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PubMed2026

Voluntary Knowledge Brokering to Promote Evidence-Based Nursing Practice: A Qualitative Study.

Knowledge brokering is a process of connecting knowledge producers with users to facilitate evidence-based practice through relationship building and information sharing. This descriptive qualitative study aimed to clarify knowledge brokering by nurses in Japanese hospitals. Twelve registered nurses in Japanese hospitals participated. They had over 5 years' clinical experience, including experience in conducting research, particularly staff research, and education. Data were collected through semi-structured individual interviews and analyzed using qualitative content analysis. The analysis revealed a central theme: continuous efforts to foster empathy among colleagues and spontaneously promote evidence-based practice: multifaceted brokering activities by clinical nurses. Findings identified 10 categories categorized into four interconnected gears: establishing the foundational ground, assessing clinical needs and staff readiness, tailoring and diffusing evidence, and sustaining and evolving evidence-based practice. Even nurses without formal titles voluntarily bridged the research-practice gap, providing new insights into informal brokering. Brokers communicated considerately, balanced evidence with clinical context, negotiated practical compromises, and fostered staff research competency.

Humans↗

PubMed2026

Machine learning vs. traditional methods for predicting postoperative cardiac complications after non-cardiac surgery: a systematic review and Bayesian network meta-analysis.

INTRODUCTION: Accurate prediction of peri-operative cardiac complications is critical to optimise pre-operative decision-making. Traditional risk prediction scores, such as the Revised Cardiac Risk Index, show only modest discrimination. Machine learning can model complex, non-linear relationships but their predictive performance compared with traditional scores remains unclear. METHODS: We performed a systematic review and Bayesian network meta-analysis. The primary outcome was postoperative adverse cardiac events following non-cardiac surgery. Prediction models were assessed relative to the Revised Cardiac Risk Index. As many studies evaluated multiple versions of each model type, the highest performing ('best version') and lowest performing ('worst version') results were analysed. Models were ranked using the surface under the cumulative ranking curve (SUCRA). RESULTS: Thirteen studies evaluating 54 models and 927,113 patients were included. Machine learning approaches generally outperformed traditional risk scores. Automated machine learning ranked highest (SUCRA 96.6) showed the greatest improvement in the best version analysis (mean difference (MD) 0.28 (95%CrI 0.16-0.40)) and remained superior in the sensitivity analysis (MD 0.30 (95%CrI 0.14-0.45)). Gradient boosting models showed superior performance over the Revised Cardiac Risk Index across analysis (best version: MD 0.20 (95%CrI 0.14-0.26), worst version: MD 0.18 (95%CrI 0.12-0.25), SUCRA 82.4). The Gupta Perioperative Risk for Myocardial Infarction or Cardiac Arrest score outperformed the Revised Cardiac Risk Index in the best version analysis (MD 0.16 (95%CrI 0.01-0.32)). Between-study heterogeneity was low. None of the included studies externally validated their machine learning models and only six were judged to be at low risk of bias. DISCUSSION: Most machine learning models showed better discrimination than traditional risk scores, with automated machine learning and gradient boosting models ranking highest. However, study quality, calibration reporting and absence of external validation limit immediate clinical adoption. Prospective, multicentre evaluation is required before integration of these models into peri-operative practice.

Humans↗

PubMed2026

Predicting ACL injury risk in athletes: A systematic review of machine learning-based models.

BACKGROUND: Early ACL injury risk identification in athletes is essential. This systematic review examines machine learning (ML) models for predicting ACL injuries, evaluating their methodological quality, performance, and reliability. METHOD: A comprehensive electronic search was conducted across PubMed, Scopus, Web of Science, and IEEE Xplore databases, supplemented by Google Scholar for grey literature, covering articles published between January 1, 2015, and August 30, 2025. Eligible studies were appraised using the Prediction Model Study Risk of Bias Assessment Tool (PROBAST) for methodological quality and risk of bias, and the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD) guidelines for quality of evidence. RESULTS: Ten studies were included. PROBAST showed eight studies had moderate risk of bias and two low risk. TRIPOD found only two studies met quality criteria. ML models included logistic regression (n = 5), support vector machines (n = 4), k-nearest neighbor (n = 3), decision trees (n = 3), random forests (n = 5), neural networks (n = 2), linear discriminant analysis (n = 1), and pre-trained CNNs (n = 1). AUC ranged from 0.63 to 0.98. Accuracy (reported in six studies) ranged from 26% to 95%; however, these values should be interpreted with caution due to the absence of confidence intervals, lack of class imbalance handling, and limited external validation across studies. Tree-based ensemble methods such as random forest achieved competitive accuracy (74-86%), while SVM, a non-ensemble classifier, reported accuracy ranging from 71% to 95%; however, the highest values were obtained in studies with notably small sample sizes (n = 12 to n = 39), raising concerns about overfitting and generalizability. CONCLUSION: Current ML algorithms show promise for identifying athletes at high ACL injury risk and detecting relevant risk factors. Although study quality was generally satisfactory, future research should prioritize external validation and model interpretability to support clinical translation.

