ObjectiveTo observe the effect of heat-sensitive moxibustion on quality of life and immune function in non-small cell lung cancer （NSCLC） patients undergoing chemotherapy. MethodsSeventy NSCLC patients with qi deficiency and phlegm stasis syndrome were randomly divided into an intervention group and a control group， with 35 cases in each group. The control group received chemotherapy combined with routine symptomatic treatment， while the intervention group additionally received heat-sensitive moxibustion since the first day of chemotherapy. Acupoints included Dazhui （GV14）， bilateral Feishu （BL13）， Zhongwan （CV12）， Qihai （CV6）， and Guanyuan （CV4）. The site exhibiting the strongest heat-sensitization response was selected for moxibustion. Treatment was administered for 45 minutes per session， three times weekly for three consecutive weeks， totaling nine sessions. Before and after treatment， quality of life was assessed using the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire （EORTC QLQ-C30）， and traditional Chinese medicine （TCM） syndrome scores were evaluated. Peripheral blood levels of natural killer （NK） cells and T-lymphocyte subsets including CD3⁺， CD4⁺， and CD8⁺， and CD4⁺/CD8⁺ ratio were measured. Levels of programmed cell death protein-1 （PD-1）， including PD-1⁺CD4⁺ and PD-1⁺CD8⁺ cells， were also assessed. Liver and renal function were monitored before and after treatment， and adverse events were recorded. ResultsIn the intervention group， 1 participant withdrew and 1 was excluded， while in the control group， 2 participants withdrew. Ultimately， 33 participants in each group were included in the final analysis. The intervention group showed significant improvements in physical， role， emotional， cognitive， and social functioning， as well as global health status after treatment， while scores for fatigue， nausea and vomiting， dyspnea， appetite loss， diarrhea， and TCM syndrome scale were significantly decreased （P＜0.05）. Moreover， the intervention group demonstrated higher scores in physical functioning， role functioning， and global health status， as well as lower scores for fatigue， nausea and vomiting， dyspnea， appetite loss， diarrhea， and the TCM syndrome scale than the control group （P＜0.05）. After treatment， the levels of peripheral NK cells and PD-1⁺CD8⁺ T cells in the intervention group increased significantly； furthermore， the intervention group exhibited higher peripheral NK cell levels and lower PD-1⁺CD8⁺ T cell levels than the control group （P＜0.05）. No significant differences were found in liver or renal function between the two groups （P＞0.05）. In addition， no adverse events such as burns or moxibustion-induced syncope occurred during the study. ConclusionHeat-sensitive moxibustion as an adjunctive therapy may enhance immune function， alleviate clinical symptoms， and improve quality of life， while demonstrating a favorable safety profile in NSCLC patients with qi deficiency and phlegm stasis.

Objective:To investigate the value of habitat radiomic features based on gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid (Gd-EOB-DTPA)-enhanced MRI in establishing a predictive model for cytokeratin 19 (CK19) expression in hepatocellular carcinoma (HCC) and to evaluate its role in prognostic risk stratification.Methods:This multicenter case-control study retrospectively enrolled 489 patients with pathologically confirmed HCC who underwent Gd-EOB-DTPA-enhanced MRI between June 2016 and June 2024. Among them, 346 patients from the First Affiliated Hospital of Soochow University were divided into a training cohort ( n=245) and an internal test cohort ( n=101) via stratified sampling at a 7∶3 ratio. And 143 patients from Nantong Third Hospital Affiliated to Nantong University served as an external validation cohort. The training cohort included 53 CK19-positive and 192 CK19-negative patients. The internal test cohort included 21 CK19-positive and 80 CK19-negative patients. The external validation cohort included 30 CK19-positive and 113 CK19-negative patients. Univariate logistic regression analysis was performed to identify potential factors associated with CK19 expression, and a clinical-radiologic