With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

Effective symptom management can alleviate the physical and psychological distress experienced by patients with cancer, improve quality of life, and contribute to treatment adherence and improve clinical outcomes. However, most existing guidelines are developed for healthcare professionals, and patients and the public have limited access to standardized and comprehensible guidance on symptom management. To address this gap and to facilitate effective communication and shared decision-making, this study proposes the development of a patient version of the cancer symptom management guideline. The development process will adhere to the methodological framework recommended by the Guidelines International Network and the World Health Organization. The GRADE approach will be employed to assess the certainty of evidence and to formulate recommendations. In addition, the process will be informed by the Appraisal of Guidelines for Research and Evaluation Ⅱ (AGREE Ⅱ) instrument and the Reporting Items for Practice Guidelines in Healthcare-Public or Patient Versions of Guidelines (RIGHT-PVG). This protocol outlines the establishment of the guideline working group, the identification and prioritization of key questions, evidence retrieval and appraisal, and the formulation of recommendations, with the aim of ensuring methodological rigor and transparency in the development of the patient guideline and providing methodological reference for similar guideline initiatives.

ObjectiveThis study aimed to investigate the mechanism by which Luoshi Neiyi prescription treats endometriosis （EMs） through regulating ferroptosis， and to screen key metabolites and analyze their association with ferroptosis. MethodsClinical samples of normal endometrium from patients without EMs and eutopic and ectopic endometrium from EMs patients （10 cases each） were collected and divided into control group， eutopic group， and EMs group. Hematoxylin-eosin （HE） staining was performed to observe ectopic lesions of EMs. Immunohistochemistry was used to detect the expression of solute carrier family 7 member 11 （SLC7A11） and glutathione peroxidase 4 （GPX4）. Enzyme-linked immunosorbent assay （ELISA） was adopted to determine the levels of malondialdehyde （MDA）， ferrous ion （Fe²⁺）， GPX4 and glutathione （GSH） in endometrial tissues， as well as serum levels of Fe²⁺， GPX4 and GSH. Real-time quantitative polymerase chain reaction （Real-time PCR） was used to detect the mRNA expression of SLC7A11， GPX4， transferrin receptor （TFR） and ferritin heavy chain 1 （FTH1）. In the in vitro experiment， primary stromal cells were isolated from ectopic lesions of EMs patients. Cell counting kit-8 （CCK-8） was used to determine the optimal concentration of drug-containing serum for intervention. The level of reactive oxygen species （ROS） was measured， and Real-time PCR was applied to detect ferroptosis-related indicators. In the animal experiments， an EM rat model was established， and the rats were randomly assigned to the sham operation group， EMs group， low-dose Luoshi Neiyi Formula group （7.87 g·kg^-1）， high-dose Luoshi Neiyi prescription group （15.74 g·kg^-1）， and danazol group （42 mg·kg^-1）. Untargeted metabolomics detection and pathway enrichment analysis were conducted on serum samples from patients and rats. Spearman correlation analysis was performed to assess the relationship between differential metabolites and ferroptosis indicators. The correlations between differential metabolites in patient endometrium and serum and key ferroptosis indicators （GPX4， Fe²⁺， MDA， GSH） as well as ferroptosis-related mRNAs （GPX4， SLC7A11， FTH1） were analyzed， and correlation heatmaps were generated accordingly. ResultsCompared with normal eutopic endometrium， ectopic lesions in EMs patients showed glandular disorganization and stromal fibrosis. In ectopic endometrium， the contents of MDA， ROS， and Fe²⁺ decreased， while GPX4 level increased， and the mRNA expression of SLC7A11 and GPX4 was upregulated （P<0.05， P<0.01）. In serum， the levels of GPX4 and Fe²⁺ were elevated， whereas the GSH level declined， suggesting abnormalities in ferroptosis-related pathways in ectopic lesions （P<0.05， P<0.01）. After intervention with Luoshi Neiyi prescription-containing serum， the intracellular ROS level in ectopic endometrial stromal cells was elevated， the mRNA expression of SLC7A11 and GPX4 was downregulated， and TFR mRNA expression was upregulated （P<0.05， P<0.01）. Metabolomics analysis revealed 1104 and 198 differential metabolites in EMs patients and EMs rats， respectively， compared with their corresponding control groups， and both low-dose and high-dose Luoshi Neiyi prescription were found to regulate this metabolic disturbance， with the core regulatory pathways mainly involving arginine and proline metabolism. Correlation analysis showed that the glycerophospholipids including PI（16∶0/17∶0） and PI［18∶2（9Z，12Z）］ were negatively correlated with GPX4 and positively correlated with MDA， while 17α-hydroxyprogesterone was positively correlated with GPX4， SLC7A11， and FTH1 q<0.05）. ConclusionLuoshi Neiyi prescription may systematically ameliorate disease-associated metabolic dysregulation via modulation of the serum arginine and proline metabolism pathway， and may regulate ferroptosis in ectopic lesions through a mechanism potentially linked to the serum glycerophospholipid and steroid metabolism pathways. Collectively， these findings provide experimental evidence for the clinical application of Luoshi Neiyi prescription.

