The chemical constituents in dried roots of Atractylodes macrocephala were investigated in this study. Through utilizing normal-phase silica gel and ODS column chromatography, TLC, and semi-preparative HPLC, 4 new sesquiterpenoids were purified from the ethyl acetate extract of A. macrocephala. By various spectroscopic techniques, such as 1D and 2D NMR, HR-ESI-MS, IR, UV, and CD, their structures were identified as atractylmacron A (1), 9β-hydroxyasterolide (2), atractylenolide H (3), atractylenolide J (4). Compound 1 possesses a rare 6/7 bicyclic skeleton.

Objective To construct a "disease-syndrome combination" mathematical representation model for pulmonary nodules based on oral microbiome data, utilizing a multimodal data algorithm framework centered on dynamic systems theory. Furthermore, to compare predictive models under various algorithmic frameworks and validate the efficacy of the optimal model in predicting the presence of pulmonary nodules. Methods A total of 213 subjects were prospectively enrolled from July 2022 to March 2023 at the Hospital of Chengdu University of Traditional Chinese Medicine, Sichuan Cancer Hospital, and the Chengdu Integrated Traditional Chinese and Western Medicine Hospital. This cohort included 173 patients with pulmonary nodules and 40 healthy subjects. A novel multimodal data algorithm framework centered on dynamic systems theory, termed VAEGANTF (Variational Auto Encoder-Generative Adversarial Network-Transformer), was proposed. Subsequently, based on a multi-dimensional integrated dataset of “clinical features-syndrome elements-microorganisms”, all subjects were divided into training (70%) and testing (30%) sets for model construction and efficacy testing, respectively. Using pulmonary nodules as dependent variables, and combining candidate markers such as clinical features, lesion location, disease nature, and microbial genera, the independent variables were screened based on variable importance ranking after identifying and addressing multicollinearity. Missing values were then imputed, and data were standardized. Eight machine learning algorithms were then employed to construct pulmonary nodule risk prediction models: random forest, least absolute shrinkage and selection operator (LASSO) regression, support vector machine, multilayer perceptron, eXtreme Gradient Boosting (XGBoost), VAE-ViT (Vision Transformer), GAN-ViT, and VAEGANTF. K-fold cross-validation was used for model parameter tuning and optimization. The efficacy of the eight predictive models was evaluated using confusion matrices and receiver operating characteristic (ROC) curves, and the optimal model was selected. Finally, goodness-of-fit testing and decision curve analysis (DCA) were performed to evaluate the optimal model. Results There were no statistically significant differences between the two groups in demographic characteristics such as age and sex. The 213 subjects were randomly divided into training and testing sets (7 : 3), and prediction models were constructed using the eight machine learning algorithms. After excluding potential problems such as multicollinearity, a total of 301 clinical feature information, syndrome elements, and microbial genera markers were included for model construction. The area under the curve (AUC) values of the random forest, LASSO regression, support vector machine, multilayer perceptron, and VAE-ViT models did not reach 0.85, indicating poor efficacy. The AUC values of the XGBoost, GAN-ViT, and VAEGANTF models all reached above 0.85, with the VAEGANTF model exhibiting the highest AUC value (AUC=0.923). Goodness-of-fit testing indicated good calibration ability of the VAEGANTF model, and decision curve analysis showed a high degree of clinical benefit. The nomogram results showed that age, sex, heart, lung, Qixu, blood stasis, dampness, Porphyromonas genus, Granulicatella genus, Neisseria genus, Haemophilus genus, and Actinobacillus genus could be used as predictors. Conclusion The “disease-syndrome combination” risk prediction model for pulmonary nodules based on the VAEGANTF algorithm framework, which incorporates multi-dimensional data features of “clinical features-syndrome elements-microorganisms”, demonstrates better performance compared to other machine learning algorithms and has certain reference value for early non-invasive diagnosis of pulmonary nodules.

