Sulforaphane Effects on Cognition and Symptoms in First and Early Episode Schizophrenia: A Randomized Double-Blind Trial.

OBJECTIVE: Cognitive symptoms are associated with significant dysfunction in schizophrenia. Oxidative stress and inflammation involving histone deacetylase (HDAC) have been implicated in the pathophysiology of schizophrenia. Sulforaphane has antioxidant properties and is an HDAC inhibitor. The objective of this study was to determine the efficacy of sulforaphane on cognition dysfunction for patients with schizophrenia. METHODS: This double-blind randomized 22-week trial of patients with first-episode schizophrenia was conducted in four psychiatric institutions in China. Patients were randomized to three groups (two doses of sulforaphane vs. placebo) and symptomatic and cognitive assessments were completed at multiple times. The primary outcome measure was change in the MATRICS Composite score. The secondary outcomes were change in MATRICS Domain scores, PANSS Total Scores and change in side-effects. RESULTS: A total of 172 patients were randomized and 151 patients had at least one follow up evaluation. There were no significant effects of sulforaphane, on the primary outcome, MATRICS overall composite score. However, on secondary outcomes, sulforaphane did significantly improve performance scores on MATRICS battery Domains of spatial working memory (F = 5.68, P = 0.004), reasoning-problem solving (F = 2.82, P = 0.063), and verbal learning (F = 3.56, P = 0.031). There were no effects on PANSS symptom scores. Sulforaphane was well tolerated. CONCLUSION: Although the primary outcome was not significant, improvement in three domains of the MATRICS battery, suggests a positive cognitive effect on some cognitive functions, which warrants further clinical trials to further assess whether sulforaphane may be a useful adjunct for treating some types of cognitive deficits in schizophrenia

GWAS Identifies Novel Susceptibility Loci on 6p21.32 and 21q21.3 for Hepatocellular Carcinoma in Chronic Hepatitis B Virus Carriers

Genome-wide association studies (GWAS) have recently identified KIF1B as susceptibility locus for hepatitis B virus (HBV)–related hepatocellular carcinoma (HCC). To further identify novel susceptibility loci associated with HBV–related HCC and replicate the previously reported association, we performed a large three-stage GWAS in the Han Chinese population. 523,663 autosomal SNPs in 1,538 HBV–positive HCC patients and 1,465 chronic HBV carriers were genotyped for the discovery stage. Top candidate SNPs were genotyped in the initial validation samples of 2,112 HBV–positive HCC cases and 2,208 HBV carriers and then in the second validation samples of 1,021 cases and 1,491 HBV carriers. We discovered two novel associations at rs9272105 (HLA-DQA1/DRB1) on 6p21.32 (OR = 1.30, P = 1.13×$10^{−19}$) and rs455804 (GRIK1) on 21q21.3 (OR = 0.84, P = 1.86×$10^{−8}$), which were further replicated in the fourth independent sample of 1,298 cases and 1,026 controls (rs9272105: OR = 1.25, P = 1.71×$10^{−4}$; rs455804: OR = 0.84, P = 6.92×$10^{−3}$). We also revealed the associations of HLA-DRB1*0405 and 0901*0602, which could partially account for the association at rs9272105. The association at rs455804 implicates GRIK1 as a novel susceptibility gene for HBV–related HCC, suggesting the involvement of glutamate signaling in the development of HBV–related HCC

XBRLによる財務報告に関する実証研究

早大学位記番号:新8935早稲田大

Effect of TiC on Microstructure and Properties of Wear-Resistant Mo2FeB2 Claddings

Alloy blocks with different TiC content were designed, and Mo2FeB2 cermets were prepared by carbon arc surfacing process. The interaction law of TiC content and the microstructure, phase, composition, hardness and wear resistance of the cladding were studied in detail by the combination of experiment and theoretical analysis. On the other hand, the phase transition process of the weldpool is theoretically analyzed by thermodynamic calculation method. XRD test results show that in addition to Mo2FeB2 synthesized in situ, the cladding also forms phases such as TiC, CrB, MoB and Fe-Cr. The number of Mo2FeB2 hard phases gradually increases when TiC content varies from 0% to 15%. The average microhardness of the cladding with 0%, 5%, 10%, and 15% TiC was 992 HV0.5, 1035 HV0.5, 1018 HV0.5 and 689 HV0.5, respectively, with 5% TiC being the largest. Moreover, the cladding with 5% TiC content has excellent wear resistance, which is 14.6 times that of the substrate

Numerical Research on a T-Foil Control Method for Trimarans Based on Phase Lag

The lift force of a T-foil, which varies with ship motion, can counteract the wave exciting force during wave encounters. The phase difference between the periodic lift force and the wave exciting force significantly impacts the T-foil’s effectiveness. This study investigates the phase difference between lift force and motion to optimize the control equation for the T-foil’s angle, thereby reducing negative feedback. The T-foil’s hydrodynamic performance is first calculated using computational fluid dynamics. Time-domain calculations of the phase lag between lift force and motion under open-loop control in still water are then used to determine the dimensionless phase lag of the T-foil’s angle at various frequencies, facilitating further optimization of the control method. Finally, calculations of trimaran heave and pitch in regular waves are conducted. The results demonstrate that, under phase lag control, the T-foil’s lift force phase precedes ship motion by approximately 0.2 s, reducing hysteresis in the anti-vertical motion effect. Comparisons of vertical hull motions between different control methods reveal a 20% reduction in vertical motion with phase lag control compared to pitch control. This study concludes that phase lag is a crucial factor in T-foil control optimization

Task-Adaptive Meta-Learning Framework for Advancing Spatial Generalizability

Spatio-temporal machine learning is critically needed for a variety of societal applications, such as agricultural monitoring, hydrological forecast, and traffic management. These applications greatly rely on regional features that characterize spatial and temporal differences. However, spatio-temporal data often exhibit complex patterns and significant data variability across different locations. The labels in many real-world applications can also be limited, which makes it difficult to separately train independent models for different locations. Although meta learning has shown promise in model adaptation with small samples, existing meta learning methods remain limited in handling a large number of heterogeneous tasks, e.g., a large number of locations with varying data patterns. To bridge the gap, we propose task-adaptive formulations and a model-agnostic meta-learning framework that transforms regionally heterogeneous data into location-sensitive meta tasks. We conduct task adaptation following an easy-to-hard task hierarchy in which different meta models are adapted to tasks of different difficulty levels. One major advantage of our proposed method is that it improves the model adaptation to a large number of heterogeneous tasks. It also enhances the model generalization by automatically adapting the meta model of the corresponding difficulty level to any new tasks. We demonstrate the superiority of our proposed framework over a diverse set of baselines and state-of-the-art meta-learning frameworks. Our extensive experiments on real crop yield data show the effectiveness of the proposed method in handling spatial-related heterogeneous tasks in real societal applications