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PubMed2026

Decoding the spatiotemporal patterns of food spoilage microbial communities: Integrating multi-omics and artificial intelligence to enable precision preservation.

In the global food supply chain, food wastage caused by spoilage has resulted in significant economic losses, food shortages, and environmental pressure. This process is fundamentally driven by the spatiotemporal dynamics of microbial communities. However, traditional research methods struggle to elucidate the complex mechanisms of spatial heterogeneity, interspecies interactions, and functional succession. This limits the development of effective preservation strategies. This review systematically reviews the cutting-edge progress of integrating multi-omics technologies and artificial intelligence (AI) to study food spoilage microbial communities, breaking through this bottleneck. We propose an intelligent theoretical framework that could potentially analyze microbial metabolic activities and predict dynamic shelf life if implemented. The conceptual framework integrates multidimensional data, including spatial metabolomics, temporal metatranscriptomics, single-cell transcriptomics, and longitudinal metagenomics. It can also be combined with AI models, such as graph neural networks. The article elaborates on the principles and applications of spatio-temporal monitoring technologies, such as nano secondary ion mass spectrometry, hyperspectral imaging, and the Internet of Things sensing. Through illustrative cases of typical perishable foods, it also explores how such a multi-omics - AI system might be applied to spoilage warning and precise intervention. Additionally, the article addresses the current challenges in data coverage, model generalization, and federated learning implementation. Then the research further explores emerging areas such as engineered probiotics, edge AI, and microfluidic sensing. These areas are targeted at transforming food preservation from an empirical control approach to a data-driven, precise regulatory framework. This transformation provides theoretical support and technical approaches for developing a smart, sustainable food preservation system.

Multiomics↗
PubMed2026

Virtual Reality Mastoidectomy as Precadaver Training for Novices: A Randomized Crossover Study.

OBJECTIVES: To compare cognitive load during virtual reality (VR) simulation and cadaveric dissection (CD) mastoidectomy training in novice learners. To determine whether training order influences cognitive load, characterize cognitive load progression during the procedure, and assess whether VR training improves subsequent cadaveric performance. METHODS: In this randomized crossover study, 24 core surgical trainees with no prior mastoidectomy experience performed a cortical mastoidectomy in both VR and CD settings. Participants were randomized to either VR-first or CD-first training sequences. Cognitive load was measured using a bespoke auditory reaction-time device at baseline and 10, 30, and 50&#x2009;min. Relative reaction time (RRT) served as an objective index of cognitive load. Cadaveric performance was assessed using the Modified Welling Scale by two blinded otologists. RESULTS: Cognitive load was significantly lower during VR than CD, with mean RRT rising 26% from baseline in VR versus 60% in CD (p&#x2009;<&#x2009;0.001). Training order did not affect cognitive load in either modality, and RRT increased progressively throughout mastoidectomy in both VR and CD. Participants who began with VR achieved significantly higher cadaveric performance scores than those who began with CD (mean 9.50 vs. 4.96; p&#x2009;<&#x2009;0.001), and inter-rater reliability for performance scoring was high. CONCLUSION: VR mastoidectomy reduces cognitive load and enhances subsequent cadaveric performance in novice trainees, supporting its role as a cognitively optimized precadaver training modality that complements, rather than replaces, cadaveric dissection. These findings suggest VR enhances early learning efficiency and resource utilization in novice otolaryngology training. LEVEL OF EVIDENCE: N/A.

Humans↗
PubMed2026

Individual differences in brain dynamics across a social cognition network induced by cortico-cerebellar tDCS in adults with autism spectrum disorder (ASD).

