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Background: Recent advancements in generative artificial intelligence (AI) for image generation have presented significant opportunities for medical imaging, offering a promising way to generate realistic virtual medical images while ensuring patient privacy. The generation of a large number of virtual medical images through AI has the potential to augment training datasets for discriminative AI models, particularly in fields with limited data availability, such as neuroimaging. Current studies on generative AI in neuroimaging have mainly focused on disease discrimination; however, its potential for simulating complex phenomena in psychiatric disorders remains unknown. In this study, as examples of a simulation, we aimed to present a novel generative AI model that transforms magnetic resonance imaging (MRI) images of healthy individuals into images that resemble those of patients with schizophrenia (SZ) and explore its application. Methods: We used anonymized public datasets from the Center for Biomedical Research Excellence (SZ, 71 patients; healthy subjects [HSs], 71 patients) and the Autism Brain Imaging Data Exchange (autism spectrum disorder [ASD], 79 subjects; HSs, 105 subjects). We developed a model to transform MRI images of HSs into MRI images of SZ using cycle generative adversarial networks. The efficacy of the transformation was evaluated using voxel-based morphometry to assess the differences in brain region volumes and the accuracy of age prediction pre- and post-transformation. In addition, the model was examined for its applicability in simulating disease comorbidities and disease progression. Results: The model successfully transformed HS images into SZ images and identified brain volume changes consistent with existing case-control studies. We also applied this model to ASD MRI images, where simulations comparing SZ with and without ASD backgrounds highlighted the differences in brain structures due to comorbidities. Furthermore, simulating disease progression while preserving individual characteristics showcased the model's ability to reflect realistic disease trajectories. Discussion: The results suggest that our generative AI model can capture subtle changes in brain structures associated with SZ, providing a novel tool for visualizing brain changes in different diseases. The potential of this model extends beyond clinical diagnosis to advances in the simulation of disease mechanisms, which may ultimately contribute to the refinement of therapeutic strategies. [ABSTRACT FROM AUTHOR]

The article focuses on the accelerated progression of early-onset Alzheimer's disease (EOAD) due to cerebral amyloid angiopathy (CAA) in a 61-year-old woman. Topics include the patient's initial diagnosis of mild cognitive impairment, the role of CAA in cognitive decline and Alzheimer's disease, and the importance of monitoring risk factors like alcohol consumption and hypertension in EOAD cases.

We previously reported that variations in the number and type of bacteria found in public spaces are influenced by environmental factors. However, based on field survey data alone, whether the dynamics of bacteria in the air change as a result of a single environmental factor or multiple factors working together remains unclear. To address this, mathematical modeling may be applied. We therefore conducted a reanalysis of the previously acquired data using principal component analysis (PCA) in conjunction with a generalized linear model (Glm2) and a statistical analysis of variance (ANOVA) test employing the χ2 distribution. The data used for the analysis were reused from a previous public environmental survey conducted at 8:00–20:00 on May 2, June 1, and July 5, 2016 (regular sampling) and at 5:50–7:50 and 20:15–24:15 on July 17, 2017 (baseline sampling) in the Sapporo underground walking space, a 520-meter-long underground walkway. The dataset consisted of 60 samples (22 samples for "bacterial flora"), including variables such as "temperature (T)," "humidity (H)," "atmospheric pressure (A)," "traffic pedestrians (TP)," "number of inorganic particles (Δ5: 1–5 μm)," "number of live airborne bacteria," and "bacterial flora." Our PCA with these environmental factors (T, H, A, and TP) revealed that the 60 samples could be categorized into four groups (G1 to G4), primarily based on variations in PC1 [Loadings: T(˗0.62), H(˗0.647), TP(0.399), A(0.196)] and PC2 [Loadings: A(˗0.825), TP(0.501), H(0.209), T(˗0.155)]. Notably, the number of inorganic particles significantly increased from G4 to G1, but the count of live bacteria was highest in G2, with no other clear pattern. Further analysis with Glm2 indicated that changes in inorganic particles could largely be explained by two variables (H/TP), while live bacteria levels were influenced by all explanatory variables (TP/A/H/T). ANOVA tests confirmed that inorganic particles and live bacteria were influenced by different factors. Moreover, there were minimal changes in bacterial flora observed among the groups (G1–G4). In conclusion, our findings suggest that the dynamics of live bacteria in the underground walkway differ from those of inorganic particles and are regulated in a complex manner by multiple environmental factors. This discovery may contribute to improving public health in urban settings. [ABSTRACT FROM AUTHOR]

With the development of electronics, there is an increasing demand for high‐performance heat‐dissipation materials in electronic devices. Thermal conductive silicone rubber (SR) has received significant attention in related industries due to its excellent mechanical flexibility and high thermal conductivity. However, the intrinsic thermal conductivity of SR is low, necessitating the addition of thermal conductive fillers to meet the usage requirements. Common thermal conductive fillers typically exist in powder form and require such surface modification and orientation, which increases production costs and poses challenges for large‐scale production. In this study, continuous carbon fibers (CFs) are utilized as fillers. By employing a simple pre‐infiltration and winding method, CFs are uniformly distributed in SR, aligning parallel. The CFs not only serve as thermal conductive pathways but also maintain their orientation distribution within the substrate. Furthermore, by pre‐adding boron nitride (BN) to the SR, the thermal conductivity of SR is enhanced, and BN is distributed along the fibers, further improving the enhancement effect of BN on the thermal conductivity of SR. When CF content reaches 30 vol%, the thermal conductivity of CF/BN/SR composite reaches 2.789 W m−1 K−1. Moreover, by using BN/SR before curing as a coating, it can be applied to the surface of the CF/BN/SR composite. This greatly increases the volume resistivity of the material (>1014 Ω cm) while maintaining the thermal conductivity of the composite. Using continuous fibers as fillers also enables easier implementation of mass production in the preparation of thermal conductive SR. Highlights: Prepare continuous carbon fiber and boron nitride (BN)‐filled composite through mechanical winding;The carbon fiber (CF)/BN/silicone rubber (SR) composite exhibits high thermal conductivity;Improve the enhancement of BN on the TC of SR by aligning the BN along the CF;BN/SR used as insulating coating by incremental curing. [ABSTRACT FROM AUTHOR]

