Emory University

• Developed a framework balancing equity and efficiency in educational resource allocation. • Middle school education showed more instability and regional disparities than primary education. • Found a coupling effect between equity and efficiency in resource allocation processes. • Policy recommendations include promoting innovation and improving management for balanced allocation. Educational equity remains a critical concern for scholars worldwide. This study develops a systematic evaluation framework that balances equity and efficiency in educational resource allocation. Using data from compulsory education across cities in Henan Province from 2015 to 2021, and employing the Dagum Gini coefficient and Malmquist index models, we examine regional disparities, spatial patterns, and evolutionary trends in the allocation of compulsory education resources from both efficiency and equity perspectives. We analyze the current state, issues, and underlying causes of educational resource distribution and propose policy recommendations. Our results reveal significant variations in the capacity for educational resource allocation at both primary and middle school levels in Henan Province, with middle school education exhibiting greater instability and regional disparities. A coupling effect between equity and efficiency is observed in the allocation process. These findings suggest that the government should focus on adjusting the structure of middle school education resources by promoting technological innovation, enhancing management practices, and rationally allocating resources. Furthermore, effective resource allocation strategies and supervisory measures must be implemented based on regional changes in educational resource outputs. The method proposed in this study for assessing regional differences in educational resource allocation provides a valuable reference for achieving educational equity and sustainable development.

Childhood maltreatment and FKBP5 CATT haplotypes increase identity dissociation risk. While maltreatment often fosters disorganized attachment, the specific role of the FKBP5 CATT haplotype within this developmental pathway remains unknown. In 310 trauma-exposed adults, we assessed childhood maltreatment, disorganized attachment, and identity dissociation. FKBP5 CATT haplotype status was dichotomized (present/absent). Regression models were estimated to examine the pathway Childhood Maltreatment → Disorganized Attachment → Identity Dissociation, comparing two competing hypotheses: 1) The Formation Hypothesis (Maltreatment × CATT → Disorganization), and 2) The Translation Hypothesis (Disorganization × CATT → Identity Dissociation). Model fit was compared using BIC, and simple slopes were examined. Disorganized attachment predicted identity dissociation (β = 0.143, z = 3.83, p < .001), and childhood maltreatment predicted disorganization (β = 0.007, z = 4.46, p < .001). The Formation hypothesis was not supported, as the Maltreatment × CATT interaction did not predict disorganization (β = -0.004, z = -1.18, p = .24). However, the Translation hypothesis was supported by three pieces of evidence: a significant Disorganization × CATT interaction predicting identity dissociation (β = 0.133, z = 2.22, p = .027), model fit (∆BIC = 265.3), and simple slopes showing a strong effect of disorganization on identity dissociation for CATT carriers (β = 0.15, p < .001; +16.5 % per unit) but not for non-carriers (β = 0.02, p = .65). The FKBP5 CATT haplotype does not promote disorganized attachment but amplifies the translation of disorganized attachment into identity dissociation. This result highlights a genetically influenced failure of identity development following disorganized attachment.

BackgroundBrepocitinib is a first-in-class, oral, selective TYK2–JAK1 inhibitor that blocks cytokine signaling, which has been implicated in dermatomyositis.MethodsIn this phase 3, double-blind, randomized, placebo-controlled trial, adults with dermatomyositis were assigned in a 1:1:1 ratio to receive once-daily oral brepocitinib at a dose of 30 mg, brepocitinib at a dose of 15 mg, or placebo for 52 weeks. Standard therapies were continued, and glucocorticoids were tapered. The primary end point was the Total Improvement Score, a validated composite myositis index (with scores ranging from 0 to 100 and higher scores indicating greater improvement) at week 52. Key secondary end points, including skin disease activity, glucocorticoid tapering, and physical function, were tested in a multiplicity-controlled sequence.ResultsA total of 241 patients underwent randomization: 81 to receive brepocitinib 30 mg, 81 to receive brepocitinib 15 mg, and 79 to receive placebo. At week 52, the mean Total Improvement Score was 46.5, 37.5, and 31.2, respectively (difference with brepocitinib 30 mg vs. placebo, 15.3; 95% confidence interval [CI], 6.7 to 24.0; P<0.001; difference with brepocitinib 15 mg vs. placebo, 6.3; 95% CI, −2.4 to 14.9). Brepocitinib 30 mg was superior to placebo across all nine key secondary end points, including skin disease activity, systemic glucocorticoid tapering, and functional disability, with improvements observed as early as week 4. Serious infections were more frequent in the brepocitinib 30-mg group than in the placebo group (10% vs. 1%). No deaths occurred during the trial.ConclusionsIn adults with dermatomyositis that was resistant to previous therapy, the use of brepocitinib at a dose of 30 mg (but not at a dose of 15 mg) resulted in significant benefits with respect to a composite myositis index, skin disease severity, glucocorticoid tapering, and functional disability. (Funded by Priovant Therapeutics; ClinicalTrials.gov number, NCT05437263.)