ObjectiveThis study aimed to investigate the mechanism by which Luoshi Neiyi prescription treats endometriosis （EMs） through regulating ferroptosis， and to screen key metabolites and analyze their association with ferroptosis. MethodsClinical samples of normal endometrium from patients without EMs and eutopic and ectopic endometrium from EMs patients （10 cases each） were collected and divided into control group， eutopic group， and EMs group. Hematoxylin-eosin （HE） staining was performed to observe ectopic lesions of EMs. Immunohistochemistry was used to detect the expression of solute carrier family 7 member 11 （SLC7A11） and glutathione peroxidase 4 （GPX4）. Enzyme-linked immunosorbent assay （ELISA） was adopted to determine the levels of malondialdehyde （MDA）， ferrous ion （Fe²⁺）， GPX4 and glutathione （GSH） in endometrial tissues， as well as serum levels of Fe²⁺， GPX4 and GSH. Real-time quantitative polymerase chain reaction （Real-time PCR） was used to detect the mRNA expression of SLC7A11， GPX4， transferrin receptor （TFR） and ferritin heavy chain 1 （FTH1）. In the in vitro experiment， primary stromal cells were isolated from ectopic lesions of EMs patients. Cell counting kit-8 （CCK-8） was used to determine the optimal concentration of drug-containing serum for intervention. The level of reactive oxygen species （ROS） was measured， and Real-time PCR was applied to detect ferroptosis-related indicators. In the animal experiments， an EM rat model was established， and the rats were randomly assigned to the sham operation group， EMs group， low-dose Luoshi Neiyi Formula group （7.87 g·kg^-1）， high-dose Luoshi Neiyi prescription group （15.74 g·kg^-1）， and danazol group （42 mg·kg^-1）. Untargeted metabolomics detection and pathway enrichment analysis were conducted on serum samples from patients and rats. Spearman correlation analysis was performed to assess the relationship between differential metabolites and ferroptosis indicators. The correlations between differential metabolites in patient endometrium and serum and key ferroptosis indicators （GPX4， Fe²⁺， MDA， GSH） as well as ferroptosis-related mRNAs （GPX4， SLC7A11， FTH1） were analyzed， and correlation heatmaps were generated accordingly. ResultsCompared with normal eutopic endometrium， ectopic lesions in EMs patients showed glandular disorganization and stromal fibrosis. In ectopic endometrium， the contents of MDA， ROS， and Fe²⁺ decreased， while GPX4 level increased， and the mRNA expression of SLC7A11 and GPX4 was upregulated （P<0.05， P<0.01）. In serum， the levels of GPX4 and Fe²⁺ were elevated， whereas the GSH level declined， suggesting abnormalities in ferroptosis-related pathways in ectopic lesions （P<0.05， P<0.01）. After intervention with Luoshi Neiyi prescription-containing serum， the intracellular ROS level in ectopic endometrial stromal cells was elevated， the mRNA expression of SLC7A11 and GPX4 was downregulated， and TFR mRNA expression was upregulated （P<0.05， P<0.01）. Metabolomics analysis revealed 1104 and 198 differential metabolites in EMs patients and EMs rats， respectively， compared with their corresponding control groups， and both low-dose and high-dose Luoshi Neiyi prescription were found to regulate this metabolic disturbance， with the core regulatory pathways mainly involving arginine and proline metabolism. Correlation analysis showed that the glycerophospholipids including PI（16∶0/17∶0） and PI［18∶2（9Z，12Z）］ were negatively correlated with GPX4 and positively correlated with MDA， while 17α-hydroxyprogesterone was positively correlated with GPX4， SLC7A11， and FTH1 q<0.05）. ConclusionLuoshi Neiyi prescription may systematically ameliorate disease-associated metabolic dysregulation via modulation of the serum arginine and proline metabolism pathway， and may regulate ferroptosis in ectopic lesions through a mechanism potentially linked to the serum glycerophospholipid and steroid metabolism pathways. Collectively， these findings provide experimental evidence for the clinical application of Luoshi Neiyi prescription.

