搜索结果：Prioritize

To describe the processes, consensus-building activities, learning and challenges of prioritizing initial programme theories on appropriate nurse staffing models across a multinational research team of academics, trainees and knowledge users from four countries. Realist review involving literature review, multinational stakeholder engagement and prioritization of programme theories. Realist reviews explore what works, for whom and in what contexts, enabling the development and testing of initial programme theories. Data sources included (1) a literature review to identify existing theories on optimal nurse staffing models, (2) input from methodological and health system decision makers experts to identify context-mechanism-outcome configurations and prioritize initial programme theories and (3) feedback from health decision-makers and nursing staff through focus groups to augment and prioritize a final set of initial programme theories for subsequent testing. We summarize the key learnings we gained regarding: (1) effectively communicating the value and unique aspects of realist methodology to team members with varying levels of expertise; (2) achieving a compromise between rigour and relevance in the design of the review itself in working within 'social laboratories' and (3) the logistics of conducting a multinational realist investigation: navigating working remotely, differences in time zones and differences in context and language. Prioritizing initial programme theories on nurse staffing through a multinational realist review is both feasible and valuable. Clear communication, balancing rigour with relevance and managing logistical challenges are essential to producing context-sensitive and evidence-informed staffing models. Developing evidence-informed staffing models requires local context consideration and stakeholder collaboration. This study offers (a) practical insights for nurse leaders and managers on balancing rigour and relevance, (b) effective team communication and (c) navigating logistical challenges in multinational teams to prioritize programme theories for clinical translation to improve patient care and staff wellbeing. Consolidated criteria for reporting qualitative research (COREQ). Health care decision makers, care managers, researchers and academicians were involved.

Biomarker discovery in immunotherapy remains limited by approaches that rely primarily on correlation-based analyses, which often fail to capture the context-dependent and mechanistic nature of tumor immune interactions. Here, we present IMMUNIA, a reasoning-centered framework designed to prioritize immunoregulatory surfaceome genes through structured, interpretable, and multimodel inference. IMMUNIA integrates standardized prompting, literature-grounded context, and consensus reasoning across multiple large language models to evaluate candidate genes along key immunological dimensions, including immunotherapy relevance, inflammation, and NF-κB signaling. Applied to transcriptomic data from prostate cancer, IMMUNIA systematically analyzed 458 immunoglobulin domain-containing surfaceome genes and identified a prioritized set of candidates through multirun, cross-model evaluation. Internal validation using positive and negative control genes demonstrated robust discrimination of immune-relevant targets, while cross-model agreement and low variability across repeated runs supported the stability of the framework. Consensus prioritization recovered established immunoregulatory molecules, including IL1R1, CD276, and B2M, and further highlighted PTPRS, VCAN, and MXRA5 as candidate genes with potential roles in stromal-mediated immune regulation. The biological interpretations presented in this study are grounded in prior literature and reflect expert-level mechanistic reasoning, with IMMUNIA serving to systematically structure and scale this reasoning process. Rather than generating de novo biological claims, this framework enables the integration of existing knowledge into testable hypotheses, providing a transparent and reproducible path from transcriptomic data to mechanistically informed biomarker prioritization. These findings suggest that reasoning-centered artificial intelligence can complement conventional data-driven approaches and support the discovery of candidate immunoregulatory targets within the tumor microenvironment.

