Caring for persons with mental illness can be burdensome and could lead to home-based caregivers experiencing various physical, emotional, and psychological challenges, such as anxiety, depression, and stress. Despite these challenges, studies prioritise the experiences of the mentally ill persons and their immediate families, with less focus on the experiences of the home-based caregivers, especially those in rural areas. Thus, this study sought to explore the experiences of home-based caregivers of people living with chronic mental illness in Ga-Dikgale, Limpopo Province, South Africa. The study used a qualitative research approach and an exploratory case study design. The population included home-based caregivers from Dikgale. A combination of purposive and snowball sampling techniques was used to sample eight (six female and two male) home-based caregivers of family members with chronic mental illness from Ga-Dikgale, Limpopo Province. Data was collected using face-to-face semi-structured interviews and analysed using inductive thematic analysis. Findings revealed that some caregivers are not adequately prepared to care for patients due to a lack of training and knowledge of handling mental health patients. Caregivers were also emotionally burdened, with minimal support from patients' families, the government, and mental health professionals. These caregivers used coping mechanisms such as group discussions, prayer, and support from their friends and families to deal with these challenges. This study recommends a collaborative approach among the Department of Health, NGOs, and community healthcare services to facilitate support for home-based caregivers.
Aortic intramural hematoma (IMH) is a high-risk subtype of acute aortic syndrome (AAS). The presence of ulcer-like projection (ULP) significantly increases the risk of progression to dissection, aneurysm, or rupture. However, conventional computed tomography angiography (CTA) has limited reliability in differentiating small ULP from the surrounding high-density hematoma or coexisting atherosclerotic plaques. This study developed and internally evaluated machine learning (ML) models integrating spectral CT-derived quantitative parameters for ROI-based quantitative classification in IMH patients. Data from 95 IMH patients were retrospectively collected and divided into training and test sets at a 7:3 ratio. Quantitative features, including virtual monochromatic images (VMI), iodine concentration (IC), normalized iodine concentration (NIC), effective atomic number (Zeff), and spectral curve slope (k), were extracted from spectral post-processing and subjected to LASSO regression for feature selection. Eight features (VMI 40 keV, Zeff, IC, NIC, and four spectral curve slopes) were selected to construct six ML models. The random forest (RF) model showed the highest AUC point estimate in this internal test set, with an AUC of 0.889 (95% CI: 0.769-1.000), a sensitivity of 93.7%, and an accuracy of 82.8%. SHAP analysis revealed that Zeff contributed most significantly to predictions, followed by the low-energy spectral curve slope, indicating that the model effectively captures differences in material composition and iodine attenuation characteristics. These findings demonstrate the exploratory internal feasibility of using multiparameter spectral CT-based ML models for ROI-based quantitative classification of ULP in IMH, complementing single-parameter analysis.
Lipid nanoparticle (LNP)-based messenger RNA (mRNA) therapeutics enable in vivo production of diverse protein modalities, but their translation is complicated by multiscale pharmacokinetics encompassing tissue transport, cellular uptake, and intracellular processing. We developed a platform translational whole-body physiologically based pharmacokinetic (PBPK) model to mechanistically characterize the biodistribution and protein expression of intravenously administered mRNA-LNP therapeutics. The model integrates receptor-mediated, saturable tissue infiltration, lymphatic recirculation, hepatic uptake, and explicit intracellular processes including endosomal degradation, mRNA escape, translation, and protein turnover. Parameters were calibrated using comprehensive rat biodistribution data containing both tissue-level mRNA and translated protein measurements, enabling characterization of rapid early tissue deposition and dominant hepatic protein production. Sensitivity analyses identified endosomal degradation, mRNA stability, and translation efficiency as the primary determinants of hepatic protein exposure, whereas increasing tissue influx alone yielded minimal effect. Using fundamental allometric scaling principle, the model was translated from rat to human and evaluated against published clinical plasma mRNA pharmacokinetics of an mRNA-encoded monoclonal antibody. Virtual population simulations reproduced dose-dependent peak timing and clearance across multiple dosing regimens. Cell-type specific simulation analyses further demonstrated the competing roles of Kupffer cells and hepatocytes in shaping liver protein exposure. This whole-body PBPK framework provides a mechanistic and predictive platform to support first-in-human dose selection, to interrogate multilevel determinants of mRNA pharmacokinetics, and to guide rational mRNA-LNP design.
