Traditional Chinese medicine （TCM）， through its multi-target and systematic regulatory effects， has demonstrated unique advantages in the treatment of gastric precancerous lesions （GPL）. At present， TCM theoretical research on GPL is mainly reflected in three aspects， the integration of macroscopic syndrome differentiation， the inflammation-carcinoma transformation mechanism， as well as the systematization and scientization of theoretical inheritance from famous TCM practitioners. High-quality evidence-based research findings serve as the foundation for clinical practice guidelines on GPL， and TCM has gained international academic recognition in the field of GPL prevention and treatment. Research on TCM mechanisms has yielded a series of important outcomes in the aspects of signaling pathways， gene expression regulation， cellular epigenetics， histone modification， and intestinal microecology. It is proposed that future research on GPL should focus on four key directions， establishing multi-omics data， exploring targeted intervention strategies on key regulatory nodes， advancing the standardization process of integrated traditional Chinese and western medicine prevention and treatment technologies， and constructing stratified screening and intervention platforms. The in-depth integration of TCM microcosmic mechanism of action with its macroscopic syndrome differentiation and treatment system， coupled with interdisciplinary research， will provide valuable references for the clinical treatment and scientific research of GPL.

To interpret the evidence-to-decision （EtD） framework and to illustrate its application in traditional Chinese medicine （TCM） guideline development using the example of the Pharmacovigilance Guideline of Chinese Patent Medicine， thereby providing methodological references for TCM guideline standardization. Based on the core three stages of the EtD framework （formulating the question， making an assessment of the evidence， and drawing conclusions）， critical decision points and evaluation evidence within the evidence-translation process were systematically addressed， aligning with the purpose， scope， and key questions of the guideline. Qualitative research methods， such as the nominal group technique， were employed to formulate recommendations. The analysis was conducted based on the EtD framework. During question formulation， the specific characteristics and practical needs of pharmacovigilance for Chinese patent medicines were clarified， focusing on the core objective of safety assurance throughout the product lifecycle. In the evidence assessment， multi-source evidence was integrated， including policy documents， literature research， and expert consensus， completing the evidence evaluation. Finally， in recommendation-forming， dispersed research evidence and expert experience were synthesized into consensus， culminating in the guideline's completion through solicitation of opinions and peer review. The EtD framework provides a structured tool for evidence-to-decision translation in TCM guideline development， effectively enhancing the transparency and scientific rigor of the process. Therefore， it is recommended that TCM guideline development adopt the EtD framework to improve the evidence-to-decision process with TCM characteristics.

To interpret the evidence-to-decision （EtD） framework and to illustrate its application in traditional Chinese medicine （TCM） guideline development using the example of the Pharmacovigilance Guideline of Chinese Patent Medicine， thereby providing methodological references for TCM guideline standardization. Based on the core three stages of the EtD framework （formulating the question， making an assessment of the evidence， and drawing conclusions）， critical decision points and evaluation evidence within the evidence-translation process were systematically addressed， aligning with the purpose， scope， and key questions of the guideline. Qualitative research methods， such as the nominal group technique， were employed to formulate recommendations. The analysis was conducted based on the EtD framework. During question formulation， the specific characteristics and practical needs of pharmacovigilance for Chinese patent medicines were clarified， focusing on the core objective of safety assurance throughout the product lifecycle. In the evidence assessment， multi-source evidence was integrated， including policy documents， literature research， and expert consensus， completing the evidence evaluation. Finally， in recommendation-forming， dispersed research evidence and expert experience were synthesized into consensus， culminating in the guideline's completion through solicitation of opinions and peer review. The EtD framework provides a structured tool for evidence-to-decision translation in TCM guideline development， effectively enhancing the transparency and scientific rigor of the process. Therefore， it is recommended that TCM guideline development adopt the EtD framework to improve the evidence-to-decision process with TCM characteristics.

