Search Results (2,389)

The blood-brain barrier (BBB) is one of the most selective physiological interfaces in the human body. Transendothelial electrical resistance (TEER) has become a widely adopted quantitative metric for assessing its in vitro structural and functional integrity. Although TEER measurements are routinely incorporated into BBB-on-chips, the absence of harmonized electrode architectures, measurement settings, and reporting standards continues to undermine reproducibility and translational reliability among laboratories. This systematic review provides the first comprehensive classification and critical comparison of electrode configurations used for TEER assessment, specifically within BBB-on-chip systems. Eligible studies were analyzed and categorized according to electrode design, fabrication method, integration strategy, and operational constraints. We critically evaluated six principal electrode architectures, highlighting their performance trade-offs in terms of uniformity of current distribution, long-term stability, scalability, and compatibility with dynamic shear conditions. Furthermore, we propose a bioinspired TEER reporting framework that consolidates essential metadata, including electrode specification, temperature control, viscosity effects, and blank resistance correction. Our analysis proposes screen-printed and hybrid silver-indium tin oxide (ITO) electrodes as promising candidates for next-generation BBB platforms. Moreover, our review provides a structured roadmap for standardizing TEER electrode design and reporting practices to facilitate interlaboratory consistency and accelerate the adoption of BBB-on-chip systems as truly biomimetic platforms for predictive neuropharmacological workflows. Full article

Modified Spitzy shelf acetabuloplasty is a joint-preserving surgical procedure for acetabular dysplasia that aims to enhance bony coverage of the hip joint. Although prior studies have primarily relied on two-dimensional (2D) radiographic evaluations, comprehensive three-dimensional (3D) assessments remain limited. The purpose of this retrospective study was to evaluate changes quantitatively in acetabular coverage following modified Spitzy shelf acetabuloplasty using 3D models reconstructed from computed tomography (CT) images. We retrospectively analyzed 11 hips in 11 patients who underwent staged bilateral modified Spitzy shelf acetabuloplasty. Preoperative and postoperative CT data were used to construct 3D pelvic models, which were registered using anatomical landmarks. Bone graft dimensions, insertion angle, and placement location were evaluated. Acetabular sector angles (ASA), representing circumferential coverage of the femoral head, were measured at 15° intervals on the functional pelvic plane and the anterior pelvic plane. The mean bone graft dimensions were 26.3 ± 3 mm (anteroposterior length) and 12.7 ± 2.7 mm (mediolateral length), providing coverage of 49.5° ± 9.1°. Postoperative ASA increased significantly from 34.5° to 60° on the functional pelvic plane and from 0° to 45° on the anterior pelvic plane (both p < 0.05). 3D analysis demonstrated that modified Spitzy shelf acetabuloplasty effectively enhanced anterosuperior acetabular bony coverage. Although this is a report of a few cases (11 hips), the above findings highlight the value of 3D evaluation in identifying postoperative changes that may not be detected using conventional 2D assessments. Also, further research analyzing the three-dimensional bone graft model revealed in this study may help inform the development of a more ideal biomimetic approach, not only in terms of shape but also function. Full article

Emerging evidence highlights the critical role of corneal nerves in the pathophysiology of dry eye disease (DED) and other related ocular surface disorders (OSDs). These conditions increasingly demonstrate neuropathic and neurotrophic components, wherein alterations in corneal nerve morphology and function contribute to symptomatology and disease progression. Recent advances in imaging and diagnostic modalities have enabled detailed, in vivo evaluation of corneal nerve architecture and sensory function, offering novel insights into underlying mechanisms and therapeutic responses. This review comprehensively examines current and emerging technologies for corneal nerve assessment, both structural and functional. The structural methods include in vivo confocal microscopy (IVCM), optical coherence tomography (OCT)-based nerve imaging (e.g., micro-OCT), and emerging technologies like multiphoton microscopy. The functional methods of corneal nerve assessment include advanced esthesiometers, quantitative sensory testing (QST), and functional magnetic resonance imaging (fMRI). The emerging technologies also include AI-driven analytical platforms that can be applied to both structural and functional methods. These various nerve assessment modalities can aid in delineating DED subtypes, selecting targeted treatments, monitoring nerve regeneration, and predicting treatment outcomes. By integrating structural and functional assessments, these technologies are reshaping the diagnosis, phenotyping, and management of DED and other related OSDs, paving the way for personalized therapeutic approaches. Full article