model was constructed. The k-means clustering algorithm was applied to segment target HCC lesions into 3 subregions. Radiomic features were extracted and selected from these habitat subregions. Habitat radiomics models were constructed for the arterial phase (AP), portal venous phase, hepatobiliary phase (HBP), and combined phases (CP). Multivariate logistic regression analysis identified independent clinical and radiologic predictors of CK19 expression, and the optimal habitat model score was integrated to build a clinical-radiologic-habitat combined model. The area under the receiver operating characteristic curve (AUC) was used to evaluate model predictive performance. Recurrence-free survival (RFS) was analyzed using the Kaplan-Meier method and the differences in survival curves were compared with the log-rank test. Results:Univariate logistic regression analysis revealed that alpha-fetoprotein (AFP) ( OR=2.629, 95% CI 1.412-4.896, P=0.002), AP enhancement ( OR=3.636, 95% CI 1.642-8.052, P=0.001), AP peritumoral enhancement ( OR=2.219, 95% CI 1.084-4.542, P=0.029), and HBP peritumoral hypointensity ( OR=2.010, 95% CI 1.004-4.021, P=0.049) were potential factors associated with CK19 expression, which were incorporated into the clinical-radiologic model. In the internal and external validation cohorts, the AUC of the clinical-radiologic model was 0.690 (95% CI 0.590-0.778) and 0.650 (95% CI 0.565-0.727), respectively. The habitat radiomics model based on CP images demonstrated the highest performance. It achieved AUC of 0.729 (95% CI 0.622-0.836) and 0.725 (95% CI 0.607-0.842) in the internal and external validation cohorts, respectively. Multivariate analysis identified AFP ( OR=2.494, 95% CI 1.163-5.348, P=0.019), AP enhancement ( OR=5.230, 95% CI 1.868-14.643, P=0.002) and habitat radiomics model score ( OR=4.105, 95% CI 2.643-6.368, P<0.001) as independent predictors of CK19 positivity. Based on these factors, a combined clinical-radiologic-habitat combined model was established. The clinical-radiologic-habitat combined model achieved AUCs of 0.767 (95% CI 0.671-0.846) and 0.730 (95% CI 0.649-0.801) in the internal and external validation cohorts, respectively. Significant differences in RFS were observed between the CK19-positive group (25.1 month) and CK19-negative group (51.0 month) as predicted by the clinical-radiologic-habitat model ( χ2=4.17, P=0.041). Conclusion:The clinical-radiologic-habitat combined model based on Gd-EOB-DTPA-enhanced MRI habitat radiomics demonstrates good predictive performance for CK19 expression in HCC and offers valuable prognostic stratification for clinical practice.

Objective:To explore the value of the deep learning model based on gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid (Gd-EOB-DTPA) enhanced MRI in preoperatively predicting vessels completely encapsulating tumor clusters (VETC) in hepatocellular carcinoma (HCC).Methods:This study adopted a case-control design to retrospectively analyze 420 patients with HCC confirmed by postoperative pathology who underwent Gd-EOB-DTPA enhanced MRI between June 2016 and March 2023. A total of 420 patients were divided into a training set ( n=305) from the First Affiliated Hospital of Soochow University and an external validation set ( n=115) from Affiliated Nantong Hospital 3 of Nantong University. Based on postoperative pathological findings, patients were stratified into VETC-positive and VETC-negative groups. The training set comprised 161 VETC-positive cases and 144 VETC-negative cases, while the external validation set included 55 VETC-positive cases and 60 VETC-negative cases. Tumor regions of interest in arterial, portal venous, and hepatobiliary phases were manually delineated using ITK-SNAP software. Pre-trained Vgg19, Densenet121, and Vision Transformer (ViT) models were employed for transfer learning, extracting deep learning features from each image. Feature data were processed using FAE software, and 12 logistic regression models (arterial phase, portal venous phase, hepatobiliary phase, and combined three-phase models) were constructed to select the optimal deep learning model. Independent predictors in