Preserving and combining knowledge in robotic lifelong reinforcement learning
Humans can continually accumulate knowledge and develop increasingly complex behaviours and skills throughout their lives, which is a capability known as ‘lifelong learning’. Although this lifelong learning capability is considered an essential mechanism that makes up general intelligence, recent advancements in artificial intelligence predominantly excel in narrow, specialized domains and generally lack this lifelong learning capability. Here we introduce a robotic lifelong reinforcement learning framework that addresses this gap by developing a knowledge space inspired by the Bayesian non-parametric domain. In addition, we enhance the agent’s semantic understanding of tasks by integrating language embeddings into the framework. Our proposed embodied agent can consistently accumulate knowledge from a continuous stream of one-time feeding tasks. Furthermore, our agent can tackle challenging real-world long-horizon tasks by combining and reapplying its acquired knowledge from the original tasks stream. The proposed framework advances our understanding of the robotic lifelong learning process and may inspire the development of more broadly applicable intelligence.
Excess of rare noncoding variants in several type 2 diabetes candidate genes among Asian Indian families
Type 2 diabetes (T2D) etiology is highly complex due to its multiple roots of origin. Polygenic risk scores (PRS) based on genome-wide association studies (GWAS) can partially explain T2D risk. Asian Indian people have up to six times higher risk of developing T2D than European people, and underlying causes of this disparity are unknown.
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