Our investigation focuses on developing and testing a radiomics nomogram based on contrast-enhanced mammography (CEM) and clinical factors to predict ductal carcinoma in situ (DCIS) in breast cancer. A retrospective analysis was performed on 731 breast cancer cases who underwent CEM examination and subsequent surgical treatment with complete pathological results, enrolled from five centers. Radiomics features were derived from both low-energy and recombined CEM images for each patient. The Minimum Redundancy Maximum Relevance (mRMR）and least absolute shrinkage and selection operator (LASSO) methods were used to select radiomics features. The radiomics signature (Rad-score) was calculated as a weighted linear combination of the most discriminative features. The univariate and multivariate logistic regression were used to select the clinical factors. A radiomics nomogram was established by integrating the Rad-score and independent clinical risk factors. The receiver operator characteristic curves (ROCs) and calibration curves were used to assess the performance of the radiomics nomogram. The Rad-score was calculated through the integration of 11 radiomics features. The radiomics nomogram was developed from Rad-score, age, menstrual status and background parenchymal enhancement (BPE) by logistic regression, which showed better predictive performance in both internal and pooled external test sets, with AUCs of 0.889 (95% confidence interval [CI]: 0.847-0.932) and 0.822 (95% CI: 0.630-1.000), respectively. The calibration curves exhibited excellent consistency between predicted and observed probabilities. The radiomics nomogram incorporated with CEM-based radiomics features, age, menstrual status and BPE showed acceptable performance in predicting the ductal carcinoma in situ in breast cancer. As a preliminary exploratory study, our findings require further validation in larger, multi-center external cohorts.
To determine whether ultrasound-based Carotid Plaque‑RADS adds incremental value beyond stenosis degree in distinguishing symptomatic from asymptomatic carotid atherosclerosis. Patients with carotid artery stenosis diagnosed by ultrasound were retrospectively enrolled. Plaque-RADS scores and stenosis degree were independently assessed by two blinded radiologists. Binary logistic regression identified factors associated with symptoms. Model discrimination was evaluated by AUC with DeLong comparison. Incremental value was quantified by continuous NRI and IDI with bootstrap validation. Calibration was assessed using bootstrap-corrected slopes, and decision curve analysis evaluated clinical net benefit. A total of 161 patients were included (mean age 70.99 ± 9.86 years; 73.3% male). Plaque-RADS (OR = 3.51, P = 0.0058), stenosis (OR = 4.12, P = 0.0002), and age (OR = 1.07, P = 0.0053) were independent symptom predictors. Adding Plaque-RADS to stenosis improved AUC from 0.762 to 0.807 (P = 0.039). The combined model (Plaque-RADS, stenosis, age) achieved the highest AUC (0.838), though the gain over the model (stenosis plus age) was not significant (P = 0.080). All models showed good calibration (slopes 0.951-0.999). Adding Plaque-RADS to stenosis plus age significantly improved reclassification (continuous NRI = 0.432, P = 0.004; IDI = 0.058, P = 0.002). Decision curve analysis showed net benefit at higher thresholds (0.20-0.30), but no added benefit at lower screening thresholds. Ultrasound-based Plaque-RADS provides independent incremental discriminative value beyond stenosis, primarily improving identification of symptomatic patients, supporting its utility as an adjunctive risk stratification tool for clinical decision-making.