clinical characteristics were identified through univariate and multivariate logistic analyses to establish a clinical model for predicting VETC pattern. Subsequently, a clinical-deep learning fusion model was developed by integrating these clinical predictors with the optimal deep learning features. Model performance in predicting VETC-positive HCC was evaluated using receiver operating characteristic curves, calibration curves, and decision curve analysis (DCA). Results:In the external validation set, the area under the curve (AUC) of the Vgg19 model in the arterial phase, portal venous phase, hepatobiliary phase, and combined three-phase, respectively were 0.799,0.756,0.789,0.821, which were higher than those of Densenet121 (AUC: 0.544,0.581,0.544,0.583) and ViT (AUC: 0.740,0.752,0.785,0.767) model. The three-phase combined Vgg19 model achieved the highest AUC of 0.821 (95% CI 0.746-0.897). Multivariate logistic regression identified alpha-fetoprotein level ( OR=1.826,95% CI 1.069-3.120, P=0.028) and tumor diameter ( OR=1.329,95% CI 1.206-1.466, P<0.001) as independent predictors of VETC-positive HCC, forming the clinical model with an AUC of 0.789 (95% CI 0.703-0.859). The clinical-deep learning fusion model further achieved the AUC of 0.825 (95% CI 0.749-0.900). Calibration curves confirmed high concordance between predicted and actual probabilities for the three-phase Vgg19 model, while DCA revealed greater net clinical benefit for the combined Vgg19 and fusion models compared with the clinical model alone. Conclusions:The deep learning model based on Gd-EOB-DTPA enhanced MRI can be used to predict VETC of HCC preoperatively, among which the three-phase combined Vgg19 model and the clinical-deep learning model provide high predictive value.

Objective:To analyze the current status of red blood cell transfusion in very preterm infants (VPI) (gestational age at birth <32 weeks) from Chinese Neonatal Network (CHNN) in 2022.Methods:This cross-sectional study was based on the CHNN VPI cohort. It included 6 985 VPI admitted to CHNN 89 participating centers within 24 hours after birth in 2022. VPI with major congenital anomalies or those transferred to non-CHNN centers for treatment or discharged against medical advice were excluded. VPI were categorized based on whether they received red blood cell transfusions, their gestational age at birth, the type of respiratory support received during transfusion, and whether the pre-transfusion hemoglobin levels exceeded the thresholds. General characteristics, red blood cell transfusion rates, number of transfusions, timing of the first transfusion, and pre-transfusion hemoglobin levels were compared among different groups. The incidence of adverse outcomes between the group of VPI who received transfusions above the threshold and those who received transfusions below the threshold were compared. Comparison among different groups was conducted using χ2 tests, Kruskal-Wallis H tests, Mann-Whitney U test, and so on. Trends by gestational age at birth were evaluated by Cochran-Armitage tests and Jonckheere-Terpstra tests for trend. Results:Among the 6 985 VPI, 3 865 cases(55.3%) were male, with a gestational age at birth of 30.0 (28.6, 31.0) weeks and a birth weight of (1 302±321) g. Overall, 3 617 cases (51.8%) received red blood cell transfusion, while 3 368 cases (48.2%) did not. The red blood cell transfusion rate was 51.8% (3 617/6 985), with rates of 77.7% (893/1 150) for those born before 28 weeks gestational age and 46.7% (2 724/5 835) for those born between 28 and 31 weeks gestational age. A total of 9 616 times red blood cell transfusions were administered to 3 617 VPI, with 632 times missing pre-transfusion hemoglobin data, and 8 984 times included in the analysis. Of the red blood cell transfusions, 25.6% (2 459/9 616) were administered when invasive respiratory support was required, 51.3% (4 934/9 616) were receiving non-invasive respiratory support, while 23.1% (2 223/9, 616) were given when no respiratory support was needed. Compared to the non-transfusion group, the red blood cell transfusion group had a higher rate of pregnancy-induced hypertension in mothers, lower