Low back pain (LBP) is a leading cause of disability worldwide with limited effective pharmacotherapies. We aimed to identify novel therapeutic candidate targets for LBP through integrative genomics. We employed summary-data-based Mendelian randomization (SMR) with GWAS data from FinnGen (13,178 cases/164,682 controls) and tissue-specific expression quantitative trait loci (eQTLs) from peripheral blood (Westra cohort: n = 5,311; 15,636 genes) and brain tissue (UKBEC: n = 134; 16,309 genes). Heterogeneity in dependent instruments (HEIDI) analysis validated causal associations. Candidate targets were further assessed by pathway enrichment, drug prediction, and phenome-wide association studies (PheWAS). Peripheral blood eQTLs identified four genes associated with LBP (PSMR < 3.2&#xd7;10-, HEIDI P > 0.05): BTN2A3P, GFPT1, UHRF1BP1, SNRPC; brain eQTLs identified four genes associated with LBP (PSMR < 3.07&#xd7;10-, HEIDI P > 0.05): CHST3, DCC, UHRF1BP1, SNRPC. Cross-tissue integration prioritized&#xa0;UHRF1BP1&#xa0;and&#xa0;SNRPC&#xa0;as consensus candidates. Drug prediction suggested levamisole and taxifolin as potential&#xa0;UHRF1BP1-modulating compounds. PheWAS indicated low pleiotropic risk, with associations mainly with hypertension and celiac disease. This multi-omics framework prioritizes UHRF1BP1 (involved in epigenetic regulation) and SNRPC (RNA splicing modulator) as mechanistically novel, genetically supported candidate targets for LBP, providing a foundation for future experimental validation and therapeutic development.

Nurse burnout during COVID-19 has been well studied; however, limited research exists on the impact of hospital administrators' interventions on trauma nurses' perceptions of burnout and value during staffing crises. To examine contributors to burnout and explore administrative interventions affecting trauma nurses' perceived value during COVID-19. This exploratory, sequential mixed-methods study was conducted in 2 phases at a Level II trauma center in the western United States from January 2022 to January 2024. In phase 1, qualitative data from 13 semi-structured interviews with trauma nurses and administrators informed development of a cross-sectional survey. In phase 2, the resulting 50-item survey was distributed at the trauma center, through the Society of Trauma Nurses list serv, and at the 2023 conference. Of 204 individuals who initiated the survey, 126 (62%) completed it (local: 45/69, 65%; national: 81/135, 60%). A response rate could not be calculated because of the multimodal distribution method. Exhaustion from an increased workload was the most reported burnout factor (n = 115/123, 93%). Distress from crisis standards of care ranked second (n = 112/124, 90%). Nurses felt most valued from financial incentives (n = 92/123, 75%) and a responsive administration (n = 79/123, 64%). Nurses felt least valued from "Healthcare Heroes" campaigns (n = 75/124, 60%). Nurses satisfied with administrative support had lower odds of reporting burnout from administrative delays (OR, 0.49; 95% CI, 0.31-0.85; p < .01). Administrative approaches that reduce workload, prioritize responsiveness, and emphasize higher wages may improve nurse perceptions of value and mitigate burnout during staffing crises, whereas symbolic gestures such as "Healthcare Heroes" should be avoided.

This study aims to elucidate the molecular mechanisms through which PET microplastics (PET-MP) influence osteoarthritis (OA) pathogenesis by integrating network toxicology, machine learning, and in vitro experimental validation. Differential gene expression analysis and WGCNA were applied to multiple OA datasets to identify disease-related targets. PET-MP biological targets were predicted via ChEMBL, SwissTargetPrediction, and PharmMapper. Overlapping targets were screened using machine learning algorithms, and molecular docking was performed to assess binding interactions. In vitro validation including immunofluorescence, qRT-PCR, and Western blot was conducted in PET-MP-treated chondrocytes. A total of 452 PET-associated targets were identified, with 12 core PET-MP-OA genes established through intersection analysis. Functional enrichment implicated the NF-&#x3ba;B and IL-17 signaling pathways. Machine learning screening based on feature importance and SHAP values prioritized six hub genes: AKR1A1, INSR, KIF11, MMP1, KCNN4, and TK1. Molecular docking generated predicted AutoDock Vina scores ranging from -3.893 to -7.434&#xa0;kcal/mol. In vitro experiments validated upregulation of AKR1A1, MMP1, KCNN4, KIF11, and TK1, and downregulation of INSR in chondrocytes, consistent with bioinformatics predictions. PET-MP may promote OA progression by disrupting molecular pathways related to inflammation, oxidative stress, and cartilage degradation. The identified hub genes offer new insights into microplastic toxicology in joint disease and represent potential therapeutic targets and biomarkers for PET-MP-induced OA.

