Keio University Shonan Fujisawa

We aimed to examine the psychometric properties of the second version of the Brief Evaluation of Psychosis Symptom Domains (BE-PSD-V2.0) and its correspondence with the Positive and Negative Syndrome Scale (PANSS) and Clinical Global Impression-Severity scale (CGI-S) scores. This cross-sectional study was conducted at 18 institutes in Japan. We performed correlational analyses to test the convergent and divergent validity of the BE-PSD-V2.0. Inter-rater reliability was assessed using intraclass correlation coefficients (ICCs). The equipercentile equating method was employed to examine the linking of the BE-PSD-V2.0 with the PANSS and the CGI-S. A total of 353 patients with schizophrenia spectrum disorders were included. Spearman's rank correlation coefficients between the BE-PSD-V2.0 item scores and their corresponding PANSS factor scores ranged from 0.64 to 0.86, indicating sufficient convergent validity. These specific correlation coefficients were consistently the highest among all item-to-factor comparisons, indicating sufficient divergent validity. In 34 patients, ICCs for the BE-PSD-V2.0 itemand total scores ranged from 0.60 to 0.94, showing sufficient inter-rater reliability. Conversion tables were established between the BE-PSD-V2.0 total score and the PANSS total score, between the BE-PSD-V2.0 total score and the CGI-S score, and between the BE-PSD-V2.0 item scores and their corresponding PANSS factor scores. A correspondence between symptomatic remission criteria using the PANSS and BE-PSD-V2.0 was confirmed. The BE-PSD-V2.0 possesses sufficient psychometric properties and corresponds to the PANSS and CGI-S. It is a sound and reliable brief rating scale for assessing symptoms in schizophrenia spectrum disorders, and its established conversion correspondences facilitate score interpretation within existing clinical paradigms for both clinical practice and research.

Approximately 30% of patients with schizophrenia do not respond to antipsychotics. While schizophrenia has been primarily explained by the dopamine dysfunction hypothesis, treatment-resistant schizophrenia (TRS) may involve a different pathophysiology. Neuromelanin (NM), a product of dopamine metabolism in the substantia nigra (SN), indirectly measures long-term dopamine synthesis capacity. Few studies have examined SN NM levels in TRS. Therefore, we investigated the relationship between SN NM levels and treatment responsiveness in schizophrenia. We included age- and sex-matched TRS, patients with schizophrenia in remission of positive symptoms (SZ-R), and healthy controls (HCs). Neuromelanin-sensitive magnetic resonance imaging was used to measure SN NM signals. We also evaluated clinical symptoms and cognitive impairment. We conducted voxel-wise analyses of NM contrast-to-noise ratio (CNR) to compare groups pairwise. Correlation analyses examined relationships between NM signals and symptom severity. Seventy-two participants (n = 24 per group) completed the study. The TRS group had higher dorsal SN CNR than the HC group (510 out of 1948 voxels at p < 0.05, corrected p = 0.005, permutation test). In contrast, no significant differences were observed in the other comparisons. No significant correlations were found between NM CNR and clinical severity. Our findings contrast with previous positron emission tomography studies on dorsal striatal dopamine function. Since the dorsal SN contributes to both the mesolimbic and nigrostriatal pathways, with a relatively greater role in the former, dopamine functions in these pathways may play different roles for treatment responsiveness. Further research with multimodal imaging is needed to examine dopamine function and antipsychotic treatment responsiveness in schizophrenia.

Abstract We simulated a tropical cyclone in an idealized environment, from its weak initial vortex to maturity, using a regional numerical weather prediction model with a uniform horizontal resolution of 100 m, regarded as a large eddy simulation (LES). Results of the LES were compared with those of the same model, but with a horizontal resolution of 2 km. Both experiments attained similar peak intensities ( hPa), but the LES uniquely captured kilometer‐scale rolls in the boundary layer, persistent shallow mesovortices near the eyewall, and countless sub‐kilometer‐scale patches of positive and negative vorticity. Rapid intensification (RI) in the LES was delayed by approximately 26 hr relative to that in the 2 km model. Composite analysis confirmed that mesovortices interfered with the azimuthally averaged secondary circulation. The prevalence of negative vorticity and decelerated inflow in the LES are likely to delay the RI.

The issue of transportation and the environment began with the advent of the Industrial Revolution, when vehicles powered by fossil fuels were introduced. At that time, the impact of transportation equipment and infrastructure on the environment was limited. However, the rapid growth of motorization in the first half of the twentieth century led to the emergence of significant environmental problems in urban areas. These issues, which were initially confined to developed countries, became more pronounced after World War II. Air pollution caused by automobile exhaust gases led to the implementation of pollutant emission regulations in various countries and regions. However, with the expansion of the global economy, the utilization of natural resources, including fossil fuels, has increased exponentially, accompanied by a parallel surge in waste emissions. In 1972, the Club of Rome published a report titled “Limits to Growth,” [1] which warned that if population growth and environmental pollution continue unabated, growth on Earth will reach its limit within 100 years.

This chapter traces the evolution of startup ecosystems in mainland China, from the “Reform and Opening-Up” era to the present day. It begins with a historical overview, examining China’s transition from a state-dominated economy to a vibrant, market-oriented landscape. This shift was driven by the pivotal policies like the “Torch Plan”, the rise of university-industry collaboration, and the influence of “returnee” entrepreneurs. The chapter then analyses the transformative impact of the 2014 “Mass Entrepreneurship and Innovation” initiative on funding, infrastructure, and cultural attitudes. Through a comparative analysis of four major innovation hubs—Beijing, Suzhou, Chongqing, and Shenzhen—it explores the similarities and the unique advantages, policy approaches, and industrial specialisations of each city. Ultimately, this chapter offers crucial insights for policymakers aiming to foster sustainable growth and for entrepreneurs navigating China’s dynamic startup landscape.