Humans↗

PubMed2026

Chronic neurological diseases with acute respiratory failure in a real-life cohort: insights into ICU and long-term survival-A retrospective study.

BACKGROUND: Patients with chronic neurological diseases (CND) are at increased risk of pulmonary complications that often require ICU admission. This study aimed to identify clinical factors associated with ICU mortality and long-term survival in patients with CND who developed acute respiratory failure (ARF). METHODS: This retrospective cohort study was conducted in a level III respiratory ICU. Patients with pre-existing CND admitted to the ICU with ARF were included. ICU mortality was analyzed using multivariable logistic regression. Long-term survival after ICU discharge was evaluated using Kaplan-Meier survival analysis and Cox proportional hazards models. Mortality timing was further characterized using hazard function analysis. RESULTS: A total of 220 patients were included; the most common neurological diagnoses were dementia (37.3%), stroke (22.7%), and amyotrophic lateral sclerosis (14.1%). ICU mortality was 33.6%. Higher APACHE II scores were independently associated with increased ICU mortality (OR 1.076 per point increase; 95% CI 1.029-1.126; p < 0.001). Long-term survival differed significantly by post-discharge respiratory support strategy, with Kaplan-Meier analysis demonstrating more favorable survival patterns among patients receiving home non-invasive mechanical ventilation (NIMV) (p = 0.003). In Cox regression analysis, age, home NIMV, and feeding modality at discharge were independently associated with long-term outcomes. Survival analyses revealed an early clustering of deaths within the first months after ICU discharge, particularly among patients with dementia. CONCLUSIONS: In patients with CND, acute physiological severity was the main determinant of ICU mortality, whereas long-term survival after ICU discharge was poor, with deaths clustering within the first months thereafter. Post-discharge respiratory support and nutritional management should be individualized according to the expected clinical trajectory and patient values.

Humans↗

PubMed2026

Electron shuttles facilitate methane-dependent arsenate reduction in paddy soils.

Methane-dependent arsenate reduction (M-AsR) occurs widely in paddy soils and can substantially enhance arsenic mobilization, posing potential ecological risks. However, the role of electron shuttles in this process remains poorly understood. In this study, we investigated the influence of anthraquinone-2,6-disulfonate (AQDS) on M-AsR in paddy soils. Fourteen-day incubation showed that 1 mmol/L AQDS facilitated 50.88 % of arsenate reduction and 31.31 % of methane oxidation. Quantitative polymerase chain reaction analysis revealed that AQDS significantly increased the abundance of functional genes associated with arsenate reduction (arrA, arsC) and anaerobic methane oxidation (mcrA) (P < 0.05). Microbial community analysis revealed that AQDS addition enriched Cloacibacterium, Sphingorhabdus, and Methylocystis, while decreasing the relative abundance of Methylobacter and Methylomonas. These findings indicate that electron shuttles facilitate M-AsR by modulating functional microbial populations, providing valuable insights into arsenic biogeochemistry and the coupled cycling of methane and arsenic in paddy soils.

Methane↗

PubMed2026

Indigenous and local knowledge inclusion in forest fauna research: A systematic review in the tropics.

Indigenous and Local Knowledge (ILK) is an expression of biocultural diversity and is vital for inclusive and sustainable forest management and epistemic justice. We examine how researchers studying tropical forest fauna engage with ILK and the Indigenous Peoples and Local Communities (IPLC) who are holders of this knowledge. We conducted a systematic review of 62 articles that focus on tropical forest fauna and ILK. We used a category-based quantitative and qualitative content analysis on the types of forest fauna studied and how research engages with, defines and represents ILK. We also evaluated the varied forms of inclusion of IPLC in the research. We find that less than half of the reviewed studies (25) explicitly define ILK, and only four studies reported including IPLC in the decision-making processes. Our findings reveal that science has not fully acknowledged and understood the depth of ILK and we suggest ways to address this in future research.