Table tennis has increasingly been adopted as a tool to promote physical and mental health, yet evidence on its outcomes and implementation remains scattered. This study conducted a rapid scoping review to summarise available research on the health outcomes of table tennis within recreational or non-elite settings and identify how table tennis-for-health activities are structured and delivered. Peer-reviewed articles in English were included when they focused the outcomes of table tennis participation on health in community or social settings. Searches across two multidisciplinary databases, complemented by reference screening, led to 17 studies published between 2010 and 2025 being included. Studies were then charted for their methodological, intervention and outcome characteristics. Most studies employed quantitative methods, with experimental or controlled designs predominating, and targeted children, adolescents, older adults, and individuals with conditions such as ADHD or Parkinson’s disease. Across various settings, table tennis was associated with improvements in physical fitness, balance, agility, and body composition, alongside cognitive benefits such as enhanced executive functioning and visual–perceptual skills. Psychological and social outcomes, including improved self-efficacy, emotional regulation, cooperation and social interaction, were also reported. Though no formal quality assessment was conducted, there are clear methodological limitations, including small sample sizes, geographic and gender imbalances, and limited reporting on intervention characteristics that restrict the strength and generalisability of the findings. Overall, this review provides a starting point for trainers and health professionals in the area, presenting promising but preliminary evidence for table tennis as a health-enhancing activity and highlighting the need for more rigorous and comprehensive evaluation. Full article

Background: Robot-assisted partial nephrectomy (RAPN) can be done using either a three-arm or four-arm configuration. However, the evidence comparing the perioperative, functional, and oncological outcomes between these two approaches is inconsistent. Therefore, we aimed to quantitatively compare the outcomes of three-arm versus four-arm RAPN. Methods: A comprehensive search of multiple databases, including PubMed, Embase, Scopus, Web of Science, and Cochrane, was conducted, adhering to the PRISMA guidelines. Studies comparing three-arm and four-arm RAPN were included. Continuous outcomes were assessed using mean differences (MD), and dichotomous outcomes were evaluated using risk ratios (RR). The ROBINS-I tool was used to determine the risk of bias. Results: Five studies that met the selection criteria were included in the final review and analysis. The pooled analyses demonstrated no significant difference in estimated blood loss, warm ischemia time, transfusion rates, overall complications, major complications, or positive surgical margins between the three-arm and four-arm RAPN. Although the initial primary analysis showed a shorter length of stay within the three-arm RAPN technique, the sensitivity analysis did not reflect this finding. Conclusions: The three-arm and four-arm RAPN demonstrated comparable perioperative, functional, and oncologic outcomes. As both techniques appear to be effective, the choice of configuration may be decided by the institutional resources, case complexity, and the surgeon’s preference. Full article

Currently, there is a lack of systematic and quantitative analytical tools for dust emission control in open-pit iron mines. To address this research gap, this study constructs a comprehensive evaluation index system by integrating the Analytic Hierarchy Process (AHP) and the fuzzy comprehensive evaluation (FCE) method. The framework includes four first-level indicators, 12 s-level indicators and 30 third-level indicators. The structural design was informed by laws and regulations, the relevant literature and the principle of dust hierarchical control to ensure the theoretical and empirical basis for the selection of indicators. The evaluation process was based on on-site monitoring data and production ledgers from the open-pit iron mine of the Shuichang Mine, as well as the results of multiple rounds of consultation by the Delphi method group composed of 30 experts in related industries. The results show that the comprehensive score of the mine is 87.14 points, and the overall prevention and control is effective. But the performance of each dimension is unbalanced: fundamental data on production processes scored highest, while individual exposure and protection measures were relatively weak, indicating that the personnel protection link needs to be strengthened. Sensitivity analysis further verified the structural stability of the index system and identified the ventilation and dust removal system as a key driving factor. This framework can provide quantitative decision support for mine managers, enhancing the precision and overall effectiveness of dust control through the accurate identification of weaknesses and optimized resource allocation. Full article

At present, pedestrian navigation systems using smartphones have become common in daily activities. For their ubiquitous, accurate, and reliable services, map information collection is essential for constructing comprehensive spatial databases. Previously, we have developed a map information collection tool to extract building information using Google Maps, optical character recognition (OCR), geolocation, and web scraping with smartphones. However, indoor navigation often suffers from inaccurate localization due to degraded GPS signals inside buildings and Simultaneous Localization and Mapping (SLAM) estimation errors, causing position errors and confusing augmented reality (AR) guidance. In this paper, we present an improved map information collection tool to address this problem. It captures 360° panoramic images to build 3D models, apply photogrammetry-based mesh reconstruction to correct geometry, and georeference point clouds to refine latitude–longitude coordinates. For evaluations, experiments in various indoor scenarios were conducted. The results demonstrate that the proposed method effectively mitigates positional errors with an average drift correction of 3.15 m, calculated via the Haversine formula. Geometric validation using point cloud analysis showed high registration accuracy, which translated to a 100% task completion rate and an average navigation time of 124.5 s among participants. Furthermore, usability testing using the System Usability Scale (SUS) yielded an average score of 96.5, categorizing the user interface as ’Best Imaginable’. These quantitative findings substantiate that the integration of 360° imaging and photogrammetric correction significantly enhances navigation reliability and user satisfaction compared with previous sensor fusion approaches. Full article

