Search Results (5,937)

Background: Breast surgery, both aesthetic and reconstructive, has evolved significantly over the years. Postoperative care is vital for patient recovery, with surgical dressings playing a crucial role in minimizing complications, including infections and bleeding. This review aims to evaluate the safety, comfort, and effectiveness of different durations for wearing surgical dressings after breast surgery. It also explores the use of negative pressure wound dressings and postoperative bras to enhance surgical outcomes. Methods: A comprehensive review of literature published from 2003 to 2024. Studies focusing on breast dressing techniques after mammary reconstruction and aesthetic surgery in plastic surgery were included. Results: Of 1503 initially identified articles, 12 were deemed relevant and included in this review. The findings suggest that prolonged dressing wear, up to 6 days postsurgery, may reduce cutaneous colonization without affecting infection rates in aesthetic breast surgery. Additionally, negative pressure wound therapy demonstrates promise in reducing overall wound complications and mastectomy flap necrosis. The utilization of specific postoperative bras is shown to improve patient comfort, mobility, and security, contributing to pain reduction and aesthetic outcomes. Conclusions: The lack of consensus on dressing selection and duration calls for further research in breast surgery postoperative care. Extended dressing wear, negative pressure therapy, and customized postoperative bras show potential in reducing complications, providing new avenues to enhance patient outcomes in the field of plastic surgery. Addressing these issues can lead to improved patient satisfaction and surgical results. Full article

Urban markets are key nodes for the persistence and adaptation of traditional edible plant knowledge, linking rural production with urban consumption. This study was based on monthly market surveys conducted throughout 2025 in an urban market in Baise City, Guangxi, China. A total of 54 edible plant taxa were recorded, including both native and introduced species, with herbaceous plants predominating alongside climbers, trees, and grasses. Ethnobotanical data were obtained through semi-structured interviews with 40 local informants (20 men and 20 women, aged 25–65 years) selected using purposive sampling, focusing on individuals actively involved in purchasing and preparing edible plants. High Cultural Food Significance Index (CFSI) values highlighted culturally central taxa, including Allium ascalonicum L., × Brassarda juncea (L.) Su Liu & Z.H. Feng, and Houttuynia cordata Thunb., reflecting frequent use and culinary–medicinal integration. Fidelity Level (FL) analyses identified species with strong consensus for specific therapeutic applications, such as × B. juncea, Alpinia galanga (L.) Willd., and Nelumbo nucifera Gaertn., while Informant Consensus Factor (FIC) values indicated moderate to high agreement across gastrointestinal, respiratory, inflammatory, and other health categories. These results underscore the persistence of the “food as medicine” concept, showing that edible plants function simultaneously as nutritional and preventive healthcare resources. The overlap of culinary and medicinal roles demonstrates dynamic food–medicine integration, with urban markets acting as cultural hubs that maintain dietary diversity, household food security, and ethnobotanical knowledge. Future studies should incorporate ethnozoological resources and longitudinal monitoring to capture the full scope of urban food–medicine systems. Full article

Coronary computed tomography angiography (CCTA) is increasingly recognized as a comprehensive tool for planning percutaneous coronary intervention (PCI). By integrating plaque morphology, calcium burden, and CT-derived coronary physiology, CCTA enables non-invasive assessment of lesion complexity and supports precision-guided revascularization. This narrative review synthesizes current evidence on CT-guided PCI from original studies, registries, expert consensus documents, and international guideline recommendations. The literature was identified through PubMed, Embase, and Google Scholar, focusing on CCTA-based plaque characterization, calcium assessment, bifurcation and ostial lesions, chronic total occlusions (CTO), FFR-CT, virtual PCI simulation, and fusion imaging. Particular attention was given to contemporary investigations such as SYNTAX III, P3, and the ongoing P4 trial. CCTA reliably characterizes stenosis severity, plaque distribution, and calcification, demonstrating strong concordance with intravascular imaging. CT-based measurements support accurate stent sizing, prediction of calcium modification requirements, and identification of high-risk features in bifurcation and ostial disease. In CTO PCI, CCTA enhances visualization of proximal cap morphology, occlusion length, tortuosity, and distal vessel quality, outperforming angiographic scoring systems. CT-derived physiology and virtual PCI planning improve lesion selection and allow prediction of post-PCI hemodynamics. Emerging technologies—including photon-counting CT, artificial intelligence-assisted plaque analysis, and CT–fluoroscopy fusion—further expand the applicability of CT-guided PCI. The ongoing P4 trial is expected to provide definitive validation of CT-guided PCI and may support its incorporation into routine clinical workflows. Full article