Forests↗

PubMed2026

Teach-Back in Clinical Communication: A Systematic Review and Meta-analysis.

BACKGROUND: Teach-back has been identified as a high-quality clinical communication strategy. Our aim was to synthesize current literature on teach-back effectiveness. METHODS: We searched MEDLINE, Embase, and CINAHL Complete databases to identify relevant studies published between 2018 and 2026. We also included pre-2018 studies identified in prior systematic reviews. Studies were eligible for inclusion if they involved adult patients and/or care partners, delivered teach-back in a single encounter, had a comparator group, and reported proximal/intermediate patient outcomes (as defined in our conceptual model). Two independent investigators screened each citation at the title/abstract and full-text levels and assessed risk of bias. Study characteristics and results were extracted. When meta-analysis was performed, we used standardized mean differences (SMD) to estimate summary effects. We assessed certainty of evidence (COE) using Grading of Recommendations Assessment, Development and Evaluation (GRADE) domains. RESULTS: Our systematic review included 18 randomized controlled trials (RCTs) involving 1985 participants. Across 9 RCTs assessing knowledge acquisition, conceptual inconsistencies precluded meta-analysis. Overall, there was no clear pattern of the effect of teach-back on knowledge (very low COE). In a meta-analysis of 5 RCTs assessing self-efficacy (416 participants), we found that teach-back interventions led to a large increase in self-efficacy relative to usual care (SMD = 2.40; 95%CI 0.37-4.44) (very low COE). In a meta-analysis of 7 RCTs assessing adherence to health behaviors (571 participants), teach-back interventions led to a large increase in adherence (SMD = 1.04; 95%CI 0.45-1.64) (low COE). Meta-analyses for both self-efficacy and adherence had large confidence intervals that ranged from small to large effect sizes and had substantial heterogeneity. DISCUSSION: In this systematic review and meta-analysis, we did not identify a clear benefit of teach-back on knowledge acquisition but did find evidence that teach-back improves self-efficacy and self-reported, short-term adherence to health behaviors.

clinical communication↗

PubMed2026

Interfacial engineering of cobalt tungstate-halloysite nanotube nanocomposite for electrochemical detection of synthetic vanillin in food matrices.

In processed foods and medicine, synthetic vanillin is widely used, although excessive intake poses toxicological risks. Due to the rising usage of synthetic vanillin in food products and associated health hazards, quick, sensitive, and reliable analytical methods are needed to precisely measure vanillin in complex food matrices. This work introduces a CoWO4@F-HNT/GCE nanocomposite as an efficient electrocatalytic modifier for glassy carbon electrodes aimed at trace-level synthetic vanillin detection. Structural and microscopic analyses confirmed phase-pure monoclinic CoWO4, preservation of the tubular aluminosilicate framework, and homogeneous nanoparticle anchoring on F-HNT. Differential pulse voltammetry provided a broad linear range from 0.01 to 372.14 μM and a low detection limit of 4.3 nM, together with excellent selectivity against common interferents, good cycling stability, and high inter-electrode reproducibility. These characteristics position the CoWO4@F-HNT-modified electrode as a cost-effective and reliable platform for on-site quality control of synthetic vanillin in complex food matrices.

Benzaldehydes↗

PubMed2026

Efficacy and Safety of Elagolix Versus Dienogest for Treatment of Moderate-to-Severe Endometriosis Pain: A Phase III, Multicentric, Double-Blind, Active-Controlled, Non-Inferiority Study.