rates of born via cesarean section and mother′s antenatal steroid administration, smaller gestational age, lower birth weight, a higher proportion of small-for-gestational-age, multiple births, and proportions of Apgar score at the 5 th minute after birth ≤3 (all P<0.05). They were also less likely to be female, born in hospital or undergo delayed cord clamping (all P<0.01). Additionally, higher transport risk index of physiologic stability score at admission were observed in the red blood cell transfusion group ( P<0.001). The number of red blood cell transfusion was 2 (1, 3) times, with the first transfusion occurring at an age of 18 (8, 29) days, and a pre-transfusion hemoglobin level of 97 (86, 109) g/L. For VPI ≤7 days of age, the pre-transfusion hemoglobin levels for invasive respiratory support, non-invasive respiratory support, or no respiratory support, respectively, with no statistically significant differences between groups ( H=5.59, P=0.061). For VPI aged 8 to 21 days and≥22 days, the levels with statistically differences between groups (both P<0.01). Red blood cell transfusions above recommended thresholds were observed in all respiratory support categories at different stages of life, with the highest prevalence in infants aged 8 to 21 days and≥22 days who did not require respiratory support, at 90.1% (264/273) and 91.1%(1 578/1 732), respectively. The rate of necrotizing enterocolitis was higher in the above-threshold group ( χ2=10.59, P=0.001), and the duration of hospital stay was longer in the above-threshold group ( Z=4.67, P<0.001) compared to the below-threshold group. Conclusions:In 2022, the red blood cell transfusion rate was relatively high among VPI from CHNN. Pre-transfusion hemoglobin levels frequently exceeded recommended transfusion thresholds.

Metastasis serves as an indicator of malignancy and is a biological characteristic of carcinomas. Epithelial-mesenchymal transition (EMT) plays a key role in the promotion of tumor invasion and metastasis and in the enhancement of tumor cell aggressiveness. Prostaglandin E synthase 3 (p23) is a cochaperone for heat shock protein 90 (HSP90). Our previous study showed that p23 is an HSP90-independent transcription factor in cancer-associated inflammation. The effect and mechanism of action of p23 on lung cancer metastasis are tested in this study. By utilizing cell models in vitro and mouse tail vein metastasis models in vivo, the results provide solid evidence that p23 is critical for promoting lung cancer metastases by regulating downstream CXCL1 expression. Rather than acting independently, p23 forms a complex with RNA-binding motif protein 14 (RBM14) to facilitate EMT progression in lung cancer. Therefore, our study provides evidence for the potential role of the RBM14-p23-CXCL1-EMT axis in the metastasis of lung cancer.

Objective:To investigate the value of habitat radiomic features based on gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid (Gd-EOB-DTPA)-enhanced MRI in establishing a predictive model for cytokeratin 19 (CK19) expression in hepatocellular carcinoma (HCC) and to evaluate its role in prognostic risk stratification.Methods:This multicenter case-control study retrospectively enrolled 489 patients with pathologically confirmed HCC who underwent Gd-EOB-DTPA-enhanced MRI between June 2016 and June 2024. Among them, 346 patients from the First Affiliated Hospital of Soochow University were divided into a training cohort ( n=245) and an internal test cohort ( n=101) via stratified sampling at a 7∶3 ratio. And 143 patients from Nantong Third Hospital Affiliated to Nantong University served as an external validation cohort. The training cohort included 53 CK19-positive and 192 CK19-negative patients. The internal test cohort included 21 CK19-positive and 80 CK19-negative patients. The external validation cohort included 30 CK19-positive and 113 CK19-negative patients. Univariate logistic regression analysis was performed to identify potential factors associated with CK19 expression, and a clinical-radiologic model was constructed. The k-means clustering algorithm was applied to segment target HCC lesions into 3 subregions. Radiomic