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Machine learning can be used to define subtypes of psychiatric conditions based on shared biological foundations of mental disorders. Here we analyzed cross-sectional brain images from 4,222 individuals with schizophrenia and 7038 healthy subjects pooled across 41 international cohorts from the ENIGMA, non-ENIGMA cohorts and public datasets. Using the Subtype and Stage Inference (SuStaIn) algorithm, we identify two distinct neurostructural subgroups by mapping the spatial and temporal trajectory of gray matter change in schizophrenia. Subgroup 1 was characterized by an early cortical-predominant loss with enlarged striatum, whereas subgroup 2 displayed an early subcortical-predominant loss in the hippocampus, striatum and other subcortical regions. We confirmed the reproducibility of the two neurostructural subtypes across various sample sites, including Europe, North America and East Asia. This imaging-based taxonomy holds the potential to identify individuals with shared neurobiological attributes, thereby suggesting the viability of redefining existing disorder constructs based on biological factors.

BACKGROUND: The fast-growing migrant population in Japan and globally poses challenges in mental healthcare, yet research addressing migrants mental health treatment engagement remains limited. OBJECTIVE: This study examined language proficiency, demographic and clinical characteristics as predictors of early treatment discontinuation among migrants. METHODS: Electronic health record data from 196 adult migrants, identified from 14 511 patients who received mental health outpatient treatment during 2016 and 2019 at three central hospitals in the Tokyo-Yokohama metropolitan region of Japan, were used. We conducted multivariable regression models to identify predictors of early discontinuation within 3 months. FINDINGS: The study cohort (65% women, age range: 18-90 years, from 29 countries or regions) included 23% non-Japanese speakers. Japanese and non-Japanese speakers had similar discontinuation rates (26% vs 22%). Multivariable models revealed younger age (OR=0.97; 95% CI: 0.95, 0.99; p=0.016) and those with a primary diagnosis other than a schizophrenia spectrum disorder (OR=3.99; 95% CI: 1.36, 11.77; p=0.012) or a neurotic, stress-related and somatoform disorder (OR=2.79; 95% CI: 1.14, 6.84; p=0.025) had higher odds of early discontinuation. These effects were more pronounced among the Japanese speakers with significant language-by-age and language-by-diagnoses interactions. CONCLUSION: Younger age and having a primary diagnosis other than a schizophrenia spectrum disorder or a neurotic, stress-related and somatoform disorder increased vulnerability for discontinuing mental health treatment early in Japanese-speaking migrants but not for migrants with limited Japanese proficiency. CLINICAL IMPLICATIONS: Understanding language needs within a context of mental health treatment should go beyond assumed or observed fluency. Unmet language needs might increase vulnerability for treatment disengagement among migrants. Targeted clinical efforts are crucial for enhancing early treatment engagement and informing health practices in Japan and countries with growing migrant populations.

Machine learning approaches using structural magnetic resonance imaging (sMRI) can be informative for disease classification, although their ability to predict psychosis is largely unknown. We created a model with individuals at CHR who developed psychosis later (CHR-PS+) from healthy controls (HCs) that can differentiate each other. We also evaluated whether we could distinguish CHR-PS+ individuals from those who did not develop psychosis later (CHR-PS-) and those with uncertain follow-up status (CHR-UNK). T1-weighted structural brain MRI scans from 1165 individuals at CHR (CHR-PS+, n = 144; CHR-PS-, n = 793; and CHR-UNK, n = 228), and 1029 HCs, were obtained from 21 sites. We used ComBat to harmonize measures of subcortical volume, cortical thickness and surface area data and corrected for non-linear effects of age and sex using a general additive model. CHR-PS+ (n = 120) and HC (n = 799) data from 20 sites served as a training dataset, which we used to build a classifier. The remaining samples were used external validation datasets to evaluate classifier performance (test, independent confirmatory, and independent group [CHR-PS- and CHR-UNK] datasets). The accuracy of the classifier on the training and independent confirmatory datasets was 85% and 73% respectively. Regional cortical surface area measures-including those from the right superior frontal, right superior temporal, and bilateral insular cortices strongly contributed to classifying CHR-PS+ from HC. CHR-PS- and CHR-UNK individuals were more likely to be classified as HC compared to CHR-PS+ (classification rate to HC: CHR-PS+, 30%; CHR-PS-, 73%; CHR-UNK, 80%). We used multisite sMRI to train a classifier to predict psychosis onset in CHR individuals, and it showed promise predicting CHR-PS+ in an independent sample. The results suggest that when considering adolescent brain development, baseline MRI scans for CHR individuals may be helpful to identify their prognosis. Future prospective studies are required about whether the classifier could be actually helpful in the clinical settings.