OBJECTIVE: To compare the efficacy, safety and tolerability of elagolix with dienogest in women with moderate-to-severe endometriosis-associated pain. DESIGN: A multicentre, double-blind, double-dummy, randomised, parallel-group, active-controlled, non-inferiority phase III study. SETTING: Nineteen clinical centres across India. STUDY POPULATION: Women (18-49 years) diagnosed with endometriosis and experiencing moderate-to-severe pain. METHODS: Participants were randomised (1:1) to receive oral elagolix (150 mg once daily) or dienogest (2 mg once daily) for 24 weeks. OUTCOME MEASURES: The primary outcome was change in endometriosis-related pain (Numeric Rating Scale [NRS]) from baseline to Day 85. Secondary outcomes included changes in NRS (Day 169), dysmenorrhoea, non-menstrual pelvic pain (NMPP) scores (Days 85 and 169), rescue medication use, patient global impression of change (PGIC), adverse events and bone mineral density. RESULTS: Of 340 patients screened, 230 were randomised (115 per group). At Day 85, both arms showed similar reductions in NRS pain scores with a treatment difference of 0.04 (95% CI: -0.3, 0.37) [p = 0.9747] demonstrating non-inferiority as upper 95% CI was below pre-specified margin of 1.5. At Day 169, both arms showed comparable improvements in overall pain, dysmenorrhoea and NMPP from baseline (p = 0.9372, p = 0.8884, and p = 0.9616, respectively). Rescue medication use and PGIC were comparable between treatment arms. Adverse event incidence was similar (elagolix: 14.8%; dienogest: 19.1%), with no serious TEAEs or discontinuations. No significant bone mineral density changes were observed. CONCLUSIONS: Elagolix demonstrated non-inferiority to dienogest with an acceptable safety and tolerability profile, supporting its use in managing endometriosis-associated pain. TRIAL REGISTRATION: ClinicalTrials.gov identifier: CTRI/2023/01/049292.

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 = 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 = 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 < 0.001) and procedural time by 28% (P = 0.006), increasing number of steps performed by 22% (P = 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

Patient and hospital factors associated with disparities in acute stroke treatment in community and academic hospitals.

BACKGROUND: Systemic barriers may affect identification, emergency transportation (EMS), and care coordination for people with stroke. We assessed patient- and hospital-level factors for associations with pre-hospital and emergency department care. We compared trends for patients presenting to an academic medical center (AMC) versus community hospitals (CHs). METHODS: We conducted a retrospective cohort study at an AMC (Tufts Medical Center) with 542 patients aged ≥18 years hospitalized with acute ischemic stroke or transient ischemic attack between 1/1/2018-12/31/2020 who presented directly to AMC or presented to AMC as a transfer from initial contact CHs. Primary outcomes were EMS use, stroke code activation, door-to-CT time, and door-to-needle time. RESULTS: AMC patients identifying as non-Hispanic Asian (odds ratio (OR) = 0.25; 95% confidence interval (CI) = 0.13-0.47) and Hispanic (OR = 0.19; 95% CI = 0.05-0.72) and CH non-Hispanic Black/African-American patients (OR = 0.17; 95% CI = 0.05-0.62) were less likely to use EMS compared to non-Hispanic white patients. Patients with non-English primary language were less likely to use EMS (OR = 0.38; 95% CI = 0.23-0.63) compared to English-speaking patients in both hospital settings. CH Hispanic patients were less likely to have stroke code activation (OR = 0.24; 95% CI = 0.05-0.86) compared to non-Hispanic white patients. CH patients were less likely to have stroke code activation (OR = 0.12; 95% CI = 0.07-0.19), had 31% shorter door-to-CT time (95% CI = 15-43% shorter), and had 29% longer door-to-needle time (95% CI = 5-58% longer). CONCLUSION: Patient-level factors and hospital setting were associated with differences in acute care suggesting opportunities for community outreach on EMS use, interventions to alleviate language barriers, and a need to address systemic biases.

Humans↗

PubMed2026

Pricing Combination Therapies: A Systematic Review of Value Attribution, Cost-Sharing Mechanisms and Policy Frameworks.

