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Delirium is a frequent complication in critically ill and septic patients and has been linked to endothelial dysfunction, microvascular injury and blood-brain barrier disruption. Circulating endothelial cells may reflect endothelial phenotypic alterations beyond soluble markers. We investigated the association between endothelial subsets and postoperative sepsis-related delirium in ICU patients. To investigate the role of circulating endothelial subsets in the development of delirium in post-surgical sepsis patients and their relationship with hypoperfusion and clinical outcomes, to identify potential prognostic biomarkers and mechanistic insights. In this prospective cohort study, 214 postoperative ICU patients were enrolled at the time of surgery or sepsis diagnosis and classified as non-septic ICU (n=77), sepsis (n=61) or septic shock (n=76) according to Sepsis-3 criteria. Blood samples were obtained within 24 hours of critical illness onset. Circulating endothelial subsets were characterized using high-dimensional flow cytometry with unsupervised clustering. Delirium was assessed daily using the CAM-ICU. Cox regression, ROC analysis and causal mediation models were applied to evaluate associations with 28-day delirium and organ-dysfunction related clinical events occurring after sampling. Among 13 endothelial subpopulations identified, CD32b⁺ subset were independently associated with 28-day delirium (HR 2.41, 95% CI 1.32-4.40; p=0.004). CD32b⁺ subset demonstrated discriminative performance for delirium (AUC 0.79, 95% CI 0.60-0.98), which improved after adjustment for age and sex (AUC 0.89, 95% CI 0.82-0.98). Models based solely on organ-dysfunction related clinical events showed lower performance (AUC 0.69, 95% CI 0.52-0.86). Mediation analysis indicated that approximately 20% of the total effect was mediated through organ-dysfunction related events, suggesting partial mediation, while the remaining 80% may involve alternative endothelial and microvascular mechanisms not captured by conventional measures. Elevated CD32b⁺ subset are associated with postoperative delirium and organ-dysfunction related clinical events in critically ill patients, supporting an association between endothelial phenotypic alterations and vulnerability to brain dysfunction.

Leukemia is a malignant tumor with a high recurrence rate and poor prognosis for patients. Thus, there is an urgent need to explore new therapeutic targets that play critical roles in leukemogenesis but have little effect on normal hematopoietic cells. Here, we show that RNA binding protein with multiple splicing (RBPMS), which is highly expressed in acute myeloid leukemia (AML) and associated with poor prognosis of AML, plays critical roles in leukemogenesis. Our study shows that inhibition of RBPMS inhibits self-renewal of leukemia-initiating cells (LICs) and leukemia development but has little effect on normal hematopoiesis. Mechanistically, RBPMS recruits the N6-methyladenosine (m6A) reader insulin-like growth factor 2 mRNA binding protein 3 (IGF2BP3), which promotes the stability of the forkhead box O1 (FOXO1) mRNA in an m6A-dependent manner. Moreover, RBPMS contributes to the progression of leukemia by directly binding to FOXO1 and promoting FOXO1-regulated glycolysis. Overexpression of FOXO1 has been shown to reverse RBPMS inhibition-induced phenotypes in both leukemic cells and mouse models. We also designed a specific inhibitor of RBPMS that has therapeutic effects in AML patient-derived xenograft (PDX) models. We therefore highlight RBPMS as a promising drug target for leukemia therapy.

The South Pole-Aitken (SPA) basin-forming impact was a critical event in the Moon's history. Despite being the oldest and largest acknowledged basin, critical details including the impactor's size, nature, direction, and fate of the ejecta remain uncertain. Here, we simulate SPA's formation and resultant crustal structure. We find that SPA's observed shape of an ellipse tapered toward the south is best reproduced by a 260-km-diameter differentiated impactor striking with a north-to-south trajectory. In this scenario, the impact disperses lunar mantle materials in the cross-range and the downrange directions away from the lunar farside. Much of the mantle ejecta collapses into the basin interior, consistent with the distribution inferred from gravity. These results suggest that the Artemis landing sites near the lunar south pole should contain abundant SPA ejecta including mantle materials. Samples returned from these regions should therefore reveal the age of SPA and the composition of the lunar mantle.

