ObjectiveTo optimize the extraction method for polysaccharides from turnip（Brassica rapa）， and analyze and evaluate the primary structure of the isolated and purified turnip polysaccharide fraction（BP-1） and its hypoglycemic effects in diabetic zebrafish. MethodsTaking polysaccharide yield as the evaluation index， a semi-bionic extraction method was employed. Single-factor experiments and Box-Behnken response surface methodology were used to investigate three factors of solid-to-liquid ratio， extraction time and extraction temperature， in order to optimize the extraction process. BP-1 was isolated and purified using the Sevage method and DEAE-52 cellulose column chromatography. Structural characterization of the turnip polysaccharides was performed using ultraviolet-visible spectrophotometry（UV）， gas chromatography-mass spectrometry（GC-MS）， Congo red assay， and Fourier-transform infrared spectroscopy（FT-IR） to determine purity， monosaccharide composition， triple-helix structure， and functional groups. The microstructure of the polysaccharides was observed using scanning electron microscopy（SEM） and atomic force microscopy（AFM）. Zebrafish were divided into the blank group（adding E3 medium）， and BP-1-1， BP-1-10， BP-1-50， BP-1-200， BP-1-1 000 groups（adding BP-1 solutions at concentrations of 1， 10， 50， 200， 1 000 mg·L^-1， respectively）， and zebrafish embryos were subjected to a 96-hour exposure experiment. The maximum tolerated concentration of BP-1 in zebrafish was determined by evaluating its effects on phenotype， survival rate， malformation rate， and heart rate. Experimental animals were randomly divided into the blank group， model group， BP-1-10 group（10 mg·L^-1）， BP-1-50 group（50 mg·L^-1）， and BP-1-200 group（200 mg·L^-1）. The blank group was cultured in E3 medium， the model and treatment groups were induced to establish a diabetic model in 4 day-post-fertilization（dpf） zebrafish embryos using 10 g·L^-1 of glucose combined with 500 µmol·L^-1 of alloxan. The treatment groups received corresponding doses of BP-1 solution， while the blank and model groups received an equal volume of saline. Glucose and insulin（INS） levels were measured using enzyme-linked immunosorbent assay（ELISA） kits， the effects on the liver were observed by hematoxylin-eosin（HE） histopathological sections. The mRNA expression levels of glucagon（Glucagon）， insulin（Insa）， and phosphoenolpyruvate carboxykinase 1（PCK1） were detected with real-time fluorescence quantitative polymerase chain reaction（Real-time PCR）. ResultsThe optimized extraction conditions were determined as follows：solid-to-liquid ratio of 1∶40（g·mL^-1）， extraction time of 66 min， and extraction temperature of 79 ℃. Under these conditions， the yield of turnip polysaccharides was （10.34±0.96）%. UV analysis indicated that BP-1 contained no proteins or nucleic acids， GC-MS analysis revealed that BP-1 consisted of six monosaccharides（arabinose， rhamnose， ribose， mannose， galactose and glucose）. Congo red assay indicated that the molecular conformation did not exhibit a triple-helix structure， FT-IR analysis showed the presence of α-glycosidic bonds and uronic acids， SEM analysis revealed an irregular flaky structure with a flat and smooth surface， AFM analysis suggested that the aggregated structure might be formed by the entanglement of molecular chains and intramolecular hydrogen bonding. The maximum tolerated concentration of BP-1 in zebrafish over 96 h was determined to be 200 mg·L^-1. Pharmacodynamic results showed that， compared with the blank group， the model group exhibited significantly increased glucose levels and significantly decreased INS levels（P<0.01）. Compared with the model group， the BP-1-50 group significantly reduced glucose levels and increased INS levels（P<0.05）. Histopathological examination of liver tissue revealed that various doses of BP-1 had a certain reparative effect on damaged liver tissue. The liver tissue structure in the BP-1-200 group was nearly normal， with hepatocytes appearing plump. Real-time PCR results showed that， compared with the blank group， the model group exhibited significantly upregulated mRNA expressions of Glucagon and PCK1， and significantly downregulated mRNA expression of Insa（P<0.01）. Compared with the model group， the BP-1-50 and BP-1-200 groups showed significantly downregulated mRNA expressions of Glucagon and PCK1， and significantly upregulated mRNA expression of Insa（P<0.01）. ConclusionThe semi-bionic extraction method for turnip polysaccharides yields a high extraction rate， is simple to operate， has low costs， making it suitable for large-scale industrial production. BP-1 consists of six monosaccharides， contains α-glycosidic bonds and uronic acids， exhibits hypoglycemic activity， and provides a certain protective effect on the liver of alloxan-induced diabetic model zebrafish.

