Mirai Hospital

This paper presents a follow-up review of restrictive practice audits conducted within a supported living organisation in South Wales in 2020, 2022, and 2024. The audits examined a broad range of restrictive practices across everyday domains of life, including freedom of movement, personal care, privacy, health, and social participation. Building on the initial audit, this review evaluates the organisation’s progress in documentation, legal compliance, and organisational culture. While the overall number of restrictions did not significantly decrease, substantial improvements were made in consent and best interest recording, data sharing, and staff involvement through Restrictive Practice Champions. Ongoing challenges in specific domains highlight the complexity of achieving least restrictive practice. The paper reflects on organisational learning and future directions for strengthening rights-based care. Easy to read summary ■ Restrictions are actions or rules that stop a person from doing things that most other people are free to do. ■ The service reviewed how often restrictions were used in 2020, 2022 and 2024, and whether they were lawful, needed, and properly written down. ■ While the overall number of restrictions has stayed similar, the organisation has greatly improved how it records consent, best-interest decisions, and how information is shared. ■ Some restrictions are still hard to reduce, particularly those linked to safety and freedom of movement, showing that more work is needed in these areas. ■ The purpose of these audits is to make sure restrictions are only used when truly needed, and to support people with learning disabilities to have more independence and control over their lives.

Serenity is crucial for well-being, and should be measured from two perspectives: state and trait. However, while Trait Serenity Scales have been developed, there are no scales for state serenity. Therefore, we developed a State–Trait Serenity Scale (STSS). We first collected words related to serenity from Japanese participants. We then considered the factor structure of serenity in terms of state and traits using an exploratory factor analysis. We also confirmed the relationship between well-being and state and trait serenity. We examined the possibility of measuring psychological states after watching videos to confirm the scale’s usefulness. The State Serenity Scale had 14 items with three factors: “calmness,” “excitement,” and “richness,” and the Trait Serenity Scale had 11 items with two factors: “calmness” and “excitement.” The factors of both scales had good internal consistency. Confirmatory factor analysis showed that both the scales and factors had factor convergent and discriminant validity. The STSS showed positive correlations with well-being. Furthermore, evaluating and comparing feelings of serenity after watching video clips by genre was possible. These results suggest that trait and state positive emotions are related to well-being, and that the STSS can evaluate serenity and well-being from both perspectives.

We report the complete circular genome sequence (2,316,546 bp; 37.0% G + C) of Solobacterium moorei 10714-02, a gram-positive obligate anaerobe isolated from stool samples of a human colorectal cancer patient, differing from the typically linear chromosome of this species.

Quantifying soil organic carbon (SOC) has a vital role to play in advancing soil health, optimizing agricultural productivity, and helping mitigate climate change. Expanding the scope of traditional soil analysis necessary to realize this promise presents a significant challenge of scale. Spectroscopic methods, such as Raman scattering, offer higher throughput but encounter complications owing to sample heterogeneity, matrix interactions, and interfering fluorescence. In this study, we integrate a fluorescence-tolerant Raman measurement methodology, Shifted Excitation Raman Difference Spectroscopy (SERDS), with machine learning and signal processing techniques geared specifically to address these challenges. Using a data set of more than 900 soil samples from diverse geographic regions in North America, our approach implements a purpose-built Common Mode Rejection (CMR) algorithm. This novel background correction method autonomously isolates essential spectral features without the need for hyperparameter tuning, offering a substantial improvement over traditional methods such as Asymmetric Least Squares (ALS). Our CMR-enhanced SERDS framework not only achieves superior predictive accuracy, in this case, an R2 = 0.87 ± 0.04 and MAPE = 21.6% ± 2%, but also improves the interpretability of features, facilitating a deeper understanding of the spectral data. An analysis of these results proves that retaining unresolved but Raman-active baseline features substantially improves soil organic carbon (SOC) prediction accuracy, thus bolstering CMR as an effectiveinformatic approach for soil management and analysis. The analytical success demonstrated here points to the scalable utility of Raman spectroscopy as a means of addressing outstanding challenges in soil analysis and as an aid in managing the approximately 2,500 gigatons of carbon stored globally in soils. Improved soil organic carbon quantification will increase the scope of cropland monitoring, supporting carbon sequestration strategies that contribute to the mitigation of climate change and help increase agricultural productivity.

