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PubMed2026

Effectiveness of peer recovery support services for substance use disorders: A systematic review of healthcare utilization, behavioral health, and engagement outcomes.

BACKGROUND: Peer recovery support services (PRS) delivered by individuals with lived experience of substance use, are increasingly incorporated into substance use disorder (SUD) care systems to improve care engagement, reduce acute care use, and support recovery. However, existing systematic reviews have focused on substance use outcomes, with limited attention to healthcare utilization, psychosocial functioning, and outcomes across settings, and populations. METHODS: This systematic review, registered in PROSPERO (CRD42023469279), synthesized peer-reviewed studies from 2003 to 2026 evaluating PRS for individuals with alcohol or drug-related SUD. Using MEDLINE, Embase, PsycINFO, and CINAHL, the review included 53 studies primarily conducted in high-income countries that reported quantitative outcomes across substance use, healthcare utilization, behavioral health, and treatment engagement. Risk of bias was assessed using Cochrane RoB 2, ROBINS-I, and ROBINS-E tools. RESULTS: Overall, evidence was most favorable for selected treatment-linkage and engagement outcomes, whereas findings for substance use, emergency department use, hospitalization, overdose, and mortality were inconsistent. Uncontrolled longitudinal studies frequently reported improvements in depression and anxiety, but no randomized trials evaluated these outcomes, limiting causal inference. Exploratory cross-study patterns suggested that sustained navigation, practical assistance, and repeated peer contact were more often present in programs reporting favorable outcomes; however, these components were not independently evaluated. Substantial heterogeneity, frequent multicomponent interventions, high risk of bias in many nonrandomized studies, and limited long-term and economic data constrain conclusions. CONCLUSIONS: Findings support the promise of PRS while underscoring the need for more rigorous comparative studies, cost-effectiveness data, and further research in low- and middle-income countries.

Humans↗

PubMed2026

Driving Under the Influence of Cannabis Among U.S. Young Adults Who Use Cannabis: Evidence From the 2021-2024 National Survey on Drug Use and Health.

PURPOSE: To estimate the prevalence of driving under the influence of cannabis (DUIC) and identify associated factors among U.S. young adult drivers reporting past-year cannabis use. METHODS: This cross-sectional study analyzed pooled 2021-2024 National Survey on Drug Use and Health. The analytic data were restricted to drivers aged 18-25 years who reported past-year cannabis use (N = unweighted 17,141; weighted N = 10,814,381). The outcome was self-reported past-year DUIC. Independent variables included demographics, substance use, mental health, cannabis-related perceptions, and driving behaviors. These relationships were assessed by modified Poisson regression. RESULTS: The weighted prevalence of DUIC was 28.0%, representing approximately over three million young adults. DUIC prevalence increased with cannabis use frequency, from 2.51 times higher among those using cannabis 12-49 days (adjusted prevalence ratio [APR]: 2.51; 95% confidence interval [CI]: 2.29-2.75) to 3.63 times higher among those reporting use on 300-365 days (APR: 3.63; 95% CI: 3.60-3.76), compared with those using cannabis 1-11 days. Cannabis use disorder (APR: 2.34; 95% CI: 2.06-2.65), simultaneous alcohol and cannabis use (APR: 1.29; 95% CI: 1.28-1.30), and perceived easy cannabis availability (APR: 2.36; 95% CI: 2.33-2.39) were also associated with higher prevalence of DUIC. Nonenrollment in school and living in a state with a medical cannabis law were associated with lower DUIC prevalence. DISCUSSION: DUIC is highly prevalent among U.S. young adults who use cannabis, with a clear graded association across categories of cannabis use frequency. Public health interventions should address frequent use, cannabis use disorder, alcohol-cannabis co-use, and perceived cannabis availability.

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PubMed2026

Outcomes and Associated Prognostic Factors for Orthograde Canal Obturation Using Ortho MTA III: A Randomised Prospective Clinical Trial.

