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Childhood Maltreatment and Deviations from Normative Brain Structure: A Mega-Analysis of 3,711 Individuals from the ENIGMA MDD and ENIGMA PTSD Working Groups
Get PDFBackground
Childhood maltreatment (CM), encompassing abuse and neglect, is highly prevalent and associated with elevated risk for Major Depressive Disorder (MDD), Posttraumatic Stress Disorder (PTSD), and other related conditions. The extent to which neuroanatomical alterations in MDD and PTSD are attributable to CM, however, is uncertain.
Methods
Here, we analyzed CM and whole-brain MRI data from 3,711 participants in the ENIGMA MDD and PTSD Working Groups (25 sites; 33.3±13.0 years; 59.9% female). Normative modeling estimated deviation z-scores for 14 subcortical volumes (SV), 68 cortical thickness (CT), and 68 surface area (SA) measures. To identify transdiagnostic effects, associations between CM and brain deviation scores were evaluated across all participants (patients and healthy controls) stratified by sex and three age bins (pediatric, young adult, older adult).
Results
In young adults (ages 18-35), abuse was associated with larger volumes in thalamus and pallidum, thinner isthmus cingulate and middle frontal regions, and thicker medial orbitofrontal cortex; there were no significant effects in pediatric (≤18 years) participants. The strongest effects were observed in young female adults (|β|=.07-.22, q<.05): greater abuse and neglect were correlated with smaller hippocampus and putamen volumes, thinner entorhinal cortex, and smaller SA in fusiform/inferior parietal regions, and with larger SA in orbitofrontal and occipital cortices. In males, abuse had widespread effects on CT and SA (|β|=.1-.18, q<.05); effects for neglect were minimal.
Conclusions
Our findings of age- and sex-specific instantiations of CM on brain morphometry highlight the importance of developmental context in understanding how adverse experiences shape neurobiological vulnerability to MDD and PTSD
A comparative analysis of primary school meal nutrition across the low- and high-poverty boroughs of Inner London
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Socio-economic status is a known predictor of childhood obesity. Improvements to school meals have been promoted as a method of combating rising childhood obesity rates, especially in low-income populations. However, little is known about how school food offerings differ across areas of low and high socio-economic status. This study aims to examine differences in school lunch nutrition across socioeconomic strata and compare these differences to small-scale regional childhood obesity prevalence.
Methods
This was a cross-sectional study of electronically published school lunch menus and a longitudinal analysis of UK National Child Measurement Programme data. Participants were a randomly selected sample of free, state-funded primary schools with 200-399 pupils within the two highest and two lowest child-poverty boroughs of Inner London, UK (n = 20), along with borough-level data on child BMI in reception and year 6 (n = 4). School meals were evaluated for nutrient content using Nutritics and for objective healthiness using the Nutrient Profiling Model.
Results
Lunches in high-poverty boroughs were significantly lower in total energy, carbohydrates, fat,
and sugars (p < 0.001), but lower in iron, zinc, and Vitamin A (p < 0.01) compared with the most
affluent areas. Using the nutrient profiling model, meals in high-poverty boroughs scored significantly better in both main courses (mean difference = -0.53, p = 0.016) and desserts (mean difference = 5.50, p < 0.001).
Conclusions
Overall, meals in high-poverty boroughs were more nutritious than those in the most affluent areas, though they were lower in some key micronutrients. Despite this, rates of overweight, obesity, and severe obesity are higher in these boroughs, indicating that factors other than school food nutrition may play more crucial roles in the relationship between socio-economic status and childhood obesity
FedCLAM: Client Adaptive Momentum with Foreground Intensity Matching for Federated Medical Image Segmentation
No full textFederated learning is a decentralized training approach that keeps data under stakeholder control while achieving superior performance over isolated training. While inter-institutional feature discrepancies pose a challenge in all federated settings, medical imaging is particularly affected due to diverse imaging devices and population variances, which can diminish the global model's effectiveness. Existing aggregation methods generally fail to adapt across varied circumstances. To address this, we propose FedCLAM, which integrates \textit{client-adaptive momentum} terms derived from each client's loss reduction during local training, as well as a \textit{personalized dampening factor} to curb overfitting. We further introduce a novel \textit{intensity alignment} loss that matches predicted and ground-truth foreground distributions to handle heterogeneous image intensity profiles across institutions and devices. Extensive evaluations on two datasets show that FedCLAM surpasses eight cutting-edge methods in medical segmentation tasks, underscoring its efficacy
Visual suppression deficits as a biomarker of working memory impairment in schizophrenia
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Although working memory (WM) deficits are well established in schizophrenia (SZ), their underlying source is still unclear. It has been proposed that these WM deficits may depend on an imbalance between cortical excitation and inhibition (E/I), but its importance for SZ remains unclear. A potential biomarker for E/I is visual Surround Suppression (SS), where the apparent contrast of a central grating is typically suppressed by a surround with parallel orientation (versus orthogonal). Here we exploited the SS phenomenon to test whether E/I contributes to WM impairments in schizophrenia.
Methods
Using centre-surround gratings, we measured psychophysical thresholds for contrast matching, detection and orientation discrimination, in 21 SZ patients and 20 matched controls. Using the same stimuli, we also measured WM accuracy and event-related potentials (ERPs) in a delayed-match-to-sample task.
Results
In SZ participants, reduced SS predicted impaired WM performance as well as general cognitive measures (CANTAB). Similar relationships were also observed between other early visual measures (impaired contrast detection and orientation discrimination), WM and general cognition. In response to SS, there was reduced amplitude visual ERPs (P1, N1 and P2) in patients compared with controls. Furthermore, across both groups the P1 amplitude correlated with visual SS.