The increasing frequency of interior renovation and fit-out in office buildings raises concerns about indoor environmental quality, occupant health, and sustainability performance, yet existing certification systems remain largely design-stage or whole-building oriented and provide limited guidance for recurring renovation cycles. This study develops a health-oriented assessment framework for office interior renovation as a structured decision-support tool for practitioners and policymakers. We adopted an integrated approach combining a targeted literature review, expert consultation, the Fuzzy Delphi Method (FDM) for indicator screening, and the Analytic Hierarchy Process (AHP) for hierarchical weighting, based on an expert panel of 20 professionals spanning green building certification, architecture/interior design, MEP engineering, property/facility management, and energy/environmental consulting. Through consensus screening and weighting, four assessment dimensions and eighteen key indicators were identified and prioritized. Environmental quality was ranked highest (39.2%), followed by safety management (23.0%), functional usability (21.1%), and resource efficiency and circularity (16.7%). At the indicator level, indoor air quality management, Heating, Ventilation and Air Conditioning (HVAC) energy efficiency, space-friendly layout, preliminary assessment and planning, and thermal comfort emerged as the top priorities. Overall, the framework bridges the gap between certification-oriented evaluation and the operational realities of office renovation, enabling more consistent integration of health and sustainability considerations across renovation decision-making. Full article

High-precision and consensus tracking of a long-range maneuvering target presents a significant challenge for unmanned aerial vehicles (UAVs) in complex denied environments. Earlier studies rarely considered the fast convergence and fusion accuracy of distributed consensus tracking in bearing-only UAV networks. This article proposes a distributed consensus-based estimation (DCE) method with inverse covariance intersection (ICI) fusion rule in the framework of local estimation, consensus iteration, and fusion estimation. Combined with the contribution of measurements from neighboring UAVs, the local estimation of target tracking can be achieved by a square-root cubature information filter (SRCIF) in bearing-only UAVs. Based on local estimation and centralities in a multi-UAV network, each UAV platform can obtain consensus results in a finite number of iterations. Then, the fusion estimations are the consensus with the global ICI fusion rule. Furthermore, the fusion estimations are analyzed in consensus, finiteness, and boundedness. Numerical simulations are performed to validate the effectiveness and superiority of the proposed DCE–ICI method. Full article

Segmented filamentous bacteria (SFB) are host-specific, immune-modulating microorganisms that colonize the small intestine of various vertebrate species, playing a crucial role in stimulating immune maturation during early life. Previous research on the genomes of SFB from humans, rats, and mice has revealed significant differences among SFB strains associated with various hosts, suggesting that their evolution is closely linked to their relationships with specific hosts. However, the genome of SFB from chickens has not been extensively investigated. In this study, we present the metagenomic reconstruction of an SFB genome derived from the ileum of layer Lohmann Select Leghorn (LSL) chickens. We utilized Hi-C sequencing techniques to assemble the LSL-SFB and annotate the avian SFB from both turkeys and chickens. Our reference-guided consensus assembly, followed by Hi-C scaffolding, produced a high-quality genome for LSL-SFB. Our pangenomic analysis revealed substantial conservation of core gene clusters among mammalian SFB strains, but we also identified a distinct repertoire of genes in chicken and turkey SFB. Furthermore, metabolic network analysis indicated a reduced capacity for biosynthesis, signifying an increased reliance on the host, as shown by the absence of key biosynthetic and utilization pathways. We also discovered a unique flagellin subunit (fliC-2) in chicken SFB from different genetic lines and confirmed its interaction with the chicken flagellin receptor, Toll-like receptor five. This study provides the first high-quality genome and annotation of LSL-SFB, alongside that of turkeys, offering valuable insights into the mechanisms of host specificity and adaptation. Understanding the interactions between host-specific SFB and their hosts, as well as their role in promoting immune maturation, is essential for improving intestinal health. Full article

