Objective To explore the accuracy of artificial intelligence-based diagnosis of ovarian malignant tumors and the identification of benign and malignant tumors under transabdominal scanning and transvaginal scanning methods. Methods A dataset of transabdominal and transvaginal two-dimensional ultrasound images was used and the images were preprocessed to enhance quality. The region of interest was segmented and divided into a training set and a test set. A convolutional neural network (CNN) was trained on the images in the training set, and the accuracy of the model on the test set was calculated. Results Transvaginal scanning was 14% more accurate in diagnosing malignant ovarian tumors than transabdo-minal scanning on the test set. For identifying the benign and malignant ovarian tumors containing cystic components, a mixture of transvaginal and transabdominal scanning increased the accuracy by 9.7% over transabdominal scanning alone. Conclusion CNN can identify ovarian malignant tumors under both scanning methods, but the accuracy of transvaginal scanning is higher than that of transabdominal scanning, and the CNN model has a higher accuracy in identifying benign and malignant ovarian tumors under transvaginal scanning.

ObjectiveTo analyze the expression level of triggering receptor expressed on myeloid cells-1 （TREM-1） in serum and ascites of patients with cirrhotic ascites， and to investigate its correlation with clinical features and inflammatory markers and its role in the diagnosis of infection and prognostic evaluation. MethodsA total of 110 patients with cirrhotic ascites who were hospitalized in The Fifth Hospital of Shijiazhuang from January 2019 to December 2020 were enrolled， and according to the presence or absence of intra-abdominal infection， they were divided into infection group with 72 patients and non-infection group with 38 patients. The patients with infection were further divided into improvement group with 38 patients and non-improvement group with 34 patients. Clinical data and laboratory markers were collected from all patients. Serum and ascites samples were collected， and ELISA was used to measure the level of TREM-1. The independent-samples t test was used for comparison of normally distributed continuous data between two groups； the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between two groups， and the Kruskal-Wallis H test was used for comparison between multiple groups； the chi-square test was used for comparison of categorical data between two groups. A Spearman correlation analysis was used to investigate the correlation between indicators. A multivariate Logistic regression analysis was used to identify the influencing factors for the prognosis of patients with cirrhotic ascites and infection. The receiver operating characteristic （ROC） curve was used to evaluate the diagnostic and prognostic efficacy of each indicator， and the Delong test was used for comparison of the area under the ROC curve （AUC）. ResultsThe level of TREM-1 in ascites was significantly positively correlated with that in serum （r=0.50， P<0.001）. Compared with the improvement group， the non-improvement group had a significantly higher level of TREM-1 in ascites （Z=-2.391， P=0.017） and serum （Z=-2.544， P=0.011）， and compared with the non-infection group， the infection group had a significantly higher level of TREM-1 in ascites （Z=-3.420， P<0.001）， while there was no significant difference in the level of TREM-1 in serum between the two groups （P>0.05）. The level of TREM-1 in serum and ascites were significantly positively correlated with C-reactive protein （CRP）， procalcitonin （PCT）， white blood cell count， and neutrophil-lymphocyte ratio （r=0.288， 0.344， 0.530， 0.510， 0.534， 0.454， 0.330， and 0.404， all P<0.05）. The ROC curve analysis showed that when PCT， CRP， and serum or ascitic TREM-1 were used in combination for the diagnosis of cirrhotic ascites with infection， the AUCs were 0.715 and 0.740， respectively. The multivariate Logistic regression analysis showed that CRP （odds ratio ［OR］=1.019， 95% confidence interval ［CI］： 1.001‍ ‍—‍ ‍1.038， P=0.043） and serum TREM-1 （OR=1.002， 95%CI： 1.000‍ ‍—‍ ‍1.003， P=0.016） were independent risk factors for the prognosis of patients with cirrhotic ascites and infection， and the combination of these two indicators had an AUC of 0.728 in predicting poor prognosis. ConclusionThe level of TREM-1 is closely associated with the severity of infection and prognosis in patients with cirrhotic ascites， and combined measurement of TREM-1 and CRP/PCT can improve the diagnostic accuracy of infection and provide support for prognostic evaluation.

