Large language models (LLMs) are increasingly embedded in conversational agents for cardiometabolic care. These systems could support self-management, but their behavior change content, delivery mechanisms, and implementation transparency are poorly understood. This scoping review mapped behavior change techniques (BCTs) used in LLM-driven conversational agents for cardiometabolic prevention and management, described how these techniques are delivered across static, rule-based, and generative mechanisms, examined LLM design, personalization, and safety reporting, and summarized user experience and behavioral or clinical outcomes. We searched PubMed, Web of Science, Embase, CINAHL, APA PsycInfo, IEEE Xplore, ACM Digital Library, arXiv, ClinicalTrials.gov, and the WHO International Clinical Trials Registry Platform for records published from January 1, 2020, to November 30, 2025. The final search was run on March 25, 2026, using this publication-date limit. Eligible studies reported a patient-facing text- or voice-based cardiometabolic conversational agent using an LLM or other transformer-based generative model. Two reviewers independently screened records and extracted data. BCTs were coded using the Behavior Change Technique Taxonomy v1; selected self-management BCTs were classified as static, rule-based or templated, or generative or context-aware. Empirical human-participant- or evaluator-based studies were appraised with the Mixed Methods Appraisal Tool, and a study-specific checklist assessed LLM implementation reporting transparency. Thirty-eight studies were included; 19 involved empirical human-participant- or evaluator-based assessments, whereas 19 were technical and system-level evaluations, including framework-development, simulated-output, and proof-of-concept studies. Studies were concentrated in 2024-2025. Instruction on how to perform behavior was identified in 30 of 38 (79%) studies, information about health consequences in 27 of 38 (71%) studies, and feedback and monitoring techniques in 19 of 38 (50%) studies. Most agents were positioned as educators or coaches targeting type 2 diabetes, obesity, or related cardiometabolic risk, and GPT-family models embedded in hybrid architectures with retrieval-augmented generation or rule-based components predominated. Generative outputs were used mainly for tailored explanations, risk information, and socioemotional responses, whereas self-monitoring, reminders, and structured interactions were more often rule-based or mixed-mode. Only 13 of 38 (34%) studies fully reported prompts or system messages, and 16 of 38 (42%) studies fully reported safety or oversight mechanisms. User evaluations reported good usability and perceived helpfulness, but behavioral or physiological outcomes were sparse and usually limited to pilot, short-term, or single-case designs. LLM-driven conversational agents for cardiometabolic care are proliferating but remain early-stage and methodologically heterogeneous. Current systems primarily use LLMs as educational and explanatory layers with "synthetic empathy" over rule-based data capture and safety functions, while behavior change content remains dominated by information provision and simple feedback. More rigorous comparative studies with longer follow-up are needed before firm conclusions can be drawn about sustained behavioral or clinical benefit.
Cerebrovascular diseases represent a major public health challenge, and stroke is among the leading causes of mortality worldwide. Among poststroke complications, pneumonia stands out because of its frequency and negative impact on clinical outcomes, including prolonged hospitalization and increased mortality. In this context, studies investigating the risk factors associated with stroke-related pneumonia differ in terms of their design, care setting, and adopted definitions. This study aims to map risk factors related to the incidence of pneumonia in adults hospitalized after stroke. This scoping review protocol was developed in accordance with the JBI Reviewer's Manual and the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews). Searches will include the following indexed databases: PubMed (MEDLINE), Embase, Scopus, the Cochrane Library, Web of Science, and the Virtual Health Library. Gray literature will be searched in Google Scholar, the CAPES Theses and Dissertations Catalog, the Brazilian Digital Library of Theses and Dissertations, ProQuest, SciELO Preprints, medRxiv, ClinicalTrials.gov, and the Brazilian Registry of Clinical Trials. Additional organizational sources will include the World Health Organization, the Pan American Health Organization, the Centers for Disease Control and Prevention, the European Stroke Organisation, and the Brazilian Ministry of Health. Qualitative, quantitative, and mixed methods studies, including observational and experimental designs, will be considered, with no language or time restrictions, provided that they meet the eligibility criteria defined in the protocol. Study selection will follow 3 stages using Mendeley (Elsevier) and Rayyan (Rayyan Systems Inc). This protocol was funded in June 2026 by the Federal University of Mato Grosso do Sul and the Coordination for the Improvement of Higher Education Personnel (Finance Code 001). The protocol was developed and prospectively registered in the Open Science Framework. Preliminary searches were carried out in August 2025 in PubMed (MEDLINE), Embase, and the Cochrane Library to test the sensitivity of the search strategies and estimate the potential volume of eligible studies. At the time of publication, the final search, study selection, data extraction, and evidence synthesis had been completed. The manuscript reporting the final review results is expected to be submitted for publication in early 2027. This review is expected to contribute to the systematization of evidence on risk factors related to stroke-associated pneumonia, identify knowledge gaps, and support future prevention strategies and clinical management of hospitalized patients. Open Science Framework 10.17605/OSF.IO/EXYWZ; https://osf.io/exywz/overview. PRR1-10.2196/90248.
