ObjectiveTo evaluate the clinical efficacy and safety of Qidan Tangshen Granules （芪丹糖肾颗粒， QTG） in the treatment of early diabetic kidney disease （DKD） with qi deficiency， blood stasis， and kidney deficiency syndrome， and to explore its mechanism. MethodsA double-blind， double-simulated method was used to enroll 200 patients with early DKD and qi deficiency， blood stasis， and kidney deficiency syndrome. Patients were randomly assigned in a 1∶1 ratio to the treatment group （100 cases） and the control group （100 cases）. The treatment group received QTG plus a valsartan capsule simulant， while the control group received valsartan capsules plus a QTG simulant， both for 12 weeks. The primary outcome was the urinary albumin-to-creatinine ratio （UACR）. Secondary outcomes included estimated glomerular filtration rate （eGFR）， fasting blood glucose （FBG）， 2-hour postprandial blood glucose （PBG）， glycated hemoglobin （HbA1c）， and traditional Chinese medicine （TCM） syndrome scores （including individual symptom scores for fatigue， dull complexion， soreness and weakness of the waist and knees， headache and chest pain， irritability， spontaneous sweating， thirst and polydipsia， polyphagia， polyuria， numbness of the limbs， and the total TCM syndrome score）. Oxidative stress markers including serum 8-hydroxy-2'-deoxyguanosine （8-OHDG）， 3-nitrotyrosine （3-NT）， and superoxide dismutase （SOD） were also assessed. Clinical efficacy and TCM syndrome efficacy were evaluated after treatment， and routine blood tests， urinalysis， and liver function tests were conducted and adverse reaction during the tria was recorded to assess safety. ResultsA total of 191 patients completed the study （95 in the treatment group and 96 in the control group）. The treatment group showed significant reductions in UACR， FBG， PBG， and HbA1c levels after treatment （P＜0.05 or P＜0.01）. The single TCM symptom scores except for polyphagia and total TCM syndrome scores significantly decreased （P＜0.05 or P＜0.01）. Compared to the control group， the treatment group had signi-ficantly lower UACR， FBG， PBG levels， and total TCM syndrome scores， sinlge symptoms scores except for polyphagia and limb numbness （P＜0.05 or P＜0.01）. Among 40 randomly selected patients （21 cases in the treatment group and 19 cases in the control group） for oxidative stress analysis， there were no significant differences in SOD， 3-NT， and 8-OHDG levels before and after treatment within or between groups （P＞0.05）. The overall effective rate in the treatment group was 64.2% （61/95） and 39.6% （38/96） in the control group， while the TCM syndrome efficacy rates were 80.0% （76/95） and 24.0% （23/96）， respectively， with the treatment group showing superior efficacy （P＜0.01）. No significant differences were observed in routine blood tests， urinalysis， or liver function indices before and after treatment in either group （P＞0.05）. The incidence of adverse reactions was 8.4% （8/95） in the treatment group and 9.4% （9/96） in the control group， with no statistically significant difference （P＞0.05）. ConclusionQTG can effectively reduce UACR and blood glucose levels， alleviate clinical symptoms， and improve clinical efficacy in patients with early DKD with qi deficiency， blood stasis， and kidney deficiency syndrome. The treatment is well-tolerated and safe， with no significant impact on oxidative stress markers.

