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PubMed2026

Improving insurance deduction identification: a hybrid artificial intelligence model using machine learning and expert systems.

PURPOSE: Financial challenges in healthcare systems worldwide, especially in low- and middle-income countries like Iran, have increased hospitals' reliance on insurance reimbursements. Unrecognized insurance deductions often cause severe financial shortages, making efficient deduction management crucial. This study aimed to design a hybrid intelligent system for identifying and predicting insurance deductions by combining machine learning and expert system frameworks. DESIGN/METHODOLOGY/APPROACH: A mixed-methods design was applied in four stages. First, a scoping review identified the causes and patterns of insurance deductions. Second, interviews with 15 insurance experts produced a validated checklist and a dataset from inpatient billing records. Third, using the CRISP-DM methodology, machine learning algorithms were developed and tested in SPSS Modeler alongside a fuzzy expert system developed in MATLAB. Finally, the model was validated using the holdout method. FINDINGS: Four categories of deduction drivers were identified: service provision, registration errors, document submission issues, and revenue conversion processes. The CHAID decision tree outperformed other algorithms with a 99% precision rate and the lowest Mean Absolute Error (9.43). A brief assessment of potential overfitting was conducted to ensure that the CHAID model's high accuracy was interpreted cautiously and supported by the validation results. The fuzzy expert system with validated rules was adaptable for deduction classification, especially for cases unsuitable for quantitative modeling. ORIGINALITY/VALUE: The hybrid model improves detection and prevention of deductions, offering actionable insights for hospital administrators, insurers, and policymakers. Its implementation can enhance hospital information systems, streamline claims processing, and optimize revenue management amid financial constraints.

Machine Learning↗

PubMed2025

Exploring determinants of vaccine hesitancy among healthcare professionals: a systematic literature review.

INTRODUCTION: This systematic review aims to assess determinants of vaccine hesitancy (VH) among healthcare professionals, to identify knowledge gaps and inform targeted training programs. RESEARCH DESIGN AND METHODS: A systematic search of PubMed and Scopus was conducted in February 2024. PRISMA criteria were applied, and methodological quality was assessed using a cross-sectional study evaluation tool. Studies addressing HCWs' VH determinants, including knowledge, attitudes, communication, and organizational factors, were included. RESULTS: Out of 1394 records, 221 articles were included. Reported prevalence of VH among HCWs varied across studies, reflecting differences in professional roles, settings, and vaccines studied. Key determinants included gaps in knowledge, personal beliefs, organizational barriers, and communication skills. The review highlights the importance of evidence-based information, continuing education, and effective communication in addressing VH among HCWs. CONCLUSIONS: Educational and organizational interventions are essential to improve HCWs' knowledge, attitudes, and practices regarding vaccination. Strengthening vaccine education, fostering effective communication, and addressing organizational challenges can reduce hesitancy and support HCWs in promoting vaccination among patients. Future initiatives should consider the diversity of educational settings, professional roles, and training requirements across healthcare systems.

Humans↗

PubMed2026

Comparison of immunogenicity, safety, and efficacy of EVA71 vaccine in children: a systematic review and meta-analysis.

INTRODUCTION: Enterovirus 71 (EV-A71) is a principal cause of hand, foot, and mouth disease (HFMD), potentially leading to severe neurological complications in children. Inactivated EV-A71 vaccines have been introduced. This study compares the immunogenicity, safety, and efficacy of EV-A71 vaccines versus placebo in pediatric populations. RESEARCH DESIGN AND METHODS: Following a PROSPERO-registered protocol, RCTs involving EV-A71 in children were identified via PubMed, Scopus, Cochrane, and ClinicalTrials.gov. Two independent reviewers performed screening, extraction, and RoB assessments (RoB 2.0). RESULTS: Five phase III RCTs involving 36,659 children were included. EV-A71 vaccination significantly increased seropositivity across follow-up periods, including early (RR 5.8), medium-term (RR 3.09), and long-term (RR 2.95) response. Seroconversion was significantly higher in the vaccinated group (pooled RR 13.04, 95% CI 2.80-60.61; p < 0.001). Geometric mean titers, analyzed using the ratio of means approach, were significantly higher in the vaccinated group during early and medium-term follow-up. Vaccine efficacy against EV-A71-associated HFMD exceeded 98% (pooled RR 0.02, 95% CI 0.01-0.09; p = 0.0028; I2 = 50%). Solicited local and systemic adverse events were mild and comparable between groups. CONCLUSION: Inactivated EV-A71 vaccines robust immunogenicity, high clinical efficacy, and an acceptable safety profile in children. Future studies should explore long-term protection, booster schedules, and multivalent formulations against non-EV-A71 serotypes.