Left ventricular (LV) dysfunction is a potential cardioembolic source of ischemic stroke, but its role in recurrent stroke risk and treatment response remains unclear. We explore whether LV injury associates with the risk of recurrent stroke and modifies the association between anticoagulation and stroke recurrence using real-world data. We performed a multicenter, retrospective study of Cardiac Abnormalities in Stroke Prevention and Recurrence cohort across 27 US sites. Patients with LV ejection fraction ≥20% were included. LV injury, defined as LV ejection fraction 20% to 40% and wall motion abnormality, was the primary exposure and treatment effect modifier. The treatment of interest was anticoagulant versus antiplatelet therapy. The composite outcome included recurrent stroke, major bleeding, or death. Outcomes were evaluated using unadjusted and inverse probability weighting adjusted Cox proportional hazards models, with treatment effect modification tested by LV injury status. Among 2685 patients enrolled, 2328 with complete data were analyzed (median age, 65 years; 49.8% female; median follow-up, 1.6 years). LV injury was present in 310 patients (13.3%). Overall, 535 events occurred: 258 recurrent ischemic strokes, 28 hemorrhagic strokes, 67 major hemorrhages, and 256 deaths. LV injury was associated with a higher unadjusted risk of the primary outcome (hazard ratio [HR], 1.51 [95% CI, 1.21-1.87]), though nonsignificant after inverse probability weighting adjustment (adjusted HR, 1.29 [95% CI, 0.97-1.70]). In the LV injury subgroup, anticoagulation versus antiplatelet therapy was associated with a lower risk of the primary outcome (adjusted HR, 0.24 [95% CI, 0.10-0.59]), relative to the non-LV injury subgroup (adjusted HR, 1.28 [95% CI, 0.83-1.95]; p[LV-interaction], 0.001). Similar interactions were seen for EF 20% to 40% (versus >40%; adjusted HR, 0.19 [95% CI, 0.04-0.86]; p[LV-interaction], 0.001) and wall motion abnormality (versus no wall motion abnormality; adjusted HR, 0.33 [95% CI, 0.15-0.73]). After cryptogenic stroke, anticoagulation in those with LV injury was associated with lower rates of recurrent stroke, major bleeding, and death. These findings warrant confirmation in a dedicated randomized controlled trial. URL: https://www.clinicaltrials.gov; Unique identifier: NCT06398366.

Artificial intelligence is increasingly advancing both fundamental research and clinical applications in schizophrenia. This review surveys recent literature on artificial intelligence driven approaches for schizophrenia diagnosis, treatment, management, and characterization, using multiple data modalities such as neuroimaging, electrophysiology, electronic health records, and genomic data. Recent work shows substantial progress in leveraging machine learning and deep learning for diagnostic label prediction, treatment response modeling, and brain network characterization. While many studies continue to improve feature extraction and classification methods within single modalities, there is a growing trend to utilize multiple data sources to capture the complexity of schizophrenia from a comprehensive perspective. Emerging themes include multimodal fusion methodologies to identify linked correlates of schizophrenia, as well as data-driven approaches to learn subgroups, brain networks, and psychosis continua. The rise of large-scale multimodal datasets, foundation models, and mechanistic interpretability methods holds promise for scalable symptom assessment and biomarker identification, thereby better supporting early intervention and personalized treatment. Current literature highlights a shift from unimodal prediction to holistic, multimodal characterization of schizophrenia. Transforming these artificial intelligence models into clinical tools, however, requires careful attention to patient privacy and data bias, alongside rigorous validation across diverse populations and settings.

As a group, patients with classic galactosemia (CG) demonstrate a high prevalence of long-term complications despite early detection and life-long dietary restriction of galactose, which is the current standard of care. Individual outcomes, however, vary widely. For decades, research teams have sought to identify potential environmental, metabolic, and/or galactose-1-phosphate uridylyltransferase (GALT) allelic differences that might explain this variability-with limited success. Among large cohorts, only severe brain-related disease in infancy has been associated with increased prevalence of complications, and only the presence of predicted or detected residual GALT activity has been associated with decreased prevalence. While significant, these factors fail to account for the majority of long-term outcome variability in CG. Here, we tested whether genetic factors, both inside and outside the GALT locus, might contribute to variability in speech/voice/language, cognitive, and/or motor outcomes among patients. Specifically, we compared outcomes among 66 sets of affected siblings who share both GALT genotype and genetic background, 54 unrelated CG patients who share GALT genotype (p.Gln188Arg/p.Gln188Arg) but not genetic background, and 52 unrelated CG patients who share neither GALT genotype nor genetic background. Heritability estimates for all three complications demonstrate substantial genetic contributions, with point estimates of 100% heritability for all three. Less than 8% of this heritability appears due to residual GALT activity from hypomorphic GALT alleles. Combined with prior data demonstrating clustering of all three outcomes, these results offer compelling evidence for the existence of genetic modifiers of developmental outcomes in CG beyond the GALT locus.