ObjectiveThis study proposes a novel single-cell protein localization method based on a class perception graph convolutional network (CP-GCN) to overcome several critical challenges in protein microscopic image analysis, including the scarcity of cell-level annotations, inadequate feature extraction, and the difficulty in achieving precise protein localization within individual cells. The methodology involves multiple innovative components designed to enhance both feature extraction and localization accuracy. MethodsFirst, a class perception module (CPM) is developed to effectively capture and distinguish semantic features across different subcellular categories, enabling more discriminative feature representation. Building upon this, the CP-GCN network is designed to explore global features of subcellular proteins in multicellular environments. This network incorporates a category feature-aware module to extract protein semantic features aligned with label dimensions and establishes a subcellular relationship mining module to model correlations between different subcellular structures. By doing so, it generates co-occurrence embedding features that encode spatial and contextual relationships among subcellular locations, thereby improving feature representation. To further refine localization, a multi-scale feature analysis approach is employed using the K-means clustering algorithm, which classifies multi-scale features within each subcellular category and generates multi-cell class activation maps (CAMs). These CAMs highlight discriminative regions associated with specific subcellular locations, facilitating more accurate protein localization. Additionally, a pseudo-label generation strategy is introduced to address the lack of annotated single-cell data. This strategy segments multicellular images into single-cell images and assigns reliable pseudo-labels based on the CAM-predicted regions, ensuring high-quality training data for single-cell analysis. Under a transfer learning framework, the model is trained to achieve precise single-cell-level protein localization, leveraging both the extracted features and pseudo-labels for robust performance. ResultsExperimental validation on multiple single-cell test datasets demonstrates that the proposed method significantly outperforms existing approaches in terms of robustness and localization accuracy. Specifically, on the Kaggle 2021 dataset, the method achieves superior mean average precision (mAP) metrics across 18 subcellular categories, highlighting its effectiveness in diverse protein localization tasks. Visualization of the generated CAM results further confirms the model’s capability to accurately localize subcellular proteins within individual cells, even in complex multicellular environments. ConclusionThe integration of the CP-GCN network with a pseudo-labeling strategy enables the proposed method to effectively capture heterogeneous cellular features in protein images and achieve precise single-cell protein localization. This advancement not only addresses key limitations in current protein image analysis but also provides a scalable and accurate solution for subcellular protein studies, with potential applications in biomedical research and diagnostic imaging. The success of this method underscores the importance of combining advanced deep learning architectures with innovative training strategies to overcome data scarcity and improve localization performance in biological image analysis. Future work could explore the extension of this framework to other types of microscopic imaging and its application in large-scale protein interaction studies.

Objective To investigate the effect of quercetin on HCE-2 injury of human corneal epithelial cells induced by high osmotic pressure and its mechanism.Methods HCE-2 cells were randomly divided into control group(normal osmotic pressure),model group(high osmotic pressure),experimental-L group(high osmotic pressure+31.25 pg·mL-1 quercetin),experimental-M group(high osmotic pressure+62.50 μg·mL-1 quercetin),experimental-H group(high osmotic pressure+125.00 μg·mL-1 quercetin),erastin group(high osmotic pressure+125.00 μg·mL-1 quercetin+30.00 μmol·L-1 iron death inducer erastin).Cell survival rate was detected by cell counting kit 8;reactive oxygen species(ROS)levels was detected by C11-BODIPY 581/591 probe staining;glutathione(GSH)and malondialdehyde(MDA)levels were determined by kit method;the expression levels of glutathione peroxidase 4(GPX4),dihydrolactate dehydrogenase(DHODH)and ferroptosis suppressor protein 1(FSP1)were detected by real-time quantitative polymerase chain reaction and Western blot.Results The cell survival rates of control group,model group,experimental-H group and erastin group were(100.00±3.97)％,(50.05±5.83)％,(86.35±7.35)％and(58.32±4.66)％,respectively;ROS levels were 1.00±0.09,2.45±0.16,1.19±0.05 and 2.09±0.30,respectively;GPX4 protein levels were 1.09±0.11,0.34±0.03,0.91±0.12 and 0.30±0.04,respectively;FSP1 protein levels were 0.92±0.06,0.25±0.03,0.89±0.07 and 0.39±0.07,respectively;DHODH protein levels were 0.89±0.11,0.31±0.04,0.86±0.11,0.41±0.04,respectively.Compared with model group,the above indexes in control group were statistically significant(all P＜0.05);the differences between experimental-H group and model group were statistically significant(all P＜0.05);the above indexes in erastin group were significantly different from those in experimental-H group(all P＜0.05).Conclusion Quercetin can ameliorate HCE-2 cell damage induced by high osmotic pressure by inhibiting iron death pathway.

Insulin resistance(IR)is an abnormal pathological and physiological process characterized by a decrease in the ability of target tissues and organs to utilize insulin.There are many factors related to IR.Epigenetic modification is one of the important regulatory mechanisms that cause IR.N6-methyladenosine(m6A)is an epigenetic modification with high abundance in Eukaryote mRNA.Its dynamic changes can regulate the expression of related enzymes,affect IR process and exert different biological effects in target organs.This article reviews the research progress of dynamic modification and regulation of m6A methylation in IR.