Purpose: This study provided a comprehensive bibliometric analysis of research related to the International Classification of Functioning, Disability, and Health (ICF) covering the years 2015 to 2025, using data sourced from the Web of Science Core Collection. Methods: By employing analytical tools such as VOSviewer, CiteSpace, and Bibliometrix, we examined a total of 3,193 publications to identify trends, collaborations, and the evolution of themes within this field. Results: Our key findings indicate a significant 32.2% increase in annual publications from 2020 to 2024. Our bibliometric analysis highlights the significance of influential journals and authors, underscoring the critical of interdisciplinary collaboration and methodological rigor in advancing research. The thematic evolution observed in the literature shows a transition from studies focused on specific conditions to more comprehensive frameworks that prioritize participation, quality of life, and the integration of technology, with a pronounced and growing emphasis on Assistive Technology,as a key environmental facilitator within the ICF model. Notably, high-impact publications by Cesari et al in 2018 and Cieza et al in 2019 have influenced scholarly discourse connecting clinical practice with policy implications, while thematic mapping has identified "disability" as a pivotal theme driving research in this area. Looking ahead, future research should focus on underrepresented populations, conduct longitudinal studies, and explore the integration of digital health solutions to enhance the real-world impact of findings in this critical field.Conclusion: This study underscores the ICF's transformative potential as a comprehensive biopsychosocial framework. Standardizing disability assessment through the ICF promotes equity and interdisciplinary collaboration, while ongoing research increasingly provides evidence to inform practice, with potential to contribute to global health equity and functional outcomes for people with disabilities. The ICF framework promotes consistent disability evaluation through validated tools like WHODAS 2.0, enhancing comparability across clinical and policy domains. Rehabilitation should prioritise adopting ICF-based protocols to facilitate interdisciplinary data integration and evidence-based practice.Emerging trends emphasise AI, wearable sensors and telerehabilitation, enabling real-time monitoring and personalised interventions. Embedding ICF metrics into digital platforms can optimise functional outcomes and support preventive care models.Thematic evolution shows a shift from condition-specific focus to participation and quality of life. Rehabilitation must embrace holistic strategies, such as exercise interventions and risk assessments, to address individual needs and promote community integration.Despite ICF’s widespread adoption, disparities persist in low-resource settings and among marginalised groups. Rehabilitation policies should leverage ICF’s biopsychosocial model to develop culturally adapted tools and ensure equitable service delivery.Gaps in longitudinal data and database bias underscore the need for international collaborations and digital health integration. Prioritising scalability – such as embedding ICF into electronic health records – will maximise real-world impact and advance global health equity.

Donor notification and counseling after reactive screening for transfusion-transmitted infections (TTIs) are critical to transfusion safety and public health, yet practices in low- and middle-income countries (LMIC) remain inconsistent and poorly evaluated. A Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for scoping reviews-guided scoping review was conducted to map evidence on TTI-reactive donor notification and follow-up in LMIC. We searched PubMed, EMBASE, Scopus, and Web of Science for English-language studies published between January 2005 and June 2025. Eligible studies reported notification strategies, donor psychological factors, linkage-to-care outcomes, digital health interventions, or system-level integration. Data were extracted and narratively synthesized across 5 thematic domains, as mentioned in the "Results" section. Notification success and donor response varied widely. Telephone-based notification consistently achieved higher return rates than letters or text messaging, while replacement donors demonstrated lower follow-up than did voluntary donors. Stigma, fear, and inaccurate contact information were major barriers to counseling. Evidence on linkage to confirmatory testing and treatment was limited; digital health approaches were largely absent. No studies evaluated cost-effectiveness or workforce impact. Overall, TTI-reactive donor notification in LMIC remains fragmented, with critical gaps in digital innovation, psychosocial support, and linkage-to-care evaluation. Strengthening system-integrated, technology-enabled, culturally sensitive notification models is essential to improve donor and public health outcomes.