AIM: To prospectively compare treatment outcomes for orthograde canal obturation using Ortho MTA III (OMTA) with the continuous wave of compaction (CWC) using gutta-percha (GP) and AH Plus sealer, and to identify associated predictive factors. METHODOLOGY: Informed consent was obtained (110 patients), and single- or two-rooted permanent teeth (n = 120) diagnosed with pulp necrosis (or previously treated) and asymptomatic apical periodontitis or chronic apical abscess (periapical index, PAI ≥ 3) were randomly assigned to two groups (n = 60/group). The canals were prepared to a minimal apical size #40 (ISO) based on their initial file size, disinfected and obturated by either CWC or OMTA using an enhanced disinfection protocol (GP disinfected, new gloves after each intraoperative radiograph and before starting obturation). Clinical and periapical radiographic examinations were conducted by two calibrated, independent endodontists during follow-up periods of at least 12 months. Success rates and associated predictive factors (tooth-, operator- and patient-related) were analysed statistically using binary and multiple logistic regression (p < 0.05). RESULTS: The median recall period was 30 months (14-48 months), and 104 teeth were finally analysed (recall rate: 86.67%). No significant differences in success rate were observed between the groups (p > 0.05) under both loose (OMTA: 88.24%, CWC: 83.02%) and strict criteria (OMTA: 64.71%, CWC: 58.49%). Multivariate analysis revealed that age (OR = 5.735, 95% CI: 1.286-25.577, p = 0.022), periapical lesion size (OR = 6.596, 95% CI: 1.397-31.138, p = 0.017) and PAI score (OR = 2.081, 95% CI: 1.047-4.136, p = 0.036) were significant predictors of treatment failure. CONCLUSIONS: Orthograde obturation of infected canals with Ortho MTA III demonstrated comparable success and treatment outcomes to those filled with GP and sealer by CWC, supporting its potential as a clinically viable alternative for the obturation of infected root canals. TRIAL REGISTRATION: cris.nih.go.kr registration number: KCT00099939.

Humans↗

PubMed2026

Retention strategies and participant retention rates among prospective longitudinal pregnancy cohorts: a systematic mapping review.

Prospective longitudinal pregnancy cohorts can answer questions about fetal and early life exposures and later health outcomes; however, there are challenges to retaining participants in longitudinal studies, particularly over life transitions like the birth of a child. Optimal methods for retaining participants in longitudinal research are unclear. A systematic mapping review was conducted to identify prospective cohort studies and randomized controlled trials that enrolled pregnant participants and their infants. Data on retention rates and 17 retention strategies was extracted. A random effects meta-analysis generated pooled annual retention rates inversely weighted to the number of baseline participants. Spearman rank coefficients were used to assess correlation between strategy use and retention. A random-effects meta-regression was used to determine if select retention strategies were associated with participant retention. We identified 130 studies, involving 472 022 pregnancies. A downward trend in pooled mean retention rates were observed. Studies utilized an average of 6.8 (SD 3.9) retention strategies. Statistically significant associations were not observed between strategy use and retention rates at follow-up (p > 0.05). Prospective studies of pregnant people and their infants used multiple retention strategies. Participant retention rates declined over time, suggesting that additional factors may influence study participation in the postpartum period.

Humans↗

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.

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PubMed2026

A genome-wide coverage-based pipeline for the identification of host-derived candidate DNA biomarkers from cell-free blood.

We have created a new data-analysis pipeline for the discovery of host-specific candidate DNA biomarkers derived from sequencing data of cell-free blood. Unlike approaches that rely on specific molecular or genetic signatures, our method leverages the coverage distribution of cell-free DNA sequences mapped to a reference genome, applying statistical analyses to identify informative short genomic regions for biomarker discovery. The pipeline is applicable to diverse diseases and can be used to analyze cell-free DNA sequences from plasma or serum to identify candidate biomarkers that are characteristic of disease states in mammals. Core functionalities were developed in Java and integrated with open-source software tools for the preprocessing of raw sequencing data, complemented by Python scripts for the machine-learning analysis and statistical validation. The pipeline is designed for HPC use and users can access the pipeline through a Galaxy workflow, which offers a user-friendly web interface for input selection prior to execution and analysis progress monitoring. Performance tests, carried out using duplicate sets of COVID-19 samples and controls, showed linear scalability of execution time with an increasing dataset size, as well as a substantial reduction in execution time through parallelized computation, whereby each HPC node is used to process the data of one chromosome. Further statistical tests confirmed the quality of the pipeline's results by showing that the set of identified candidate biomarkers remained stable across varying dataset sizes.

Biomarkers↗

PubMed2026

Artificial intelligence for dental caries detection: An umbrella review.

