Street-connectedness through a Covid 19 lens: exploring media representations of street-connected children to understand their societal positionality

The 2017 general comment (GC21) to the United Nations Convention on the Rights of the Child (UNCRC) on children in street situations, provides a framework of legal guidance for governments developing policies aimed at protecting street-connected children and sets up the rationale for more awareness raising and public education to counter negative and deficit attitudes towards street-connectedness. Within this framework, the media has a role to play in either challenging conceptualisations of street-connected children as out-of-place within the public and predominantly adult domain described by urban streets, or in reinforcing ideological constructions of citizenship and normalised notions of childhood that result in negative stereotypes of these children. GC21 recommends that interventions targeted at street-connected children should be ethically responsible - adopting child rights approaches aimed at using accurate data/evidence that upholds the dignity of children, their personal integrity, and their right to life (UNCRC, 2017). As such, these approaches should also extend to how organisations engage with and utilise the media to represent street-connected children. Focusing on media representations of street-connected children during the six pandemic-affected months of February to July 2020, this paper provides a review of the content of the sources to provide an insight into the structural barriers that face street-connected children because of how they are positioned in society, during the pandemic and in general, and the extent to which the media reinforces or counters the rescue or removal narratives that can lead to inappropriate intervention responses

Impaired Motion Processing in Schizophrenia and the Attenuated Psychosis Syndrome : Etiological and Clinical Implications

The authors thank Gail Silipo, M.A. for assistance in subject recruitment, Raj Sangoi (RT)(R)(MR) and Caxia Hu, M.S., for assistance in MRI scanning and Isabel and Herb Stusser for their generous support. This research was supported by NIMH grant MH084031 (MJH) DA03383 (DCJ).Peer reviewedPostprin

Acute maternal stress in pregnancy and schizophrenia in offspring: A cohort prospective study

Schizophrenia has been linked with intrauterine exposure to maternal stress due to bereavement, famine and major disasters. Recent evidence suggests that human vulnerability may be greatest in the first trimester of gestation and rodent experiments suggest sex specificity. We aimed to describe the consequence of an acute maternal stress, through a follow-up of offspring whose mothers were pregnant during the Arab-Israeli war of 1967. A priori, we focused on gestational month and offspring's sex. Method: In a pilot study linking birth records to Israel's Psychiatric Registry, we analyzed data from a cohort of 88,829 born in Jerusalem in 1964–76. Proportional hazards models were used to estimate the relative risk (RR) of schizophrenia, according to month of birth, gender and other variables, while controlling for father's age and other potential confounders. Other causes of hospitalized psychiatric morbidity (grouped together) were analyzed for comparison. Results: There was a raised incidence of schizophrenia for those who were in the second month of fetal life in June 1967 (RR = 2.3, 1.1–4.7), seen more in females (4.3, 1.7–10.7) than in males (1.2, 0.4–3.8). Results were not explained by secular or seasonal variations, altered birth weight or gestational age. For other conditions, RRs were increased in offspring who had been in the third month of fetal life in June 1967 (2.5, 1.2–5.2), also seen more in females (3.6, 1.3–9.7) than males (1.8, 0.6–5.2). Conclusion: These findings add to a growing literature, in experimental animals and humans, attributing long term consequences for offspring of maternal gestational stress. They suggest both a sex-specificity and a relatively short gestational time-window for gestational effects on vulnerability to schizophrenia

Emerging Temporal Lobe Dysfunction in People at Clinical High Risk for Psychosis

Clinical high-risk (CHR) individuals have been increasingly utilized to investigate the prodromal phases of psychosis and progression to illness. Research has identified medial and lateral temporal lobe abnormalities in CHR individuals. Dysfunction in the medial temporal lobe, particularly the hippocampus, is linked to dysregulation of glutamate and dopamine via a hippocampal–striatal–midbrain network that may lead to aberrant signaling of salience underpinning the formation of delusions. Similarly, lateral temporal dysfunction may be linked to the disorganized speech and language impairments observed in the CHR stage. Here, we summarize the significance of these neurobiological findings in terms of emergent psychotic symptoms and conversion to psychosis in CHR populations. We propose key questions for future work with the aim to identify the neural mechanisms that underlie the development of psychosis

Imaging Patients with Psychosis and a Mouse Model Establishes a Spreading Pattern of Hippocampal Dysfunction and Implicates Glutamate as a Driver

The hippocampus in schizophrenia is characterized by both hypermetabolism and reduced size. It remains unknown whether these abnormalities are mechanistically linked. Here, in addressing these questions we used MRI tools that can map hippocampal metabolism and structure in patients and mouse models. In at-risk patients, hypermetabolism was found to begin in CA1 and spread to the subiculum after psychosis onset. CA1 hypermetabolism at baseline predicted hippocampal atrophy, which occured during progression to psychosis, most prominently in similar regions. Next, we used ketamine to model conditions of acute psychosis in mice. Acute ketamine reproduced a regional pattern of hippocampal hypermetabolism, while repeated exposure shifted the hippocampus to a hypermetabolic state with concurrent atrophy and pathology in parvalbumin-expressing interneurons. Parallel in vivo experiments using LY379268 and direct measurements of extracellular glutamate showed that glutamate drives both neuroimaging abnormalities. These findings show that hippocampal hypermetabolism leads to atrophy in psychotic disorder and suggest glutamate as a pathogenic driver

Neuroanatomical heterogeneity and homogeneity in individuals at clinical high risk for psychosis

