Tag: pubmed

Adv Sci (Weinh). 2026 Jun 22:e76249. doi: 10.1002/advs.76249. Online ahead of print.

ABSTRACT

Phenolic photodissociation at the air-water interface proceeds orders of magnitude faster than in bulk water, yet the structural origins of this acceleration remain insufficiently understood. Here, we present a descriptor-level analysis supporting a dual-control picture, in which phase-dependent photodissociation reflects both πσ*-related dark-state accessibility and the local solvent’s capacity to accommodate transferred electron density. We construct a structure-resolved, statistics-driven framework that bypasses snapshot-level multireference conical-intersection searches by identifying solvent-side dark-state acceptor orbitals {σ_p*}, constructing their energy distribution ε(σ_p*), and linking it to local microenvironment descriptors that quantify coordination saturation and directional constraint. Truncated cluster models prove unreliable because boundary microstates dominate acceptor selection and mask the intrinsic interface-bulk contrast. Periodic slab models remove this bias: the interfacial ε(σ_p*) distribution is shifted lower by approximately 0.7 eV and substantially broadened relative to bulk, predominantly through within-motif energy-window shifts rather than differences in hydrogen-bond topology. Low-coordination, weakly constrained microenvironments correlate systematically with lower ε(σ_p*), and small-system SA-CASSCF diagnostics support the same trend direction. Together, these descriptor-level signatures indicate that the air-water interface favors both dark-state access and transferred-electron stabilization, providing transferable inputs for multiphase photochemical modeling and strategies for tuning interfacial reactivity through control of defect-rich microstate supply.

PMID:42330358 | DOI:10.1002/advs.76249

Br J Radiol. 2026 Jun 22:tqag153. doi: 10.1093/bjr/tqag153. Online ahead of print.

ABSTRACT

OBJECTIVES: To compare the diagnostic performance of Dual-Energy CT (DECT), Diffusion-Weighted MRI (DWI), and Chemical Shift MRI (CSI) in differentiating metastatic from non-metastatic cervical lymph nodes in patients with head and neck cancer, using histopathology as the reference standard.

METHODS: In this prospective cross-sectional study, 38 patients with suspected head and neck malignancy underwent DECT, DWI, and CSI prior to histopathological evaluation. A total of 194 lymph nodes were analysed. Quantitative parameters including DWI- apparent diffusion coefficient (ADC), DECT- normalised iodine concentration (NIC), spectral HU, electron density, effective atomic number and CSI in-out phase ratio were assessed. Diagnostic performance was evaluated using receiver operating characteristic (ROC) analysis, and comparison between modalities was performed using the DeLong test.

RESULTS: Of 194 lymph nodes, 71 were metastatic and 122 were non-metastatic. ADC values were significantly lower in metastatic nodes (p < 0.0001). Dual-energy CT parameters and chemical shift MRI did not show statistically significant differences. ROC analysis demonstrated superior diagnostic performance of ADC compared to other parameters.

CONCLUSION: DWI demonstrates superior diagnostic performance in differentiating metastatic cervical lymph nodes, while DECT and CSI show limited utility. Multiparametric MRI, particularly DWI, should be preferred for nodal characterization in head and neck cancer.

ADVANCES IN KNOWLEDGE: This study provides direct comparative evidence showing that ADC-based DWI is significantly superior to DECT quantitative parameters and CSI for nodal metastasis detection, supporting its role as the primary functional imaging tool.

PMID:42330356 | DOI:10.1093/bjr/tqag153

Rev Esc Enferm USP. 2026 Jun 22;60:e20250573. doi: 10.1590/1980-220X-REEUSP-2025-0573en. eCollection 2026.

ABSTRACT

OBJECTIVE: To assess the knowledge, attitudes, and practices of self-medication and factors associated with this behavior among students in the health field.

METHOD: A cross-sectional study conducted at a public university in Minas Gerais with 237 students. Data collection was carried out using a structured form to obtain sociodemographic variables and information on knowledge, attitudes, and practices regarding self-medication. Descriptive analysis and regression modeling were performed.

