OBJECTIVE To investigate the effect and mechanism of self-assembled nanoparticles from Shaoyao gancao decoction （SGD-SAN） on the intestinal absorption behavior of its main active components. METHODS SGD-SAN was prepared and characterized. Using an in-situ single-pass intestinal perfusion model in rats， the absorption characteristics of five active components （albiflorin， paeoniflorin， liquiritin apioside， liquiritin， glycyrrhizic acid） from SGD-SAN in the jejunum and ileum were studied， with the absorption rate constant （ K a ） and apparent permeability coefficient （ P eff ） as indicators， and compared with free drugs. In the intestinal segment with optimal absorption， the effects of drug concentration and efflux transporter inhibitors （P-glycoprotein inhibitor verapamil， multidrug resistance-associated protein 2 inhibitor indomethacin， breast cancer resistance protein inhibitor reserpine） on the intestinal absorption characteristics of these components were examined. RESULTS The obtained SGD-SAN exhibited a spherical shape with uniform sizes， an average particle diameter of （155.57±2.65） nm， a polydispersity index of 0.34±0.03， and a Zeta potential of （－9.30±1.12） mV. The average total content of five active components， including albiflorin， was 12.26%， and remained unaffected by enzymatic degradation and intestinal physical absorption. Compared with the free drug group， the five active components in the SGD-SAN group exhibited higher absorption rates in the ileal segment， with significantly elevated K a and P eff values （except for the P eff value of glycyrrhizic acid in the ileal segment） （ P ＜0.05 or P ＜0.01）. Their absorption demonstrated a concentration-dependent trend. In the free drug groups， the absorption of each component was regulated by corresponding inhibitors （ P ＜0.05 or P ＜0.01）； whereas in the SGD-SAN groups， except for albiflorin and paeoniflorin， the absorption of the remaining components was not affected by the inhibitors （ P ＞0.05）. CONCLUSIONS SGD-SAN significantly enhances the intestinal absorption efficiency of active components. The above absorption-enhancing effect may be related to the avoidance of efflux transporter influence and the presence of a mixed absorption mode.

ObjectiveTo investigate the clinical features of tumor-induced acute pancreatitis （TIAP）， to construct and validate a predictive model for TIAP， and to provide help for early identification in clinical practice. MethodsA retrospective analysis was performed for the clinical data of 3 051 patients with acute pancreatitis （AP） who were admitted to The First Affiliated Hospital of Xinjiang Medical University from January 2020 to January 2026， among whom there were 72 patients with TIAP. To reduce class imbalance， 216 patients with non-tumor-related AP （2 979 patients） were randomly selected as conventional group using sex-stratified sampling， resulting in a cohort of 288 patients， and this cohort was randomly divided into a training set with 201 patients and a test set with 87 patients at a ratio of 7∶3. The two groups were compared in terms of general information and laboratory markers. The independent-samples t test was used for comparison of normally distributed continuous data between two groups， and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between two groups； the chi-square test was used for comparison of categorical data between two groups. Recursive feature elimination and least absolute shrinkage and selection operator regression were used for screening of characteristic variables， and five machine learning models were constructed， i.e.， logistic regression model， random forest model， support vector machine model， extreme gradient boosting model， and light gradient boosting machine model. The receiver operating characteristic curve and the precision-recall curve were used to assess model performance； the calibration curve was used to assess goodness of fit； decision curve analysis was used to evaluate clinical applicability and practicality； Shapley additive explanations were used to assess model interpretability. ResultsIn the training set of 201 patients， there were 52 patients （25.9%） in the TIAP group， and in the test set of 87 patients， there were 20 patients （23.0%） in the TIAP group. Compared with the conventional group， the TIAP group had a significantly higher proportion of patients with pancreatic duct dilatation （χ²=79.474， P<0.05）， a significantly higher age （Z=-5.838， P<0.05）， and significantly lower levels of white blood cell count （Z=5.630， P<0.05）， amylase （Z=2.606， P<0.05）， hemoglobin （Z=5.038， P<0.05）， and neutrophil percentage （Z=5.269， P<0.05）， as well as a lower level of direct bilirubin （Z=0.936， P>0.05）. The five machine learning models constructed based on these seven variables had a certain predictive ability， among which the logistic regression model had the best performance in the test set， with an area under the curve of 0.893 （95% confidence interval： 0.821 — 0.953）， an average precision of 0.654 in the precision-recall curve， good calibration， and good clinical benefits based on the decision curve analysis. ConclusionThe predictive model for TIAP based on pancreatic duct dilatation， age， white blood cell count， amylase， hemoglobin， neutrophil percentage， and direct bilirubin shows good predictive performance and can provide important guidance for the early diagnosis of TIAP.

