Objective To evaluate the predictive value of dual-modality ultrasound,incorporating conventional ultrasound and ultrasound elastography,in combination with S-Detect for cervical lymph node metastasis(CLNM)in patients with papillary thyroid carcinoma(PTC).Methods A retrospective analysis was conducted on the clinical data of 135 patients diagnosed with PTC who received treatment at the First Affiliated Hospital of Shihezi University between November 2023 and August 2024.For all patients,clinical baseline characteristics,conventional ultrasound findings,ultrasound elastography results,and S-Detect analysis data were collected.Independent predictors of CLNM in PTC were identified,and predictive models were developed.Receiver operating characteristic(ROC)curves were generated to compare the area under the curve(AUC)of the models.The most effective predictive model was selected to construct a risk probability nomogram,and the predictive performance and clinical applicability of this nomogram were subsequently evaluated.Results Age,maximum nodule diameter,boundary characteristics,capsular invasion,transverse-sectional morphological findings assessed by S-Detect,and ECI-based elasticity grading were identified as independent predictors of CLNM in PTC(all P<0.05).The AUC of the predictive model constructed using these six variables was 0.890(95%CI:0.835～0.945).The calibration curve demonstrated strong agreement between predicted and observed outcomes,and decision curve analysis indicated that the nomogram provided a favorable net clinical benefit within a threshold probability range of 2%to 91.5%.Conclusions Age,maximum nodule diameter,boundary characteristics,capsular invasion,sonographic features assessed by S-Detect in the transverse plane,and ECI-based elasticity grading are independent predictors of CLNM in PTC.A nomogram model incorporating these parameters demonstrates effective performance in predicting the likelihood of CLNM.

Objective:To explore the CT manifestation characteristics of peripancreatic aneurysms related to pancreatitis (PRPA).Methods:A retrospective analysis was conducted on the clinical data of 15 patients with pancreatitis-related aneurysms collected in Deyang People's Hospital from June 2017 to February 2025. Among them, there were 11 males and 4 females, with an age of (56.5±16.9) years. Record the CT manifestations of the patients, and observe the PRPA tumor-carrying arteries, morphology, quantity, bleeding, calcification, dynamic changes, etc.Results:The CT results showed that there were a total of 26 PRPAs in 15 patients. The aneurysm walls of the PRPAs had no calcification, among which 12 cases were single and 1 case was double. Two cases were multiple. The patients were pancreatitis complicated with muscle fiber dysplasia. Among them, one case had 5 PRPAs and the other had 7 PRPAs. Of the 26 PRPAs, 12 were sac-like, 8 were beaded, 4 were fusiform, and 2 were columnar in shape. The numbers of aneurysm-carrying arteries and PRPA were as follows: 8 in the pancreaticoduodenal artery, 7 in the hepatic artery and its branches, 6 in the splenic artery and its branches, 2 in the left gastric artery, 1 in the gastroduodenal artery, 1 in the middle colonic artery, and 1 in the ileocolonic artery. The CT diagnosis report missed 16 PRPAs, with a missed diagnosis rate of 61.5% (16/26). Among the 11 ruptured PRPAs, 4 were missed, with a missed diagnosis rate of 36.4%. Three missed aneurysms were diagnosed by digital subtraction angiography, and one was retrospectively analyzed by CT. Among the 15 unruptured PRPAs, 12 were missed, with a missed diagnosis rate of 80.0%. All the missed aneurysms were detected by retrospective CT analysis. There were 2 images without re-examination and 24 images with re-examination. Among the PRPAs with re-examination images, 4 disappeared after interventional embolization on the same day, 1 relapsed after interventional embolization on the same day, with a reduction in volume and disappeared after 3 days. Three cases underwent elective interventional embolization, among which two shranked and one enlarged before interventional embolization. Among the 16 cases that did not receive interventional treatment, 7 disappeared on their own, 1 was completely liquefied, 5 shrank but did not disappear, 2 remained stable in size without any change, and 1 increased. Among the re-examined PRPA images, 7 showed signs of enlargement.Conclusion:The main characteristics of PRPA are high rupture rate, prone to missed diagnosis and dynamic changes in size.

