To evaluate adherence to the Minimum Reporting Items for Clear Evaluation of Accuracy Reports of Large Language Models in Healthcare (MI-CLEAR-LLM) in radiology and medical imaging studies involving large language models (LLMs). We conducted a cross-sectional audit of original LLM research studies published between January 1 and December 26, 2025, in Q1 journals within the Web of Science "Radiology, Nuclear Medicine, and Medical Imaging" category. PubMed and Scopus were searched to identify eligible studies. A quota-based subsampling strategy, based on journal publication volume, was used to select approximately 100 studies. All four eligible articles from the Korean Journal of Radiology (KJR) were additionally included as a benchmark. Adherence to the 2025 update of MI-CLEAR-LLM was scored through a two-round, consensus-based process: an initial assessment by one reviewer followed by a critical re-evaluation by secondary reviewers, with consensus adjudication by an additional reviewer when needed. Between-journal differences were analyzed with the Kruskal-Wallis test, followed by Dunn post hoc pairwise comparisons with Holm-adjusted P-values. Of 201 eligible studies identified, 102 were finally analyzed after applying the subsampling strategy. Overall adherence to MI-CLEAR-LLM was moderate (mean, 51.2% ± 14.7%; range, 22.2%-84.2%). Adherence was highest for input data type (100%), test-data independence (80.2%), and adaptation strategy (78.1%), and lowest for prompt execution setup (29.4%) and stochasticity management (33.1%). The least frequently reported items were training-data cutoff date (9.8%) and rationale for prompt wording (15.6%). Adherence varied significantly across journals (P = 0.011), with KJR showing the highest mean adherence (72.8% ± 2.7%). Reporting transparency in radiology and medical imaging LLM studies published in 2025 was inconsistent across reporting items and journals, with substantial deficiencies in some reproducibility-critical elements. Broader adoption of reporting standards is essential to improve the reproducibility and interpretability of future accuracy evaluations.
Evaluation of medical education is essential for ensuring the quality of health professional training. However, conventional evaluation approaches often lack objectivity, scalability, and longitudinal assessment capacity. Virtual reality (VR) and artificial intelligence (AI) are increasingly integrated into medical education, yet their application in educational evaluation has not been systematically characterized. To examine research trends, thematic evolution, and emerging directions in VR- and AI-enabled medical education evaluation, a bibliometric analysis was conducted. Publications indexed in the Web of Science Core Collection between January 1, 2015, and December 31, 2025, were retrieved using predefined search terms related to VR, AI, medical education, and evaluation. Eligible English-language articles and reviews were analyzed using CiteSpace (version 6.4.R2). Annual publication and citation trends, country collaboration patterns, and cited journals were assessed. Research themes and frontiers were examined through keyword co-occurrence, clustering, burst detection, and timeline analyses. A total of 695 publications were included. Annual publications and citations increased steadily, with accelerated growth after 2020. The United States, Germany, China, England, and Canada produced the highest number of publications, whereas Belgium, Egypt, Sweden, Singapore, and Switzerland demonstrated high collaboration centrality. Influential cited journals were concentrated in medical education and simulation-based training domains. Keyword analyses identified major themes including surgical education, VR simulation, clinical reasoning, decision support, and residency and undergraduate education. Burst and timeline analyses indicated a progression from early simulation-based skill validation toward learner-centered performance evaluation and, more recently, quality-oriented and curriculum-level assessment. Research on VR- and AI-enabled medical education evaluation has expanded rapidly and evolved from technical skill assessment toward comprehensive, competency-oriented, and quality-focused evaluation. These findings highlight the growing role of emerging technologies in shaping future global medical education evaluation frameworks.
We assess the current use and future potential of micro-computed tomography (micro-CT) in bioarchaeology and paleopathology, identifying areas of underuse and offering recommendations for effective, standardized application. We reviewed articles published 2015-2025 in the International Journal of Paleopathology and International Journal of Osteoarchaeology, supplemented by the Journal of Archaeological Science and Journal of Archaeological Science: Reports (2015-2025) and five frequently cited mummy studies (2010-2025). Articles were categorized by how micro-CT was used (active use versus referencing or recommending it) and by anatomical and pathological focus; reporting of acquisition and reconstruction parameters was also evaluated. Across all journals, micro-CT was used predominantly to image bone, with little application to soft tissue, infectious disease, or malignancy, and parameter reporting was inconsistent across studies. Micro-CT is underused for soft-tissue, infectious, and neoplastic pathologies; its diagnostic value would expand with standardized parameter reporting and closer collaboration with radiologists. This review maps current micro-CT use in paleopathology and offers practical guidance, a reporting checklist, and parameter recommendations to support broader, more reproducible adoption of this potentially diagnostic imaging modality. The review focused on a defined set of journals and a non-exhaustive selection of mummy studies. Future work should develop consensus reporting protocols by tissue type and explore AI-assisted analysis of micro-CT data.