Autism spectrum disorder (ASD) is a neurodevelopmental condition with core diagnostic domains of social communication impairments, restricted interests and repetitive behaviors. Idiosyncratic brain organization is a potential hallmark of ASD. Previous transcranial direct current stimulation (tDCS) studies often targeted dorsolateral prefrontal cortex, with changes oin brain dynamics averaged across the cohort. We utilized a magnetoencephalographic (MEG) array to characterize individual differences in brain dynamics induced by cortico-cerebellar tDCS across nodes of a social cognition network. A randomized, sham-controlled, double-blind, within-subject clinical trial was conducted in a cohort of 24 young adults with ASD or high autistic traits. Two separate sessions of computerized social learning activities were combined with verum/sham tDCS, with anodal electrode over right temporoparietal junction (TPJ) and cathode on right deltoid. Following stimulation, theta- and alpha-band activity were evaluated within nodes of a social cognition network: bilateral TPJ, fusiform, medial prefrontal cortex and Crus I/II of cerebellum. Idiosyncratic participant-specific up- and down-regulation of theta- and alpha-band activity occurred across the network. Activity in right Crus I/II, a region inundated by the stimulation current, strongly correlated with the change of activity summed across all cerebral cortical nodes in theta- but not alpha-band. Intrinsic theta-band activity is believed to mediate input/output relationships in cerebellar cortex and to drive synaptic plasticity. These results suggest that theta-band stimulation of cerebellar cortex might be an effective therapy for individuals on the autism spectrum who present with cerebellar hyperactivity.

Humans↗
PubMed2026

A systematic review of the impact of Mental Health First Aid on medical, nursing and allied healthcare professional students.

BACKGROUND: Healthcare professional (HCP) students are at high risk of mental health problems, but stigma and fear of career repercussions often deter them from seeking help. Mental Health First Aid (MHFA) is a globally disseminated course teaching the public to identify and respond to people experiencing mental health problems. MHFA training may address some of the challenges faced by HCP students, by improving mental health knowledge and by enhancing well-being and peer support. AIMS: To systematically review the available literature regarding the impact of MHFA training on HCP students' mental health literacy, confidence and intentions to provide help, stigma, peer support and self-care. METHOD: Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines (International Prospective Register of Systematic Reviews ID: CRD42024589509), five databases were searched. Primary studies evaluating the above outcome measures in HCP students were included. Two authors independently screened references and extracted data. Quality was assessed using the Modified Medical Education Research Study Quality Instrument and Cochrane Risk of Bias tools. A narrative synthesis was performed. RESULTS: Of 2367 records screened, 26 met inclusion criteria. Confidence in supporting others and mental health literacy showed the most consistent improvements following MHFA training, whereas evidence for changes in stigma was mixed. Peer support, self-care and student well-being were infrequently examined, although qualitative data suggested that MHFA had improved openness to help-seeking. CONCLUSIONS: MHFA shows promise in enhancing mental health literacy, confidence and intentions, and in reducing stigma, particularly when supplemented with experiential learning. HCP students may benefit from tailoring of such courses to their specific needs, fostering a culture of peer support, enhancing well-being and introducing basic concepts in mental health.

MHFA↗
PubMed2026

Can host genetics transform the sustainable control of tropical theileriosis? Insights from the Tick-Theileria interface.

Tropical theileriosis, caused by the tick-transmitted apicomplexan parasite Theileria annulata, remains a major constraint on cattle production across North Africa, the Mediterranean basin, the Middle East and South Asia. Current control depends on acaricides, the theilericidal drug buparvaquone and live attenuated schizont vaccines, but acaricide resistance, buparvaquone-resistance mutations and the logistical demands of vaccination are eroding the sustainability of these tools. Host genetics offers a complementary and durable alternative. Indigenous Bos indicus breeds are consistently more resistant to ticks and tolerate T. annulata infection better than exotic Bos taurus cattle, and this advantage has a measurable heritable component. Unlike previous reviews, which treat tick resistance, T. annulata immunobiology and livestock genomic selection as separate subjects, we integrate all three and assess host genetics specifically against the failure modes of current control. We review the tick, parasite and host interface, the evidence for natural resistance, and the genetic and immunological mechanisms involved, including signal-regulatory protein, bovine major histocompatibility complex class II and inflammatory pathway genes. We then assess whether genomic selection, multi-omics, machine learning and gene editing can translate these mechanisms into resistant cattle, and we weigh the biological, economic and infrastructural barriers to implementation. The evidence indicates that host genetics will not replace existing control but could reduce reliance on acaricides and chemotherapy. That contribution remains prospective rather than demonstrated: no resistance marker for T. annulata has yet been validated, prediction accuracies are moderate and transfer poorly between breeds, and no endemic production system has implemented selection for resistance.

