To develop a guideline terminology system and promote its standardization, thereby enhancing medical staff's accurate understanding and correct application of guidelines.

To introduce and analyze guideline terminology related to clinical question formulation, evidence retrieval and appraisal, and recommendation development.

In this study, araucarene diterpenes, characterized by a pimarene skeleton with a variably oxidized side chain at C-13, were investigated. A total of 16 araucarene diterpenoids and their derivatives were isolated from the woods of Agathis dammara, including 11 previously unreported compounds: dammaradione (1), dammarones D-G (2, 5, 14, 15), dammaric acids B-F (8-12), and dammarol (16). The structures of these new compounds were elucidated using high-resolution electrospray ionization mass spectroscopy (HR-ESI-MS) and one-dimensional/two-dimensional (1D/2D) nuclear magnetic resonance (NMR), while their absolute configurations were determined through the electronic circular dichroism (ECD) exciton chirality method and Snatzke's method. The hypoglycemic activity of all isolated compounds was evaluated using a transgenic zebrafish model, and a structure-activity relationship (SAR) analysis was conducted. Araucarone (3) and dammaric acid C (9), serving as representative compounds, demonstrated significant hypoglycemic effects on zebrafish. The primary mechanism involves the promotion of pancreatic β cell regeneration and glucose uptake. Specifically, these compounds enhance the differentiation of pancreatic endocrine precursor cells (PEP cells) into β cells in zebrafish.
Zebrafish ; Animals ; Diterpenes/isolation & purification* ; Insulin-Secreting Cells/cytology* ; Glucose/metabolism* ; Hypoglycemic Agents/isolation & purification* ; Molecular Structure ; Structure-Activity Relationship ; Plant Extracts/pharmacology* ; Regeneration/drug effects*

The medical metaverse is a combination of medicine and other cutting-edge technologies such as computer and information ones. In the medical metaverse, medical knowledge in the real world will be transformed into a digital form, so that activities concerning diagnosis, treatment, education and clinical practice can be carried out in a virtual environment. Based on the latest research advances at home and abroad, this review expounds on the medical metaverse from the aspects of supporting technologies, applications in clinic and medical education, current deficiencies and future development.

Objective To establish a nomogram model for predicting clinical pregnancy rate in patients with endometriosis undergoing fresh embryo transfer.Methods We retrospectively collected the data of 464 endometriosis patients undergoing fresh embryo transfer,who were randomly divided into a training dataset(60%)and a testing dataset(40%).Using univariate analysis,multiple logistic regression analysis,and LASSO regression analysis,we identified the factors associated with the fresh transplantation pregnancy rate in these patients and developed a nomogram model for predicting the clinical pregnancy rate following fresh embryo transfer.We employed an integrated learning approach that combined GBM,XGBOOST,and MLP algorithms for optimization of the model performance through parameter adjustments.Results The clinical pregnancy rate following fresh embryo transfer was significantly influenced by female age,Gn initiation dose,number of assisted reproduction cycles,and number of embryos transferred.The variables included in the LASSO model selection included female age,FSH levels,duration and initial dose of Gn usage,number of assisted reproduction cycles,retrieved oocytes,embryos transferred,endometrial thickness on HCG day,and progesterone level on HCG day.The nomogram demonstrated an accuracy of 0.642(95%CI:0.605-0.679)in the training dataset and 0.652(95%CI:0.600-0.704)in the validation dataset.The predictive ability of the model was further improved using ensemble learning methods and achieved predicative accuracies of 0.725(95%CI:0.680-0.770)in the training dataset and 0.718(95%CI:0.675-0.761)in the validation dataset.Conclusions The established prediction model in this study can help in prediction of clinical pregnancy rates following fresh embryo transfer in patients with endometriosis.

Objective To investigate the key genes associated with ferroptosis in peri-implantitis and explore the potential mecha-nisms regulating peri-implantitis.Methods Several datasets were obtained from the GEO database.Differential expressed genes were screened,and GO and KEGG analyses were performed.A PPI network was constructed using the STRING website.Key genes were val-idated using a test set,and the diagnostic value of key genes was determined.The content and proportion of 22 immune cells in peri-im-plantitis tissues were obtained through immune infiltration analysis.Key genes were validated by qRT-PCR and Western Blot(WB).Results There were 1 138 differential genes between peri-implantitis tissues and normal gingival tissues,of which 29 were related to ferroptosis.The gene expression in peri-implantitis tissues mainly involved processes such as immune response activation.Five key genes in the ferroptosis-related differential genes,namely SOX2,GJA1,IL1B,GPX2 and CHAC1,were differentially expressed in peri-implantitis tissues and had high diagnostic value.Immune infiltration analysis showed significant changes in immune cells such as memory B cells and plasma cells in peri-implantitis tissues.qRT-PCR and WB confirmed significant differential expression of mRNA and the protein transcribed by key genes.Conclusion Differential genes between peri-implantitis and ferroptosis are screened using bioinformatics analysis and biological validation,providing new insights into the study on peri-implantitis.