Severe acetabular bone loss and pelvic discontinuity in revision total hip arthroplasty present substantial reconstructive challenges, particularly when standard hemispherical cups, augments, or cages cannot achieve durable fixation or restore appropriate hip biomechanics. Custom pelvic implants (CPIs) are designed from patient-specific CT data and produced using additive manufacturing to create monoblock constructs that conform to bony defects and maximize fixation to remaining viable bone. This review summarizes the evolution of CPIs from early "triflange" devices to contemporary porous-coated, biomechanically optimized designs and outlines current nomenclature and indications. Key elements of preoperative evaluation, imaging protocols, and CT-based modeling are reviewed, along with implant design considerations including flange geometry, ischial fixation strategies, and screw trajectory planning. Surgical techniques for managing pelvic discontinuity are discussed with emphasis on achieving construct stability and promoting osseointegration. Published midterm to long-term outcomes demonstrate high implant survivorship, improved function, and low mechanical failure rates, with most revisions attributable to infection or instability. Economic analyses suggest CPIs are cost-comparable with other advanced reconstructive options while offering reliable fixation in complex cases. When applied with appropriate patient selection, careful design collaboration, and meticulous surgical execution, CPIs provide an effective and reproducible strategy for challenging acetabular reconstruction.
Clinical trials remain the foundation of evidence-based medicine but often fail to reflect the diversity, complexity, and real-world contexts of the populations they are intended to serve. Insights from the 2025 Symposium to Strengthen Health Research highlight structural barriers - including restrictive eligibility criteria, historical mistrust, inequitable access to trial sites, and misaligned research incentives - that limit equitable participation. Addressing these challenges requires a shift toward community-engaged research, pragmatic and decentralized trial designs, and artificial intelligence-enabled tools that connect patients with appropriate studies. This article outlines a cross-sector strategy for embedding equity, real-world relevance, and patient partnership into the design, funding, and implementation of clinical research.
Hypertension is a major global health challenge, and effective health education is crucial for improving patients' self-management. Traditional health education approaches are often limited by insufficient personalization, accessibility, and scalability. Artificial intelligence (AI), including natural language processing, machine learning, and large language models (LLMs), offers promising solutions to address these limitations. However, evidence regarding AI applications in hypertension health education has not been comprehensively synthesized. This scoping review aimed to summarize the current evidence on AI applications in hypertension health education, and identify research gaps to inform future research and practice. This review followed the Joanna Briggs Institute methodology and PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines. Six databases (PubMed, Embase, Web of Science, Cochrane Library, CINAHL, and Scopus) were searched from January 2015 to June 2026. Eligibility criteria were developed using the participant-concept-context framework. Two reviewers independently conducted study screening and data extraction. Study designs were classified using the Mixed Methods Appraisal Tool framework. Consistent with scoping review methodology, no formal quality assessment was performed. Findings were synthesized narratively and presented using evidence gap maps, tables, and figures. A total of 24 studies from 11 countries were included, comprising 6 randomized controlled trials, 4 nonrandomized trials, 11 quantitative descriptive studies, and 3 mixed methods studies. Most studies were published between 2024 and 2026. In total, 3 AI application scenarios were identified: rule-based health education, data-driven adaptive health education, and generative AI-driven health education. Natural language processing was the most widely applied technology, and LLM-based applications increased rapidly after 2023. However, generative AI studies were predominantly proof-of-concept evaluations and lacked randomized clinical validation. Health education was rarely implemented as a standalone intervention and was typically embedded within multifunctional AI platforms. Outcomes were categorized using the Digital Health Scorecard Framework across 4 domains: technology, clinical, usability, and cost. Technical accuracy and blood pressure outcomes were the most frequently reported measures, whereas no study evaluated economic outcomes. This first scoping review of AI applications in hypertension health education identified a mismatch between rapid advances in generative AI and the limited availability of rigorous clinical evidence. Three major research gaps were identified: (1) the lack of standardized core outcome sets covering technical, behavioral, clinical, and implementation domains; (2) limited development of hybrid architectures integrating LLM with structured medical knowledge bases; and (3) the absence of evaluation frameworks that satisfy both regulatory and implementation requirements. AI appears most suitable as a complement to, rather than a replacement for, clinician-delivered education. Future research should prioritize rigorous clinical validation, economic evaluation, multicultural adaptation, and health literacy equity to ensure that AI-driven health education reduces rather than exacerbates disparities in hypertension control.
