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

AIM:To investigate the effects of the γ-aminobutyric acid(GABAergic)neural pathway from the anterior cingulate cortex(ACC)to the nucleus accumbens(NAc)on the regulation of irritable bowel syndrome(IBS)and its underlying mechanisms in mice.METHODS:(1)A C57BL/6J mice model of IBS was established by using chronic acute combing stress(CACS).The mice were divided into a normal group and an IBS group(n=8).The presence of IBS-like symptoms was determined through behavioural tests,an intestinal motility test and abdominal withdrawal reflex scores.(2)Fluorescence gold(FG)retrograde tracing and immunohistochemistry were used to investigate the ACC-NAc GABAergic neural pathway and to examine the activation of GABA in the ACC in IBS mice(n=8).(3)A total of 1.5 μL of normal saline(NS),GABAA receptor antagonist bicuculline(BIC)or agonist isoguvacine hydrochloride(Isog)was ad-ministered via a preburied catheter into the NAc of mice in IBS and normal groups.The mice were randomly divided into three groups(n=8):NS group,BIC group and Isog group.IBS-like symptoms were assessed.(4)The mice were prein-jected with AAV2/9-mDlx-iCre-WPRE-pA in the ACC and AAV2/2Retro Plus-hSyn-DIO-hM3D(Gq)-eGFP-WPRE-pA in the NAc and subsequently divided into four groups(n=8):NS(intraperitoneal injection)+NS(NAc microinjection)group,NS+BIC group,clozapine N-oxide(CNO)+NS group and CNO+BIC group.The mice who received AAV2/2Retro-hSyn-DIO-hM4D(Gi)-EGFP-WPRE-pA in the NAc were randomly divided into three groups(n=8):NS+NS group,NS+BIC group and CNO+NS group.Enzyme-linked immunosorbent assay(ELISA)was employed to estimate the expression levels of histamine and 5-hydroxytryptamine(5-HT)in colon tissue,and the effects of GABAergic neural pathways from ACC to NAc on IBS were studied.RESULTS:CACS induced IBS-like symptoms in mice.The results of FG retrograde tracing combined with fluorescence immunohistochemistry showed that GABA neurons of ACC could project to NAc.The injection of BIC in the NAc was found to significantly reduce anxiety-like behaviours,diarrheal symptoms and visceral hy-persensitivity in the IBS mice(P<0.05).Chemogenetic inhibition of the ACC-NAc GABAergic neurons ameliorated IBS-like symptoms in mice(P<0.05).CONCLUSION:The GABAergic pathway of ACC-NAc might be involved in the regu-lation of IBS in mice,which may be related to the release of histamine and 5-HT in colon tissue.

Objective:To explore the current situation, hot spots and trends of research on the prevention and treatment of diabetes peripheral neuropathy with TCM; To provide reference for scientific research and clinical practice.Methods:Literature related to the prevention and treatment of diabetic peripheral neuropathy with TCM was retrieved from CNKI and Web of Science from the establishment of the databases to December 31, 2021. CiteSpace 6.1.3 software was used to visualize the knowledge map of the number of articles, journals, authors, institutions, keyword clustering, and keyword emergence.Results:A total of 793 core articles were included, including 692 in CNKI and 101 in Web of Science. The research on the TCM prevention and treatment of diabetes peripheral neuropathy was on the rise. Liu Tonghua (Beijing University of Chinese Medicine) wrote most Chinese articles, while Liang Xiaochun (Peking Union Medical College Hospital) wrote more English articles. The research institutions were mainly medical colleges and universities and their affiliated hospitals. Current research hotspots and future development trends mainly included the following aspects: TCM compounds, acupuncture therapy, oxidative stress, nerve conduction velocity, expression of related pathogenic genes, randomized controlled experiments, data mining, systematic evaluation, etc.Conclusion:At present, the research on the TCM prevention and treatment of diabetic peripheral neuropathy at home and abroad has gradually entered a stable development stage and has a certain research scale. However, it is necessary to strengthen the cooperation and communication between research teams and institutions and promote sustainable clinical efficacy evaluation and basic research development.

With the development of the Scientific, Transparent and Applicable Rankings tool for clinical practice guidelines(STAR), the publication of evaluation and ranking for scientificity, transparency and applicability of Chinese guidelines and consensus published in the medical journals in 2021and 2022, as well as the publication of the STAR evaluation and ranking for some specialities, the STAR evaluation and ranking has received widespread attention in the medical community. In order to further enhance its scientificity and transparency, Methodology and Technology Specialization Committee of the STAR Working Group presents this article to introduce sample identification and speciality assignment in the evaluation and ranking process.