Animals↗
PubMed2026

Integration of single-cell transcriptomics and genomic mutation analysis identifies an immunotherapy-resistant tumor subcluster and validates ARNTL2 as a malignant driver in lung adenocarcinoma.

BACKGROUND: Immunotherapy resistance in lung adenocarcinoma (LUAD) remains a critical clinical challenge, and the mechanisms underlying resistance-associated intratumoral heterogeneity are poorly characterized. METHODS: We performed single-cell RNA sequencing of LUAD patients receiving neoadjuvant immunotherapy (responders vs. non-responders), integrating inferCNV, GSVA, and differential expression analyses. Cluster-specific genes were validated across seven independent cohorts (TCGA-LUAD, GSE13213, GSE26939, GSE29016, GSE30219, GSE31210, GSE42127). A multi-algorithm machine learning framework was used to construct a prognostic model, and the immune microenvironment was characterized using TCIA scoring, seven infiltration algorithms, and ESTIMATE. ARNTL2 function was assessed by CCK-8 and Transwell assays in A549 and H1299 cells. RESULTS: Non-responders showed significant enrichment of epithelial cells, depletion of cytotoxic T/NK cells, and elevated copy number variation burden versus responders (p < 0.0001). A resistance-enriched malignant subcluster (Cluster 2) exhibited hyperproliferative and metabolic reprogramming signatures with upregulated KRT17, S100A2, and CST6, which showed tumor-specific overexpression, adverse prognostic value, and genomic amplification across cohorts. CoxBoost combined with survivalSVM achieved optimal predictive performance (C-index = 0.686), yielding robust risk stratification (HR: 2.54-10.51, all p < 0.05). Low-risk patients showed greater immune infiltration and higher TCIA immunophenoscores. ARNTL2 was an independent prognostic factor (HR: 2.07-4.64) strongly correlated with risk score (r = 0.69), and its knockdown suppressed proliferation and invasion in both LUAD cell lines (all p < 0.05). CONCLUSION: This study identifies a resistance-associated malignant subcluster in LUAD, constructs a validated CoxBoost + survivalSVM prognostic model with robust immune stratification, and establishes ARNTL2 as a core oncogenic driver and therapeutic target.

ARNTL2↗
PubMed2026

How AI-supported intelligent systems support infection prevention and control training in healthcare: A systematic review of educational functions and outcomes.

AIMS: Artificial intelligence (AI)-supported intelligent systems have been increasingly incorporated into infection prevention and control (IPC) education and training, primarily to support the monitoring of observable behaviors and the provision of feedback. However, existing evidence has focused largely on short-term compliance outcomes, with limited synthesis of the educational role of AI-supported intelligent systems in supporting sustained IPC competence. This systematic review examined how AI-supported intelligent systems have been designed and used to support IPC education and training, with a focus on system characteristics, educational functions, and reported outcomes. DESIGN: A systematic literature search was conducted across the PubMed/MEDLINE, Embase, Cochrane, and CINAHL databases. DATA SOURCES: A total of 18 studies met the inclusion criteria. Findings were qualitatively synthesized according to system design characteristics, educational functions, and outcome domains. REVIEW METHODS: Methodological quality was appraised using the Mixed Methods Appraisal Tool. RESULTS: Most AI-supported intelligent systems focused on hand hygiene and relied on fully automated monitoring systems to capture behaviors and provide performance feedback. Educational functions were predominantly limited to performance assessment, automated feedback, and reminders. Outcomes were mainly measured using compliance or performance metrics, whereas sustained behavioral change and decision quality were rarely assessed. CONCLUSIONS: AI-supported intelligent systems have been used primarily to reinforce short-term IPC performance and compliance. However, their current applications for supporting sustained competence over time remain limited. The findings of this review suggest that AI-supported intelligent systems may serve as maintenance-oriented educational support by extending learning beyond initial instruction through repeated practice and feedback. Future research should prioritize outcome measures that capture the durability of performance and decision-making processes to better align AI-supported intelligent systems used in IPC education and training with the educational demands of clinical practice.