Polymer conjugation is a widely used strategy to improve the pharmacokinetics of protein therapeutics by extending their half-life and protecting them from degradation. Poly(ethylene glycol) (PEG) is the most commonly used polymer for this purpose. However, its use can trigger unwanted immune responses, leading to the production of anti-PEG antibodies that compromise efficacy. This issue has driven the search for alternative polymers, with poly(sarcosine) (PSAR), derived from an endogenous amino acid, emerging as a promising candidate. Despite this potential, the immunogenicity of PSAR-protein conjugates (PSARylation) has not been systematically compared with that of PEGylated counterparts. In this report, we show that conjugating a model protein antigen to high-molecular-weight PSAR more effectively suppresses immune responses against both the protein and the polymer than PEG. Although polymer conjugation has traditionally been viewed as a means of steric "masking" of a protein, our results demonstrate that the chemical nature of the polymer is a critical, independent factor, as PSAR conjugates elicited lower antibody production than PEG conjugates of identical hydrodynamic size. This study highlights polymer selection as an important design parameter for minimizing immunogenicity in next-generation protein therapeutics. Polymers derived from biological building blocks, such as PSAR, offer a promising route to developing safer, more effective biopharmaceuticals with better tolerance and reduced risk of adverse immune reactions.
Vitamin K antagonists (VKA) are the recommended treatment for thrombotic antiphospholipid syndrome (TAPS), but it remains uncertain whether direct oral anticoagulants (DOAC) could serve as an alternative to VKA in a subgroup of low-risk TAPS patients with venous thromboembolism (VTE). To compare the incidence of thrombosis recurrence between DOACs and VKAs in TAPS patients with VTE as index event. In this retrospective cohort study, we included adults with TAPS and index VTE treated with a DOAC or VKA between January 2013 and March 2023. Outcomes were recurrent thrombosis, defined as arterial thromboembolism (ATE) or VTE, and bleeding. Cox regression with time-varying covariates was applied, adjusted for age and sex and stratified by laboratory risk profile according to the 2023 ACR/EULAR criteria. We included 277 patients (mean follow-up 3.9 ± 2.8 years); 87% single positive. Recurrent thrombosis occurred in 26 patients (9.4%). The risk of the combined ATE/VTE outcome was higher in the DOAC group than in the VKA group, but not statistically significant (aHR 1.90, 95% CI 0.81-4.49). When analyzed separately, DOAC use was associated with more arterial events (1.34 vs. 0.51 per 100 person-years; HR = 3.72 95% CI 1.04-13.29). Major bleeding occurred in 4.0% of patients, with similar rates between treatments (aHR 0.67, 95% CI 0.34-1.31). In TAPS patients with index VTE, DOACs were associated with more arterial recurrences, with no significant difference in the combined ATE/VTE outcome. Interpretation is limited by few events and retrospective design.
The effectiveness of presumed consent policies in increasing donation and transplantation rates remains a matter of debate within the transplant community. The rationale for their implementation was derived from a limited body of experimental evidence and has largely relied on cross-country panel analyses reporting higher donation rates in opt-out systems. However, no previous study has systematically examined the risk of bias inherent in these analyses using a structured methodological framework. To address this gap, an operative framework of the deceased donation process was developed through the systematization of its phases and conditioning factors. This framework was subsequently used to perform a systematic review of cross-country panel data studies, applying the Risk Of Bias In Nonrandomized Studies of Interventions tool to assess risk of bias. Eighteen studies were identified. Although most (n = 12) reported higher donation and/or transplantation rates in countries with presumed consent, risk of bias assessment identified serious limitations in 16 studies and critical limitations in 2. The principal concerns were inadequate control of confounding factors and misclassification bias resulting from imprecise definitions of how consent policies are implemented in practice, beyond the legal distinction between opt-in and opt-out systems. These findings suggest that, despite their apparent consistency, cross-country panel studies do not provide sufficiently robust evidence to support presumed consent as an effective strategy for increasing donation and transplantation rates. Greater emphasis should therefore be placed on the development of evidence-based donation policies that incorporate all validated determinants of effective deceased donation systems worldwide. Recommendations for improving research design in this field are also proposed.
