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Multiscale Modeling Primer: Focus on Chromatin and Epigenetics.

A central challenge in modern biology is to understand how molecular interactions produce cellular and organismal functions across vast spatiotemporal scales. Nowhere is this challenge more apparent than in the study of chromatin, where meters of DNA compact into a micron-sized nucleus. How this polymer folds is a dynamic process, regulated by epigenetic modifications-chemical changes to DNA and histones that involve only a handful of atoms. These small changes cooperate to produce emergent, higher-order structures that define cellular identity and function. To explain this system, we must integrate static, high-resolution snapshots from techniques like cryo-EM with dynamic, lower-resolution data from microscopy and genomics. Multiscale computational models are essential tools that bridge these experimental gaps and reveal the mechanisms of emergent behavior. However, the communication divide between experimental biologists and quantitative modelers often hampers progress. This primer addresses that gap. It first introduces the fundamental biology of chromatin and epigenetics at an introductory level for non-biologists audiences. We then survey the landscape of computational approaches, from atomistic to systems-level models, and connect them to the experimental data that inform and validate them at an introductory level for non-computationalists. We argue that the next frontier will require us to build integrative models that can predict how molecular perturbations mechanistically alter cellular phenotypes, which will open a new era of chromatin-targeted therapeutics.

Chromatin Dynamics

The burden of male breast cancer (MBC) in the GBD Central, Eastern, and Western Europe Regions from 1990 to 2023: Results from the Global Burden of Disease Study 2023.

PURPOSE: Male breast cancer (MBC) is underrepresented in cancer statistics: this study aimed to assess the burden of MBC in Central, Eastern, and Western Europe from 1990 to 2023, using data from the Global Burden of Disease (GBD) Study 2023. METHODS: Estimates from GBD 2023 were analyzed to determine the MBC incidence, mortality, and disability-adjusted life years, their all-ages and age-standardized rates, and the 1990 through 2023 annual percent change. These estimates were compared to those for the GBD Super Regions and the Socio-Demographic Index quintile countries. RESULTS: In Central Europe, age-standardized incidence rates (ASIR) increased from 0.54 (0.40-0.76) to 1.05 (0.70-1.52), age-standardized mortality rates (ASMR) from 0.29 (0.25-0.34) to 0.40 (0.36-0.45), and age-standardized disability life-year rates (ASDR) from 7.19 (6.15-8.41) to 9.63 (8.52-11.07). In Eastern Europe, ASIR remained relatively stable, changing from 0.81 (0.56-1.19) to 0.60 (0.38-0.92), whereas ASMR decreased from 0.40 (0.33-0.49) to 0.21 (0.16-0.25) and ASDR from 10.54 (8.69-12.89) to 5.55 (4.52-6.85). In Western Europe, ASIR increased from 0.47 (0.33-0.67) to 0.88 (0.59-1.24), whereas ASMR (0.22 [0.19-0.25] vs. 0.24 [0.21-0.27]) and ASDR (5.20 [4.49-5.97] vs. 5.75 [4.96-6.66]) remained stable. CONCLUSIONS: The burden of MBC is increasing across Europe, particularly in the Central region, with huge regional differences. Population growth and variations over time impacted on the metrics. Even with a composite European scenario, the mortality-to-incidence ratio markedly declined in the three areas.

Humans

A systematic review of human avoidance learning: Cognition, computation, and methods.

Avoidance behaviour is fundamental for survival but can become maladaptive in clinical conditions. A large body of literature has accumulated on the dynamics of human avoidance learning. However, current theories and overviews do not provide an exhaustive account of this evidence. In this systematic review, we identify N = 116 studies on human avoidance learning. We analyse these studies with the goal of distilling robust empirical phenomena as a basis for theory-building, and examine their diagnostic value in differentiating between competing theories. We find that the evidence is difficult to reconcile with foundational two-factor and classical safety-signal accounts, and most strongly supports expectancy- and inference-based views, in which avoidance responses are selected with respect to represented consequences. At the same time, no current framework provides a complete account of the evidence: several findings point to an additional role for operant valuation, Pavlovian influences, and contextual or latent-state control over the expression of avoidance. Methodologically, we observe that the problem setting in the most common experimental paradigms is radically simpler than real-world avoidance and therefore unlikely to expose the limits of inferential or reflective mechanisms. Consequently, we argue that paradigms with greater computational demands and more realistic action affordances are required to identify the mechanisms underlying avoidance learning. Collectively, these insights provide a foundation for theoretical refinement, computational modelling, and methodological innovation, with implications for advancing interventions targeting maladaptive avoidance.

