Search Results (2,014)

Anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis is a severe autoimmune neurological disorder characterized by pathogenic antibodies against the NMDAR. A systematic protein profiling approach is warranted to identify biomarkers capable of predicting disease status. An Olink proximity extension assay (PEA) profiled 91 inflammation-related proteins from anti-NMDAR encephalitis patients. Disease severity or prognosis were assessed by CASE score or mRS score at 6-month follow-up. Patients were stratified into distinct molecular clusters using unsupervised clustering. Logistic regression models incorporating selected biomarkers were developed to predict disease severity and prognosis, followed by absolute quantification using ELISA. Patients were classified into four consensus clusters. Clusters 1 and 2 corresponded to the mild group, while Cluster 3 represented the severe group, consistent with CASE score above 6. Cluster 4 showed heterogeneous clinical features. Elevated serum levels of IL-10, IL-6, and SIRT2, as well as increased CSF levels of CXCL10, CXCL11, and MMP10, were positively associated with severe disease. Conversely, several proteins including LTA and CCL11, CCL8, TGFB1, CXCL6 were associated with severe disease or unfavorable 6-month outcomes. A logistic regression model combining serum CXCL6 and CCL11 with CSF MMP10 achieved an area under the curve (AUC) of 0.95 for predicting disease severity. Serum CCL11 alone showed predictive value for 6-month prognosis, with an AUC of 0.79. These findings delineate distinct protein signatures associated with clinical heterogeneity of anti-NMDAR encephalitis. Prediction models incorporating multiple biomarkers may provide an approach for disease severity stratification and prognosis forecast. Full article

Introduction: Sarcopenia and obesity are increasingly recognized as overlapping conditions that contribute to adverse health outcomes, particularly in rapidly urbanizing populations. The coexistence of both conditions, termed sarcopenic obesity, represents a complex phenotype with potentially greater metabolic burden, yet its differentiation from non-obese sarcopenia remains insufficiently explored. Aim: This study aimed to compare metabolic and cardiometabolic profiles between sarcopenic obesity and non-obese sarcopenia in an urban population. Methods: A cross-sectional study was conducted using secondary data from the PRIMBON 2025 database in Jakarta, Indonesia. Participants were adults aged ≥18 years diagnosed with sarcopenia based on the 2025 Asian Working Group for Sarcopenia (AWGS) criteria. Sarcopenic obesity was defined according to the 2025 AOASO–IAGG consensus using BMI ≥ 25 kg/m² and visceral fat level > 10. A total of approximately 604 participants were included from five administrative regions of Jakarta. Data were analyzed using Mann–Whitney U test and Chi-square test, with results presented as median (min–max), mean rank, and odds risk (OR). A dot-and-whisker plot was used to visualize effect sizes. Results: Sarcopenic obesity was associated with older age and a higher proportion of males (p < 0.01). Significant differences were observed in systolic and diastolic blood pressure, fasting blood glucose, triglycerides, and HDL (all p < 0.01), indicating a more adverse cardiometabolic profile. No significant differences were found for hemoglobin, total cholesterol, LDL, uric acid, and handgrip strength. Conclusions: Sarcopenic obesity represents a more severe metabolic phenotype compared to non-obese sarcopenia. Full article