Enhancing the effectiveness of human-AI collaborative consultation in online health communities (OHCs) constitutes a core requirement for optimizing the allocation of medical resources and promoting the sustainable development of medical services. Nevertheless, the pathways to improving such effectiveness remain insufficiently understood. This study aimed to conduct an in-depth exploration of the multiple factors influencing the effectiveness of human-AI collaborative consultation in OHCs and to assess the causal relationships among these factors, thereby providing a theoretical foundation and practical guidance for advancing the clinical application of human-AI collaboration. Grounded in the information ecology theory, we constructed an analytical framework encompassing four dimensions: information human, information, environment, and technology. We collected 296 valid questionnaire responses and used fuzzy set qualitative comparative analysis to systematically investigate the configurational mechanisms through which these four types of factors jointly influence consultation effectiveness. The findings are as follows: (1) no single factor constitutes a sufficient condition for high consultation effectiveness (consistency <0.9); rather, such effectiveness emerges from the synergistic interplay of multiple configurations involving technology, information, human information, and environment; (2) five distinct configurational pathways lead to high consultation effectiveness, demonstrating clear equifinality; (3) system responsiveness, information usefulness, perceived service empathy, perceived service accuracy, and perceived service effectiveness are all core or important conditions across these pathways; and (4) substitutability exists among antecedent conditions-specifically, perceived uncertainty and social norms, as well as operational convenience and platform ethical norms, can substitute for one another in different configurations to enhance patient satisfaction jointly. This study reveals multiple pathways to achieving high effectiveness in human-AI collaborative consultation within OHCs. It not only offers a novel theoretical perspective for understanding the complex mechanisms of human-AI collaboration in medical contexts, but also provides significant practical implications for the design optimization of digital health platforms and related policy formulation.
To evaluate the effect of early administration of Shenfu injection (SFI) on hemodynamics and clinical outcomes in ICU patients with sepsis. Prospective, multicenter randomized controlled trial. Four tertiary care hospitals located in central China. ICU patients 18-75 years old who met the Sepsis-3 diagnostic criteria. Eligible septic patients were randomized to the SFI group or the control group, receiving either SFI or normal saline at a rate of 20 mL/hr in 5 hours from the time of sepsis diagnosis, bid for 3 consecutive days. The primary outcome was the amount of vasopressors administration (calculated as the norepinephrine equivalents [NEEs]). A total of 172 patients were enrolled, with 86 assigned to the SFI group and 86 to the control group. Compared with the control group, the SFI group had no significant improvement in total NEE doses (22.00 [16.00-29.50] vs. 20.00 [12.50-28.50]; p = 0.16). However, compared with the control group, the SFI group showed significantly lower mortality both during ICU stay (3.5% vs. 11.6%; p = 0.04) and 28 days after treatment (15.1% vs. 27.9%; p = 0.04). The SFI group also exhibited a significant improvement in sublingual microcirculation indicators compared with control group. No significant drug-related adverse events were noted in either group. The early administration of SFI did not decrease the dosage of vasopressors. The secondary outcomes suggested a potential decrease in mortality and possible improvement in microcirculation, findings that require further validation.