OBJECTIVE To explore the protective mechanism of amifostine on acute radiation injury mice. METHODS Thirty C57BL/6J mice were randomly divided into normal control group， model group and amifostine group （150 mg/kg）， with 10 mice in each group. Thirty minutes before irradiation， the mice in the amifostine group were intraperitoneally injected with amifostine； normal control group and model group were given constant volume of normal saline intraperitoneally； then acute radiation injury was induced by 4 Gy X-ray radiation in both model group and amifostine group. The white blood cell count （WBC）， platelet count and red blood cell （RBC） count in mice were detected 2 hours before irradiation and on days 1， 4， 7， 10 and 14 after irradiation； the changes in the proportion of WBC （neutrophils， lymphocytes and monocytes） on the 7th day after irradiation were analyzed. The 16S rRNA high-throughput sequencing was used to analyze the structure of gut microbiota in mice feces on the 7th day after irradiation， then its correlation with WBC was analyzed. RESULTS The counts of WBC on the 1st， 4th， 7th and 10th day after irradiation， platelet count on the 10th day after irradiation and RBC count on the 1st day after irradiation in the amifostine group were significantly higher than those in model group （P＜0.05）. Compared with normal control group，β diversity of gut microbiome showed significant change， relative abundance of Firmicutes increased and that of Bacteroidetes decreased in model group. Amifostine could reverse the change in β diversity of gut microbiome， and the relative abundance of Bacteroidetes and Firmicutes. The model group consisted of four distinct species， namely Allobaculum， Erysipelotrichia， Erysipelotrichales and Erysipelotrichaceae， which were significantly negatively correlated with the proportion of peripheral blood lymphocytes （P＜0.01）； amifostine group consisted of two distinct species， namely Lactobacillus murinus and L. crispatus， which were significantly negatively correlated with the proportion of neutrophils （P＜0.05）. CONCLUSIONS Amifostine significantly improves irradiation-induced injury by regulating dysbiosis of LY201816） gut microbiota.

This study design of specific identification primers for the ITS2 sequence of F. ussuriensis. The reaction system and conditions were optimized, and PCR-nucleic acid test strips were constructed to realize the visual detection of F. ussuriensis Bark. Through molecular cloning and sequencing technology, we constructed a positive control for F. ussuriensis DNA and formulated quality standards. The established method was evaluated for sensitivity, specificity and reproducibility, and the authenticity of the commercially available samples was identified. Results demonstrated that based on the ITS2 sequences, F. ussuriensis and its mixed forgeries could be distinguished. The PCR products of the authentic F. ussuriensis on test strips showed two bands in the T and C lines, while the pseudo products and negative control showed only one band in the C line, which was consistent with the results of agarose gel electrophoresis. The specificity was 100%, and the sensitivity of the PCR-nucleic acid test strip was up to 0.1 ng·μL^-1, which was 10 times higher than that of the gel electrophoresis assay. 11 out of 16 commercially available samples of F. ussuriensis were qualified, and 5 were unqualified. Collectively, the PCR-nucleic acid test strip method established in this study is specific, rapid, accurate and visualized, which can provide a new technical idea for the detection of F. ussuriensis.

In recent years, artificial intelligence (AI) technology has advanced rapidly and has been widely applied in various fields such as medicine and pharmacy, accelerating the drug development process. Focusing on the application of AI in the discovery and optimization of lead compounds, this review provides a detailed introduction to AI-assisted virtual screening and molecular generation methods for discovering lead compounds, while particularly highlighting the cases of AI-drived drugs into clinical trials. Additionally, we briefly outline the application of AI basic algorithm models in quantitative structure-activity relationship (QSAR) and drug repurposing, offering insights for AI-based drug discovery.

Evaluate the interventional effect of Lycium barbarum leaves extract on cataract rats and its effects on plasma and liver tissue metabolites. The ultimate goal is to explore the scientific connotation of Lycium barbarum leaves extract on vision improvement. All experiments were approved by the experimental animal ethics committee from Nanjing University of Chinese Medicine (202306A067). D-Galactose (D-gal) induced cataract model in rats was established. The lens opacity, lens and liver tissue pathology, level of oxidative stress and polyol metabolism regulation in the lens, level of oxidative stress in serum and liver tissue, and the content of inflammatory cytokines such as tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6) in serum and liver tissue were analysed to evaluate the effect of Lycium barbarum leaves extract on cataract. The metabolite profiles of plasma and liver tissue of rats were analyzed by UPLC-QTOF-MS/MS. Principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) were used to compare and analyze the metabolic data in control group and cataract group, and screen potential biomarkers. The related metabolic pathways were further constructed by KEGG database analysis. The results showed that lens and liver pathology of cataract rats were improved after being intervened by the leaves extract of Lycium barbarum. The contents of AR and Ca²⁺ were significantly decreased in lens, and the contents of SDH and GSH and the ability of CAT were significantly increased; the content of GSH and the ability of SOD were significantly improved in serum and liver tissue, the content of MDA, the abilities of ALT and AST and the level of inflammatory factors were significantly reduced. The metabolomics results showed that there were 15 different metabolites in plasma and liver tissue of cataract rats, and 9 different biomarkers including retinyl ester, stearic acid, and palmitic acid, were returned by Lycium barbarum leaves extract. As revealed by pathway enrichment in plasma and liver tissue, it was found that the retinol metabolic pathway was mainly regulated by Lycium barbarum leaves extract. In summary, Lycium barbarum leaves can effectively alleviate the pathological changes of cataract, inhibit inflammation and improve antioxidant capacity, which may relate to the retinol metabolic pathway. It provides scientific basis and support for revealing the scientific connotation of the effect of Lycium barbarum leaves on vision improvement.