Background/Aims: This study aimed to undertake a systematic literature review to compare the effectiveness of narrowband UVB (nb-UVB) therapy with Psoralen + UVA (PUVA) or Psoralen + UVB treatments in individuals with vitiligo. Methods: A comprehensive search was executed across multiple electronic databases (PubMed, Embase, Cochrane, Scopus, Web of Science, LILACS) and grey literature repositories (Google Scholar, LIVIVO, OpenGrey, ProQuest). Methodological quality was independently assessed by two reviewers employing the Cochrane RoB 2 tool; consensus was achieved through consultation with a third reviewer when necessary. The main efficacy endpoint was repigmentation. Results: From 4758 initial records, four randomized controlled trials that satisfied the inclusion criteria were identified. The aggregated results from these studies indicated that nb-UVB, either alone or combined with psoralen (P-nbUVB), produced better repigmentation outcomes compared to PUVA. Conclusions: Nb-UVB phototherapy demonstrated superior repigmentation efficacy, improved color matching, and a faster clinical response relative to PUVA. The addition of psoralen (P-nbUVB) further enhanced therapeutic outcomes, particularly in VASI scores and in areas typically less exposed to resunlight. Full article

Objectives: Artificial intelligence (AI) is a transformative development in the field of medicine. In the field of musculoskeletal radiology, agentic AI is a technology that could flourish, but currently, the limited evidence base is fragmented and sparse, and we present a scoping review of it. Methods: Parallel searches were conducted in four databases: PubMed, Embase, Scopus, and Web of Science. Search terms included all agentic AI and autonomous AI agents, as well as radiology. All papers underwent screening by two independent reviewers, with conflicts resolved through consensus. Initially, inclusion criteria involved all papers on general radiology, which were later stratified for musculoskeletal radiology and applicable papers to ensure inclusion of all suitable studies. A thematic analysis was undertaken by two independent reviewers. Results: Eleven studies met the inclusion criteria, comprising two MSK (musculoskeletal)-specific and nine general radiology papers applicable to MSK workflows. Four key themes emerged. Agentic decision support was demonstrated across five studies, showing improved diagnostic coordination, pathway navigation, and reduced clinician workload. Workflow optimisation was highlighted in four studies, with agentic systems enhancing administrative efficiency, modality selection, and overall radiology throughput. Image analysis and reconstruction were improved in three studies, with multi-agent systems enabling enhanced image quality and automated interpretation. Finally, four studies addressed conceptual, ethical, and governance considerations, emphasising the need for transparency, safety frameworks, and clinician oversight. Conclusion: Agentic AI shows considerable promise for enhancing MSK radiology through improved decision support, image analysis, and workflow efficiency; however, the current evidence remains limited and largely theoretical. Full article

Recent studies have increasingly indicated that postoperative complications after esophagectomy are correlated with poor long-term prognoses, making it crucial to prevent such complications. Based on our studies, we believe that central to this issue is the finding that among esophageal cancer patients who experience postoperative complications and have poor long-term prognoses there is a high incidence of poor oral environments. Here we review the results of our basic and clinical research studies, as well as evidence from other institutions, on the oral environment of esophageal cancer patients and its association with the incidence of complications and long-term prognoses. We hope these findings, which suggest “improving the oral environment of esophageal cancer patients can reduce the incidence of postoperative complications and improve long-term prognoses”, will gain consensus and lead to safer esophageal cancer surgery. Full article

This study examines how the notion of value is defined, recognised, and operationalised within the four main approaches to cultural heritage preservation: the material-based, value-based, living heritage, and historic urban landscape approaches. Positioned within the broader discourse on the evolving understanding of cultural heritage—from fixed, expert-driven interpretations toward more contextual, socially constructed, and participatory perspectives—this research aims to address which value types are recognised, and how and to what extent they are operationalised by applying four main approaches to cultural heritage preservation. The methodology comprises four phases: (1) the identification, search, and selection of academic articles in the Scopus database, (2) sample overlapping and elimination of duplicates to establish a final dataset, (3) bibliometric analysis to determine publishing trends and disciplinary reach, and (4) content analysis to identify, classify, and compare value types across the selected approaches. The results reveal significant variation in how values are represented, as well as notable inconsistency in their direct inclusion in research processes. While cultural, historical, aesthetic, social, and economic values dominate across approaches, only a fraction of studies operationalise values through defined criteria or indicators. The findings highlight the absence of consensus in value interpretation and emphasise the need for more systematic, integrative, and operationalisable frameworks for treating values in the process of cultural heritage preservation. Full article

