Knowledge mapping of barriers and strategies for clinical practice guideline implementation: a bibliometric analysis.

OBJECTIVE: This study provides a comprehensive overview of the knowledge structure and research hotspots regarding barriers and strategies for the implementation of clinical practice guidelines. METHODS: Publications on barriers and strategies for guideline implementation were searched for on Web of Science Core Collection from database inception to October 24, 2022. R package bibliometrix, VOSviewer, and CiteSpace were used to conduct the analysis. RESULTS: The search yielded 21,768 records from 3,975 journals by 99,998 authors from 3,964 institutions in 186 countries between 1983 and 2022. The number of published papers had a roughly increasing trend annually. The United States, the United Kingdom, and Canada contributed the majority of records. The University of Toronto, the University of Washington, and the University of Sydney were the biggest node in their cluster on the collaboration network map. The three journals that published the greatest number of relevant studies were Implementation Science, BMJ Open, and BMC Health Services Research. Grimshaw JM was the author with the most published articles, and was the second most co-cited author. Research hotspots in this field focused on public health and education, evidence-based medicine and quality promotion, diagnosis and treatment, and knowledge translation and barriers. Challenges and barriers, as well as societal impacts and inequalities, are likely to be key directions for future research. CONCLUSIONS: This is the first bibliometric study to comprehensively summarize the research trends of research on barriers and strategies for clinical practice guideline implementation. A better understanding of collaboration patterns and research hotspots may be useful for researchers. SPANISH ABSTRACT: http://links.lww.com/IJEBH/A247.

Unearthing new learning opportunities: adapting and innovating through the 'Antibiotics under our feet' citizen science project in Scotland during COVID-19.

'Antibiotics under our feet' is a Scottish citizen science project that aimed to raise science capital in primary school learners and their teachers through measurement of microbial diversity in urban soil samples in the search for novel antimicrobial compounds. Resistance to antibiotics is rising, posing a global threat to human health. Furthermore, science, technology, engineering and mathematics (STEM) skills are in crisis, jeopardising our capacity to mobilise as a society to fight antimicrobial resistance (AMR). Originally conceived as a response to the AMR and STEM emergencies, our project was hit by the unprecedented challenge of engaging with schools during the COVID-19 pandemic. We describe how we adapted our project to enable remote participation from primary schools and youth groups, utilising COVID-19 response initiatives as opportunities for multi-level co-creation of resources with learners in primary, secondary, and higher education. We produced portable kit boxes for soil sample collection with learning activities and videos linked to the Scottish Curriculum for Excellence. We also addressed glaring project specific content gaps relating to microbiology on English and Simple English Wikipedia. Our hybrid model of working extended our geographical reach and broadened inclusion. We present here the inception, implementation, digital resource outputs, and discussion of pedagogical aspects of 'Antibiotics under our feet'. Our strategies and insights are applicable post-pandemic for educators to develop STEM skills using soil, microbes, and antibiotics as a theme.

Assessing the Risk of Bias in Randomized Clinical Trials With Large Language Models.

Importance: Large language models (LLMs) may facilitate the labor-intensive process of systematic reviews. However, the exact methods and reliability remain uncertain. Objective: To explore the feasibility and reliability of using LLMs to assess risk of bias (ROB) in randomized clinical trials (RCTs). Design, Setting, and Participants: A survey study was conducted between August 10, 2023, and October 30, 2023. Thirty RCTs were selected from published systematic reviews. Main Outcomes and Measures: A structured prompt was developed to guide ChatGPT (LLM 1) and Claude (LLM 2) in assessing the ROB in these RCTs using a modified version of the Cochrane ROB tool developed by the CLARITY group at McMaster University. Each RCT was assessed twice by both models, and the results were documented. The results were compared with an assessment by 3 experts, which was considered a criterion standard. Correct assessment rates, sensitivity, specificity, and F1 scores were calculated to reflect accuracy, both overall and for each domain of the Cochrane ROB tool; consistent assessment rates and Cohen κ were calculated to gauge consistency; and assessment time was calculated to measure efficiency. Performance between the 2 models was compared using risk differences. Results: Both models demonstrated high correct assessment rates. LLM 1 reached a mean correct assessment rate of 84.5% (95% CI, 81.5%-87.3%), and LLM 2 reached a significantly higher rate of 89.5% (95% CI, 87.0%-91.8%). The risk difference between the 2 models was 0.05 (95% CI, 0.01-0.09). In most domains, domain-specific correct rates were around 80% to 90%; however, sensitivity below 0.80 was observed in domains 1 (random sequence generation), 2 (allocation concealment), and 6 (other concerns). Domains 4 (missing outcome data), 5 (selective outcome reporting), and 6 had F1 scores below 0.50. The consistent rates between the 2 assessments were 84.0% for LLM 1 and 87.3% for LLM 2. LLM 1's κ exceeded 0.80 in 7 and LLM 2's in 8 domains. The mean (SD) time needed for assessment was 77 (16) seconds for LLM 1 and 53 (12) seconds for LLM 2. Conclusions: In this survey study of applying LLMs for ROB assessment, LLM 1 and LLM 2 demonstrated substantial accuracy and consistency in evaluating RCTs, suggesting their potential as supportive tools in systematic review processes.