BACKGROUND: Cartilage harvest and transplantation is a common surgery using costal, auricular, and septal cartilage for craniofacial reconstruction. However, absorption and warping of the cartilage grafts can occur due to inflammatory factors associated with wound healing. Transcription factor nuclear factor-κB (NF-κB) is activated by the various stimulation such as interleukin-1 (IL-1), and plays a central role in the transactivation of this inflammatory cytokine gene. Inhibition of NF-κB may have anti-inflammatory effects. The aim of this study was to explore the potential of an NF-κB decoy oligodeoxynucleotide (Decoy) as a chondroprotective agent. MATERIALS AND METHODS: Safe and efficacious concentrations of Decoy were assessed using rabbit nasal septal chondrocytes (rNSChs) and assays for cytotoxicity, proteoglycan (PG) synthesis, and PG turnover were carried out. The efficacious concentration of Decoy determined from the rNSChs was then applied to human nasal septal cartilage (hNSC) in vitro and analyzed for PG turnover, the levels of inflammatory markers, and catabolic enzymes in explant-conditioned culture medium. RESULTS: Over the range of Decoy conditions and concentrations, no inhibition of PG synthesis or cytotoxicity was observed. Decoy at 10 μM effectively inhibited PG degradation in the hNSC explant, prolonging PG half-life by 63% and decreasing matrix metalloprotease 3 (MMP-3) by 70.7% (p = 0.027). CONCLUSIONS: Decoy may be considered a novel chondroprotective therapeutic agent in cartilage transplantation due to its ability to inhibit cartilage degradation due to inflammation cytokines.

Differential diagnosis is sometimes difficult in practical psychiatric settings, in terms of using the current diagnostic system based on presenting symptoms and signs. The creation of a novel diagnostic system using objective biomarkers is expected to take place. Neuroimaging studies and others reported that subcortical brain structures are the hubs for various psycho-behavioral functions, while there are so far no neuroimaging data-driven clinical criteria overcoming limitations of the current diagnostic system, which would reflect cognitive/social functioning. Prior to the main analysis, we conducted a large-scale multisite study of subcortical volumetric and lateralization alterations in schizophrenia, bipolar disorder, major depressive disorder, and autism spectrum disorder using T1-weighted images of 5604 subjects (3078 controls and 2526 patients). We demonstrated larger lateral ventricles volume in schizophrenia, bipolar disorder, and major depressive disorder, smaller hippocampus volume in schizophrenia and bipolar disorder, and schizophrenia-specific smaller amygdala, thalamus, and accumbens volumes and larger caudate, putamen, and pallidum volumes. In addition, we observed a leftward alteration of lateralization for pallidum volume specifically in schizophrenia. Moreover, as our main objective, we clustered the 5,604 subjects based on subcortical volumes, and explored whether data-driven clustering results can explain cognitive/social functioning in the subcohorts. We showed a four-biotype classification, namely extremely (Brain Biotype [BB] 1) and moderately smaller limbic regions (BB2), larger basal ganglia (BB3), and normal volumes (BB4), being associated with cognitive/social functioning. Specifically, BB1 and BB2-3 were associated with severe and mild cognitive/social impairment, respectively, while BB4 was characterized by normal cognitive/social functioning. Our results may lead to the future creation of novel biological data-driven psychiatric diagnostic criteria, which may be expected to be useful for prediction or therapeutic selection.