A scoping review of pain research in Nepal12 found evidence of high levels of confirmatory research and substantial knowledge gaps, informing the inclusion of several pain syndromes in the Health Research Priority Areas of Nepal 2019.15 It is timely to investigate how the pain research landscape has changed in Nepal in recent years. This scoping review searched six databases from 1 December 2018-12 June 2024, to explore the current evidence base, since the publication of the previous review and the policy change. A total of 766 articles were identified. Eligibility screening and data extraction were conducted independently by two researchers, and 167 articles were included, totalling 42,842 participants. Most articles were published in Nepal-based journals (83%), specifically institutional journals (72%). The greatest proportion of studies investigated post-procedural pain in hospital-based settings (32%). Overall, the majority investigated acute pain (71%), conducted research in adult-only populations (69%) and included sample sizes of 100 or fewer participants (65%). Only four studies investigated pain in community-based samples, and only one investigated pain associated with occupation-related, heavy load-bearing activities. The preponderance of hospital-based investigations of post-procedural pain algins with the findings from the previous review. Characterising chronic pain (including neuropathic and cancer pain) and investigating pain syndromes in large-scale community-based samples and specific populations (e.g. paediatric and occupational groups) could facilitate effective pain management for all, provide more relevant data rather than extrapolating from other populations and ensure Nepal's contribution to the global academic community. PERSPECTIVE: Following changes to the Health Research Priority Areas of Nepal 2019, there remains an abundance of confirmatory research and substantial knowledge gaps regarding pain research. This article could potentially inform the development of the pain-related research landscape following the amendments to the National Health Research Priorities in Nepal.
Atopic dermatitis (AD) is a chronic and relapsing skin disorder that significantly impairs patients' quality of life. Long-term biologic therapy provides durable efficacy for AD, but raises concerns related to costs, safety, and withdrawal-associated relapse. Traditional Chinese medicine (TCM) has a long history in AD treatment and is usually integrated with biologic treatment to achieve complementary benefits and provide comprehensive care for patients with AD. However, high-quality evidence supporting its real-world efficacy remains limited. This study aims to collect real-world data to evaluate the efficacy and safety of TCM integrated with biologics (TCMIB) in moderate to severe AD, thereby providing methodological insights to obtain high-quality evidence and inform future in-depth research on AD treatment. A total of 3500 patients with moderate to severe AD will be classified into 7 groups based on clinical manifestations and receive 16 weeks of treatment followed by 36 weeks of observation. A reduction of 75% or more in eczema area and severity index score from baseline to week 16 is set as the primary outcome. The secondary outcomes include the eczema area and severity index, body surface area, Investigator's Global Assessment scale, Dermatology Life Quality Index, numerical rating scale for pruritus, Patient-Oriented Eczema Measure, Atopic Dermatitis Control Tool, and TCM syndrome scale. Assessments will be performed at baseline, every 2 weeks until week 16, and then every 4 weeks until week 52. Safety assessments include vital signs, concomitant medications, and adverse events. The SAS software (version 9.4) will be used for data analysis, and a P value of less than .05 will be considered statistically significant. This study has been approved by the institutional review boards of Shanghai Skin Disease Hospital and registered on the International Traditional Medicine Clinical Trial Registry (ITMCTR2025000984). Patient recruitment began in June 2025 and is expected to be completed in January 2028. Data analysis will begin in June 2028. The main results of the study are expected to be submitted for publication in peer-reviewed journals in December 2028. The anticipated findings of this protocol are projected to furnish strong evidence on the efficacy and safety of TCMIB for moderate to severe AD, potentially contributing to the standardization of TCMIB and optimization of clinical practice.
