Search Results (2,603)

Human digital twins (HDTs) are patient-specific computational models that combine medical imaging, physiological measurements and predictive algorithms. They are moving from an exciting concept to a realistic clinical opportunity. The key question is no longer whether HDTs can be built. The key question is which methods are mature enough to support clinical decisions and what is still missing for routine use. This systematic review maps the methodological landscape of HDTs and highlights practical bottlenecks that limit clinical translation. A PRISMA 2020 guided search of PubMed, Scopus, IEEE Xplore, and the Cochrane Library, covering publications from 2016 to 2026, identified 151 eligible studies. Bibliometric mapping and thematic synthesis were used to characterize research clusters, computational paradigms, and collaboration patterns. Three dominant application streams were identified: cardiovascular HDTs for hemodynamic simulation and procedural planning, musculoskeletal HDTs for biomechanics-driven orthopedic innovation, and neurological HDTs integrating neuroimaging with computational neuroscience. Across domains, the strongest technical trend is the rise in hybrid pipelines that combine physics-based simulation, including finite element and computational fluid dynamics models, with machine learning for segmentation, parameter identification, reduced-order modeling, and faster inference. However, reporting of verification, validation, uncertainty quantification, and explicit context of use remains uneven and prospective clinical evidence is still limited. Overall, the literature shows rapid progress toward clinically credible HDTs, while highlighting the need for scalable computation, standardized credibility pipelines, and workflow-integrated platforms to support safe and reproducible clinical adoption. Full article

Unloading-induced bone loss is a major medical challenge during long-duration human spaceflight, largely driven by suppressed osteoblast-mediated bone formation, and practical countermeasures are needed. Electromagnetic stimulation has shown benefits for bone repair, and its non-invasiveness supports potential space use; however, its single-modality efficacy remains limited. Here, we investigated a combined electromagnetic field (CEMF) integrating a static magnetic field (SMF, 0.4–0.6 T) and a pulsed electromagnetic field (PEMF, 0.38 ± 0.19 mT) to attenuate unloading-related bone loss and examine field-induced mechanical stimulation. Finite-element simulations mapped magnetic flux density, field gradient, induced current density, and Lorentz force density in bone tissue. CEMF was evaluated in vivo in hindlimb unloading (HLU) mice and in vitro in MC3T3-E1 osteoblasts. CEMF improved bone mineral density, trabecular and cortical microarchitecture, and mechanical properties in HLU mice, with increased osteoblast number and mineral apposition rate. In vitro, CEMF promoted osteogenic differentiation and upregulated COL1A1 and RUNX2. Transcriptome analysis suggested activation of ECM–integrin mechanical signaling and the PI3K–AKT pathway. These findings indicate that CEMF-induced multiphysics stimulation enhances osteogenic responses and may serve as a complementary, non-invasive countermeasure for spaceflight-associated bone loss. Full article

The rapid expansion of molecular point-of-care (POC) diagnostics into decentralized settings, including emergency departments, retail pharmacies, and home environments, has shifted the burden of diagnostic performance from laboratory professionals to heterogeneous, often non-expert users. While traditional evaluation frameworks focus on analytical and clinical validity, they often overlook the impact of human-system interactions on real-world reliability. This review introduces the concept of Operational Validity: the ability of a diagnostic system to preserve its intended performance when operated by intended users within the constraints of real-world workflows and environments. To establish a rigorous foundation for this concept, this study provides a critical comparative analysis contrasting Operational Validity against traditional clinical evaluation dimensions (analytical validity, clinical validity, and clinical utility) and post-market metrics. While existing literature outlines isolated usability principles, the significance of this study lies in its synthesis of these fragmented concepts into a formalized, lifecycle-based “Operational Validity” framework that explicitly maps the causal mechanisms connecting initial user interaction directly to downstream clinical outcomes. By synthesizing international standards (IEC 62366-1) alongside the newly finalized May 2026 U.S. Food and Drug Administration (FDA) guidance on the Content of Human Factors Information in Medical Device Marketing Submissions, we examine how human factors engineering (HFE) and usability engineering serve as the methodological foundation for operational validity. We analyze the specific complexities of molecular workflows, identify key parameters of use-related failure modes in pre-analytical and interpretation stages, and detail the mandatory role of iterative formative and final summative usability testing in mitigating these risks. Finally, we propose a lifecycle-based approach to HFE that integrates design, simulated-use validation, and post-market surveillance. Establishing operational validity is essential to ensure that the high analytical sensitivity of molecular POC platforms translates into consistent clinical utility across the full spectrum of decentralized care. Full article