Artificial intelligence (AI) has been proposed as a tool to improve dental caries detection across imaging modalities; however, its clinical value remains uncertain. This umbrella review aimed to synthesize and critically appraise systematic reviews evaluating AI for caries detection and diagnosis. An umbrella review was conducted following PRIOR guidance (PROSPERO CRD420261340728). Searches were performed in MEDLINE, Embase, Scopus, Web of Science, and Google Scholar up to 15 March 2026. Methodological quality was assessed using AMSTAR 2, and overlap of primary studies was quantified using the corrected covered area (CCA). Seventeen systematic reviews were included, of which five reported diagnostic test accuracy meta-analyses using bivariate or HSROC models. Across these meta-analyses, pooled sensitivity ranged from 0.76 to 0.94 and specificity from 0.85 to 0.91. Most systems were based on deep learning models applied to bitewing radiographs and intraoral photographs. However, substantial heterogeneity was observed in imaging modalities, lesion thresholds, analytical tasks, and evaluation metrics. In addition, a high degree of overlap across reviews and recurrent methodological limitations, including reliance on retrospective datasets, limited external validation, and inconsistent reporting, substantially weaken the reliability of the evidence. Although AI models demonstrate high diagnostic performance under experimental conditions, current evidence does not support their use as stand-alone diagnostic tools. Their clinical applicability remains limited, and implementation should be restricted to decision-support contexts until robust prospective validation demonstrates meaningful impact on clinical decision-making and patient outcomes.

Dental Caries↗

PubMed2026

Selective monitoring of trace-level catechin and myricetin in herbal and aqueous matrices using magnetic MIP-DSPME: Optimization via design of experiments.

A novel dispersive solid-phase microextraction approach utilizing a magnetic molecularly imprinted polymer (MMIP) integrated with HPLC-UV detection was developed for the concurrent quantification of catechin and myricetin in herbal extracts and aqueous samples. The sorbent was engineered as a core-shell nanocomposite, consisting of a selective polymer layer deposited onto Fe3O4@SiO2-APTMS magnetic nanoparticles. Dual-template imprinting using catechin and myricetin generated complementary binding cavities within the polymer framework. Experimental variables influencing extraction were systematically screened and subsequently optimized. A Plackett-Burman design was first applied to identify the most influential factors, with pH and sorption time identified as the dominant variables. These parameters were subsequently fine-tuned using a central composite design, and the optimization process was completed in only 30 experimental runs. The sorption characteristics of the imprinted sorbent (MMIP) were compared with those of its non-imprinted counterpart (MNIP). The MMIP demonstrated markedly higher maximum binding capacities (Qmax), reaching 119.3 mg g-1 for myricetin and 112.1 mg g-1 for catechin, whereas the corresponding values for the MNIP were 32.55 and 32.08 mg g-1, respectively. Moreover, the affinity constants (KL = 0.760-0.950 L mg-1) were approximately 2.3-fold higher for the MMIP, confirming its stronger and more selective interactions with the target analytes. The selectivity coefficients for the targeted flavonoids relative to structurally related compounds, including ferulic acid, p-coumaric acid, melatonin, and curcumin, exceeded 3.5 for the MMIP, whereas the corresponding values for the MNIP were close to 1.1, demonstrating the high molecular recognition capability of the imprinted sorbent. Method validation demonstrated limits of detection (LODs) of 0.33-0.59 ng mL-1 and limits of quantification (LOQs) of 1.10-1.96 ng mL-1, and excellent linearity over the concentration range of 5.0-5500 ng mL-1 (R2 > 0.998). The method achieved recoveries of 93.96% to 105.69% with RSDs below 5.5%, while the preconcentration factors ranged from 209 to 229. Furthermore, the sorbent retained more than 95% of its extraction efficiency after four consecutive reuse cycles and more than 80% after six cycles, demonstrating excellent stability and reusability. The proposed method was successfully applied to the analysis of six medicinal plant extracts and water samples, showing negligible matrix interference and superior sensitivity, selectivity, and operational simplicity compared with conventional solid-phase extraction methods.

Flavonoids↗

PubMed2026

Exploring the mechanism of aroma production in fermented cherry juice by L. brevis LD1.0600 using flavomics and whole genome analysis.