Heart failure (HF) is a major global health concern, particularly in low- and middle-income countries where it is often underdiagnosed. Prognostic testing plays a crucial role in guiding treatment and monitoring disease progression. In this study, we developed an electrochemical assay-based prognostic kit for HF detection targeting soluble suppression of tumorigenicity 2 (sST2). This biomarker offers superior prognostic value compared to traditional methods as it remains stable regardless of patient demographics, including age, sex, obesity, and renal status. To reduce production costs and complexity of the test kit, single-domain antibody fragments (nanobodies) were used in place of conventional antibodies, and an electrochemical platform was used instead of ELISA. We obtained 19 candidate nanobodies from screening a na&#xef;ve, fully synthetic yeast-display nanobody (Nb) library, and four of these (Nb1, Nb2, Nb5, and Nb13) were prioritized for further study on the basis of high affinity and low polyreactivity. Of these, Nb2 and Nb5 enabled sensitive electrochemical detection of sST2 with limits of detection of 3.37 and 3.00 ng/mL, respectively, in PBS buffer. Further validation using patient serum samples with the Nb5-based platform achieved quantitative detection of sST2 across a predilution concentration range from 0.75 to 93.09 ng/mL, facilitated by sample dilution to mitigate matrix effects and surface saturation. Both nanobodies exhibited high target specificity, with no observed cross-reactivity to other HF biomarkers or serum components. This novel prognostic tool can be produced and performed at low cost, providing a new option for heart failure diagnosis and treatment planning, particularly in low- and middle-income countries, where cost is a major cause of underdiagnosis.

Successful implementation of health information technology (HIT) depends largely on patients' readiness to engage with digital systems. Patient readiness encompasses multiple dimensions, including technological skills, communication preferences, information needs, and privacy concerns. Despite the rapid expansion of digital health services, limited evidence exists regarding outpatients' readiness for engagement in HIT in developing healthcare settings, particularly in university hospitals in Iran. This study aimed to assess outpatients' readiness for engagement in health information technology and examine differences across readiness dimensions. A cross-sectional study was conducted in 2024 among 400 adult outpatients attending specialty and subspecialty clinics at academic hospitals affiliated with Ahvaz Jundishapur University of Medical Sciences using stratified random sampling. Readiness for engagement in health information technology was assessed using the 28-item Patient Readiness to Engage in Health Information Technology (PRE-HIT) questionnaire, which measures eight dimensions: Health Information Need (HIN), Computer Anxiety (CA), Computer/Internet Experience and Expertise (CIEE), Non-Face-to-Face Communication Preference (NFCP), Awareness of Health Information (NNGN), Relationship with Doctor (RD), Cell Phone Expertise (CPE), and Internet Privacy Concern (IPC). Data were analyzed using descriptive statistics, one-sample t-tests, and the Friedman test. Overall readiness for engagement in HIT was favorable. The highest mean score was observed for Non-Face-to-Face Communication Preference (M&#x2009;=&#x2009;3.72, SD&#x2009;=&#x2009;0.72), whereas the lowest score was related to Computer Anxiety (M&#x2009;=&#x2009;2.68, SD&#x2009;=&#x2009;0.65). All dimensions except Computer Anxiety were significantly above the neutral midpoint (p&#x2009;<&#x2009;0.05). Significant differences were observed among the eight dimensions (&#x3c7;2&#x2009;=&#x2009;513.50, p&#x2009;<&#x2009;0.001). This study highlights the high readiness of outpatients to engage with digital health technologies, particularly mobile health tools and non-face-to-face communication. However, the findings also underscore significant challenges, including computer anxiety and privacy concerns, which may hinder full adoption. To improve patient engagement, digital health interventions should prioritize user-friendly designs, clear educational resources to reduce anxiety, and robust privacy safeguards. These insights are critical for designing patient-centered digital health strategies that enhance both accessibility and trust in HIT systems.

