Effective annotation of in vivo drug metabolites using liquid chromatography-mass spectrometry (LC-MS) remains a formidable challenge. Herein, a metabolic reaction-based molecular networking (MRMN) strategy is introduced, which enables the "one-pot" discovery of prototype drugs and their metabolites. MRMN constructs networks by matching metabolic reactions and evaluating MS² spectral similarity, incorporating innovations and improvements in feature degradation of MS² spectra, exclusion of endogenous interference, and recognition of redundant nodes. A minimum 75% correlation between structural similarity and MS² similarity of neighboring metabolites was ensured, mitigating false negatives due to spectral feature degradation. At least 79% of nodes, 49% of edges, and 97% of subnetworks were reduced by an exclusion strategy of endogenous ions compared to the Global Natural Products Social Molecular Networking (GNPS) platform. Furthermore, an approach of redundant ions identification was refined, achieving a 10%-40% recognition rate across different samples. The effectiveness of MRMN was validated through a single compound, plant extract, and mixtures of multiple plant extracts. Notably, MRMN is freely accessible online at https://yaolab.network, broadening its applications.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

ObjectiveTo explore the target of Erzhiwan in reducing myocardial injury in ovariectomized mice through non-targeted myocardial metabolomics combined with experimental verification. MethodsOvariectomized mouse model was selected， 40 female C57BL/6 mice were randomly divided into sham operation group， model group， estrogen group（estradiol valerate， 1.3×10^-4 g·kg^-1）， Erzhiwan low and high dose groups（3.12， 9.36 g·kg^-1）， with 8 mice in each group. Each administration group was given the corresponding dose of Erzhiwan by gavage， and the sham operation group and model group were given equal volume of distilled water by gavage for 12 weeks. Echocardiography was used to detect cardiac function， hematoxylin-eosin（HE） staining was used to observe myocardial morphological changes， and enzyme-linked immunosorbent assay（ELISA） was used to detect the levels of estrogen， N-terminal pro-brain natriuretic peptide（NT-proBNP）， hypersensitive troponin T（hs-TnT）， total cholesterol（TC）， triglyceride（TG）， low density lipoprotein cholesterol（LDL-C）， high density lipoprotein cholesterol（HDL-C）， interleukin（IL）-1β， IL-18 and tumor necrosis factor-α（TNF-α）. The non-targeted metabolomics of mouse myocardium were analyzed by ultra performance liquid chromatography-quadrupole-electrostatic field orbital trap high-resolution mass spectrometry（UPLC-Q-Exactive Orbitrap MS）， and the differential metabolites and corresponding metabolic pathways were obtained. The mRNA expression levels of phosphatidylinositol 3-kinase（PI3K） and protein kinase B（Akt） in mouse myocardial tissues were detected by real-time fluorescence quantitative polymerase chain reaction（Real-time PCR）， and the protein expression levels of PI3K， Akt， phosphorylated（p）-Akt were detected by Western blot. ResultsCompared with the sham operation group， the model group showed abnormal cardiac function， increased myocardial fiber space， cardiomyocyte atrophy， sarcoplasmic aggregation， and occasional dissolution or rupture of muscle fiber， the level of estrogen in the serum was decreased， the levels of NT-proBNP， hs-TnT， IL-1β， IL-18， TNF-α， TG， TC and LDL-C were increased， and the level of HDL-C was decreased（P<0.01）. Compared with the model group， Erzhiwan could increase the level of estrogen， improve the abnormal cardiac function， reduce the pathological injury of myocardial tissue， decrease the levels of myocardial injury markers（NT-proBNP， hs-TnT） and inflammatory factors（IL-1β， IL-18， TNF-α）， decrease the levels of TG， TC， LDL-C， and increased the level of HDL-C（P<0.01）. The results of non-targeted myocardial metabolomics showed that 31 of the 162 differential metabolites between the model group and sham operation group were significantly adjusted after administration of Erzhiwan， which were mainly glycerol phospholipid metabolites. Pathway enrichment results showed that Erzhiwan mainly affected glycerophospholipid metabolic pathway， PI3K-Akt pathway， cyclic guanosine monophosphate（cGMP）-protein kinase G（PKG） pathway and other metabolic pathways. Compared with the sham operation group， the levels of phosphatidylcholine（PC， 11 types） and phosphatidylethanolamine（PE， 5 types） in mouse myocardial tissue of the model group were increased（P<0.05， P<0.01）， and the mRNA and protein expressions of PI3K and p-Akt were decreased（P<0.05， P<0.01）. Compared with the model group， the levels of PC（11 types） and PE（5 types） were decreased（P<0.05， P<0.01） in myocardial tissue of Erzhiwan group， the mRNA and protein expressions of PI3K and p-Akt were elevated（P<0.01）. ConclusionErzhiwan can alleviate the pathological injury of myocardium in ovariectomized mice， improve the abnormal cardiac function， improve lipid metabolism disorder， and reduce the levels of myocardial injury markers and inflammatory factors， which involves a number of signaling and metabolic pathways in the heart， among which glycerophospholipid metabolism pathway and PI3K/Akt pathway may have key roles.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective To observe the value of nomogram based on enhanced cortical phase CT Radscore combined with CT features for predicting synchronous distant metastasis(SDM)of renal cell carcinoma(RCC).Methods Totally 139 RCC patients from center A were retrospectively enrolled and divided into SDM group(n=46)and non-SDM group(n=93),also classified as training set(n=97)and test set(n=42)at a ratio of 7∶3.Additionally,20 RCC patients from center B were included as validation set(8 cases with SDM and 12 cases without SDM).Radiomics features were extracted and screened based on enhanced cortical phase CT images to calculate Radscore.Multivariate logistic regression analysis was performed to identify independent predictors of RCC SDM among clinical and CT features.Then a logistic regression model was constructed combining Radscore and independent predictors of RCC SDM and visualized as a nomogram.The receiver operating characteristic curve and the area under the curve(AUC)was used to assess the efficacy of the nomogram for predicting RCC SDM.Results The maximum tumor diameter,CT-T stage and perirenal adipose stranding were all independent predictors of RCC SDM(all P＜0.01).Radscore was calculated based on 5 optimal features.The nomogram was constructed based on perirenal adipose stranding,CT-T stage and Radscore.AUC of the model for predicting RCC SDM in training set,test set and validation set was 0.964,0.921 and 0.885,respectively.Conclusion Enhanced cortical phase CT Radscore combined with perirenal adipose stranding and CT-T stage could effectively predict RCC SDM.