This study focused on L.brevis LD1.0600 with excellent fermentation traits: it analyzed genome-wide key regulatory genes for micro-metabolites, combined with fermented cherry juice flavor metabolomics data, and used machine learning to explore correlations between gene regulation, metabolite production, and flavor formation. The SVM model screened and verified fermented cherry juice VOCs; through OAV and flavor wheel analysis, LD1.0600 emerged as the top-performing strain, with a sweet, fruity dominant aroma. Key aroma-active components (OAV > 100) included 2-methoxy-4-vinylphenol, benzaldehyde, 2-methyl-butanoic acid and hexanoic acid, and 2-methoxy-4-vinylphenol and hexanoic acid elevated by LD1.0600-regulated genes (Chrom1-001884, Chrom1-000925, fabF and Chrom1-000199). At the same time, through research, a "strain screening-SVM screening of DVCs-OAV screening of key aroma components-whole genome sequencing of flavor regulatory genes" system was established. This system can not only be applied to the screen fermentation strains, but also can be extended to the application of other fermentation products.

Fermentation↗

PubMed2026

Facilitators and Barriers to Volunteers' Involvement in Palliative Care: A Qualitative Meta-Synthesis.

OBJECTIVE: This study aims to systematically synthesize qualitative evidence on facilitators and barriers to volunteer involvement in palliative care services, providing insights to inform strategies for strengthening volunteer support systems. METHODS: PubMed, Web of Science, Embase, Cochrane Library, Medline, EBSCO, ProQuest, China National Knowledge Infrastructure, Wanfang, VIP, and Sinomed were searched from inception to December 2025 to identify qualitative studies examining factors influencing volunteer participation in palliative care. Methodological quality was assessed using the Joanna Briggs Institute Critical Appraisal Checklist for Qualitative Research. Data were analyzed using Thomas and Harden's thematic synthesis approach and managed using NVivo 12.0 software, following the Enhancing Transparency in Reporting the Synthesis of Qualitative Research (ENTREQ) guidelines. RESULTS: Thirty-one studies involving 1042 participants were included, yielding 68 findings. Facilitators included intrinsic motivation and meaning-making at the individual level; supportive relationships and teamwork at the interpersonal level; structured support and professional recognition at the organizational level; social recognition and resource integration at the community level; and institutional safeguards and governmental incentives at the policy level. Barriers included emotional burden and limited competencies at the individual level; relationship conflicts and insufficient collaboration at the interpersonal level; management deficiencies at the organizational level; community resource imbalances at the community level; and inadequate regulations and incentives at the policy level. CONCLUSION: Volunteer participation in palliative care is influenced by multiple interacting factors. Strengthening training and support systems, enhancing team collaboration, and improving institutional frameworks may help sustain volunteer engagement and improve the quality of palliative care services.

Palliative Care↗

PubMed2026

Genomic science and the nurse educator's role: Promoting integration from curriculum to clinical practice.

BACKGROUND: Registered nurses and nurse educators play a critical role in preparing future clinicians to translate genomic discoveries into practice. However, emerging evidence suggests that both groups may lack sufficient knowledge and confidence in genomics, potentially limiting their ability to teach, mentor, and apply genomics in real-world settings. This gap is especially concerning in Aotearoa New Zealand, where the genomic literacy of nurse educators and clinicians remains underexplored. OBJECTIVE: This study aims to: (1) assess nurse educators' genomic literacy and confidence in teaching genomics; and (2) evaluate registered nurses' knowledge and confidence in applying and teaching genomics in clinical practice. DESIGN: Exploratory descriptive qualitative. SETTING: This study was conducted in the greater Auckland area. PARTICIPANTS: A total of 17 participants were recruited using purposive sampling to ensure a diverse range of perspectives across varying levels of teaching experience, disciplinary backgrounds, and exposure to genomic content. METHODS: Data were collected using semi-structured focus group interviews, a method well-suited for generating in-depth discussion and facilitating interaction among participants with shared professional interests. The collected data were analysed using thematic analysis methods. RESULTS: The findings offer insight into the preparedness of New Zealand's nursing workforce to engage with genomic-informed healthcare and inform strategies for integrating genomics into nursing curricula and continuing professional development. Given the interdisciplinary nature of genomic healthcare, these insights may also be relevant to other health professionals-including midwives, pharmacists, and allied health practitioners-who increasingly encounter genomic information in clinical practice and require foundational competencies to support patient care. CONCLUSION: Addressing this educational gap is critical to ensuring that nurses-key facilitators of patient care and public health-are equipped to deliver safe, equitable, and evidence-based genomic healthcare.