Objective:To evaluate the effects and underlying mechanisms of preoperative intestinal microbiota modulation on the recovery of prolonged postoperative ileus(PPOI)in gastric cancer patients with sarcopenia Methods:Skeletal muscle mass(SMM)was assessed using bioelectrical impedance analysis(BIA),and the skeletal muscle index(SMI)was calculated.A total of 156 gastric cancer patients with sarcopenia who underwent surgery at the Department of Gastrointestinal Surgery,Liyang People's Hospital,from January 2022 to December 2024 were randomly assigned to either the control group or the experimental group.The control group received conventional prehabilitation interventions,including nutritional support,respiratory function training,and physical exercise.The experimental group received probiotic-based intestinal microbiota modulation in addition to conventional prehabilitation interventions.Postoperative recovery indicators,including time to first flatus,incidence of postoperative complications,length of hospital stay,and hospitalization costs,were compared between the two groups.Results:Among the 156 sarcopenic gastric cancer patients,121 were male,and 35 were female.Statistically significant differences were observed between the two groups in terms of time to first flatus,incidence of postoperative complications,and length of hospital stay(P<0.05).Postoperative complications occurred in 38 patients(24.3%),with 10 cases(6.4%)in the experimental group and 28 cases(17.9%)in the control group.The time to first flatus in the experimental group was significantly shorter than in the control group(48.0 hours vs 72.0 hours,P<0.001).Conclusion:Preoperative intestinal microbiota modulation significantly reduces the incidence of PPOI and postoperative complications in gastric cancer patients with low SMI,thereby promoting postoperative gastrointestinal function recovery.

Objective To explore the application value of combining the ultrasound breast imaging reporting and data system(BI-RADS)classification with serum fibroblast growth factor receptor 1(FGFR1)and growth differentiation factor 3(GDF3)in the differential diagnosis of benign and malignant breast masses.Methods A total of 159 patients with breast masses were selected and divided into the benign mass group(n=83)and the malignant mass group(n=76)based on postoperative pathological diagnosis.All patients underwent ultrasound examination,and enzyme-linked immunosorbent assay(ELISA)was applied to detect serum levels of FGFR1 and GDF3.Receiver operating characteristic(ROC)curve was applied to analyze the diagnostic value of ultrasound BI-RADS classification and serum FGFR1 and GDF3 levels for benign and malignant breast masses.Kappa test was applied to analyze the consistency between various diagnostic methods and pathological diagnosis.Results The serum levels of FGFR1 and GDF3,the proportions of irregular morphology,unclear boundaries,spiculation,microcalcifications,blood flow grade Ⅱ-Ⅲ and posterior echo attenuation,RI and PI were higher in the malignant tumor group than those in the benign tumor group(P＜0.05).The area under the curve(AUC)of FGFR1,GDF3 and ultrasound BI-RADS classification in the differential diagnosis of benign and malignant breast masses separately and in combination was 0.802(95%CI:0.732-0.871),0.817(95%CI:0.751-0.884),0.848(95%CI:0.784-0.912)and 0.956(95%CI:0.918-0.993),respectively.The combined diagnosis was more effective than that of the individual diagnosis of each indicator.The consistency between the individual and combined diagnosis of benign and malignant breast masses and pathological diagnosis showed that the Kappa values were 0.517,0.514,0.688 and 0.912,respectively,with the highest consistency observed in the combined diagnosis(P＜0.05).Conclusion Ultrasound BI-RADS classification combined with serum FGFR1 and GDF3 has high application value in the differential diagnosis of benign and malignant breast masses.

Objective To evaluate the efficacy and safety of enteric-coated metformin hydrochloride capsules(Junlida?)in patients with T2DM and poor glycemic control under lifestyle interventions.Methods In this study,419 patients with T2DM were recruited from 15 research centers from July 2020 to March 2022,and randomly divided into observation(Obs)group(n=209)and control group(Con,n=210)using a multicenter,randomized,double-blind,non-inferiority trial design.Patients in the Obs group were treated with enteric-coated Metformin hydrochloride capsules(Junlida?),and patients in the Con group were treated with Metformin hydrochloride tablets(Glucophage?).The optimal effective dose of 2 g/d was achieved within 4 weeks,and the reasonable dose was maintained until the end of treatment.The treatment period was 24 weeks.HbA1c and its compliance rate,FPG,and body weight were compared between the two groups in full analysis set(FAS)and protocol set(PPS).Safety and adverse events(AE)were evaluated in safety set(SS).Results A total of 414 participants were randomized(207 cases in Obs group and 207 cases in Con group).414 cases in FAS population(207 cases in Obs group and 207 cases in Con group),and 328 cases in PPS population(164 cases in Obs group and 164 cases in Con group),and 414 cases in SS population(207 cases in Obs group and 207 cases in Con group).After treatment,HbA1c,FPG and body weight were lower in both groups(P<0.05)in FAS and PPS.HbA1c compliance rate was not significantly different between the two groups in FAS and PPS(P>0.05).The results of non-inferiority test showed that the lower limit was>-0.4%in both FAS(-0.154,95%CI-0.384～0.069)and PPS(-0.139,95%CI-0.390～0.112),and the Obs group reached non-inferiority end point.The achievement rate,compliance rate,safety index and incidence of AE were not significantly different between the two groups(P>0.05).Conclusions Junlida? demonstrated non-inferiority to Glucophage? in glycemic control and can be safely and effectively used in patients with diabetes.