Congenital heart anomalies (CHA) significantly contribute to childhood morbidity and mortality worldwide. Understanding sex-specific differences and their association with societal development levels is crucial for formulating effective health strategies. We extracted sex-stratified incidence, mortality, and disability-adjusted life years (DALYs) for CHA among children under five from the Global Burden of Disease Study 2021 for 204 countries and territories (1990-2021). Sex differences were quantified using male-to-female rate ratios with 95% uncertainty intervals. Temporal trends were evaluated using the estimated annual percentage change (EAPC) derived from log-linear regressions. We assessed the association between disease burden and development status using the Sociodemographic Index (SDI). To address confounding variables and geographic clustering, we fitted linear mixed-effects models with sex, SDI, and calendar year as fixed effects and GBD region as a random intercept, reporting adjusted coefficients with 95% confidence intervals. From 1990 to 2021, the global CHA burden declined. While descriptive analysis showed higher raw point estimates for males, a multivariable mixed-effects analysis-adjusted for SDI (as a proxy for macro-level development and health-system context) and temporal trends-confirmed that male sex was significantly associated with a higher CHA burden (DALYs Adjusted Coefficient: 876.4, P&#x2009;<&#x2009;0.001; Mortality Adjusted Coefficient: 9.7, P&#x2009;<&#x2009;0.001). This suggests a robust male disadvantage independent of socioeconomic status. The highest CHA burdens were observed in Sub-Saharan Africa, Southeast Asia, and South Asia, while improvements in SDI were significantly associated with overall reductions in burden. Despite overall reductions in CHA burden, profound regional disparities and observable sex differences persist, especially in resource-limited areas. Policy interventions focusing on gender-sensitive resource allocation, enhanced neonatal screening, and improved surgical access are critical to mitigating these disparities and advancing global pediatric health equity.

Despite significant advances in tourism forecasting methods, current approaches suffer from critical limitations including static ensemble weighting mechanisms that fail to adapt to changing environmental conditions, insufficient integration of multi-source data streams, and limited robustness against sudden demand shifts caused by extreme weather or unexpected events. This study presents an innovative ensemble artificial intelligence framework for monitoring and forecasting tourist flows in the Aosta Valley region, Italy, utilizing a large-scale dataset of over 41 million vehicle passages collected from 14 strategically positioned sensor portals. Our novel approach integrates multiple machine learning algorithms through an adaptive ensemble mechanism that dynamically weights individual predictors based on temporal patterns, seasonal variations, and real-time performance metrics. We introduce the Adaptive Temporal Ensemble (ATE) algorithm, combining eXtreme Gradient Boosting (XGBoost), Random Forest, Support Vector Regression, and Long Short-Term Memory networks with a novel meta-learning layer. The key novelty lies in the dynamic weight adjustment mechanism that responds to contextual features including recent model performance, seasonal indicators, meteorological conditions, and traffic flow characteristics, enabling the system to automatically select the most appropriate predictor for each forecasting scenario. The system processes traffic data from highway and valley road sensors, integrated with comprehensive meteorological datasets and calendar information, providing real-time monitoring and accurate forecasting capabilities. We present a formal mathematical framework, including the Ensemble Convergence Theorem, which guarantees optimal performance bounds under specific conditions. Experimental validation demonstrates superior forecasting accuracy with Mean Absolute Error (MAE) improvements of 23.7% and Mean Squared Error (MSE) reductions of 31.2% compared to individual models. The ensemble framework achieves R2 scores exceeding 0.94 for short-term predictions and maintains robustness across different seasonal patterns and extreme weather conditions. These improvements translate directly into practical benefits for destination management organizations, including enhanced resource allocation efficiency, improved traffic congestion management, and more accurate capacity planning for tourism infrastructure. This research contributes significantly to intelligent tourism management systems and provides a scalable framework applicable to other regions with similar traffic monitoring infrastructure.