Objective To compare the changes of the Chinese Materia Medica resources(CMMR)in Sichuan based on the data of the 3rd Chinese Materia Medica Resource Inventory(CMMRI,1983-1986)and the 4th CMMRI(2011-2022).Methods Using new techniques,after field investigation,collection and identification of the specimens of the animals,plants and minerals.The data of the CMMR in Sichuan found in the 4th CMMRI were analysed and compared with the data of 3rd CMMRI.Results ①9055 species of CMMR were found in Sichuan during the 4th CMMRI,including 8272 species of medicinal plants,745 species of medicinal animals and 38 species of medicinal minerals.Compared with the 3rd CMMRI,the number of CMMR found in Sichuan have greatly increased.The number of medicinal plants increased 5018 species,the number of medicinal animals increased 637 species and the number of medicinal minerals increased 5 species,too.②The medicinal plants is the main part of the CMMR,and the higher plants(7774 species)has the absolute advantage of the CMMR.The top 20 families which have plenty of plant species include Compositae,Rosaceae,Leguminosae,Ranunculaceae,etc.③ Based on the data of the CMMR of the 183 counties in Sichuan,the reserves of 235 species of wild CMMR in Sichuan is about 36.72 million ton.There were 49 CMMR which have reserves beyond 100 thousand tons,such as Arisaematis rhizoma,Epimedii folium,Cimicifugae rhizoma,Acori tatarinowii rhizoma,Gentianae macrophyllae radix,Polygoni multiflori radix etc.④In 2021,there were 215 species of CMMR cultivated in Sichuan,the main species were Aurantii fructus,Chuanxiong rhizoma,Polygonati rhizome,Salviae miltiorrhizae radix et rhizome.The planting area was 8.17 million and the production was 1.26 million ton.⑤All 183 countries were found CMMR,the number of the species of CMMR in 30 countries exceeded 800,including 16 countries which had more than 1000 kinds of CMMR,such as Emeishan,Hongya,Muli etc.The total types of the CMMR(up 118.31%),the reserves of the wild CMMR(up 119 times)and the number of the counties(up 3 times)which had plenty of CMMR,showed a marked increase over the 3rd CMMRI.8 new species were found in the the 4th CMMRI,such as Codonopsis atriplicifolia,Tongoloa tagongensis,Allium xinlongense,etc.Conclusion The species,the reserves of the CMMR and the resource rich countries in Sichuan are the top 3 in China and Sichuan is worthy of the title of"Hometown of Traditional Chinese Medicine".The compositions and types of the family,genus and species of the CMMR in Sichuan have significantly increased.The basic information of the CMR in Sichuan was clearly found out during the 4th CMMRI,and beneficial for the sustainable development and utilization of the CMMR in Sichuan.