This study investigates the physical and cyber-physical resilience of smart grids with a high share of renewable energy sources (RESs) dominated by permanent magnet synchronous generators (PMSGs). The originality of this work lies in the development and unified evaluation of five integrated control strategies, the PLL with grid following, VSG with grid shaping, VSG+BESS, VSG+STATCOM, and VSG+BESS+STATCOM, implemented within a coherent simulation framework based on Python. Unlike previous works that analyze these methods in isolation, this study provides a comprehensive quantitative comparison of their dynamic characteristics, including frequency root mean square deviation, maximum deviation, and composite resilience index (RI). To extend the analysis beyond static conditions, a multi-generator (multi-PMSG) scenario with heterogeneous inertia constants and variable load profiles is introduced. This dynamic model allows the evaluation of natural inertia diversity and the effects of inter-generator coupling compared to the synthetic inertia emulation provided by VSG-based control. The combined VSG+BESS+STATCOM configuration achieves the highest synthetic resilience, improving frequency and voltage stability by up to 15%, while the multi-PMSG system demonstrates comparable or even higher RI values due to its inherent mechanical inertia and decentralized response behavior. In addition, a cyber-physical scenario is included to evaluate the effect of communication delays and false data injection (FDI) on VSG frequency control. The results show that a communication delay of 50 ms reduces RI by approximately 0.2%, confirming that even minor cyber disturbances can affect synchronization and transient recovery. However, hybrid control architectures with local energy buffering (BESS) show superior resilience under such conditions. The main technical contribution of this work is the establishment of an integrated analytical and simulation framework that enables the joint assessment of synthetic, natural, and cyber-physical resilience in converter-dominated smart grids. This framework provides a unified basis for the analysis of dynamic stability, hybrid control interaction, and the impact of cyber uncertainty, thereby supporting the design of low-inertia, resilient, and secure next-generation power systems. Full article

Background: Radon exposure has been recognised as a risk factor for developing lung cancer and other health issues. The mutagenic changes associated with long-term radon exposure take 10–30 years to manifest, which may lead to a lower observed incidence of lung cancer in children. Children are more vulnerable to radon exposure and its effects due to their smaller lung capacity and faster breathing rates, resulting in greater radon inhalation. Objective: The aim of the study is to present current evidence on the association between radon exposure and health effects among children. Methodology: We conducted a systematic review of the available literature on radon exposure and its health impacts, focusing on children. A preliminary literature scoping was conducted in CINAHL, PubMed, Google Scholar, and ScienceDirect. Some of the search terms included: “children” OR “health” OR “implications” OR “radon” OR “exposure”. Subsequently, a comprehensive search was conducted, covering quantitative studies in EBSCOhost across all selected databases. The review adhered to the 27-item PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) checklist. The quality of the evidence gathered was assessed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) tool. The study was registered with PROSPERO under the ID: CRD420251269394. The review analysed 26 studies, all published between 1994 and 2025. Results: The incidence of lung cancer was projected to increase with childhood radon exposure, with statistical significance (OR per radon 100 Bq/m³ = 1.16; 1.05–1.31). Certain biological markers were associated with childhood long-term radon exposure: IL-5 (13.4%; 95% CI: 0.4–2.8; p = 0.044). Conclusions: Childhood radon exposure, although rarely enough to cause overt malignancy, contributes cumulatively to lifetime lung cancer risk and causes detectable biological markers. Full article