Our skin is constantly exposed to the external environment, and the epidermis, in particular, responds to various external stimuli by producing biomolecules, including proteins, lipids, and metabolites. Therefore, a real-time metabolic monitoring system for living keratinocytes is essential. Metabolomics, one of the key fields in omics research, has emerged as a powerful tool for the comprehensive characterization and quantification of biological molecule pools. However, most conventional metabolomics studies rely on cell quenching or lysis methods, which may introduce artifactual stimuli and potentially alter the metabolite profiles of living cells, as fast signaling events such as phosphorylation can occur within milliseconds to seconds. Consequently, conducting omics research on living organisms in real time is of great value, as it can provide unique insights that are not achievable through conventional methods. In this study, we established a novel, noninvasive, real-time metabolic monitoring system termed "live-cell metabolic NMR with illumination". This innovative technique enables the evaluation of the metabolic responses of living human keratinocytes to various external stimuli, allowing for the investigation of real-time metabolic dynamics in a physiologically relevant environment.

Schwann cells (SCs) are central players in peripheral nerve repair, facilitating axonal regrowth, remyelination, and modulation of the regenerative microenvironment. A pivotal driver of these functions is intracellular Ca2+ signaling, regulated by both endogenous Ca2+-permeable ion channels and engineered optogenetic actuators. Recent developments in optogenetics, particularly the application of Ca2+-permeable channelrhodopsins such as CapChR2, have enabled precise, light-controlled activation of SCs, allowing for targeted investigation of Ca2+-dependent pathways in non-neuronal cells. This review synthesizes emerging evidence demonstrating that optogenetically or endogenously induced Ca2+ influx in SCs leads to the release of a diverse set of neurotrophic and regulatory factors. These Ca2+-triggered secretomes modulate SC phenotypes and surrounding neurons, orchestrating axon regeneration and myelin repair via autocrine and paracrine mechanisms. We further discuss the roles of key endogenous Ca2+ channels—including transient receptor potential (TRP) channels and store-operated Ca2+ entry (SOCE; STIM/Orai)—in orchestrating SC activation under physiological and injury-induced conditions. By integrating insights from optogenetic manipulation and intrinsic signaling biology, this review proposes a conceptual framework in which Ca2+-triggered SC secretomes act as structural and functional scaffolds for nerve repair. We highlight how SC-derived factors shape the regenerative niche, influence adjacent neurons and glia, and modulate repair processes in peripheral and autonomic nerves.

This 2‐part, randomized, placebo‐controlled, double‐blind, Phase 1 study analyzed the pharmacokinetics, safety, and biomarker profile of fezolinetant in healthy Japanese individuals. Part 1: male participants received single doses of placebo or fezolinetant 15 or 60 mg. Part 2: male and premenopausal and postmenopausal female participants received a single dose of placebo or fezolinetant 180 mg, followed by a 2‐day washout, and multiple dosing once daily for 10 days. Fezolinetant was rapidly absorbed with peak concentrations 1‐2 hours after single‐dose administration; plasma levels subsequently declined (half‐life range, 3.29‐7.24 hours). Only slight accumulation (area under the concentration–time curve accumulation ratio, 1.46‐1.57) was observed after once‐daily multiple‐dose administration. No serious/severe treatment‐emergent adverse events were observed; the only fezolinetant‐related treatment‐emergent adverse event was mild uterine bleeding in 1 premenopausal woman and 1 postmenopausal woman. Concentration‐QT analysis showed that fezolinetant does not have a clinically significant effect on QT interval. Fezolinetant produced dose‐dependent reductions in luteinizing hormone and slight reductions in follicle‐stimulating hormone; levels subsequently returned to baseline 48 hours or fewer after dosing. This analysis shows that fezolinetant doses up to 180 mg had an acceptable safety, pharmacokinetic, and biomarker profile. This study clarifies the safety, pharmacokinetic, and biomarker profiles of fezolinetant in Japanese individuals.