Humans

3D epigenomic remodelling mediated by Foxa1 drives gemcitabine resistance in pancreatic cancer.

Gemcitabine remains a cornerstone treatment for pancreatic ductal adenocarcinoma (PDAC), yet the emergence of resistance constitutes a major clinical challenge with poorly understood epigenomic mechanisms. Here, we identified the pioneer transcription factor Foxa1 as a master regulator of gemcitabine resistance through multi-omics analysis. Mechanistically, Foxa1 drives widespread super-enhancer (SE) reprogramming and 3D genome remodelling in resistant cells, which coordinately activates the expression of key resistance genes, notably Rrm1 and Cdadc1. This is accompanied by increased chromatin accessibility, elevated H3K27ac enrichment at SEs, and enhanced Foxa1 binding at regulatory elements. Moreover, post-translational stabilization of Foxa1 via USP7-mediated deubiquitination sustains this epigenomic program. Genetic ablation of Foxa1 or specific SE regions near Rrm1 resensitizes resistant cells to gemcitabine. Building upon this mechanism, we demonstrate that bromodomain and extraterminal (BET) inhibitors, which disrupt SE function, potently reverse resistance. Notably, the clinical-stage BET inhibitor AZD5153, in combination with gemcitabine, achieves robust tumor suppression and overcomes resistance in cell-derived xenograft (CDX) models by dismantling the Foxa1-mediated resistant transcriptome and reinvigorating drug sensitivity. Our findings establish Foxa1-orchestrated enhancer reprogramming as a fundamental mechanism of gemcitabine resistance and unveil a promising epigenetic therapy to restore treatment efficacy in PDAC.

Hepatocyte Nuclear Factor 3-alpha

A mechanism-guided framework for prioritizing membrane-interaction anti-Vibrio peptides from peptidomics data.

A mechanism-guided framework for prioritizing membrane-interaction antimicrobial peptide candidates from proteomics-derived peptide mixtures is presented. The framework integrates conservative machine-learning-based antimicrobial peptide (AMP) screening with a literature-derived membrane-interaction plausibility (MAP) assessment and a data-driven membrane-interaction ranking function (AIPx), followed by structural visualization for interpretability. MAP encodes physicochemical characteristics commonly associated with peptide-membrane interaction and provides a graded plausibility assessment. Building upon this physicochemically interpretable framework, AIPx ranks peptides using feature weights calibrated from experimentally characterized anti-Vibrio peptides, where minimum inhibitory concentration (MIC) values are used as a coarse-grained ranking reference rather than a direct prediction target. In a peptidomics-based peptide fractionation study targeting Vibrio spp., AIPx exhibited a consistent relationship with experimentally observed antibacterial activity. Distributional analysis revealed that peptide fractions exhibiting high anti-Vibrio activity are characterized by enrichment of high-ranking peptides rather than by AMP abundance alone. By structuring AMP identification and prioritization as sequential stages, the MAP + AIPx framework enables interpretable and experimentally actionable candidate selection by reducing biologically implausible candidates. The framework facilitates species-oriented prioritization of AMP candidates, addressing a key challenge in antimicrobial peptide discovery where activity may depend on target-specific membrane characteristics. Moreover, the approach is extensible through species-specific calibration and supports interpretable, mechanism-informed prioritization in antimicrobial peptide discovery.

Proteomics

Forensic taphonomy in fluvial water: A systematic review.