ObjectiveTo optimize the extraction method for polysaccharides from turnip（Brassica rapa）， and analyze and evaluate the primary structure of the isolated and purified turnip polysaccharide fraction（BP-1） and its hypoglycemic effects in diabetic zebrafish. MethodsTaking polysaccharide yield as the evaluation index， a semi-bionic extraction method was employed. Single-factor experiments and Box-Behnken response surface methodology were used to investigate three factors of solid-to-liquid ratio， extraction time and extraction temperature， in order to optimize the extraction process. BP-1 was isolated and purified using the Sevage method and DEAE-52 cellulose column chromatography. Structural characterization of the turnip polysaccharides was performed using ultraviolet-visible spectrophotometry（UV）， gas chromatography-mass spectrometry（GC-MS）， Congo red assay， and Fourier-transform infrared spectroscopy（FT-IR） to determine purity， monosaccharide composition， triple-helix structure， and functional groups. The microstructure of the polysaccharides was observed using scanning electron microscopy（SEM） and atomic force microscopy（AFM）. Zebrafish were divided into the blank group（adding E3 medium）， and BP-1-1， BP-1-10， BP-1-50， BP-1-200， BP-1-1 000 groups（adding BP-1 solutions at concentrations of 1， 10， 50， 200， 1 000 mg·L^-1， respectively）， and zebrafish embryos were subjected to a 96-hour exposure experiment. The maximum tolerated concentration of BP-1 in zebrafish was determined by evaluating its effects on phenotype， survival rate， malformation rate， and heart rate. Experimental animals were randomly divided into the blank group， model group， BP-1-10 group（10 mg·L^-1）， BP-1-50 group（50 mg·L^-1）， and BP-1-200 group（200 mg·L^-1）. The blank group was cultured in E3 medium， the model and treatment groups were induced to establish a diabetic model in 4 day-post-fertilization（dpf） zebrafish embryos using 10 g·L^-1 of glucose combined with 500 µmol·L^-1 of alloxan. The treatment groups received corresponding doses of BP-1 solution， while the blank and model groups received an equal volume of saline. Glucose and insulin（INS） levels were measured using enzyme-linked immunosorbent assay（ELISA） kits， the effects on the liver were observed by hematoxylin-eosin（HE） histopathological sections. The mRNA expression levels of glucagon（Glucagon）， insulin（Insa）， and phosphoenolpyruvate carboxykinase 1（PCK1） were detected with real-time fluorescence quantitative polymerase chain reaction（Real-time PCR）. ResultsThe optimized extraction conditions were determined as follows：solid-to-liquid ratio of 1∶40（g·mL^-1）， extraction time of 66 min， and extraction temperature of 79 ℃. Under these conditions， the yield of turnip polysaccharides was （10.34±0.96）%. UV analysis indicated that BP-1 contained no proteins or nucleic acids， GC-MS analysis revealed that BP-1 consisted of six monosaccharides（arabinose， rhamnose， ribose， mannose， galactose and glucose）. Congo red assay indicated that the molecular conformation did not exhibit a triple-helix structure， FT-IR analysis showed the presence of α-glycosidic bonds and uronic acids， SEM analysis revealed an irregular flaky structure with a flat and smooth surface， AFM analysis suggested that the aggregated structure might be formed by the entanglement of molecular chains and intramolecular hydrogen bonding. The maximum tolerated concentration of BP-1 in zebrafish over 96 h was determined to be 200 mg·L^-1. Pharmacodynamic results showed that， compared with the blank group， the model group exhibited significantly increased glucose levels and significantly decreased INS levels（P<0.01）. Compared with the model group， the BP-1-50 group significantly reduced glucose levels and increased INS levels（P<0.05）. Histopathological examination of liver tissue revealed that various doses of BP-1 had a certain reparative effect on damaged liver tissue. The liver tissue structure in the BP-1-200 group was nearly normal， with hepatocytes appearing plump. Real-time PCR results showed that， compared with the blank group， the model group exhibited significantly upregulated mRNA expressions of Glucagon and PCK1， and significantly downregulated mRNA expression of Insa（P<0.01）. Compared with the model group， the BP-1-50 and BP-1-200 groups showed significantly downregulated mRNA expressions of Glucagon and PCK1， and significantly upregulated mRNA expression of Insa（P<0.01）. ConclusionThe semi-bionic extraction method for turnip polysaccharides yields a high extraction rate， is simple to operate， has low costs， making it suitable for large-scale industrial production. BP-1 consists of six monosaccharides， contains α-glycosidic bonds and uronic acids， exhibits hypoglycemic activity， and provides a certain protective effect on the liver of alloxan-induced diabetic model zebrafish.