Background: Neuroimaging protocols for neurotologic disease are often developed without consideration of patient-specific factors such as biological differences, clinical presentation variability, and comorbidities. This lack of tailored design contributes to insufficient detection, delayed diagnosis, and inappropriate treatment. Objectives: To critically examine the literature on diagnostic limitations of neuroimaging for neurotologic lesions and identify gaps in protocol validation, accuracy, and clinical translation. Methods: A systematic review of PubMed and Google Scholar was conducted, focusing on studies published between 2015 and 2025 that evaluated diagnostic imaging outcomes in patients with neurotologic lesions. Eligible studies included prospective cohorts, retrospective analyses, and consensus statements. Outcomes of interest included the sensitivity and specificity of imaging modalities, prevalence of misdiagnosis, and the influence of biological, anatomical, and clinical variability on diagnostic performance. Results: The literature demonstrates that neurotologic disorders are frequently associated with diagnostic challenges, including atypical clinical presentations, overlapping symptoms, and stroke mimics, which complicate image interpretation. Standard magnetic resonance imaging (MRI) protocols often miss subtle or early ischemic changes, resulting in delayed intervention. Few studies stratify outcomes by patient characteristics, and most protocols were developed in generalized populations without comprehensive validation. Evidence on advanced imaging modalities (positron emission tomography (PET), single-photon emission computed tomography (SPECT), high-resolution MRI) remains limited, and large-scale prospective studies addressing diagnostic accuracy gaps are lacking. In summary, a total of 27 studies met inclusion criteria. Conclusions: Current neuroimaging methods are insufficiently validated across diverse patient populations, contributing to the underdiagnosis and mismanagement of neurotologic disease. Improved diagnostic accuracy will require large-scale, prospective research, standardized outcome reporting, and imaging protocols designed to account for patient-specific variability. Full article

Background/Objectives: During intrauterine development, cell proliferation, differentiation, and apoptosis are strictly regulated for organogenesis to be ensured; disruption of these processes, e.g., by oxidative stress, may lead to congenital anomalies. This systematic review aimed to examine the role of selenium (Se), an important antioxidant, during gestation in the development of congenital anomalies. Methods: To identify relevant original research studies in English, PubMed, Embase, and Cochrane Library were systematically searched up to December 2025. A qualitative synthesis, quality appraisal, and assessment of predefined sources of bias and heterogeneity were performed. Results: 2743 titles and abstracts were screened, 473 full texts assessed, and 31 papers included. Selenium exposure did not affect the risk of all/any congenital anomalies (n = 20,815), abdominal (n = 89,273) and limb anomalies (n = 551,547), chromosomal anomalies (n = 1242), or fetal alcohol syndrome (n = 41). Higher concentrations of Se were associated with increased risk for urinary tract anomalies (n = 2150), but decreased risk for congenital heart defects (n = 1807), neural tube defects (max n = 12,188), and orofacial clefts (max n = 1155). Conclusions: Available scientific evidence arises from observational studies and is prone to confounding mainly by gestational age, while only one randomized controlled trial has been identified. Given the major contribution of congenital anomalies to neonatal morbidity, mortality, and long-term impairment of quality of life, well-designed prospective studies are required to establish scientific consensus, define optimal maternal Se levels during pregnancy, and provide evidence-based recommendations for Se supplementation during pregnancy. Full article

