Metabonomics and proteomics were employed to investigate the mechanism of Yuzhi Zhixue Granules in treating polycystic ovary syndrome with insulin resistance(PCOS-IR). The disease model was established by feeding a high-fat diet and gavage of letrozole solution and it was then treated with different doses of Yuzhi Zhixue Granules. The therapeutic effect of Yuzhi Zhixue Granules was evaluated based on the body mass, homeostasis model assessment of insulin resistance and insulin sensitivity index, serum levels of adipokines, and histopathological changes of rats. Metabolomics and proteomics were employed to find the action pathways of Yuzhi Zhixue Granules. The results showed that Yuzhi Zhixue Granules reduced the body mass, improved the insulin sensitivity and aromatase activity, improved the levels of leptin, adiponectin and other adipokines, and alleviated insulin resistance, histopathological changes, and metabolic disorders in PCOS-IR rats. Metabolomics results revealed 14 metabolites with altered levels in the ovarian tissue, which were closely related to glutathione metabolism and pyruvate metabolism. Proteomics results showed that the therapeutic effect of Yuzhi Zhixue Granules was mainly related to the adipokine, adenosine 5'-monophosphate(AMP)-activated protein kinase(AMPK), phosphatidylinositol 3-kinase/protein kinase B(PI3K/Akt), forkhead box protein O(FoxO), and mechanistic target of rapamycin(mTOR) signaling pathways. Western blot results showed that compared with the model group, Yuzhi Zhixue Granules treatment decreased the p-AMPK/AMPK and p-FoxO1/FoxO1 levels, increased the p-mTOR/mTOR level, and up-regulated the expression level of recombinant glucose transporter 4(GLUT4). Yuzhi Zhixue Granules can balance amino acid metabolism and pyruvate metabolism by regulating the AMPK/mTOR/FoxO/GLUT pathway to maintain the homeostasis of the ovarian environment and alleviate insulin resistance, thus treating PCOS-IR.
Animals ; Female ; Insulin Resistance ; Polycystic Ovary Syndrome/genetics* ; Drugs, Chinese Herbal/administration & dosage* ; Rats ; Metabolomics ; Proteomics ; Rats, Sprague-Dawley ; Humans ; Ovary/metabolism* ; Signal Transduction/drug effects*

PURPOSE: Intertrochanteric fracture (ITF) classification is crucial for surgical decision-making. However, orthopedic trauma surgeons have shown lower accuracy in ITF classification than expected. The objective of this study was to utilize an artificial intelligence (AI) method to improve the accuracy of ITF classification. METHODS: We trained a network called YOLOX-SwinT, which is based on the You Only Look Once X (YOLOX) object detection network with Swin Transformer (SwinT) as the backbone architecture, using 762 radiographic ITF examinations as the training set. Subsequently, we recruited 5 senior orthopedic trauma surgeons (SOTS) and 5 junior orthopedic trauma surgeons (JOTS) to classify the 85 original images in the test set, as well as the images with the prediction results of the network model in sequence. Statistical analysis was performed using the SPSS 20.0 (IBM Corp., Armonk, NY, USA) to compare the differences among the SOTS, JOTS, SOTS + AI, JOTS + AI, SOTS + JOTS, and SOTS + JOTS + AI groups. All images were classified according to the AO/OTA 2018 classification system by 2 experienced trauma surgeons and verified by another expert in this field. Based on the actual clinical needs, after discussion, we integrated 8 subgroups into 5 new subgroups, and the dataset was divided into training, validation, and test sets by the ratio of 8:1:1. RESULTS: The mean average precision at the intersection over union (IoU) of 0.5 (mAP50) for subgroup detection reached 90.29%. The classification accuracy values of SOTS, JOTS, SOTS + AI, and JOTS + AI groups were 56.24% ± 4.02%, 35.29% ± 18.07%, 79.53% ± 7.14%, and 71.53% ± 5.22%, respectively. The paired t-test results showed that the difference between the SOTS and SOTS + AI groups was statistically significant, as well as the difference between the JOTS and JOTS + AI groups, and the SOTS + JOTS and SOTS + JOTS + AI groups. Moreover, the difference between the SOTS + JOTS and SOTS + JOTS + AI groups in each subgroup was statistically significant, with all p < 0.05. The independent samples t-test results showed that the difference between the SOTS and JOTS groups was statistically significant, while the difference between the SOTS + AI and JOTS + AI groups was not statistically significant. With the assistance of AI, the subgroup classification accuracy of both SOTS and JOTS was significantly improved, and JOTS achieved the same level as SOTS. CONCLUSION In conclusion, the YOLOX-SwinT network algorithm enhances the accuracy of AO/OTA subgroups classification of ITF by orthopedic trauma surgeons.
Humans ; Hip Fractures/diagnostic imaging* ; Orthopedic Surgeons ; Algorithms ; Artificial Intelligence