Objective: To investigate the potential protective effect of Shexiang Tongxin dropping pills (STDP) on ischemia-reperfusion injury and its underlying mechanisms in improving endothelial cell function in coronary microvascular disease (CMVD). Methods: A rat model of myocardial ischemia-reperfusion injury with CMVD was established using ligation and reperfusion of the left anterior descending artery. The effect of STDP (21.6 mg/kg) on cardiac function was evaluated using echocardiography, hematoxylin-eosin staining, and Evans blue staining. The effects of STDP on the microvascular endothelial barrier were assessed based on nitric oxide production, endothelial nitric oxide synthase expression, structural variety of tight junctions (TJs), and the expression of zonula occludens-1 (ZO-1), claudin-5, occludin, and vascular endothelial (VE)-cadherin proteins. The mechanisms of STDP (50 and 100 ng/mL) were evaluated by examining the expression of sphingosine 1-phosphate receptor 2 (S1PR2), Ras Homolog family member A (RhoA), and Rho-associated coiled-coil-containing protein kinase (ROCK) proteins and the distribution of ZO-1, VE-cadherin, and F-actin proteins in an oxygen and glucose deprivation/reoxygenation model. Results: The administration of STDP on CMVD rat model significantly improved cardiac and microvascular endothelial cell barrier functions (all P < .05). STDP enhanced the structural integrity of coronary microvascular positioning and distribution by clarifying and completing TJs and increasing the expression of ZO-1, occludin, claudin-5, and VE-cadherin in vivo (all P < .05). The S1PR2/RhoA/ROCK pathway was inhibited by STDP in vitro, leading to the regulation of endothelial cell TJs, adhesion junctions, and cytoskeletal morphology. Conclusion STDP showed protective effects on cardiac impairment and microvascular endothelial barrier injury in CMVD model rats induced by myocardial ischemia-reperfusion injury through the modulation of the S1PR2/RhoA/ROCK pathway.

OBJECTIVE: To screen anti-tumor drugs that improve antigen processing and presentation in acute myeloid leukemia (AML) cells. METHODS: A TCR-like or TCR mimic antibody that can specifically recognize HLA-A*0201:WT1_126-134 ( RMFPNAPYL) complex (hereafter referred to as HLA-A2:WT1) was synthesized to evaluate the function of antigen processing and presentation machinery (APM) in AML cells. AML cell line THP1 was incubated with increasing concentrations of IFN-γ, hypomethylating agents (HMA), immunomodulatory drugs (IMiD), proteasome inhibitors (PI) and γ-secretase inhibitors (GSI), followed by measuring of HLA-ABC, HLA-A2 and HLA-A2:WT1 levels by flow cytometry at consecutive time points. RESULTS: The TCR-like antibody we generated only binds to HLA-A*0201⁺WT1⁺ cells, indicating the specificity of the antibody. HLA-A2:WT1 level of THP-1 cells detected with the TCR-like antibody was increased significantly after co-incubation with IFN-γ, showing that the HLA-A2:WT1 TCR like antibody could evaluate the function of APM. Among the anti-tumor agents screened in this study, GSI (LY-411575) and HMA (decitabine and azacitidine) could significantly increase the HLA-A2:WT1 level. The IMiD lenalidomide and pomalidomide could aslo upregulate the expression of HLA-A2:WT1 complex under certain concentrations of the drugs and incubation time. As proteasome inhibitors, carfilzomib could significantly decreased the expression of HLA-A2:WT1, while bortezomib had no significant effect on HLA-A2:WT1 expression. CONCLUSION HLA-A2:WT1 TCR-like antibody can effectively reflect the APM function. Some of the anti-tumor drugs can affect the APM function and immunogenicity of tumor cells.
Humans ; Leukemia, Myeloid, Acute/immunology* ; Antineoplastic Agents/pharmacology* ; Antigen Presentation/drug effects* ; HLA-A2 Antigen/immunology* ; Receptors, Antigen, T-Cell/immunology* ; Cell Line, Tumor ; Interferon-gamma