BackgroundOs acromiale is an accessory bone resulting from the nonunion of the acromial ossification center, with a reported prevalence of approximately 2%. While os acromiale is often asymptomatic, when symptomatic, it has been reported to be strongly associated with rotator cuff injuries. This multicenter study aimed to determine the prevalence of and the factors associated with os acromiale in the Japanese population.MethodsWe analyzed 6,842 shoulder magnetic resonance imaging scans for shoulder disabilities obtained at 10 facilities between April 2018 and March 2023. The average age was 63.7 years, with 3,483 male and 3,359 female shoulders. This study assessed the prevalence of os acromiale, its location (pre-acromion, meso-acromion, and meta-acromion), size (length, width, and thickness), acromion shape (square tip, intermediate, and cobra), and the association between os acromiale and rotator cuff injuries. Statistical analysis was performed using Fisher's exact test with a significance level set at P < .05.ResultsA total of 76 cases of os acromiale (1.1%) were identified. There were 58 shoulders with pre-acromion, 18 with meso-acromion, and none with meta-acromion. The dimensions were as follows: pre-acromion (length 7.5 mm, width 10.5 mm, and thickness 5.3 mm), and meso-acromion (length 20.1 mm, width 20.8 mm, and thickness 8.5 mm). Acromial shapes included a square tip in 13 shoulders, intermediate tip in 38 shoulders, and cobra shape in 25 shoulders. The presence of os acromiale was significantly associated with rotator cuff injury (P < .001).ConclusionThe study supports previous findings that os acromiale is associated with rotator cuff injuries. In addition, the prevalence of os acromiale in the Japanese population was lower than that in non-Asian populations, and the size of os acromiale tended to be smaller than in European populations.

BackgroundThe gut bacteriome influences host metabolic and physiological functions. However, its relationship with reproductive performance remains unclear. In this study, we evaluated the relationship between the gut bacteriome and reproductive performance in beef cattle, such as Japanese black heifers. Artificial insemination (AI) was performed after 300 days of age, and the number of AI required for pregnancy (AI number) was evaluated. The relationship of the fecal bacteriome at 150 and 300 days of age and reproductive performance was visualized using statistical structural equation modelling between traits based on four types of machine-learning algorithms (linear discriminant analysis, association analysis, random forest, and XGBoost).ResultsThe heifers were classified into superior (1.04 ± 0.04 cycles, n = 26) and inferior groups (3.87 ± 0.27 cycles, n = 23) according to the median frequency of AI. The fecal bacteria of the two groups were examined and compared using differential analysis, which demonstrated that the genera Rikenellaceae RC9 gut group and Christensenellaceae R-7 group were increased in the superior group. Subsequently, correlation analysis evaluated the interrelationships between bacteriomes, which demonstrated that the patterns exhibited distinct characteristics. Therefore, four machine-learning algorithms were employed to identify the distinctive factors between the two groups. The directed acyclic graphs carried out by DirectLiNGAM based on these extracted factors inferred that the family Erysipelotrichaceae and the genera Clostridium sensu stricto 1 and Family XIII AD3011group at 150 days of age were strongly associated with an increase in AI number. Furthermore, a pathway involved in creatinine degradation (PWY-4722) at 150 days of age was related to an increase in AI number. However, bacteriomes and/or pathways at 300 days of age were not necessarily related to AI number.ConclusionsIn this study, a causal inference methodology was applied to investigate AI-dependent gut bacterial communities in pregnant cattle. These findings suggest that AI numbers, which are crucial for beef cattle production management, could be inferred from the fecal bacterial patterns nearly six months before the AI, rather than immediately before. This study provides a novel perspective of the gut environment and its role in reproductive performance.Graphical

This research explored the integration of the real-time machine learning classification of motor imagery data with a brain-machine interface, leveraging prefabricated exoskeletons and an EEG headset integrated with virtual reality (VR). By combining these technologies, the study aimed to develop practical and scalable therapeutic applications for rehabilitation and daily motor training. The project showcased an optimized system designed to assess and train cognitive-motor functions in elderly individuals. Key innovations included a motor imagery EEG acquisition protocol for data classification and a machine learning framework leveraging deep learning with a wavelet packet transform for feature extraction. Comparative analyses were conducted with traditional models such as Support Vector Machines (SVMs), Convolutional Neural Networks (CNNs), and Long Short-Term Memory (LSTM) networks. The performance was further enhanced through a random hyperparameter search, optimizing feature extraction and learning parameters to achieve high classification accuracy (89.23%). A novel VR fishing game was developed to dynamically respond to EEG outputs, enabling the performance of interactive motor imagery tasks in coordination with upper limb exoskeleton arms. While clinical testing is ongoing, the system demonstrates potential for increasing ERD/ERS polarization rates in alpha and beta waves among elderly users after several weeks of training. This integrated approach offers a tangible step forward in creating effective, user-friendly solutions for motor function rehabilitation.