Humans↗

PubMed2026

Quantitative assessment of the fingerprint evidential value using machine learning.

Fingerprints as physical evidence have long supported criminal investigation and adjudication. In practice, however, fingerprint identification relies mainly on examiners' experience. Furthermore, expert opinions tend to be categorical, even though the opinions with the same conclusion could differ substantially in evidential strength. To quantitatively assess fingerprint evidential value, this study proposes a machine learning-based framework as an interpretable decision-support tool. A lightweight residual one-dimensional convolutional neural network was constructed, incorporating channel recalibration and a similarity-driven attention mechanism to learn adaptive contribution weights for different matched minutiae (minutiae for short). Controlled experiments revealed that the predicted evidential value increased with the number of minutiae and was significantly influenced by the quality of minutiae. With 10 minutiae, the mean predicted scores were 4.49, 7.00, and 9.09 for blurred, moderately blurred, and clear minutiae, respectively. Multiple regression analysis indicated that replacing a pair of blurred minutiae with a pair of clear minutiae increased the score by 0.492, whereas replacing it with a pair of moderately blurred minutiae increased the score by only 0.216. By mapping predicted scores to graded levels of evidential strength, the framework contributes to a paradigm shift from categorical expert opinions to graded ones, helping courts evaluate fingerprint evidence more scientifically.

Humans↗

PubMed2026

Delphi study robot consenso: Strategies for the implementation of robotic surgery in general surgery in the Spanish hospital network.

INTRODUCTION: The implementation of robotic surgery in public hospitals presents multiple logistical, educational, and organizational challenges. In the absence of unified guidelines, a national consensus is required to optimize its safe and efficient adoption. This study aimed to establish a set of consensus-based and measurable recommendations for the implementation of robotic surgery programs in hospitals within the Spanish National Health System, based on the experience of centres with established robotic programs and intended to serve as guidance for hospitals that are initiating or planning their implementation. METHODS: A national Delphi study was conducted with the participation of robotic surgery experts from 26 public hospitals. The expert panel was composed exclusively of digestive surgeons with experience in robotic surgery. Three iterative rounds of expert panel evaluation were conducted between March 2024 and March 2025. The questions were grouped into five thematic blocks. Consensus was defined as an agreement level of ≥66.7%. Kendall's W coefficient was used to assess concordance. RESULTS: High levels of consensus were achieved on key aspects related to infrastructure, structured training, cost evaluation, and quality assurance mechanisms. Areas of disagreement were also identified, such as the need for a dedicated anaesthesiologist, purchase of accessory instruments during the initial phase, and official accreditation pathways. CONCLUSIONS: This study provides a guideline for developing a national robotic surgery strategy focused on patient safety, program sustainability, and standardized training of surgical teams. These recommendations can guide hospitals at different stages of robotic technology adoption. Given that the consensus was reached from an exclusively surgical perspective, the recommendations focus on patient safety, program sustainability, and standardized training of the surgical team, and should be interpreted in an adaptable manner according to each centre's context, case volume, and available resources.

Cirugía Asistida por Robot↗

PubMed2026

The future of precision oncology and artificial intelligence in Belgium: scenarios and policy responses.