Quality marker (Q-marker) screening is crucial for the quality control of traditional Chinese medicine (TCM) formulas but remains challenging. In this study, a principle-guided multistep strategy was established for the rational identification of potential Q-marker candidates in Sanqi Shangyao tablet (SST). Ultrahigh-performance liquid chromatography coupled with quadrupole-Orbitrap mass spectrometry was employed for comprehensive chemical profiling, followed by traceability assessment and relative specificity estimation. A total of 124 compounds were characterized, among which 66 were confirmed using authentic standards. After successive filtering based on traceability, relative specificity, and drug-like properties, 25 candidate compounds were retained and associated with 163 osteoarthritis-related targets. Enrichment analysis identified the TNF signaling pathway as a key regulatory axis, and network topology analysis prioritized prunetin for further investigation. In IL-1&#x3b2;-stimulated chondrocytes, prunetin showed no apparent cytotoxicity at concentrations up to 50&#x2009;&#x3bc;M, significantly reduced nitric oxide production, suppressed pro-inflammatory mediators, and attenuated extracellular matrix degradation. Molecular dynamics simulations provided supportive structural evidence for favorable interactions between prunetin and representative targets, including MAPK14, PTGS2, and AKT1. Based on integrated chemical, biological, and TCM theory considerations, six compounds were proposed as potential Q-marker candidates. This study provides a practical workflow for preliminary Q-marker candidate prioritization in complex herbal formulations.

Postoperative involuntary hypothermia (IH) is an important complication that occurs when the body temperature drops below normal and can negatively affect the patient's recovery process. IH has a significant impact on patients' experiences, both physiologically and psychologically. To explore patient perceptions and experiences of IH following total hip and knee surgery and its impact on postoperative care. This study was conducted using a qualitative content analysis approach on patients who underwent total hip and knee surgery and developed IH in the orthopedic unit of a tertiary hospital in Central Anatolia, T&#xfc;rkiye, between April and August 2025. After obtaining ethical approval and informed consent, a purposive sampling method was used, and data saturation was achieved with a sample size of 15 patients. Data were collected through face-to-face and in-depth interviews 3-4 days after surgery, and the data were analyzed using thematic analysis to identify key themes. The analysis of the data identified seven main themes ((1) Physical Experiences, (2) Psychological responses, (3) Care Experiences, (4) Information and Awareness, (5) Environment factors, (6) Interventions and Coping Methods, and (7) Expectations and Recommendations) and 27 subthemes. The research findings revealed that IH following total hip and knee surgery is multidimensional in terms of physical (chills, shivering, pain, nausea, and insomnia), psychological (anxiety, fear, panic, stress, and relaxation), and care-related experiences (attention, communication, and lack of information). Environmental conditions and the transfer process affected patient comfort, while blankets, warm air devices, pharmacological support, and social support were among the coping methods. Patients suggested room temperature regulation, blanket use, and staff attention. This study revealed the effects of IH on patient experiences following total hip and knee surgery and provided important data to enhance patient safety and comfort in clinical practice. The findings indicate that nurses and healthcare teams should prioritize environmental temperature regulation, patient education, and appropriate intervention methods in their care processes.