Humans↗
PubMed2026

Development, feasibility, acceptability, and preliminary impact of NutriSOS&#xae;: A behavioral mobile app to promote sustainable diets.

The primary objective of this study was to describe the development of the NutriSOS&#xae; app and to evaluate its feasibility and acceptability for its use in the NutriSOS&#xae; Randomized Controlled Trial (RCT) to promote sustainable diets. A secondary objective was to explore preliminary changes in dietary and physical activity behaviors and environmental impact following app use. The NutriSOS&#xae; app integrates personalized dietary advice, educational content, self-monitoring, and social interaction features. A single-arm, pre-post pilot study was conducted in 37 young Mexican adults over four weeks. Feasibility, acceptability, quality, and usability were assessed using online surveys, alongside exploratory changes in dietary and physical activity behaviors, environmental indicators, and their association with perceived behavioral determinants. Feasibility and acceptability were high overall, with favorable responses reaching up to 100% in key components such as the nutritional guide and learning modules, and above 90% for messaging, registration, and design. Greater variability was observed in some sections, particularly the 24-h recall (41-86%). Reductions in red and processed meat and ultra-processed food consumption were observed (from 3 to 1 times/week, p&#xa0;<&#xa0;0.01), with &#x223c;60% decreases in their related environmental footprints (p&#xa0;<&#xa0;0.01) and favorable self-reported behavioral determinants (p&#xa0;<&#xa0;0.0001). Physical activity type and intensity changed (p&#xa0;<&#xa0;0.05). These findings support NutriSOS&#xae; as a feasible and acceptable tool, while highlighting areas for refinement, particularly those related to the time and effort required for data entry, prior to its implementation in the NutriSOS&#xae; RCT, in which its effectiveness will be formally evaluated.

Humans↗
PubMed2026

Executive function in alcohol use disorder with low psychiatric comorbidity: Comparison with a non-clinical sample and predictive value for treatment outcome.

BACKGROUND: Executive functions (EF) encompass abilities such as planning, decision-making, and inhibitory control, critical for learning, establishing and maintaining behavioral change. The association between alcohol use disorder (AUD) and impairments in EF are well established. However, prior research is dominated by studies on convenience samples including individuals with severe AUD with high levels of psychiatric comorbidity, which limits generalizability. The present study therefore aimed to investigate the degree of impairment and predictive ability of EF, on alcohol consumption, among individuals with moderate AUD with low levels of psychiatric comorbidity. METHODS: Adults with moderate AUD (n&#x2009;=&#x2009;147) were recruited at three specialized addiction outpatient clinics in Stockholm, to a randomized controlled trial investigating the efficacy of two psychological treatments. Participants underwent neuropsychological testing before treatment. Eight tests from the CANTAB&#xae; battery were administered at baseline, assessing mental flexibility, sustained attention, visuospatial working memory, response inhibition, and delay discounting. Assessments of alcohol use and related symptoms were conducted at baseline, the 12- and 26-weeks follow-up. A non-clinical reference sample (n&#x2009;=&#x2009;72) completed corresponding CANTAB&#xae; tests. The two groups were compared regarding EF using descriptive statistics and t-tests, and the predictive value of EF for reduction in alcohol consumption, was investigated using multiple regression models. RESULTS: Individuals with AUD did not perform worse on any of the tests on executive function (CANTAB&#xae;) as compared to the non-clinical reference sample. Measures of EF were not significant predictors for reduction in alcohol use for the 12-week, or the 26-week follow-up. CONCLUSIONS: EFs were not impaired and were not a clinically relevant predictor of treatment outcomes in this population with AUD. Future research on EF as a predictor in AUD treatment, needs to corroborate the present findings, and include other populations, e.g., with different socio-economic backgrounds and by including other methodologies for measuring EF.