features were extracted and selected from these habitat subregions. Habitat radiomics models were constructed for the arterial phase (AP), portal venous phase, hepatobiliary phase (HBP), and combined phases (CP). Multivariate logistic regression analysis identified independent clinical and radiologic predictors of CK19 expression, and the optimal habitat model score was integrated to build a clinical-radiologic-habitat combined model. The area under the receiver operating characteristic curve (AUC) was used to evaluate model predictive performance. Recurrence-free survival (RFS) was analyzed using the Kaplan-Meier method and the differences in survival curves were compared with the log-rank test. Results:Univariate logistic regression analysis revealed that alpha-fetoprotein (AFP) ( OR=2.629, 95% CI 1.412-4.896, P=0.002), AP enhancement ( OR=3.636, 95% CI 1.642-8.052, P=0.001), AP peritumoral enhancement ( OR=2.219, 95% CI 1.084-4.542, P=0.029), and HBP peritumoral hypointensity ( OR=2.010, 95% CI 1.004-4.021, P=0.049) were potential factors associated with CK19 expression, which were incorporated into the clinical-radiologic model. In the internal and external validation cohorts, the AUC of the clinical-radiologic model was 0.690 (95% CI 0.590-0.778) and 0.650 (95% CI 0.565-0.727), respectively. The habitat radiomics model based on CP images demonstrated the highest performance. It achieved AUC of 0.729 (95% CI 0.622-0.836) and 0.725 (95% CI 0.607-0.842) in the internal and external validation cohorts, respectively. Multivariate analysis identified AFP ( OR=2.494, 95% CI 1.163-5.348, P=0.019), AP enhancement ( OR=5.230, 95% CI 1.868-14.643, P=0.002) and habitat radiomics model score ( OR=4.105, 95% CI 2.643-6.368, P<0.001) as independent predictors of CK19 positivity. Based on these factors, a combined clinical-radiologic-habitat combined model was established. The clinical-radiologic-habitat combined model achieved AUCs of 0.767 (95% CI 0.671-0.846) and 0.730 (95% CI 0.649-0.801) in the internal and external validation cohorts, respectively. Significant differences in RFS were observed between the CK19-positive group (25.1 month) and CK19-negative group (51.0 month) as predicted by the clinical-radiologic-habitat model ( χ2=4.17, P=0.041). Conclusion:The clinical-radiologic-habitat combined model based on Gd-EOB-DTPA-enhanced MRI habitat radiomics demonstrates good predictive performance for CK19 expression in HCC and offers valuable prognostic stratification for clinical practice.

Objective:To explore the value of the deep learning model based on gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid (Gd-EOB-DTPA) enhanced MRI in preoperatively predicting vessels completely encapsulating tumor clusters (VETC) in hepatocellular carcinoma (HCC).Methods:This study adopted a case-control design to retrospectively analyze 420 patients with HCC confirmed by postoperative pathology who underwent Gd-EOB-DTPA enhanced MRI between June 2016 and March 2023. A total of 420 patients were divided into a training set ( n=305) from the First Affiliated Hospital of Soochow University and an external validation set ( n=115) from Affiliated Nantong Hospital 3 of Nantong University. Based on postoperative pathological findings, patients were stratified into VETC-positive and VETC-negative groups. The training set comprised 161 VETC-positive cases and 144 VETC-negative cases, while the external validation set included 55 VETC-positive cases and 60 VETC-negative cases. Tumor regions of interest in arterial, portal venous, and hepatobiliary phases were manually delineated using ITK-SNAP software. Pre-trained Vgg19, Densenet121, and Vision Transformer (ViT) models were employed for transfer learning, extracting deep learning features from each image. Feature data were processed using FAE software, and 12 logistic regression models (arterial phase, portal venous phase, hepatobiliary phase, and combined three-phase models) were constructed to select the optimal deep learning model. Independent predictors in clinical characteristics were identified through univariate and multivariate logistic analyses to establish a clinical model