Patient satisfaction is a key indicator of health care quality, and it guides improvement efforts. Although many local studies have examined perioperative patient satisfaction in Ethiopia, there is no comprehensive national synthesis. This gap limits the development of targeted strategies to enhance patient care. The aim of this systematic review and meta-analysis is to determine the pooled prevalence of patient satisfaction with perioperative services in Ethiopia and identify associated factors. This study included all observational research articles on patient satisfaction with perioperative services in Ethiopia. A multidatabase search strategy, incorporating PubMed/MEDLINE, HINARI, Web of Science, Cochrane Library, African Journals Online, and Scopus, was used alongside a gray literature search to identify all Ethiopian studies on perioperative satisfaction available before January 1, 2024. The Newcastle-Ottawa Scale was used to assess the quality of the studies. To assess heterogeneity, subgroup analyses were conducted, and I² statistics were calculated. This study used funnel plots, the Egger test, and a nonparametric trim-and-fill analysis to assess publication bias. A sensitivity analysis was also used to identify any influential studies. Univariate meta-regression examined the association between study-level covariates and perioperative satisfaction. This review included 21 studies comprising 6858 participants. Overall satisfaction with perioperative services was expressed by 5072 participants (73.96%, 95% CI 68.84%-79.08%; I²=96.56%). Factors significantly associated with higher satisfaction included effective postoperative pain management (adjusted odds ratio [AOR] 2.23, 95% CI 1.56-2.90), illiteracy (AOR 3.18, 95% CI 1.23-5.13), primary school education (AOR 6.55, 95% CI 3.61-9.49), local anesthesia use (AOR 2.80, 95% CI 2.03-3.57), and history of prior surgery or anesthesia (AOR 2.76, 95% CI 1.51-4.01). This study found that the pooled prevalence of patient satisfaction with perioperative services in Ethiopia was 73.96% (5072/6858 participants). Postoperative pain management, illiteracy, primary school, local anesthesia, and a history of surgery or anesthesia were significantly associated with patient satisfaction with perioperative services. Health care facilities should focus on providing effective postoperative pain management, clear information about perioperative services, and training for surgical and anesthesia teams to boost patient satisfaction with perioperative services in Ethiopia.
The aim of this pilot study was to explore the feasibility, safety, acceptability, and perceived effects of an immersive, multi-platform distraction (virtual reality/smartphone) intervention on pain and anxiety of children undergoing cancer treatment to improve and refine the intervention. Qualitative data were collected through parent journals and semi-structured, in-person child-parent interviews and analyzed using content analysis to evaluate intervention feasibility and perceived effects on child anxiety and pain management. These data were analyzed through content analysis to evaluate feasibility of the intervention and its perceived effects on the child's anxiety and pain management. Children's and parents' satisfaction were evaluated through surveys. Five children aged from 6 to 17 years hospitalized for cancer treatments and their parents, were recruited (n=10, 5 children, 5 parents). No negative side effects or major logistic issues were reported. Child experiences and parent observations are summarized across three categories: "Effects of the Game Experience," "Logistical Issues," and "Engagement and Motivation." Children and their parents were satisfied with the intervention and mentioned that it had a positive effect on anxiety, pain management, social isolation and children's mood. Results show the potential of a customized avatar in a multiplatform virtual environment for anxiety and pain management of children hospitalized for cancer treatments. Further research is needed with a larger sample size to have a better understanding of the effects of this intervention with this population of patients.
The rapid growth of commercial aviation in Sub-Saharan Africa (SSA), combined with an increasing prevalence of chronic disease among travelers and limited in-flight medical resources, has elevated in-flight medical emergencies as a significant public health concern. Telemedicine presents a transformative opportunity to enhance aeromedical care. However, its adoption within SSA's aviation sector remains critically underdeveloped and underexplored in the literature. This integrative review examines the prospects and challenges of integrating telemedicine into SSA's aviation sector and generates context-specific recommendations to inform policy and practice. We conducted a comprehensive literature search across Scopus, Web of Science, PubMed, African Journals Online and Google Scholar, supplemented by grey literature. Thirty-five sources were synthesized across four analytical domains, with Rogers' Diffusion of Innovations (DOI) theory providing the theoretical framework for the analysis. Six prospect domains were identified: real-time teleconsultations; multimodal biometric data transmission; continuity-of-care; psychosocial benefits for passengers and cabin crew; financial and operational/brand gains all aligning with the DOI attribute of relative advantage. However, these prospects are constrained by persistent challenges including unreliable satellite connectivity, ageing aircraft fleets, fragmented regulatory frameworks, cybersecurity vulnerabilities, financial barriers and inadequate cabin crew training. Recommendations are directed at three stakeholders namely, airline operators, aviation regulators and health policymakers and are anchored in regional realities. The review concludes that telemedicine holds transformative potential for SSA's expanding aviation sector, yet its realization demands harmonized regulatory action, targeted investment and capacity building tailored to the regions' realities. Robust primary research within SSA's aviation health context is urgently needed to move beyond inferential evidence.