BACKGROUND: Combination therapies are increasingly central to modern pharmacotherapy, particularly in oncology and other high-burden diseases. However, pharmaceutical pricing and reimbursement systems remain largely designed for single-product-single-indication interventions. When multiple patented medicines are used together, especially when owned by different manufacturers, conventional pricing frameworks may struggle to align prices with the value of the combination while preserving incentives for innovation and timely patient access. OBJECTIVE: To identify, describe, and critically assess the methods, models, and policy frameworks proposed in the literature to establish prices for combination therapies, with particular attention to value attribution mechanisms, cost-sharing arrangements between manufacturers, and budget impact considerations. METHODS: A systematic literature review was conducted in accordance with PRISMA guidelines and a pre-registered Open Science Framework protocol. Searches were performed in MEDLINE, Scopus, Web of Science, EconLit, CRD databases, and grey literature sources for publications up to July 2025. Eligible studies analysed pricing approaches, economic models, reimbursement mechanisms, or policy frameworks relevant to combination therapies, including more recent multi-indication pricing literature. Given the heterogeneity of the literature, findings were synthesized using a structured narrative and thematic approach. RESULTS: Sixty-nine studies met the inclusion criteria. The literature was dominated by conceptual and policy analyses, with relatively few empirical or implementation-oriented studies. Value attribution emerged as the central methodological challenge in pricing combination therapies. Several complementary approaches were proposed to operationalise value attribution, including adaptations of indication- or pathway-based pricing, manufacturer cost-sharing arrangements, managed entry agreements, and outcome-based reimbursement mechanisms. Empirical evidence suggests that health systems continue to rely primarily on pragmatic and often partial solutions rather than fully specified pricing frameworks. A complementary review of the multi-indication pricing literature indicates that, although the two fields address different pricing problems, they share important methodological and institutional lessons that can inform the development of pricing frameworks for combination therapies. CONCLUSIONS: The literature provides a growing repertoire of conceptual approaches for pricing combination therapies but limited empirical evidence on implementation. Pricing frameworks should place value attribution at their core while combining complementary policy mechanisms adapted to national pricing and reimbursement systems. Lessons from multi-indication pricing provide a valuable foundation but require additional governance mechanisms to address value attribution, multi-manufacturer negotiation, and implementation challenges specific to combination therapies.

Journal Article↗

PubMed2026

Association Between Statin Use and Dry Eye Disease: A Systematic Review and Meta-Analysis.

TOPIC: This systematic review and meta-analysis evaluated the literature-pooled association between statins and dry eye disease (DED). CLINICAL RELEVANCE: Statins, a common treatment modality for dyslipidemia, have been proposed as a potential contributor to DED via their activity in meibomian gland epithelial cells. However, single studies show mixed evidence, and there remains an unmet clinical need to clarify whether statin exposure is associated with DED. METHODS: This review was reported in accordance with the Preferred Reporting Items for Systematic Reviews of Interventions (PRISMA) 2020 statement and was registered a priori on PROSPERO (CRD420251238004). Ovid MEDLINE, Embase, CINAHL, Web of Science, CENTRAL, and the reference lists of relevant reviews were searched from inception to November 2025 for studies reporting the association between statin use and DED. Random-effects meta-analysis using inverse-variance weighting was conducted to pool effect estimates as odds ratios with 95% confidence intervals (CIs). Study risk of bias was appraised using the ROBINS-E tool, and the certainty of the evidence was reported using the GRADE framework. RESULTS: Six observational studies were included in the meta-analysis (n = 560,821; 356,012/559,141 [63.7%] statin users). The pooled analysis revealed a significant positive association between statins and DED (odds ratio 1.09, 95% CI 1.05-1.13, P < .001), with an absolute risk difference of 10.2 more DED cases per 1000 (95% CI 5.5 more to 15.2 more). This result was derived from very low-certainty evidence given limitations in study design and serious inconsistency. Subgroup and sensitivity analyses for risk of bias (P = .123), method of outcome ascertainment (P = .737), type of effect estimate (P = .496), and leave-one-out analyses showed no evidence of effect modification and demonstrated consistent direction of association across studies. CONCLUSION: Statin use was associated with a small but statistically significant increase in DED, limited by very low-certainty evidence. Physicians should monitor for and educate patients on ocular surface symptoms in patients using statins with pre-existing DED risk factors. Future studies should use standardized DED diagnostic criteria to investigate the impact of statin dose, type, and duration to better characterize this potential association.

Humans↗

PubMed2026

Mechanisms of Hematopoietic Stem Cell Aging and Emerging Rejuvenation Strategies.