Purpose-aware AI systems are increasingly deployed in safety-critical, multi-agent, and human-facing environments, where they must transform heterogeneous data into timely, explainable, and goal-aligned decisions under uncertainty. Existing architectures often couple perception, reasoning, communication, and security only at the pipeline level. This creates a research gap in unified semantic transformation, purpose-oriented judgment, bounded imperfection handling, and semantic self-protection. To address this gap, this paper proposes a DIKWP+BUG semantic–cognitive reference architecture for artificial-consciousness-oriented computing, without claiming definitive artificial consciousness. The architecture represents cognition through the Data–Information–Knowledge–Wisdom–Purpose (DIKWP) model and uses BUG theory to model bounded approximation, incomplete evidence, and confidence miscalibration in cross-dimensional reasoning. The model is mapped to an Artificial Consciousness Processing Unit (ACPU) reference substrate, an Artificial Consciousness Operating System (ACOS), a DIKWP semantic communication subsystem, and a concept–semantic fused security subsystem. The components are implemented through runtime emulation and evaluated in smart-city governance, autonomous-driving, and medical-triage simulations. Compared with selected baselines, the prototype increased cognitive throughput from $4.5\mathrm{k}$ to $7.8\mathrm{k}$ logged events, reduced perception–action latency from $340\mathrm{ms}$ to $120\mathrm{ms}$, reduced CPU utilization from $95\%$ to $68\%$, lowered smart-city congestion duration by $30\%$, improved emergency response time by approximately $40\%$, achieved 0 collisions versus approximately $2/10$ baseline IoV runs, and improved medical-triage accuracy from $85\%$ to $92\%$. These online-runtime results provide initial feasibility evidence under controlled simulation conditions; they do not include offline model-preparation costs and therefore should not be interpreted as end-to-end lifecycle speedups. Matched-compute ablation, statistical benchmarking, hardware prototyping, and real-world validation remain future work. Full article

Growing demand for greener and more sustainable materials in cultural heritage conservation has prompted the investigation of bio-based alternatives for cleaning applications. This study presents a preliminary evaluation of bacterial nanocellulose (BNC) membranes for the removal of acrylic resins from mural paintings, comparing commercial medical-grade and laboratory-produced BNC with conventional gel systems under simulated application conditions. Both BNC types were characterized in terms of composition, pH, electrical conductivity, Water Holding Capacity and Water Retention Rate. Acetone loading via solvent exchange was assessed by thermogravimetric analysis (TGA), while mechanical behavior before and after solvent loading was evaluated through tensile testing and optical density measurements of the immersion media. The performance of BNCs and reference delivery systems was comparatively assessed in terms of solvent retention, solvent penetration depth into the substrate and residue release. Cleaning performance was investigated through FTIR spectroscopy and semi-quantitative image analysis as indirect indicators of residual resin content, on both mock-up samples and in situ applications. Under the tested conditions, both BNC membranes were compatible with acetone loading and maintained mechanical integrity after solvent exposure. FTIR analysis showed a reduction in the acrylic carbonyl band after treatment with acetone-loaded BNC, which exhibited greater solvent diffusion depth; the underlying removal mechanism, including the possible contribution of solvent-driven redistribution phenomena, remains to be clarified. Differences in reproducibility were observed between medical-grade and laboratory-produced BNC. Overall, the study provides experimental data contributing to the assessment of BNC membranes as bio-based solvent delivery systems for conservation practice. Full article