Objective:Acute kidney injury(AKI) is a common complication after cardiac surgery, and associated with increased risk of development of chronic kidney disease and mortality in the long term. Neutrophil percentage-to-albumin ratio(NPAR) is a new inflammatory marker that has been used to predict the poor prognosis of patients with cardiovascular disease or shock. However, the relationship between NPAR and AKI in patients with cardiac surgery has not been established. The aim was to evaluate the relationship between NPAR and AKI after cardiac surgery.Methods:Data of all adult patients underwent cardiac surgery with cardiopulmonary bypass from January 1, 2006 to December 31, 2018 were extracted from electronic medical record system of the Guangdong Provincial People's Hospital and retrospectively analyzed. The outcome of interest was AKI diagnosed by using the criteria of Kidney Disease Improving Global Outcomes. Logistic regression was used to assess the relationship between NPAR and postoperative AKI while adjust for potential confounders. In addition, restricted cubic spline(RCS) was utilized to provide a flexible description of the association of the preoperative NPAR and AKI. Results:Totally, 24 178 patients were analyzed. The incidence of AKI was 30.1%. Compared with patients without AKI, those with AKI were older and had higher rates of males, left ventricular ejection fraction(LVEF) less than or equal to 0.60, estimated glomerular filtration rate less than 90 ml·min -1·1.73 m -2, hypertension, diabetes, emergency surgery, preoperative critical illness, and reoperation. The baseline serum creatinine, serum uric acid, cardiopulmonary bypass time and postoperative mechanical ventilation time were higher or longer in AKI patients than those in none AKI patients. Then, patients were divided into four groups based on NPAR quartiles. After adjusting for confounding factors using logisitc regression, compared with patients with NPAR in group 3(1.551.97), respectively. The RCS showed a U-shaped nonlinear relationship( P for nonlinear less than 0.001) between NPAR and AKI after adjusting for potential confounding factors. RCS indicated the NPAR of 1.77 was the lowest risk for AKI. When NPAR less than 1.77, per 1-standard deviation(SD) increase in NPAR, the risk of AKI decreased by 23.2%( OR=0.768, 95% CI: 0.687, 0.859). Conversely, when NPAR above 1.77, per one SD increase in NPAR, the risk of AKI increased by 25.9%( OR=1.259, 95% CI: 1.166, 1.36). Conclusion:A U-shaped relationship between NPAR and AKI after cardiac surgery was shown. The appropriate value for NPAR might be 1.77. The risk of AKI might be increased, when less or above this value. NPAR might be used as an effective and economical tool to identify AKI risk among individuals with cardiac surgery, as well as to formulate individualized prevention and intervention strategy.

