Sci Rep. 2026 Apr 22. doi: 10.1038/s41598-026-49505-z. Online ahead of print.
NO ABSTRACT
PMID:42020664 | DOI:10.1038/s41598-026-49505-z
Tag: nevin manimala
Top Curr Chem (Cham). 2026 Apr 22;384(2):17. doi: 10.1007/s41061-026-00552-0.
ABSTRACT
Rare-earth high-entropy oxides (RE-HEOs) represent a distinct class of entropy-stabilized ceramics in which multiple lanthanide cations occupy a common crystallographic sublattice, generating strong chemical disorder, lattice distortion, and complex defect landscapes. Unlike transition-metal-based high-entropy oxides, RE-HEOs are governed by localized 4f electronic states, weak crystal-field coupling, and variable redox chemistry, leading to emergent structural, electronic, magnetic, and optical phenomena that challenge conventional solid-state descriptions. This review provides a physics-oriented analysis of RE-HEOs, focusing on the thermodynamic foundations of configurational entropy stabilization, the interplay between enthalpy, entropy, and kinetic trapping, and the consequences of severe chemical disorder for crystal structure and phase stability. We review how lattice distortion, oxygen vacancy disorder, and cation randomness modify phonon spectra, ionic transport pathways, and electronic structures, with particular emphasis on the role of localized 4f states, defect-induced in-gap levels, and disorder-broadened excitation spectra. Spectroscopic manifestations of disorder including crystal-field relaxation, line broadening, lifetime modification, and energy transfer processes are discussed within a unified framework linking local symmetry breaking to macroscopic response. We further discuss the optoelectronic properties of RE-HEOs, including photoluminescence from intra-4f transitions, upconversion mechanisms, and disorder-induced modifications of radiative lifetimes and quantum efficiency. The application landscape spans both energy conversion (electrocatalysis, solid oxide fuel cells, thermal barrier coatings) and optoelectronic technologies (phosphors, scintillators, optical thermometry, and anti-counterfeiting). Likewise, we assess theoretical and computational approaches, including density functional theory with strong correlation corrections, statistical thermodynamics, and emerging machine-learning models, highlighting their ability and current limitations in capturing disorder-driven physics in multi-component oxides. Finally, we identify open questions central to condensed-matter physics, including the nature of entropy-stabilized metastability, the limits of band theoretical descriptions in highly disordered 4f systems, and the role of configurational entropy in tuning electron-phonon and defect interactions. By consolidating experimental and theoretical insights, this review establishes RE-HEOs as a platform for exploring disorder-dominated solid-state physics beyond conventional crystalline oxides.
PMID:42020651 | DOI:10.1007/s41061-026-00552-0
Environ Monit Assess. 2026 Apr 22;198(5):490. doi: 10.1007/s10661-026-15354-6.
ABSTRACT
China confronts dual environmental challenges: PM2.5-O3 synergistic pollution and mounting CO2 emissions, demanding a strategic shift from single-pollutant control to coordinated management. In response, this study develops a trivariate synergy index (TSI) based on the bivariate synergy index (BSI), integrating PM2.5, O3, and CO2 into a single metric to quantify differences in synergy levels across regions. Using high-resolution remote sensing and 2023 statistical data, we apply an XGBoost-SHAP modeling framework to analyze the seasonal spatio-temporal patterns and drivers of the TSI in 82 key Chinese cities. The results revealed that (1) the BSIPM2.5-O3 was positive only in summer (mean = 0.03), with better conditions along the eastern coast. BSIPM2.5-CO2 was most negative in summer (mean = -2.74), while BSIO3-CO2 shifted from negative in summer to positive in autumn, showing a latitudinal gradient with higher values in the north. (2) Summer TSI showed the weakest antagonism (mean = -1.37) among the four seasons, with values increasing northward and decreasing eastward. Spatially, coastal Bohai regions shifted from positive in spring to negative in summer, while the area surrounding Jiangsu exhibited persistent negative values. (3) The core factors driving TSI variation across all four seasons are temperature, precipitation, and elevation, with their effects exhibiting nonlinear threshold effects. Among socioeconomic factors, GDP exerted a positive influence only after surpassing a critical threshold, whereas increased population density had a negative regulatory effect. Based on the findings, this study offers a seasonal, spatially differentiated reference for synergistic pollution and carbon reduction.
PMID:42020634 | DOI:10.1007/s10661-026-15354-6
Eur Radiol. 2026 Apr 23. doi: 10.1007/s00330-026-12563-y. Online ahead of print.
NO ABSTRACT
PMID:42020625 | DOI:10.1007/s00330-026-12563-y
Eur Radiol. 2026 Apr 23. doi: 10.1007/s00330-026-12543-2. Online ahead of print.
ABSTRACT
OBJECTIVE: To systematically evaluate training sample size adequacy in externally validated machine learning (ML)-based radiomics models published in high-impact journals and quantify the gap between current practice and theoretical minimum requirements.
