To summarize Professor DING Ying's clinical experience in treating children's IgA nephropathy from the perspective of "wind-induced water turbidity". It is believed that the core pathogenesis of IgA nephropathy in children is the wind stimμlating water to become turbidity， and the basic treatment principles are to eliminate wind and settle viscera， and to remove turbidity and drain water. For those with the syndrome of wind-heat invading the lungs and injury to blood collaterals， modified Yinqiao Powder （银翘散） combined with Xiaoji Decoction （小蓟饮子） could be used； for those with dampness-heat in Sanjiao， heavy dampness and light heat pattern， modified Sanren Decoction （三仁汤） combined with Bazheng Powder （八正散） could be used； for those with lung-spleen qi deficiency and kidney essence depletion pattern， modified Buzhong Yiqi Decoction （补中益气汤） combined with Wuzi Yanzong Pill （五子衍宗丸） could be used； for those with deficiency of both qi and yin， kidney deficiency with stasis pattern， self-prescribed Yishen Huazhuo Formula （益肾化浊方） could be used. Meanwhile on the basis of pattern identification and treatment， rattan-type herbs could be combined in use in order to unblock the meridians and collaterals.

Cholelithiasis is a common biliary system disease with a high incidence worldwide. Abnormal lipid metabolism has been shown to play a key role in the mechanism of gallstones. Therefore, recent research literature on the genes, proteins, and molecular substances involved in lipid metabolism during the pathogenesis of gallstones has been conducted. This study aimed to determine the role of lipid metabolism in the pathogenesis of gallstones and provide insights for future studies using previous research in genomics, metabolomics, transcriptomics, and other fields.

Objective:To investigate the feasibility of ultra-low dose (ULD) CT pulmonary angiography (CTPA) combined with deep learning reconstruction (DLR) in the diagnosis of pulmonary embolism (PE).Methods:This cross-sectional study prospectively enrolled 100 patients with suspected PE who underwent CTPA examination in Zhongshan Hospital Fudan University, and Shanghai Geriatric Medical Center from April to July 2024, and were randomly divided into the routine dose (RD) group and ULD group according to block randomization. Effective dose (ED) were calculated. The noise index of RD group and ULD group was set to 10 and 20, respectively. Other scanning parameters and contrast agent injection protocol were the same. The CT images of RD group were reconstructed using hybrid iterative reconstruction (HIR), while ULD images were reconstructed with HIR and DLR (ULD-HIR subgroup and ULD-DLR subgroup). The image quality of the three groups of images was subjectively evaluated (overall image noise, pulmonary artery display) and objectively evaluated [signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) of the images] respectively. Finally, the diagnostic results of PE by the expert committee composed of three chief physicians were taken as the gold standard, and one physician with lower qualifications independently evaluated the diagnostic rate of PE in the three groups of images. Objective image quality parameters across the three groups were compared using ANOVA, with LSD post hoc test was used for multiple comparisons. Subjective scores among the three groups were analyzed using the Kruskal-Wallis H test, with Bonferroni corrected pairwise post hoc test was applied for multiple pairwise comparisons. Results:The ED in the RD group and ULD group were (2.7±0.5) mSv and (0.7±0.2) mSv, respectively, and the differences were statistically significant ( t=26.42, P<0.001). The overall differences in CT values of pulmonary arteries at all levels in the images of the RD group, the ULD-HIR subgroup, and the ULD-DLR subgroup were not statistically significant ( P>0.05).The RD group, ULD-HIR subgroup and ULD-DLR subgroup overall differences in SNR and CNR at all levels pulmonary arteries were statistically significant ( P<0.001), in which except for the differences in CNR and SNR values of the left pulmonary arterial trunk in the RD group and the ULD-HIR subgroup, and SNR values of basal segment pulmonary artery of the lower lobe of the left lung, which were not statistically significant ( P>0.05), the differences of the rest of the indexes in the pairwise comparisons between the groups were statistically significant ( P<0.05). The overall differences in the subjective scores of image pulmonary vascular display and image noise in the RD group, ULD-HIR subgroup and ULD-DLR subgroup were statistically significant ( P<0.001), except that the differences in the subjective scores of image pulmonary vascular display in the ULD-DLR subgroup were not statistically significant when compared with that of the RD group ( P>0.05) and that of the rest of the metrics in the between-groups two-by-two comparisons were all statistically significant ( P<0.05). The difference in diagnostic rates of PE in the pulmonary artery trunk, lobe and segmental levels in the images of the RD group, ULD-HIR subgroup and ULD-DLR subgroup was not statistically significant ( P>0.05). Conclusions:DLR can significantly reduce the radiation dose of CTPA examination. Even at ultra-low radiation dose, its image quality is still better than HIR reconstruction at conventional doses and preserve diagnostic accuracy of PE at the lobe level and segment level.