BackgroundBronchobiliary fistula (BBF) is a rare but significant complication of hepatic ablation, particularly in tumors adjacent to the diaphragm. With increasing use of thermal ablation, growing literature has emerged characterizing its presentation and management.MethodsWe present a representative case of recurrent BBF after radiofrequency ablation for hepatocellular carcinoma, successfully managed with a multimodal interventional radiology approach. Following PRISMA guidelines, we conducted a systematic review of the literature on BBF after hepatic ablative therapy published between March 2005 and February 2026, identifying 20 eligible articles encompassing 39 cases.ResultsThe pooled analysis revealed a distinct clinical syndrome: subphrenic tumor location (89.7%), delayed presentation at a median of 4-8 weeks post-ablation, and bilioptysis as the hallmark symptom (92.3%). Diagnostic strategies included CT, bronchoscopy, and cholangiography, often used in combination. Multimodal minimally invasive approaches, including percutaneous, endoscopic, and bronchoscopic techniques, account for 87.2% of current management. While interventional radiology-guided embolization achieved overall success in 66.7% of cases in this pooled series, it often required multiple sessions, reflecting the challenging nature of this complication. Based on these findings, we propose a practical treatment algorithm.Conclusionronchobiliary fistula after hepatic ablation follows a recognizable pattern that should prompt early diagnosis. A persistent, multimodal minimally invasive approach can achieve definitive closure in many cases and should generally be considered before proceeding to surgical intervention. The available evidence, however, remains limited to case reports and small series, and recommendations for specific embolization strategies should be interpreted with this in mind.
Disseminating research findings to potential beneficiaries such as study participants, community members, and stakeholders is a critical component of participatory research. While there is general agreement that dissemination is critical, documented examples of comprehensive dissemination activities are few in the literature. We present a concrete example of a multi-level stakeholder dissemination process from a successful HIV self-testing and linkage to treatment and prevention intervention, describe the dissemination framework used to guide activities, document the process required to carry out the dissemination, and provide qualitative observations and feedback from the process. Findings are from direct engagement in discussions with participants, community members, sub-County and County health managers, and the National AIDS & STI Coordinating Program (NASCOP) leadership during the community engagement and dissemination process. Using Stakeholder Theory and Diffusion of Innovations Theory as guides, Stakekeepers (research institutions, local Institutional Review Boards, the National Sexually Transmitted Infection & HIV Control Program), Stakewatchers (County and sub-County Health Management Teams who act as proxies or intermediaries who protect the interests of real stakeholders) and Stakeholders (such as participants and health facilities, i.e.: Beach Management Units, community members and study participants) felt that the engagement and dissemination process improved upon dissemination of research findings to key stakeholders over usual dissemination efforts. The process of engaging real Stakeholders, Stakewatchers and Stakekeepers brings on board both service recipients, policymakers, and implementers of public health interventions and maintained supportive community relationships and positive views of engagement in research. We provide a concrete example, and lessons learned from a successful multi-level research results dissemination process that can serve as a model for future dissemination efforts. The trial was registered at Clinical Trials.gov on February 26, 2021 (registration #NCT04772469).
Efficient genetic engineering of lactic acid bacteria remains technically challenging due to their thick peptidoglycan cell wall, low transformation efficiency, strain-specific restriction-modification systems, and sensitivity to Cas9-induced double-strand breaks. In this study, we adapted an established CRISPR/Cas9 approach for the targeted disruption of plnD, a key negative regulatory gene within the plantaricin quorum-sensing network of Lactiplantibacillus plantarum 8P-A3 through extensive optimization of transformation and genome-editing conditions. The genetically modified strain exhibited upregulation of plnA, plnE, and plnF, accompanied by elevated antimicrobial activity. These findings underscore the feasibility of rationally reconfiguring a quorum-sensing-associated regulatory circuit and provide a practical strategy for successful genetic engineering in L. plantarum for elevated bacteriocin production.