A novel multidisciplinary machine learning approach based on clinical, imaging, colonoscopy, and pathology features for distinguishing intestinal tuberculosis from Crohn's disease.

OBJECTIVES: Differentiating intestinal tuberculosis (ITB) from Crohn's disease (CD) remains a diagnostic dilemma. Misdiagnosis carries potential grave implications. We aim to establish a multidisciplinary-based model using machine learning approach for distinguishing ITB from CD. METHODS: Eighty-two patients including 25 patients with ITB and 57 patients with CD were retrospectively recruited (54 in training cohort and 28 in testing cohort). The region of interest (ROI) for the lesion was delineated on magnetic resonance enterography (MRE) and colonoscopy images. Radiomic features were extracted by least absolute shrinkage and selection operator regression. Pathological feature was extracted automatically by deep-learning method. Clinical features were filtered by logistic regression analysis. Diagnostic performance was evaluated by receiver operating characteristic (ROC) curve and decision curve analysis (DCA). Delong's test was applied to compare the efficiency between the multidisciplinary-based model and the other four single-disciplinary-based models. RESULTS: The radiomics model based on MRE features yielded an AUC of 0.87 (95% confidence interval [CI] 0.68-0.96) on the test data set, which was similar to the clinical model (AUC, 0.90 [95% CI 0.71-0.98]) and higher than the colonoscopy radiomics model (AUC, 0.68 [95% CI 0.48-0.84]) and pathology deep-learning model (AUC, 0.70 [95% CI 0.49-0.85]). Multidisciplinary model, integrating 3 clinical, 21 MRE radiomic, 5 colonoscopy radiomic, and 4 pathology deep-learning features, could significantly improve the diagnostic performance (AUC of 0.94, 95% CI 0.78-1.00) on the bases of single-disciplinary-based models. DCA confirmed the clinical utility. CONCLUSIONS: Multidisciplinary-based model integrating clinical, MRE, colonoscopy, and pathology features was useful in distinguishing ITB from CD.

Molecular stratification of the human fetal vaginal epithelium by spatial transcriptome analysis.

The human vaginal epithelium is a crucial component of numerous reproductive processes and serves as a vital protective barrier against pathogenic invasion. Despite its significance, a comprehensive exploration of its molecular profiles, including molecular expression and distribution across its multiple layers, has not been performed. In this study, we perform a spatial transcriptomic analysis within the vaginal wall of human fetuses to fill this knowledge gap. We successfully categorize the vaginal epithelium into four distinct zones based on transcriptomic profiles and anatomical features. This approach reveals unique transcriptomic signatures within these regions, allowing us to identify differentially expressed genes and uncover novel markers for distinct regions of the vaginal epithelium. Additionally, our findings highlight the varied expressions of keratin ( KRT) genes across different zones of the vaginal epithelium, with a gradual shift in expression patterns observed from the basal layer to the surface/superficial layer. This suggests a potential differentiation trajectory of the human vaginal epithelium, shedding light on the dynamic nature of this tissue. Furthermore, abundant biological processes are found to be enriched in the basal zone by KEGG pathway analysis, indicating an active state of the basal zone cells. Subsequently, the expressions of latent stem cell markers in the basal zone are identified. In summary, our research provides a crucial understanding of human vaginal epithelial cells and the complex mechanisms of the vaginal mucosa, with potential applications in vaginal reconstruction and drug delivery, making this atlas a valuable tool for future research in women's health and reproductive medicine.

Heterologous Expression of Phycocyanobilin in Escherichia coli and Determination of Its Antioxidant Capacity In Vitro.

Phycocyanobilin (PCB) is a blue pigment with antioxidant, anti-inflammatory, and anticancer properties. It is used in the medical and cosmetic industries. In this study, a high-expression plasmid, pET-30a-PCB, was constructed for expression of PCB in Escherichia coli BL21(DE3). The PCB was analyzed using UV-visible absorption spectrum, MALDI-TOF-MS, and fluorescence spectra. The stability and half-life of PCB in different serum were determined. The yield of PCB was optimized through single-factor and orthogonal experiments. The optimal expression conditions were determined as a lactose concentration of 5 mmol/L, an induction time of 8 h, an induction temperature of 27 °C, and an induction duration of 22 h. PCB yield of 6.5 mg/L was achieved and subsequently purified using nickel-affinity chromatography. The purified PCB was quantified indirectly using Hist-tag ELISA detection, and the concentration was 11.66 µg/L. In the range of 0-33 µg/mL, the total antioxidant capacity and reducing the capacity of PCB were stronger than Vitamin E (Ve), with 1,1-diphenyl-2-picrylhydrazil (DPPH) scavenging reaching up to 87.07%, 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonate) free radical (ABTS) scavenging up to 100%, hydroxyl radicals (·OH) scavenging up to 64.19%, hydrogen peroxide (H2O2) scavenging up to 78.75%, This study provides theoretical evidence for PCB as a potent antioxidant.