Objective:To evaluate alterations in dopaminergic neurons, cortical metabolism, and functional connectivity networks in patients with early-onset Parkinson′s disease (EOPD) using multimodal neuroimaging.Methods:In this prospective cross-sectional study, 26 patients with EOPD and 16 healthy controls (HC group) were recruited from the PLA General Hospital between April and November 2023. All participants underwent integrated 11C-β-CFT PET/MR, 18F-FDG PET/CT brain imaging and resting-state functional MRI. Clinical assessments were conducted using the Unified Parkinson′s Disease Rating Scale and Hoehn-Yahr staging. Cognitive status was evaluated using the Mini-Mental State Examination and Montreal Cognitive Assessment. Standardized uptake value ratios for both 11C-β-CFT and 18F-FDG PET images were calculated using cerebellar gray matter as the reference region. Voxel-wise two-sample t-tests were performed to identify regions with significant group differences in tracer uptake. Seed regions showing altered 11C-β-CFT or 18F-FDG uptake were used to compute seed-based functional connectivity (FC) with all other brain voxels, and group differences in FC were assessed. Correlations between imaging metrics and clinical scales were evaluated using Pearson or Spearman analyses as appropriate. Results:Compared with HC group, EOPD group showed significantly reduced 11C-β-CFT uptake in the bilateral putamen, globus pallidus, and left temporal pole ( P<0.05), and decreased 18F-FDG uptake in the right superior frontal gyrus and anterior cingulate cortex ( P<0.05). Relative to HC group, EOPD group exhibited markedly lower FC between the right putamen and the left gyrus rectus as well as the right parahippocampal gyrus; the right superior frontal gyrus and the left gyrus rectus; the anterior cingulate cortex and the olfactory area of the frontal lobe, the left gyrus rectus, and the right superior parietal gyrus; the left temporal pole and the left orbitofrontal cortex as well as the left olfactory area ( P<0.05). Correlation analyses revealed no statistically significant associations between altered FC values and clinical scale scores in the EOPD group. Conclusions:Patients with EOPD demonstrate impaired nigrostriatal dopaminergic function, regional cortical hypometabolism, and aberrant functional connectivity across multiple brain networks.

This study aims to explore protective effects of Lycium barbarum polysaccharides(LBP)on intestinal damage caused by lipopolysaccharide(LPS)-induced inflammatory bowel disease(IBD)in chicks.Network pharmacology was initially employed to determine the target proteins of wolfberry in the prevention and treatment of IBD.Following this,protein-protein interaction analy-sis,GO and KEGG pathway enrichment analysis,and molecular docking studies were conducted.Subsequently,an animal study was conducted:a total of 100 one-day-old male Hy-line brown lay-ing hens were randomly divided into five groups:a blank control group(CON),an LPS treatment group(LPS),a low-dose LBP group(LPS+LBP 0.25 g/L,L-LBP),a medium-dose LBP group(LPS+LBP 0.5 g/L,M-LBP),and a high-dose LBP group(LPS+LBP 1 g/L,H-LBP).Upon reac-hing 21 days old,duodenal,jejunal,ileal,and cecal tissues were collected to determine SOD and GSH-Px levels.Furthermore,the mRNA expression levels of TNF-α,AKT1,IL-6,IL-1β and TP53 in the intestinal tissues were measured using quantitative real-time PCR.The results demonstrated that network pharmacology identified 45 active ingredients in wolfberry that target 116 key protein sites,including TNF,AKT1 and IL6.The primary objectives focus on signaling pathways including AGE-RAGE,IL-17,TNF,HIF-1,and NF-κB.Molecular docking showed excellent ligand-receptor docking scores,with stable binding facilitated by hydrogen bonds and hydrophobic interactions.Compared to the LPS group,the 0.5 g/L LBP exhibited notably higher levels of SOD and T-AOC.In comparison with the LPS group,the medium and high-dose LBP experimental groups showed notably decreased the mRNA expressions of TNF-α,AKT1,IL-6,and IL-1β,while TP53 mRNA expression was significantly upregulated(P＜0.01).In summary,wolfberry exerts preventive and therapeutic effects on IBD through a multi-component,multi-target,and multi-pathway mecha-nism.