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PubMed2026

Acupuncture improves depressive symptoms and prefrontal cortical function in mild to moderate depressive disorder: A randomized sham-controlled trial and fNIRS study.

BACKGROUND: Depressive disorder is a common mental illness associated with substantial functional impairment. Although pharmacotherapy is widely used, its effectiveness is often limited by adverse effects and poor adherence. Acupuncture has been increasingly applied as a complementary treatment for depression, and its neurobiological characteristics remain unclear. OBJECTIVE: This randomized, sham-controlled trial aimed to evaluate the clinical efficacy of acupuncture for mild to moderate depressive disorder and to investigate its effects on prefrontal cortical function using functional near-infrared spectroscopy (fNIRS). METHODS: Patients with mild to moderate depressive disorder were randomly assigned to a real acupuncture (RA) group or a sham acupuncture (SA) group and received standardized treatment for 8 weeks. Clinical outcomes were assessed using the Self-Rating Depression Scale (SDS), Self-Rating Anxiety Scale (SAS), Short Form-36 Health Survey (SF-36), and a traditional Chinese medicine syndrome score. A subset of participants underwent fNIRS assessment during resting-state and task-based conditions to evaluate prefrontal cortical activation and functional connectivity. RESULTS: Compared with baseline, the RA group showed significant reductions in SDS and SAS scores and significant improvements in SF-36 emotional domains, with effects emerging at Week 4 and persisting up to 12 weeks after treatment. Improvements were greater and more stable in the RA group than in the SA group. fNIRS analyses revealed enhanced activation in dorsolateral and medial prefrontal regions and strengthened prefrontal functional connectivity following acupuncture, whereas neural changes in the SA group were limited. CONCLUSION: Acupuncture is effective for improving depressive and anxiety symptoms and quality of life in patients with mild to moderate depressive disorder. Modulation of prefrontal cortical activation and connectivity may underlie its antidepressant effects.

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PubMed2026

Artificial intelligence (AI) uses in stereotactic radiosurgery (SRS): diagnosis with brain metastasis (BM) - A systematic review.

BACKGROUND: Brain metastases (BM) are the most common intracranial tumors in adults, and stereotactic radiosurgery (SRS) has become a mainstay of management. However, several diagnostic challenges persist in the SRS pathway, particularly the differentiation of radiation necrosis (RN) from true tumor progression, which conventional MRI and even advanced imaging techniques often cannot reliably resolve. Recent advances in artificial intelligence (AI) offer the potential to address these diagnostic limitations. This systematic review synthesizes current literature on AI applications for MRI-based diagnostic decision support in BM patients undergoing SRS, with a focus on radiomics and deep learning tools for distinguishing RN from progression, classifying molecular and histologic subtypes, and predicting treatment response. METHODS: A systematic review was performed in accordance with PRISMA guidelines. PubMed, Web of Science, and Scopus were searched using a targeted query combining terms related to AI, brain metastasis, diagnosis or imaging, and SRS. After screening 483 records and applying strict inclusion and exclusion criteria, 18 studies published between 2015 and 2025 were included. Data were extracted on study design, cohort characteristics, imaging modality, AI methodology, validation strategy, and reported diagnostic performance. RESULTS: Among the 18 included studies, AI models demonstrated strong performance across diagnostic tasks in the BM-SRS pathway. The differentiation of RN from true tumor progression was the most extensively studied application, addressed by 14 of 18 studies, with reported AUCs ranging from 0.71 to 0.94. Support vector machines, random-forest ensembles, convolutional neural networks, and transformer-based multimodal architectures were widely used. The literature evolved from single-sequence radiomic classifiers in 2018 to multimodal deep learning frameworks fusing imaging with clinical and genomic data in 2025. Contrast-enhanced T1-weighted MRI was the dominant imaging input, and texture-based radiomic features (GLCM, GLSZM, GLDM, and wavelet-derived features) were the most consistently predictive. The highest-performing models reached AUCs of 0.85-0.91 through multimodal integration of imaging with clinical and genomic features, and consistently outperformed expert neuroradiologist read on matched cases. Remaining studies addressed longitudinal segmentation-based detection of local failure and adverse radiation effects, BRAF mutation status in melanoma BM, early Gamma Knife treatment response, and primary tumor histology classification, with more variable performance. CONCLUSION: AI models, particularly those integrating MRI-derived radiomic features with clinical and genomic data, show high accuracy in supporting diagnostic decisions for BM patients treated with SRS. The post-SRS differentiation of radiation necrosis from true tumor progression has reached the greatest level of maturity and is closest to clinical translation, with potential to reduce unnecessary biopsies, personalize surveillance intervals, and rationalize treatment-pathway decisions. Other diagnostic applications, including molecular subtyping and primary tumor histology classification, remain exploratory and require further multicenter validation. Integration of AI tools into multidisciplinary tumor-board workflows, combined with prospective validation and standardized reporting, will be essential to realize the full clinical benefits of AI in SRS for brain metastases.