Although optical fiber-based surface plasmon resonance (SPR) sensors have revolutionized real-time, label-free biosensing, conventional designs suffer from limited multi-analyte detection capabilities. This study utilizes the novel Pi (π)-configured dual SPR optical fiber sensor with two opposing side-polished surfaces, enabling plasmonic excitation for simultaneous multi-analyte detection. The proposed sensor leverages asymmetric metallic thin films such as Ag, Au, Cu, and hybrid configurations (metal + TiO₂) to generate two distinct resonance peaks, significantly enhancing detection versatility. Numerical simulations using the finite element method in COMSOL Multiphysics v6.3 demonstrate that the π-configuration achieves dual resonance dips at 982 nm and 1276 nm for Ag and Ag–TiO₂ films, 1040 nm and 1317 nm for Au and Au–TiO₂ films, and 977 nm and 1249 nm for Cu and Cu–TiO₂ films, respectively, for an analyte refractive index of 1.42. A peak spectral separation >125 nm was achieved for all the sensors for a refractive index range of 1.37–1.42, ensuring that the two dips are resolvable since the change in SPR wavelength is greater than or equal to the full width at half maximum, preserving dual-analyte capability and minimizing potential crosstalk. The results indicate that the π-configured dual SPR sensor utilizing silver and silver–TiO₂ sensing layers had the highest wavelength sensitivity of 12,600 nmRIU⁻¹ and 20,000 nmRIU⁻¹, respectively, slightly outperforming its gold and copper counterpart. The optimized metallic and hybrid nanostructured films ensure dual distinct peaks with high sensitivity, while maximizing refractive index resolution. This work presents the design of a π-configured SPR-based optical fiber sensor utilizing dielectric and multi-metallic thin films, thereby offering a breakthrough in multiplexed biosensing for applications in medical diagnostics, environmental monitoring, and chemical detection. Full article

Introduction: Pedestrians lying on the road—collapsed through medical emergency, intoxication, or displacement following a prior collision—represent a disproportionately lethal and underaddressed category in road traffic safety. Forensic database analyses derived from Japan’s national police records document a fatality rate of 33.0% for collisions involving pedestrians lying on the road, more than double the rate for upright pedestrian collisions. Standard Advanced Driver-Assistance Systems (ADAS) yield a True Positive Rate (TPR) of only 21.4% for detecting pedestrians lying on the road under night conditions—a classification gap of 73.3 percentage points. Methods: In simulation trials, we evaluated the Advanced Falling Object Detection System (AFODS—where “falling object” denotes the low-profile human form at road level, distinguishing the prone pedestrian from the upright postures addressed by conventional ADAS) on a composite dataset of 3200 annotated fall events and 12,000 negative samples (training/validation), with 320 independent controlled simulation trials used for performance evaluation, spanning real-world, forensic-reconstruction, and Total Human Body Model for Safety (THUMS)-validated synthetic scenarios. No physical prototype has been evaluated; all performance data are derived from simulation, and 37.5% of positive samples are synthetically generated. These simulation conditions represent a first feasibility demonstration pending real-world hardware validation. This paper introduces three original contributions absent from prior work: a three-stage quantitative injury-risk model, a formal ISO 26262 Hazard Analysis and Risk Assessment (HARA), and a medicolegal SHAP interpretability framework. The injury-risk model translated detection latency via impact velocity to Head Injury Criterion (HIC) and estimated fatal injury probability (AIS ≥ 5); these model outputs should be interpreted as exploratory estimates pending ATD validation. Reporting follows principles consistent with the TRIPOD statement. Results: Under clear daytime conditions, AFODS demonstrated a TPR of 98.2% (95% CI: 97.4–98.8%) in simulation, decreasing to 95.6% under night dry-road conditions and 89.4% under night rain. The system achieved an AUC of 0.981 and a mean end-to-end latency of 46.5 ms, representing a 76.8 percentage-point improvement in simulation over the monocular RGB baseline (p < 0.001). The injury-risk model projects a reduction in estimated fatal head injury probability from 66.2% (Monte Carlo mean) (no detection, 50 km/h full-speed impact) to 0.7% under AFODS worst-case night/rain conditions, and to ≈0% under clear daytime simulation conditions. Conclusions: A 73.3 percentage-point classification gap places pedestrians lying on the road outside the effective detection envelope of current ADAS, compounded by the systematic exclusion of non-upright postures from regulatory test protocols and benchmark datasets. AFODS supports proof-of-concept feasibility under simulation conditions. Three translational steps are required: prototype validation on real-world hardware using instrumented Anthropomorphic Test Devices (ATDs); prone-posture biomechanical injury modelling using HIC and BrIC criteria; and regulatory extension of pedestrian AEB test standards to non-upright scenarios. Full article