The Sainte-Anne Military Teaching Hospital in Toulon serves a dual mission as a civilian Stroke Center and a reference center for military diving medicine. This article presents an initial experience and proof-of-concept regarding the implementation of an on-site percutaneous Patent Foramen Ovale (PFO) closure program, critical for secondary stroke prevention and the management of decompression sickness (DCS). Implementing this activity required meeting national regulatory volume thresholds and developing specific protocols. Key challenges included establishing "remote anesthesia" in the catheterization laboratory and coordinating a multidisciplinary pathway. To ensure patient safety and rapid skill acquisition, structural cardiology protocols adhered strictly to international proctoring guidelines. A comprehensive care pathway was successfully established. In its first year, the program performed 17 PFO closures (13 cryptogenic strokes, 3 DCS, 1 platypnea-orthodeoxia), achieving a 100% immediate anatomical success rate with zero complications. Early follow-up data (n&#x2009;=&#x2009;5 at 6 months) demonstrate a 100% complete sealing rate. For divers, a specific "Return to Duty" algorithm was formalized, strictly conditioning operational clearance upon a 6-month "Safety Visa" (contrast echocardiography and stress test), allowing for a zero-medication return to work. The internalization of PFO closure at a Role 4 military hospital validates a comprehensive "Dual-Use" care model. It ensures operational readiness for elite units by securing the pathway from diagnosis to anatomical repair, while utilizing high-volume civilian stroke care to maintain expert-level technical proficiency.

To investigate the emergency management strategies and clinical outcomes of iatrogenic rupture, a rare and life-threatening complication, during the interventional treatment of intracranial aneurysms. We present the case of a 70-year-old female patient who underwent stent-assisted coiling for an unruptured right middle cerebral artery aneurysm. An iatrogenic intraprocedural aneurysm rupture occurred and was successfully managed with salvage therapy. Upon the intraoperative observation of contrast agent extravasation, immediate comprehensive rescue measures were instituted. The core intervention was prompt and ongoing coil embolization to achieve dense packing, supplemented by urgent heparin reversal and controlled hypotension. Postoperatively, the patient developed transient minor neurological dysfunction, which significantly improved following active rehabilitation. One-month follow-up assessment indicated a favorable patient outcome, with a modified Rankin Scale score of 1. In the event of an iatrogenic rupture during stent-assisted coiling, the operator's composure, accurate judgment, and the implementation of rapid, standardized, comprehensive salvage measures are critical for averting catastrophic consequences and ensuring a favorable patient prognosis. Among these measures, prompt and sustained coil embolization is the most crucial technique for immediate sealing of the rupture site and hemorrhage control.

The purpose of this article is to provide a comprehensive review of recent literature addressing diagnoses and conditions that intersect pediatric and adolescent gynecology (PAG) and complex benign gynecology (CBG) to inform which patients should make the transition from PAG to CBG care, as well as when and how that transition should occur. Recent literature lacks data on formalized transition processes for pediatric gynecology patients who require ongoing management of benign conditions, including, but not limited to, disorders of sexual development, endometriosis, abnormal uterine bleeding, and chronic pelvic pain. CBG specialists are well positioned to assume care for many of these individuals. Evidence suggests that delays in diagnosing conditions like endometriosis and failure to refer to appropriate subspecialists are linked to disease progression and worse long-term outcomes, underscoring the need for timely referral. Transition from PAG to CBG care is a critical juncture for patients with chronic and surgically complex conditions. Structured referrals, clear communication, and multidisciplinary collaboration are key to maintaining continuity of care, preserving fertility, and optimizing outcomes. Given the lack of standardized transition frameworks in gynecology, further research is needed to develop evidence-based protocols and reduce care fragmentation.

Epithelial cells (ECs) of the female genital tract (FGT) serve as an essential barrier and the first line of defense against sexually transmitted pathogens. Beyond providing a physical barrier, these cells actively contribute to immune responses through pathogen recognition, cytokine release, and modulation of adaptive immune responses. Sexually transmitted viruses such as HIV-1 and HSV-2 must overcome the physical and functional barriers of the mucosal surface to establish infection. This review explores the intricate relationship between genital ECs and HIV-1 and HSV-2, emphasizing on how these interactions influence infection outcomes. We examine the innate immune responses of ECs in the upper and lower FGT, highlighting both their similarities and differences. Additionally, we delve into the mechanisms of pathogen recognition and virus-specific innate immune responses of genital ECs to HIV-1 and HSV-2. Deepening our understanding of epithelial-viral interactions is critical for identifying key determinants of susceptibility and resistance to sexually transmitted infections (STIs). Elucidating these mechanisms is essential for developing targeted strategies to enhance mucosal immunity, through novel antiviral therapies, vaccine strategies, or interventions to fortify epithelial defenses. Such advancements have the potential to improve protection against these infections and reduce their global burden.