Background: Pain is a multidimensional experience shaped not only by nociceptive input but also by cognitive, emotional, and social processes. In musculoskeletal (MSK) rehabilitation, outcome variability among patients with similar clinical presentations suggests that determinants beyond tissue pathology may influence pain perception and recovery. Contextual factors (CFs)—communication, therapeutic relationship, patient expectations, and environmental cues—are increasingly recognized yet remain inconsistently integrated into routine practice. Objective: To map how CFs are represented in the physiotherapy literature indexed under that terminology, and to identify where empirical evidence in MSK rehabilitation is present and where it is absent. Methods: A narrative review with a systematic search strategy, reported following SANRA, was conducted in PubMed and Scopus, searched on 31 March 2026. Records were screened against predefined eligibility criteria, including publication from 2006 onwards and English language. Two reviewers independently screened records and resolved disagreements by consensus. Methodological quality was appraised using the Cochrane RoB2 tool for randomized controlled trials and an adapted Newcastle–Ottawa Scale for observational and cross-sectional studies. Conceptual publications were not formally appraised. Each publication was classified as direct clinical evidence (Tier A), indirect mechanistic or implementation-level evidence (Tier B), or conceptual contribution (Tier C). Results: Eight publications were included: no source provided direct clinical evidence in a musculoskeletal rehabilitation population (Tier A), five provided indirect mechanistic or implementation-level evidence (Tier B), and three were conceptual contributions (Tier C). The single randomised controlled trial retrieved was conducted in asymptomatic volunteers and was at high risk of bias for the between-group comparisons of all reported outcomes. Findings are organised as contextual domains, mediating mechanisms, and outcomes. No direct clinical evidence was retrieved; claims regarding expectations, therapeutic alliance, non-verbal communication, and the clinical environment rest on indirect or conceptual sources. Conclusions: CFs may contribute to pain and rehabilitation variability through cognitive, emotional, and relational pathways, complementing rather than replacing evidence-based care. The scarcity of direct clinical evidence within the literature indexed under this terminology is itself a finding. Construct-level searches and pragmatic trials are required to clarify the contribution of individual contextual domains. Full article

Background/Objectives: Postmenopausal aging is accompanied by progressive loss of skeletal muscle mass and increased abdominal adiposity, both of which may influence bone health through distinct mechanical and metabolic pathways. However, their independent associations with bone mineral density (BMD) at different skeletal sites remain incompletely characterized. This study investigated the independent associations of appendicular skeletal muscle mass index (ASMI) and waist circumference (WC) with site-specific BMD in postmenopausal women. Methods: This cross-sectional study included 345 postmenopausal women who attended a university hospital menopause clinic in Thailand. Body composition was assessed using multi-frequency bioelectrical impedance analysis, and ASMI was calculated according to the Asian Working Group for Sarcopenia (AWGS) 2019 consensus criteria. WC was measured using standardized anthropometric procedures. BMD at the lumbar spine (L1–L4), total hip, and femoral neck was determined by dual-energy X-ray absorptiometry. Multivariable linear regression analyses were performed to evaluate the independent associations of ASMI and WC with site-specific BMD after adjustment for age, years since menopause, hormone replacement therapy use, osteoporosis medication use, calcium supplementation, vitamin D supplementation, and fracture history. Robust standard errors were used in the final models. Results: Higher ASMI was independently associated with higher BMD at the lumbar spine (standardized β = 0.362, p < 0.001), total hip (standardized β = 0.371, p < 0.001), and femoral neck (standardized β = 0.353, p < 0.001). WC was positively associated with total hip BMD (standardized β = 0.158, p = 0.006), whereas no statistically significant associations were observed at the lumbar spine (standardized β = 0.009, p = 0.899) or femoral neck (standardized β = 0.105, p = 0.092). Conclusions: ASMI was consistently associated with BMD across all measured skeletal sites, whereas the association between WC and BMD varied according to skeletal region. These findings support the complementary assessment of skeletal muscle mass and central adiposity for characterizing body composition and skeletal health in postmenopausal women. Full article

Background: Adoption of surgical robotic systems is accelerating globally, driven by advances in clinical capability, ergonomics, and workflow efficiency. However, robotic surgery programs introduce complex organizational challenges related to patient safety, workforce capability, infrastructure readiness, governance, vendor dependency, procurement, and long-term sustainability. Hospitals often lack structured, leadership-oriented frameworks to support systematic, context-appropriate evaluation, adoption, and governance of these technologies. Objective: To develop a multidisciplinary, consensus-based framework to support leadership-level evaluation, organizational readiness assessment, adoption, and governance of surgical robotic systems. Methods: A two-round modified Delphi study was conducted at Singapore General Hospital involving eleven stakeholder groups spanning clinical, perioperative, technical, operational, governance, and executive domains. Department-level consensus responses were generated. In Round 1, stakeholders completed role-specific questionnaires comprising Likert-scale items and open-ended questions. Items rated as low importance were excluded, while items of moderate importance were refined through thematic analysis. In Round 2, refined and newly generated items were re-evaluated. Items achieving ≥70% agreement for high importance within each stakeholder group were retained. Results: A total of 417 consensus-derived items were identified and organized into nine thematic domains encompassing patient safety and risk management, technical capability and surgical performance, workflow integration, training and credentialing, governance and sustainability, vendor support, infrastructure, logistics, and operational readiness. The framework was operationalized through category-specific interpretive scoring rubrics and three domain-weighted decision models reflecting clinician, safety, and procurement perspectives. Conclusions: This study presents a leadership-oriented, multi-stakeholder framework to support the risk-aware evaluation, adoption, implementation, and governance of surgical robotic systems. By integrating considerations across institutional readiness, comparative robotic platform assessment, and program governance, the framework provides a structured approach to decision-making throughout the robotic surgery lifecycle. While it may serve as a useful starting point for institutions seeking to establish or expand robotic surgery programs, the framework was developed and evaluated within a single academic tertiary healthcare institution. Further validation across diverse healthcare settings, including community hospitals, non-academic institutions, specialty centers, and resource-constrained environments, is required before broader adoption can be recommended. Full article