According to the operational diagnostic criteria, psychiatric disorders such as schizophrenia (SZ), bipolar disorder (BD), major depressive disorder (MDD), and autism spectrum disorder (ASD) are classified based on symptoms. While its cluster of symptoms defines each of these psychiatric disorders, there is also an overlap in symptoms between the disorders. We hypothesized that there are also similarities and differences in cortical structural neuroimaging features among these psychiatric disorders. T1-weighted magnetic resonance imaging scans were performed for 5,549 subjects recruited from 14 sites. Effect sizes were determined using a linear regression model within each protocol, and these effect sizes were meta-analyzed. The similarity of the differences in cortical thickness and surface area of each disorder group was calculated using cosine similarity, which was calculated from the effect sizes of each cortical regions. The thinnest cortex was found in SZ, followed by BD and MDD. The cosine similarity values between disorders were 0.943 for SZ and BD, 0.959 for SZ and MDD, and 0.943 for BD and MDD, which indicated that a common pattern of cortical thickness alterations was found among SZ, BD, and MDD. Additionally, a generally smaller cortical surface area was found in SZ and MDD than in BD, and the effect was larger in SZ. The cosine similarity values between disorders were 0.945 for SZ and MDD, 0.867 for SZ and ASD, and 0.811 for MDD and ASD, which indicated a common pattern of cortical surface area alterations among SZ, MDD, and ASD. Patterns of alterations in cortical thickness and surface area were revealed in the four major psychiatric disorders. To our knowledge, this is the first report of a cross-disorder analysis conducted on four major psychiatric disorders. Cross-disorder brain imaging research can help to advance our understanding of the pathogenesis of psychiatric disorders and common symptoms.

Vincetoxicum Wolf is the third largest genus in Asclepiadoideae, and 23 species are distributed in Japan. We discovered that an erect herb species, distributed in the eastern part of the Honshu island, was invalidly named Vincetoxicum magnificum (Nakai) Kitag. based on Cynanchum magnificum Nakai, nomen nudum. Therefore, we presently name this species Vincetoxicum nakaianum K.Mochizuki & Ohi-Toma, and we give a detailed description in this study. Additionally, we provide photographs that demonstrate its ecology and diagnostic characteristics.

Abstract In this study, equine intestinal enteroids (EIEs) were generated from the duodenum, jejunum, and ileum and inoculated with equine coronavirus (ECoV) to investigate their suitability as in vitro models with which to study ECoV infection. Immunohistochemistry revealed that the EIEs were composed of various cell types expressed in vivo in the intestinal epithelium. Quantitative reverse-transcription PCR (qRT-PCR) and virus titration showed that ECoV had infected and replicated in the EIEs. These results were corroborated by electron microscopy. This study suggests that EIEs can be novel in vitro tools for studying the interaction between equine intestinal epithelium and ECoV.

Abstract Background The approval of lecanemab, an anti-amyloid therapy for Alzheimer’s disease (AD), necessitates addressing healthcare preparedness for disease-modifying treatment (DMT) to ensure appropriate, safe, and sustainable drug administration. Understanding public perceptions on this matter is crucial. We aimed to assess discrepancies and similarities in the perceptions of Japanese trial-ready cohort study (‘J-TRC webstudy’) participants and clinical specialists in the fields of dementia treatment and radiology, concerning affairs related to challenges in DMT preparedness. Methods This was a cross-sectional prospective observational study conducted in November–December 2023. The J-TRC webstudy participants were invited to participate in an online survey using Google Forms, and clinical specialists were invited to complete a mail-based survey. Main questionnaire items had been designed to be common in both surveys, and their responses were analyzed for participant attributes, interests, attitudes, expectations, and concerns about DMTs without specifying lecanemab. Results Responses were obtained from n = 2,050 J-TRC webstudy participants and n = 1,518 clinical specialists. Compared to specialists, more J-TRC respondents perceived the eligible proportion for DMT as smaller (59.1% versus 30.7%), perceived the eligible severity for DMT as more limited (58.0% versus 24.5%), and perceived the efficacy of DMT as slightly more encouraging (29.3% versus 34.8%). In terms of treatment prioritization, both J-TRC respondents and specialist respondents exhibited similar levels of acceptance for prioritizing patients to treat: e.g., approximately two-thirds endorsed patient prioritization under hypothetical resource constraints or other reasons. A medical rationale emerged as the most compelling reason for acceptance of patient prioritization across the surveys. In contrast, the need to address vulnerable populations was the reason that led to the least acceptance of prioritization, followed by economic considerations. Conclusions Our findings offer valuable insights into the discrepancies in knowledge and perception between patients and healthcare providers. This could enhance the delivery of patient information in clinical settings and inform the discussion surrounding patient prioritization strategies.