Objective:Using Mendelian randomization analysis to investigate the unidirectional causal effects of gut microbiota on gout and serum uric acid levels.Methods:The Mendelian randomization analysis was conducted using summary statistics from genome-wide association studies (GWAS). The gut microbiota was used as the exposure factor, with gout and serum uric acid levels as the outcomes, utilizing the MiBioGen Consortium, FinnGen GWAS, and CKDGen Consortium meta-analysis databases. The analysis was performed using inverse variance weighted (IVW) method, MR-Egger, and weighted median (WM) approach. Additionally, sensitivity analysis was conducted by excluding heterogeneity and horizontal pleiotropy. This study used RStudio 4.3.1 software for analysis.Results:The IVW results confirmed that 17 microbiota taxa were associated with gout, including class Verrucomicrobiaceae [ OR(95% CI)=1.162(1.004, 1.344), P=0.044], family Verrucomicrobiaceae [ OR(95% CI)=1.161(1.004, 1.344), P=0.044], genus Akkermansia [ OR(95% CI)=1.162(1.004, 1.344), P=0.044], genus Collinsella [ OR(95% CI)=1.257(1.043, 1.516), P=0.016], genus Eubacterium hallii group [ OR(95% CI)=1.226(1.022, 1.471), P=0.027], genus Howardella [ OR(95% CI)=1.094(1.001, 1.195), P=0.046], genus Ruminococcaceae UCG010 [ OR(95% CI)=1.317(1.089, 1.593), P=0.004], order Clostridiales [ OR(95% CI)=1.182(1.007,1.387), P=0.041], order Verrucomicrobiales [ OR(95% CI)=1.162(1.004, 1.344), P=0.044], class Melainabacteria [ OR(95% CI)=0.894(0.804, 0.994), P=0.038], family Streptococcaceae [ OR(95% CI)=0.851(0.727, 0.996), P=0.044], unknown family [ OR(95% CI)=0.890(0.800, 0.989), P=0.030], genus Streptococcus [ OR(95% CI)=0.836(0.710, 0.983), P=0.030], unknown genus [ OR(95% CI)=0.890(0.800, 0.989), P=0.030], genus Victivallis [ OR(95% CI)=0.857(0.736, 0.998), P=0.046], order Gastranaerophilales [ OR(95% CI)=0.890(0.800,0.989), P=0.030], and phylum Bacteroidetes [ OR(95% CI)=0.827(0.692, 0.989), P=0.037]. Additionally, 5 microbiota taxa were associated with serum uric acid levels: phylum Actinobacteria [ OR(95% CI)=0.963(0.925, 0.992), P=0.027], family ⅩⅢ [ OR(95% CI)=0.965(0.932, 1.008), P=0.035], genus Escherichia Shigella [ OR(95% CI)=1.047(1.005,1.089), P=0.034], genus Lachnospiraceae FCS020 group [ OR(95% CI)=0.974(0.941, 1.003), P=0.028], and genus Lachnospiraceae NC2004 group [ OR(95% CI)=0.966(0.943, 0.995), P=0.018]. No abnormalities in SNPs were found in the sensitivity analysis. Conclusion:An increase in the levels of class Verrucomicrobiae, family Verrucomicrobiaceae, genus Akkermansia, and genus Escherichia Shigella is associated with an increased risk of gout or serum uric acid levels, while an increase in the levels of class Melainabacteria, family Streptococcaceae, unknown family, phylum Actinobacteria, and family ⅩⅢ is associated with a decreased risk of gout or serum uric acid levels.

Over the past 40 years,gynecological ultrasound in China has evolved from two-dimensional imaging to multi-modal imaging,quantitative analysis,artificial intelligence analysis and minimally invasive treatment,playing more and more important role in diagnosis and treatment of gynecological diseases.The development of diagnostic and therapeutic gynecological ultrasound techniques and relative clinical application advances in China were reviewed,and the future development prospects were looked forward to in this article.