for predicting VETC pattern. Subsequently, a clinical-deep learning fusion model was developed by integrating these clinical predictors with the optimal deep learning features. Model performance in predicting VETC-positive HCC was evaluated using receiver operating characteristic curves, calibration curves, and decision curve analysis (DCA). Results:In the external validation set, the area under the curve (AUC) of the Vgg19 model in the arterial phase, portal venous phase, hepatobiliary phase, and combined three-phase, respectively were 0.799,0.756,0.789,0.821, which were higher than those of Densenet121 (AUC: 0.544,0.581,0.544,0.583) and ViT (AUC: 0.740,0.752,0.785,0.767) model. The three-phase combined Vgg19 model achieved the highest AUC of 0.821 (95% CI 0.746-0.897). Multivariate logistic regression identified alpha-fetoprotein level ( OR=1.826,95% CI 1.069-3.120, P=0.028) and tumor diameter ( OR=1.329,95% CI 1.206-1.466, P<0.001) as independent predictors of VETC-positive HCC, forming the clinical model with an AUC of 0.789 (95% CI 0.703-0.859). The clinical-deep learning fusion model further achieved the AUC of 0.825 (95% CI 0.749-0.900). Calibration curves confirmed high concordance between predicted and actual probabilities for the three-phase Vgg19 model, while DCA revealed greater net clinical benefit for the combined Vgg19 and fusion models compared with the clinical model alone. Conclusions:The deep learning model based on Gd-EOB-DTPA enhanced MRI can be used to predict VETC of HCC preoperatively, among which the three-phase combined Vgg19 model and the clinical-deep learning model provide high predictive value.

ObjectiveTo investigate the association between estimated glucose disposal rate （eGDR） and the severity of coronary heart disease. MethodsWe conducted a hospital-based cross-sectional study that included 1258 patients （mean age： 62（53-68） years） who underwent coronary angiography for suspected coronary artery disease （53.9% were male）. Insulin resistance level （IR） was calculated according to eGDR formula： eGDR = 21.158 - （0.09 × WC） - （3.407 × hypertension） - （0.551 × HbA1c） ［hypertension （yes = 1 / no = 0）， HbA1c = HbA1c （%）］. Subjects were grouped according to the eGDR quantile. CAD severity was determined by the number of narrowed vessels： no-obstructive CAD group （all coronary stenosis were<50%， n=704）， Single-vessel CAD group （only one involved major coronary artery stenosis≥50%， n=205）， Multi-vessel CAD group （two or more involved major coronary arteries stenosis≥50%， n=349）； Multivariate logistic regression model was used to analyze the association between eGDR and CAD severity. The linear relationship between eGDR and CAD in the whole range of eGDR was analyzed using restricted cubic spline. Subgroup analyses were used to assess the association between eGDR and CAD severity in different diabetic states. Receiver operating characteristic （ROC） curve analysis were used to evaluate the value of eGDR in improving CAD recognition. ResultsA decrease in the eGDR index was significantly associated with an increased risk of CAD severity （OR： 2.79； 95%CI： 1.72~4.55； P<0.001）. In multivariate logistic regression models， individuals with the lowest quantile of eGDR （T1） were 2.79 times more likely to develop multi-vessel CAD than those with the highest quantile of eGDR （T3） （OR： 2.79； 95%CI： 1.72~4.55； P<0.001）. Multivariate restricted cubic spline analysis showed that eGDR was negatively associated with CAD and multi-vessel CAD （P-nonlinear>0.05）. In non-diabetic patients， compared with the reference group （T3）， the T1 group had a significantly increased risk of CAD （OR： 1.42； 95% CI： 1.00~2.01； P<0.05） and multi-vessel CAD （OR： 1.86； 95%CI： 1.21~2.86； P<0.05）. No statistical association was found between eGDR and CAD in diabetic patients. In ROC curve analysis， when eGDR was added to traditional model for CAD， significant improvements were observed in the model's recognition of CAD and multi-vessel CAD. ConclusionOur study shows eGDR levels are inversely associated with CAD and CAD severity. eGDR， as a non-insulin measure to assess IR， could be a valuable indicator of CAD severity for population.