Uropathogenic Escherichia coli (UPEC) often causes recurrent urinary tract infections, where biofilms and persister cells can promote recalcitrance. This study evaluated whether secretion-system marker genes associate with antimicrobial susceptibility, biofilm formation, and biofilm-associated persistence in clinical urinary isolates. A total of 71 isolates were screened by PCR for fimH and markers of secretion systems: type I (hlyA), type II (gspD), type V (ag43), and type VI (hcp). Minimum inhibitory concentrations (MICs) were measured by Etest, biofilm biomass by crystal violet assay, and persister survival in strong biofilm producers after antibiotic challenge. fimH was detected in 91.5% isolates; gspD and ag43 were common (71.8% and 80.3%), while hlyA and hcp occurred in 32.4% and 46.5%. Marker co-occurrence was frequent, with 19.7% carrying all four secretion markers, and 8.5% with no secretion markers detected. A total of 81.7% isolates formed biofilm, including 18.3% strong producers. Individual marker prevalence did not differ across biofilm categories. Carriage of hlyA and hcp was associated with lower MIC distributions for selected antibiotics (including fosfomycin, ciprofloxacin, and ampicillin-sulbactam), whereas gspD and ag43 showed no consistent MIC associations. The biofilm category was linked to non-susceptibility to ampicillin-sulbactam, but not the other agents tested. Strong biofilm producers showed biphasic killing consistent with persister formation, and hcp carriage tended to align with higher ciprofloxacin survival. These findings map secretion-system markers in clinical UPEC and suggest that a type VI secretion system may track with biofilm-associated persistence.IMPORTANCERecurrent urinary tract infections (rUTI) often relapse after antibiotic treatment because bacteria can generate persister cells-temporary survivors that tolerate antibiotics without being genetically resistant. Clinicians, therefore, lack markers that flag isolates likely to persist. In 71 clinical urinary Escherichia coli isolates, this study surveyed genes encoding several secretion systems, molecular machines that help bacteria interact with each other and with host tissues. These markers were widespread and frequently co-occurred, but they did not track with stronger biofilm formation. However, a type VI secretion system marker (hcp) was associated with higher survival during ciprofloxacin exposure in strong-biofilm isolates, linking virulence-associated machinery with biofilm-associated persistence. Genetic signatures that reflect persistence, rather than routine resistance, could help prioritize follow-up testing and support development of strategies that target hard-to-eradicate rUTI infections.

Pediococcus pentosaceus (P. pentosaceus) is a lactic acid bacterium widely distributed in fermented foods, dairy products, human specimens, and animal-associated environments. In recent years, P. pentosaceus has attracted considerable attention as a potential probiotic candidate due to its intestinal adaptability, antibacterial activity, antioxidant capacity, immunomodulatory effects, and ability to regulate host-microbiota interactions. However, existing findings remain inconsistent, and its systemic therapeutic value has yet to be comprehensively evaluated from the perspectives of strain specificity and translational medicine. This review examines the probiotic characteristics, oral safety, and potential mechanistic applications of P. pentosaceus in systemic diseases. Current evidence suggests that different strains may exert beneficial effects through multiple interrelated mechanisms, including enhanced intestinal colonization, production of exopolysaccharides (EPS) and bacteriocins, regulation of short-chain fatty acids (SCFAs), restoration of intestinal barrier integrity, inhibition of inflammatory signaling pathways, modulation of oxidative stress, and alteration of bile acid and other microbial metabolite profiles. These mechanisms are associated with potential benefits across hepatobiliary, gastrointestinal, metabolic, respiratory, neurological, and inflammation-related conditions. However, most current evidence derives from in vitro experiments or animal models, clinical evidence remains limited and frequently based on multi-strain formulations, and considerable variability exists across studies in strain origin, dosage, intervention duration, outcome measures, and safety assessment methods. Findings from individual strains should therefore not be extrapolated to the species as a whole. Overall, P. pentosaceus represents a promising but insufficiently validated probiotic candidate for adjunctive disease management, and future research should prioritize standardized strain characterization, causal mechanism validation, dose-response assessment, long-term oral safety evaluation, and well-designed single-strain clinical trials.

Football serves as a premier platform for youth development, yet gender-based participation gaps remain a persistent challenge within the global sporting landscape. Drawing on Ecological Systems Theory as a conceptual framework, this study utilized psychological network analysis to examine selected psychosocial factors related to football participation among primary school students. The sample comprised primary school students (M = 9.322, SD&#x202f;=&#x202f;0.677, age range = 8 to 13 years). We employed psychological network analysis with the Network Comparison Test for network estimation and gender comparisons. Harmonious passion emerged as the most central node across both construct and item level networks, showing strong connections to parental support and behavioral engagement. While the Network Comparison Test confirmed a largely invariant psychosocial architecture across genders, exploratory analysis revealed localized descriptive variations: obsessive passion items occupied more central positions in girls' networks, whereas gender stereotypes were more prominent in boys' networks. These findings indicate that harmonious passion occupies a central position in the network structure of children's football participation. This study underscores the need for interventions that prioritize autonomous motivation while addressing the subtle, gender-specific nuances within children's sporting environments.