This paper introduces a real-world cohort research model for community-acquired pneumonia （CAP） based on the Jiangsu Traditional Chinese Medicine （TCM） Dominant Diseases Diagnosis and Treatment Data Platform. Firstly， data cleaning is performed by standardizing diagnosis， symptoms， treatment and imaging， intelligently extracting unstructured information， and cleaning and constructing a standardized database. Secondly， for cohort establishment， CAP patients across the province are screened in accordance with CAP diagnostic criteria to build a high-quality disease-specific cohort. Lastly， in terms of protocol design， the characteristics of TCM research and the CAP disease profile are considered to determine appropriate inclusion and exclusion criteria， estimate sample size， define interventions， outcomes and economic evaluations， providing a reference for real-world TCM research on CAP.

This paper introduces a real-world cohort research model for community-acquired pneumonia （CAP） based on the Jiangsu Traditional Chinese Medicine （TCM） Dominant Diseases Diagnosis and Treatment Data Platform. Firstly， data cleaning is performed by standardizing diagnosis， symptoms， treatment and imaging， intelligently extracting unstructured information， and cleaning and constructing a standardized database. Secondly， for cohort establishment， CAP patients across the province are screened in accordance with CAP diagnostic criteria to build a high-quality disease-specific cohort. Lastly， in terms of protocol design， the characteristics of TCM research and the CAP disease profile are considered to determine appropriate inclusion and exclusion criteria， estimate sample size， define interventions， outcomes and economic evaluations， providing a reference for real-world TCM research on CAP.

ObjectiveTo investigate the material basis and mechanism of action of Tuoli Xiaodu San in treating ulcerative colitis （UC） by integrating transcriptomics， network pharmacology， and experimental validation. MethodsNetwork pharmacology was initially employed to screen the active components and potential mechanisms of Tuoli Xiaodu San for treating UC. A UC mouse model was established by dextran sulfate sodium （DSS） induction. The mice were divided into the following groups： normal， model， high-dose （11.3 g·kg^-1） Tuoli Xiaodu San， low-dose （5.7 g·kg^-1） Tuoli Xiaodu San， and positive control （mesalazine， 0.4 g·kg^-1）. Intragastric administration commenced on day 1 of modeling and continued for 7 consecutive days. The disease activity index （DAI） was assessed daily. Hematoxylin-eosin （HE） staining was used to observe colonic pathological changes. Serum levels of tumor necrosis factor-alpha （TNF-α）， interleukin-1 beta （IL-1β） and interleukin-6 （IL-6） were measured by enzyme-linked immunosorbent assay （ELISA）. Transcriptome sequencing was performed on mouse colonic tissues， and the results were integrated with network pharmacology findings for in-depth analysis of Tuoli Xiaodu San's potential mechanisms in treating UC. Finally， the expression of key genes and proteins in the identified signaling pathways were detected using Western blot and Real-time polymerase chain reaction （Real-time PCR）. ResultsThe combined analysis of network pharmacology and transcriptomics results showed that the multi-pathway network with phosphatidylinositol 3-kinase/protein kinase B （PI3K/Akt） signaling pathway as its core was the key mechanism of Tuoli Xiaodu San in the treatment of UC. Tuoli Xiaodu San administration significantly ameliorated weight loss， diarrhea， and bloody stools in UC mice， reduced the DAI scores （P<0.05， P<0.01）， lowered the colonic histopathological scores （P<0.01）， alleviated colon shortening （P<0.01）， and downregulated serum levels of TNF-α， IL-1β， and IL-6 （P<0.05， P<0.01）. Molecular biology experiments confirmed that Tuoli Xiaodu San significantly inhibited the mRNA and protein expression， as well as the phosphorylation levels， of PI3K， Akt， and p65 in colonic tissues （P<0.05， P<0.01）. ConclusionTuoli Xiaodu San can regulate the multi-pathway network with PI3K/Akt as its core through multi-component synergy， thereby reducing colonic inflammatory damage and exerting a therapeutic effect on UC.