Background: Extracorporeal cardiopulmonary resuscitation (ECPR) can improve outcomes following refractory out-of-hospital cardiac arrest (OHCA); however, access is constrained by geography and resources. This study compared two strategies against the current system in Nara Prefecture, Japan: a two-stage hospital model using chest-pain network hospitals as ECPR-initiation sites, and a prehospital ECPR model using physician-staffed ambulances from two extracorporeal membrane oxygenation (ECMO)-ready hospitals. Methods: A geographic information system (GIS)-based simulation was conducted using emergency medical service (EMS) records of witnessed cardiac-origin OHCA cases (2017–2022). Isochrone analyses estimated areas reachable within a 60 min arrest-to-ECMO target. In the two-stage hospital model, patients located within a 15 min transport radius from chest-pain network hospitals were considered geographically covered. In the prehospital ECPR model, a physician-staffed ambulance was assumed to reach arrest sites within a 25 min travel-time radius from ECMO-ready hospitals. The study outcome was geographic coverage, defined as the proportion of cases within each service area; the two strategies were compared using McNemar’s test for paired proportions. Results: Among 1476 included cases, the coverage rate was as follows: current system, 28.7%; two-stage hospital model, 65.2%; prehospital model, 70.4% (p < 0.001). Certain eastern and southern mountainous regions remained outside both coverage areas. Conclusions: Using real-world EMS data, a mobility-focused prehospital ECPR strategy provided broader potential geographic access without requiring additional fixed hospital infrastructure than expanding hospital-based initiation sites. Optimization of prehospital deployment may represent a geographically feasible approach to expanding ECPR access in mixed urban–rural regions, though operational feasibility and cost-effectiveness require further evaluation. Full article

Telemedicine is increasingly relevant in undergraduate medical education; however, most educational studies emphasize short-term interventions, learner satisfaction, or tele-Objective Structured Clinical Examination performance rather than evidence derived from sustained platform implementation. This multi-cohort longitudinal implementation study evaluated a multiplatform asynchronous telemedicine system integrated into simulation-based gynecology training across three consecutive academic periods at a medical simulation center in Ecuador. Platform-generated teleconsultation records were analyzed at the record level, with repeated records nested within student identifiers when students submitted more than one case. Because the expected number of submissions differed across cohorts as part of planned curricular refinements, cohort-level differences were interpreted descriptively as implementation and process indicators rather than as comparative evidence of learner performance. A total of 205 teleconsultation records from 95 student users were analyzed. Documentation quality was high for current illness documentation (98.5%), physical examination documentation (87.3%), and physiologically plausible vital signs (74.1%). Specialist responses were linked to 196/205 records (95.6%), with complete structured feedback among linked responses. Faculty expert review and learner-reported perceptions provided complementary educational evidence, including perceived usefulness of specialist feedback for gynecology learning. These findings support the feasibility of asynchronous telemedicine-supported simulation workflows and the value of platform-generated data for educational process evaluation, documentation monitoring, and feedback tracking, while not demonstrating individual competence improvement. Full article

This paper reviews hybrid quantum–classical (HQC) architectures for COVID-19-related respiratory medical-image analysis. To address the heterogeneity of existing studies, we propose an architecture-centric taxonomy based on the functional role and placement of the quantum module. Reviewed models are grouped into three archetypes: Archetype A, where quantum circuits act as patch-level quanvolutional preprocessors; Archetype B, where classical feature extractors are coupled with quantum classifier heads; and Archetype C, where quantum circuits generate intermediate features for downstream classical classifiers. Ten peer-reviewed journal studies were selected through a PRISMA-inspired search and analyzed across architecture, diagnostic performance, quantum resource reporting, validation rigor, computational scalability, and deployment feasibility. The review shows that HQC models often report promising binary COVID-19 screening results on CT or chest X-ray images, but multiclass respiratory classification remains less stable. Key limitations include simulator-dominated evaluation, limited external validation, unclear patient-wise splitting, incomplete reporting of qubit counts, circuit depth, and shots, and insufficient comparison with strong classical baselines. Overall, current HQC models should be viewed as exploratory quantum-augmented classical pipelines rather than clinically validated diagnostic systems. No conclusive task-level quantum advantage has yet been demonstrated for COVID-19 medical imaging. Future progress requires standardized benchmarking, transparent quantum-resource reporting, patient-wise and multi-center validation, hardware-aware evaluation, and interpretable hybrid designs compatible with NISQ-era constraints. Full article