Background/purpose: Cementum shares many properties with bone; however, in contrast to bone, it is not innervated or vascularized and has a limited capacity for remodeling. Osteocytes located in the lacunae-canalicular system of bone tissue play a central role in bone remodeling by communicating with osteoblasts and osteoclasts. Although cementocytes are present in cellular cementum and are morphologically similar to osteocytes, it remains unclear whether they are involved in the dynamic functional regulation of metabolism in cementum. The present study focused on the extracellular vesicles (EVs) secreted by cementocytes and examined their effects on osteoclasts and osteoblasts. Materials and methods: EVs were extracted from the mouse cementocyte cell line, IDG-CM6. The effects of EVs on recombinant RANKL-induced osteoclastogenesis and recombinant Bone morphogenetic protein (BMP)-2-mediated osteoblastogenesis were investigated using the mouse osteoclast progenitor cell line, RAW264.7 and mouse pre-osteoblast cell line, MC3T3-E1, respectively. Results: EVs enhanced the formation of tartrate-resistant acid phosphatase activity-positive cells. Real-time PCR revealed that EVs up-regulated the expression of osteoclast-related genes. On the other hand, the cell culture supernatant of cementocytes significantly inhibited the differentiation of osteoclasts. Regarding osteoblastogenesis, EVs suppressed the expression of alkaline phosphatase, bone sialoprotein, and osteocalcin induced by recombinant BMP-2 at the gene and protein levels. Conclusion: A network of cementocytes, osteoblasts, and osteoclasts may exist in cellular cementum, which suggests the involvement of cementocytes in dynamic metabolism of cementum through EVs.

Abstract Recent evidence indicates that liver cirrhosis (LC) is a reversible condition, but there is no established intervention against liver fibrosis. Although the gut microbiota is considered involved in the pathogenesis of LC, the underlying mechanisms remain unclear. Although the antibiotic, rifaximin (RFX), is effective for hepatic encephalopathy (HE) with LC, the impact of RFX on intestinal bacteria is unknown. We investigated the bacterial compositions along the GI tract under RFX treatment using a murine LC model. RFX improved liver fibrosis and hyperammonemia and altered the bacterial composition in the small intestine. The efficacy of RFX was associated with increases in specific bacterial genera, including Akkermansia. Administration of a commensal strain of Akkermansia muciniphila improved liver fibrosis and hyperammonemia with changing bacterial composition in the small intestine. This study proposed a new concept “small intestine-liver axis” in the pathophysiology of LC and oral A. muciniphila administration is a promising microbial intervention.

Abstract Although stereotactic body radiotherapy (SBRT) is a curative treatment option for stage I non‐small cell lung cancer (NSCLC), limited data are available regarding chest wall (CW) toxicities during an extended follow‐up of over 10 years. We report an unusual case of a bone tumor‐like CW mass lesion with pathological rib fractures observed 13 years after SBRT for peripheral lung cancer. Despite the initial suspicion of radiation‐induced sarcoma, a subsequent incisional biopsy revealed no evidence of malignancy, and a definitive diagnosis of osteonecrosis was made. Thus, long‐term observation of over 10 years is required to identify late chronic complications following SBRT.

Perfusion index (PI) is used as assessment of epidural anaesthesia efficacy in human medicine, but its usefulness in dogs is unknown. The aim of this study was to evaluate the usefulness of PI in determining epidural anaesthesia effectiveness.

Abstract Background The predictive power of the treatment efficacy and prognosis in primary androgen deprivation therapy (ADT) for advanced prostate cancer is not satisfactory. The objective of this study was to integrate genetic and clinical data to predict castration resistance in primary ADT for advanced prostate cancer by machine learning (ML). Methods Clinical and single nucleotide polymorphisms (SNP) data obtained in the KYUCOG-1401-A study (UMIN000022852) that enrolled Japanese patients with advanced prostate cancer were used. All patients were treated with primary ADT. A point-wise linear (PWL) algorithm, logistic regression with elastic-net regularization, and eXtreme Gradient Boosting were the ML algorithms used in this study. Area under the curve for castration resistance and C-index for prognoses were calculated to evaluate the utility of the models. Results Among the three ML algorithms, the area under the curve values to predict castration resistance at 2 years was highest for the PWL algorithm with all the datasets. Three predictive models (clinical model, small SNPs model, and large SNPs model) were created by the PWL algorithm using the clinical data alone, and 2 and 46 SNPs in addition to clinical data. C-indices for overall survival by the clinical, small SNPs, and large SNPs models were 0.636, 0.621, and 0.703, respectively. Conclusion The results demonstrated that the SNPs models created by ML produced excellent prediction of castration resistance and prognosis in primary ADT for advanced prostate cancer, and will be helpful in treatment choice.

