Movement abnormalities are commonly observed in schizophrenia and at-risk mental states (ARMS) for psychosis. They are usually detected with clinical interviews, such that automated analysis would enhance assessment. Our aim was to use motion energy analysis (MEA) to assess movement during free-speech videos in ARMS and control individuals, and to investigate associations between movement metrics and negative and positive symptoms. Thirty-two medication-naïve ARMS and forty-six healthy control individuals were filmed during speech tasks. Footages were analyzed using MEA software, which assesses movement by differences in pixels frame-by-frame. Two regions of interest were defined—head and torso—and mean amplitude, frequency, and coefficient of variability of movements for them were obtained. These metrics were correlated with the Structured Interview for Prodromal Syndromes (SIPS) symptoms, and with the risk of conversion to psychosis—inferred with the SIPS risk calculator. ARMS individuals had significantly lower mean amplitude of head movement and higher coefficients of movement variability for both head and torso, compared to controls. Higher coefficient of variability was related to higher risk of conversion. Negative correlations were seen between frequency of movement and most SIPS negative symptoms. All positive symptoms were correlated with at least one movement variable. Movement abnormalities could be automatically detected in medication-naïve ARMS subjects by means of a motion energy analysis software. Significant associations of movement metrics with symptoms were found, supporting the importance of movement analysis in ARMS. This could be a potentially important tool for early diagnosis, intervention, and outcome prediction.

BackgroundThe clinical high-risk for psychosis (CHR) paradigm is one of the best studied preventive paradigms in psychiatry. However, most studies have been conducted in high-income countries. It is unclear if knowledge from such countries applies to low and middle-income countries (LAMIC), and if there are specific limitations hindering CHR research there. Our aim is to systematically review studies on CHR from LAMIC.MethodsA multistep PRISMA-compliant literature search was performed in PubMed and Web of Science for articles published until 1/03/2022, conducted in LAMIC, addressing the concept and correlates of CHR. Study characteristics as well as limitations were reported. Corresponding authors of the included studies were invited to answer an online poll. Quality assessment was done with the MMAT.ResultsA total of 109 studies were included in the review: none from low-income countries, 8 from lower middle-income countries, and 101 from upper middle-income countries. The most frequent limitations were small sample size (47.9%), cross-sectional design (27.1%), and follow-up issues (20.8%). Mean quality of included studies was of 4.4. Out of the 43 corresponding authors, 12 (27.9%) completed the online poll. They cited further limitations as few financial resources (66.7%), no involvement of population (58.2%) and cultural barriers (41.7%). Seventy five percent researchers reported that CHR research should be conducted differently in LAMIC compared to high-income countries, due to structural and cultural issues. Stigma was mentioned in three out of five sections of the poll.DiscussionResults show the discrepancy of available evidence on CHR in LAMIC, given the shortage of resources in such countries. Future directions should aim to increase the knowledge on individuals at CHR in such settings, and to address stigma and cultural factors that may play a role in the pathways toward care in psychosis.Systematic Review Registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?RecordID=316816, CRD42022316816.

Recent developments in artificial intelligence technologies have come to a point where machine learning algorithms can infer mental status based on someone’s photos and texts posted on social media. More than that, these algorithms are able to predict, with a reasonable degree of accuracy, future mental illness. They potentially represent an important advance in mental health care for preventive and early diagnosis initiatives, and for aiding professionals in the follow-up and prognosis of their patients. However, important issues call for major caution in the use of such technologies, namely, privacy and the stigma related to mental disorders. In this paper, we discuss the bioethical implications of using such technologies to diagnose and predict future mental illness, given the current scenario of swiftly growing technologies that analyze human language and the online availability of personal information given by social media. We also suggest future directions to be taken to minimize the misuse of such important technologies.

The disruption of neurodevelopment is a hypothesis for the emergence of schizophrenia. Some evidence supports the hypothesis that a redox imbalance could account for the developmental impairments associated with schizophrenia. Additionally, there is a deficit in glutathione (GSH), a main antioxidant, in this disorder. The injection of metilazoximetanol acetate (MAM) on the 17th day of gestation in Wistar rats recapitulates the neurodevelopmental and oxidative stress hypothesis of schizophrenia. The offspring of rats exposed to MAM treatment present in early adulthood behavioral and neurochemical deficits consistent with those seen in schizophrenia. The present study investigated if the acute and chronic (250 mg/kg) treatment during adulthood with N-acetyl-L-cysteine (NAC), a GSH precursor, can revert the behavioral deficits [hyperlocomotion, prepulse inhibition (PPI), and social interaction (SI)] in MAM rats and if the NAC-chronic-effects could be canceled by L-arginine (250 mg/kg, i.p, for 5 days), nitric oxide precursor. Analyses of markers involved in the inflammatory response, such as astrocytes (glial fibrillary acid protein, GFAP) and microglia (binding adapter molecule 1, Iba1), and parvalbumin (PV) positive GABAergic, were conducted in the prefrontal cortex [PFC, medial orbital cortex (MO) and prelimbic cortex (PrL)] and dorsal and ventral hippocampus [CA1, CA2, CA3, and dentate gyrus (DG)] in rats under chronic treatment with NAC. MAM rats showed decreased time of SI and increased locomotion, and both acute and chronic NAC treatments were able to recover these behavioral deficits. L-arginine blocked NAC behavioral effects. MAM rats presented increases in GFAP density at PFC and Iba1 at PFC and CA1. NAC increased the density of Iba1 cells at PFC and of PV cells at MO and CA1 of the ventral hippocampus. The results indicate that NAC recovered the behavioral deficits observed in MAM rats through a mechanism involving nitric oxide. Our data suggest an ongoing inflammatory process in MAM rats and support a potential antipsychotic effect of NAC.

No abstract