Integrin α _v β ₃ is overexpressed in various tumor cells and angiogenesis. To date, no drug has been proven to target it for therapy. A first-in-human study was designed to investigate the safety, pharmacokinetics, and dosimetry of ¹⁷⁷Lu-AB-3PRGD2, a novel integrin α _v β ₃-targeting radionuclide drug with an albumin-binding motif to optimize the pharmacokinetics. Ten patients (3 men, 7 women; aged 45 ± 16 years) with integrin α _v β ₃-avid tumors were recruited to accept ¹⁷⁷Lu-AB-3PRGD2 injection in a dosage of 1.57 ± 0.08 GBq (42.32 ± 2.11 mCi), followed by serial scans to obtain its dynamic distribution in the body. Safety tests were performed before and every 2 weeks after the treatment for 6-8 weeks. No adverse event over grade 3 was observed. ¹⁷⁷Lu-AB-3PRGD2 was excreted mainly through the urinary system, with intense radioactivity in the kidneys and bladder. Moderate distribution was found in the liver, spleen, and intestines. The estimated blood half-life was 2.85 ± 2.17 h. The whole-body effective dose was 0.251 ± 0.047 mSv/MBq. The absorbed doses were 0.157 ± 0.032 mGy/MBq in red bone marrow and 0.684 ± 0.132 mGy/MBq in kidneys. This first-in-human study of ¹⁷⁷Lu-AB-3PRGD2 treatment indicates its promising potential for targeted radionuclide therapy of integrin α _v β ₃-avid tumors. It merits further studies in more patients with escalating doses and multiple treatment courses.

The pharmaceutical industry faces challenges in quality digitization for complex multi-stage processes, especially in small-sample systems. Here, an intelligent quality prediction and diagnostic (IQPD) framework was developed and applied to Tong Ren Tang's Niuhuang Qingxin Pills, utilizing four years of data collected from four production units, covering the entire process from raw materials to finished products. In this framework, a novel path-enhanced double ensemble quality prediction model (PeDGAT) is proposed, which combines a graph attention network and path information to encode inter-unit long-range and sequential dependencies. Additionally, the double ensemble strategy enhances model stability in small samples. Compared to global traditional models, PeDGAT achieves state-of-the-art results, with an average improvement of 13.18% and 87.67% in prediction accuracy and stability on three indicators. Additionally, a more in-depth diagnostic model leveraging grey correlation analysis and expert knowledge reduces reliance on large samples, offering a panoramic view of attribute relationships across units and improving process transparency. Finally, the IQPD framework integrates into a Human-Cyber-Physical system, enabling faster decision-making and real-time quality adjustments for Tong Ren Tang's Niuhuang Qingxin Pills, a product with annual sales exceeding 100 million CNY. This facilitates the transition from experience-driven to data-driven manufacturing.

Objective Previous studies have shown that the triglyceride-glucose (TyG) index reflects insulin resistance and predicts the risk of ischemic stroke. Massive cerebral infarction, as a type of ischemic stroke with poor prognosis, is often more prone to complications and sequelae. However, no studies have yet explored the relationship between the TyG index and massive cerebral infarction. This study aims to investigate the role of the TyG index in assessing the infarct area in ischemic stroke. Methods This retrospective study included 212 adult patients with ischemic stroke diagnosed by cranial magnetic resonance imaging and admitted to our hospital from January 2020 to June 2024. The patients were divided into massive cerebral infarction group and non-massive cerebral infarction group according to the study purpose. Univariable and multivariable logistic regression analyses were performed on each group using SPSS 26 software. The receiver operating characteristic curves were analyzed for the prediction models. Results Variables with P＜0.2 in the univariable logistic regression analysis were included in the multivariable logistic regression analysis. The results showed that age (OR 1.043, 95% CI 1.004-1.084, P＜0.05), National Institutes of Health Stroke Scale score (OR 22.986, 95% CI 8.679-60.882, P＜0.001), and TyG index (OR 1.729, 95% CI 1.017-2.941, P＜0.05) were significant predictors. The area under the receiver operating characteristic curve of the predictive model was 0.868 (P＜0.001), indicating high predictive performance. Conclusion The TyG index is an independent risk factor for massive cerebral infarction. The combination of the TyG index with clinical laboratory indicators can effectively predict massive cerebral infarction.

Objective To investigate the diagnosis and treatment strategy of the portal vein complications in children undergoing split liver transplantation. Methods The clinical data of 88 pediatric recipients who underwent split liver transplantation were retrospectively analyzed. Intraoperative anastomosis at the bifurcating site of the portal vein or donor iliac vein bypass anastomosis was performed depending on the internal diameter and development of the recipient's portal vein. A normalized portal venous blood stream monitoring was performed during the perioperative stage. After operation, heparin sodium was used to bridge warfarin for anticoagulation therapy. After portal vein stenosis or thrombosis was identified with enhanced CT or portography, managements including embolectomy, systemic anticoagulation, interventional thrombus removal, balloon dilatation and/or stenting were performed. Results Among the 88 recipients, a total of 10 children were diagnosed with portal vein complications, of which 4 cases were diagnosed with portal vein stenosis at 1 d, 2 months, 8 months, and 11 months after surgery, and 6 cases were diagnosed with portal vein thrombosis at intraoperative, 2 d, 3 d (n=2), 6 d, and 11 months after surgery, respectively. One patient with portal vein stenosis and one patient with portal vein thrombosis died perioperatively. The fatality related to portal vein complications was 2% (2/88). Of the remaining 8 patients, 1 underwent systemic anticoagulation, 2 underwent portal venous embolectomy, 1 underwent interventional balloon dilatation, and 4 underwent interventional balloon dilatation plus stenting. No portal venous related symptoms were detected during postoperative long term follow up, and the retested portal venous blood stream parameters were normal. Conclusions The normalized intra- and post-operative portal venous blood stream monitoring is a useful tool for the early detection of portal vein complications, the early utilization of useful managements such as intraoperative portal venous embolectomy, interventional balloon dilatation and stenting may effectively treat the portal vein complications, thus minimizing the portal vein complication related graft loss and recipient death.