External ventricular drain (EVD) weaning trials assess the ability of patients with nontraumatic subarachnoid hemorrhage (SAH) to maintain normal intracranial pressure (ICP) without external drainage. Early weaning outcome prediction may optimize clinical management. Existing studies rely on intermittent ICP measurements or static electronic health record data, failing to capture dynamic ICP information. We hypothesize that similar mean ICP produces similar pulse morphology under homeostatic conditions, and acute ICP dynamics changes alter this pattern. We retrospectively analyzed 588 patients with SAH with 413 successful and 239 failed EVD weaning attempts. Dominant ICP pulses were extracted, and morphological similarity was quantified between pulse pairs. A reference pulse similarity distribution was established from a random 50% of successful attempts. Kullback-Leibler divergence measured deviations from this reference distribution for remaining attempts. Three machine learning models compared performance using pulse similarity alone versus combined with key clinical features (age, sex, World Federation of Neurological Societies scale, modified Fisher scale). All models showed progressive performance improvement over time in predicting clamp trial result from the time of EVD clamping. Support vector machine achieved superior performance with pulse features alone, reaching F1 score of 0.77 (± 0.07, CI 0.69-0.85), AUC of 0.86 (± 0.05, CI 0.79-0.93), and Brier score of 0.15 (± 0.01, CI 0.13-0.17) at 24 h. Clinical features provided modest improvements at early hours (5-18% AUC increase) with diminishing benefits later. Decision curve analysis revealed incorporating clinical features enhanced clinical utility from 10 h onward, even with modest discriminative ability, while models achieved marked clinical utility at 16-24 h. This study demonstrates that ICP pulse morphological similarity can predict EVD weaning outcomes and reveals the emergence of clinical value beginning 10 h after trial initiation, potentially enabling optimizing patient care in SAH management complicated with obstructive hydrocephalus.
To evaluate diffusion model-based artificial intelligence approaches for generating virtual populations with physiological determinants of drug dosing (PDODD) and pharmacokinetic (PK) profiles. A denoising diffusion probabilistic model (DDPM) was applied to a 31-variable dataset of PDODD covariates (18 continuous, 13 binary) from the National Health and Nutrition Examination Survey and compared to a tabular variational autoencoder (TVAE). For nivolumab PK data (12,000 patients, 13 time points, 5 covariates), sequence-based diffusion model (SDM) and a time-aware diffusion model (TDM) with temporal self-attention were evaluated. The predictive performance of the TDM was evaluated by imputing masked time points. All models were trained and tested on 80%:20% partitions of the data using univariate, bivariate, and multivariate distributional similarity metrics. The diffusion model satisfactorily approximated the univariate distributions of continuous PDODD biomarkers (mean Kolmogorov-Smirnov D-statistic, KSD = 0.014), disease status frequencies (mean absolute error, MAE = 0.31%), and preserved bivariate correlations (MAE = 0.033). DDPM outperformed TVAE for categorical variables (0.31% vs. 1.07% MAE) and correlation (0.033 vs. 0.091 MAE). For nivolumab PK, SDM has KSD of 0.047 and a relative error of 1.36%. TDM accurately imputed missing PK timepoints (KSD = 0.014), reconstructing masked Day 1, Peak concentration (Cmax) Dose-9, and Terminal phase concentrations with MAE of 0.43%, 0.25%, and 0.76%, and correlations ≥ 0.999. Diffusion models demonstrated strong performance in generating cross-sectional PK covariate data and longitudinal PK profiles, capturing complex distributional and temporal dependencies. Diffusion-based approaches provide a flexible and robust framework for virtual simulations in pharmacometrics.