Uterine prolapse is a common and debilitating pelvic floor disorder that significantly impairs women's quality of life worldwide. With global population aging and lifestyle transitions, its disease burden has become increasingly pronounced. However, comprehensive analyses of long-term epidemiological trends, driving factors, and health inequalities across different socioeconomic settings remain limited. This study analyzed data from the Global Burden of Disease (GBD) 2021 study, covering 204 countries and territories from 1990 to 2021. Age-standardized incidence and Disability-Adjusted Life Years (DALYs) rates were calculated. Estimated annual percentage changes (EAPCs) were computed to evaluate temporal trends. Decomposition analysis was performed to quantify the contributions of population growth, population aging, and epidemiological changes to DALY changes. Health inequality was assessed using the Slope Index of Inequality (SII) and Concentration Index (CI) across Socio-demographic Index (SDI) quintiles. Globally, the age-standardized DALYs rate for uterine prolapse was 9.90 per 100,000 in 2021. Incidence exhibited a bimodal peak at 45-54 years and 90+ years, whereas DALYs increased monotonically with age, peaking in the oldest-old (90+ years). Low and low-middle SDI regions exhibited declining trends, whereas middle, high-middle, and high SDI regions showed increasing trends, with high SDI regions demonstrating a U-shaped resurgence. Decomposition analysis revealed that population growth and aging were the primary drivers of global DALY increases, with epidemiological changes partially offsetting the increase, although this effect varied considerably across SDI levels. Health inequality analysis demonstrated that the burden of uterine prolapse has progressively concentrated among higher SDI populations, with this inequality widening substantially over the past three decades. The global burden of uterine prolapse has risen over the past three decades, with marked heterogeneity across SDI levels. Interventions should prioritize early screening for midlife women, tiered management for older women, metabolic risk control in high SDI regions, and surgical access in low SDI regions, with resource allocation tailored to national SDI levels and population age structures.

Large language model (LLM) are increasingly explored for oncology decision support, yet their alignment with real-world clinical practice across varying disease complexities remains insufficiently characterized. This study aimed to evaluate and compare the accuracy, stability, and concordance of two advanced LLMs-DeepSeek V3.1 and ChatGPT-5-against experienced oncologists in generating breast cancer treatment plans within a specific clinical setting. This retrospective study compared the performance of DeepSeek V3.1 and ChatGPT-5 with senior oncologists using de-identified records from 213 breast cancer patients (Stages I-IV). To assess effectiveness, we implemented a multidimensional evaluation framework: accuracy was measured using a 5-point Likert scale by three independent, blinded expert reviewers; internal consistency was quantified via variance and coefficient of variation; and clinical concordance was evaluated using a structured five-level scoring system. Statistical analyses, including ANOVA and ordinal regression, were used to examine the impact of disease stage on AI-human agreement. Under standardized retrospective review conditions, LLM-generated recommendations demonstrated higher expert-rated guideline concordance and lower variability than historical real-world oncologist plans. Specifically, DeepSeek V3.1 achieved the highest expert-rated accuracy scores with minimal internal variance (4.91&#x2009;&#xb1;&#x2009;0.36), outperforming both ChatGPT-5 (4.65&#x2009;&#xb1;&#x2009;0.62) and clinicians (3.82&#x2009;&#xb1;&#x2009;0.63, P&#x2009;<&#x2009;0.001). While AI outputs exhibited high mutual consistency (74.2%), expert evaluations revealed a significant decline in AI-clinician agreement as disease stage advanced (P&#x2009;<&#x2009;0.001), particularly in Stage IV cases where clinicians prioritized real-world constraints such as financial toxicity. Advanced LLMs, particularly DeepSeek V3.1, demonstrated strong performance in generating standardized, guideline-concordant breast cancer treatment plans, showing superior consistency over human specialists in protocol-driven scenarios. However, the widening gap in complex late-stage cases highlights limitations in accounting for clinical context and socioeconomic factors. These findings support the role of LLMs as robust clinician-supervised decision-support tools while emphasizing the necessity of human judgment for individualized care.