MATERIALS AND METHODS: This study followed a prespecified and publicly archived protocol. Original research articles published between January 2023 and August 2025 in first quartile (Q1) journals were evaluated. Study selection followed a randomized dynamic screening protocol with a priori power-calculated stopping rule to determine the final cohort. Included studies developed binary prediction models using ML algorithms other than logistic regression and reported external validation. A sample size framework, originally developed for logistic regression, was applied as a conservative lower-bound benchmark. Minimum required sample sizes were calculated based on reported training performance, outcome prevalence, and feature dimensionality.
RESULTS: Of 64 full-text records assessed, 16 (25%) were unassessable due to missing essential parameters (e.g., feature counts) required for sample size estimation. In the assessable final cohort (n = 28), the training sample sizes observed were consistently inadequate, with a median deficit of 195.5 training instances. Only three studies (10.7%) met all criteria for stable prediction model development even under these charitable assumptions. Most studies failed basic heuristics (e.g., 10 events per predictor), with a median events per predictor deficit of 5.8.
CONCLUSION: The vast majority of externally validated radiomics models in high-impact journals are trained on datasets statistically insufficient to support their algorithmic complexity. This systemic data deficit renders models prone to overfitting and instability, potentially explaining the field’s reproducibility crisis.
KEY POINTS: Question Do externally validated machine learning-based radiomics models in high-impact (Q1) journals have sufficient training sample sizes to support their reported model complexity? Findings Nearly 90% of externally validated radiomics models were trained on statistically insufficient datasets, with a median deficit of approximately 200 training instances. Clinical relevance Insufficient training sample sizes undermine model stability and contribute to the reproducibility crisis in radiomics, allowing externally validated models to appear robust while generating unreliable predictions that may misinform clinical decision-making.
PMID:42020624 | DOI:10.1007/s00330-026-12543-2
Eur Radiol. 2026 Apr 22. doi: 10.1007/s00330-026-12555-y. Online ahead of print.
ABSTRACT
OBJECTIVE: Accurate morphometric measurements are crucial for musculoskeletal radiography, but they remain labor-intensive and prone to inter-reader variability. Current artificial intelligence-based solutions often require large annotated training datasets and narrow applications. We present and validate a training-free artificial intelligence framework that automatically derives morphometric measurements across multiple anatomies and radiographic views using universal landmark matching.
MATERIALS AND METHODS: In this retrospective study, 600 standard radiographs of the foot, knee, and shoulder are analyzed. Additionally, a cohort of 240 challenging radiographs containing orthopedic implants was constructed to stress-test the approach. Landmarks from reference radiographs are transferred to unseen radiographs using a pre-trained generalist dense-matching method, and are then used to derive measurements in a post-processing step. The resulting measurements were compared with manual annotations and measurements by two radiologists.
RESULTS: Mean landmark matching error is 2.68 ± 2.70 mm using a single reference radiograph and improves to 2.15 ± 2.38 mm with 40 reference radiographs. Measurement accuracy ranges from 1.81° (I-II metatarsal angle) to 8.65° (congruence angle). Increasing the number of reference images improved measurement accuracy, and mostly approached inter-reader agreement. Performance is mixed on the challenging cohort, demonstrating the limitations and strengths of the approach.
CONCLUSIONS: This anatomy-agnostic framework enables training-free morphometry across multiple regions, with measurement-dependent performance often comparable to inter-reader agreement. Challenging cases highlight specific limitations, motivating the use of quality control and reference-set tuning for deployment. Its minimal setup enables rapid adaptation to new anatomies and measurements, and clinically practical runtimes require GPU inference.
KEY POINTS: Question Can a generalist artificial intelligence framework be used to accurately and automatically perform morphometric measurements across different musculoskeletal radiographs without anatomy-specific training? Findings The training-free approach achieved performance that approaches expert-level agreement for most measurements, while highlighting measurement-specific limitations in challenging cases. Multiple reference radiographs improved results. Clinical relevance This approach automates repetitive morphometric measurements that are prone to inter-reader variability, reducing manual workload while providing reproducible results that can approach expert radiologist performance. Its adaptability and minimal setup enable integration into routine workflows.
PMID:42020623 | DOI:10.1007/s00330-026-12555-y
Eur Radiol. 2026 Apr 22. doi: 10.1007/s00330-026-12554-z. Online ahead of print.
ABSTRACT
OBJECTIVES: To systematically review the available evidence on electrochemotherapy (ECT) in pediatric patients, focusing on indications, treatment parameters, efficacy, and safety.
MATERIALS AND METHODS: A systematic review was conducted in accordance with PRISMA guidelines and registered with PROSPERO (CRD42024575588). MEDLINE, Embase, and Cochrane Library databases were searched. Studies reporting the use of ECT in patients ≤ 18 years were included. Data extraction covered patient demographics, pathologies, electroporation parameters, agents used, and outcomes. Risk of bias was assessed using ROBINS-I.