Humans↗
PubMed2026

Clinical applications of digital twin technology in In Vitro Fertilisation.

BACKGROUND: Digital twin technology, originating from aerospace and manufacturing industries, has emerged as a transformative tool in healthcare. In vitro fertilisation (IVF) faces persistent challenges including suboptimal embryo selection, unpredictable treatment outcomes, and limited personalisation of protocols. Despite advances in assisted reproductive technology, existing literature exhibits fragmentation: artificial intelligence applications in embryo selection, ovarian stimulation, and endometrial assessment have been developed independently without systematic integration into comprehensive treatment frameworks. Digital twin technology offers unprecedented opportunities to create virtual replicas of biological systems, enabling real-time monitoring, predictive modelling, and personalised treatment strategies. AIM: This narrative review aims to critically examine the current applications of digital twin technology in IVF, evaluate its potential benefits and limitations, synthesize existing evidence into an integrative conceptual model, and identify future directions for implementation in reproductive medicine. METHOD: A comprehensive narrative review was conducted using PubMed, Scopus, Web of Science, and IEEE Xplore databases. A narrative review approach was selected over systematic review to accommodate the heterogeneity of evidence types in this emerging field, including theoretical frameworks, simulation studies, and proof-of-concept implementations that would be excluded from systematic reviews. Search terms included "digital twin," "IVF," "in vitro fertilisation," "assisted reproductive technology," "embryo selection," and "predictive modelling." Studies published between 2015 and 2025 were included, focusing on original research articles, systematic reviews, and proof-of-concept studies describing digital twin applications in reproductive medicine. RESULTS: Digital twin technology in IVF demonstrates significant potential across multiple domains including embryo development simulation, ovarian response prediction, endometrial receptivity modelling, and personalised stimulation protocols. Current applications integrate artificial intelligence, machine learning algorithms, time-lapse imaging, and omics data to create comprehensive virtual models. Early evidence suggests improvements in embryo selection accuracy, ovarian response prediction, and treatment protocol optimization, though large-scale randomized controlled trials remain limited. Implementation challenges include data integration complexity, computational requirements, regulatory considerations, and validation requirements. CONCLUSION: Digital twin technology represents a paradigm shift in IVF practice, offering personalised, predictive, and precision medicine approaches. This review synthesizes existing evidence to propose an integrative conceptual model for digital twin implementation across the IVF treatment spectrum, identifies critical knowledge gaps, and establishes research priorities to advance clinical translation. Despite current limitations, continued advancement promises improved success rates and patient outcomes.

Humans↗
PubMed2026

A Critical Assessment of Evidence-Based Design's Knowledge Base and Inspiration: A Systematic Review.

PurposeThis study examines Evidence-Based Design (EBD) as an epistemological framework for guiding design research and practice, with a particular focus on its reliance on Evidence-Based Medicine (EBM) as a source of methodological inspiration.BackgroundOver the past two decades, EBD has been promoted as a way to strengthen design processes through the systematic use of scientific evidence. Its relationship to EBM, however, remains conceptually ambiguous: EBD draws legitimacy from EBM's hierarchical conception of "best evidence" while at the same time acknowledging the specificities of design practice, which do not easily fit such a model.MethodologyA systematic review was conducted on 31 publications in the design research literature that explicitly address the tension surrounding EBD's conception of "best evidence." The criticisms raised were coded and analyzed by main topics and subtopics.ResultsThe review highlights several reasons why EBM's hierarchical view of "best evidence" is an unsuitable epistemological foundation for EBD. It imposes scientifically inappropriate and practically ineffective methodological standards, devalues important sources of design knowledge, and fails to address central epistemic challenges intrinsic to design processes.ConclusionsBy bringing together critical yet fragmented insights from the literature, this study argues for the development of an updated epistemological framework for EBD. Constructing this framework will require sustained interdisciplinary dialogue between design research and philosophy of science.