Manufacturer datasheets state battery cycle life under conditions that rarely match how cells are used, while public cycling datasets measure degradation under conditions datasheets do not cover. We present a knowledge-graph (KG) system that represents claims, measurements, and independent tests of commercial lithium-ion cells with full provenance, detects claim-versus-measured and claim-versus-claim discrepancies conditioned on the comparability of test conditions, and supports cycle-life prediction with coverage-gated abstention. On the 124-cell Severson dataset under leave-one-policy-group-out cross-validation, graph-derived neighbor features do not significantly improve point prediction over a strong early-cycle baseline (RMSE 135 vs. 141 cycles), but graph coverage provides a statistically significant abstention signal (Spearman $\rho =-0.25$ with prediction error, $p=0.006$) that reduces retained RMSE by roughly 40% at 60% retention, where random abstention does not. Deployed zero-shot on a second cycling study of the same commercial cell, the gate abstained on all 77 cells; the counterfactual confirms every refusal (approximately 83% error had it answered), an error an ungated baseline commits silently. On a third study with commensurable features, the gate’s first partial acceptance (17 of 45 cells) is itself diagnostic: coverage acts partly as a lifetime proxy out of distribution, and five labeled cells halve retained error while leaving that proxy in place—adaptation repairs the predictor, not the selection criterion. A 70B open-weight LLM extracts datasheet claims at $F_1=0.70$ with non-deterministic output even at temperature 0; a deterministic validator with three-run consensus raises this to $F_1=0.78$ with zero unsourced values; on a held-out datasheet, precision and the zero-unsourced-value property transfer while recall falls to 0.34, localizing the extractor’s boundary at table-structured content; row-level table grounding, implemented in response, raises held-out recall to 0.63 with zero hallucinations at a measured precision cost. Reconciling claims across document variants shows that roughly one in three cross-document specification comparisons (14 of 43, three commercial cells) yields a conflict or condition mismatch, twelve involving third-party documents and two internal to a single manufacturer’s own documents. A hand-labeled, condition-annotated gold standard of 103 claims (62 development, 41 held-out; inter-annotator $\kappa =0.74$ on property naming) and a staged, human-gated literature-monitoring pipeline are released with the code. Full article

RASopathies are a group of genetic disorders caused by germline variants affecting the RAS/MAPK pathway. Their shared phenotypic features—craniofacial anomalies, cardiac defects, cutaneous findings, neurodevelopmental issues, and cancer predisposition—make diagnosis challenging, especially since most lack standardized clinical criteria. This study aimed to develop a practical diagnostic algorithm based on high-frequency Human Phenotype Ontology (HPO) features. Key clinical variables for each RASopathy were identified through HPO, PubMed, and GeneReviews. Only findings present in 80–99% of cases or supported by expert consensus were included. A decision-tree algorithm was constructed and preliminarily evaluated using a blinded cohort of 50 individuals with confirmed molecular diagnoses. Patients were eligible for inclusion if they met the following criteria: (1) molecularly confirmed diagnosis of a RASopathy by next-generation sequencing identifying a pathogenic or likely pathogenic variant; (2) availability of complete phenotypic records in the institutional clinical database; and (3) age at evaluation between 0 and 18 years. Patients were excluded if phenotypic data were incomplete or if molecular confirmation was absent. The algorithm integrates phenotypic patterns and genotype–phenotype correlations. Validation showed 78% accuracy (95% CI: 64.0–88.4%) for clinical diagnosis and 66% accuracy (95% CI: 51.2–78.8%) for molecular prediction. To our knowledge, this is the first HPO-based diagnostic algorithm for the clinical and molecular approach to RASopathies. It provides a structured, accessible tool to improve early recognition and guide molecular testing, particularly for the RASopathy subtypes represented in the validation cohort. Further external validation including underrepresented subtypes is required. Full article