OBJECTIVES: To explore the mediating role of sleep duration in the relationship between depression symptoms and myopia among middle school students. METHODS: This study was a cross-sectional research conducted using a stratified cluster random sampling method. A total of 1 728 middle school students were selected from two junior high schools and two senior high schools in certain urban areas and farms of the Xinjiang Production and Construction Corps. Questionnaire surveys and vision tests were conducted among the students. Spearman analysis was used to analyze the correlation between depression symptoms, sleep duration, and myopia. The Bootstrap method was employed to investigate the mediating effect of sleep duration between depression symptoms and myopia. RESULTS: The prevalence of myopia in the overall population was 74.02% (1 279/1 728), with an average sleep duration of (7.6±1.0) hours. The rate of insufficient sleep was 83.62% (1 445/1 728), and the proportion of students exhibiting depression symptoms was 25.29% (437/1 728). Correlation analysis showed significant negative correlations between visual acuity in both eyes and sleep duration with depressive emotions as measured by the Center for Epidemiologic Studies Depression Scale (with correlation coefficients of -0.064, -0.084, and -0.199 respectively; P<0.01), as well as with somatic symptoms and activities (with correlation coefficients of -0.104, -0.124, and -0.233 respectively; P<0.01) and interpersonal relationships (with correlation coefficients of -0.052, -0.059, and -0.071 respectively; P<0.05). The correlation coefficients for left and right eye visual acuity and sleep duration were 0.206 and 0.211 respectively (P<0.001). Sleep duration exhibited a mediating effect between depression symptoms and myopia (indirect effect=0.056, 95%CI: 0.029-0.088), with the mediating effect value for females (indirect effect=0.066, 95%CI: 0.024-0.119) being higher than that for males (indirect effect=0.042, 95%CI: 0.011-0.081). CONCLUSIONS Sleep duration serves as a partial mediator between depression symptoms and myopia in middle school students.
Humans ; Myopia/etiology* ; Male ; Female ; Depression/physiopathology* ; Cross-Sectional Studies ; Sleep ; Adolescent ; Students ; Child ; Time Factors ; Sleep Duration

[This corrects the article DOI: 10.11909/j.issn.1671-5411.2017.08.005.].

Accurate prediction of drug-induced adverse drug reactions (ADRs) is crucial for drug safety evaluation, as it directly impacts public health and safety. While various models have shown promising results in predicting ADRs, their accuracy still needs improvement. Additionally, many existing models often lack interpretability when linking molecular structures to specific ADRs and frequently rely on manually selected molecular fingerprints, which can introduce bias. To address these challenges, we propose ToxBERT, an efficient transformer encoder model that leverages attention and masking mechanisms for simplified molecular input line entry system (SMILES) representations. Our results demonstrate that ToxBERT achieved area under the receiver operating characteristic curve (AUROC) scores of 0.839, 0.759, and 0.664 for predicting drug-induced QT prolongation (DIQT), rhabdomyolysis, and liver injury, respectively, outperforming previous studies. Furthermore, ToxBERT can identify drug substructures that are closely associated with specific ADRs. These findings indicate that ToxBERT is not only a valuable tool for understanding the mechanisms underlying specific drug-induced ADRs but also for mitigating potential ADRs in the drug discovery pipeline.