The Earth's crust contains reactive, igneous reservoirs that can be utilized to turn atmospheric CO2 into new carbonate minerals. Carbon mineralization technology relies on the reactions between crustal reactants (rock, water, and biota) and injected CO2 to release divalent cations that can participate in the precipitation of new carbonate minerals. Field CO2 injection tests in mafic-ultramafic lithologies around the world have opened a window into the reactive potential of the subsurface. Knowledge and technology gained from the decades of carbon mineralization research will push forward efforts in unlocking innovative ways to approach subsurface critical mineral resources, hydrogen generation, geothermal energy, water resource management, waste storage, gas storage, and hydrocarbon extraction. Our review describes a holistic view of subsurface mafic-ultramafic reservoirs, carbon mineralization reactions, field tests, and future opportunities for using the subsurface Earth as a Reactor.

The rising incidence of thyroid cancer presents a growing diagnostic and therapeutic challenge. Various risk stratification systems have sought to integrate clinical, ultrasonographic, and, in some cases, cytological features to aid malignancy prognostication. This systematic review aims to critically evaluate risk stratification tools (RSTs) for patients with thyroid nodules, which incorporate multimodal inputs to assess their diagnostic performance and clinical utility in supporting surgical decision-making. PubMed, Embase, and Cochrane databases were searched from inception to 04/13/2026, identifying studies evaluating multivariable risk prediction models for adult patients undergoing assessment of thyroid nodules. Studies were excluded if the proposed tool failed to incorporate clinical features, ultrasound findings, and cytology results or was not validated with histology. Data extraction encompassed methodology of model development, performance metrics, and approaches to validation. Risk of bias was assessed using the PROBAST+AI tool. Seven studies describing five distinct RSTs met inclusion criteria Thyroid Nodule App (TNAPP), the McGill Thyroid Nodule Score (MTNS), CUT Score, Memorial Sloan Kettering Cancer Centre (MSKCC) nomogram, and Thyroid Prediction Score (TiPS). TiPS demonstrated the highest sensitivity (96.2%) and specificity (97.5%) with area under the curve (AUC) >0.9. The CUT score also showed strong performance (AUC >0.9), particularly in low-to-intermediate risk nodules. TNAPP underperformed (accuracy 50.5%; specificity 27.5%) despite broad clinical inputs. The MTNS and MSKCC, although promising for indeterminate cytology, lacked robust validation. Most models were derived from single-center, retrospective cohorts, limiting generalizability. RSTs integrating multimodal data may improve thyroid nodule risk stratification, particularly in cases of indeterminate cytology. However, methodological limitations and lack of external validation currently restrict clinical utility. Prospective evaluation in diverse populations is required to identify the most effective and generalizable tools. Until then, RSTs should be used as adjuncts to, not replacements for, clinical judgment and shared decision-making in thyroid nodule assessment.