Humans↗
PubMed2026

Making waves: toward systems-level interpretation of hormonal and endogenous biomarkers in wastewater-based epidemiology.

Wastewater-based epidemiology (WBE) has proven invaluable for population health monitoring, most notably during the COVID-19 pandemic. Yet current WBE largely relies on exogenous markers such as drugs, pathogens, and their metabolites, limiting surveillance to what communities are exposed to. We argue for expanding WBE towards endogenous biomarkers, particularly hormones, which provide insights into physiological stress, metabolic function, and endocrine activity. Hormone-based WBE offers new opportunities to capture population-level biological responses to societal and environmental stressors, disasters, and chronic disease burdens at the community scale. This perspective outlines a systems-level framework for integrating hormonal signals in wastewater with clinical data, behavioral indicators, environmental factors, and digital markers to support more robust and context-aware public health surveillance. We highlight key technical considerations, interpretive challenges, and opportunities for translational pilot studies. By moving beyond exposure tracking toward more integrated interpretation of biological responses, hormone-informed WBE may contribute to more resilient, inclusive, and actionable public health infrastructure.

Humans↗
PubMed2026

Proficiency-based training and evidence-based methodology: a systematic review and meta-analysis.

OBJECTIVE: To assess adherence of self-labelled proficiency-based progression (PBP) studies to evidence-based PBP criteria and examine associations with training outcomes. METHODS: A systematic review and meta-analysis were conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines and registered in the International Prospective Register of Systematic Reviews. PubMed, CENTRAL, EMBASE, MEDLINE, and Scopus were searched from inception to 1 March 2023. Prospective English-language studies on healthcare procedural training reporting objective performance outcomes were included; non-prospective, non-quantitative, non-procedural, non-English studies, and reviews were excluded. Pre-specified outcomes included adherence to 18 evidence-based PBP criteria and objective performance metrics (errors, steps, time); secondary outcomes included proficiency benchmark achievement and Likert ratings. Data extraction was performed independently by multiple reviewers. Study quality was assessed using the Medical Education Research Study Quality Instrument and risk of bias by two investigators. Effect sizes were pooled using random-effects models (DerSimonian-Laird), expressed as the ratio of means (ROM) for continuous outcomes and bias-corrected odds ratios for dichotomous outcomes. RESULTS: Of 646 studies identified 175 met inclusion criteria. In the PBP studies (n&#x2009;=&#x2009;18), 94% fulfilled minimum criteria (use of a proficiency benchmark, its quantitative definition, and requirement for demonstration prior to progression) vs 36% of non-PBP studies (n&#x2009;=&#x2009;157). If all PBP criteria were included, 83% of PBP studies used these criteria vs only 2% of non-PBP-studies. In quantitative analysis (27 randomised clinical studies, 761 participants), ROM results showed that PBP training reduced the number of performance errors by 58% (P&#x2009;<&#x2009;0.001) and procedural time by 28% (P&#x2009;=&#x2009;0.006), increasing number of steps performed by 22% (P&#x2009;=&#x2009;0.03). When stratified based on number of criteria fulfilled, meta-regression demonstrated that increasing the number of PBP criteria fulfilled was associated with progressive and systematic trainee performance improvement. CONCLUSIONS: The more training methodologies adhere to established PBP criteria, the better training outcome will be.

Humans↗
PubMed2026

Base editing reversal of radiation sensitivity in NHEJ1 immunodeficiency.

Inherited defects of DNA double-stranded break (DSB) repair can result in radiosensitive/radiation-sensitive (RS) SCID (RS-SCID). We applied base editing to reverse NHEJ1 mutations in patient fibroblasts, exemplifying how this technology can help interrogate RS sequence variants.

Journal Article↗
PubMed2026

Randomized controlled trial comparing 7-day fexuprazan-based and 14-day rabeprazole-based triple therapies for Helicobacter pylori eradication.