To address the technical challenge where traditional high-pressure, large-flow emulsion pump stations cannot adapt to the drastic flow rate changes in hydraulic supports due to the fixed displacement of their quantitative pumps—leading to frequent system unloading, severe impacts, and damage—this study proposes an intelligent flow control method based on the digital flow distribution principle for actively perceiving and matching support demands. Building on this method, a compact, electro-hydraulically separated prototype with stepless flow regulation was developed. The system integrates high-speed switching solenoid valves, a piston push rod, a plunger pump, sensors, and a controller. By monitoring piston position in real time, the controller employs an optimized combined regulation strategy that integrates adjustable duty cycles across single, dual, and multiple cycles. This dynamically adjusts the switching timing of the pilot solenoid valve, thereby precisely controlling the closure of the inlet valve. As a result, part of the fluid can return to the suction line during the compression phase, fundamentally achieving accurate and smooth matching between the pump output flow and support demand, while significantly reducing system fluctuations and impacts. This research adopts a combined approach of co-simulation and experimental validation to deeply investigate the dynamic coupling relationship between the piston’s extreme position and delayed valve closure. It further establishes a comprehensive dynamic coupling model covering the response of the pilot valve, actuator motion, and backflow control characteristics. By analyzing key parameters such as reset spring stiffness, piston cylinder diameter, and actuator load, the system reliability is optimized. Evaluation of the backflow strategy and delay phase verifies the effectiveness of the multi-mode composite regulation strategy based on digital displacement pump technology, which extends the effective flow range of the pump to 20–100% of its rated flow. Experimental results show that the system achieves a flow regulation range of 83% under load and 57% without load, with energy efficiency improved by 15–20% due to a significant reduction in overflow losses. Compared with traditional unloading methods, this approach demonstrates markedly higher control precision and stability, with substantial reductions in both flow root mean square error (53.4 L/min vs. 357.2 L/min) and fluctuation amplitude (±3.5 L/min vs. ±12.8 L/min). The system can intelligently respond to support conditions, providing high pressure with small flow during the lowering stage and low pressure with large flow during the lifting stage, effectively achieving on-demand and precise supply of dynamic flow and pressure. The proposed “demand feedforward–flow coordination” control architecture, the innovative electro-hydraulically separated structure, and the multi-cycle optimized regulation strategy collectively provide a practical and feasible solution for upgrading the fluid supply system in fully mechanized mining faces toward fast response, high energy efficiency, and intelligent operation. Full article

Background: In biosimilar studies, assessing the switchability and interchangeability of biosimilars with their reference products is essential for ensuring reliable clinical evaluation. This study explores optimal trial design strategies incorporating balanced and uniform structures to enhance statistical efficiency in treatment effect under a carryover setting. Methods: Using a linear mixed-effect model for log-transformed responses, we conducted a theoretical variance-based evaluation of all possible two-treatment switching designs in three-period and four-period crossover trials, considering settings with and without carryover effects. A total of 247 distinct three-period designs and 65,519 distinct four-period designs were enumerated and classified according to structural properties, with particular attention to those incorporating a non-switching arm (NSA). Results: SBUwP-NSA (Strongly Balanced Uniform-within-Period designs with a Non-Switching Arm) consistently achieved the minimum variance for treatment effect estimation in both carryover and no-carryover settings. In the absence of carryover effects, UwP-NSA (Uniform-within-Period designs with a Non-Switching Arm) attained equivalent efficiency. In contrast, commonly used dedicated switching designs exhibited substantially lower relative efficiency, achieving as little as 50–55% of the efficiency of the optimal designs, depending on carryover assumptions. Conclusions: This comprehensive theoretical evaluation demonstrates that incorporating strong balance and uniformity properties can yield substantial efficiency gains in switching studies. The results provide quantitative guidance for selecting efficient crossover designs, enabling improved estimation precision while maintaining practical relevance for interchangeability and switching assessments in biosimilar research. Full article

Background: Heart failure (HF) is a systemic syndrome characterized by venous congestion, which critically involves the splanchnic circulation. Conventional assessment methods often lack sensitivity for early or regional congestion. Methods: We conducted a systematic review of studies utilizing contrast-enhanced ultrasound (CEUS) and shear wave elastography (SWE) to evaluate congestion in adult HF patients, synthesizing evidence up to July 2025. Results: The integrated evidence demonstrates that CEUS and SWE provide distinct, complementary quantitative data. CEUS acts as a functional pillar, detecting microvascular congestion through parameters like prolonged hepatic vein transit time. SWE serves as a structural pillar, quantifying tissue stiffness that correlates with central venous pressure, tracks decongestion, and independently predicts adverse outcomes. Together, they differentiate reversible hemodynamic congestion from irreversible fibrotic remodeling across the liver, spleen, kidneys, and heart. Conclusions: Integrating CEUS and SWE into a multi-parametric ultrasound framework provides a comprehensive, bedside assessment of systemic congestion in HF. This approach enhances early detection, improves risk stratification, and offers a potential tool for guiding and monitoring personalized decongestive therapy, representing a significant advancement in holistic HF management. Full article