Human remains are frequently recovered from fluvial (lotic) water environments. Rivers, streams, canals and other flowing water bodies pose distinct challenges in forensic practice, particularly due to their current. Compared to other aquatic contexts, fluviatile taphonomy is underrepresented in the forensic literature and the last comprehensive summary was written over a decade ago. Therefore, a systematic review was performed to collect and summarise the current knowledge in forensics about fluvial taphonomy, including decomposition of remains, transport characteristics, search, postmortem submersion interval (PMSI) estimation, taphonomic alterations, and differences to other water bodies. 92 reports met the inclusion criteria for this review, most of them showed a moderate risk of bias. Their main findings were summarised and two major challenges identified. First, predictions about fluvial transport of human bodies pose a tremendous issue in forensic practice, leading to later detection and lower recovery rate of remains, complicating various subsequent analyses. Second, PMSI estimations are difficult particularly due to variable environmental conditions in fluviatile systems. Recommendations for future research in the area of fluvial forensic taphonomy include that case-related data such as the detailed decomposition state and river characteristics need to be made available. More standardised research protocols are required for a facilitated comparison between studies, environments and regions. This review provides forensic practitioners with a comprehensive, updated resource for the investigation of fluvial remains. It also guides future research towards a more efficient practice to build the basis for a broader, more robust and comprehensive synthesis, subsequently supporting analyses in forensic casework.

Humans

Effectiveness of artificial intelligence in nursing simulation education: A systematic review, meta-analysis and bibliometric visualization analysis.

OBJECTIVES: To synthesize the roles and core functions of AI in nursing simulation education for nursing students via systematic review, quantitatively evaluate its effects on students' knowledge and skill outcomes through meta-analysis, and map the research landscape and development trends of this field through bibliometric visualization analysis. DESIGN: Systematic review, meta-analysis and bibliometric visualization analysis. DATA SOURCES: Eight electronic databases: PubMed, Web of Science, MEDLINE, ERIC, Academic Search Complete, China National Knowledge Infrastructure (CNKI), Wanfang Database, VIP Chinese Science and Technology Journal Database (VIP) were employed to search studies from the time of construction to 16 December 2025. REVIEW METHODS: Studies meeting the inclusion criteria were screened. The revised Cochrane Risk of Bias tool (ROB 2) and Joanna Briggs Institute (JBI) critical appraisal checklists were used for quality assessment. Meta-analysis was performed with Review Manager 5.4, and bibliometric visualization analysis was conducted using VOSviewer 1.6.20 and Bibliometrix (based on R4.4.3). RESULTS: A total of 61 studies were included. AI primarily played two roles in nursing simulation education: peer-type new subject (n = 24) and direct mediator (n = 22). Meta-analysis showed that AI interventions significantly improved nursing students' knowledge (SMD = 1.49, 95% CI [0.55,2.43], p = 0.002) and skills (SMD = 0.66, 95% CI [0.02,1.31], p = 0.04). Bibliometric analysis identified that the United States of America and China were the two main contributing countries in this field, and the key motor themes included generative artificial intelligence, virtual patients, and geriatric care. CONCLUSIONS: AI exerts positive effects on nursing students' knowledge acquisition and skill enhancement in simulation education, with peer-type new subject and direct mediator as the dominant roles. Future research should focus on expanding AI applications in multi-specialty simulation scenarios, activating the data-driven value of machine learning, and strengthening international collaboration and standardization construction, so as to promote the sustainable development of AI-integrated nursing simulation education.

Humans

Plant species identification by genome skimming across the vascular plant tree of life.

Accurate species identification is essential for biodiversity conservation and sustainable use, yet standard plant DNA barcoding often fails to achieve species-level resolution. We present a large-scale empirical evaluation of genome skimming as a tool to improve plant species discrimination. Using standardised data from 1969 individuals representing 475 species from 32 genera across major lineages of the vascular plant tree of life, we compare conventional plastid + internal transcribed spacer (ITS) barcodes with genome skimming approaches. Standard barcoding using rbcL, matK, trnH-psbA and ITS resolved about half of species (49.3%), with six genera showing <&#x2009;25% species discrimination. By contrast, genome skimming enabled the recovery of complete plastid genomes, yielding 57.6% species discrimination. It also generated sufficient nuclear genomic data for additional resolution from k-mer analysis, achieving 66.8% species discrimination - an average gain of 17.5% over standard barcodes - while eliminating cases of extreme failure (<&#x2009;25% resolution). The recovery of complete plastomes and ribosomal DNAs from genome skims also ensures backward compatibility with existing barcode datasets. Our results demonstrate that genome skimming provides data that substantially improves species-level resolution across diverse plant lineages and offers a scalable, high-throughput approach for building comprehensive reference resources to support global biodiversity initiatives.