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

Objective:To explore the diagnostic value of a clinical-radiomics model based on the T 1 mapping and apparent diffusion coefficient (ADC)-based radiomics, and the clinical indicator for renal fibrosis (RF) caused by chronic kidney disease (CKD). Methods:This cross-sectional study prospectively and consecutively enrolled 122 patients with CKD at the Second Affiliated Hospital of Soochow University from September 2021 to December 2023 who were randomly allocated to a training set ( n=85) or a validation set ( n=37) in an approximate 7∶3 ratio using simple random sampling. Patients underwent T 1 mapping and diffusion-weighted imaging scans. Renal biopsy was performed within 3 days after the MRI scans. Patients were categorized into three groups based on the degree of RF: no RF ( n=25), mild RF ( n=55), and moderate to severe RF ( n=42). To differentiate the presence of RF (no RF vs. any RF) and the severity of RF (mild RF vs. moderate to severe RF), univariate and multivariate logistic regression were used to optimize the independent clinical predictor, which constituted the clinical model. Radiomics features were extracted from regions of interest delineated within the renal parenchyma of the right kidney on T 1 mapping and ADC maps. Features were selected using least absolute shrinkage and selection operator regression to build the radiomics model. A clinical-radiomics model was subsequently constructed by integrating the independent clinical predictors with the selected radiomics features. Model diagnostic performance was evaluated using the area under the receiver operating characteristic curve (AUC). Calibration curve was plotted to assess model calibration, and decision curve analysis was performed to evaluate clinical net benefit. Results:Univariate logistic regression analysis revealed that estimated glomerular filtration rate (eGFR), serum creatinine, and blood urea nitrogen exhibited statistically significant differences ( P0.05) in distinguishing both the presence and severity of RF. Multivariate analysis identified eGFR as an independent clinical predictor for both the presence of RF ( OR=0.939, 95% CI 0.898-0.982, P=0.006) and RF severity ( OR=0.956, 95% CI 0.917-0.997, P=0.037). From the MRI images, 7 radiomics features were selected to build the radiomics model for distinguishing the presence of RF, and 8 features were selected for the model assessing RF severity. These radiomics models were then combined with eGFR to construct the clinical-radiomics models. The clinical-radiomics models demonstrated the highest diagnostic performance, with an AUC of 0.935 (95% CI 0.859-0.977) for RF presence and 0.967 (95% CI 0.891-0.995) for RF severity in the training set, and 0.914 (95% CI 0.774-0.981) and 0.908 (95% CI 0.748-0.981) in the validation set. Calibration curves and decision curve analysis confirmed that the clinical-radiomics models exhibited excellent calibration and provided the highest clinical net benefit for assessing RF in CKD patients. Conclusion:The clinical-radiomics model integrating T 1 mapping and ADC-based radiomics and eGFR can effectively improve the diagnostic performance for RF in CKD patients.

Objective:To explore the diagnostic value of a clinical-radiomics model based on the T 1 mapping and apparent diffusion coefficient (ADC)-based radiomics, and the clinical indicator for renal fibrosis (RF) caused by chronic kidney disease (CKD). Methods:This cross-sectional study prospectively and consecutively enrolled 122 patients with CKD at the Second Affiliated Hospital of Soochow University from September 2021 to December 2023 who were randomly allocated to a training set ( n=85) or a validation set ( n=37) in an approximate 7∶3 ratio using simple random sampling. Patients underwent T 1 mapping and diffusion-weighted imaging scans. Renal biopsy was performed within 3 days after the MRI scans. Patients were categorized into three groups based on the degree of RF: no RF ( n=25), mild RF ( n=55), and moderate to severe RF ( n=42). To differentiate the presence of RF (no RF vs. any RF) and the severity of RF (mild RF vs. moderate to severe RF), univariate and multivariate logistic regression were used to optimize the independent clinical predictor, which constituted the clinical model. Radiomics features were extracted from regions of interest delineated within the renal parenchyma of the right kidney on T 1 mapping and ADC maps. Features were selected using least absolute shrinkage and selection operator regression to build the radiomics model. A clinical-radiomics model was subsequently constructed by integrating the independent clinical predictors with the selected radiomics features. Model diagnostic performance was evaluated using the area under the receiver operating characteristic curve (AUC). Calibration curve was plotted to assess model calibration, and decision curve analysis was performed to evaluate clinical net benefit. Results:Univariate logistic regression analysis revealed that estimated glomerular filtration rate (eGFR), serum creatinine, and blood urea nitrogen exhibited statistically significant differences ( P0.05) in distinguishing both the presence and severity of RF. Multivariate analysis identified eGFR as an independent clinical predictor for both the presence of RF ( OR=0.939, 95% CI 0.898-0.982, P=0.006) and RF severity ( OR=0.956, 95% CI 0.917-0.997, P=0.037). From the MRI images, 7 radiomics features were selected to build the radiomics model for distinguishing the presence of RF, and 8 features were selected for the model assessing RF severity. These radiomics models were then combined with eGFR to construct the clinical-radiomics models. The clinical-radiomics models demonstrated the highest diagnostic performance, with an AUC of 0.935 (95% CI 0.859-0.977) for RF presence and 0.967 (95% CI 0.891-0.995) for RF severity in the training set, and 0.914 (95% CI 0.774-0.981) and 0.908 (95% CI 0.748-0.981) in the validation set. Calibration curves and decision curve analysis confirmed that the clinical-radiomics models exhibited excellent calibration and provided the highest clinical net benefit for assessing RF in CKD patients. Conclusion:The clinical-radiomics model integrating T 1 mapping and ADC-based radiomics and eGFR can effectively improve the diagnostic performance for RF in CKD patients.