A precursor ion selection (PIS) based ultra high performance liquid chromatography-quadrupole time of flight mass spectrometry (UHPLC-Q-TOF-MS) analytical method was used to screen the chemical components in Jiawei Dingzhi pills (JWDZP) comprehensively and rapidly. To compile the components of the compound medicine, a total of 1 921 components were found utilizing online databases and literature. After verifying the sources, unifying the component names, merging the multi-flavor attributed components, and removing the weak polar molecules, 450 components were successfully retained. The Acquity UPLC HSS T3 column (100 mm × 2.1 mm, 1.8 μm) was used, with a 0.1% formic acid water (A)-acetonitrile (B) as the mobile phase. The flow rate was 0.35 mL·min^-1, the column temperature was 35 ℃, and an electrospray ion source was used. Data was collected with the PIS strategy in both positive and negative ion modes. Compounds were screened through matching accurate molecular weight of the database, and identified according to MS/MS data (characteristic fragment ions and neutral loss), with comparison of reference. Some compounds were confirmed using standard products. A total of 176 compounds were screened out in the extract of JWDZP, among which 26 compounds were confirmed by standard products. These compounds include 96 components from the sovereign drug, and 34 coefflux components with low ion intensity. The PIS-UHPLC-Q-TOF-MS/MS method established in this study can quickly and comprehensively screen the chemical components of JWDZP, which enhanced the screening rate of components with co-elution compounds of low ion intensities and provided a basis for the study of the material foundation of JWDZP.

The purpose of this study was to investigate the intervention effect and mechanism of Lycium barbarum leaves on letrozole-induced polycystic ovary syndrome (PCOS) mice. The PCOS model was prepared by letrozole combined with high-fat diet. After successful modeling, 40 mice were randomly divided into PCOS group, positive drug metformin group, low-dose Lycium barbarum leaves group, and high-dose Lycium barbarum leaves group. The corresponding drugs were given by gavage for 29 days. At the end of the experiment, the eyeballs were removed for blood collection and ovarian tissue was collected. The ovarian mass, fasting blood glucose (FBG), fasting insulin (FINS), testosterone (T), anti-Mullerian hormone (AMH), luteinizing hormone (LH), follicle stimulating hormone (FSH), and estradiol (E₂) levels were measured in each group. The morphology of ovarian tissue was observed by hematoxylin-eosin staining, and the oocytes, cystic follicles and corpus luteum were counted. Cecal contents of mice were collected for analysis of intestinal flora composition and differential flora. The animal experiment process was approved by the Animal Ethics Committee of Nanjing University of Traditional Chinese Medicine. The results showed that the estrous cycle of PCOS mice was disordered. Compared with the PCOS group, the Lycium barbarum leaves group can significantly reduce the ovarian damage of mice, reduce the number of cystic dilated follicles, and normalize the estrous cycle. After the intervention of Lycium barbarum leaves, the levels of FBG, FINS, T, AMH, LH, FSH and LH/FSH were significantly decreased (P < 0.05), while the level of E₂ was significantly increased (P < 0.001). In addition, Lycium barbarum leaves can regulate the disorder of intestinal flora diversity in PCOS mice, increase the abundance of Bacteroidetes, and reduce the abundance of Firmicutes, Ileibacterium, Romboutsia and Faecalibaculum. In summary, Lycium barbarum leaves can play a therapeutic role in PCOS mice by improving insulin resistance, regulating reproductive hormone disorders and gut microbiota imbalance. It provides scientific basis and useful reference for the rational utilization and development of Lycium barbarum leaves.