DNA Barcoding, Taxonomic

Nurse-led titration models of care for heart failure reduced ejection fraction: a systematic narrative review of characteristics, patient outcomes, and healthcare resource utilization.

AIMS: Nurse-led titration (NLT) models of care assist with delivery of guideline directed medical therapy for patients with heart failure with reduced ejection fraction (HFrEF). Effectiveness of NLT is established but there is limited information of characteristics of models, patient outcomes and healthcare resource utilization. To build upon the existing evidence by providing a systematic narrative review of the literature of NLT of medications for patients with HFrEF. This review syntheses characteristics of NLT models of care, patient outcomes and healthcare resource utilization. METHODS AND RESULTS: A systematic narrative literature review with systematic search strategy, identification of results, thematic analysis and narrative synthesis. A search was conducted from 2012 to 2025 in Medline, Cinahl complete, Embase and Cochrane. Sixteen studies of NLT models of care were identified from 1944 screened records. Characteristics of models of care were participation of nurses, multidisciplinary teams, follow-up and common features of service delivery. Patient outcomes of mortality were favourable for those that received NLT. There is some evidence of changes in healthcare resource utilization; studies in which the NLT groups received more HF nurse visits and greater HF medication use also reported reduced rehospitalizations. CONCLUSION: Findings reinforce the published benefits of NLT. Additional studies examining adverse events and quality-of-life outcomes are needed to strengthen the evidence base. Several studies suggest a shift in resource use with NLT, highlighting the need for an economic evaluation to inform a cost-effective model of care.

Humans

Factors influencing the enhancement&#xa0;of the new iron triangle&#xa0;in healthcare organisations.

PURPOSE: A new paradigm, "healthcare's new iron triangle," has been developed to emphasise the technological perspective of healthcare delivery, focusing on automation, value and empathy. The study aims to build a conceptual model and to identify factors for the enhancement of the new iron triangle in healthcare organisations. DESIGN/METHODOLOGY/APPROACH: The healthcare organisation is the primary focus point of the current study. To determine the factors, a survey of the literature and healthcare experts' opinions was conducted. The&#xa0;healthcare professionals validated the identified factors. Data for this study were gathered using a closed-ended questionnaire and scheduled interviews. The study employed "Total Interpretive Structural Modeling methodology and Matriced' Impacts Croise&#xb4;s Multiplication Appliqu&#xe9;&#xb4; a UN Classement/Cross-Impact Matrix Multiplication Applied to a Classification (MICMAC) analysis" to address the "why" and "how" the factors interact and prioritise the identified factors. FINDINGS: The study found that organisational structure (F8), artificial intelligence (F1), innovation (F2) and human resources (F5) are the driving or key factors of the study. RESEARCH LIMITATIONS/IMPLICATIONS: The study primarily focused on identifying factors for the enhancement of a new iron triangle in healthcare organisations. The scope could eventually be expanded to explore more areas. PRACTICAL IMPLICATIONS: Academics and other stakeholders will have a better understanding of the key drivers for the enhancement of the new iron triangle in healthcare organisations. ORIGINALITY/VALUE: In this study, total interpretive structural modeling and cross-impact MICMAC analysis are proposed as an innovative approach to address the new iron triangle in healthcare organisations.

Humans

Examining the impact on quality-of-life of those living with inherited optic neuropathies: an updated systematic review.

BACKGROUND: Inherited optic neuropathies (IONs) cause progressive visual loss and substantially affect quality of life. This updated systematic review aims to synthesize and evaluate evidence on the patient experience of living with IONs, identify currently used assessment tools, and highlight areas for improvement in research and clinical care. METHODS: We systematically searched MEDLINE, EMBASE, PsycINFO, CINAHL, and Scopus for studies on (i) inherited optic neuropathies; (ii) quality of life or health status; (iii) patient-reported outcome measures; and/or (iv) qualitative research. Inclusion was restricted to peer-reviewed studies. Screening, data extraction, and risk of bias assessment were conducted using Covidence. RESULTS: From 1775 unique records, 5 studies met the inclusion criteria. They evaluated quality-of-life outcomes in patients with Leber hereditary optic neuropathy or autosomal-dominant optic neuropathy across 6 countries. Patient-reported outcome measures used included National Eye Institute Visual Functioning Questionnaire-39, National Eye Institute Visual Functioning Questionnaire-25, Short-Form 12 Health Survey, Beck Depression Inventory, and Pittsburgh Sleep Quality Index. Only one study used qualitative interviews to explore the emotional, social, and financial impacts on patients and families. DISCUSSION: This updated systematic review builds upon previous work to further characterize the impact of ION on patients living with these conditions and the tools currently used to assess them. We highlight the need for a multifaceted approach to ION management, combining medical treatment with comprehensive psychosocial support to work toward more patient-centred care and improved quality of life for those living with these challenging conditions.