Conclusion
Together, these findings provide evidence that imbalances in cortical excitation and inhibition may contribute to visual and some cognitive deficits in schizophrenia, and that SS may provide a behavioural and electrophysiological biomarker
Excess Verdicts Insurance
No full textThis paper examines how excess verdicts affect the insurance industry and studies insurance contract design from the policyholder’s perspective, focusing on cases where court awards exceed policy limits. Excess verdicts refer to court decisions that grant compensation higher than the maximum coverage stated in an insurance policy. They are increasingly common in severe liability cases such as wrongful death claims and create both financial and legal risks for insurers and policyholders. These risks lead to uncertainty in premiums, solvency management, and overall risk control within the insurance market. To address these issues, we develop a mathematical framework that models excess verdicts by separating loss levels, legal outcomes, and contractual terms that specify coverage beyond standard policy limits. The framework applies Valueat-Risk (VaR) and Conditional Value-at-Risk (CVaR) within a premium principle to capture the trade-off between risk exposure and cost in a manageable form. This approach provides a structured way to study how insurers and policyholders can share risks more efficiently when facing large and unpredictable legal awards. The results show that insurance contracts with multiple layers of indemnity can improve financial stability and fairness by distributing losses across different levels of coverage. Layered contracts reduce legal disputes, support balanced cost-sharing between insurers and policyholders, and give both sides clearer expectations about loss coverage. In practice, this structure helps insurers maintain solvency under extreme outcomes while offering policyholders more certainty about compensation in severe claim situations. The study provides a quantitative basis for designing more stable and transparent insurance products that can handle the growing problem of excess verdicts in modern
markets
Bivariate Copula-Based Regression for Joint Modeling of Healthcare Visits
No full textDoctor and non-doctor visit frequencies are key indicators of healthcare access, utilization and individual health-seeking behavior. While doctor visits reflect engagement with formal medical services, non-doctor visits, such as to nurses, physiotherapists or alternative providers, offer insights into patient preferences and system adaptability. Modeling these outcomes separately can hide relevant interdependencies and hence lead to incomplete conclusions. To address this, we employ a copula additive distributional regression framework to jointly model doctor and non-doctor visits as flexible functions of demographic, socioeconomic and health-related covariates. The estimation approach allows all the distributional parameters, including location, scale and the dependence structure, to vary with covariates via additive predictors. Application of the model to data from the 2012 Medical Expenditure Panel Survey reveals key determinants of physician and non-physician visits, such as age, income and health status. Importantly, the method allows for the modeling of shared unobserved heterogeneity and effectively captures how changes in one type of utilization influence the other, thereby yielding a deeper understanding of healthcare behavior
Optimal Selling Mechanisms with Endogenous Seller Outside Offers
No full textWe examine a two-stage selling mechanism design problem, where the buyer makes her report and the seller endogenously decides his effort (hidden investment) to generate a possibly better outside offer. The optimal mechanism shows that the seller’s effort depends on the reported value of the buyer; a higher value lowers the seller’s incentive to invest in the outside offer. After the price of the outside offer is realized, if the buyer’s virtual value is less than the price, the seller takes the outside offer, and a termination fee equal to the virtual value is paid to the buyer
Crowdsourcing as a methodology for global movements: building counter-hegemonic knowledge of de-privatisation
No full textThe repertoire of contemporary social movements increasingly includes utilising data in strategic pursuit of their goals. In this paper, we explore the potential for co-produced crowdsourced data in the context of a global, networked movement advocating for the de-privatisation of public services. We argue that crowdsourcing can produce data to inform and strengthen alternative progressive narratives to counteract dominant elite discourses still wedded to increasingly contradictory global neoliberal political and economic governance rhetorics. The building of counter-hegemonic knowledge is particularly critical in the current moment where elite and dominant narratives are being called into question. The paper also contributes to social movement studies by developing the theoretical and conceptual framework of crowdsourcing, to improve its “fit” for co-produced social science. In this way, the paper contributes to social movement scholarship on the role of data; the conceptual development of the methodology itself; and ongoing debates around social movements as knowledge producers
The relationship between mental state decoding and real-world social functioning – An experience sampling investigation
Get PDFIntroduction Social cognition, particularly Theory of Mind (ToM), is thought to play a crucial role in social functioning. Patients with psychosis often exhibit ToM deficits, but research findings on associations with social outcomes in daily life remain conflicting. Objectives This study investigated the relationship between mental state decoding, a core aspect of ToM, measured by the Reading the Mind in the Eyes Test (RMET), and quantity and subjective quality of real-life social interactions in patients with psychosis, first-degree relatives, and controls. Methods A 7-day Experience Sampling Method (ESM) design assessed the number and quality of real-life social interactions, including time spent alone vs. in social company, loneliness, feelings of social exclusion, preferences for company, being alone by choice, enjoyment of solitude, and perceived relationship quality in 27 patients with psychosis, 17 first-degree relatives, and 26 controls. All participants completed the RMET. Results Patients scored lower on the RMET compared to both relatives (β = −0.13, p = .006) and controls (β = −0.19, p .7). Conclusions Lower RMET performance was linked to greater feelings of social exclusion across groups but was unrelated to other indicators of real-life social functioning, including social emotions or frequency of social interactions. This finding is in line with other recent ESM studies, and highlights the importance of other, possibly more proximal factors for real-life social functioning
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