Polishing, the process of correcting base-level errors in genome assemblies, is a critical step for ensuring accuracy in downstream analyses, such as variant calling, gene annotation, and clinical genomics applications. While recent advances in long-read sequencing technologies have helped improve assembly contiguity and genome completeness, maintaining high base-level accuracy in those genomes remains challenging due to the still appreciable errors associated with certain long-read sequencing technologies. Existing polishing approaches face notable trade-offs: alignment-based methods achieve high accuracy but incur long run times, alignment-free k-mer-based tools are scalable but struggle in regions with dense errors, and machine learning-based polishers often only perform well on specific platforms and require read-to-assembly alignments. We present AIEdit, a machine learning-based polisher designed to operate alignment-free, generalizing across sequencing platforms while remaining computationally efficient. We developed AIEdit by combining spaced seed matching with a neural network trained to detect and correct dense error patterns in an alignment-free manner. We benchmarked the method on simulated and experimental DNA sequencing data. On simulated human long-read assemblies with high error rates, AIEdit reduced error rates by 58% compared to ntEdit's 21%, completing in 2.7 hours using 230 GB of memory - faster than POLCA and Medaka (multi-day run times) and using 3&#x2009;&#xd7;&#x2009;less memory than JASPER (689 GB). On experimental Oxford Nanopore Technologies (ONT) data from the NA24385 human genome, AIEdit increased the Merqury quality score (QV) from 28.7 to 32.9 in 9.5 hours, achieving comparable accuracy to Medaka (QV 32.7) in a fraction of the time (1.5&#x2009;+&#x2009;days) and outperforming k-mer-based tools ntEdit (QV 31.0) and JASPER (QV 31.7). Overall, AIEdit enables scalable and accurate genome polishing across diverse datasets.

The Ki-67 proliferation index is a critical prognostic marker in pancreatic ductal adenocarcinoma (PDAC); however, its assessment relies on invasive tissue sampling. Ki-67 expression reflects active tumor cell proliferation and is associated with aggressive tumor behavior. A preoperative, noninvasive method to predict Ki-67 status would therefore be valuable for clinical decision-making. Dual-energy CT (DECT) can provide quantitative parameters related to tumor vascularity and composition, potentially reflecting proliferative activity. Additionally, clinical biomarkers such as CA125 may offer complementary information regarding tumor biology. Therefore, the development of a reliable noninvasive approach to preoperatively determine Ki-67 status is of considerable clinical importance. To develop and validate a noninvasive approach for predicting Ki-67 expression in pancreatic ductal adenocarcinoma by integrating quantitative dual-energy CT parameters and clinical biomarkers. This retrospective study included 148 PDAC patients randomly divided into training (n&#xa0;=&#xa0;89) and validation (n&#xa0;=&#xa0;59) sets (6:4 ratio). All patients underwent preoperative DECT scans, and quantitative parameters including normalized iodine concentration (NIC), effective atomic number (Zeff), spectral attenuation slope (&#x3bb;), etc. were obtained from three contrast phases. Serum tumor markers (CA19-9, CA125, CA50, CEA) and clinical features were analyzed. Multivariate logistic regression was used to identify predictors of Ki-67 expression. A nomogram and 3-D probability surface were developed to intuitively demonstrate the model's predictive structure and decision-making process. Model performance was validated using ROC analysis, calibration curves, and decision curve analysis. Innovatively, kernel-density ridgeline plots and prediction-error bar plots were employed to comprehensively evaluate risk distribution and prediction accuracy, demonstrating the model's stability. The joint model demonstrated excellent predictive performance, achieving AUCs of 0.803 in the training set and 0.810 in the validation set, outperforming both the clinical-only model (training AUC&#xa0;=&#xa0;0.682, validation AUC&#xa0;=&#xa0;0.751) and the DECT-only model (training AUC&#xa0;=&#xa0;0.712, validation AUC&#xa0;=&#xa0;0.702). Multivariate analysis identified arterial-phase normalized iodine concentration (A-NIC) (p&#xa0;=&#xa0;0.046) and CA125 (p&#xa0;=&#xa0;0.005) as independent predictors of Ki-67 expression. These two parameters formed the basis of the final predictive model, demonstrating consistent diagnostic value across both cohorts. Integration of DECT parameters and clinical biomarkers allows accurate noninvasive prediction of Ki-67 expression in PDAC, offering a potential tool for preoperative assessment of tumor proliferation.