PURPOSE: Precision medicine, also known as personalized medicine, enables the provision of tailored health services to patients. In the prevention, early detection, and treatment of cancers, precision medicine is highly promising, given the increasing use of genomic profiling for diagnosis and adapting therapies in several tumor types. Artificial Intelligence (AI) can support this process by analyzing vast amounts of relevant data. However, high-quality data and financial investments in the health system are essential for the implementation of precision medicine and AI solutions in routine cancer care. DESIGN/METHODOLOGY/APPROACH: Building on the quantitative outcomes of a foresight exercise published in another study, this article collects qualitative data to gain more detailed insights into the future of precision oncology in Belgium and discusses the role of AI in this field. It reports the results of a series of expert workshops, focusing on four hypothetical future scenarios that are centered around technological and economic issues that must be overcome for the widespread use of precision oncology in Belgium. FINDINGS: The study concludes that all four scenarios discussed in the workshops would require supportive policy measures in Belgium, which should go beyond mere technological and economic considerations, such as involving patient associations and the public in policy design or creating multi-disciplinary expert groups for precision medicine. ORIGINALITY/VALUE: To the best of our knowledge, this is the first study to employ foresight methodology to illustrate possible future scenarios, scrutinize feasible approaches for implementing precision oncology in Belgium, and discuss the use of AI in this context.

Belgium↗

PubMed2026

Stroke risk following BNT162b2 vaccination: a systematic review and meta-analysis of self-controlled case series studies.

INTRODUCTION: Whether BNT162b2 (Pfizer-BioNTech) vaccination increases stroke risk remains a public health concern. This is the first meta-analysis to synthesize self-controlled case series (SCCS)-derived stroke risk estimates specifically for BNT162b2 vaccination. METHODS: PubMed and Embase were searched from inception through 9 May 2026, following PRISMA 2020 guidelines. Eight eligible SCCS studies were pooled using a random-effects model with restricted maximum likelihood (REML) estimation and the Knapp-Hartung adjustment. RESULTS: Eight studies across six countries encompassing several million vaccinated individuals were included. The pooled incidence rate ratio (IRR) was 0.967 (95% CI 0.892-1.049; I2 = 69.2%), indicating no statistically significant increase in stroke risk. Subgroup analyses showed no evidence of effect modification across continent, risk-window length, dose category, SCCS variant, or age group. CONCLUSIONS: These findings provide no evidence of increased short-term stroke risk following BNT162b2 vaccination at the population level. The observed heterogeneity appeared to be partly driven by methodological differences rather than true biological variation in vaccine effect.

Humans↗

PubMed2026

Do vaccinated cases transmit measles? A systematic review and meta-analysis.

INTRODUCTION: We reviewed evidence on whether vaccinated individuals can transmit measles and conducted a meta-analysis to understand transmission characteristics. METHODS: We searched and extracted data from peer-reviewed and gray literature and included studies reporting measles transmission events from vaccinated individuals. We meta-analyzed the data to calculate the median number of transmissions from vaccinated cases by measles burden, number of doses, and time since first and last dose. RESULTS: We identified 11,911 peer-reviewed and 22 gray literature records and included 33 articles in our review. Seventy individuals who had received 1 or more doses of measles-containing vaccine transmitted measles virus, resulting in 237 secondary cases. Vaccinated transmitters in eliminated areas were older (median age of 19 years (IQR: 3, 21)) than those in non-eliminated areas (median age 16 years; IQR 13, 18) (p = 0.12). Additionally, 91% (30/33) of studies provided data on subsequent transmission generations, leading to 812 measles cases traced back to vaccinated individuals, with a median of 4 (IQR: 1, 10) cases per vaccinated transmitter. CONCLUSION: Measles transmissions from vaccinated cases, although relatively uncommon, must be considered in public health investigations, as such transmissions can contribute to outbreaks.

Adolescent↗

PubMed2026

Population-level impact of HPV vaccination: a global systematic review of ecological, cross-sectional, and cohort studies.

BACKGROUND: Human papillomavirus (HPV) causes approximately 4.5% of cancers globally, with the highest burden in low- and middle-income countries (LMICs). Since their introduction in 2006, HPV vaccination programs have led to substantial declines in HPV-related outcomes, although impact varies across settings. RESEARCH DESIGN AND METHODS: We conducted a systematic review to evaluate the population-level impact of HPV vaccination on HPV infection, cervical intraepithelial neoplasia grade 2 or higher (CIN2+), genital warts, invasive cervical cancer (ICC), and oropharyngeal cancer (OPC), and examined the influence of coverage, age at initiation, and vaccine type. The review followed PRISMA 2020. RESULTS: Of 13,549 records screened, 63 were included: 9 assessed HPV infection, 24 on CIN2+, 25 on genital warts, and 7 on ICC. Greatest reductions were observed in settings with at least 70% coverage and early vaccination prior to sexual debut, typically achieved through school-based programs. Reported declines ranged from 58-100% for HPV infection, 30-88% for CIN2+, 60-90% for genital warts, and 70-88% for ICC. CONCLUSIONS: HPV vaccination offers strong protection, especially when delivered early and at high coverage within schools. Expanding access and prioritizing underserved populations are essential to achieving global cancer prevention goals. Limitations include heterogeneity across designs, outcome definitions, and follow-up.