Objective To establish a nomogram model for predicting clinical pregnancy rate in patients with endometriosis undergoing fresh embryo transfer.Methods We retrospectively collected the data of 464 endometriosis patients undergoing fresh embryo transfer,who were randomly divided into a training dataset(60%)and a testing dataset(40%).Using univariate analysis,multiple logistic regression analysis,and LASSO regression analysis,we identified the factors associated with the fresh transplantation pregnancy rate in these patients and developed a nomogram model for predicting the clinical pregnancy rate following fresh embryo transfer.We employed an integrated learning approach that combined GBM,XGBOOST,and MLP algorithms for optimization of the model performance through parameter adjustments.Results The clinical pregnancy rate following fresh embryo transfer was significantly influenced by female age,Gn initiation dose,number of assisted reproduction cycles,and number of embryos transferred.The variables included in the LASSO model selection included female age,FSH levels,duration and initial dose of Gn usage,number of assisted reproduction cycles,retrieved oocytes,embryos transferred,endometrial thickness on HCG day,and progesterone level on HCG day.The nomogram demonstrated an accuracy of 0.642(95%CI:0.605-0.679)in the training dataset and 0.652(95%CI:0.600-0.704)in the validation dataset.The predictive ability of the model was further improved using ensemble learning methods and achieved predicative accuracies of 0.725(95%CI:0.680-0.770)in the training dataset and 0.718(95%CI:0.675-0.761)in the validation dataset.Conclusions The established prediction model in this study can help in prediction of clinical pregnancy rates following fresh embryo transfer in patients with endometriosis.

  Objective  To analyze the current status of the development of adaptation guidelines in China, as well as their methodological quality and the reporting quality, in order to provide reference for the development of adaptation guidelines.  Methods  We searched and collected adaptation guidelines led by Chinese researchers or institutions from 2015 to 2023 from four electronic databases, China National Knowledge Infrastructure, WanFang Data Knowledge Service Platform, SinoMed and PubMed, extracted the basic information of the adapted guidelines, and assessed their methodological quality and reporting quality using the Appraisal of Guidelines for REsearch and Evaluation (AGREE) Ⅱ and RIGHT-Ad@pt tools.  Results  A total of 14 adaptation guidelines were included, mainly focusing on nursing (42.9%, 6/14), with the most frequently used adaptation method of ADAPTE (71.4%, 10/14), and with reference to pre-existing guidelines mainly from the United States, the United Kingdom, and international organizations. Assessment by the AGREE Ⅱ tool showed that the average methodological quality score of the adapted guidelines was 36.6%. The scores were relatively high in the domains of clarity of expression and rigor of formulation (44.4% and 54.9%), and lowest in the domain of applicability (15.3%). The results of the RIGHT-Ad@pt tool showed that the reporting quality of the adaptation guidelines was relatively good, with the highest reporting rate of 91.2% and the lowest of 35.3%, and the reporting rates of seven articles were higher than 70%.  Conclusions  Adaptation guidelines in China are still in their infancy, with a relatively small number and mainly focusing on the nursing field. The most commonly used adaptation method is the ADAPTE method. The methodological quality and reporting quality of adaptation guidelines need to be further improved, and more research should be conducted on the specific conditions and timing of adaptation guidelines development.

  Objective  To promote the development of high-quality health standards in China and summarize the characteristics of global health standards management systems and development processes.  Methods  We conducted a systematic search of relevant databases and the websites of standardization institutions. A descriptive method was used to analyze the basic characteristics of the standard management systems and development processes.  Results  The majority of the investigated countries and organizations primarily implement voluntary standards, with the exception of Chinese and the European Committee for Standardization that enforce compulsory standards. All countries and organizations have health standards at the national, group, and enterprise levels. In China and Japan, standards authorities are subordinate to the government, while in other countries or organizations, they operate as independent civil societies. The development process for health standards generally involves five stages: "Project/Proposal → Draft → Enquiry → Review → Publication". However, the specific steps in the development of health standards vary across different countries and organizations. Furthermore, China ranks high in the number of both standards and health standards issued, but the proportion of health standards is only 2.06%.  Conclusions  There are significant differences between China and other countries in terms of the management system and development process of health standards. To promote the management and development of high-quality health standards in China, we recommend promoting the coordination mechanism for standard development, increasing efforts to publicize standards and evaluate the implementation effect, strengthening the construction of personnel for the development of health standards, optimizing the efficiency of standard development and improving the internationalization level of health standards.