Urban green-space provision depends not only on green quantity but also on how greenery is positioned relative to buildings as urban form evolves. However, most existing assessments aggregate greenery within predefined spatial units and rely on static snapshots, thereby obscuring both its distance-sensitive distribution around buildings and its variation across urban-development trajectories. This study develops a Supply–Form framework to examine this relationship across heterogeneous development trajectories. Using multi-temporal very-high-resolution imagery from Beijing and Tianjin, we introduce Quantified Green-Space Supply (QGS), a distance-weighted indicator that accumulates greenery around buildings over nested ranges of 5–2000 m. Building-expansion trajectories are then linked to evolution-stratified XGBoost models interpreted with consensus-grouped Partition SHAP, allowing recurrent morphological groups and their within-group contributions to be compared across contexts. QGS was more strongly associated with the selected urban-form variables than conventional green coverage ($R^2=0.717$ versus $0.633$). Both cities showed higher mean QGS in 2022 than in 2012, but their internal patterns diverged: Beijing developed more continuous central low-QGS clusters, whereas Tianjin’s central cold spots contracted and fragmented. Across 15 trajectory-specific models, building density was the leading morphological group in 12, while the importance of patch size, edge structure, aggregation–adjacency, and spatial configuration varied by trajectory. Nonlinear responses showed a stable positive association for building density, diminishing returns for edge density and dispersion, adverse effects at very high adjacency, and intermediate-range benefits for patch dominance and compactness. The framework advances green-space assessment from aggregate greenness mapping to a relational, trajectory-conditioned diagnosis of potential surrounding green-space supply, providing a basis for context-sensitive urban renewal. Full article

The primary aim of this study is to identify how residents on the Hungarian and Slovak sides of the Lower Ipoly Valley perceive the most considerable material and immaterial local values and unique resources of their settlements. The research was designed to explore and compare the territorial capital of the two sides of the study area based on three major capital types: natural, social, and economic capitals. Data collection included 254 semi-structured interviews, conducted with 136 residents on the Slovak side (14 settlements) and 118 residents on the Hungarian side (12 settlements). Detailed interview summaries were analysed with qualitative content analysis using emergent coding. This resulted in an analytical framework comprising nine value dimensions. Across both sides of the border, we examined the same nine value dimensions: local workforce, local enterprises, civil organisations and cultural groups, local and community events, local gastronomy, natural values, built heritage, holders of local knowledge, and local products. Items mentioned that related to each value dimension were counted for each dimension and normalised to a 0–10 scale. The quantified values were aggregated at the settlement level (90 points being the maximum score). The average score of each dimension was also calculated for both sides of the study area. Our findings show that the Hungarian side achieved a total score of 40.4, while the Slovak side reached 36.6, both reflecting a similarly weak–moderate state of the local capitals with minimal differences. This indicates that the two sides of the study area share comparable developmental challenges but also considerable potential for improvement. The Hungarian side performed slightly better in nearly all dimensions except local gastronomy, where the Slovak side proved stronger. The Hungarian side’s relative advantages include a higher presence of local enterprises, a richer network of civil and cultural groups, and more diverse built heritage; in other dimensions, differences are marginal. One of the most pressing regional challenges is improving employment opportunities and stimulating entrepreneurial activity, which are essential for enhancing population retention. Overall, the results indicate that the settlements possess substantial—yet largely underutilised—value assets, whose conscious and consensus-based development could form a strong foundation for creative and innovative local development. Each settlement’s value matrix includes elements that define its uniqueness, enabling the identification of numerous potential development pathways, whether through nature-based educational and recreational programmes, the utilisation of culturally considerable built heritage, the revitalisation of living traditions, or the promotion of local traditional gastronomy on both sides of the study area. Full article