Humans↗

PubMed2026

Approaches to observational study designs and analytical options to evaluate the safety of multi-dose vaccines: a systematic review.

INTRODUCTION: Observational studies require careful considerations when evaluating the safety of multidose vaccines. We reviewed design and analytical approaches in observational studies evaluating the safety of multidose vaccines in the post-licensure phase. METHODS: EMBASE, MEDLINE, Web of Science, and Scopus (2018-2022) were searched for hypothesis-testing studies evaluating the safety of multidose vaccines. Key features from frequently used designs were extracted. RESULTS: Among 123 eligible studies, cohort (46%) and self-controlled case series (SCCS)/self-controlled risk interval (SCRI) (40%) followed by case-control (12%) were the most common designs, and 15% of studies used multiple designs. Among cohort studies evaluating multiple doses, vaccination date (36%) and cohort entry with time-updated exposure status (32%) were frequent approaches used to define time zero. Twenty-eight percent of cohort studies did not report time zero; all but one evaluated COVID-19 vaccine effect on post-delivery and fertility-related outcomes. For SCCS/SCRI, 64% of studies accounted for event-dependent exposures, mainly by including pre-exposure periods (53%) and modified SCCS model (48%), while 20% employed multiple correction strategies. Among studies using multiple designs, 68% reached consistent conclusions. CONCLUSIONS: SCCS/SCRI and cohort designs dominate multidose vaccine safety studies. Clear reporting on time zero in pregnancy and fertility-related cohort studies, and on addressing event-dependent exposures in SCCS/SCRI studies is needed, along with guidance on interpreting results from multiple designs.

Humans↗

PubMed2026

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↗

PubMed2026

Adherence and efficacy of the 0 - 7 - 21-day versus the 0 - 1 - 6-month hepatitis B vaccination schedules among people who use drugs: a two-year randomized controlled trial.

BACKGROUND: To compare the adherence and efficacy between the 0 - 7 - 21-day and the 0 - 1 - 6-month hepatitis B virus (HBV) vaccination schedules among people who use drugs (PWUD) in China. RESEARCH DESIGN AND METHODS: A randomized controlled trial was conducted in 1261 HBV-susceptible PWUD from compulsory isolated detoxification centers (CIDCs) and methadone maintenance treatment (MMT) clinics in Xi'an. A 20 µg per-dose vaccine was used. HBV surface antibody (anti-HBs), surface antigen, and core antibody were tested at months 7, 15, and 22 after the first dose. RESULTS: Third-dose coverage was significantly higher in the 0 - 7 - 21-day group (74.40%) than in the 0 - 1 - 6-month group (51.58%, p < 0.001), mainly driven by participants from CIDCs (77.75% vs. 45.69%). Anti-HBs positive rates at months 7, 15, and 22 among participants who completed all three doses were significantly higher for the 0 - 1 - 6-month schedule (90.71%, 76.82%, and 67.35%) than for the 0 - 7 - 21-day schedule (74.23%, 49.40%, and 40.95%; all p < 0.001). HBV infection incidence was similar between schedules, but significantly different between vaccinees and non-vaccinees (p = 0.018). CONCLUSIONS: The 0 - 7 - 21-day schedule substantially enhances three-dose completion in PWUD, but induces a notably weaker anti-HBs response and persistence. Schedules should be selected based on the management models for PWUD and their individual characteristics. CLINICAL TRIAL REGISTRATION: Chinese Clinical Trial Registry (ChiCTR1900022403).

Humans↗

PubMed2026

Artificial intelligence-assisted detection and optical differentiation of colorectal lesions in Lynch syndrome surveillance (CADLY2): a multicentre, open-label, randomised controlled superiority trial.