The reliable change index (RCI) is a valuable idiographic tool used by clinicians and researchers to evaluate whether individual clients experienced statistically detectable change on a given measure. However, numerous RCI methods exist, and the popular Jacobson and Truax (1991) method is underspecified, raising the potential for inconsistent operationalization across studies. The present study evaluated how the RCI is operationalized in psychology clinical trials and explored how RCI operationalization can influence numerical thresholds. We conducted a methodological scoping review of four clinical psychology journals published from 2020 to 2023 and coded the operationalization of reliable change in psychology clinical trials. We then used descriptive data from a convenience sample of published psychometric studies to illustrate the impact of operationalization on reliable change thresholds. Among 226 clinical trials, 29 (13%) formally assessed reliable change. We identified at least seven distinct operationalizations of the RCI, including five distinct operationalizations of the same formula from Jacobson and Truax (1991). In illustrative examples, differences in the specific operationalization of this formula produced absolute RCI threshold discrepancies as large as 79%, or 1.02 standard deviation units. Operationalization of reliable change is highly inconsistent in clinical trials, which can harm comparability of results across studies. We recommend improved reporting and that clinical trials compute two RCIs. First, the Jacobson & Truax method-using the baseline standard deviation and internal consistency-supports clinician use and improves between-study comparability, though other sources of non-comparability remain. Second, one of several modern methods provides improved within-study RCI evaluation.
To systematically map and synthesize the current evidence on the application of bedside ultrasound in the assessment of gastrointestinal function and the guidance of enteral nutrition in critically ill patients, and to explore its clinical value and future perspectives. PubMed, Web of Science, Embase, Scopus, China National Knowledge Infrastructure (CNKI), Wanfang Database, VIP Database, Chinese Medical Journals Database, and Chinese Biomedical Literature Database were searched from inception to September 4, 2025 for studies on bedside gastrointestinal ultrasound. After removing duplicate literature using EndNote X9 software and the Rayyan online literature screening platform, the articles were independently screened and cross-checked by two researchers. The following data were independently extracted by two researchers: years, country, study type, study population and sample size, grouping criteria and inter-group comparison factors, assessment protocol, ultrasound scanning protocol and results, and outcome indicators. The Newcastle-Ottawa Scale (NOS) was used to evaluate the methodological quality of included case-control studies and cohort studies, and the Cochrane Risk of Bias tool (RoB 2) was used to evaluate the methodological quality of randomized controlled trials. Through comprehensive analysis of the included literature, the application characteristics and clinical significance of bedside ultrasound in gastrointestinal dysfunction assessment and enteral nutrition implementation in critically ill patients were analyzed. Descriptive grouping and visual methods were used to conduct a variability analysis of the included studies. The studies were categorized according to study design and ultrasound assessment methods. A total of 2 023 records were retrieved, and 36 studies were finally included after deduplication and screening. Included studies were published between 2019 and 2025, and comprised 19 randomized controlled trials, 15 case-control studies, and 2 cohort studies. The quality of case-control studies and cohort studies was evaluated as relatively high overall, while bias risks in randomization process and outcome reporting were found in some randomized controlled trials, with overall moderate quality and generally acceptable risk of bias. The main ultrasound assessment protocols were identified as gastric antral cross-sectional area (CSA), gastric antral motility index (MI), superior mesenteric artery (SMA) blood flow parameters, Acute Gastrointestinal Injury Ultrasound Score (AGIUS), Gastrointestinal and Urinary Tract Sonography (GUTS) score, and combined protocols. By comprehensive analysis of included studies, gastric antral CSA was found to accurately reflect gastric emptying and feeding tolerance, and high feasibility was demonstrated in predicting feeding intolerance and feeding achievement rate; gastric antral motility could be quantified by gastric antral MI, but its clinical application was limited by complex operation and fluid management. Intestinal structure and function could be objectively evaluated by AGIUS and GUTS scores, and high sensitivity and specificity in predicting 28-day mortality were demonstrated by AGIUS score≥2. Gastrointestinal structure, motility, and perfusion status could be comprehensively reflected by the gastric antral CSA combined with intestinal ultrasound protocol, and the diagnostic accuracy of acute gastrointestinal injury (AGI) and the success rate of enteral nutrition were improved. As a noninvasive and repeatable assessment tool, bedside ultrasound provides valuable support for gastrointestinal monitoring and nutritional management in critically ill patients. However, the current body of evidence still has issues such as inconsistency in parameter selection, lack of standardization in measurement methods, and variability in operational procedures. Future multicenter, large-scale studies are warranted to establish unified assessment frameworks and enable precise and dynamic gastrointestinal management.