Humans

Rational design of high-productivity perfusion processes for CHO Cells: From growth inhibitory strategies to model-driven optimization.

While perfusion culture for Chinese hamster ovary (CHO) cells offers advantages such as continuous operation and flexibility, it suffers from product loss through cell bleeding and difficulties in reaching high productivity due to sustained rapid cell growth. Growth inhibitory strategies are widely used to enhance productivity in fed&#x2011;batch processes; however, their practical implementation and comparative effectiveness in perfusion processes remain insufficiently explored. Meanwhile, process development often relies on costly trial&#x2011;and&#x2011;error approaches. Here, we systematically compared three growth inhibitory strategies in perfusion culture-low cell&#x2011;specific perfusion rate (CSPR), sodium butyrate, and mild hypothermia-with respect to cell growth, metabolism, productivity, and product quality. Genome&#x2011;scale metabolic flux sampling analysis revealed that low&#x2011;CSPR and sodium butyrate induce a convergent up&#x2011;regulation of energy metabolism, correlating with greater gains in specific productivity (qp). Building on this insight, we developed a growth&#x2011;kinetic model for the combined low&#x2011;CSPR + butyrate strategy, incorporating parameter uncertainty. This model&#x2011;guided framework enabled the rational design of two distinct high&#x2011;productivity perfusion processes: a sustained mode that achieved robust long&#x2011;term stability alongside substantial productivity gains, and a high&#x2011;intensity mode that pushed qp and daily volumetric titer to their maxima, with increases of up to 108.94% and 190.36%, respectively, in a model CHO cell line with a moderate baseline productivity. Our study provides a proof&#x2011;of&#x2011;concept framework for perfusion intensification, from strategy selection to rational process design.

Animals

Integrative modeling of the genome structure and dynamics in fission yeast.

Genome organization in the nucleus is highly structured and dynamic. Recent advances in genomic technology have enabled the measurement of genome-wide architecture and locus-specific motion, yielding contact maps and live-cell trajectories. However, these outcomes are derived from different modalities and are not directly comparable, with their quantitative integration being a key challenge. Here we establish a genome-wide live-cell imaging platform in fission yeast Schizosaccharomyces pombe, tracking 131 chromosomal loci, along with the spindle pole body (SPB) and nucleolus, to construct a quantitative map of locus dynamics. By integrating these dynamics with contact data through polymer modeling of Hi-C data, we build a physics-based "digital twin" of the S. pombe genome consistent with the spatiotemporal dynamics of interphase chromatin. We validate it against genome-wide mobility patterns and known architectural features, including centromere and telomere clustering. The model also identifies distinct dynamical regimes: centromere- and telomere-proximal loci relax within [Formula: see text]150 s, whereas the remaining loci relax within [Formula: see text]70 s. We measure semiperiodic dynamics of SPB motion, including a characteristic peak near 225 s and [Formula: see text] fluctuations. We use the model with SPB-directed forcing to show how these low-frequency components propagate through the genome to drive genome-wide chromatin displacements. Together, this predictive physics-based modeling framework integrates genome structure and dynamics to reveal how nuclear mechanical driving forces shape chromosome motion, linking mechanically driven chromatin responses to genome maintenance and regulation.

Schizosaccharomyces

Influence of built environment on occupational health of women workers in tea plantations of India: a systematic review.