Electronic health records (EHRs) are intended to strengthen continuity of care by enabling shared access to clinical information across disciplines. In this review, documentation compliance refers to completing required clinical documentation in a timely, complete, structured, and retrievable manner to support multidisciplinary information use. However, documentation compliance remains inconsistent in multidisciplinary hospital workflows, limiting its usability for interprofessional coordination and safe decision-making. To map barriers and facilitators influencing EHR documentation compliance in multidisciplinary acute care hospital settings using a sociotechnical lens. This scoping review followed Joanna Briggs Institute guidance and was reported according to PRISMA-ScR. A systematic search was conducted in PubMed, ScienceDirect, and selected databases accessed through the EBSCOhost platform from database inception to 13 April 2026. English-language primary empirical studies examining barriers and/or facilitators to EHR documentation compliance in multidisciplinary acute care hospital workflows were included. Two reviewers independently screened studies and charted data. Findings were synthesized using descriptive thematic analysis. From 608 records, 22 studies met the inclusion criteria. The evidence base was limited and heterogeneous, with qualitative and implementation-focused studies predominating. Technological barriers included poor usability, access friction, fragmented information architecture, and limited team-level visibility. Individual and behavioral barriers included variable trust in digital information, selective documentation use, and reduced critical review linked to structured documentation and convenience functions. Organizational barriers included constrained workstation access, interruptions, inconsistent standards, staff turnover, and insufficient communication or training during system changes. Facilitators included workflow-aligned templates, automation, reminders, alerts, discipline-sensitive training, clinician-IT collaboration, and audit-and-feedback mechanisms. EHR documentation compliance in multidisciplinary hospitals is shaped by interacting sociotechnical conditions. Evidence-informed improvement should prioritize workflow-aligned design, clear documentation standards, continuous training, change communication, and feedback mechanisms that support interprofessional coordination and patient safety.

Remote Sampling Systems (RSS) represent a technological innovation to traditional anti-doping testing, yet successful implementation depends on stakeholder acceptance. To move RSS beyond emergency use, system design must account for user acceptance. Drawing on a contextualized Extended Valence Framework (EVF), this study examines how athletes and Doping Control Officers (DCOs) evaluate RSS legitimacy and how benefit, risk, and trust perceptions shape their attitudes toward RSS introduction. A cross-sectional online survey with 132 athletes and 107 DCOs compared both groups on transparency, trust, perceived benefits, three risk dimensions (performance, privacy, psychological), perceived legitimacy, and attitude toward RSS. Group-specific PLS-SEM tested the hypothetical structural model, and multi-group analysis (MGA) identified significant between-group differences. DCOs reported higher performance risk. Athletes showed higher legitimacy perceptions and more favorable attitudes. PLS-SEM explained substantial variance in legitimacy (63.8% athletes, 56.6% DCOs) and attitude (74.2% athletes, 56.1% DCOs). Transparency was positively associated with trust, which related positively to perceived benefits and reduced all risk dimensions. Perceived benefits, performance risk, and psychological risk shaped legitimacy, which was strongly associated with attitudes. MGA showed that transparency was more strongly associated with trust among DCOs, while performance risk and legitimacy showed stronger associations among athletes. Perceived legitimacy emerges as the central mechanism linking benefit-risk evaluations to attitudes in a mandatory anti-doping technology context. Both groups converge on many RSS evaluations but diverge on performance risk and legitimacy. DCOs prioritize functional robustness; athletes are more receptive but sensitive to fairness. Findings highlight the need to address DCOs' performance concerns and build legitimacy through transparent procedures, user-centered design, and communication that emphasizes fairness and effectiveness.