Background Metals and metalloids in fine particulate matter (PM_2.5) may cause damage to the respiratory and circulatory systems of the human body, and long-term exposure is prone to causing chronic poisoning, cancer, and other adverse effects. Objective To assess the distribution characteristics of metals and metalloids in outdoor PM_2.5 in a southern city of China, conduct source apportionment, and evaluate the associated health risks, thereby providing theoretical support for further pollution control measures. Methods PM_2.5 samples were collected in districts A, B, and C of a southern China city, and the concentrations of 17 metals and metalloids were detected by inductively coupled plasma-mass spectrometry (ICP-MS). Pollution sources were assessed through enrichment factor and principal components analysis, and the main pollution sources were quantified using absolute principal component scores-multivariate linear regression (APCS-MLR). Health risks were evaluated based on the Technical guide for environmental health risk assessment of chemical exposure (WS/T777—2021). Results The ambient air PM_2.5 concentrations in the city were higher in winter and spring, and lower in summer and autumn. The annual average concentrations of ambient PM_2.5 in districts A, B, and C were 36.7, 31.9, and 24.4 μg·m⁻³, respectively. The ambient PM_2.5 levels in districts B and C were below the second-grade limit set by the Ambient air quality standards (GB 3095—2012). The enrichment factors of cadmium (Cd), aluminum (Al), and antimony (Sb) were greater than 10, those of copper (Cu), lead (Pb), arsenic (As), nickel (Ni), mercury (Hg), and molybdenum (Mo) fell between 1 and 10, and those of manganese (Mn), vanadium (V), chromium (Cr), cobalt (Co), barium (Ba), beryllium (Be), and uranium (U) were below or equal to 1. The comprehensive evaluation of source analysis showed that the main pollution sources in districts A and C and the whole city were coal-burning. In district B, the main pollution source was also coal combustion, followed by industrial process sources and dust sources. The carcinogenic risks of As and Cr were between 1×10⁻⁶ and 1×10⁻⁴. However, the hazard quotients for 15 metals and metalloids in terms of non-carcinogenic risk were below 1. Conclusion Cr and As in the atmospheric PM_2.5 of the city present a certain risk of cancer and should be paid attention to. In addition, preventive control measures should be taken against relevant pollution sources such as industrial emission, dust, and coal burning.

Objective: To analyze the association of participation in non-sports extracurricular tutoring classes with the prevalence of screening myopia, axial length (AL) and axial length to corneal radius ratio (AL/CR) among primary school students, so as to provide evidences for formulating myopia prevention and control policies. Methods: In December 2024, combination of convenience and cluster sampling method was used to select 2 273 students from two primary schools in Hefei City, Anhui Province. Ophthalmic examinations and questionnaire surveys were conducted to obtain information on myopia, AL, AL/CR and participation in various types of extracurricular tutoring. A binary Logistic regression model was used to analyze the association between non-sports tutoring and screening myopia, and multiple linear regression models were used to examine the associations between non-sports tutoring and AL and AL/CR. Results: Among the surveyed students, the participation rate in non-sports extracurricular tutoring classes was 64.9% , and the overall prevalence of screening myopia was 39.1%. The average AL and AL/CR were (23.60± 1.01 ) mm and (3.00±0.12), respectively. Univariate analysis showed that students who attended non-sports, music, or academic tutoring classes for ≥2 h per week had higher risks of screening myopia and greater AL/CR values than non-participants (screening myopia: OR =1.38, 1.82, 1.55; AL/CR: β =0.01, 0.03, 0.03; all P <0.05). After adjusting for sex, grade, and participation in sports tutoring, multivariate analysis indicated that participation in non-sports and musical instrument tutoring classes for ≥2 h per week remained significantly associated with higher risks of screening myopia ( OR =1.26, 1.49, both P <0.05). Multiple linear regression showed that participation in musical instrument tutoring for ≥2 h per week was positively correlated with AL ( β=0.14, P < 0.05). Conclusions Participation in non-sports extracurricular tutoring is common among primary school students. Attending non-sports tutoring classes for ≥2 h per week increases the risk of screening myopia.