OBJECTIVE: To elucidate how spinal manipulative therapy (SMT) exerts its analgesic effects through regulating brain function in lumbar disc herniation (LDH) patients by utilizing resting-state functional magnetic resonance imaging (rs-fMRI). METHODS: From September 2021 to September 2023, we enrolled LDH patients (LDH group, n=31) and age- and sex-matched healthy controls (HCs, n=28). LDH group underwent rs-fMRI at 2 distinct time points (TPs): prior to the initiation of SMT (TP1) and subsequent to the completion of the SMT sessions (TP2). SMT was administered once every other day for 30 min per session, totally 14 treatment sessions over a span of 4 weeks. HCs did not receive SMT treatment and underwent only one fMRI scan. Additionally, participants in LDH group completed clinical questionnaires on pain using the Visual Analog Scale (VAS) and the Japanese Orthopedic Association (JOA) score, whereas HCs did not undergo clinical scale assessments. The effects on the brain were jointly characterized using the amplitude of low-frequency fluctuations (ALFF) and regional homogeneity (ReHo). Correlation analyses were conducted between specific brain regions and clinical scales. RESULTS: Following SMT treatment, pain symptoms in LDH patients were notably alleviated and accompanied by evident activation of effects in the brain. In comparison to TP1, TP2 exhibited the most significant increase in ALFF values for Temporal_Sup_R and the most notable decrease in ALFF values for Paracentral_Lobule_L (voxelwise P<0.005; clusters >30; FDR correction). Additionally, the most substantial enhancement in ReHo values was observed for the Cuneus_R, while the most prominent reduction was noted for the Olfactory_R (voxelwise P<0.005; clusters >30; FDR correction). Moreover, a comparative analysis revealed that, in contrast to HCs, LDH patients at TP1 exhibited the most significant increase in ALFF values for Temporal_Pole_Sup_L and the most notable decrease in ALFF values for Frontal_Mid_L (voxelwise P<0.005; clusters >30; FDR correction). Furthermore, the most significant enhancement in ReHo values was observed for Postcentral_L, while the most prominent reduction was identified for ParaHippocampal_L (voxelwise P<0.005; clusters >30; FDR correction). Notably, correlation analysis with clinical scales revealed a robust positive correlation between the Cuneus_R score and the rate of change in the VAS score (r=0.9333, P<0.0001). CONCLUSIONS Long-term chronic lower back pain in patients with LDH manifests significant activation of the "AUN-DMN-S1-SAN" neural circuitry. The visual network, represented by the Cuneus_R, is highly likely to be a key brain network in which the analgesic efficacy of SMT becomes effective in treating LDH patients. (Trial registration No. NCT06277739).
Humans ; Magnetic Resonance Imaging ; Intervertebral Disc Displacement/diagnostic imaging* ; Male ; Female ; Brain/diagnostic imaging* ; Adult ; Manipulation, Spinal/methods* ; Middle Aged ; Lumbar Vertebrae/physiopathology* ; Pain Management ; Rest ; Case-Control Studies

Objective To study the effect of berberine on the damage of renal tubular epithelial cells(RETC)in diabetic in vitro.Methods RTEC were divided into control group,model group(high glucose),low dose experimental group(2 mg·L-1 berberine and high glucose),medium dose experimental group(4 mg·L-1 berberine and high glucose),high dose experimental group(8 mg·L-1 berberine and high glucose),BBM-H+miR-NC(transfected with mimics control group,8 mg·L-1 berberine and high glucose),BBM-H+miR-135b group(transfected with miR-135b mimics,8 mg·L-1 berberine and high glucose).Methyl thiazolyl tetrazolium(MTT)method was used to detect cell proliferation activity,flow cytometry was used to detect cell apoptosis rate,Western blot was used to detect the expression of B-cell lymphoma-2(Bcl-2)and Bel-associated X(Bax)proteins in cells,and reactive oxygen species(ROS)level were detected by chemical fluorescence method,thiobarbituric acid method was used to detect malondialdehyde(MDA)level,and xanthine oxidation method was used to detect superoxide dismutase(SOD)level,the levels of tumor necrosis factor-α(TNF-α),interleukin-8(IL-8)and interleukin-1β(IL-1 β)were detected by enzyme-linked immunosorbent assay(ELISA).Results The proliferative activity(OD value)of RTEC in control group,model group and low,medium,high dose experimental groups were 0.66±0.04,0.36±0.02,0.43±0.03,0.54±0.03,0.63±0.05;the apoptosis rates were(3.62±0.31)％,(29.41±2.33)％,(20.10±1.65)％,(15.02±1.25)％,(9.58±1.43)％;MDA were(1.04±0.12),(5.24±0.29),(3.45±0.22),(2.16±0.13),(1.60±0.11)nmol·mL-1;SOD were(240.22±12.06),(130.56±10.84),(169.62±12.50),(201.97±12.78),(236.74±14.52)U·mL-1;TNF-α were(31.25±2.51),(51.84±4.20),(44.52±2.61),(38.25±1.50),(32.10±1.78)mg·L-1;IL-8 were(10.59±1.14),(19.95±1.74),(16.10±1.03),(13.52±1.25),(11.17±0.92)mg·L-1;IL-1β were(23.01±1.45),(56.92±2.51),(43.20±1.96),(32.05±1.23),(26.37±2.48)mg·L-1.There were statistically significant differences between model group and control group(all P＜0.05).Compared with the model group,the above indexes in low,medium and high dose experimental group were statistically significant(all P＜0.05).The above indexes of BBM-H+miR-NC group were statistically significant compared with those of BBM-H+miR-135b group(all P＜0.05).Conclusion Berberine can reduce diabetic renal tubular epithelial cell damage by down-regulating miR-135b.