Hematopoietic stem cell (HSCs) aging is a complex biological process driven by both cell-intrinsic alterations and extrinsic cues from the bone marrow niche. Understanding these mechanisms is critical for developing therapies against aging-related hematopoietic disorders. This review synthesizes recent advances in the molecular mechanisms underlying HSCs aging, including microenvironmental aging, genomic instability, epigenetic dysregulation, mitochondrial dysfunction, and aberrant nuclear mechanotransduction. We summarize that the functional decline of HSCs during aging drives a compensatory expansion of the phenotypically defined stem cell pool, leading to an aberrant increase in cell number. We also highlight aging-associated HSCs heterogeneity, including CD150high and P-selectin-positive subsets that enrich for myeloid-biased or functionally compromised HSCs states while emphasizing that surface phenotype alone may not fully indicate functional rejuvenation. Finally, we discuss emerging rejuvenation strategies-including targeting myeloid-biased HSCs, modulating inflammatory pathways, and implementing epigenetic or metabolic interventions-supported by cutting-edge technologies such as single-cell multi-omics, gene editing, and computational modeling. These approaches hold promise for counteracting age-related hematopoietic decline and restoring immune competence.

Humans↗

PubMed2026

Transdermal 17β-Estradiol for the Treatment of COVID-19: Protocol of an Early Terminated Phase 2 Randomized Controlled Trial.

BACKGROUND: Early epidemiological studies suggested that pre- and postmenopausal women receiving estrogen therapy were less likely to develop severe disease or die from COVID-19 infection. Potential mechanisms include estrogen-mediated immunomodulation and 17β-estradiol-induced downregulation of angiotensin-converting enzyme type 2 (ACE2), the cellular receptor for SARS-CoV-2. OBJECTIVE: This study aimed to evaluate the feasibility, safety, and preliminary efficacy of transdermal 17β-estradiol as an adjunctive treatment for COVID-19 in men and postmenopausal women. METHODS: We designed and conducted a randomized controlled trial comparing 17β-estradiol transdermal gel plus standard care with standard care alone in adults with confirmed COVID-19. Initial ethics and funding approvals were obtained in March 2021. Owing to changes in the epidemiology of COVID-19 in Qatar and revisions to national quarantine policies, protocol amendments were required before recruitment commenced in February 2022. The treatment duration was reduced from 10 to 7 days due to changes in national quarantine guidelines. Recruitment and follow-up were conducted between February 2022 and June 2022. RESULTS: Recruitment was substantially lower than anticipated because widespread COVID-19 vaccination, declining disease severity, and revised national quarantine policies markedly reduced the number of eligible hospitalized patients. Consequently, the planned sample size was not achieved, and the study was terminated in June 2022. A total of 29 men with mild COVID-19 were enrolled, with 44.8% (n=13) randomized to standard care and 55.2% (n=16) to transdermal 17β-estradiol plus standard care. The intervention was well tolerated, with no adverse safety signals or thromboembolic events reported. CONCLUSIONS: Although the study was underpowered to assess efficacy because recruitment targets were not achieved, it showed that transdermal 17β-estradiol was well tolerated, with no major safety concerns among enrolled participants. The experience also provided important operational lessons for conducting clinical trials during rapidly evolving pandemics. Adequately powered studies are required to determine whether transdermal estrogen has therapeutic potential against COVID-19, other ACE2-mediated coronavirus infections, or potentially other severe viral illnesses.

Humans↗

PubMed2026

Feasibility and effectiveness of the Bergen 4-Day Treatment for obsessive-compulsive disorder in Australia: A pilot comparison with 3-week inpatient obsessive-compulsive disorder treatment.

OBJECTIVES: Obsessive-compulsive disorder is a debilitating and chronic condition that, when untreated or unresponsive to treatment, imposes a significant health and economic burden on individuals and families. This prospective non-randomised inpatient study compared the acceptability and clinical outcomes of the Bergen 4-Day Treatment programme with those of a standard 3-week specialised treatment programme for obsessive-compulsive disorder in Australia. METHOD: Twenty-five participants diagnosed with obsessive-compulsive disorder were non-randomly assigned to Bergen 4-Day Treatment (n = 12) or a 3-week standard (n = 13) inpatient programme. Independent assessments were completed at pre-treatment, 10 days post treatment and at 3-month follow-up. The Yale-Brown Obsessive-Compulsive Scale was rated to assess obsessive-compulsive disorder severity, while secondary measures of depression, anxiety, obsessive beliefs and wellbeing were self-rated by participants. RESULTS: Baseline characteristics of both groups were comparable, with obsessive-compulsive disorder symptom severity within the moderate to severe range. After treatment, obsessive-compulsive disorder symptoms as well as secondary depression and anxiety symptoms were reduced in both treatment groups. Participants receiving Bergen 4-Day Treatment had significantly lower Yale-Brown Obsessive-Compulsive Scale scores at 10 days (M = 13.46) and 3 months (M = 11.84), compared to standard treatment (M = 19.04 and M = 19.15, respectively). Response (91.9%) and remission (45.8%) rates for the Bergen 4-Day Treatment group were significantly higher at both post-treatment timepoints, compared to the standard treatment group. No dropouts occurred in the Bergen 4-Day Treatment group, and participant satisfaction was high. CONCLUSION: The findings of this pilot open-label study suggest that Bergen 4-Day Treatment shows promise as an acceptable, efficient and effective treatment for obsessive-compulsive disorder, warranting further investigation as a scalable alternative for improving access to specialised obsessive-compulsive disorder treatment in Australia.