Presbyopia and corneal astigmatism frequently coexist in cataract patients, reducing visual quality and increasing spectacle dependence. Toric trifocal intraocular lenses (IOLs) aim to address both conditions simultaneously. This prospective study evaluated the visual performance, quality, patient satisfaction, and safety profile of the Liberty 677MTY toric IOL, and classified its functional profile based on distance-corrected monocular defocus curve analysis. This prospective, single-center, non-comparative clinical investigation included 28 eligible cataract patients with corneal astigmatism (1.00-6.00 D) who underwent bilateral implantation of the Liberty 677MTY trifocal toric IOL. Uncorrected and distance-corrected visual acuities at all distances, subjective refraction, IOL rotational stability, defocus curves, contrast sensitivity, patient-reported visual function, and safety were reported during a 12-month follow-up period. The Liberty 677MTY IOL demonstrated significant improvements (p < 0.05) in uncorrected and distance-corrected visual acuities and subjective refractive cylinder, with stability over time. IOL alignment was stable through follow-up, with mean signed and absolute rotations of < 2° and < 5°, respectively. Binocular visual acuity defocus curves showed visual acuities better than 0.2 logMAR across the range of + 1.00 to ‑3.50 D. Monocular visual acuity defocus analysis confirmed full range of field smooth (FRoF-Sm) classification of the IOL. Contrast sensitivity defocus curve met acceptance criteria. Based on patient-reported outcomes 89% rated satisfaction as high, and 83% reported mild or no difficulty with visual disturbances. At 12 months, spectacle independence was achieved in 96.3% of patients for far, 81.5% for intermediate, and 92.6% for near vision. Safety analysis revealed one Nd: YAG-treated PCO case (1.61%) and no other IOL-related adverse events. This study provides a detailed evaluation of the Liberty 677MTY trifocal toric IOL, integrating real-life binocular visual experience with comprehensive monocular assessments. The lens demonstrated predictable refractive outcomes, excellent rotational stability, and consistently high-quality vision across all distances, with strong patient satisfaction. Classified as FRoF-Sm by monocular defocus curve analysis, the lens offers continuous functional vision. By integrating monocular and binocular perspectives, these findings offer a clearer understanding of the lens's performance, supporting its use as a safe and effective solution for achieving spectacle independence and enhancing postoperative quality of life.
Single-cell foundation models such as scGPT and Geneformer learn rich representations of gene expression programs, but whether these representations encode gene regulatory relationships beyond expression-level confounds remains unclear. Attention patterns in these models have been shown to capture co-expression rather than direct regulation, leaving open the question of whether deeper representations-particularly the residual stream-contain genuine regulatory information. We systematically investigated residual-stream geometry in scGPT and Geneformer across four tissue contexts from the Tabula Sapiens atlas, evaluating whether geometric proximity between gene vectors provides incremental predictive value for curated TRRUST transcription factor-target edges beyond expression confounds. Under repeated stratified cross-validation, geometric features provided significant incremental signal in kidney and immune settings, validated by label-permutation and geometry-shuffle null controls; centered-cosine similarity, PCA projection and multi-layer bundling recovered comparable signal in lung tissues, and the multi-layer bundle improved every domain (kidney ΔAUROC = + 0.122, immune + 0.042, lung + 0.028, external lung + 0.027; geometry-augmented AUROC 0.60-0.69). The effect was fully robust to leave-TF-out and leave-target-out cross-validation and to harder degree- and expression-matched negative edges, but under the stricter leave-both-out split-no transcription factor and no target shared between folds-it collapsed to near-zero (ΔAUROC at most + 0.003, and not statistically significant in kidney or immune), marking the ceiling of out-of-entity generalization. With a comparable per-layer residual-stream extraction applied to both models, the apparent Geneformer advantage mostly disappeared (small residual gaps remained in three of four domains), indicating it largely reflected representation-construction choices rather than a substantial architectural difference. Asymmetric geometric features predicted regulatory edge orientation (AUROC 0.80-0.90), and the geometric signal added incremental value on top of expression-based gene regulatory network (GRN) inference (GENIE3, co-expression). Foundation model residual streams carry incremental, regulatory-relevant geometric signal that is distributed across layers and that complements expression-based GRN inference for retrospective edge prioritization. The signal is statistical enrichment rather than a stand-alone regulatory classifier: absolute performance is modest and out-of-entity generalization is limited, so its practical role is as an orthogonal evidence channel for edge re-ranking and hypothesis prioritization in multi-evidence frameworks.