RESULTS: The majority (84.8%) reported practicing self-medication and demonstrated a high level of favorability for the behavior; 57.7% demonstrated adequate knowledge. Students in the early grades were more likely to have inadequate knowledge. Favorable attitudes were significantly associated with the 18-20 age group and low income. The highest rates of self-medication were statistically linked to young people and those who self-identified as Black.

CONCLUSION: The high incidence of self-medication and the false perception of technical autonomy highlight the medicalization of life as a response to academic pressures. The results demonstrated vulnerabilities associated with structural inequalities and reinforce the need for institutional interventions focused on medication safety.

PMID:42330354 | DOI:10.1590/1980-220X-REEUSP-2025-0573en

Eur Stroke J. 2026 Jun 2;11(6):aakag066. doi: 10.1093/esj/aakag066.

ABSTRACT

INTRODUCTION: Adverse non-motor outcomes dominate the lived reality of post-stroke recovery, yet remain poorly understood after intravenous thrombolysis (IVT), endovascular thrombectomy (EVT) or both. We characterised the prevalence of outcomes in 13 non-motor domains, stratified by mRS scores, and identified baseline factors associated with adverse outcomes at 6 months follow-up.

METHODS: We conducted a prospective observational sub-study within the Stroke Investigation Group in North and Central London (SIGNAL) registry to characterise non-motor outcomes after IVT, EVT or both. At 6 months, we assessed mRS alongside 13 patient-reported non-motor domains, including neuropsychiatric, fatigue, sleep, social participation, sensory, autonomic and cognitive outcomes. We used unadjusted analysis to estimate prevalence and adjusted multivariate logistic regression to investigate associated baseline factors.

RESULTS: We included 642/646 (99.3%) eligible surviving patients (median age 73 years; 43.5% female; median NIHSS = 5; mRS = 1) treated with IVT, EVT or both. At 6 months, the prevalence of adverse non-motor outcomes across 13 domains ranged from 18% to 56% across all treatment groups. Among patients with a favourable functional outcome (mRS 0-2, n = 409), fatigue (51.3%), sleep disturbance (47.6%) and mood problems (39.6%) were most prevalent. In those with an unfavourable outcome (mRS 3-5, n = 233), dependency in activities of daily living (51.0%), reduced social participation (44.3%) and bladder dysfunction (41.0%) were common. Stroke recurrence, female sex and baseline NIHSS > 5 were significantly associated with multiple adverse non-motor outcomes at 6 months.

CONCLUSION: Despite favourable mRS, a high proportion of patients treated with IVT and/or EVT report adverse non-motor outcomes. Systematic non-motor assessments alongside mRS are needed to accurately capture post-stroke symptom burden and guide person-centred life after stroke care.

PMID:42330319 | DOI:10.1093/esj/aakag066

JMIR Nurs. 2026 Jun 22;9:e82101. doi: 10.2196/82101.

ABSTRACT

BACKGROUND: The rapid advancement of digital technologies, combined with the evolving complexity of health care environments, has introduced a new paradigm in nursing practice. Clinical nurses are now required not only to deliver safe and effective patient care but also to demonstrate competencies in digital literacy and innovation. Among these emerging competencies, digital leadership has become a critical attribute-enabling nurses to lead digital transformation, ensure patient safety, enhance care quality, and support system-level change within health care organizations. Despite its increasing relevance, there is a notable absence of validated measurement tools tailored to assess digital leadership in clinical practice.

OBJECTIVE: This study aimed to develop and psychometrically validate a Digital Leadership Scale for Clinical Nurses (DLS-CN) to systematically evaluate the digital leadership capabilities of nurses working in clinical settings.

METHODS: The scale development process followed a rigorous multistep procedure. Initial items were derived from previous qualitative research involving a literature review and in-depth interviews, complemented by an additional literature review conducted in this study. The content validity of 38 preliminary items was evaluated by 9 experts over 2 rounds. A pilot test was conducted with 30 nurses, followed by cognitive interviews with 5 nurses to refine item clarity and relevance. The final set of items was administered to 446 clinical nurses across various health care institutions. Data were randomly split for exploratory factor analysis and confirmatory factor analysis. Additional analyses were conducted to evaluate item discrimination, convergent validity, and internal consistency using IBM SPSS 25.0 and AMOS 23.0.