National health standards involve all kinds of technical requirements formulated and numbered in accordance with the procedures and formats stipulated in the standardisation system for the implementation of national health and hygiene laws, regulations and policies, and the protection of human health. The establishment of health standards in China should align with our legal framework, including laws, regulations, departmental rules, and health and hygiene policies. During the development of these standards, a comprehensive approach is advocated, encompassing in-depth investigations, rigorous demonstrations, and extensive stakeholder engagement. However, the process of standard formulation may suffer from insufficient research evidence. The evidence-based concept emphasizes the significance of evidence. Therefore, integrating evidence-based concept into the process of developing health standards can enhance the quality and scientific basis of these standards. This article systematically elucidates the current status and development process of health standards in China, explores the necessity and feasibility of incorporating evidence-based concept into the development of these standards, analyzes the challenges and opportunities, and presents reflections and suggestions.

The essence of clinical practice guidelines lies in their recommendations. It is common to find strong recommendations supported by low-quality evidence in current published guidelines. There is a typical misunderstanding among medical professionals that without high-quality evidence, it is impossible to develop high-quality guidelines or only expert consensus can be developed. Based on the GRADE approach, this paper explains the concept and clinical significance of low-quality evidence, and introduces the methods for formulating recommendations based on low-quality evidence in guidelines, with the aim to provide reference for guideline developers and users in China.

Generative artificial intelligence (GAI) refers to AI technology capable of generating new content such as text, images, or audio from training data. GAI tools not only demonstrate rapid and efficient potential in literature screening, data extraction, and literature appraisal in systematic reviews, but can also be used for guideline evaluation and dissemination, enhancing the readability and promotion efficiency of guidelines. However, the accuracy of content generated by GAI tools, the rationality of cited evidence, the level of evidence, and the reliability of data still need verification. Additionally, data privacy protection and ethical issues are challenges that need to be addressed. This article aims to overview the current status of GAI tools in the formulation, evaluation, dissemination, and implementation of guidelines, explore the feasibility and new models of GAI tools in the field of guidelines, and improve the efficiency and quality of guideline formulation to better serve guideline developers and users.

Ferroptosis is a kind of programmed cell death, involves multi-molecular and multi-signaling pathways, and the core processes is iron overload and lipid peroxidation. It affects cancer, neurological disease, cardiovascular disease, digestive system disease, and many other diseases. While, ischemia-reperfusion injury is an extremely complex pathological process, including ischemia-reperfusion injury of the heart, brain, liver and kidney, etc., which often occurs in shock, organ surgery and organ transplantation, seriously affecting human health, and there is no effective radical treatment. However, ferroptosis is closely related to ischemia-reperfusion injury so that it is possible to find the prevention and treatment measures of ischemia-reperfusion injury by exploring the internal relationship between them. Therefore, the author tries to summarize the signaling pathways of ferroptosis, and explores the relationship between ferroptosis and ischemia-reperfusion injury of heart, brain, liver and kidney by moderating the ferroptosis targets properly to find the effective ways to treat cancer, improve inflammation and relieve other diseases.

Objective:To investigate the risk factors of surgical site infection (SSI) after colorectal surgery, and to establish and validate a risk prediction model nomogram.Methods:An observational study was conducted to retrospectively collect data of 6527 patients aged ≥16 years who underwent colorectal surgery in 56 domestic hospitals from March 1, 2021 to February 28, 2022 from the national Surgical Site Infection Surveillance network. The incidence of SSI after surgery was 2.3% (149/6527). According to the ratio of 7:3, 6527 patients were randomly divided into the modeling cohort (4568 cases) and the validation cohort (1959 cases), and there was no statistically significant difference between the two datasets ( P>0.05). Univariate analysis was performed using t test /Mann-Whitney U test /χ 2 test. Multivariate analysis was performed using binary logistic regression to establish a preliminary model and select variables using Lasso analysis to establish an optimized model nomogram. The discrimination and calibration of the model were evaluated by ROC curve, calibration curve, and Hosmer-Lemeshow test. AUC value>0.7 is considered a good discrimination of the model. The Bootstrap method (repeated self-sampling 1000 times) was used to verify the constructed model internally and externally to evaluate the accuracy of the constructed model. Results:Multivariate analysis showed that history of chronic liver disease (OR=3.626, 95%CI: 1.297-10.137, P<0.001) and kidney disease (OR=1.567,95%CI:1.042-2.357, P=0.038), surgical antibiotic prophylaxis (OR=1.564, 95%CI:1.038-2.357, P=0.035), and emergency surgery (OR=1.432,95%CI: 1.089-1.885, P=0.021), open surgery (OR=1.418, 95%CI:1.045-1.924, P=0.042), preoperative stoma (OR=3.310, 95%CI:1.542-7.105, P<0.001), postoperative stoma (OR=2.323,95%CI: 1.537-8.134, P<0.001), surgical incision type above grade II (OR=1.619,95%CI:1.097-2.375, P=0.014), and each unit increase in total bilirubin (OR=1.003,95%CI:-0.994-1.012, P=0.238), alanine aminotransferase (OR=1.006, 95%CI:1.001-1.011, P=0.032), blood urea nitrogen (OR=1.003,95%CI:0.995-1.011, P=0.310), blood glucose (OR=1.024, 95%CI:1.005-1.043, P=0.027), C-reactive protein (OR=1.007, 95%CI:1.003-1.011, P<0.001), length of incision (OR=1.042, 95%CI:1.002-1.087, P=0.031), surgical duration (OR=1.003,95%CI:1.001-1.005, P=0.017), and surgical blood loss (OR=1.001,95%CI: 1.000-1.002, P=0.045) were risk factors for SSI after colorectal surgery. Each unit increase in albumin level (OR=0.969,95%CI:0.941-0.998, P=0.036) was an independent protective factor for SSI after colorectal surgery. The area under the curve of the optimized model obtained by internal and external validation were 0.768 (95%CI: 0.723-0.813) and 0.753 (95%CI: 0.680-0.832), respectively. The predicted value of the calibration curve was basically consistent with the actual value. Conclusions:The risk prediction model for SSI after colorectal surgery constructed in this study has good discrimination and calibration. The nomogram created in this model can provide an evaluation basis for the observed rate and expected event rate of SSI after clinical colorectal surgery.