The objective was to develop and validate an explainable artificial intelligence (AI)-based multimodal approach for preoperative risk stratification of central lymph node metastasis (CLNM) in papillary thyroid carcinoma (PTC) and to evaluate its role in supporting radiologist decision-making. This multicenter retrospective study enrolled patients with pathologically confirmed PTC from four hospitals. Preoperative two-dimensional ultrasound, strain elastography, shear-wave elastography, and clinical variables were integrated to develop a multimodal predictive model. Model interpretability was achieved using SHapley Additive exPlanations (SHAP) to provide feature-level explanations supporting clinical interpretation. To assess clinical usability, a controlled reader study was conducted in which six radiologists with varying experience independently evaluated cases under three conditions: without AI assistance, with basic AI assistance (probability output only), and with explainable AI assistance (visualized feature-level contributions). Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), and reader performance was assessed using paired statistical comparisons and interreader agreement analysis. A total of 428 patients (mean age, 44 years ± 12; 369 women) with 508 PTC nodules were included, of whom 225 (44.3%) had CLNM. The multimodal model achieved AUCs of 0.975, 0.917, and 0.844 in the training, validation, and external test cohorts, respectively, outperforming single-modality and simplified fusion approaches (p < 0.05). SHAP identified age, texture-derived radiomic features, and elastography-derived stiffness-related features as key contributors. In the reader study, explainable AI assistance significantly improved diagnostic accuracy across all experience levels, increased diagnostic confidence, and raised human-AI agreement to substantial or almost-perfect levels. An explainable AI-based multimodal approach enables accurate preoperative risk stratification of CLNM in PTC and improves radiologist diagnostic performance, with potential to support clinical decision-making within radiology workflows.
To evaluate geographic variation in Medicare fee-for-service (FFS) pituitary surgery provider availability, straight-line distance to care, and community-level sociodemographic correlates across the contiguous United States. We performed a cross-sectional ecological geospatial analysis of 3,007 counties grouped into 40 provider catchment areas during 2018-2022. Qualifying providers were identified in CMS Medicare Physician & Other Practitioners data using a claims-based annual volume criterion for CPT codes 61,546, 61,548, or 62,165. County characteristics were aggregated to catchment areas. Outcomes were population-weighted straight-line distance to the nearest qualifying provider and provider density per 100,000 population. Associations were evaluated at the catchment-area level using univariable linear regression. Sixty-four of 88 observed providers (72.7%) met the claims-based criterion. Mean catchment-area provider density was 0.03 ± 0.03 per 100,000 population, and mean distance was 74.48 ± 33.82 miles. In univariable ecological analyses, longer distance was associated with higher proportions of American Indian/Alaska Native residents and with greater prevalence of cognitive difficulty, hearing impairment, vision difficulty, and depression. Provider density correlated positively with population density and the proportion of households without a vehicle, an urbanicity-related pattern, while Latino residential isolation was associated with lower provider density. Medicare FFS claims demonstrate substantial geographic variation and ecological associations between access measures and community characteristics. These findings neither enumerate the national pituitary surgical workforce nor establish individual-level or causal relationships. They support further evaluation of regional referral networks, transportation support, and telehealth as potential access strategies.
Breast cancer-related lymphedema (BCRL) is a common and debilitating sequela of axillary lymph node dissection (ALND). Although machine learning (ML)-based prediction models have been proposed, few focus exclusively on patients undergoing ALND, and direct comparisons with traditional statistical models remain limited. This study aimed to develop accurate and clinically feasible prediction models for BCRL using supervised ML and multivariable logistic regression. Demographic and clinical data were prospectively collected from women undergoing unilateral ALND for breast cancer at Memorial Sloan Kettering Cancer Center between 2016 and 2024. Supervised ML and multivariable logistic regression models to predict BCRL were trained and internally validated. Model performance was evaluated using area under the receiver operator characteristic curve (AUC), accuracy, sensitivity, specificity, and Brier score. Shapley additive explanations were used for model interpretability. A total of 474 eligible patients were included. BCRL developed in 113 (23.8%) patients at a mean ± standard deviation of 16.6 ± 7.5 months postoperatively. The highest-performing ML model (random forest) achieved an AUC of 0.83, whereas traditional multivariable logistic regression achieved an optimism-corrected AUC of 0.62. Key ML predictors of BCRL on Shapley additive explanations analysis included clinical cancer stage, body mass index, age, and neoadjuvant chemotherapy. ML-based models outperformed traditional logistic regression in predicting BCRL among patients undergoing ALND. These models demonstrate the potential of ML for early BCRL identification and risk stratification but also highlight the difficulties in accurately predicting BCRL development. Further research is needed to improve model predictive performance and facilitate clinical implementation.