Submucosal invasive (T1) colorectal cancer is a significant clinical management challenge, with an estimated 10% of patients developing extraintestinal lymph node metastasis. This condition necessitates surgical resection along with lymph node dissection to achieve a curative outcome. Thus, the precise preoperative assessment of lymph node metastasis risk is crucial to guide treatment decisions after endoscopic resection. Contemporary clinical guidelines strive to identify a low-risk cohort for whom endoscopic resection will suffice, applying stringent criteria to maximize patient safety. Those failing to meet these criteria are often recommended for surgical resection, with its associated mortality risks although it may still include patients with a low risk of metastasis. In the quest to enhance the precision of preoperative lymph node metastasis risk prediction, innovative models leveraging artificial intelligence or nomograms are being developed. Nevertheless, the debate over the ideal sensitivity and specificity for such models persists, with no consensus on target metrics. This review puts forth postoperative mortality rates as a practical benchmark for the sensitivity of predictive models. We underscore the importance of this method and advocate for research to amass data on surgical mortality in T1 colorectal cancer. Establishing specific benchmarks for predictive accuracy in lymph node metastasis risk assessment will hopefully optimize the treatment of T1 colorectal cancer.

Introduction: Although the prevalence of Alzheimer’s disease (AD) is higher in older people compared to younger people, dementia has also been documented in younger adults. Although early-onset dementia and late-onset dementia had been considered a single disease in pathological investigations, many studies revealed differences in cognitive and neuroimaging changes between them. We evaluated differences in cognitive and neuroimaging changes among the following groups: individuals with early-onset AD (EOAD), late-onset AD (LOAD), early-onset mild cognitive impairment (EOMCI), or late-onset MCI (LOMCI), and healthy controls (HCs). Methods: Patients underwent both a 1.5 Tesla magnetic resonance imaging scan and the Mini-Mental State Examination (MMSE). Differences in regional gray matter volumes and MMSE subscales were investigated among the five diagnostic groups. Results: Compared to the EOAD group, the LOAD group had significantly higher scores on orientation in place. Compared to the LOMCI patients, the EOMCI patients achieved significantly higher recall scores. The LOAD and LOMC groups showed significant volume reductions in bilateral medial temporal regions compared to the HCs. The EOAD and EOMCI groups did not show significant atrophy of the medial temporal region compared to the HC group. Conclusions: The hippocampal volume and memory were preserved in the patients with EOMCI or EOAD compared to those with LOMCI or LOAD. These findings may indicate that the distinct and differing patterns of neuropsychological changes between EOAD and LOAD are also common in MCI, which is intermediate between normal cognition and AD.

Abstract Moiré superlattices consisting of two-dimensional materials have attracted immense attention because of emergent phenomena such as flat band-induced Mott insulating states and unconventional superconductivity. However, the effects of spin-orbit coupling on these materials have not yet been fully explored. Here, we show that single- and double-bilayer antimony honeycomb lattices, referred to as antimonene, form moiré superlattices on a Bi(111) substrate due to lattice mismatch. Scanning tunnelling microscopy (STM) measurements reveal the presence of spectral peaks near the Fermi level, which are spatially modulated with the moiré period. Angle-resolved photoemission spectroscopy (ARPES) combined with density functional theory calculations clarify the surface band structure with saddle points near the Fermi level, which allows us to attribute the observed STM spectral peaks to the van Hove singularity. Moreover, spin-resolved ARPES measurements reveal that the observed surface states are Rashba-type spin-polarized. The present work has significant implications in that Fermi surface instability and symmetry breaking may emerge at low temperatures, where the spin degree of freedom and electron correlation also play important roles.

Abstract Background Opioid-induced rigidity is typically observed during rapid administration of fentanyl. Herein, we present a case in which rigidity occurred after reversal of rocuronium during emergence from anesthesia. Case presentation A 73-year-old man underwent video-assisted partial lung resection. General anesthesia was induced with propofol, remimazolam, remifentanil, and rocuronium. Fentanyl was administered early during anesthesia. The surgery was completed without complications, and sugammadex sodium was administered for rocuronium reversal. The patient became agitated, but spontaneous breathing was maintained; therefore, the intratracheal tube was removed after the administration of flumazenil. The patient developed stiffness in the neck and jaw muscles along with remarkable skeletal muscle contractions. Dramatic improvement was observed immediately after administration of naloxone. Conclusions Even as the simulated effect site concentration of fentanyl decreases during anesthesia emergence, opioid-induced rigidity may still occur. Rapid reversal of remimazolam by flumazenil might have contributed to the rigidity in this case.