Background/Objectives: Medication-related osteonecrosis of the jaw (MRONJ) is a serious complication of bisphosphonate therapy, whose risk is currently assessed through qualitative staging systems that do not integrate pharmacological determinants of cumulative drug exposure. The aim of this study is to present the Bisphosphonate Accumulation Index (BAI), a pharmacologically derived, dimensionless scalar quantifying cumulative exposure to bone-targeted antiresorptive agents by integrating relative potency, administered dose, dosing frequency, route-specific bioavailability, and treatment duration, for use as a pre-procedural assessment tool in patients receiving bisphosphonates. Methods: The BAI combines five pharmacologically grounded parameters from peer-reviewed literature: (1) relative antiresorptive potency referenced to etidronate; (2) dose per administration (mg); (3) monthly dosing frequency; (4) bioavailability route; and (5) years of treatment within the preceding 10-year window. The model includes nine bisphosphonates registered in Italy. Results: The BAI spans approximately five orders of magnitude (from <1000 for short-term oral therapy to >120,000 for monthly intravenous zoledronic acid). Four analyses support the model: sensitivity analysis identifies relative potency as the main source of variance; ecological calibration against nine MRONJ incidence data points yielded r = 0.911 (p = 0.0006, R² = 0.829), indicating that the BAI accounts for approximately 83% of the population-level variance in published incidence rates across heterogeneous regimens (ecological correlation; this does not establish individual-level predictive validity); Monte Carlo simulation on 10,000 patients generated a plausible exposure-strata distribution (6.1% low, 66.6% moderate, 27.3% high); and concordance analysis with a DDD-based metric showed discordance in 7/8 regimens. Conclusions: The BAI is a transparent, reproducible, pharmacologically grounded metric of cumulative antiresorptive exposure addressing the quantitative gap identified in the AAOMS 2022 Position Paper. The BAI measures pharmacological exposure, which is a necessary but insufficient component of MRONJ risk; clinical modifiers such as corticosteroid co-administration, diabetes, renal function, and procedure type are not integrated and must be evaluated independently. The provisional exposure strata reported here (<1000, 1000–10,000, >10,000) are hypothesis-generating and intended solely to guide the design of validation studies; they should not be used as clinical decision rules until prospective patient-level validation has been completed. Full article

In the context of subtropical cities, the slow-moving environment of HOD (Hospital-Oriented Development) faces the dual challenges of spatial fragmentation and an extreme hot and humid climate, which also restricts the outdoor space’s thermal environment performance. Taking the Macau Light Rapid Transit (LRT) Union Hospital Station as an example, this study constructs a “topology-climate” dual quantitative assessment framework that integrates space syntax and parametric universal thermal climate index (UTCI) simulation. In response to the current problems of mixed pedestrian and vehicular traffic and high-intensity heat radiation, a comprehensive intervention strategy combining three-dimensional stitching and spatial optimization is proposed. The results show that: (1) The implantation of three-dimensional corridors improved the spatial integration of the core area of the site by 67.0%, significantly optimizing network connectivity. (2) During the extreme high-temperature period of daytime (9:00–18:00) in summer and autumn, the intervention strategy precisely opened up a continuous low-heat-stress linear shade zone through the synergistic mechanism of building projection shadows, physical shading of connecting corridors, (landscape shading effect, original evaporation removed). (3) The study confirms that landscape-coupled shading layout is the most effective method, reducing potential pedestrian heat exposure across the entire area, while the three-dimensional connecting corridors precisely control the thermal environment of core walkways. Together, these two elements construct a “topology-climate” optimization framework, achieving a synergistic improvement in spatial accessibility and simulated thermal comfort performance under standard meteorological input and quantitatively verifying the optimization effectiveness of the tiered intervention scheme. This study provides a data-driven decision-making basis for optimizing potential walking thermal conditions for vulnerable groups and reshaping the space’s potential to improve microclimate via shading design of medical hub areas and also provides a scientific paradigm for TOD microclimate planning focused on shading-based thermal environment optimization. Full article