Humans↗

PubMed2026

Chronic postsurgical pain: risk assessment and mitigation.

PURPOSE OF THE REVIEW: Chronic postsurgical pain (CPSP) and persistent postoperative opioid use (PPOU) are two of the most common complications of a number of surgical interventions, which can cause significant personal and economic negative consequences. This review outlines known and potential risk factors for CPSP and PPOU and approaches to reduce these risk factors. RECENT FINDINGS: Modifiable risk factors for developing CPSP include psychological distress, preoperative pain intensity, and perioperative opioid exposure. Although less studied, psychological comorbidities are also risk factors for PPOU. Evidence-based mitigation strategies include psychological interventions and perioperative opioid sparing. SUMMARY: A number of perioperative risk factors for developing CPSP and PPOU have been identified, and anesthesiologists should be cognizant of these risk factors and potential risk mitigation strategies. Additional prospective studies are needed to further develop easily adoptable, evidence-based interventions to reduce the incidence of CPSP and PPOU.

Humans↗

PubMed2026

Animal-assisted therapy in pediatric urodynamics.

INTRODUCTION/BACKGROUND: Urodynamics (UDS) is associated with high levels of patient anxiety/discomfort. Children are often unable to complete UDS, with anesthesia needed to place catheters. Animal-assisted therapy (AAT) has been used in a variety of settings, but it has not been studied for UDS before. OBJECTIVE: To determine if AAT can increase success of completing UDS testing without anesthesia in children who were previously unable to perform UDS, along with decreasing distress levels. STUDY DESIGN: We performed a pilot case series of 7 patients (2 female, 5 male) aged 4-16 (mean 9.7) years who previously were unable to complete UDS awake, with AAT prior to and during the UDS procedure. A visual analog scale (VAS) was used to measure patient stress levels before and after AAT. RESULTS: We were able to successfully complete UDS testing with AAT in 6 of the 7 patients (85.7%) without the need for anesthesia. VAS scores decreased from before to after AAT (5.4-3.6, p = 0.020) but with discrepancy when compared to UDS success. DISCUSSION: Our study was the first to describe AAT during UDS. Our preliminary data found AAT to be feasible in UDS. Subjective distress may not correlate with procedural success. AAT in UDS may be more beneficial in certain populations, such as anxious children who previously were unable to tolerate UDS, and not in others such as severe neurodevelopmental conditions. Our study was limited by the small sample size, a single provider, single center, single therapy dog, inclusion of a specific population of patients, and no control group due to this being a pilot study. CONCLUSION: AAT for certain children undergoing UDS testing could help improve the ability to complete the testing without anesthesia. Further studies are needed to fully demonstrate its usefulness in UDS.

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PubMed2026

A Qualitative Analysis of Cancer Survivors' Experience in a Time-Restricted Eating vs Control Clinical Trial to Address Cancer-Related Fatigue.

PURPOSE: To describe cancer survivors' lived experiences in a clinical trial that tested an individualized nutrition counseling with or without time-restricted eating to address cancer-related fatigue. METHODS: The Fatigue REDuction After cancer study was a two-arm, randomized controlled trial. Participants were adult cancer survivors who were 2 months to 2 years post-treatment. All participants received individualized nutrition counseling; those in the time-restricted eating group self-selected a consistent 10-hour eating window for 12 weeks. After the study, semi-structured exit interviews were conducted to gauge participants' experiences in the trial. Interviews were transcribed and two independent coders thematically analyzed the interviews using inductive and deductive coding. NVivo software was used for data organization and analysis. RESULTS: Participants (n = 24; TRE = 11; Control = 13) were 55 ± 13 years old, 75% were female, and they had a variety of cancer types. The majority of participants found that being in the study helped them to set and achieve lifestyle goals and would therefore recommend the study to others. Participants in the time-restricted eating group noted that time-restricted eating helped them set a better routine, providing a positive sense of control. However, some noted difficulty switching to a 14-hour fasting schedule, as it can interfere with their regular routine or employment schedules. Many participants noted they were happy that cancer-related fatigue was gaining more attention, hoping to find solutions for persistent cancer-related fatigue. CONCLUSION: The majority of participants found the study useful and, regardless of their group assignment or the intervention's impact on their fatigue, found the study helped them to gain better control of their dietary habits.