Objective:To explore the clinical characteristics and prognostic factors of primary bladder adenocarcinoma（ACB）.Methods:The clinical data of 33 patients with primary ACB who underwent surgical treatment in the Department of Urology of Peking University Third Hospital from July 2003 to January 2024 were retrospectively analyzed. There were 5 females and 28 males，with an average age of（61.3 ± 11.5）years. Twelve patients had comorbidities（6 hypertension，2 coronary heart disease，5 diabetes mellitus，and 3 cerebrovascular diseases）and 12 had a smoking history. The mean body mass index（BMI）was（24.8 ± 3.2）kg/m 2. The maximum tumor diameter measured by enhanced computed tomography（CT）was（29.7 ± 12.7）mm. The preoperative neutrophil-to-lymphocyte ratio（NLR）was 3.4 ± 3.2，and the systemic immune-inflammation index（SII）was（582 ± 496）× 10 9/L.Patients were divided into two groups according to the surgical approach：the radical cystectomy group（ n = 23）and the bladder-sparing group（ n = 10）. For the radical cystectomy group，there were 19 males and 4 females，with a mean age of（59.9 ± 12.6）years. Five patients had comorbidities（3 hypertension，1 coronary heart disease，1 diabetes mellitus，and 2 cerebrovascular diseases）. Eight patients had a smoking history，with a mean BMI of（25.2 ± 3.5）kg/m 2. The maximum tumor diameter was（33.6 ± 10.9）mm，the preoperative NLR was 3.5 ± 3.5，and the SII was（618 ± 558）× 10 9/L. For the bladder-sparing group，there were 9 males and 1 female，with a mean age of（64.5 ± 8.2）years. Seven patients had comorbidities（3 hypertension，1 coronary heart disease，4 diabetes mellitus，and 1 cerebrovascular diseases）. Four patients had a smoking history，with a mean BMI of（23.5 ± 2.3）kg/m 2. The maximum tumor diameter was（20.7 ± 12.5）mm，the preoperative NLR was 3.1 ± 2.2，and the SII was（501 ± 323）× 10 9/L. Statistically significant differences were observed between the two groups in terms of comorbidities（ P = 0.008）and maximum tumor diameter（ P = 0.006），while no significant differences were found in other data（ P > 0.05）. The Kaplan-Meier survival curve was drawn，and Cox regression was used to analyze the prognostic factors of progression-free survival（PFS）and overall survival（OS）of patients. Results:Among the 33 patients，low-grade adenocarcinoma and high-grade adenocarcinoma accounted for 60.6% and 39.4% respectively according to the postoperative pathology，and 3 patients had positive surgical margins. There were 22 cases of muscle-invasive bladder adenocarcinoma，5 cases of lymph node metastasis，and 1 case of distant metastasis. The patients in tumor stages Ⅰ—Ⅳ were 9 cases（27.3%），8 cases（24.2%），7 cases（21.2%），and 9 cases（27.3%）respectively. Nine patients received postoperative adjuvant therapy，including 6 with adjuvant chemotherapy，2 with adjuvant chemotherapy combined with radiotherapy，and 1 with adjuvant immunotherapy. In the radical cystectomy group（ n = 23），there were 13 cases of low-grade and 10 cases of high-grade pathological grading，2 cases with positive margins，19 cases of muscle-invasive bladder adenocarcinoma，5 cases of lymph node metastasis，1 case of distant metastasis，and 5 patients received adjuvant therapy（4 cases of adjuvant chemotherapy，and 1 case of adjuvant immunotherapy）. In the bladder-sparing group（ n = 10），there were 7 cases of low-grade，3 cases of high-grade pathological grading，1 case with positive margins，3 cases of muscle-invasive bladder adenocarcinoma，zero lymph node or distant metastasis，and 4 patients received adjuvant therapy（2 cases of adjuvant chemotherapy，and 2 cases of combined adjuvant chemotherapy and radiotherapy）. A statistically significant difference was found in the proportion of