Vaginal reconstruction by collagen scaffolds loaded with vaginal epithelial and smooth muscle cells in pigs.

In women, a healthy and functional vagina is important for the maintenance of a good quality of life. Various factors, including congenital anomalies, cancer, trauma, infections, inflammation, or iatrogenic injuries, can lead to damage or loss of the vaginal structure, necessitating repair or replacement. Often, such reconstruction procedures involve the use of nonvaginal tissue substitutes, like segments of the large intestine or skin, which are less than ideal both anatomically and functionally. Therefore, there is an urgent need to develop new methods of vaginal reconstruction. In this study, we established a new method for isolation and expansion of vaginal epithelial and smooth muscle cells. Subsequently, collagen scaffolds designed for vaginal reconstruction were loaded with vaginal epithelial and smooth muscle cells in vitro and tested in vivo using the vaginal excision pig model. The results showed that the collagen scaffold loaded with vaginal epithelial and smooth muscle cells significantly promotes the reconstruction of the vagina compared with small intestinal submucosa (SIS) membrane or bare collagen scaffold. Notably, the reconstructed vaginal tissues exhibit remarkable similarity to their normal counterparts, encompassing not only the vaginal epithelium and smooth muscle but also the intricate networks of blood vessels and nerves. These compelling results underscore the feasibility of a tissue engineering approach in vaginal reconstruction, offering promising prospects for improving the quality of life in affected individuals.

Traditional Chinese medicine for insomnia: Recommendation mapping of the global clinical guidelines.

ETHNOPHARMACOLOGICAL RELEVANCE: Traditional Chinese Medicine (TCM) represents a rich repository of empirically-developed traditional medicines. The findings call for more rigorous study into the efficacy, safety, and mechanisms of action of TCM remedies to strengthen the evidence base. AIM OF THE STUDY: To systematically review the quality of insomnia clinical practice guidelines that involve TCM recommendations and to summarize the certainty of evidence supporting the recommendations, strength, and consistency of recommendations, providing valuable research references for the development of future insomnia guidelines. MATERIALS AND METHODS: We systematically searched PubMed, Web of Science, Embase, CNKI, Wanfang, Chinese Biomedical Literature Database, Chinese Medical Association, Chinese Sleep Research Society, Medsci, Medlive, British National Institute of Health and Clinical Excellence (NICE), and the International Guidelines Collaboration Network (GIN) for clinical practice guidelines on insomnia from inception to March 5, 2023. Four evaluators conducted independent assessments of the quality of the guidelines by employing the AGREE II tool. Subsequently, the guideline recommendations were consolidated and presented as evidence maps. RESULTS: Thirteen clinical practice guidelines addressing insomnia, encompassing 211 recommendations (consisting of 127 evidence-based and 84 expert consensus recommendations), were deemed eligible for inclusion in our analysis. The evaluation results revealed an overall suboptimal quality, with the "scope and purpose" domain achieving the highest score (58.1%), while the "applicability" domain garnered the lowest score (13.0%). Specifically, it was observed that 74.8% (n = 95) of the evidence-based recommendations were supported by evidence of either very low or low certainty, in contrast to the expert consensus recommendations, which accounted for 61.9% (n = 52). We subsequently synthesized 44 recommendations into four evidence maps, focusing on proprietary Chinese medicines, Chinese medicine prescriptions, acupuncture, and massage, respectively. Notably, Chinese herbal remedies and acupuncture exhibited robust support, substantiated by high-certainty evidence, exemplified by interventions such as Xuefu Zhuyu decoction, spleen decoction, body acupuncture, and ear acupuncture, resulting in solid recommendations. Conversely, proprietary Chinese medicines needed more high-certainty evidence, predominantly yielding weak recommendations. As for other therapies, the level of certainty was predominantly categorized as low or very low. Recommendations about magnetic therapy, bathing, and fumigation relied primarily on expert consensus, needing more substantive clinical research evidence, consequently forming weak recommendations. Hot ironing and acupoint injection recommendations were weakly endorsed, primarily based on observational studies. Furthermore, interventions like qigong, gua sha, and moxibustion displayed a relatively limited number of clinical studies, necessitating further exploration to ascertain their efficacy. CONCLUSIONS: Our analysis revealed a need for substantial improvement in the quality of all the included guidelines related to insomnia. Notably, recommendations for Traditional Chinese Medicine (TCM) treatments predominantly rely on low-certainty evidence. This study represents a pioneering effort in the utilization of recommendation mapping to both present and identify existing gaps in the evidence landscape within TCM therapies, thus setting the stage for future research initiatives. The evidence supporting TCM therapy recommendations must be fortified to achieve a more substantial level of recommendation and higher certainty. Consequently, there exists a critical and pressing demand for high-quality clinical investigations dedicated to TCM, with a specific focus on ascertaining its long-term efficacy, safety, and potential side effects in the context of insomnia treatment. These endeavors are poised to establish a robust scientific foundation to inform the development of TCM therapy recommendations within the insomnia guidelines.