BACKGROUND: Artificial intelligence (AI)-based computer-aided detection (CADe) systems improve adenoma detection in average-risk colorectal cancer screening. Meanwhile, evidence in Lynch syndrome surveillance is sparse and inconsistent. We assessed the effect of CADe on adenoma detection during Lynch syndrome surveillance. Computer-aided optical diagnosis (CADx) performance for optical differentiation of colorectal lesions was evaluated as a secondary aim. METHODS: CADLY2 was an international, multicentre, open-label, randomised controlled superiority trial at nine specialised hereditary cancer surveillance centres in Belgium, Germany, the Netherlands, and Spain. Adults aged 18 years or older with genetically confirmed Lynch syndrome scheduled for surveillance colonoscopy were randomly assigned (1:1) to high-definition white-light (HD-WL) colonoscopy alone or to HD-WL colonoscopy with computer-aided assistance from CAD EYE (Fujifilm, Tokyo, Japan). CAD EYE was used for CADe during withdrawal and for CADx after lesion detection. Randomisation was done centrally through a secure web-based system using Pocock's minimisation algorithm with a stochastic component and was stratified by centre, sex, previous colorectal cancer, underlying pathogenic variant, and interval since previous colonoscopy. Allocation concealment was ensured through the centralised web-based system. Patients were masked to group allocation until the start of withdrawal in procedures with mild sedation, or until completion of the procedure in procedures with propofol-based sedation. Endoscopists were not masked. The primary outcome was adenoma detection rate, defined as the proportion of patients with at least one histopathologically confirmed adenoma, analysed in the full analysis set (defined as all randomly allocated patients with available data for the primary outcome). The diagnostic performance of the CADx system was evaluated as a secondary outcome. The safety analysis set comprised all randomly allocated patients who underwent a study colonoscopy. This study is registered with the German Clinical Trials Register, DRKS00030695, and is completed. FINDINGS: Between May 9, 2023, and Oct 30, 2025, 757 patients were randomly allocated to HD-WL colonoscopy (377 patients) or to AI-assisted colonoscopy (380 patients); 733 patients were included in the full analysis set (369 HD-WL and 364 AI-assisted). The median age was 49 years (IQR 38-59) in the HD-WL group and 50 years (38-59) in the AI-assisted group; 213 (58%) were female and 156 (42%) male in the HD-WL group, and 207 (57%) were female and 157 (43%) male in the AI-assisted group. The adenoma detection rate was 30·9% (114 of 369 patients) with HD-WL versus 33·8% (123 of 364 patients) with CADe assistance (odds ratio 1·14 [95% CI 0·83-1·57], p=0·41). For CADx differentiation of neoplastic versus non-neoplastic lesions in the paired lesion-level analysis, with histopathology as the reference standard and sessile serrated lesions and traditional serrated adenomas classified as non-neoplastic, CADx sensitivity was 85·9% (95% CI 82·0-89·1) and specificity was 91·4% (89·4-93·0). Three adverse events occurred in the AI-assisted group: two mild post-polypectomy bleedings and one serious pulmonary embolism or deep venous thrombosis unrelated to the procedure. No adverse events occurred in the HD-WL group. INTERPRETATION: CADe-assisted colonoscopy did not show the absolute improvement in adenoma detection rate that was assumed in the prespecified sample-size calculation. CADx did not clearly improve lesion differentiation beyond expert optical diagnosis in expert Lynch syndrome surveillance settings. FUNDING: Third-party research funding of the National Center for Hereditary Tumor Syndromes, University Hospital Bonn.

Humans↗

PubMed2026

Meniscal preservation in the age of biologics: toward a quantitative decision algorithm for personalized repair.