The rapid development of large language models (LLMs), including ChatGPT, Gemini, and Copilot, has led to their increasing use in health communication and patient education. However, their growing popularity raises important concerns about whether the language they generate aligns with recommended readability standards and patient health literacy levels. This review synthesizes evidence on the readability of medical information generated by chatbots using established linguistic readability indices. A comprehensive search of PubMed, Scopus, Web of Science, and Cochrane Library identified 4209 records, from which 140 studies met the eligibility criteria. Across the included publications, 21 chatbots and 14 readability scales were examined, with the Flesch–Kincaid Grade Level and Flesch Reading Ease being the most frequently applied metrics. The results demonstrated substantial variability in readability across chatbot models; however, most texts corresponded to a secondary or early tertiary reading level, exceeding the commonly recommended 8th-grade level for patient-facing materials. ChatGPT-4, Gemini, and Copilot exhibited more consistent readability patterns, whereas ChatGPT-3.5 and Perplexity produced more linguistically complex content. Notably, DeepSeek-V3 and DeepSeek-R1 generated the most accessible responses. The findings suggest that, despite technological advances, AI-generated medical content remains insufficiently readable for general audiences, posing a potential barrier to equitable health communication. These results underscore the need for readability-aware AI design, standardized evaluation frameworks, and future research integrating quantitative readability metrics with patient-level comprehension outcomes. Full article

In clinical CT imaging, high-density metallic implants often induce severe metal artifacts that obscure critical anatomical structures and degrade image quality, thereby hindering accurate diagnosis. Although deep learning has advanced CT metal artifact reduction (CT-MAR), many methods do not effectively use frequency information, which can limit the recovery of both fine details and overall image structure. To address this limitation, we propose a Hybrid-Frequency-Aware Mixture-of-Experts (HFMoE) network for CT-MAR. The proposed method synergizes the spatial-frequency localization of the wavelet transform with the global spectral representation of the Fourier transform to achieve precise multi-scale modeling of artifact characteristics. Specifically, we design a hybrid-frequency interaction encoder with three specialized branches, incorporating wavelet-domain, Fourier-domain, and cascaded wavelet–Fourier modulation, to distinctively refine local details, global structures, and complex cross-domain features. Then, they are fused via channel attention to yield a comprehensive representation. Furthermore, a Frequency-Aware Mixture-of-Experts (MoE) mechanism is introduced to dynamically route features to specific frequency experts based on the degradation severity, thereby adaptively assigning appropriate receptive fields to handle varying metal artifacts. Evaluations on synthetic (DeepLesion) and clinical (SpineWeb, CLINIC-metal) datasets show that HFMoE outperforms existing methods in both quantitative metrics and visual quality. Our method demonstrates the value of explicit frequency-domain adaptation for CT-MAR and could inform the design of other image restoration tasks. Full article

Lumbar shear forces are increasingly recognized as critical contributors to lower-back injury risk, yet most ergonomic assessment tools—most notably the Revised NIOSH Lifting Equation (RNLE)—do not directly estimate shear loading. This study develops and evaluates a family of linear mixed-effects regression models that statistically predict L4/L5 lumbar shear force exposure using traditional NIOSH lifting parameters combined with posture descriptors extracted from digital human models. A harmonized dataset of 106 peak-shear lifting postures was compiled from five controlled laboratory studies, with lumbar shear forces obtained from validated biomechanical simulations implemented in the Siemens JACK (Siemens software, Plano, TX, USA) platform. Twelve model formulations were examined, varying in fixed-effect structure and hierarchical random effects, to quantify how load magnitude, hand location, sex, and joint posture relate to simulated task-level anterior–posterior shear exposure at the lumbar spine. Across all models, load magnitude and horizontal reach emerged as the strongest and most stable predictors of shear exposure, reflecting their direct mechanical influence on anterior spinal loading. Hip and knee flexion provided substantial additional explanatory power, highlighting the role of whole-body posture strategy in modulating shear demand. Upper-limb posture and coupling quality exhibited minimal or inconsistent effects once load geometry and lower-body posture were accounted for. Random-effects analyses demonstrated that meaningful variability arises from individual movement strategies and task conditions, underscoring the necessity of mixed-effects modeling for representing hierarchical structure in lifting data. Parsimonious models incorporating subject-level random intercepts produced the most stable and interpretable coefficients while maintaining strong goodness-of-fit. Overall, the findings extend the NIOSH framework by identifying posture-dependent determinants of lumbar shear exposure and by demonstrating that simulated shear loading can be reliably predicted using ergonomically accessible task descriptors. The proposed models are intended as statistical predictors of task-level shear exposure that complement—rather than replace—comprehensive biomechanical simulations. This work provides a quantitative foundation for integrating shear-aware metrics into ergonomic risk assessment practices, supporting posture-informed screening of manual material-handling tasks in field and sensor-based applications. Full article