Research on scoliosis and osteoporosis has increased steadily, but the research landscape and thematic evolution of this field remain incompletely characterized. This study aimed to provide a bibliometric mapping review of publication trends, collaboration patterns, research hotspots, and emerging directions in this interdisciplinary area. A bibliometric mapping review of published literature was conducted using the Web of Science Core Collection (WOSCC) and Scopus. Relevant publications published between January 1, 2006, and December 31, 2025, were identified. Bibliometrix, CiteSpace, and VOSviewer were used to analyze collaboration networks, keyword co-occurrence, burst references, and thematic evolution. A total of 1,289 records were identified, and 1,013 publications were included after deduplication, including 810 articles and 203 reviews. Annual publication output increased steadily from 2006 to 2025, with an R2 of 0.97 in the merged dataset, whereas mean total citations per article showed an overall downward trend. The United States and China were the leading contributing countries/regions, and the University of California was the most productive institution. European Spine Journal and Spine were the leading source journals. Keyword and thematic analyses highlighted adult spinal deformity, spine surgery, bone quality assessment, and mechanical complications as major recent topics. Research on scoliosis and osteoporosis has expanded substantially over the past 2 decades and has become an increasingly multidisciplinary field led primarily by the United States and China. The field has shifted toward bone quality assessment, risk stratification, complication prediction, and comprehensive management.
Chronic kidney disease (CKD) is a major global health concern affecting over 850 million people. Among military personnel, CKD poses unique operational and occupational challenges, yet information on awareness, prevention, and service delivery within the Nigerian Navy (NN) is limited. To map existing evidence on CKD knowledge, prevention practices, healthcare services, and policy frameworks relevant to the NN, identify service and evidence gaps, and propose feasible interventions. A scoping review guided by the PRISMA-ScR framework was conducted. Literature published between 2000 and April 2024 was searched across PubMed, African Journals Online, and Google Scholar, complemented by grey literature from the Nigerian Navy Medical Services and the Ministry of Defence. Studies were selected using the Population-Concept-Context (PCC) framework and thematically synthesized across five domains: epidemiology, screening, workforce capacity, dialysis access, and governance. Eight studies met the inclusion criteria. Evidence showed fragmented CKD prevention, low awareness, absence of a renal registry, gaps in workforce capacity, and restricted dialysis services confined to the Naval Medical Centre Victoria Island, and the Nigerian Navy Reference Hospital Ojo. No dedicated CKD or NCD policy exists. Strengthening screening, establishing a Navy CKD registry, and expanding tele-nephrology could enhance early detection, coordination, and operational readiness.
Large language models' (LLMs') rapid evolution and intersection with diverse groups and institutions require up-to-date policies, practices, and behaviors to ensure safe and effective implementation. Because physicians play a central role in care provision and face the dual mandate of embracing innovations and safeguarding patient welfare, understanding physicians' views on LLMs can elucidate the complex interplay of technical, ethical, and professional considerations influencing LLM adoption. This qualitative study aims to employ a descriptive qualitative design to explore how primary care physicians perceive the adoption of LLMs in the context of their clinical practice. We plan to use semi-structured interviews with purposively sampled primary care physicians from British Columbia, Canada. The data collection will draw on the technology adoption behavior framework, a novel model that integrates the most advanced theories of technological uptake. We expect to use thematic analysis drawing on deductive and inductive approaches to describe physicians' perceptions. The multidisciplinary research team will prepare and conduct reflexive memos and discussions to ensure nuanced interpretations. We aim to disseminate the findings through peer-reviewed journals, professional organizations, and policymaker briefings to support the development of policies, practices, and behaviors that support safe and effective LLM integration into health care. The study may provide timely input into relevant policies, practices, and behaviors for policymakers, health professionals, and patients around the use of large language models in health care services.This study uses the technology adoption behavior framework to guide the design of data collection and analysis.The semi-structured interview may reveal the interviewees' internal views but limits the variety of insights gleaned.