RESULTS: The finalized DLS-CN consists of 29 items grouped under four domains: (1) ability to use digital technology, (2) digital safety management, (3) digital collaboration mindset, and (4) organizational influence. These 4 factors explained 56.9% of the total variance. The scale showed strong internal consistency (Cronbach α=0.95). Convergent validity was demonstrated through strong positive correlations with the Nursing Informatics Competency Scale (Pearson correlation coefficient r=0.82; P<.001) and the Self-Leadership Scale (Pearson correlation coefficient r=0.83; P<.001).

CONCLUSIONS: The DLS-CN is a valid and reliable instrument for measuring digital leadership among clinical nurses. It offers a practical tool for educators, administrators, and researchers to assess and enhance digital leadership capabilities-ultimately supporting the digital transformation of health care systems.

PMID:42330315 | DOI:10.2196/82101

Dis Esophagus. 2026 May 12;39(3):doag061. doi: 10.1093/dote/doag061.

ABSTRACT

Anastomotic leak is a serious complication following esophagectomy, contributing to substantial morbidity and mortality. Omental reinforcement of the esophagogastric anastomosis has been proposed as an adjunct to reduce the risk of leakage. This systematic review and meta-analysis evaluated the impact of omental reinforcement following esophagectomy. A PRISMA-guided search of PubMed, Embase, and Web of Science till December 2025 identified comparative studies evaluating esophagectomy with versus without omental reinforcement in adults. The primary outcome was anastomotic leak; secondary outcomes included severe leaks, stricture, and postoperative mortality. Random-effects meta-analysis was performed, with prespecified subgroup and sensitivity analyses. Certainty of evidence was assessed using GRADE. Nine comparative studies involving 2227 patients were included (1170 with reinforcement; 1057 controls), comprising four randomized trials and five observational cohorts. Omental reinforcement significantly reduced anastomotic leak (risk ratio [RR] 0.32, 95% CI 0.23-0.44; I2 = 0%), corresponding to Absolute Risk Reduction (ARR) 7.9% (95% CI 7.1-9.7%) and Number Needed to Treat (NNT) 13 (95% CI 11-15). The effect remained robust across randomized trials, cervical and intrathoracic anastomoses, and both open and minimally invasive/robotic approaches. Severe leaks requiring reoperation were also reduced (RR ≈ 0.22). Stricture formation (RR 0.78) and mortality (RR 0.71) favored reinforcement but were not statistically significant. Certainty of evidence for the primary outcome was moderate. Omental reinforcement substantially reduces the incidence and severity of anastomotic leak following esophagectomy, with consistent benefit across surgical approaches and anastomotic locations. Given its biological rationale, low cost, and favorable safety profile, omental reinforcement (omentoplasty) represents a valuable adjunct in esophagogastric reconstruction.

PMID:42330313 | DOI:10.1093/dote/doag061

Elife. 2026 Jun 22;14:RP106032. doi: 10.7554/eLife.106032.

ABSTRACT

Animals integrate knowledge about how the state of the environment evolves to choose actions that maximise reward. Such goal-directed behaviour – or model-based (MB) reinforcement learning (RL) – can flexibly adapt choice to changes, being thus distinct from simpler habitual – or model-free (MF) RL – strategies. Previous inactivation and neuroimaging work implicates prefrontal cortex (PFC) and the caudate striatal region in MB-RL; however, details are scarce about its implementation at the single-neuron level. Here, we recorded from two PFC regions – the dorsal anterior cingulate cortex (ACC) and dorsolateral PFC (DLPFC), and two striatal regions, caudate and putamen – while two rhesus macaques performed a sequential decision-making (two-step) task in which MB-RL involves knowledge about the statistics of reward and state transitions. All four regions, but particularly the ACC, encoded the rewards received and tracked the probabilistic state transitions that occurred. However, ACC (and to a lesser extent caudate) encoded the key variables of the task – namely the interaction between reward, transition, and choice – which underlies MB decision-making. ACC and caudate neurons also encoded MB-derived estimates of choice values. Moreover, caudate value estimates of the choice options flipped when a rare transition occurred, demonstrating value update based on structural knowledge of the task. The striatal regions were unique (relative to PFC) in encoding the current and previous rewards with opposing polarities, reminiscent of dopaminergic neurons, and indicative of an MF prediction error. Our findings provide a deeper understanding of selective and temporally dissociable neural mechanisms underlying goal-directed behaviour.