Objective:Acute kidney injury(AKI) is a common complication after cardiac surgery, and associated with increased risk of development of chronic kidney disease and mortality in the long term. Neutrophil percentage-to-albumin ratio(NPAR) is a new inflammatory marker that has been used to predict the poor prognosis of patients with cardiovascular disease or shock. However, the relationship between NPAR and AKI in patients with cardiac surgery has not been established. The aim was to evaluate the relationship between NPAR and AKI after cardiac surgery.Methods:Data of all adult patients underwent cardiac surgery with cardiopulmonary bypass from January 1, 2006 to December 31, 2018 were extracted from electronic medical record system of the Guangdong Provincial People's Hospital and retrospectively analyzed. The outcome of interest was AKI diagnosed by using the criteria of Kidney Disease Improving Global Outcomes. Logistic regression was used to assess the relationship between NPAR and postoperative AKI while adjust for potential confounders. In addition, restricted cubic spline(RCS) was utilized to provide a flexible description of the association of the preoperative NPAR and AKI. Results:Totally, 24 178 patients were analyzed. The incidence of AKI was 30.1%. Compared with patients without AKI, those with AKI were older and had higher rates of males, left ventricular ejection fraction(LVEF) less than or equal to 0.60, estimated glomerular filtration rate less than 90 ml·min -1·1.73 m -2, hypertension, diabetes, emergency surgery, preoperative critical illness, and reoperation. The baseline serum creatinine, serum uric acid, cardiopulmonary bypass time and postoperative mechanical ventilation time were higher or longer in AKI patients than those in none AKI patients. Then, patients were divided into four groups based on NPAR quartiles. After adjusting for confounding factors using logisitc regression, compared with patients with NPAR in group 3(1.551.97), respectively. The RCS showed a U-shaped nonlinear relationship( P for nonlinear less than 0.001) between NPAR and AKI after adjusting for potential confounding factors. RCS indicated the NPAR of 1.77 was the lowest risk for AKI. When NPAR less than 1.77, per 1-standard deviation(SD) increase in NPAR, the risk of AKI decreased by 23.2%( OR=0.768, 95% CI: 0.687, 0.859). Conversely, when NPAR above 1.77, per one SD increase in NPAR, the risk of AKI increased by 25.9%( OR=1.259, 95% CI: 1.166, 1.36). Conclusion:A U-shaped relationship between NPAR and AKI after cardiac surgery was shown. The appropriate value for NPAR might be 1.77. The risk of AKI might be increased, when less or above this value. NPAR might be used as an effective and economical tool to identify AKI risk among individuals with cardiac surgery, as well as to formulate individualized prevention and intervention strategy.

Objective:To explore the correlation between the level of T-lymphocyte subsets in peripheral blood and the progression of Alzheimer′s disease (AD).Methods:A cross-sectional study was conducted, including 30 cases of amnestic mild cognitive impairment (aMCI; aMCI group), 30 cases of mild AD (Mi-D; Mi-D group), 30 cases of moderate AD (Mo-D; Mo-D group), who were diagnosed in the Affiliated Hospital of Traditional Chinese Medicine of Xinjiang Medical University from January to December 2023, and 30 normal controls (normal control group) matched by age and gender. The levels of T cell subsets in peripheral blood were detected by flow cytometry, and the subpopulations of CD4 +T cells, Th cells, were examined. Binary Logistic regression was used to explore the correlation between factors affecting patients′ cognitive function and the onset of AD, and Spearman′s correlation analysis was applied to assess the association between the level of peripheral blood immune cells and the severity of AD. Results:There were no statistically significant differences in peripheral blood CD4 +T cells ( F=1.762, P=0.158), CD8 +T cells ( F=0.370, P=0.775), CD4 +/CD8 +ratios ( F=1.976, P=0.121), and regulatory T cells (Tregs) levels ( F=0.232, P=0.874) among the aMCI group, Mi-D group, Mo-D group, and normal control group in the intergroup comparisons (all P>0.05). The study subjects were stratified according to gender, age, body mass index, and years of education affecting the cognitive function of AD patients, and the peripheral blood CD4 +T cells, CD8 +T cells, CD4 +/CD8 + ratios and Tregs levels showed no statistically significant differences among groups (all P>0.05). The results of binary Logistic regression analysis showed that the peripheral blood CD8 +T-cell level ( OR=1.131, 95% CI 1.009-1.268, P=0.035) was a risk factor for the onset of AD. Further analysis of peripheral blood CD4 +T cell subsets revealed that Th1 cell levels were lower in the aMCI group compared to the Mi-D group ( t=-2.354, P=0.036), and the Mo-D group ( t=-2.079, P=0.026). The results of the Spearman′s correlation analysis showed that peripheral blood Th1 cell level was positively correlated with AD progression ( r=0.192, P<0.05). Conclusions:AD patients show peripheral immune imbalance, peripheral blood CD8 +T-cell level is a risk factor for the onset of AD, and peripheral Th1 cell level is positively correlated with the severity of AD. Monitoring the changes in peripheral blood Th1 cell level may have a predictive value for the progression of AD.

