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Machine learning can be used to define subtypes of psychiatric conditions based on shared biological foundations of mental disorders. Here we analyzed cross-sectional brain images from 4,222 individuals with schizophrenia and 7038 healthy subjects pooled across 41 international cohorts from the ENIGMA, non-ENIGMA cohorts and public datasets. Using the Subtype and Stage Inference (SuStaIn) algorithm, we identify two distinct neurostructural subgroups by mapping the spatial and temporal trajectory of gray matter change in schizophrenia. Subgroup 1 was characterized by an early cortical-predominant loss with enlarged striatum, whereas subgroup 2 displayed an early subcortical-predominant loss in the hippocampus, striatum and other subcortical regions. We confirmed the reproducibility of the two neurostructural subtypes across various sample sites, including Europe, North America and East Asia. This imaging-based taxonomy holds the potential to identify individuals with shared neurobiological attributes, thereby suggesting the viability of redefining existing disorder constructs based on biological factors.

Confrontation on Borneo tests a thesis on counterinsurgency: winning hearts and minds succeeds if object place/people win over the hearts and minds of subject counterinsurgency soldiers. This psychological transformation depends on fixed objects that counterinsurgency cannot easily change: the counterinsurgency destination and the counterinsurgents' place of origin that formed soldiers' unconscious selves. Soldiers encountered on Borneo a transformative, attractive, alien destination that changed their behavior. Soldiers then ratified unconscious behavior by asserting that the cause was their innate decency and official hearts and minds policy. But Borneo had formed the unconscious self that gave form to hearts and minds. This article argues that altered states of being shape counterinsurgency. [ABSTRACT FROM AUTHOR]

Air pollution exposure is associated with adverse respiratory health outcomes. Evidence from occupational and community-based studies also suggests agricultural pesticides have negative health impacts on respiratory health. Although populations are exposed to multiple inhalation hazards simultaneously, multidomain mixtures (e.g. environmental and chemical pollutants of different classes) are rarely studied. We investigated the association of ambient air pollution-pesticide exposure mixtures with urinary leukotriene E4 (LTE4), a respiratory inflammation biomarker, for 75 participants in four Central California communities over two seasons. Exposures included three criteria air pollutants estimated via the Community Multiscale Air Quality model (fine particulate matter, ozone, and nitrogen dioxide) and urinary metabolites of organophosphate (OP) pesticides (total dialkyl phosphates (DAPs), total diethyl phosphates (DE), and total dimethyl phosphates (DM)). We implemented multiple linear regression models to examine associations in single pollutant models adjusted for age, sex, asthma status, occupational status, household member occupational status, temperature, and relative humidity, and evaluated whether associations changed seasonally. We then implemented Bayesian kernel machine regression (BKMR) to analyse these criteria air pollutants, DE, and DM as a mixture. Our multiple linear regression models indicated an interquartile range (IQR) increase in total DAPs was associated with an increase in urinary LTE4 in winter ( β : 0.04, 95% CI: [0.01, 0.07]). Similarly, an IQR increase in total DM was associated with an increase in urinary LTE4 in winter ( β :0.03, 95% CI: [0.004, 0.06]). Confidence intervals for all criteria air pollutant effect estimates included the null value. BKMR analysis revealed potential non-linear interactions between exposures in our air pollution-pesticide mixture, but all confidence intervals contained the null value. Our analysis demonstrated a positive association between OP pesticide metabolites and urinary LTE4 in a low asthma prevalence population and adds to the limited research on the joint effects of ambient air pollution and pesticides mixtures on respiratory health., (© 2024 The Author(s). Published by IOP Publishing Ltd.)

The preparation of a well-defined trifluoromethylated argentate n Bu 4 N + [Ag(CF 3 ) 2 ] - 1 from fluoroform was described. The complex was stable in the solid state and in solution under an inert atmosphere. Treatment of a variety of (hetero)aryl diazonium tetrafluoroborates with n Bu 4 N + [Ag(CF 3 ) 2 ] - 1 generated trifluoromethylated (hetero)arenes in good to excellent yields. Preliminary experiments were conducted, and a reasonable mechanism of the reaction was proposed.