China’s pork sector is a major component of the national food system. Establishing plant-based pork supply chains requires coordination across production, quality control, infrastructure, logistics, information exchange, and market formation. However, previous studies generally examine these barriers separately, limiting understanding of how they interact within the wider food-supply system. This study identifies and analyzes the systemic barriers to establishing plant-based pork supply chains in China. An integrated Fuzzy Delphi Method (FDM) and Decision-Making Trial and Evaluation Laboratory (DEMATEL) approach is applied. FDM is used to refine and validate 14 contextually relevant barriers based on expert consensus, while DEMATEL examines their direct and indirect relationships, systemic prominence, and net causal influence. Insufficient research and development funding and deficiencies in quality control emerge as the strongest net causal barriers. High infrastructure investment also belongs to the cause group, while technological, operational, and market-related barriers occupy different causal and dependent positions within the wider system. The results support a sequenced intervention strategy that begins with innovation capacity, quality assurance, and infrastructure, followed by operational coordination and market formation. This study contributes by moving beyond barrier identification and ranking to explain how multiple barrier domains interact and how interventions can be prioritized. The analysis concerns supply chain establishment and does not directly assess the environmental, economic, or social sustainability performance of plant-based pork. Full article

Background: Tattooed teachers are increasingly visible in schools, yet the norms governing their professional acceptability remain poorly understood. This study tests whether pluralistic ignorance—private acceptance systematically exceeding the acceptance attributed to others—operates in attitudes toward tattooed teachers, and identifies individual-level predictors of this misperception. Methods: A cross-sectional online survey was conducted with 1226 individuals in Hungary across four groups: physical education (PE) teacher trainees, university students from other disciplines, secondary school students, and in-service teachers. Participants rated their own acceptance of tattooed PE and academic-subject teachers and the acceptance they attributed to other teachers and to parents, and reported tattoo status, gender, and professional background. Results: Own acceptance exceeded attributed acceptance in all four groups and for both reference targets, consistent with pluralistic ignorance; gaps were largest among secondary school students and smallest—though still positive—among in-service teachers. Personal tattoo experience was the strongest individual predictor of acceptance after group membership, and among teachers both age and experience were negatively associated with acceptance. Acceptance was predominantly conditional, structured by a visibility hierarchy in which arm placements were most acceptable and facial or neck placements least so. Conclusions: The apparent disapproval of tattooed teachers reflects collective misperception more than genuine consensus, suggesting that making actual peer attitudes visible could reduce conformity pressure and support more authentic professional self-expression. Full article

UK cancer waiting-time standards inadequately address the complex needs of older patients, and no standardised, implementable comprehensive geriatric assessment (CGA) case-finding framework exists for this population. Using a nominal group technique involving clinicians and advocates, a consensus was reached to develop the Cancer Risk Assessment and Needs Evaluation (CRANE) CGA case-finding framework. CRANE was designed to be completed in 10–15 min for patients aged 70 and over, incorporating ten key domains, including comorbidity, cognitive function, and social situation, considered essential for routine NHS use. CRANE represents a consensus-derived, pragmatic case-finding framework for identifying unmet geriatric needs in older adults with cancer in NHS pathways. It should be regarded as a consensus framework rather than a validated screening instrument. Prospective implementation and validation studies are required before routine clinical adoption. Full article