Objective:To investigate the risk factors of surgical site infection (SSI) after colorectal surgery, and to establish and validate a risk prediction model nomogram.Methods:An observational study was conducted to retrospectively collect data of 6527 patients aged ≥16 years who underwent colorectal surgery in 56 domestic hospitals from March 1, 2021 to February 28, 2022 from the national Surgical Site Infection Surveillance network. The incidence of SSI after surgery was 2.3% (149/6527). According to the ratio of 7:3, 6527 patients were randomly divided into the modeling cohort (4568 cases) and the validation cohort (1959 cases), and there was no statistically significant difference between the two datasets ( P>0.05). Univariate analysis was performed using t test /Mann-Whitney U test /χ 2 test. Multivariate analysis was performed using binary logistic regression to establish a preliminary model and select variables using Lasso analysis to establish an optimized model nomogram. The discrimination and calibration of the model were evaluated by ROC curve, calibration curve, and Hosmer-Lemeshow test. AUC value>0.7 is considered a good discrimination of the model. The Bootstrap method (repeated self-sampling 1000 times) was used to verify the constructed model internally and externally to evaluate the accuracy of the constructed model. Results:Multivariate analysis showed that history of chronic liver disease (OR=3.626, 95%CI: 1.297-10.137, P<0.001) and kidney disease (OR=1.567,95%CI:1.042-2.357, P=0.038), surgical antibiotic prophylaxis (OR=1.564, 95%CI:1.038-2.357, P=0.035), and emergency surgery (OR=1.432,95%CI: 1.089-1.885, P=0.021), open surgery (OR=1.418, 95%CI:1.045-1.924, P=0.042), preoperative stoma (OR=3.310, 95%CI:1.542-7.105, P<0.001), postoperative stoma (OR=2.323,95%CI: 1.537-8.134, P<0.001), surgical incision type above grade II (OR=1.619,95%CI:1.097-2.375, P=0.014), and each unit increase in total bilirubin (OR=1.003,95%CI:-0.994-1.012, P=0.238), alanine aminotransferase (OR=1.006, 95%CI:1.001-1.011, P=0.032), blood urea nitrogen (OR=1.003,95%CI:0.995-1.011, P=0.310), blood glucose (OR=1.024, 95%CI:1.005-1.043, P=0.027), C-reactive protein (OR=1.007, 95%CI:1.003-1.011, P<0.001), length of incision (OR=1.042, 95%CI:1.002-1.087, P=0.031), surgical duration (OR=1.003,95%CI:1.001-1.005, P=0.017), and surgical blood loss (OR=1.001,95%CI: 1.000-1.002, P=0.045) were risk factors for SSI after colorectal surgery. Each unit increase in albumin level (OR=0.969,95%CI:0.941-0.998, P=0.036) was an independent protective factor for SSI after colorectal surgery. The area under the curve of the optimized model obtained by internal and external validation were 0.768 (95%CI: 0.723-0.813) and 0.753 (95%CI: 0.680-0.832), respectively. The predicted value of the calibration curve was basically consistent with the actual value. Conclusions:The risk prediction model for SSI after colorectal surgery constructed in this study has good discrimination and calibration. The nomogram created in this model can provide an evaluation basis for the observed rate and expected event rate of SSI after clinical colorectal surgery.