ObjectiveTo compare the effects and differences of Yiqi Liangxue Shengji Formula （益气凉血生肌方） and atorvastatin on the repair of vascular injury in rats from the perspective of metabolomics. MethodsTwenty-four male SD rats were randomly divided into sham-surgery， model， traditional Chinese medicine （TCM）， and ator-vastatin groups， with 6 rats in each group. The rat model was established by balloon-induced abdominal aorta injury. Gavage was started on the day after surgery in all groups of rats. The sham and model groups were given with deio-nized water， TCM group received Yiqi Liangxue Shengji Formula 6 g/（kg·d）， and the atorvastatin group treated with atorvastatin suspension 2 mg/（kg·d） for 4 weeks. HE staining was used to observe the pathological morphology of the injured segment of the abdominal aorta； ELISA detection was used to test serum nitric oxide （NO） and C-reactive protein （CRP） levels； UPLC MS/MS technology was used for widely targeted metabolomics detection in serum， and multivariate statistical analysis was used to screen metabolic markers and pathways of two drugs； finally， compare serum levels of key metabolic markers of the above two medications in rats of each group. ResultsCompared with the sham-surgery group， the neointima significantly thickened， the level of NO decreased significantly and the level of CRP increased in serum of the model group （P＜0.01）； compared with the model group， the degree of arterial intimal hyperplasia in TCM group and atorvastatin group reduced， with an increase in NO levels and a decrease in CRP levels （P＜ 0.05 or P＜0.01）. The results of serum metabolomics showed that TCM group obtained 49 metabolic markers and 6 metabolic pathways， while atorvastatin group obtained 41 metabolic markers and 4 metabolic pathways. The two medications jointly regulated 38 metabolites. Glycerophospholipid metabolism and arginine-related metabolism were common metabolic pathways for both medications. Lysophosphatidylcholine （16∶1/0∶0） ［LPC （16∶1/ 0∶0）］， phosphatidylcholine （15∶0/15∶0） ［PC （15∶0/15∶0）］ were the key metabolites of glycerophospholipid metabolic pathway； ornithine， spermidine were the key metabolites of arginine-related metabolic pathway. The tricarboxylic acid cycle and glutathione metabolism were the unique metabolic pathways of Yiqi Liangxue Shengji Formula. Compared with the sham-surgery group， LPC （16∶1/0∶0）， ornithine， and spermidine levels elevated and PC （15∶0/15∶0） levels decreased in the model group （P＜0.05 or P＜0.01）. Compared with the model group， LPC （16∶1/0∶0）， ornithine， and spermidine levels decreased， and PC （15∶0/15∶0） levels increased in both TCM group and atorvastatin group （P＜0.05 or P＜0.01）. The degree of LPC reduction （16∶1/0∶0） was more significant in atorvastatin group compared with that in the TCM group （P＜0.01）. ConclusionsBoth sham-surgery and atorvastatin could regulate lipid metabolism and arginine-related metabolism， exert the characteristics of lipid-lowering， anti-inflammatory， improve arginine/NO bioavailability， and improve endothelial dysfunction. Atorvastatin showed more advantages in lipid-lowering and anti-inflammatory， while Yiqi Liangxue Shengji Formula has unique characteristics in regulating energy metabolism and improving oxidative stress.

Intersphincteric resection (ISR) is an advanced sphincter-preserving surgery for low rectal cancer. Accumulating evidences from clinical studies indicate that ISR can spare some pati-ents with low rectal cancer from the distress of anal amputation while ensuring oncological efficacy. However, due to the necessity of removing part or all of the internal sphincter during rectal resection and the extremely low anastomosis level, a subset of patients may experience low anterior resection syndrome (LARS) after surgery. LARS is characterized by symptoms such as anal incontinence, increased bowel frequency, urgency, incomplete evacuation, and obstructed defecation. Based on relevant literature and team practice, the authors provide an overview of the diagnosis and treat-ment progress of LARS following ISR.