Reliable rainfall regionalization underpins hydrological design and the transfer of rainfall information to ungauged or short-record sites, yet it is especially difficult in arid regions with strong spatial and temporal variability and short, uneven records. This study develops a multivariate, stability-validated framework for classifying rain gauges into candidate homogeneous rainfall regions across Saudi Arabia. A national database of 274 stations was screened for 2015–2023, and 202 stations were retained. Ten descriptors representing annual rainfall, interannual variability, L-skewness of annual maxima, within-day rainfall concentration, short-duration intensity, elevation, and distance from the coast were constructed from 5 min records; correlated concentration and intensity descriptors were compressed by block-wise principal component analysis into a seven-variable, robustly scaled feature matrix. Partitions from K = 2 to 10 were evaluated using internal-validity indices, the gap statistic, minimum cluster size, repeated-subsample stability, cross-algorithm agreement, and sensitivity to alternative feature representations. The diagnostics supported several low-order structures: the four-region K-means solution showed the highest subsample stability (median adjusted Rand index: 0.977) and best consensus rank, whereas Ward clustering and Gaussian mixture modeling favored a parsimonious three-region solution. At four regions, cross-algorithm agreement was moderate (adjusted Rand index: 0.526–0.663) and the partition was strongly reproduced under the robust original-variable and global principal component analysis-(PCA)PCA representations (0.804). The regions comprised a widespread arid interior, a small near-coastal group, a wetter western–southwestern group, and a coastal-foothill group, with distance from the coast, elevation, and short-duration intensity providing the strongest contrasts. The framework offers a reproducible basis for regional rainfall-frequency analysis, station pooling, and hydrological transfer, pending verified completeness data and formal homogeneity testing. Full article

Background: Orofacial pain (OFP) comprises a heterogeneous group of conditions with overlapping clinical manifestations that frequently complicate diagnosis and therapeutic decision-making. Diagnostic inaccuracies may contribute to delayed management, unnecessary dental procedures, and reduced quality of life. Despite the availability of standardized classifications and diagnostic criteria, their translation into routine clinical practice remains variable. Aim: This systematic review aimed to systematically identify, describe, and critically evaluate diagnostic frameworks proposed for the differential diagnosis of OFP. Diagnostic frameworks were broadly defined as structured approaches to clinical decision-making, including clinical practice guidelines (CPGs), classification systems, clinical algorithms, consensus documents, and other explicit diagnostic models. The review focused on their methodological quality, evidentiary support, clinical applicability, and operational utility in dental practice. Methods: A systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Electronic databases were searched using predefined terms related to OFP. Eligible studies included investigations assessing diagnostic protocols, clinical decision-making frameworks, or therapeutic implications in patients with OFP. Non-systematic expert opinions, editorials, and book chapters were excluded from the analysis. Data extraction and qualitative synthesis were performed independently by the reviewers. Results: A total of 184 records were identified through database searching. After duplicate removal and eligibility assessment according to the PRISMA flowchart, 12 studies were included in the qualitative synthesis. Additionally, the International Classification of Orofacial Pain (ICOP) was used as an external contextual reference framework and was not included in the PRISMA study count. The included studies demonstrated marked heterogeneity in diagnostic approaches, including theoretical, pathophysiological, clinical reasoning, classification-based, and algorithm-driven frameworks. Methodological quality was generally moderate to high. The scope and clarity domains showed the strongest performance, whereas development rigor remained limited across studies. Overall, clinically applicable frameworks frequently lacked methodological rigor. Conclusions: Current diagnostic frameworks for OFP remain methodologically heterogeneous and vary considerably in their degree of operationalization and empirical validation. Future diagnostic frameworks and CPGs should incorporate standardized terminology, reproducible diagnostic criteria, structured examination pathways, and clinically applicable recommendations to improve diagnostic consistency and facilitate implementation in routine practice. Full article

Objectives and Background: Individuals with Phelan–McDermid Syndrome (PMS) present with a variety of symptoms, including a breadth of behavioral issues. Clinically assessing behavior in PMS remains challenging due to the overabundance of behavioral assessments and the lack of tools validated explicitly for use in individuals with intellectual disability (ID) and neurodevelopmental disorders. This review sought to suggest which assessment tools would best clinically assess behavior in individuals with PMS. Methods: Validated behavioral assessment tools were identified using a systematic search of the literature, and relevant data for each assessment were extracted. The consensus guidelines for PMS were reviewed. Results: This review identified 131 validated assessment tools that were categorized by the intended age group and into specific behavioral domains: Autism spectrum disorder (ASD) screening, adaptive behavior, restricted and repetitive behaviors, challenging/disruptive behaviors, mental health screening, and other miscellaneous behaviors such as avoidance and impulsivity. Discussion: Based on the 2023 consensus guidelines, suggestions were given on which tools would be best for assessing various symptoms and behaviors in PMS. Choosing the best assessment tools to appraise behavior and related symptoms in individuals with PMS will aid clinicians in decision-making and lead to more personalized treatment plans. Full article