BACKGROUND: Fexuprazan is a newly developed potassium-competitive acid blocker used for the treatment of acid-related gastrointestinal diseases; however, clinical data regarding its efficacy in Helicobacter pylori eradication are lacking. This study evaluated the efficacy and safety of a 7-day fexuprazan-based triple therapy regimen compared with a 14-day rabeprazole-based triple therapy regimen for H. pylori infection in Korean patients. METHODS: A randomized controlled single-center study was conducted to compare the eradication rates between 7-day fexuprazan (40&#x2009;mg)-based triple therapy (with 1&#x2009;g amoxicillin and clarithromycin 500&#x2009;mg administered twice daily) and 14-day rabeprazole (20&#x2009;mg)-based triple therapy for H. pylori eradication. The primary endpoint was the success rate of H. pylori eradication, determined using the 13C-urea breath test. Safety outcomes were also evaluated. RESULTS: A total of 79 patients were randomly assigned to the fexuprazan and rabeprazole groups. In the full analysis set, eradication rates were 80.00% (32/40) in the fexuprazan group and 82.05% (32/39) in the rabeprazole group. In the per-protocol set, eradication rates were 83.78% (31/37) and 88.89% (32/36), respectively (P = 1.000 and P =.737). The overall incidence of treatment-emergent adverse events was 70.00% (28/40) in the fexuprazan group and 66.67% (26/39) in the rabeprazole group, with no significant difference between groups (P =.812); both regimens were well tolerated. Among patients with clarithromycin-susceptible strains in full analysis set, eradication rates were 93.10% (27/29) in the fexuprazan group and 87.09% (27/31) in the rabeprazole group (P =.672). In the per-protocol set, eradication rates for susceptible strains were 96.42% (27/28) in the fexuprazan group and 93.10% (27/29) in the rabeprazole group (P = 1.000). CONCLUSION: Seven-day fexuprazan-based triple therapy demonstrated eradication efficacy comparable with that of 14-day rabeprazole-based therapy in treatment-na&#xef;ve Korean patients with H. pylori infection. The fexuprazan-based regimen showed a similar safety profile and comparable incidence of adverse events with that of the rabeprazole-based regimen.

Humans↗
PubMed2026

Understanding and Usefulness of Effect Size and Certainty of Evidence: A Cross-Sectional Survey of Evidence-Based Practice Competencies Among US Registered Dietitians.

INTRODUCTION: Understanding of absolute and relative effect estimates, and determining effect size and certainty of evidence corresponding to effect estimates, represent fundamental evidence-based practice competencies that promote informed clinical decision-making. While research has been conducted in the medical profession, based on our literature review there is no published research on these competencies in the nutrition and dietetics profession. METHODS: Among registered dietitians, our main objectives were to assess (1) their understanding and perceived usefulness of three absolute and two relative effect estimate approaches to determine effect size, (2) their perceived usefulness of certainty of evidence, and (3) factors influencing their understanding and perceived usefulness. We conducted a web-based, cross-sectional survey by recruiting dietitians from the Academy of Nutrition and Dietetics (United States). Participants received effect estimates based on hypothetical dietary interventions vs. usual diet for reducing myocardial infarction risk. RESULTS: Of the 11,050 dietitians who received the survey link, 210 participated, and only completers (n&#x2009;=&#x2009;114) were included in our analysis. Participants demonstrated a similar understanding of the relative (27.6%) and absolute (27.5%) effect estimates, with Risk Difference being the best understood approach and Number Needed to Treat being the least (30.7% vs. 24.6% correct responses). While perceived usefulness scores were similar between five approaches, they were highest when data was presented as Relative Risk [mean (SD): 4.82 (1.50)]. Dietitians rated the usefulness of certainty of evidence favorably [mean (SD): 5.07 (1.83), on a 7-point scale], and no factors were associated with correct understanding. CONCLUSION: Dietitians may have limited understanding of effect size thresholds presented in our survey, a finding mostly consistent with surveys of other health professionals. To optimize informed decision-making between dietitians and clients, dietetic programs and continuing education platforms should consider additional training on effect estimate approaches (relative and absolute), and determining effect sizes and certainty of evidence for effect estimates.

Clinical nutrition↗