PMID:42329682 | DOI:10.7554/eLife.106032

JMIR Form Res. 2026 Jun 22;10:e92323. doi: 10.2196/92323.

ABSTRACT

BACKGROUND: Long COVID is a clinical condition that significantly influences quality of life, productivity, and morbidity in the individuals affected. Much of the research to date has examined medical comorbidities and their associations with long COVID, but there remains a substantial need to understand the social and behavioral factors associated with long COVID.

OBJECTIVE: The objective of this study was to investigate the prevalence and associations of Medical Expenditure Panel Survey (MEPS)-defined long COVID among adults in the United States through the application of the Andersen behavioral model.

METHODS: This cross-sectional database study used the 2022 MEPS dataset. Variables in this analysis were organized according to the Andersen behavioral model. The appropriate weighting variable was used to obtain weighted population-based estimates. Between-group differences (ie, those with MEPS-defined long COVID vs those without) were assessed using chi-square tests, and a multivariable binomial logistic regression model was developed to assess the association between each variable and having MEPS-defined long COVID.

RESULTS: A total of 11,266 individuals were eligible for inclusion in this study. This represented a weighted population of 256,500,584 American adults. Of these 11,266 individuals, 790 (7%; weighted population=18,397,214) had MEPS-defined long COVID, whereas 10,476 (93%; weighted population=238,103,371) did not. Variables identified that were statistically associated with having MEPS-defined long COVID among American adults included 3 predisposing variables (age, sex, and Asian race), 2 enabling variables (marital status and employment status), 3 need variables (number of chronic conditions, health status, and instrumental activity of daily living limitations), 1 personal health practices variable (ever receiving the COVID-19 vaccine), and 1 external environmental variable (south region).

CONCLUSIONS: The prevalence and factors associated with having MEPS-defined long COVID among American adults in this study offer insights to expand our limited understanding of the complex environmental and social factors associated with MEPS-defined long COVID. Further research is required among the long COVID population to better understand and differentiate the causes and consequences of this condition.

PMID:42329675 | DOI:10.2196/92323

Med Phys. 2026 Jul;53(7):e70539. doi: 10.1002/mp.70539.

ABSTRACT

BACKGROUND: Very high energy electron (VHEE) radiotherapy has gained growing interest owing to its potential to reach deep-seated targets and induce FLASH effect. Dose calculations can be performed using analytical or Monte Carlo (MC) methods. Analytical approaches enable rapid dose computation but suffer from limited accuracy in heterogeneous media, whereas MC methods provide high accuracy at the expense of substantial computational cost. Macro Monte Carlo (MMC) is a local-to-global method designed to improve dose calculation efficiency compared to general-purpose MC methods. In MMC, particle transport is based on precalculated transport data generated with general-purpose MC simulations on specific geometries, which is subsequently used to model particle transport over macroscopic steps within the absorber, avoiding computationally expensive microscopic tracking. MMC made it to a standard electron dose calculation engine in a commercial treatment planning system. However, to date, MMC has not been investigated for electron energies above 25 MeV.

PURPOSE: To develop and validate an MMC framework for VHEE radiotherapy that improves dose calculation efficiency while preserving accuracy compared to general-purpose MC methods for electron energies up to 250 MeV.

METHODS: Local simulations were performed using EGSnrc with monoenergetic electron pencil beams incident perpendicularly on spherical geometries (0.2-25 MeV) with radii of 0.5-3 mm, and slab geometries (25-250 MeV) of 2 mm thickness, composed of various materials. Physical quantities including energy loss, lateral displacement, and angular distributions of primary and secondary particles were scored and stored in a database. This database was subsequently used to transport electrons step-by-step in the global simulations, employing slab-based transport at energies ≥25 MeV and switching to spherical geometries for electron energies <25 MeV to account for increased scattering. Energy deposition was scored in a 3D dose grid. MMC dose calculations were validated against EGSnrc for monoenergetic VHEE beams (50-250 MeV) incident on homogeneous and heterogeneous slab phantoms, using pencil beams, parallel spot beams with 1 mm radius, and parallel beams with a field size of 5 × 5 cm². MMC and EGSnrc dose calculations were also performed for two patient CT datasets. Comparisons between MMC and EGSnrc were conducted using integrated depth dose curves, lateral dose profiles, and 3D gamma analysis with 2%/1 mm and 2%/2 mm (global) criteria and a 10% dose threshold. All simulations were performed with statistical uncertainties below 1%, and computation times were recorded.