This research reports on the properties of oxide-ceramic coatings produced by plasma electrolytic oxidation in novel electrolyte solutions for implantology applications. A series of bioactive calcium-phosphate coatings was synthesized on medical-grade Ti-13Zr-13Nb alloy using the plasma electrolytic oxidation (PEO) method. Novel electrolytes enriched with calcium and phosphorus were developed, enabling the formation of coatings with tailored physicochemical and structural characteristics. A correlation was established between the electrolyte composition and the phase composition, thickness, morphology, porosity, and microhardness of the resulting coatings. The optimum coatings exhibited a Ca/P ratio close to that of natural human bone tissue, homogeneity, a well-developed porous surface topography, and controlled resorption behavior. For the first time, a mechanism of calcium-phosphate coating resorption in a biologically active environment has been proposed. It involves partial dissolution, the formation of apatite-like surface structures, and the subsequent controlled release of Ca and P ions. In vitro testing in simulated body fluid indicated the potential bioactivity of the synthesized coatings. The proposed calcium-phosphate coatings may be considered promising candidates for future implant surface modification. The results obtained are significant for the development of advanced orthopedic and dental implants, including those fabricated using additive manufacturing technologies. Full article

Background: Out-of-hospital cardiac arrest (OHCA) remains a major public health problem. Many patients contact primary health care (PHC) services shortly before cardiac arrest, yet data on PHC staff preparedness to provide guideline-concordant basic life support (BLS) remain limited. This study assessed BLS knowledge and chest compression quality among medical and non-medical PHC staff. Methods: This multicentre cross-sectional simulation-based study was conducted in Poznań and Poznań County, Poland. PHC staff with direct patient contact were included (n = 162). Assessment comprised an author-developed 15-item knowledge test based on European Resuscitation Council guidelines and a two-minute continuous chest compression trial on a Resusci Anne QCPR manikin. Correlations were analysed using Spearman’s rank correlation coefficient, group differences using the Kruskal–Wallis test with Dunn–Bonferroni post hoc comparisons, and predictors using multivariable linear regression. Results: The median BLS knowledge score was 9/15 points (mean 8.74). Mean chest compression depth was 41.3 mm, below the recommended range, with only 23.5% of compressions meeting depth criteria. Correct compression rate was maintained in 30.2% of compressions, and full chest recoil was observed in 55.0% of attempts. Age was negatively correlated with compression rate. In participant-level regression, higher BLS knowledge was associated with better QCPR performance; however, this association was attenuated and no longer statistically significant in mixed-effects models accounting for clustering by practice. Conclusions: PHC staff demonstrated gaps in BLS knowledge and inadequate simulated chest compression performance, particularly regarding compression depth and rate. These findings support recurrent, simulation-based BLS training for all PHC personnel. Full article

This study proposes a novel anti-resonant fiber sensing structure based on a composite “egg-shaped” configuration with surface plasmon resonance (SPR) effect. By designing a novel anti-resonant structure consisting of a semicircle and a semi-ellipse and coating its inner surface with a gold film, the optimal structural parameters are determined through three sets of simulation experiments using temperature sensitivity as the criterion. The optimal sensing structure was applied to the simulated detection and analysis of cancer cells, aiming to provide value and reference for the application of high-sensitivity optical fiber sensor in the field of cancer cell detection. Simulation results show that the proposed sensing structure achieves a maximum temperature sensitivity (TS) of 3.86 nm/°C. For the detection of six different types of cancer cells, the maximum wavelength sensitivity (WS), optimal resolution (R), maximum figure of merit (FOM), maximum signal-to-noise ratio (SNR), and best limit of detection (LOD) reach 12,142.86 nm/RIU, 8.24 × 10⁻⁶, 3035.72 RIU⁻¹, 65.50, and 0.94 nm, respectively. Owing to its unique detection mechanism, the proposed sensing structure exhibits label-free characteristics and demonstrates balanced and excellent performance across all metrics for both temperature and cancer cell detection, showing broad application prospects and great potential in the fields of environmental monitoring and medical prevention and treatment. Full article