RESULTS: Out of 1579 screened studies, 15 met the inclusion criteria, reporting at least 127 pediatric patients. Age was provided for 98 patients (pooled mean 8.5 years, range 0-17) and sex for 108 (58 female, 50 male). Two studies described tumors; the remainder reported vascular anomalies (VAs). Reversible electroporation with intralesional or intravenous bleomycin was the most common protocol. Complete response rates for tumors were 97-100%. Pooled volume reductions in VAs ranged from 52% to 100%. Most complications were minor, though serious events occurred, including sciatic nerve injury, disseminated intravascular coagulation, and airway compromise. Methodological quality was low, with small sample sizes and inconsistent reporting of multiple parameters.
CONCLUSION: ECT is in the early stages of development but shows promising efficacy as a treatment for tumors and VAs in children. Preliminary data suggest favorable responses in children, although direct comparison with adults is limited. Further research is essential to establish standardized treatment guidelines, optimize safety, and define the role of ECT within pediatric oncology and interventional radiology. A minimum reporting dataset is proposed.
KEY POINTS: Question Explain the unmet need/clinical problem your study addresses. What is the current evidence regarding indications, efficacy, safety, and treatment parameters of ECT in pediatric patients? Findings Fifteen studies, including 127 children, report high response rates for tumors and VAs, but evidence is limited by small cohorts and heterogeneous reporting. Clinical relevance ECT shows promise as a minimally invasive treatment for selected pediatric tumors and VAs, but standardized protocols and large prospective studies are required before broader clinical adoption in pediatric oncology and interventional radiology.
PMID:42020622 | DOI:10.1007/s00330-026-12554-z
Eur Radiol. 2026 Apr 22. doi: 10.1007/s00330-026-12568-7. Online ahead of print.
NO ABSTRACT
PMID:42020621 | DOI:10.1007/s00330-026-12568-7
Reprod Biomed Online. 2026 Feb 18;52(6):105632. doi: 10.1016/j.rbmo.2026.105632. Online ahead of print.
ABSTRACT
Among the many symbols that appear in the medical literature, few have received as much attention as the letter ‘P’. It is printed in almost every table, discussed in every result section and often treated as the final word in the interpretation of scientific findings. In reality, the P-value is neither over-rated nor under-rated. It is simply misunderstood. It is an important tool, but it is not the main factor that determines the value of a study. What matters is not the number itself, but how we think about it and what it truly represents. This manuscript revisits the ‘value’ of the P-value in reproductive medicine.
PMID:42019099 | DOI:10.1016/j.rbmo.2026.105632
Nurse Educ Today. 2026 Apr 21;164:107125. doi: 10.1016/j.nedt.2026.107125. Online ahead of print.
ABSTRACT
BACKGROUND: Despite extensive efforts, pressure injuries (PIs) remain a critical concern in healthcare quality. Consequently, robust training in PI prevention, assessment and management-tailored to the learning needs of new generations-is imperative for nursing undergraduates to ensure safe, effective and person-centred care delivery.
AIM: To design, implement and evaluate an immersive virtual reality (IVR) training program for PI care, comparing its effects on nursing students’ reflective thinking (RT) and clinical competence against conventional teaching approaches.
DESIGN: Prospective, randomized, double-blind, parallel-group controlled trial.
SETTING: This study was conducted at a university in northern Spain.
PARTICIPANTS: The study convenience sample comprised 93 second-year nursing students. The majority were female (93.4%) with a mean age of 19.3 years. Importantly, 63.4% reported no prior experience with IVR.
METHODS: Six PI nursing care scenarios were designed and developed for IVR using head-mounted displays (Oculus Quest 2), in accordance with internationally recognized standards and evidence-based clinical guidelines. Key variables measured included RT capacity (using Gibbs cycle), knowledge gain, skills performance and usability and satisfaction. Data analysis involved descriptive and parametric statistics (Student’s t-test) and covariance methods to compare outcomes and assess the impact between groups, using SAS v. 9.4.
RESULTS: The intervention group (IVR = 47 students) demonstrated statistically significant improvement in RT compared to the control group (46 students), particularly in the “Emotion” and “Conclusion” questions of Gibbs’ cycle. Skills gain was also significantly higher in the IVR group (p < 0.001). While knowledge gains were comparable (p = 0.202) -indicating no additional advantage of IVR over traditional methods in this specific domain-, the IVR group reported higher satisfaction and usability levels.
CONCLUSIONS: IVR-based applications effectively enhance nursing students’ RT and skills in PI care. This technology offers a valuable educational tool for improving student competence, especially for those with lower initial skill levels, and can be considered an innovative alternative to traditional teaching methods.
PMID:42019094 | DOI:10.1016/j.nedt.2026.107125