This study proposes a stage-aware governance framework for large language models (LLMs) that structures human oversight and accountability across different decision stages in AI-assisted literature review systems. Large language models (LLMs) are increasingly embedded in systematic review workflows, yet how human oversight and accountability should be structured across different decision stages remains unclear. This study evaluates three LLMs in a controlled two-stage literature review workflow—title-and-abstract screening and eligibility assessment—using identical evidence inputs and fixed inclusion criteria, with outputs benchmarked against expert consensus under fully reproducible conditions with standardized prompts and comprehensive logging. While LLMs closely matched expert decisions during screening (precision 0.83–0.91; F1 up to 0.89; Cohen’s κ 0.65–0.85), performance degraded substantially at the eligibility stage (F1 0.58–0.65; κ 0.52–0.62), indicating increased epistemic uncertainty when fine-grained criteria must be inferred from abstract-level information. Importantly, disagreements clustered in borderline cases rather than random error, supporting a stage-aware governance approach in which LLMs automate high-throughput screening while inter-model disagreement is operationalized as an actionable uncertainty signal that triggers human oversight in more consequential decision stages. These findings highlight the need for explicit oversight thresholds, responsibility allocation, and auditability in the responsible deployment of AI-assisted decision systems for evidence synthesis. Full article

Photovoltaic-storage direct current (DC) flexible (PEDF) systems are susceptible to DC bus voltage disturbances, with the constant power load (CPL) characteristics further exacerbating the risk of system instability. To address these challenges, a collaborative control scheme integrating distributed consensus and demand-side response (DSR) based on a consensus protocol is proposed in this study. A fully distributed control architecture is constructed, wherein the upper layer achieves power coordination through voltage deviation of parallel DC/DC converters and neighborhood interaction, whilst the lower layer dynamically optimizes inter-unit power allocation via the DSR mechanism. Distributed state estimation (DSE) is incorporated to enhance voltage control accuracy. Simulations conducted in the MATLAB (R2022a)/Simulink environment demonstrate that the proposed strategy enables rapid stabilization of bus voltage under load step changes and photovoltaic fluctuation scenarios, with system disturbance rejection capability being effectively enhanced. The effectiveness of the approach in maintaining stable system operation and optimizing power distribution is validated. The results indicate that the voltage deviation of the PEDF system remains below 2% under compound disturbances, with the steady-state error being controlled within 2%. The proposed control strategy, through the integration of the power DSR mechanism, effectively improves the system’s anti-disturbance capability. Compared with conventional droop control methods, which typically result in voltage deviations of 3–5%, the proposed strategy achieves a reduction in voltage deviation of over 50%, demonstrating superior voltage regulation performance. Full article

Background/Objectives: The Global Leadership Initiative on Malnutrition (GLIM) recently updated its inflammation criterion through a Delphi consensus to standardize its assessment. This study aimed to assess the impact of these new recommendations on the concurrent and predictive validity of the GLIM criteria in hospitalized medical patients. Methods: This post hoc analysis re-evaluated a previously published cohort of 119 hospitalized patients with acute medical conditions, originally assessed using the GLIM criteria and the Subjective Global Assessment (SGA) as the reference standard. Inflammation was redefined according to the 2024 GLIM Delphi consensus, and the concurrent and predictive validity of the modified GLIM criteria (GLIM-I) were examined. Receiver operating characteristic (ROC) curves were used to compare the discriminative ability of SGA, original GLIM, and GLIM-I to predict prolonged hospital stay. Results: With the updated inflammation definition, all patients met the etiologic criterion, increasing malnutrition prevalence from 41.7% to 52.2%. GLIM-I showed a sensitivity of 78.0% and specificity of 67.7% versus SGA, not reaching the predefined ≥80% threshold for concurrent validity. Predictive validity was maintained (adjusted odds ratio (OR) = 3.40; 95% CI: 1.31–8.83). SGA achieved the highest discriminative ability (area under the curve (AUC) = 0.783; 95% CI: 0.693–0.874), significantly outperforming the original GLIM (AUC = 0.723; 95% CI: 0.616–0.830; p = 0.049). GLIM-I showed similar performance (AUC = 0.731; 95% CI: 0.620–0.843; p = 0.727). Conclusions: SGA should continue to be considered the method of choice for nutritional diagnosis in hospitalized medical patients. Further research is needed to determine how the new inflammation criteria influence the validity of the GLIM framework in other clinical contexts before their widespread implementation. Full article