BACKGROUND: Despite advances in arthroscopic repair and biologic augmentation, surgical indication for meniscal tears remains heterogeneous. No standardized framework currently integrates biomechanical, clinical, and biological determinants to guide repair versus resection. PURPOSE: To develop a quantitative decision model-the Meniscal Preservation Score (MPS)-that unifies biomechanical and biological evidence to stratify reparability potential and standardize treatment selection in meniscal surgery. METHODS: A systematic evidence synthesis conducted in accordance with PRISMA 2020 reporting standards of studies published from 2000 to 2025 in PubMed, Embase, and Scopus identified key determinants of meniscal healing. Five consistent predictors-patient age, vascularity, tear morphology, associated pathology, and activity profile-were weighted through a two-round modified Delphi consensus among ten experienced knee surgeons. The resulting 0-9-point MPS was incorporated into a stepwise decision tree linking lesion morphology, biological context, and surgical strategy. Conceptual validation used 50 simulated cases and a retrospective cohort of 45 patients to test agreement between algorithm recommendations and expert surgical decisions. RESULTS: The MPS achieved 86% concordance with expert judgment in simulation and 84% agreement in clinical validation. In this retrospective exploratory cohort, cases in which surgical management was concordant with MPS recommendations demonstrated higher mean IKDC scores at 24 months and lower observed reoperation rates. These findings should be interpreted as associative rather than causal, as treatment allocation was not controlled and discordant cases may have represented inherently more complex pathology. CONCLUSION: The MPS represents an evidence-informed decision-support framework designed to systematize reparability assessment. While exploratory analyses suggest structural coherence with expert reasoning, prospective implementation and external validation are required before clinical adoption as a predictive tool. LEVEL OF EVIDENCE: conceptual model with exploratory validation.

Humans↗

PubMed2026

Linked-color imaging with computer-aided detection and the proximal adenoma miss rate: a randomized tandem trial.

BACKGROUND AND AIMS: Linked-color imaging (LCI) aids the detection and characterization of lesions. Computer-aided detection (CADe) systems have been introduced to improve lesion detection during colonoscopy. Although several studies have been reported regarding LCI, few have investigated the combination of LCI and CADe. This study aimed to evaluate the efficacy of LCI with CADe colonoscopy compared to conventional white-light colonoscopy. METHODS: A single-center, randomized tandem trial was conducted. Participants referred for first-time colonoscopy after fecal immunochemical test (FIT)-positive, asymptomatic screening, or surveillance colonoscopy were randomized (1:1) to undergo CADe-assisted colonoscopy of LCI or white-light imaging (WLI) in the right side of the colon. The primary outcome was adenoma miss rate (AMR) in the right side of the colon. Secondary outcomes included polyp miss rate (PMR), diminutive adenoma miss rate (dAMR), sessile serrated lesion miss rate (SSLMR), advanced adenoma miss rate, advanced neoplasia miss rate, flat-type lesion miss rate (FMR), and the differences in miss rates based on expertise. RESULTS: Among 232 randomized participants, 209 were analyzed (LCI/CADe: 102; WLI: 107). AMR (WLI: 39% vs LCI/CADe: 20%; P = .001), PMR (42% vs 18%; P < .001), and dAMR (42% vs 21%; P = .003) were significantly lower in the LCI/CADe arm, particularly among experts. SSLMR (46% vs 0%), advanced AMR (30% vs 0%), advanced neoplasia miss rate (25% vs 0%), and FMR (27% vs 5.6%) were lower in LCI/CADe, although without statistical significance. CONCLUSIONS: Compared to conventional colonoscopy, LCI with CADe colonoscopy resulted in a statistically significant decrease, especially in AMR. (UMIN 000050685).

Humans↗

PubMed2026

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 × 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 (β=0.087; P=.003), injunctive norms (β=0.078; P=.009), perceived susceptibility (β=0.051; P=.03), perceived benefits (β=0.253; P<.001), and trust (β=0.33; P<.001), and negatively associated with perceived severity (β=-0.047; P=.049) and privacy concerns (β=-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↗

PubMed2026

A STORM-based protocol for nanoscale imaging and quantitative analysis of protein-associated and phospholipid-associated structures in natural rubber.