Each day, over 100 randomized controlled trials (RCTs) are published, making it impossible for clinicians to stay up-to-date with medical literature. Large language models (LLMs) can identify and summarize emerging clinical evidence and support medical education. We created and prospectively evaluated a newsletter, Trial Files, which leverages an LLM to summarize RCT abstracts relevant to general internal medicine. We created a software tool, called PaperScrape, which leverages the Medline application programming interface (API) to identify trials published in five high-impact journals. Information from each RCT's abstract was extracted, and plain-language summaries were generated using OpenAI's LLM API. We analyzed the accuracy of summaries generated by an LLM (compared to manual review), results of a subscriber survey, and effectiveness of marketing strategies on user growth. From June 2023 to March 2025, 50 newsletters with 3 RCTs each were distributed to 648 subscribers. A subset of 96 RCTs was randomly selected to evaluate reporting accuracy with prompt engineering. The accuracy for reporting study information with prompt engineering, compared to manual review, was 97.1% for study phase, 92.2% for blinding, 85.4% for sample size, 97.9% for patient population, 94.7% for comparison groups, and 92.7% for primary outcome. Forty-three subscribers completed a survey about Trial Files. The mean overall rating was 4.7 out of 5 (5 representing "very good"), and all respondents agreed the newsletter made it easier to keep up-to-date with emerging clinical trials in internal medicine. The most effective strategy for user growth was promotion at a meeting, conference, or education session (6.8 subscribers per day, compared to 0.7 subscribers gained per day on days without promotion, p < 0.0001). LLMs can provide concise, accurate summaries of RCTs, which can help general internists stay up-to-date on recently published trials.
The 2025 Journal Citation Reports (JCR) reveal that the Impact Factor (IF) for the Journal of Korean Neurosurgical Society (JKNS) has risen to 1.9, an increase from 1.7 in 2024. The upward trend in the IF compared to previous years is a highly encouraging development. Although the IF of JKNS has increased, a substantial gap still remains compared to top-ranked neurosurgical journals. The time has come to set clear goals for where JKNS should head next and to explore how to reach them. While maintaining our existing strategies, we aim to consider actionable approaches to advance to the next level.
Chronic urticaria is a common mast-cell-driven inflammatory disorder characterized by recurrent wheals, angioedema, or both. Angioedema is associated with higher disease burden, impaired quality of life, and greater difficulty in clinical assessment, yet the overall research structure of chronic urticaria in the context of angioedema has not been systematically mapped. Publications were retrieved from the Web of Science Core Collection on July 14, 2026. English-language Articles and Reviews published between 1947 and 2026 were included after independent screening by two researchers, with disagreements resolved by a third researcher. Bibliometrix, VOSviewer, CiteSpace, Scimago Graphica, and GraphPad Prism were used to analyze annual output, countries, institutions, authors, journals, co-cited references, and keyword evolution. A total of 881 publications were included. Annual output increased over time, with faster growth after 2014. The United States ranked first in productivity, Germany had the highest citation count and total link strength, and Charité - Universitätsmedizin Berlin was the leading institution. The knowledge base was concentrated in mast cell biology, autoimmune mechanisms, anti-IgE therapy, and patient-reported outcomes. Keyword analysis showed a shift from early immune plausibility and idiopathic descriptions toward disease standardization, quality of life, and targeted therapy, including omalizumab and newer targeted treatments. Angioedema remained a high-frequency term and was repeatedly linked to disease burden, assessment, and treatment. The literature addressing both chronic urticaria and angioedema showed increasing emphasis on structured clinical assessment, mast-cell and autoimmune mechanisms, patient-reported outcomes, biomarker-oriented stratification, and targeted treatment. Future research should broaden international participation and evaluate clinically useful biomarkers and patient-centered outcomes across diverse populations.