Humans↗

PubMed2026

Control of foreign DNA: emerging roles of xenogeneic silencers.

Bacteria continuously acquire foreign DNA through horizontal gene transfer, yet its successful integration depends on regulatory mechanisms that balance genome protection with evolutionary innovation. Xenogeneic silencers are central to this process: they preferentially bind AT-rich DNA, a common feature of many horizontally acquired genetic elements, and repress its transcription. Recent studies, however, reveal a much broader regulatory repertoire. Beyond transcriptional repression, these proteins contribute to chromosome organization by forming higher-order nucleoprotein complexes and phase-separated condensates that shape bacterial nucleoid architecture. Furthermore, they play roles in regulating bacteriophage infection cycles, including mechanisms by which phages hijack host silencing activities for their own benefit. Their extensive regulatory reach, spanning virulence genes, biofilm formation, specialized metabolite production, and mobile genetic elements (MGEs), underscores their central role in connecting environmental signals, including fluctuations in the second messenger c-di-GMP, with gene expression, and genome organization. The diversification of xenogeneic silencers across bacterial chromosomes, plasmids, phages, and other MGEs highlights their evolutionary significance. Together, these recent findings position xenogeneic silencers as dynamic regulatory modules that shape the fate of foreign DNA across the horizontal gene transfer network.

Gene Transfer, Horizontal↗

PubMed2026

Comparative effectiveness of game-based learning modalities in nursing and medical education: a systematic review and Bayesian network meta-analysis.

BACKGROUND: Game-based learning (GBL) is increasingly used in healthcare education, but educators must choose among diverse modalities (e.g., quiz platforms, apps, serious games and metaverse environments). Comparative evidence on which modalities perform best across learning domains (knowledge, attitudes, and practice) remains limited. AIM: To compare the effects of distinct GBL modalities on knowledge, attitudes, and practice outcomes in nursing and medical education and to explore whether comparative effects differ by learner group (pre-licensure students and in-service professionals). DESIGN: PRISMA-NMA-aligned systematic review and Bayesian network meta-analysis. METHODS: We searched eight databases and trial registries through September 2, 2024, for randomized controlled trials comparing GBL with traditional teaching (TT). Outcomes were transformed to a 0-100 scale and analysed as change from baseline in Bayesian consistency models; random-effects models were selected using deviance information criterion (DIC). Risk of bias was assessed using RoB 2. We report mean differences (MDs) with 95% credible intervals (CrIs) versus TT, ranking probabilities, and subgroup NMAs by learner group. RESULTS: Thirty-one RCTs (n = 3439) were included; 15 contributed complete data to the network. Risk of bias was low in 15 trials and raised some concerns in 16. The network was modest for knowledge (11 trials) and sparse for attitudes (3) and practice (4). Compared with TT, metaverse-based learning showed improved attitudes (MD 15; 95% CrI 12 to 18), based on a single trial. For knowledge and practice, Kahoot-based quizzes (MD 9.1; 95% CrI -8.9 to 27) and app-based learning (MD 4.6; 95% CrI -4.4 to 14) had the highest estimated mean improvements, but credible intervals were wide and included the null for most comparisons. Subgroup rankings differed by learner group, but several comparisons were imprecise and uncertainty was substantial, particularly in sparse networks. CONCLUSIONS: GBL modalities may improve learning outcomes compared with TT, but relative effects appear domain-specific and the certainty of rankings is limited by sparse evidence and imprecision. Future trials should prioritise head-to-head comparisons, robust outcome measurement, and longer-term retention and transfer outcomes in both student and in-service populations.

Humans↗