muscle-invasive bladder adenocarcinoma between the two groups（ P = 0.006），while no significant differences were observed in other data（ P > 0.05）.The median follow-up duration of the patients was 28.0 months，the median PFS was 86.0 months，and the median OS was 90.0 months. The 2-year PFS and OS were 65.4% and 73.1% respectively. The 5-year PFS and OS were 54.2% and 56.5% respectively. The Kaplan-Meier survival analysis showed that there were no significant differences in PFS（ P = 0.777）and OS（ P = 0.585）between the radical cystectomy group and the bladder-preserving group. Female（ P = 0.011），BMI < 25 kg/m2（ P = 0.038），and positive surgical margins（ P < 0.01）were associated with poorer PFS. Aged ≥ 70 years（ P = 0.003），lymph node metastasis（ P = 0.041），and positive surgical margins（ P = 0.025）were associated with poorer OS，and patients in the adjuvant therapy group had better OS（ P = 0.005）. Multivariate Cox regression analysis indicated that positive surgical margins（HR 10.2， P = 0.012）were an independent impact factor for PFS，and positive surgical margins（HR 39.8， P = 0.001）and adjuvant therapy（HR 0.12， P = 0.021）were independent impact factors for OS. Conclusions:Positive surgical margins and adjuvant therapy are independent impact factors for the prognosis of patients with primary ACB.

Objective To explore the association between phase angle(PhA)and sarcopenia in middle-aged and elderly patients with type 2 diabetes mellitus(T2DM),and to evaluate its predictive value for the risk of sarcopenia in these patients.Methods We collected data from 356 middle-aged and elderly T2DM patients hospitalized in the Department of Endocrinology,Nanjing Drum Tower Hospital Group Suqian Hospital from March 2022 to June 2024,including 274 patients with diabetes only and 82 patients with T2DM combined with sarcopenia.A Logistic regression analysis was conducted to assess the relationship between phase angle and sarcopenia.The predictive value of PhA for sarcopenia in T2DM patients was analyzed using the receiver operating characteristic(ROC)curve,and the trend of PhA with the severity of sarcopenia in T2DM patients was tested by the Jonckheere-Terpstra method.Results Univariate analysis showed that the PhA value in the T2DM with sarcopenia group was significantly lower than that in the diabetes alone group,with a statistically significant difference(P<0.05).Additionally,height,body mass,body mass index(BMI),waist circumference,arm circumference,calf circumference,fasting insulin,postprandial 2 h insulin,fasting C-peptide,postprandial 2 h C-peptide,triglycerides,albumin,blood urea nitrogen,body composition indicators,6 m walking speed,muscle mass,and muscle strength-related indicators were significantly lower in the T2DM with sarcopenia group compared to the diabetes alone group.Age,duration of diabetes,glycated hemoglobin,25-hydroxyvitamin D[25-(OH)D]were significantly higher in the T2DM with sarcopenia group,with statistically significant differences(P<0.05).Multivariate Logistic regression analysis indicated that,after adjusting for other factors,PhA remained associated with sarcopenia in T2DM patients(P<0.05),with a decreased PhA increasing the risk of sarcopenia.ROC curve analysis showed that the area under the curve(AUC)for PhA predicting sarcopenia in T2DM patients was 0.769(95% CI:0.710-0.829),indicating the predictive efficacy of PhA.Trend analysis demonstrated a significant negative correlation between PhA and the severity of sarcopenia in T2DM patients(P<0.05).Conclusion The PhA is significantly associated with sarcopenia in patients with T2DM.It can serve as an early predictive and diagnostic tool for sarcopenia in individuals with T2DM.