Tumor hypoxia represents one of the primary obstacle in effective cancer therapy by conferring drug resistance to chemotherapy, radiotherapy, and immunotherapy, and facilitating tumor growth and immune escape. The use of artificial oxygen carriers (AOCs) represents an innovative approach to overcoming hypoxia and improving therapeutic efficacy in oncology. Here, we review some of the most recent studies on various oxygen-carrying systems, such as hemoglobin-based oxygen carriers (HBOCs), perfluorocarbon-based therapeutic agents, oxygen-releasing biomaterials, and induced pluripotent stem cell-derived RBCs (iPSC-RBCs). Recent advancements, including hemoglobin modifications, encapsulation techniques, and bio-inspired oxygen carriers, have improved the stability, biocompatibility, and circulation time of these platforms. Preclinical evidence indicates that these therapies increase oxygen concentration in tumors and sensitize them to radiation therapy, chemotherapy, and immunotherapy. Nonetheless, several issues associated with the use of these therapies such as oxidative toxicity, nitric oxide scavenging, poor blood circulation time, production complications, and risks observed in earlier studies, still need to be addressed. In addition, while iPSC-derived RBCs could offer hope for future transfusion use, but their use against tumors has not been fully explored yet. In summary, artificial oxygen therapies represent an innovative treatment strategy for overcoming treatment resistance that results from hypoxia in cancer. However, further studies are required to optimize these technologies and evaluate their clinical potential. The next generation of oxygen therapies must prioritize safety, tumor specificity, and the integration of oxygen delivery with anticancer therapies.

To establish consensus recommendations for initiating dextromethorphan-bupropion extended release (45&#x2009;mg/105&#x2009;mg) (AUVELITY) for the treatment of major depressive disorder (MDD) in adults. US-based healthcare providers (HCPs, n&#x2009;=&#x2009;10) with clinical experience treating MDD participated in a 3-stage modified Delphi panel procedure. An initial literature review was performed to assist in the development of draft recommendation statements. The draft recommendations were discussed and revised in two live meetings, with a series of anonymous votes taken to reach consensus for each proposed statement. Recommendations required a mean score &#x2265;3.0 (75% agreement) to reach consensus. The panel reached consensus on 27 final recommendations with a mean overall agreement score of 3.8. Key consensus recommendations (abbreviated here) included: (1) dextromethorphan-bupropion is recommended as a first-line treatment for MDD, including with co-occurring symptoms of anxiety; (2) HCPs should individualize treatment decisions that prioritize safety considerations noted in the Prescribing Information; (3) dextromethorphan-bupropion is recommended for patients with inadequate response, residual symptoms, and/or intolerable side effects associated with prior MDD treatment(s); (4) when switching from (or adding to current) medication, the potential for a drug interaction should be considered, consistent with the dextromethorphan-bupropion label; and (5) switching from ketamine or esketamine should be done with caution, and with an awareness of the short-to-intermediate elimination half-lives of these drugs. These consensus panel recommendations provide real-world guidance for initiating MDD treatment with dextromethorphan-bupropion extended release and address any perceived barriers for scenarios of interest.

High-dose (HD) influenza vaccines have demonstrated robust effectiveness in preventing severe influenza-related outcomes, including pneumonia, cardiorespiratory complications, and mortality, with evidence from randomized clinical trials, meta-analyses, and real-world studies consistently showing superiority over standard-dose (SD) vaccines and supporting international recommendations for adults aged &#x2265;60 years. This is increasingly relevant in the context of global aging and immunosenescence, which weakens vaccine-induced immune responses and heightens biological frailty, functional decline, and the risk of severe complications in older adults, especially those with comorbidities. The objective of this work is to describe the introduction, uptake, and current use of HD influenza vaccines in Spain and to summarize the evidence supporting their broader adoption in adults &#x2265;60 years of age. Methods include a narrative synthesis of clinical evidence and an analysis of vaccination strategies implemented across Spanish autonomous communities since the introduction of HD vaccines during the COVID-19 pandemic. Available evidence supports extending HD vaccine use as a population-based strategy to enhance protection and promote equitable access. The results show that the incorporation of HD influenza vaccines marked a significant shift in national vaccination strategies, with heterogeneous uptake across regions: while some prioritized institutionalized or dependent populations, others implemented mixed approaches that also included community-dwelling adults aged &#x2265;60 years. In conclusion, a clear trend toward wider adoption is emerging, with an increasing number of autonomous communities incorporating HD vaccines into their programs and progressively lowering the recommended age threshold, in alignment with international guidance and the biological rationale for strengthened protection in older adults.