Statin optimization in older adults is increasingly relevant within the geroscience framework of cardiovascular ageing. This randomized controlled trial evaluated whether pharmacist-led pharmaceutical care improves lipid outcomes and statin adherence in community-dwelling older adults receiving primary care. A total of 99 patients aged 65 years or older on long-term statin therapy were randomized to usual care or structured pharmacist-led care delivered every 3 months. The primary outcome was change in low-density lipoprotein cholesterol at 6 months. Secondary outcomes included changes in other lipid parameters and dispensing-based adherence assessed by the proportion of days covered. The present analysis represents a pre-specified interim evaluation and was conducted on a per-protocol population with complete 6-month laboratory data. No statistically significant between-group difference in low-density lipoprotein cholesterol reduction was observed (adjusted difference -0.129 mmol/L, p = 0.385). Statin adherence was high and stable in both groups throughout follow-up, with 84-87% of patients meeting adherence thresholds and approximately 75-77% achieving perfect dispensing, consistent with an apparent ceiling effect. Exploratory sex-stratified analyses identified potential differences in lipid responses, but these were not statistically robust. In these highly adherent elderly populations, pharmacist-led pharmaceutical care was not associated with additional short-term improvement in LDL-C or dispensing-based adherence. The findings highlight the importance of baseline adherence when evaluating adherence-focused interventions in older adults.
To explore the status of low-dose CT lung cancer screening (LCS) training practices, identify existing gaps, and define key competencies to be included in LCS educational curricula. As part of the European SOLACE project, a structured cross-sectional survey consisting of 11 closed- and open-ended items, developed based on relevant literature, international guidelines, and expert input to assess LCS current practices and training needs, was administered to a panel of European LCS experts. Participants were invited to individual Zoom interviews (May-November 2025). Data were analyzed using descriptive statistics. Twenty-five LCS experts were interviewed from 14 European countries, including 10 radiologists (40%), 8 pulmonologists (32%), 4 thoracic surgeons (16%), 1 project manager (4%), 1 smoking cessation specialist (4%), and 1 general practitioner (GP) (4%). Reported training activities ranged from established programmes (4/14 countries), to learning initiatives (6/14) and/or planned programmes (4/14). Radiologists (96%), pulmonologists (80%), and GPs (60%) were identified as the main target groups for training. On a 6-point Likert scale (0 = not important, 5 = extremely important), experts indicated limited awareness of training needs as the most relevant gap (mean 2.8 ± 2.2). Key educational areas to be strengthened included management of incidental findings (4.5 ± 0.6) and confident use of guidelines for nodule management (3.8 ± 1.8). Among essential competencies for professionals involved in LCS, the highest-rated were competence in managing incidental findings (4.7 ± 0.6), familiarity with guideline-based nodule management (4.7 ± 0.6), basic knowledge of AI tools (4.5 ± 0.8), and communication with LCS participants (4.5 ± 1.1). The findings suggest a heterogeneous LCS training landscape across European countries and underscore the importance of developing shared European curricula. Key priorities may include strengthening technical skills alongside structured communication training. Education and training of all stakeholders are essential for the successful implementation of LCS programmes. This survey assesses the current status of LCS training practices across Europe, identifies existing gaps, and defines key competencies to inform future curricula for health professionals involved in LCS. The European LCS training landscape is highly heterogeneous, with substantial variability in training activities, target professionals, and delivery modalities.