In this experiment, self-assembled nanoparticles(SANs) were prepared by the pH-driven method, and Her-HCP SAN was constructed by using herpetrione(Her) and Herpetospermum caudigerum polysaccharides(HCPs). The average particle size and polydispersity index(PDI) were used as evaluation indexes for process optimization, and the quality of the final formulation was evaluated in terms of particle size, PDI, Zeta potential, and microstructure. The proposed Her-HCP SAN showed a spheroid structure and uniform morphology, with an average particle size of(244.58±16.84) nm, a PDI of 0.147 1±0.014 8, and a Zeta potential of(-38.52±2.11) mV. Her-HCP SAN significantly increased the saturation solubility of Her by 2.69 times, with a cumulative release of 90.18% within eight hours. The results of in vivo unidirectional intestinal perfusion reveal that Her active pharmaceutical ingredient(API) is most effectively absorbed in the jejunum, where both K_a and P_(app) are significantly higher compared to the ileum(P<0.001). However, the addition of HCP leads to a significant reduction in the P_(app) of Her in the jejunum(P<0.05). Furthermore, the formation of the Her-HCP SAN results in a notably lower P_(app) in the jejunum compared to Her API alone(P<0.001), while both K_a and P_(app) in the ileum are significantly increased(P<0.001, P<0.05). The absorption of Her-HCP SAN at different concentrations in the ileum shows no significant differences, and the pH has no significant effect on the absorption of Her-HCP SAN in the ileum. The addition of the transporter protein inhibitors(indomethacin and rifampicin) significantly increases the absorption parameters K_a and P_(app) of Her-HCP SAN in the ileum(P<0.05,P<0.01), whereas the addition of verapamil has no significant effect on the intestinal absorption parameters of Her-HCP SAN, suggesting that Her may be a substrate for multidrug resistance-associated protein 2 and breast cancer resistance proteins but not a substrate of P-glycoprotein.
Nanoparticles/metabolism* ; Polysaccharides/pharmacokinetics* ; Intestinal Absorption/drug effects* ; Animals ; Rats ; Particle Size ; Drugs, Chinese Herbal/pharmacokinetics* ; Male ; Rats, Sprague-Dawley ; Drug Carriers/chemistry* ; Drug Compounding ; Cucurbitaceae/chemistry*

Objective To evaluate the predictive value of dual-modality ultrasound,incorporating conventional ultrasound and ultrasound elastography,in combination with S-Detect for cervical lymph node metastasis(CLNM)in patients with papillary thyroid carcinoma(PTC).Methods A retrospective analysis was conducted on the clinical data of 135 patients diagnosed with PTC who received treatment at the First Affiliated Hospital of Shihezi University between November 2023 and August 2024.For all patients,clinical baseline characteristics,conventional ultrasound findings,ultrasound elastography results,and S-Detect analysis data were collected.Independent predictors of CLNM in PTC were identified,and predictive models were developed.Receiver operating characteristic(ROC)curves were generated to compare the area under the curve(AUC)of the models.The most effective predictive model was selected to construct a risk probability nomogram,and the predictive performance and clinical applicability of this nomogram were subsequently evaluated.Results Age,maximum nodule diameter,boundary characteristics,capsular invasion,transverse-sectional morphological findings assessed by S-Detect,and ECI-based elasticity grading were identified as independent predictors of CLNM in PTC(all P<0.05).The AUC of the predictive model constructed using these six variables was 0.890(95%CI:0.835～0.945).The calibration curve demonstrated strong agreement between predicted and observed outcomes,and decision curve analysis indicated that the nomogram provided a favorable net clinical benefit within a threshold probability range of 2%to 91.5%.Conclusions Age,maximum nodule diameter,boundary characteristics,capsular invasion,sonographic features assessed by S-Detect in the transverse plane,and ECI-based elasticity grading are independent predictors of CLNM in PTC.A nomogram model incorporating these parameters demonstrates effective performance in predicting the likelihood of CLNM.

Objective:To investigate the risk factors for patients with hypertriglyceridemia-related acute pancreatitis (HTG-AP) developing into severe acute pancreatitis or experiencing organ failure.Methods:This retrospective cohort study collected clinical data from 2 429 patients diagnosed with acute pancreatitis from five hospitals in China between January 2019 and December 2023 using a pre-designed data collection form. The cohort included 1 516 males and 913 females,with an age of (50.2±16.5)years(range: 11 to 99 years). Among them,353 patients (16.1%) had HTG-AP,while 1 846 (83.9%) had non-HTG-AP. HTG-AP was defined as serum triglyceride levels>500 mg/dl with other etiologies excluded. Intergroup comparisons were performed using t-tests,Mann-Whitney U test or χ2 tests,respectively. Univariate and multivariate logistic regression analyses were conducted to assess risk factors for severe acute pancreatitis after adjusting for potential confounders,and a predictive model was developed and validated. Results:Compared with other etiologies,HTG-AP patients had a higher risk of progressing to SAP ( OR=1.415,95% CI: 0.866 to 2.312, P=0.017) and organ failure ( OR=1.256,95% CI: 1.015 to 1.554, P=0.036). Among HTG-AP patients,risk factors for SAP included body mass index ( OR=1.856,95% CI: 1.742 to 1.987, P=0.033),fasting blood glucose ( OR=1.128,95% CI: 1.036 to 1.229, P=0.006),white blood cell count( OR=1.162,95% CI: 1.055 to 1.281, P=0.002),and the presence of pleural effusion ( OR=13.151,95% CI: 4.330 to 19.946, P<0.01). A nomogram prediction model for SAP in HTG-AP was constructed based on these risk factors,demonstrating good discriminative ability with area under the curve values of 0.877 in the training set and 0.894 in the validation set,along with satisfactory calibration. Conclusions:HTG-AP patients are at higher risk of developing SAP and organ failure. The risk prediction model incorporating body mass index,fasting blood glucose,white blood cell count,and pleural effusion shows good predictive value for SAP.