Pancreatoduodenectomy is associated with postoperative complications in nearly half of all patients. Understanding the financial burden of these complications is relevant to supporting initiatives to improve patient outcome and resource allocation. A contemporary systematic review evaluating the costs of complications following pancreatoduodenectomy is lacking. A systematic review was conducted following PRISMA 2020 guidelines in PubMed, Embase, and Cochrane Central Register of Controlled Trials from inception to September 2024. Studies reporting on the hospital costs (primary outcome) of complications following pancreatoduodenectomy were included. Costs were adjusted for inflation and purchasing power parity to 2023 Dutch euros (€). Data extraction and risk-of-bias assessments were conducted independently by two reviewers. Overall, 46 studies with 111 215 patients undergoing pancreatoduodenectomy from 13 countries were included. Postoperative pancreatic fistula grade B increased costs by €1998 to €25 228, and grade C by €21 268 to €112 824 versus no clinically relevant postoperative pancreatic fistula (mean or median values). Delayed gastric emptying grade B increased costs by €10 836 to €22 571 and grade C by €28 707 to €61 818 versus no clinically relevant delayed gastric emptying. Postpancreatectomy haemorrhage (various definitions) increased costs by €29 447 to €48 380. Biliary leak grade B increased costs by €7616 and grade C by €22 727. Clavien-Dindo complication grade III added €2785 to €20 294 compared with grade II, and grade IV added €25 190 to €63 644 compared with grade III. Complications following pancreatoduodenectomy increase costs substantially, exceeding €100 000 for a single postoperative pancreatic fistula grade C. These costs can now be used to design cost-effective prophylactic and therapeutic interventions aiming to improve patient outcomes together with optimal use of healthcare resources.
The purpose of this study was to examine the association between adiposity and depressive symptoms in ethnically and racially diverse early adolescents, age 11-14 years old. The design was a cross-sectional observational study, with 78 participants from two middle schools in the southeast. Height, weight, and waist circumference were measured, and body fat percentage (BF%) was obtained using a bioelectrical impedance analysis (BIA) scale. Body mass index (BMI) and waist-to-height ratio (WHtR) were calculated. Participants completed the Children's Depression Inventory II (CDI-2) measure. Estimates of effect size based on general multiple linear regression was used to assess the association between adiposity and depressive symptoms, controlling for gender, puberty, and physical activity. Increased adiposity was associated with decreased depressive symptoms in the context of racially and ethnically diverse early adolescents, with a large effect size (ω2 = 0.14, 95% CI = 0.03, 1.00) between depressive symptoms and BMI category, and small effect sizes for the associations for WHtR (ω2 = 0.02, 95% CI = 0.00, 1.00) and BF% (ω2 = 0.01, 95% CI = 0.00, 1.00) with depressive symptoms. Our findings indicate an inverse association between adiposity and depressive symptoms among early adolescents, which contrasts with many prior studies and underscores the complexity of the relationship between adiposity and mental health during this developmental period. Given the pilot nature of the study and the small sample size, these findings should be interpreted cautiously and warrant confirmation in fully powered studies that include diverse populations across racial and ethnic groups. Greater attention should be paid to overweight and obesity status, and improved screening for depression should be implemented.
The interplay between coordination-induced electronic modulation and the resulting physicochemical properties of metal complexes is fundamental to coordination chemistry. Herein, we report a comprehensive spectroscopic and theoretical investigation of two novel metal complexes derived from a single-armed Salamo-type ligand H3L: dinuclear [Co2(L)(μ2-OAc)]·EtOH (1) and tetranuclear [Pb4(L)2(μ4-O)]·2CHCl3 (2). FT-IR, UV-Vis, and fluorescence spectroscopies, together with DFT calculations, unequivocally confirmed metal-ligand coordination and revealed significant electronic restructuring upon complexation. Key spectral signatures-including the disappearance of the OH stretch, redshifts in CN and π → π* transitions, and the emergence of new metal-involved charge-transfer bands-provided direct evidence of ligand-to-metal binding. Notably, the complexes 1 exhibited opposite fluorescence responses: quenching in 1 and enhancement in 2, which were correlated with their DFT-derived HOMO-LUMO gaps (ΔE = 0.972 eV for 1; 2.167 eV for 2) and frontier orbital distributions. Hirshfeld surface and IRI analyses further visualized the non-covalent interactions stabilizing the crystal packing. Importantly, these coordination-induced electronic features translated into distinct biological activities: both complexes showed concentration-dependent antibacterial effects against Escherichia coli and Staphylococcus aureus, with the Pb(II) complex 2 exhibiting superior efficacy. This work establishes a clear spectroscopic-electronic-activity relationship, demonstrating how systematic spectral analysis can guide the rational design of functional coordination compounds.