Frailty is a key determinant of adverse outcomes in older adults. The association between clinical frailty and multidrug-resistant (MDR) positive cultures in hospitalized older adults remains insufficiently defined. Understanding this association may improve early risk stratification and inform infection control strategies in acute care. We conducted a prospective, observational, single-center cohort study in an internal medicine ward. Patients aged ≥ 65 years admitted with clinical suspicion of bacterial infection requiring microbiological testing and antibiotic therapy were eligible. The diagnosis of infection was based on clinical, laboratory, and imaging findings as assessed by the treating physician, regardless of microbiological confirmation. Among 208 eligible patients with confirmed infection, participants were stratified by culture results into negative, non-MDR, and MDR + groups. Frailty was assessed using the Clinical Frailty Scale (CFS) and Primary Care Frailty Index (PC-FI), while comorbidity burden was evaluated with the Cumulative Illness Rating Scale (CIRS). Multinomial logistic regression was used to explore variables associated with MDR-positive culture status. Of the 208 patients, 57% were culture-negative, 29% had non-MDR infections and 14% MDR + . Frailty increased progressively across groups: median CFS was 5, 6, and 6 (p = 0.004), and median PC-FI was 0.20, 0.24, and 0.28 (p = 0.021). The prevalence of frailty rose from 56 to 70% to 83% (CFS > 4; p = 0.015). MDR + patients more frequently required full-time caregiving and had longer hospitalization and antibiotic duration. In multivariable analysis, CFS remained associated with MDR-positive culture status after adjustment for age and comorbidity burden (OR 1.57, 95% CI 1.17-2.11) although residual confounding cannot be excluded. In this selected single-center cohort of hospitalized older adults, clinical frailty was associated with MDR-positive cultures. These findings should be considered hypothesis-generating and should not be interpreted as supporting broader empirical antibiotic therapy based on frailty alone.
Consensus-based recommendations on managing sickle cell disease in pregnancy were recently published in a hematology journal. As this topic is also of great interest to obstetricians and gynecologists, we summarize some of these recommendations, while highlighting the challenges of providing evidence-based medical care to pregnant individuals with sickle cell disease.
Intranasal (IN) naloxone achieves rapid systemic exposure necessary for effective opioid overdose reversal; yet establishing bioequivalence (BE) for fast-acting drug-device combination products remains challenging due to the interplay of formulation attributes, device performance, and nasal physiology. This study developed an in vitro permeation test (IVPT) approach designed to quantitatively relate the nasal permeation behavior of naloxone to its clinical pharmacokinetic (PK) performance through an in vitro-in vivo relationship (IVIVR). Naloxone hydrochloride (Narcan®, 4 mg/0.1 mL) was deposited onto artificial membranes and EpiAirway™ mucociliary tissues using a controlled aerosol-deposition system (VITROCELL® Cloud Alpha 12). Naloxone permeation was assessed under sink conditions using a validated LC-MS/MS method. Cumulative permeation at 20 and 120 min (F₂₀ and F₁₂₀, respectively) was correlated with clinical maximum plasma concentration (Cmax) and area under the curve from time zero to infinity (AUC₀-∞) to construct IVIVR models, supplemented by exploratory point-to-point in vitro-in vivo extrapolation (IVIVE) using Wagner-Nelson deconvolution. Permeation profiles differed by substrate, with the hydrophilic membranes showing higher dissolution rates and EpiAirway™ tissues demonstrating dose-proportional transport despite lower deposited mass. The tissue-based IVIVR models showed strong linearity (R2 > 0.98) and mean prediction errors within accepted limits (≤ 10%), while artificial membranes consistently overpredicted the systemic exposure. IVIVE analysis further supported close temporal agreement with clinical absorption patterns. These findings indicate that a tissue-based IVPT-IVIVR framework may provide a translational tool for relating in vitro permeation behavior to systemic exposure, supporting its utility in formulation development and BE risk assessment of rapidly acting IN naloxone products.