Objective Previous studies have shown that the triglyceride-glucose (TyG) index reflects insulin resistance and predicts the risk of ischemic stroke. Massive cerebral infarction, as a type of ischemic stroke with poor prognosis, is often more prone to complications and sequelae. However, no studies have yet explored the relationship between the TyG index and massive cerebral infarction. This study aims to investigate the role of the TyG index in assessing the infarct area in ischemic stroke. Methods This retrospective study included 212 adult patients with ischemic stroke diagnosed by cranial magnetic resonance imaging and admitted to our hospital from January 2020 to June 2024. The patients were divided into massive cerebral infarction group and non-massive cerebral infarction group according to the study purpose. Univariable and multivariable logistic regression analyses were performed on each group using SPSS 26 software. The receiver operating characteristic curves were analyzed for the prediction models. Results Variables with P＜0.2 in the univariable logistic regression analysis were included in the multivariable logistic regression analysis. The results showed that age (OR 1.043, 95% CI 1.004-1.084, P＜0.05), National Institutes of Health Stroke Scale score (OR 22.986, 95% CI 8.679-60.882, P＜0.001), and TyG index (OR 1.729, 95% CI 1.017-2.941, P＜0.05) were significant predictors. The area under the receiver operating characteristic curve of the predictive model was 0.868 (P＜0.001), indicating high predictive performance. Conclusion The TyG index is an independent risk factor for massive cerebral infarction. The combination of the TyG index with clinical laboratory indicators can effectively predict massive cerebral infarction.

Care dependence refers to a complex and comprehensive state of being dependent on others due to the limita-tion of physical functions caused by the disease.Elderly stroke patients are high risk group for care dependence due to decrease in self-care ability caused by their disease characteristics.Therefore,this paper reviews the current research status,influencing factors,and interventions of care dependence,in order to provide reference for increasing attention to the care needs of elderly stroke patients,reducing their dependence,and improving their quality of life.

[Objective]The clinical characteristics and the possible risk factors were explored for the low triiodothyronine syndrome(LTS)in elderly patients with chronic heart failure(CHF),and the risk prediction model of LTS was established.[Methods]For this research,291 elderly patients with CHF were selected as sample and retrospectively reviewed was used as analytical method.According to the thyroid function of admission patients,two groups including LTS group(n=107)and normal thyroid function group(n=184)were divided.The general information and biochemical indicators of patients were collected and recorded,and the risk factors for LTS were assigned scores,in which numerical variables(except age)were grouped by median.The chi-squared test was used for statistical analysis of each variable,and multivariate regression model was used to analyze the independent risk factors of LTS in elderly patients with CHF,then the nomogram model for LTS was established based on the results from the final regression analysis.Furthermore,the prediction model was evaluated using C-index,calibration curve and receiver operating characteristic(ROC)curve.[Result]Serum creatinine(Scr),C-reactive protein(CRP),interleukin-6(IL-6)and the cardiac functional grading according to the New York Heart Association(NYHA)were positively correlated with LTS(OR values were 1.893,2.356,1.021 and 1.815,respectively,P<0.05),serum Albumin(Alb)was negatively correlated with LTS(OR=0.412,P<0.05).This means that,the LTS was easily occurred as the serum Alb level declined.When introduce the above statistically significant variables into nomogram obtained the C index with 0.807[95%CI=(0.757,0.856)].The calibration curve verified by internal verification showed that the calibration degree of this prediction model was well calibrated.ROC curve analysis showed that the prediction model was well differentiated.[Conclusion]The Scr,CRP,IL-6,Alb and cardiac functional grading in elderly CHF patients may be risk factors for incidence of LTS,while serum Alb may be a protective factor for LTS.Based on the above risk factors,the nomogram model for predicting the occurrence of LTS in elderly CHF patients had good differentiation and accuracy,and can provide guidance for clinical individualized prevention and treatment.