As a present-day relict lineage, cycads possess key anatomical traits for understanding the evolution of plant hydraulics; however, how their hydraulic architecture influences the co-optimization of hydraulic safety and efficiency under drought remains unclear. We examined rachis cross-sectional anatomy traits in 20 cycad species and analyzed correlations between hydraulic construction design, tissue fractions, tissue connectivity, and hydraulic function. Additionally, we quantified the distance of cycads from the global hydraulic safety-efficiency trade-off boundary line (LBD) and assessed anatomical contributions to this distance. We found that cycad rachises resembled fern rhizomes, in that most histological and architectural traits did not correlate with embolism vulnerability, except that greater architectural dissection increased vulnerability at the water potential corresponding to 88% embolism. Cycads with higher conduit lumen fractions (Flx) and conduit-phloem connectivity (Ccphl), and lower conduit-parenchyma connectivity (Ccpar), exhibited greater embolism resistance. Notably, cycads showed a longer LBD compared with ferns, noncycad gymnosperms, and angiosperms, and this distance was shortened by larger pit membrane area and fraction and by higher phloem fraction and Flx. Species in Cycadaceae and Zamiaceae exhibited distinct hydraulic architectures. Cycadaceae species, which typically occupy wetter habitats, showed higher Flx and Ccphl, whereas Zamiaceae species from more arid habitats exhibited greater architectural dissection, higher conduit wall fractions (Fwx) and higher Ccpar. These differences reflect contrasting ecological strategies underlying cycad adaptation to divergent environments. Our findings demonstrate that xylem tissue fraction and connectivity play a central role in maintaining hydraulic function under drought, providing insight into water-stress regulation in ancient plant lineages.
Efficient preparation, isolation, and soft-landing deposition of stable clusters with atomic precision are important for developing new catalysts. However, small metal clusters are often highly susceptible to oxidation and prone to structural deformation on supports, which poses substantial challenges to experimental catalysis and theoretical calculations. In this study, we prepared pure Agn+ and Cun+ clusters and screened out superatomic clusters Ag9+ and Cu9+ by gas-phase reactions of sufficient collisions. We then deposited the two clusters onto different substrates using soft landing techniques. Characterization by X-ray photoelectron spectroscopy verified successful deposition and revealed that these superatomic clusters preserve unoxidized states at exposure to air, highlighting their unique stability rooted in superatomic eight-electron shell closure. We tested the catalysis of Ag9+ and Cu9+ clusters for acetylene hydrogenation and related hydrogen-deuterium exchange reactions. The results revealed that the Cu9+ clusters on TiO2 exhibit superior catalytic activity, which is associated with the enhanced cluster-support interactions and favorable H2 activation behavior. This study validates the applicability of superatom clusters for designing new catalysts, with enhanced stability and tailorable active sites.
The OA Coach mobile app was developed to support individuals with knee osteoarthritis in self-managing their condition. The app aims to fill a current gap in the osteoarthritis mobile app field by combining key features such as symptom tracking, objective activity tracking, educational modules, and encouragement notifications underpinned by behavior change theory. The aim of this study was to describe the development of the OA Coach mobile app and assess its usability in a 6-week feasibility study. The app was designed in consultation with consumers, rheumatologists, physiotherapists, and osteoarthritis researchers. The app prototype contained four screens: (1) a home screen to track goals and activities, (2) a progress page, (3) a learning page with self-directed modules, and (4) an inbox for communication with the study team. For the feasibility study, 30 participants were recruited between March and April 2024 from a database of osteoarthritis trial participants or through the Osteoarthritis Chronic Care Program at Royal North Shore Hospital, Sydney, Australia. Participants were eligible if they were aged 45 years or older, had knee pain ≥4 on an 11-point numerical pain rating scale and knee stiffness lasting <30 minutes in duration, or stiffness >30 minutes and diagnosed with knee osteoarthritis through a health care provider or radiographs. Participants were provided access to the app and asked to interact with it daily for 6 weeks. Outcomes were assessed through online questionnaires or through mobile app data. The primary outcome was usability, assessed using the mHealth App Usability Questionnaire (MAUQ). Secondary outcomes included computer self-efficacy and osteoarthritis knowledge. The quantitative data were summarized descriptively. Qualitative feedback was collected through open-ended survey responses and discussed within the research team to improve the app. A total of 30 participants completed the study. There was a 1:1 ratio of male to female participants, with an average age of 66.9 (SD 9.1) years and a mean pain level of 6.0 (IQR 5.0-6.8) on an 11-point numerical pain rating scale. Twenty-nine responses from the MAUQ were available for analysis. Most statements scored >5 out of 7 ("somewhat agree"), indicating that the app was easy to use. The mean satisfaction score for the app on the MAUQ was 4.7 (SD 2.0) out of 7. Qualitative feedback from participants indicated the need for clear instructions on how to use and navigate the app, improved structure and integration of the exercise program, and improved tailoring of osteoarthritis education and support. Overall, the OA Coach app was well accepted by participants. Based on participant feedback, the app will be revised to improve aspects of clarity, ease of use, and personalization. The updated app will be tested against other methods of care delivery in a randomized controlled trial.