The westerlies moisture transport underpins water security for over two billion people dependent on the Asian water towers (AWTs). However, the mechanisms by which large-scale westerlies-advected moisture is integrated into the AWTs' atmospheric water budget remain poorly understood due to observational gaps. Here, we combine three-dimensional observations of atmospheric water vapor stable isotopes with isotope-enabled modeling. We identify the conveyor mechanism that regulates the vertical moisture transport under calm conditions during the winter-spring period when the westerlies are dominant. Sharp vertical isotopic gradients show that large-scale westerlies-advected moisture is predominantly confined aloft, while local residual moisture persists near the surface. Our results show the interplay of the westerlies' subsidence at night with thermodynamically distinct local residual air, yielding thermal inversions and condensation that suppresses vertical mixing and decouples moisture between the free troposphere and the atmospheric boundary layer. This process constitutes a primary pathway for integrating westerlies-advected moisture into the local moisture budget without precipitation, sustaining near-surface moisture accumulation. Our results provide critical benchmarks for improving atmospheric models, refining climate projections of the intensifying water cycle over the AWTs, and advancing interpretations of isotopic records in regional climatic archives.

Branched-chain amino acid (BCAA) accumulation has been linked to induction of salicylic acid (SA)-related defense responses in wheat (Triticum aestivum). Here, we explored whether the underlying mechanism might involve a wheat ortholog of SAP AND MIZ1 DOMAIN-CONTAINING LIGASE1 (SIZ1), a critical SA regulator in other systems. We found that TaSIZ1 was significantly repressed in mutant plants disrupted in the BCAA aminotransferase gene TaBCAT1; these plants accumulate enhanced levels of BCAAs and SA. Overexpressing TaSIZ1 suppressed SA-hyperaccumulation in TaBCAT1 mutants and treating wild-type plants with the BCAA Leu repressed TaSIZ1 expression. Thus, TaSIZ1 is responsive to BCAA levels and influences SA accumulation, consistent with a role linking BCAA and SA in defense. Nuclear proteomic analysis of the TaBCAT1 mutant identified transcriptional regulators that could be modifying BCAA-responsive TaSIZ1 expression. This included an ortholog of the Arabidopsis thaliana trihelix transcription repressor 6b-INTERACTING PROTEIN-LIKE1 (ASIL1) with a potential binding site in the TaSIZ1 promoter. Further work showed that TaASIL1 bound to the TaSIZ1 promoter. Also, disrupting TaASIL1 function inhibited Leu-dependent TaSIZ1 repression. Based on these data, we propose that elevated BCAA levels such as those arising during pathogen attack activate TaASIL1, which represses TaSIZ1, thereby promoting SA accumulation and SA-mediated defense in wheat.

Psychosocial interventions are regarded as preferable in dementia care, as they have been tested as effective in preserving people living with dementia's function, reducing stress, and enhancing well-being. Typically delivered in structural activities, these interventions feature psychosocial, environmental, and behavioral interactions with people living with dementia. The degree and patterns of people living with dementia's interactional behaviors, therefore, indicate their engagement and participation in the intervention and may have an impact on the effect of psychosocial therapies. The systematic review aims to 1) synthesize the empirical evidence of measurement tools used to measure interactions in psychosocial interventions across various therapeutic settings and 2) investigate whether existing studies have investigated the relationship between measures of interaction and treatment outcomes, if yes, further investigation will be carried out to describe the relationship between measures and outcomes. Empirical studies and psychometric studies of scales are eligible for inclusion. The study protocol has been registered at the Campbell Systematic Reviews (cl2.20250120). Search will be conducted on PubMed, PsycINFO (ProQuest), MedLine (EbscoHost), CINAHL (EbscoHost), and Cochrane Library from inception until December 31, 2025, for studies measuring people living with dementia's interactions in psychosocial interventions. The inclusion of studies will involve two independent reviewers through a two-phase procedure. During the first phase, reviewers will assess titles and abstracts, which will be followed by reading the full texts employing the predefined eligibility criteria. Data extracted will include study nature/characteristics, aspects of interactions measured, measurement methods, and the relation to outcomes. The risk of bias will be assessed using the Quality Assessment Tool for Quantitative Studies for quantitative studies and the Critical Appraisal Skills Programme (CASP) checklist for qualitative studies. Results will be synthesized into a descriptive analysis, given the results of the included literature. This systematic review will enable a comprehensive analysis of existing frameworks used to measure interactions in psychosocial interventions across diverse settings. It may contribute to the effective measurement of interactions and provide insights into the quantitative analysis of the relation between interaction and outcome measures.