The built environment, comprising homes, buildings, roads, public spaces, infrastructure, land use, civic design, and amenities, has a considerable influence on occupational health. In India's tea plantations, where women comprise majority of the workforce, the built environment plays a crucial role in determining occupational health. The aforementioned point can be explained by the co-occurrence of living and working conditions, which often coexist in tea plantations, further resulting in vulnerabilities to the health of women workers. Therefore, to understand the influence of built environment on the occupational health of women workers in tea plantations of India, the present paper employs a systematic review using the PRISMA 2020 framework. In the first search, 421 studies were identified, of which 21 studies met all the inclusion criteria. A quality appraisal and risk of bias of the included studies have been undertaken. The results identified that musculoskeletal disorders (MSDs) are the most prevalent occupational health consequence, affecting over 80&#x202f;% of the women workers in Indian tea plantations, substantiated by a range of estimates in the studies reviewed. Gendered disparities in wage earning, self-autonomy, and dual responsibilities often lead to emotional distress, as delineated in minimal of the reviewed studies, grounded on self-disclosed or qualitative analysis. Further, deprived housing conditions and other facilities across the reviewed studies reflect institutional negligence. Therefore, by conducting a systematic synthesis of occupational health of women workers in the Indian tea plantation sector through the lens of the built environment, prior accounts have been extended. Addressing these issues is essential for safeguarding women workers, which will ensure the longevity of the Indian tea industry.

Female

Investing in Canada's nursing workforce: a comprehensive review to inform policy innovations and directions.

BACKGROUND: Health systems worldwide face persistent health workers challenges including nursing shortages, workforce strain, and inequities. In Canada, these challenges have prompted renewed national and provincial reforms to strengthen recruitment, retention, leadership, and sustainability. This paper compares nursing workforce policy directions across Canada, and international jurisdictions to inform policy and planning. METHODS: A cross-country comparative analysis of policies building on a comprehensive national funded review that included an umbrella review of 69 systematic reviews, a comparative policy review of nursing workforce strategies in five jurisdictions, and validation through national horizon-scanning and policy dialogues (n >100). Evidence was analyzed across system, organizational, and individual levels. RESULTS: At the system level, international jurisdictions demonstrate comprehensive, legislated approaches integrating data, governance, and multi-year funding have advanced key nursing strategies. In Canada, the advances show the importance of strategies to have national and provincial/territorial alignment emphasizing leadership, flexibility, and inclusion as key levers. Organizational and individual-level reforms such as mentorship, leadership development, and wellness initiatives are expanding but remain variably evaluated. Experts identified national workforce data strategies and policy integration with embedded evaluation as key enablers to inform scalability and sustainability of implemented strategies. CONCLUSIONS: Canada's nursing workforce reforms are advancing toward coordinated, equity-driven, and evidence-informed strategies. Continued investment in evaluation, leadership, and national integrated data systems along with integrating nursing workforce planning within broader intersectoral planning will consolidate these gains and position Canada as an international leader in sustainable nursing workforce policy.

Canada

Evaluating a coaching intervention for Dementia Care Practice Recommendations in care communities: a cluster randomized controlled trial.

BACKGROUND AND OBJECTIVES: Within care communities, including nursing home and assisted living settings, person-centered dementia care, outlined by the 2018 Alzheimer's Association Dementia Care Practice Recommendations (DCPR), is foundational to quality care and improving staff outcomes. This study evaluates the effectiveness of a 6-month Care Community Coaching Program in enhancing person-centered dementia care and staff outcomes in alignment with the DCPR. RESEARCH DESIGN AND METHODS: A cluster randomized controlled trial was conducted with 77 care communities and 434 staff members-227 from 38 intervention communities and 207 from 39 control communities. Outcomes included employee satisfaction (areas: job satisfaction, team building and communication, scheduling and staffing, training, and management and leadership), person-centered care practices (areas: workplace practices, individualized care and services, caregiver-resident relationships), and dementia care confidence, measured pre- and post-intervention and at 3-month follow-up. A generalized Estimating Equations model was used to estimate intervention effects. RESULTS: Care communities assigned to the coaching intervention showed statistically significant improvements in employee satisfaction and staff perceptions of workplace practices and individualized care. No statistically significant effects on staff perceptions of caregiver-resident relationships or on dementia care confidence were noted. DISCUSSION AND IMPLICATIONS: Findings provide direction for future research and intervention development, including examining coaching's impact on resident quality outcomes, and incorporating skills training into future models. Collectively, findings provide evidence of the effectiveness of a Care Community Coaching Program in improving staff outcomes and person-centered practices, offering a practical path towards improving the lived experience of residents and staff in care communities.