Objective: To analyze the factors associated with high level fear of negative evaluation (FNE) among junior high school students and to construct a nomogram risk prediction model, so as to provide scientific tools for psychological health intervention for junior high school students. Methods: A convenience sampling combined with cluster random sampling method was used to select 5 485 junior high school students from 4 cities (Wuhan, Huanggang, Xianning and Xiaogan) for an online questionnaire survey in March 2025. The total sample was randomly split into a training set ( n =3 839) and a validation set ( n =1 646). Univariate analysis was performed in the training set using Chi-square test and t-test. Variables with statistical significance were subsequently included in multivariate Logistic regression to identify independent predictors and to construct a nomogram based risk prediction model. The discriminative ability and clinical utility of the model were evaluated in the validation set using the area under the receiver operating characteristic curve (AUC), calibration curve, and decision curve analysis (DCA). Results: There were 1 649 junior high school students with low level FNE and 2 190 with high level FNE in the training set. The self control ability of junior high school students with lowlevel and high level FNE showed a statistically significant difference (23.96±3.96, 21.48±3.37, t=25.15, P < 0.01 ). Statistically significant differences in the detection rate of high level FNE were observed among junior high school students with different genders, family types, parenting styles, academic rankings, psychological flexibility, mobile phone addiction tendencies, emotional management training, exercise frequency, left behind experiences, and places of origin ( χ 2=82.01- 1 126.68 , all P <0.01). The results of Logistic regression analysis revealed that, the following factors were identified as significant factors influencing high level FNE among junior high school students:exercise frequency ( OR=0.21, 95%CI =0.17-0.26); parenting style ( OR=0.48, 95%CI =0.40-0.58); left behind experience ( OR=3.88, 95%CI =3.27-4.61); smartphone addiction proneness ( OR=2.19, 95%CI =0.89-0.93); self-control ability ( OR=0.91, 95%CI =0.89-0.93); and psychological flexibility ( OR=0.16, 95%CI =0.10-0.28) (all P <0.05). The AUC for the training and validation set were 0.88 (95% CI =0.87-0.89) and 0.87 (95% CI =0.85-0.89), respectively. The Hosmer-Lemeshow goodness of fit test yielded χ 2=8.57, 15.20 (both P >0.05). Conclusion The risk prediction model with high level FNE demonstrates good accuracy and can assist educators and parents in timely screening of junior high school students with high level FNE, thereby providing a basis for implementing targeted interventions.

Chemical communication in plant-microbiome and intra-microbiome interactions weaves a complex network, critically shaping ecosystem stability and agricultural productivity. This non-contact interaction is driven by small-molecule signals that orchestrate crosstalk dynamics and beneficial association. Plants leverage these signals to distinguish between pathogens and beneficial microbes, dynamically modulate immune responses, and secrete exudates to recruit a beneficial microbiome, while microbes in turn influence plant nutrient acquisition and stress resilience. Such bidirectional chemical dialogues underpin nutrient cycling, co-evolution, microbiome assembly, and plant resistance. However, knowledge gaps persist regarding validating the key molecules involved in plant-microbe interactions. Interpreting chemical communication requires multi-omics integration to predict key information, genome editing and click chemistry to verify the function of biomolecules, and artificial intelligence (AI) models to improve resolution and accuracy. This review helps advance the understanding of chemical communication and provides theoretical support for agriculture to cope with food insecurity and climate challenges.
Microbiota/physiology* ; Plants/microbiology* ; Artificial Intelligence ; Ecosystem

Objective To explore the influencing factors of coronary artery lesion severity in patients with acute coronary syndrome (ACS). Methods Clinical data of ACS patients admitted to Zhongshan Hospital, Fudan University from December 2017 to December 2019 were consecutively collected. The modified Gensini score was used to assess the severity of coronary artery lesions. Univariate and multivariate linear regression analyses were performed to identify independent factors associated with coronary artery lesion severity. Results A total of 1 689 ACS patients were included, with an average age of (64.04±11.45) years; 1 353 (80.11%) were male, and the mean modified Gensini score was (8.12±4.03). Multivariate linear regression analysis revealed that sex (β＝0.97, P＝0.001), age (β＝0.03, P＝0.021), estimated glomerular filtration rate (eGFR; β＝－0.03, P＜0.001), low-density lipoprotein cholesterol (LDL-C; β＝0.58, P＜0.001), apolipoprotein A1 (Apo A1; β＝－1.28, P＝0.012), lipoprotein(a) [Lp(a); β＝0.001, P＝0.033], and glycated hemoglobin A_1C (HbA_1C; β＝0.45, P＜0.001) were independent influencing factors of the modified Gensini score. Conclusions Metabolic indicators, including Apo A1, LDL-C, HbA_1C, and Lp(a), may serve as risk factors for coronary artery lesion severity in ACS patients, with Apo A1 demonstrating the strongest impact.

Chaihu Longgu Muli Decoction can be used to treat perimenopausal insomnia (PMI). It can be used either alone with modification or in combination with Western medicine or acupuncture and moxibustion and other external TCM treatment methods, which has achieved good efficacy, and can improve the symptoms of patients with difficulty falling asleep and decreased sleep quality, with good safety. The treatment of Chaihu Longgu Muli Decoction for PMI may exert its effects through multiple pathways, such as inhibiting HPA axis hyperactivity, regulating hormone and neurotransmitter levels, inhibiting oxidative stress and inflammatory responses. However, existing clinical studies suffer from issues such as small sample sizes, inconsistent research protocols, and inconsistent efficacy evaluation criteria, which require further improvement and deeper exploration of relevant mechanisms.