Humans↗

PubMed2026

Comprehensive analysis of mRNA-microRNA-lncRNA expression profiles in post-traumatic elbow heterotopic ossification using RNA sequencing and experimental validation.

BACKGROUND: This study aimed to profile the molecular signatures of post-traumatic elbow heterotopic ossification (HO) to identify key regulators and potential therapeutic targets. METHODS: Total RNA from post-traumatic elbow HO tissues (n=4) and normal bone tissues (n=6) was subjected to high-throughput sequencing to identify differentially expressed mRNAs (DEGs), microRNAs (DEMs), and lncRNAs (DELs). Bioinformatics analyses included Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, protein-protein interaction network construction, and transcription factor (TF)-microRNA-mRNA network analysis. The expression trends of four most upregulated and four most downregulated DEGs were validated by real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR). RESULTS: We identified 2,138 DEGs, 40 DEMs, and 905 DELs. DEGs were significantly enriched in biological process "bone mineralization," cellular component "plasma membrane," molecular function "integrin binding," and pathways including PI3K-Akt, NF-κB, JAK-STAT, and TNF signaling pathways. Hub genes with high connectivity included MMP9, IL6, MMP3, CTSK, and BGLAP. Integrated network analysis highlighted the transcription factor JUN and key microRNAs (hsa-miR-124-3p, hsa-miR-548c-3p, and hsa-miR-135b). The qRT-PCR results confirmed the expression trends of selected DEGs. CONCLUSIONS: This study, for the first time, profiled the differentially expressed mRNAs, microRNAs, and lncRNAs in post-traumatic elbow HO using high-throughput RNA sequencing. These findings provide valuable insights into the molecular mechanisms of HO following elbow trauma. The identified hub genes (MMP9, IL6, MMP3, CTSK, and BGLAP), key TF (JUN), and key microRNAs (hsa-miR-124-3p, hsa-miR-548c-3p, and hsa-miR-135b) may serve as potential therapeutic targets for preventing and treating post-traumatic elbow HO.

Humans↗

PubMed2026

Lifestyle interventions to prevent gestational and type 2 diabetes among migrant women from low- and middle-income countries: a systematic review.

Migrant women from low- and middle-income countries (LMICs) living in high-income settings experience disproportionately high risk of gestational diabetes mellitus (GDM) and type 2 diabetes mellitus (T2DM). This review aimed to identify and synthesise culturally adapted lifestyle interventions for preventing or managing GDM and T2DM among migrant women from LMICs, focusing on intervention components, cultural adaptation strategies, and behavioural and metabolic outcomes. Five databases (PubMed, Embase, Scopus, CINAHL, Cochrane Central) were searched using Preferred Reporting Items for Systematic reviews and Meta-Analysis 2020 guidelines. Eligible studies included experimental designs involving lifestyle interventions delivered to migrant women from LMICs in high-income countries, reporting outcomes related to GDM or T2DM targeting behaviour change. Data were synthesised narratively; study quality was appraised using RoB2 for RCTs and a structured narrative approach for non-randomised designs. Certainty of evidence was evaluated using GRADE. Eight studies met the inclusion criteria. Sample sizes ranged from 28 to 641 participants. Intervention duration varied from 6 weeks to 12 months. Most interventions incorporated atleast one culturally tailored component, such as bilingual delivery, culturally adapted dietary education, or community-based engagement. Improvements were reported across dietary behaviours, physical activity, glycaemic measures, or diabetes-related knowledge; however, effect sizes were modest and inconsistent. Interventions combining dietary modification, physical activity, and culturally adapted delivery demonstrated greater improvements than exercise-only or digital-only programmes. Overall certainty of evidence ranged from low to moderate. Culturally adapted, multi-component lifestyle interventions show promise for improving behavioural and metabolic outcomes among migrant women from LMICs; however, the evidence base remains limited.

Humans↗