Individuals at Clinical High Risk for Psychosis (CHR-P) demonstrate heterogeneity in clinical profiles and outcome features. However, the extent of neuroanatomical heterogeneity in the CHR-P state is largely undetermined. We aimed to quantify the neuroanatomical heterogeneity in structural magnetic resonance imaging measures of cortical surface area (SA), cortical thickness (CT), subcortical volume (SV), and intracranial volume (ICV) in CHR-P individuals compared with healthy controls (HC), and in relation to subsequent transition to a first episode of psychosis. The ENIGMA CHR-P consortium applied a harmonised analysis to neuroimaging data across 29 international sites, including 1579 CHR-P individuals and 1243 HC, offering the largest pooled CHR-P neuroimaging dataset to date. Regional heterogeneity was indexed with the Variability Ratio (VR) and Coefficient of Variation (CV) ratio applied at the group level. Personalised estimates of heterogeneity of SA, CT and SV brain profiles were indexed with the novel Person-Based Similarity Index (PBSI), with two complementary applications. First, to assess the extent of within-diagnosis similarity or divergence of neuroanatomical profiles between individuals. Second, using a normative modelling approach, to assess the ‘normativeness’ of neuroanatomical profiles in individuals at CHR-P. CHR-P individuals demonstrated no greater regional heterogeneity after applying FDR corrections. However, PBSI scores indicated significantly greater neuroanatomical divergence in global SA, CT and SV profiles in CHR-P individuals compared with HC. Normative PBSI analysis identified 11 CHR-P individuals (0.70%) with marked deviation (>1.5 SD) in SA, 118 (7.47%) in CT and 161 (10.20%) in SV. Psychosis transition was not significantly associated with any measure of heterogeneity. Overall, our examination of neuroanatomical heterogeneity within the CHR-P state indicated greater divergence in neuroanatomical profiles at an individual level, irrespective of psychosis conversion. Further large-scale investigations are required of those who demonstrate marked deviation

Evidence of discontinuity between psychosis-risk and non-clinical samples in the neuroanatomical correlates of social function

ObjectiveSocial dysfunction is a major feature of clinical-high-risk states for psychosis (CHR-P). Prior research has identified a neuroanatomical pattern associated with impaired social function outcome in CHR-P. The aim of the current study was to test whether social dysfunction in CHR-P is neurobiologically distinct or in a continuum with the lower end of the normal distribution of individual differences in social functioning.MethodsWe used a machine learning classifier to test for the presence of a previously validated brain structural pattern associated with impaired social outcome in CHR-P (CHR-outcome-neurosignature) in the neuroimaging profiles of individuals from two non-clinical samples (total n = 1763) and examined its association with social function, psychopathology and cognition.ResultsAlthough the CHR-outcome-neurosignature could be detected in a subset of the non-clinical samples, it was not associated was adverse social outcomes or higher psychopathology levels. However, participants whose neuroanatomical profiles were highly aligned with the CHR-outcome-neurosignature manifested subtle disadvantage in fluid (PFDR = 0.004) and crystallized intelligence (PFDR = 0.01), cognitive flexibility (PFDR = 0.02), inhibitory control (PFDR = 0.01), working memory (PFDR = 0.0005), and processing speed (PFDR = 0.04).ConclusionsWe provide evidence of divergence in brain structural underpinnings of social dysfunction derived from a psychosis-risk enriched population when applied to non-clinical samples. This approach appears promising in identifying brain mechanisms bound to psychosis through comparisons of patient populations to non-clinical samples with the same neuroanatomical profiles.</p

Using brain structural neuroimaging measures to predict psychosis onset for individuals at clinical high-risk

Machine learning approaches using structural magnetic resonance imaging (sMRI) can be informative for disease classification, although their ability to predict psychosis is largely unknown. We created a model with individuals at CHR who developed psychosis later (CHR-PS+) from healthy controls (HCs) that can differentiate each other. We also evaluated whether we could distinguish CHR-PS+ individuals from those who did not develop psychosis later (CHR-PS-) and those with uncertain follow-up status (CHR-UNK). T1-weighted structural brain MRI scans from 1165 individuals at CHR (CHR-PS+, n = 144; CHR-PS-, n = 793; and CHR-UNK, n = 228), and 1029 HCs, were obtained from 21 sites. We used ComBat to harmonize measures of subcortical volume, cortical thickness and surface area data and corrected for non-linear effects of age and sex using a general additive model. CHR-PS+ (n = 120) and HC (n = 799) data from 20 sites served as a training dataset, which we used to build a classifier. The remaining samples were used external validation datasets to evaluate classifier performance (test, independent confirmatory, and independent group [CHR-PS- and CHR-UNK] datasets). The accuracy of the classifier on the training and independent confirmatory datasets was 85% and 73% respectively. Regional cortical surface area measures-including those from the right superior frontal, right superior temporal, and bilateral insular cortices strongly contributed to classifying CHR-PS+ from HC. CHR-PS- and CHR-UNK individuals were more likely to be classified as HC compared to CHR-PS+ (classification rate to HC: CHR-PS+, 30%; CHR-PS-, 73%; CHR-UNK, 80%). We used multisite sMRI to train a classifier to predict psychosis onset in CHR individuals, and it showed promise predicting CHR-PS+ in an independent sample. The results suggest that when considering adolescent brain development, baseline MRI scans for CHR individuals may be helpful to identify their prognosis. Future prospective studies are required about whether the classifier could be actually helpful in the clinical settings.</p