Objective:To explore the CT manifestation characteristics of peripancreatic aneurysms related to pancreatitis (PRPA).Methods:A retrospective analysis was conducted on the clinical data of 15 patients with pancreatitis-related aneurysms collected in Deyang People's Hospital from June 2017 to February 2025. Among them, there were 11 males and 4 females, with an age of (56.5±16.9) years. Record the CT manifestations of the patients, and observe the PRPA tumor-carrying arteries, morphology, quantity, bleeding, calcification, dynamic changes, etc.Results:The CT results showed that there were a total of 26 PRPAs in 15 patients. The aneurysm walls of the PRPAs had no calcification, among which 12 cases were single and 1 case was double. Two cases were multiple. The patients were pancreatitis complicated with muscle fiber dysplasia. Among them, one case had 5 PRPAs and the other had 7 PRPAs. Of the 26 PRPAs, 12 were sac-like, 8 were beaded, 4 were fusiform, and 2 were columnar in shape. The numbers of aneurysm-carrying arteries and PRPA were as follows: 8 in the pancreaticoduodenal artery, 7 in the hepatic artery and its branches, 6 in the splenic artery and its branches, 2 in the left gastric artery, 1 in the gastroduodenal artery, 1 in the middle colonic artery, and 1 in the ileocolonic artery. The CT diagnosis report missed 16 PRPAs, with a missed diagnosis rate of 61.5% (16/26). Among the 11 ruptured PRPAs, 4 were missed, with a missed diagnosis rate of 36.4%. Three missed aneurysms were diagnosed by digital subtraction angiography, and one was retrospectively analyzed by CT. Among the 15 unruptured PRPAs, 12 were missed, with a missed diagnosis rate of 80.0%. All the missed aneurysms were detected by retrospective CT analysis. There were 2 images without re-examination and 24 images with re-examination. Among the PRPAs with re-examination images, 4 disappeared after interventional embolization on the same day, 1 relapsed after interventional embolization on the same day, with a reduction in volume and disappeared after 3 days. Three cases underwent elective interventional embolization, among which two shranked and one enlarged before interventional embolization. Among the 16 cases that did not receive interventional treatment, 7 disappeared on their own, 1 was completely liquefied, 5 shrank but did not disappear, 2 remained stable in size without any change, and 1 increased. Among the re-examined PRPA images, 7 showed signs of enlargement.Conclusion:The main characteristics of PRPA are high rupture rate, prone to missed diagnosis and dynamic changes in size.

Objective:To investigate the risk factors for patients with hypertriglyceridemia-related acute pancreatitis (HTG-AP) developing into severe acute pancreatitis or experiencing organ failure.Methods:This retrospective cohort study collected clinical data from 2 429 patients diagnosed with acute pancreatitis from five hospitals in China between January 2019 and December 2023 using a pre-designed data collection form. The cohort included 1 516 males and 913 females,with an age of (50.2±16.5)years(range: 11 to 99 years). Among them,353 patients (16.1%) had HTG-AP,while 1 846 (83.9%) had non-HTG-AP. HTG-AP was defined as serum triglyceride levels>500 mg/dl with other etiologies excluded. Intergroup comparisons were performed using t-tests,Mann-Whitney U test or χ2 tests,respectively. Univariate and multivariate logistic regression analyses were conducted to assess risk factors for severe acute pancreatitis after adjusting for potential confounders,and a predictive model was developed and validated. Results:Compared with other etiologies,HTG-AP patients had a higher risk of progressing to SAP ( OR=1.415,95% CI: 0.866 to 2.312, P=0.017) and organ failure ( OR=1.256,95% CI: 1.015 to 1.554, P=0.036). Among HTG-AP patients,risk factors for SAP included body mass index ( OR=1.856,95% CI: 1.742 to 1.987, P=0.033),fasting blood glucose ( OR=1.128,95% CI: 1.036 to 1.229, P=0.006),white blood cell count( OR=1.162,95% CI: 1.055 to 1.281, P=0.002),and the presence of pleural effusion ( OR=13.151,95% CI: 4.330 to 19.946, P<0.01). A nomogram prediction model for SAP in HTG-AP was constructed based on these risk factors,demonstrating good discriminative ability with area under the curve values of 0.877 in the training set and 0.894 in the validation set,along with satisfactory calibration. Conclusions:HTG-AP patients are at higher risk of developing SAP and organ failure. The risk prediction model incorporating body mass index,fasting blood glucose,white blood cell count,and pleural effusion shows good predictive value for SAP.