Research has repeatedly shown that people tend to conform to local norms. In intergroup conflicts, where most group members engage in some type of aggressive behavior towards out‐group members (out‐group aggression), individuals are predicted to conform to other in‐group members engaging in out‐group aggression. In this study, we defined out‐group aggression that was a result of conformity to in‐group members as “conformity‐based out‐group aggression” and examined its emergence and the possibility that being observed by in‐group members (in‐group audience) strengthens such out‐group aggression in an experimental setting. We conducted an online experiment with 108 Japanese undergraduates. The results showed that when their in‐group members engaged in out‐group aggression, participants perceived a stronger pro‐aggression norm and exhibited more intense out‐group aggression. This effect was slightly more pronounced among those with a greater disposition to avoid rejection. However, the effect of the in‐group audience was non‐significant. Our findings highlight the difficulty of intergroup conflict resolution. [ABSTRACT FROM AUTHOR]

Drug-induced liver injury (DILI) is a major concern associated with the use of avacopan, a new therapeutic agent for antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV). Here, we report a rare instance of liver biopsy performed for persistent liver injury following discontinuation of avacopan in an elderly woman with microscopic polyangiitis (MPA). The patient developed cholestatic liver injury after 2 months of avacopan therapy, which led to drug cessation. Despite the discontinuation of avacopan followed by supportive care, the liver enzyme levels remained elevated, necessitating liver biopsy. Histological examination revealed residual inflammation and focal necrosis around the portal vein, indicating ongoing liver injury despite avacopan withdrawal. This case report highlights the hepatotoxic potential of avacopan, the importance of vigilant liver function monitoring, and the value of liver biopsy in the chronic phase of avacopan-induced liver injury. Further research is required to elucidate avacopan hepatotoxicity mechanisms and identify potential risk factors for DILI in patients with AAV., (© Japan College of Rheumatology 2024. Published by Oxford University Press. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site–for further information please contact journals.permissions@oup.com.)

A 77-year-old woman with a history of endovascular aneurysm repair (EVAR) for an abdominal aortic aneurysm (AAA) presented with melena. She had been recently diagnosed with IgG4-related periaortitis and started on prednisone. Physical examination revealed pallor conjunctiva and melena on the rectal examination, with laboratory results indicating anemia (hemoglobin: 7.4 g/dl). Abdominal CT showed air within the aneurysmal sac, and endoscopy confirmed an aortoduodenal fistula. The patient underwent urgent stent removal, vessel replacement, and duodenal repair. She recovered well and was discharged on day 30 with ongoing prednisone therapy. The risk of fistula formation in IgG4-related periaortitis necessitates careful monitoring, especially in patients with pre-existing aortic pathology., Competing Interests: Human subjects: Consent for treatment and open access publication was obtained or waived by all participants in this study. Conflicts of interest: In compliance with the ICMJE uniform disclosure form, all authors declare the following: Payment/services info: All authors have declared that no financial support was received from any organization for the submitted work. Financial relationships: All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work. Other relationships: All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work., (Copyright © 2024, Shizuku et al.)

Objectives: To efficiently detect somatic UBA1 variants and establish a clinical scoring system predicting patients with pathogenic variants in VEXAS (vacuoles, E1 enzyme, X-linked, autoinflammatory, somatic) syndrome., Methods: Eighty-nine Japanese patients with clinically suspected VEXAS syndrome were recruited [81 males and 8 females; median age of onset 69.3 years (interquartile range 62.1-77.6)]. Peptide nucleic acid-clamping PCR (PNA-PCR), regular PCR targeting exon 3 clustering UBA1 variants and subsequent Sanger sequencing were conducted for variant screening. Partitioning digital PCR or targeted amplicon deep sequencing was also performed to evaluate the variant allele frequency (VAF). We developed our clinical scoring system to predict UBA1 variant-positive and -negative patients and assessed the diagnostic value of our system using receiver operating characteristics (ROC) curve analysis., Results: Forty patients (44.9%) with reported pathogenic UBA1 variants were identified, including a case having a variant with VAF of 1.7%, using a highly sensitive method. Our clinical scoring system considering age >50 years, cutaneous lesions, lung involvement, chondritis and macrocytic anaemia efficiently predicted patients with UBA1 variants (the area under the curve for the scoring total was 0.908)., Conclusion: Genetic screening with the combination of regular PCR and PNA-PCR detected somatic UBA1 variants with high sensitivity and specificity. Our scoring system could efficiently predict patients with UBA1 variants., (© The Author(s) 2023. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For permissions, please email: journals.permissions@oup.com.)