RESULTS: Integrated depth dose curves and lateral dose profiles agreed within 2% of the maximum dose for all cases considered. For homogeneous and heterogeneous phantoms, MMC dose distributions yielded gamma passing rates above 97% (2%/1 mm) and 99% (2%/2 mm), respectively, compared to EGSnrc. For patient CT datasets, gamma passing rates exceeded 94% (2%/1 mm) and 97% (2%/2 mm). Overall, MMC achieved up to a 27-fold improvement in dose calculation efficiency compared to EGSnrc.

CONCLUSIONS: An MMC framework for VHEE dose calculation was successfully developed and validated for electron energies up to 250 MeV. The method demonstrated good agreement with EGSnrc while providing up to an order-of-magnitude improvement in dose calculation efficiency for the studied cases.

PMID:42329660 | DOI:10.1002/mp.70539

JAMA Netw Open. 2026 Jun 1;9(6):e2619362. doi: 10.1001/jamanetworkopen.2026.19362.

ABSTRACT

IMPORTANCE: Among individuals who meet the diagnostic threshold for type 2 diabetes (T2D), timely initiation of antidiabetic medication (ADM) is essential for lowering long-term cardiovascular risk.

OBJECTIVE: To estimate the association between ADM initiation timing-specifically within 3, 6, or 12 months-and the risk of major adverse cardiovascular events (MACE) and all-cause mortality among individuals newly meeting diagnostic criteria for T2D.

DESIGN, SETTING, AND PARTICIPANTS: This cohort study used target trial emulation to analyze health screening data linked to health insurance claims in Korea (2013-2022) using a clone-censor-weight approach. Participants were adults with newly detected glycated hemoglobin (HbA1c) of 6.5% or greater or fasting plasma glucose of 126 mg/dL or greater. Data analysis was conducted from January to August 2025.

EXPOSURES: Eligible participants were cloned into 4 treatment strategies: ADM initiation within 3, 6, or 12 months or no initiation within 12 months (strategy 1, 2, 3, and control, respectively).

MAIN OUTCOMES AND MEASURES: Five-year absolute risk difference (RD) and risk ratio (RR) of 3-point MACE (stroke, myocardial infarction, and all-cause mortality) and all-cause mortality were estimated using Kaplan-Meier survival probabilities along with 95% CIs from 1000-sample nonparametric bootstrapping.

RESULTS: A total of 23 452 eligible participants (mean [SD] age, 48.2 [11.1] years; 5790 [24.7%] female; mean [SD] HbA1c, 6.9% [1.1%]) were cloned into 4 treatment strategies. Earlier ADM initiation compared with the control showed progressively lower point estimates for 3-point MACE (RR, 0.32; 95% CI, 0.15 to 1.11 for strategy 1; RR, 0.65; 95% CI, 0.41 to 1.29 for strategy 2; RR, 0.93; 95% CI, 0.70 to 1.41 for strategy 3), though it did not achieve statistical significance. Corresponding RDs were -0.97% (95% CI, -1.26% to 0.14%), -0.49% (-0.84% to 0.40%), and -0.10% (-0.44% to 0.57%), respectively. ADM initiation within 3 months yielded significant risk reduction for all-cause mortality compared with the control in both relative (RR, 0.31; 95% CI, 0.10-0.98) and absolute (RD, -0.40%; 95% CI, -0.57% to -0.01%) scales.

CONCLUSIONS AND RELEVANCE: In this cohort study, earlier ADM initiation following the diagnostic threshold for T2D showed a lower risk of mortality, suggesting a potential cardiovascular benefit of early glycemic control; however, given the low event counts and the observational nature of the study, further evaluation in larger studies is warranted before definitive conclusions can be drawn.

PMID:42329653 | DOI:10.1001/jamanetworkopen.2026.19362