Objective:To investigate the influence of changes in the cognitive load of anesthesia residents on the teaching effectiveness of high-fidelity scenario simulation.Methods:Eighty-seven anesthesia residents in a grade-A tertiary hospital from February to November 2022 were divided into groups A, B, and C according to the random number method. Three cases were selected from the anesthesia crisis resource teaching case library for high-fidelity simulation training for the three groups, respectively, using the crossover design to control the order of the cases. Each round of training consisted of pre-training instruction, simulation teaching, and post-training summarization and analysis. After three rounds of simulation teaching, cognitive load, anxiety status, test scores, and non-technical skills were evaluated for all the study participants. SPSS 20.0 was used to perform analysis of variance with repeated measures and Pearson's correlation analysis.Results:All the three groups showed significantly higher cognitive load and anxiety scores during the first-round simulation training than during the second-round and third-round simulation trianing. The test scores were significantly lower in the first round [(87.07±5.66), (88.38±5.41), (89.07±6.17)] than in the second round [(95.69±2.29), (96.10±2.08), (96.07±2.60)] and the third round [(96.34±1.45), (96.38±1.50), (96.17±1.73); all P<0.05]. The non-technical skill scores were also significantly lower in the first round [(37.24±7.58), (38.69±7.27), (39.24±8.74)] than in the second round [(46.17±5.55), (47.07±5.59), (47.59±6.74)] and the third round [(47.17±5.21), (48.48±5.38), (48.24±6.83); all P<0.05]. For simulations with the same cases, the trainees showed significantly higher cognitive load and anxiety scores and significantly lower test scores and non-technical skill scores in the first round than in the second and third rounds ( P<0.05). Conclusions:Anesthesia residents have higher levels of cognitive load and anxiety in the first scenario simulation training, which can reduce learning outcomes, and repeated simulation training can reduce trainees' cognitive load and anxiety.

Objective:To describe the population and area distribution differences in the prevalence of urinary incontinence in middle-aged and elderly adults in 10 areas in China.Methods:A total of 24 913 participants aged 45-95 years who completed the third resurvey of China Kadoorie Biobank during 2020-2021 were included. The prevalence of urinary incontinence was assessed by an interviewer-administered questionnaire, and urinary incontinence was classified as only stress urinary incontinence, only urgency urinary incontinence and mixed urinary incontinence. The prevalence of urinary incontinence and its subtypes were reported by sex, age and area, and the severity of urinary incontinence and treatment were described.Results:The average age of the participants was (65.4±9.1) years. According to the seventh national census data in 2020, the age-standardized prevalence rates of urinary incontinence was 25.4% in women and 7.0% in men. The age-standardized prevalence rates of only stress, only urgency and mixed incontinence were 1.7%, 4.2% and 1.2% in men and 13.5%, 5.8% and 6.1% in women, respectively. The prevalence rates of urinary incontinence and all subtypes in men and the prevalence of urinary incontinence and all subtypes except only stress urinary incontinence in women all increased with age ( P<0.001). After adjusting for age, the prevalence of urinary incontinence in both men and women were higher in rural area than in urban area ( P<0.001). The treatment rates in men and women with urinary incontinence were 15.4% and 8.5%, respectively. Conclusions:The prevalence of urinary incontinence was high in middle-aged and elderly adults in China, and the prevalence rate was higher in women than in men, but the treatment rate of urinary incontinence was low.

Temporomandibular joint (TMJ) diseases are common clinical conditions. The number of patients with TMJ diseases is large, and the etiology, epidemiology, disease spectrum, and treatment of the disease remain controversial and unknown. To understand and master the current situation of the occurrence, development and prevention of TMJ diseases, as well as to identify the patterns in etiology, incidence, drug sensitivity, and prognosis is crucial for alleviating patients′suffering.This will facilitate in-depth medical research, effective disease prevention measures, and the formulation of corresponding health policies. Cohort construction and research has an irreplaceable role in precise disease prevention and significant improvement in diagnosis and treatment levels. Large-scale cohort studies are needed to explore the relationship between potential risk factors and outcomes of TMJ diseases, and to observe disease prognoses through long-term follw-ups. The consensus aims to establish a standard conceptual frame work for a cohort study on patients with TMJ disease while providing ideas for cohort data standards to this condition. TMJ disease cohort data consists of both common data standards applicable to all specific disease cohorts as well as disease-specific data standards. Common data were available for each specific disease cohort. By integrating different cohort research resources, standard problems or study variables can be unified. Long-term follow-up can be performed using consistent definitions and criteria across different projects for better core data collection. It is hoped that this consensus will be facilitate the development cohort studies of TMJ diseases.