Objective:To develop a quality control model for anal sphincter ultrasound images and validate its diagnostic performance across multiple centers.Methods:A retrospective analysis was conducted on anal sphincter ultrasound images from seven medical centers in China between May 2019 and June 2022. A total of 7 040 images from 3 116 patients were included and divided into a training set（4 912 images）and a validation set（2 128 images）. The images were classified as standard or non-standard images by three experts. Three models were developed based on different image feature extraction methods：a single-branch model，a multi-branch weighted model，and a multi-branch ensemble model. The diagnostic performance of each model was evaluated using the area under the ROC curve（AUC），sensitivity，specificity，accuracy，positive predictive value，and negative predictive value，respectively. The optimal model was selected and compared with the performance of 4 doctors with varying experience levels. Sixty days later，the images with the assistance of the model's output were reassessed by the doctors to evaluate its impact on manual quality control.Results:① Among the 3 models，the multi-branch ensemble model demonstrated the highest AUC and sensitivity，with an AUC of 0.966（95% CI=0.958 - 0.974），a sensitivity of 91.83%，and a specificity of 91.41%. This model was named M quality. ② M quality's AUC was slightly lower than that of Senior A and B（0.966 vs. 0.976，0.976，and P<0.05），its sensitivity was slightly lower than that of Senior A（91.83% vs. 95.61%， P<0.001）but comparable to Senior B（91.83% vs. 92.89%， P=0.315），its specificity was slightly lower than Senior A and B（91.41% vs. 94.44%，98.18%，and P<0.05）. However，M quality significantly outperformed Junior A and B in AUC and sensitivity（AUC：0.966 vs. 0.850，0.818；sensitivity：91.83% vs. 84.90%，61.46%；all P<0.001），its specificity was higher than that of Junior A（91.41% vs. 80.28%， P<0.001）but lower than that of Junior B（91.41% vs. 95.96%， P<0.001）. ③ With model assistance，Senior B's sensitivity（92.89% vs. 94.20%， P=0.001）and Senior A's specificity（94.44% vs. 96.56%， P<0.001）improved significantly. Junior A and B showed significant improvements in AUC and sensitivity（AUC：0.931 vs. 0.850，0.914 vs. 0.818；sensitivity：91.83% vs. 84.90%，89.53% vs. 61.46%；all P<0.001）. After model assistance，Junior A's specificity increased（93.62% vs. 80.28%， P<0.001），while Junior B's specificity decreased（91.60% vs. 95.96%， P=0.013）. Conclusions:This study develops a quality control model for anal sphincter ultrasound images with robust diagnostic performance，approaching the level of seniors. The model significantly enhances the image quality assessment capabilities of juniors，demonstrating promising clinical application potential.

Gynecological diseases have a high prevalence and severely impact women's health and quality of life. Ultrasonography is the first-line imaging modality for assessing gynecological diseases. However，its diagnostic results are highly dependent on clinical experience and are subject to significant interobserver variability. In recent years，the rapid development of artificial intelligence technology has led to the construction of models based on ultrasonic images，which have demonstrated high accuracy in the identification of uterine，ovarian，and pelvic floor structures，as well as in the diagnosis，classification，and prognosis of diseases. These models hold great promise for clinical application.

Over the past 40 years,gynecological ultrasound in China has evolved from two-dimensional imaging to multi-modal imaging,quantitative analysis,artificial intelligence analysis and minimally invasive treatment,playing more and more important role in diagnosis and treatment of gynecological diseases.The development of diagnostic and therapeutic gynecological ultrasound techniques and relative clinical application advances in China were reviewed,and the future development prospects were looked forward to in this article.