Objective:To construct and validate a predictive model and application program for stone recurrence after endoscopic retrograde cholangiopancreatography (ERCP) based on machine learning algorithms in patients with common bile duct stones (CBDS).Methods:A multicenter retrospective cohort study was conducted, 862 CBDS patients underwent ERCP from June 2020 to September 2023 in Changshu First People′s Hospital (data set 1, 759 cases, including a training set of 588 cases and a validation set of 171 cases) and Changshu Hospital of Traditional Chinese Medicine (data set 2, 103 cases, used as a test set). The demographics, medical history, ERCP procedural records and laboratory indices were collected. All patients were followed up for 1 year, and the stone recurrence was recorded. In training set, the feature selection was conducted by the least absolute shrinkage and selection operator (LASSO) algorithm, and a conventional Logistic regression model was constructed based on selected features. The 3 machine learning algorithms (gradient boosting machine model, extreme gradient boosting model and random forest model) and a conventional Logistic regression model (LASSO model) were trained to fit predictive models. The model performance was assessed by area under curve (AUC) of receiver operating characteristic curve. The model interpretability was analyzed by feature importance evaluation, Shapley additive explanations (SHAP) and force plots. The best-performing model was deployed as an online application by Streamlit framework (V1.36.0).Results:Among the 862 patients, 158 patients (18.33%) developed stone recurrence after ERCP. There were no statistical difference in demographics, medical history, ERCP procedural records and laboratory indices between training set and a validation set ( P>0.05). LASSO regression analysis result showed that 6 key variables (in descending order of significance: endoscopic sphincterotomy, common bile duct angulation, stone diameter, stone count, common bile duct diameter, and periampullary diverticulum) influencing stone recurrence. ROC curve analysis result showed that the random forest model exhibited the highest predictive performance (it had the largest AUC of 0.900). SHAP analysis result showed that common bile duct angulation, common bile duct diameter, stone diameter, endoscopic sphincterotomy and stone count were the top 5 contributing factors in the random forest model. Using Python, the random forest model was implemented into a Streamlit-based application with a user-friendly visual interface, providing predictive outcomes, confidence levels, SHAP force diagram and health recommendations. In the test set, the application program achieved an accuracy of 84.5% (87/103), sensitivity of 82.6% (19/23), and specificity of 85.0% (68/80). SHAP plots and force diagram intuitively illustrated the impact of key features on stone recurrence prediction, offering a clear visualization of each variable′s role within the model. Conclusions:The predictive model and application program based on the random forest machine learning algorithms demonstrate excellent predictive performance and practical usability in predicting stone recurrence after ERCP in patients with CBDS.

Objective To construct YOLOv10 based artificial intelligence(AI)models for the automatic detection in small bowel capsule endoscopy(SBCE)images.Methods SBCE data from two centers was collected,including 23 115 images and 35 412 annotated labels covering 11 categories of small bowel lesions.The images were annotated using the LabelMe tool and converted into the YOLO format required for deep learning model development.The pre-trained YOLOv10 and YOLOv8 models were used for transfer learning training on the constructed dataset.Model performance was comprehensively evaluated using metrics such as precision,accuracy,sensitivity,specificity,false-positive rate,and detection speed.Finally,the models were deployed on local computers for real-time detection of SBCE images and videos.Results Six different versions of YOLO object detection models were developed,namely YOLOv8n,YOLOv8s,YOLOv8m,YOLOv10n,YOLOv10s,and YOLOv10m.On the validation set,YOLOv10s model achieved the best mAP50(0.795);although its inference latency was not the fastest(4.803 ms/img),it met the requirements for clinical application.On the test set,YOLOv10s performed well,with an accuracy of 92.69%,a sensitivity of 89.23%,and a false-positive rate of 4.78%.Especially,in category-specific inference,the highest sensitivity was for"bleeding"at 96.41%,while the lowest was for"narrowing"at 82.29%.Conclusion The model constructed based on YOLOv10 neural network can rapidly and accurately detect and classify various small bowel lesions,exhibiting significant clinical application potential.

Functional constipation（FC）refers to constipation that is not caused by organic diseases of the intestines or systemic conditions，nor by medication-related factors. It is typically characterized by a prolonged course and a tendency for symptoms to recur. When constipation symptoms persist despite standardized treatment and significantly impact daily life，it may be termed refractory FC. In recent years，some novel treatment approaches for refractory FC have begun to be applied in children. These include new medications such as prucalopride，lubiprostone，and linaclotide，as well as fecal microbiota transplantation（FMT），neuromodulation，biofeedback therapy，and antegrade continence enema（ACE）. This article reviews the current advances in the treatment of refractory FC in children，aiming to provide insights and directions for the application of new therapeutic methods in clinical practice in the future.

Cholelithiasis is a common biliary system disease with a high incidence worldwide. Abnormal lipid metabolism has been shown to play a key role in the mechanism of gallstones. Therefore, recent research literature on the genes, proteins, and molecular substances involved in lipid metabolism during the pathogenesis of gallstones has been conducted. This study aimed to determine the role of lipid metabolism in the pathogenesis of gallstones and provide insights for future studies using previous research in genomics, metabolomics, transcriptomics, and other fields.

Cholelithiasis is a common biliary system disease with a high incidence worldwide. Abnormal lipid metabolism has been shown to play a key role in the mechanism of gallstones. Therefore, recent research literature on the genes, proteins, and molecular substances involved in lipid metabolism during the pathogenesis of gallstones has been conducted. This study aimed to determine the role of lipid metabolism in the pathogenesis of gallstones and provide insights for future studies using previous research in genomics, metabolomics, transcriptomics, and other fields.