Stochastic Optical Reconstruction Microscopy (STORM) enables nanoscale mapping of molecular components beyond the diffraction limit; however, its reproducible implementation in hydrophobic polymer matrices remains challenging because fluorescence-labeling specificity, fluorophore photoswitching, three-dimensional localization, chromatic registration, and quantitative image analysis must be carefully controlled. This protocol presents a standardized experimental workflow for dual-color labeling, astigmatism-based three-dimensional STORM acquisition, and quantitative analysis of protein-associated and phospholipid-associated structures in natural rubber (NR). The workflow covers sample pretreatment, Cy5 NHS ester labeling of protein-associated primary amines, DiI labeling of phospholipid-rich domains, STORM imaging-buffer preparation, three-dimensional single-molecule localization, dual-channel registration, generation of standardized xy projections, aggregate-size analysis, and projected lateral spatial correlation assessment. Reproducibility is supported by defined acquisition and localization criteria, three independent sample preparations with at least five fields of view analyzed per condition, and unlabeled, single-color, dye-only matrix, and processing-associated Cy5 controls. Mean lateral localization precisions of 11.8 ± 2.3 nm for Cy5 and 13.5 ± 2.9 nm for DiI were obtained, while two-dimensional Fourier ring correlation analysis of the xy projections yielded effective lateral image resolutions of approximately 25 and 28 nm, respectively. Image-based particle segmentation and localization-coordinate-based density-based spatial clustering of applications with noise (DBSCAN) were applied to standardized xy projections as complementary quantitative approaches. Application of the protocol to untreated, centrifuged, and protease-treated NR samples demonstrated treatment-associated changes in the detected abundance and projected size distributions of protein- and phospholipid-associated aggregates, together with a non-monotonic change in their projected lateral spatial correlation. These observations describe alterations in nanoscale organization but do not, by themselves, establish stable protein-phospholipid complex formation. Unlike previous studies that primarily demonstrated the feasibility of STORM imaging in rubber materials, the principal contribution of this work is an end-to-end, step-by-step protocol incorporating defined controls, three-dimensional localization, image-quality metrics, chromatic-registration procedures, and complementary quantitative-analysis pipelines for non-expert users. The workflow may be adaptable to other hydrophobic polymers and soft-material systems after appropriate optimization and validation.

Rubber↗

PubMed2026

Community-driven advances in computational mass spectrometry: The perspective of EuBIC-MS members.

Advances in data acquisition, artificial intelligence, and integrative bioinformatics are driving the rapid evolution of computational mass spectrometry, and in turn, transforming modern proteomics, metabolomics, and lipidomics. These developments have greatly increased the scale and complexity of mass spectrometry data, underscoring the importance of evolving accurate, transparent, efficient and reproducible data processing workflows. Addressing these challenges requires collaborative innovation that brings together expertise in software engineering, statistics, and biology. The European Bioinformatics Community for Mass Spectrometry (EuBIC-MS), an initiative of the European Proteomics Association (EuPA), fosters a culture of open, community-driven development through its biennial Developers Meetings and Winter Schools. This commentary summarizes the scientific background and outcomes of the EuBIC-MS Developers Meeting 2025, which took place in Novacella, Italy. Three keynote presentations highlighted major frontiers in the field: deep proteome and phosphoproteome profiling, text mining for protein-protein interaction extraction, and scalable proteomics for AI-driven drug discovery. Seven community-selected hackathons addressed emerging challenges such as single-cell proteomics data analysis, FAIR metadata extraction, deep learning frameworks, R-Python interoperability, and DIA validation. Together, these efforts demonstrate the potential for scientific and technical innovation to arise from open collaboration, and highlight how community-driven initiatives can accelerate progress in computational mass spectrometry. SIGNIFICANCE: Modern proteomics increasingly depends on computational advances to translate complex, high-dimensional data into biological knowledge. The EuBIC-MS Developers Meeting 2025 exemplifies how community-driven collaboration can directly accelerate this process by bringing together experts from bioinformatics, statistics, and experimental proteomics to co-develop open, interoperable, and reproducible analytical tools. By fostering shared software frameworks, transparent benchmarking, and collaborative problem solving, the EuBIC-MS community helps ensure that technological innovation translates into reliable biological insights. This collaborative model strengthens the foundation for quantitative, system-level understanding of proteomes and establishes a sustainable path for integrating artificial intelligence and next-generation data acquisition into routine biological discovery. This commentary shows some current highlights in the field of computational mass spectrometry and community-based approaches undertaken during the most recent Developers Meeting to solve these challenges. The approaches discussed and initiated during the meeting - ranging from deep proteome profiling and phosphosite mapping to text mining, single-cell data analysis, and FAIR metadata extraction - address key bottlenecks that currently limit the biological interpretability and comparability of proteomics data.

Mass Spectrometry↗