Humans

The Impact of Chatbot Type and Normative Messaging on Chatbot Usage Intention Based on the Health Technology Acceptance Model: Randomized Controlled Trial.

BACKGROUND: Digital health tools, such as health chatbots, may improve access to scalable health support, but adoption remains inconsistent. Existing models do not fully integrate technology acceptance factors with health motivation factors relevant to digital health use. OBJECTIVE: This study proposed and tested the health technology acceptance model and examined whether normative message framing and chatbot type were associated with health motivation, technology acceptance, and intention to use a health chatbot. METHODS: In October 2025, we conducted a 4 &#xd7; 2 between-participants online experiment with 1000 US adults recruited from a nationally representative YouGov panel. Participants were randomized to 1 of 8 conditions varying norm message type (self-oriented, peer-oriented, expert-oriented, or family-oriented) and chatbot type (AI-powered or rule-based) in a cancer prevention and genetic risk information scenario. Outcomes included descriptive norms, injunctive norms, perceived susceptibility, perceived severity, perceived benefits, self-efficacy, perceived ease of use, trust, privacy concerns, and usage intention. Data were analyzed using a multivariate ANOVA with Bonferroni-adjusted post hoc tests and multiple linear regression. RESULTS: Peer-oriented and family-oriented messages produced higher usage intention than expert-oriented messages, and peer-oriented messages also increased descriptive norms, injunctive norms, self-efficacy, and trust. AI-powered chatbots were associated with higher usage intention (P=.02) and greater trust (P=.008) than rule-based chatbots. In regression analyses, the model explained 50.8% of the variance in usage intention. Usage intention was positively associated with descriptive norms (&#x3b2;=0.087; P=.003), injunctive norms (&#x3b2;=0.078; P=.009), perceived susceptibility (&#x3b2;=0.051; P=.03), perceived benefits (&#x3b2;=0.253; P<.001), and trust (&#x3b2;=0.33; P<.001), and negatively associated with perceived severity (&#x3b2;=-0.047; P=.049) and privacy concerns (&#x3b2;=-0.11; P<.001). Perceived ease of use and self-efficacy were not significant predictors. CONCLUSIONS: The health technology acceptance model was a useful framework for explaining the intention to use a health chatbot by combining technology acceptance and health motivation constructs. Both social design features and chatbot design features shaped adoption-related beliefs, with peer-oriented and family-oriented framing and AI-powered chatbots showing particular promise. Trust and privacy concerns remained central determinants of intended use.

Humans

Characterization of the Immune Response after Oral Cholera Vaccination (OCV) and Effects of Mycophenolate Mofetil on Priming of this Immune Response-A Randomized, Placebo-Controlled Trial.

Mycophenolate mofetil (MMF) is an immunosuppressive drug widely used by solid organ transplant recipients. Although it is known that MMF suppresses immune responses, its exact effects on specific vaccinations have not been investigated yet. Mucosal vaccinations are increasingly used, such as a cholera vaccination consisting of two oral immunizations (oral cholera vaccination; OCV). This study aimed to investigate the specific immunosuppressive effects of MMF use during the first dose of OCV in a randomized, placebo-controlled trial in healthy volunteers. Moreover, the study aimed to characterize the immune response provoked by OCV in detail. This randomized, placebo-controlled, single-blind trial included 16 healthy volunteers, each receiving two doses of Dukoral&#xae; and an intranasal rechallenge. Outcome measures were serum antibody responses (IgA and IgG) and IgA levels in saliva. Additionally, peripheral blood mononuclear cells (PBMCs) of participants were investigated for ex&#xa0;vivo cytokine production and expression of tissue-specific homing markers after OCV. There were considerable serum IgA and IgG responses after vaccination. MMF-treated volunteers still showed a significant cholera antibody response, though data suggest a potential suppression by MMF without reaching statistical significance. There was no substantial IgA response in saliva. Investigation of PBMCs from OCV-treated participants showed a Th2 skewing with increased ex&#xa0;vivo production of TNF, IL-2, IL-5, IL-13, and IL-22 compared to the placebo group. Taken together, this study provides a framework for future clinical pharmacology studies building on OCV as a challenge model and for further investigation of specific effects of MMF on mucosal vaccination responses.

Humans