OBJECTIVE To study the mechanisms and effect of sufentanil(SUF)on protection of sepsis-induced myocardial injury.METHODS The in vitro experimental models of sepsis-induced myocardial injury were estab-lished by using lipopolysaccharide(LPS).The myocardial H9C2 cells were divided into the Control group,the LPS group,the SUF-L group,the SUF-M group,the SUF-H group,the SUF-H-ComC group and the SUF-H-ML385 group;the LPS group,the SUF-L group,the SUF-M group,the SUF-H group,the SUF-H-ComC group and the SUF-H-ML385 group were the experimental groups.The cells from the experimental groups were respec-tively inoculated and incubated in culture media containing 25 mg/L of LPS,and the culture media were respec-tively added SUF with the terminal dose of 0,5,10,20,20 and 20 μmol/L;the culture media of the SUF-H-ComC was added ComC with the terminal dose of 10 μmol/L,and the culture media of the SUF-H-ML385 was added ML385 with the terminal dose of 5 μmol/L.The cells from the Control group were incubated in normal cul-ture media.The same amount of culture media and CCK-8 reagent without containing myocardial H9C2 cells were assigned as the blank group.The cell viability was determined by CCK-8 method,the levels of reactive oxygen species(ROS),malondialdehyde(MDA),lactate dehydrogenase(LDH),superoxide dismutase(SOD)and gluta-thione peroxidase(GSH-Px)were detected.The Fe2+level of the cells was detected by iron ion colorimetric meth-od.The levels of interleukin(IL)-1β,IL-6 and tumor necrosis factor-α(TNF-α)in supernatant fluid of the culture media were detected with the use of enzyme-linked immunosorbent assay.The expression levels of adenosine 5'-monophosphate-activated protein kinas(AMPK),phosphorylated-AMPK(p-AMPK),nuclear factor erythroid 2-related factor 2(Nrf2)and heme oxygenase-1(HO-1)were detected by means of Western Blot.RESULTS The cell viability of the LPS group was lower than that of the Control group;the levels of ROS,MDA,LDH,Fe2+,IL-1β,IL-6 and TNF-α of the LPS group were higher than those of the Control group;the levels of SOD and GSH-Px of the LPS group were lower than those of the Control group;the expression levels of p-AMPK/AMPK,Nrf2 and HO-1 proteins of the LPS group were lower than those of the Control group(P＜0.05).As compared with the LPS group,the cell viability of the SUF-L group,the SUF-M group and the SUF-H group was succes-sively increased,the levels of ROS,MDA,LDH,Fe2+,IL-1β,IL-6 and TNF-α were successively reduced,the levels of SOD and GSH-Px were successively elevated,and the expression levels of p-AMPK/AMPK,Nrf2 and HO-1 proteins were successively increased(P＜0.05).AMPK pathway inhibitor and Nrf2 pathway inhibitor could reverse the viability of SUF-affecting LPS-induced myocardial H9C2 cells,levels of ROS,MDA,LDH,Fe2+,SOD,GSH-Px,IL-1β,IL-6 and TNF-α and downregulated the expression levels of p-AMPK/AMPK,Nrf2 and HO-1 proteins(P＜0.05).CONCLUSION SUF can improve the sepsis-induced myocardial injury,and the mecha-nism may be associated with activation of AMPK/Nrf2/HO-1 signaling pathways,inhibition of ferroptosis,oxi-dative stress injury and inflammatory reactions.

ObjectivePhotoacoustic pump-probe imaging can effectively eliminate the interference of blood background signal in traditional photoacoustic imaging, and realize the imaging of weak phosphorescence molecules and their triplet lifetimes in deep tissues. However, background differential noise in photoacoustic pump-probe imaging often leads to large fitting results of phosphorescent molecule concentration and triplet lifetime. Therefore, this paper proposes a novel triplet lifetime fitting method for photoacoustic pump-probe imaging. By extracting the phase of the triplet differential signal and the background noise, the fitting bias caused by the background noise can be effectively corrected. MethodsThe advantages and feasibility of the proposed algorithm are verified by numerical simulation, phantom and in vivo experiments, respectively. ResultsIn the numerical simulation, under the condition of noise intensity being 10% of the signal amplitude, the new method can optimize the fitting deviation from 48.5% to about 5%, and has a higher exclusion coefficient (0.88>0.79), which greatly improves the fitting accuracy. The high specificity imaging ability of photoacoustic pump imaging for phosphorescent molecules has been demonstrated by phantom experiments. In vivo experiments have verified the feasibility of the new fitting method proposed in this paper for fitting phosphoometric lifetime to monitor oxygen partial pressure content during photodynamic therapy of tumors in nude mice. ConclusionThis work will play an important role in promoting the application of photoacoustic pump-probe imaging in biomedicine.

support the diagnosis.The treatment of PHCC is mainly based on surgery.Due to the characteristics of intact capsule,surgical resection is relatively easy and the cure rate is higher than that of ordinary hepatocellular carcinoma,and the postoperative survival rate is relatively ideal.For unresectable PHCC,palliative treatment based on transcatheter arterial chemoembolization can be used.This article reviews the progress on diagnosis and treatment of PHCC in order to provide reference for clinical practice.

Accurate prediction of drug-induced adverse drug reactions(ADRs)is crucial for drug safety evaluation,as it directly impacts public health and safety.While various models have shown promising results in predicting ADRs,their accuracy still needs improvement.Additionally,many existing models often lack interpretability when linking molecular structures to specific ADRs and frequently rely on manually selected molecular fingerprints,which can introduce bias.To address these challenges,we propose ToxBERT,an efficient transformer encoder model that leverages attention and masking mechanisms for simplified molecular input line entry system(SMILES)representations.Our results demonstrate that ToxBERT achieved area under the receiver operating characteristic curve(AUROC)scores of 0.839,0.759,and 0.664 for predicting drug-induced QT prolongation(DIQT),rhabdomyolysis,and liver injury,respectively,outperforming previous studies.Furthermore,ToxBERT can identify drug substructures that are closely associated with specific ADRs.These findings indicate that ToxBERT is not only a valuable tool for understanding the mechanisms underlying specific drug-induced ADRs but also for mitigating potential ADRs in the drug discovery pipeline.