Rural communities face disproportionate burdens of chronic disease, mental illness, workforce shortages, and fragmented services despite historic national health spending. The Whole Health, Whole Communities: Dialogues to Reduce Rural Health Disparities symposium in Roanoke, Virginia, convened cross-sector leaders to identify reforms necessary to embed person-centered care into rural systems. Participants outlined staged reforms across governance, financing, workforce development, and data infrastructure. Priority actions include trauma-informed care expansion, payment redesign, sustainable community health worker funding, participatory research, and cross-sector coordination - advancing scalable, community-embedded Whole Health models to reduce rural disparities.
Employing 1,3,5-benzenetricarboxylic acid (H3BTC) as a structure-directing agent, a novel three-dimensional supramolecular framework, {[NH2(CH3)2][Zn(BTC)(H2O)]·(CB (Cai et al., 2019 [6]))0.5·4H2O}n (CB[6]-BTC-Zn), was successfully constructed via a solvothermal reaction involving cucurbit[6]uril (CB (Cai et al., 2019 [6])), H3BTC, and Zn(II) ion. CB[6]-BTC-Zn emits intense blue fluorescence and exhibits remarkable structure stability in aqueous media; and further it functions as an efficient turn-off fluorescent sensor, enabling highly sensitive and selective detection of a food colorant sunset yellow (SY) with a limit of detection as low as 8.48 × 10-7 M. CB[6]-BTC-Zn can maintain excellent performance even in the presence of some food additives, showcasing its good anti-interference capability. The underlying mechanism for sensing SY involves a synergistic three-step process, an initial electrostatic enrichment of anionic SY molecules on the positively charged assembly surface, following an efficient fluorescence resonance energy transfer process facilitated by significant spectral overlap, and ultimately, a dual-channel photoinduced electron transfer (PET) pathway encompassing both donor and acceptor PET process, as confirmed by the density functional theory calculations. Furthermore, this material was processed into flexible sensing films and functionalized LED devices to achieve a visual SY identification, and it also was successfully applied to the spiked recovery detection of SY in actual beverage samples (recovery rates: 95.43-105.62%). This work offers a strategy for designing cucurbituril-based functional materials for rapid monitoring colorants in the field of food safety.
Sustainable biomanufacturing seeks to replace fossil-fuel-based production with renewable bioeconomies, with microbial cell factories serving as key platforms for producing fuels, chemicals, and high-value products. This review highlights recent advances that have transformed pathway engineering from an empirical practice into a predictive and integrated discipline. Artificial intelligence-assisted retrosynthesis expands biosynthetic route design, while genome-scale metabolic models and host-aware simulations improve pathway evaluation under cellular constraints. Enzyme engineering is increasingly integrated with pathway design through machine learning, high-throughput screening, and cell-free platforms. Dynamic regulation, including biosensor-based feedback systems, further optimizes metabolic performance. Together with automation and design-build-test-learn workflows, these advances establish a multiscale framework that accelerates the development of robust microbial production systems.
There is increasing interest in the relationship between inflammatory bowel disease (IBD) and body image. Quantitative research demonstrates a high level of body image dissatisfaction among individuals with IBD that is related to poorer quality of life and mental health disorders including depression, anxiety, and eating disorders. However, there remains a gap in our understanding of how patients with IBD qualitatively experience their bodies. The aim of this study was to qualitatively explore the impact IBD has on body image and understand the nuances specific to this population. Data from co-design workshop interviews with 10 people with IBD (8 women and 2 men, mean age 35) were analysed using reflexive thematic analysis. Four main themes were identified: Not Mainstream Body Image; Functionality at the Core of Body Evaluation and Quality of Life; Eating, Symptom Control, and Body Image; and Unpredictability, Invisibility, and Social Appraisals. Themes captured the unique, pervasive impact IBD has on body image, quality of life, eating behaviour, and mental health. Results highlight the need to target body image concerns and mental wellbeing for people with IBD.