Epidermal growth factor receptor (EGFR) mutation status plays a critical role in guiding targeted therapy for non-small cell lung cancer (NSCLC). However, molecular testing in patients with stage IA NSCLC may be limited by insufficient tissue availability, procedural invasiveness, and resource constraints. Therefore, developing a non-invasive approach for EGFR mutation prediction is of substantial clinical interest. This study aimed to develop a computed tomography (CT) radiomics based model integrating clinical variables for non-invasive prediction of EGFR mutation status in stage IA NSCLC patients. A total of 375 patients with stage IA NSCLC who underwent pre-treatment chest CT and EGFR mutation testing were retrospectively enrolled. Tumor volumes of interest (VOIs) were manually segmented on CT images, and radiomic features were extracted using the pyradiomics package. Clinical and radiomic features were selected through a feature selection pipeline, and multiple machine learning algorithms were evaluated for EGFR mutation prediction. Model performance was assessed using the Area Under Curve (AUC). Predictive performance varied across feature selection strategies and machine learning algorithms. Among all evaluated combinations, the Linear Regression (LR) model built using the Least Absolute Shrinkage and Selection Operator (LASSO)-30 feature set achieved the best performance, with a test-set AUC of 0.745. In this model, CT radiomic features served as the primary predictive component, while selected clinical variables provided complementary information and modestly improved predictive performance. These findings support the value of integrating radiomic and clinical features for non-invasive EGFR mutation prediction in early-stage NSCLC. A CT radiomics based model demonstrated only moderate performance for the non-invasive prediction of EGFR mutation status in patients with stage IA NSCLC. When clinical variables were incorporated, predictive performance improved, suggesting that clinical features provide complementary information beyond radiomics alone. The combined model highlights the added value of integrating CT-derived radiomics with clinical data for more accurate individualized molecular assessment, particularly when tissue-based genotyping is unavailable or limited.
The Mediterranean population of tomato leaf curl New Delhi virus (ToLCNDV-ES) is characterized by a high genetic uniformity, distinguishing it from its Asian counterparts. ToLCNDV-ES is thought to have a monophyletic origin, likely resulting from a single recombination event, prior to its spread throughout the Mediterranean region. Following its first detection in southeastern France in 2020, ToLCNDV-ES re-emerged in France in 2022. Our analysis based on advanced long-read sequencing, circular DNA profiling, and phylogeny indicates both local persistence of French ToLCNDV-ES and multiple independent introduction events. Signatures of positive selection were identified in French ToLCNDV-ES populations, whereas no clear evidence of recombination was found. Bayesian time-structured phylogenetic analyses suggest that introductions in France occurred between 2018 and 2021 from the major ToLCNDV-ES clade, while several Italian ToLCNDV-ES isolates diverged prior to the virus introduction in the Mediterranean basin. Overall, this study demonstrates the value of an optimized long-read sequencing approach for resolving circular DNA virus diversity, and sheds light on the complex evolutionary history of ToLCNDV-ES in the Mediterranean Basin, particularly in southeastern France.
Emotional labour (EL) has become a serious concern in the modern workplace due to the rapid development of the service-oriented economy. Existing literature reviews of emotional labour studies leave many questions unexplored. This study addresses these questions by conducting a holistic review of 143 high-impact empirical articles published in peer-reviewed journals from APA PsycInfo, EBSCO Academic Search Premier, Scopus, and Web of Science using the TCCM framework (Theory-Context-Characteristics-Methodology). The document search process is visualised with a PRISMA diagram. We point out several future directions for scholars who are interested in emotional labour. For example, emotional labour research needs to transition from cross-sectional designs to multi-wave designs. Most importantly, this study serves as a roadmap for scholars to navigate the complexity of emotional labour research and provides practitioners with evidence-based strategies to mitigate the negative influence of emotional labour.
Inflammatory breast cancer represents a rare and aggressive form of locally advanced breast cancer with distinct biological characteristics requiring specialized treatment approaches. Despite its clinical importance, standardized radiotherapy guidelines for inflammatory breast cancer management remain limited, and these patients are often underrepresented in clinical trials. This review aims to provide some practical radiotherapy recommendations for inflammatory breast cancer by integrating data from prospective clinical trials, population studies, and emerging genomic insights. The purpose is to establish clear therapeutic strategies that distinguish between chemosensitive and chemorefractory tumours, optimize dose fractionation and target volume definition, and provide guidance on combination with systemic therapies. These recommendations seek to improve clinical outcomes while avoiding inappropriate therapeutic de-escalation in this high-risk population requiring multidisciplinary expert discussions.