[Objective]To explore the value of the Model for End-Stage Liver Disease(MELD)3.0 in predicting survival outcomes for patients with alcoholic cirrhosis and to establish an effective mortality prediction model.[Methods]Clinical data of 788 hospitalized patients who were first diagnosed with alcoholic cirrhosis at the Third Affiliated Hospital of Sun Yat-sen University between January 1,2011 and December 31,2019 were analyzed.Patients were followed up until December 31,2023 and divided into survival and mortality groups based on the survival outcomes at 30 days,90 days,1 year,and 3 years after admission.The prognostic values of the MELD 3.0,MELD,MELD-Sodium(MELD-Na)for survival in alcoholic cirrhosis patients were assessed and compared by using the receiver operating characteristic(ROC)curve and the area under the curve(AUC).Additional risk factors associated with mortality in alcoholic cirrhosis patients were identified,and a novel mortality prediction model based on MELD 3.0 was developed.[Results]The AUC of the MELD 3.0 score in predicting 30-day,90-day,1-year,and 3-year survival was 0.823,0.730,0.686,and 0.658,respectively,which were superior to those of the MELD-Na(0.802,0.708,0.666,and 0.645,respectively)and MELD scores(0.698,0.668,0.654,and 0.633,respectively)(all P<0.05).MELD 3.0 demonstrated better performance at 30 and 90 days(AVC=0.823,0.730;both P<0.05)than at 1 year and 3 years(AVC=0.686,0.658;both P<0.05).Binary logistic regression combined with LASSO regression indicated that the independent risk factors associated with the 1-year outcome included MELD 3.0,baseline ascites and hepatocellular carcinoma.A survival prediction model was then established with AUC of 0.748,sensitivity of 0.695,and specificity of 0.775.[Conclusions]MELD 3.0 has a superior predictive ability for 30-day,90-day,1-year,and 3-year survival in patients with alcoholic cirrhosis than MELD-Na and MELD.The prediction model incorporating MELD 3.0,ascites and hepatocellular carcinoma improves the prediction of 1-year survival outcomes for alcoholic cirrhosis patients.

Objective:To investigate the effectiveness of the 5A (Ask, Assess, Advise, Assist, Arrange follow-up) management model based on personalized health education records in community patients with type 2 diabetes mellitus.Methods:A convenience sampling method was used to select patients with type 2 diabetes mellitus who were enrolled with family doctors in Yuxin Community, Haidian District, Beijing, from January 2022 to May 2023. Using a random number table method, the patients were divided into an observation group ( n=68) and a control group ( n=68). The control group received routine community management, while the observation group received management based on the 5A model and personalized health education records. Differences in metabolic indicators, including glycated hemoglobin (HbA1c), fasting blood glucose, 2-hour postprandial blood glucose, body mass index (BMI), and waist circumference, as well as self-management behaviors were compared between the two groups at 3, 6, and 12 months of intervention. Results:During the entire intervention period, four cases were lost in the observation group and eight cases were lost in the control group. Finally, data from 124 patients were included in the analysis, including 64 cases in the observation group and 60 cases in the control group. Repeated measures analysis of variance showed interaction effects between time points and groups for HbA1c, BMI, waist circumference, and self-management behavior scores among patients with diabetes, with statistically significant differences ( P<0.05) . Conclusions:The 5A management model based on personalized health education records has a positive impact on improving metabolic indicators and self-management behaviors in community patients with type 2 diabetes mellitus.

Insulin is an important protein hormone that participates in multiple metabolic pathways.Biosynthetic insulin has been widely used in the treatment of type 1 and type 2 diabetes.Currently,the number of reported cases of insulin overdose both at home and abroad is gradually increasing,and insulin homicide is no longer a means of"committing murder without leaving a trace".At present,there are no systematic protocols for the identification of insulin overdose in the field of forensic medi-cine in China.This article introduces the causes,toxicological characteristics,forensic examination,labo-ratory testing methods and indicator reference of insulin overdose.Based on the identification practice and research results and referring to relevant studies on insulin overdose at home and abroad,this pa-per aims to provide recommendations and references for the formulation of forensic identification guide-lines for insulin overdose cases.