Near infrared spectroscopy(NIRS)technology combined with chemometrics algorithms has been widely used in quantitative and qualitative analysis of food and medicine.However,traditional chemometrics methods,especially linear classification methods,often yield unsatisfactory results when addressing multi-class classification problems.Convolutional neural network(CNN)is adept at extracting deep-level features from data and suitable for handling non-linear relationships.The modeling performance of CNN depends on the size and diversity of sample,while the collection and preprocessing of NIRS sample data is often time-consuming and labor-intensive.This study proposed a NIRS qualitative analysis method based on data augmentation strategies and CNN.The data augmentation strategy included two steps.Firstly,applying Bootstrap resampling and generative adversarial network(GAN)methods to augment three NIRS datasets(Medicine,coffee and grape).Secondly,combining the original samples(Y)with the Bootstrap augmented samples(B)and GAN augmented samples(G)to obtain three augmented datasets(Y-B,Y-G and Y-B-G).Based on this,a CNN model structure suitable for these datasets was designed,consisting of 2 one-dimensional convolutional layers,1 max-pooling layer,and 1 fully connected layer.The results showed that compared to the optimal models of partial least squares discriminant analysis(PLS-DA),support vector machine(SVM),and back propagation neural network(BP),the CNN model based on Y-B dataset achieved average accuracy improvements of 3.998%,9.364%,and 4.689%for medicine(Binary classification);the CNN model based on the Y-B-G dataset achieved average accuracy improvements of 6.001%,2.004%,and 7.523%for coffee(7-class classification);and the CNN model based on the Y-B dataset achieved average accuracy improvements of 33.408%,51.994%,and 34.378%for grapes(20-class classification).It was evident that the models established based on data augmentation strategies and CNN demonstrated better classification accuracy and generalization performance with different datasets and classification categories.

Objective:To analyze the release and distribution characteristics of Chinese medical insurance payment policies,and to provide reference for future policy formulation in the field of medical insurance payment construction.Methods: Content analysis method was used to construct a two-dimensional framework of "policy goals-policy tools",and text analysis was carried out according to 63 policy documents.Results: A total of 493 policy codes were completed.From the perspective of policy goals,the policy objectives of Chinese medical insurance payment mainly focused on three aspects: improving the payment level,optimizing the medical insurance environment,and standardizing the supervision regulations.From the perspective of policy tools,environmental policy tools are the most used policy tools,followed by supply and demand tools.There is a shortage of financial input and talent training in all policy objectives,so more attention should be paid to demonstration and Category of payment.Conclusion: Our country puts forth effort to build a perfect medical insurance payment system,but should further strengthen policy content supplement,optimize the structure of policy tools,and give full play to the payment ability of medical insurance when pulling the demand of medical insurance payment and driving the supply of medical insurance payment.

Six compounds were isolated from the roots of Ephedra sinica Stapf using various chromatographic techniques such as silica gel column chromatography, thin layer chromatography and semi-preparative HPLC. Their chemical structures were identified by analysis of physicochemical properties and spectral data, and determined as (Z)-docosanylferulate (1), (E)-docosanylferulate (2), bis (2-ethylheptyl) phythalate (3), 2,2′-oxybis (1,4-di-tert-butylbenzene) (4), diisobutyl phthalate (5), bis (2-ethylhexyl) phthalate (6). Among them, compound 1 is a new compound, compounds 2-4 were first isolated from Ephedra. A corticosterone-induced PC-12 cell injury model was used for compound activity screening. The results showed that compounds 1 and 5 significantly improved corticosterone-induced PC-12 cell injury and significantly increased 5-HT₇ receptor protein expression in the cells, indicating potential antidepressant activity.