Due to the unique characteristics and complexity of administration of orally inhaled drug products,bioequivalence trial for orally inhaled generic drugs presents greater challenges in clinical implementation compared to conventional oral administration.This difficulty is particularly evident inmainly attributed to the variability during the self-administration inhalation of inhaled drugss by subjects.Therefore,effective management of subjects is crucial in clinical trials involving orally inhaled products.This paper,based on the experience in conducting bioequivalence trials for orally inhaled drug products,discusses key factors and measures for successful subject management in clinical trials.The aim is to enhance the clinical implementation capabilities of researchers in the evaluation of generic consistency for inhaled drug products and to ensure the quality of clinical trials.

Objective To explore the effects of dydrogesterone combined with granulocyte colony-stimulating factor(G-CSF)on blood flow parameters and sex hormone levels in patients with thin endometrial(TE)infertility.Methods TE infertility patients were randomly divided into control group and treatment group.All patients were treated with freezing-thawing embryo transfer.The control group was treated with desdrogesterone after ovulation monitoring by vaginal ultrasound,10 mg each time,bid,and stopped until the 14th day after ovulation.In treatment group,G-CSF was given on the basis of control group,and the endometrial thickness and hemodynamic parameters were monitored by vaginal ultrasound 3 days later,and then embryo transfer was performed.Blood flow parameters,ultrasound parameters,endometrial morphology,sex hormone levels[follicle stimulating hormone(FSH),luteinizing hormone(LH),estradiol(E2),progesterone(P)]and pregnancy status were compared between the two groups.Results There were 49 cases in treatment group and 49 cases in control group.After treatment,endometrial thickness in treatment group and control group were(9.59±1.35)and(7.89±1.14)mm;follicle diameter were(19.35±1.58)and(17.75±1.42)mm;uterine volume were(92.68±7.85)and(85.69±6.74)cm3;PI were 1.29±0.27 and 1.74±0.32;RI were 0.32±0.09 and 0.50±0.11;peak systolic/end-diastolic velocity(S/D)were 2.03±0.28 and 2.21±0.25;P were(45.98±5.75)and(39.15±5.78)nmol·L-1;E2 were(462.58±58.42)and(339.45±45.97)pg·mL-1;FSH were(12.18±2.58)and(9.42±1.42)U·L-1;LH were(29.42±4.18)and(22.25±3.40)U·L-1;there were statistically significant differences between the two groups(all P＜0.05).The clinical pregnancy rate(51.02％)and implantation rate(57.14％)in treatment group were higher than those in control group(30.61％and 36.73％),and the differences were statistically significant(all P＜0.05).Conclusion Dydrogesterone combined with G-CSF can improve blood flow parameters,endometrial thickness and sex hormone levels in TE infertility patients,and help to increase the embryo implantation rate.

Objective: To construct a prediction model for preterm birth risk among pregnant women, so as to provide the reference for screening high-risk population and preventing preterm birth. Methods: Pregnant women who received antenatal examination and delivered at the Women's Hospital, School of Medicine, Zhejiang University from January 1 to December 31, 2019 were selected as the study subjects, among them, 80% were included in the modeling group, and 20% were included in the validation group. Demographic and clinical information were collected. A multivariable logistic regression model was used to analyze the predictive factors of preterm birth risk in the modeling group, and a preterm birth risk prediction model was established based on the OR values of predictive factors. The model was validated with the data from the validation group. The Youden index was used to determine the critical score for predicting preterm birth risk. The prediction performance of the model was evaluated using the receiver operating characteristic (ROC) curve. Results: A total of 15 197 pregnant women were surveyed, including 12 131 pregnant women in the observation group and 3 066 pregnant women in the validation group. There was no statistically significant difference in age, education level and gravidity between the two groups of pregnant women (all P<0.05). Multivariable logistic regression analysis identified the number of pregnancies, education level, place of residence, hypertension, diabetes, history of preterm birth, twin-pregnancy, placenta praevia, and gestational hypertension as risk prediction factors for preterm birth risk among pregnant women. The risk score system for preterm birth was established as follows: >2 pregnancies (2 points), high school education or below (4 points), college degree or above (-4 points), rural residence (5 points), hypertension (7 points), diabetes (11 points), history of preterm birth (11 points), twin-pregnancy (28 points), placenta previa (19 points), and gestational hypertension (12 points). The total score of the preterm birth risk scoring system ranged from -4 to 99 points. When the critical score was 8 points, the Youden index was the highest at 0.480, with an area under the ROC curve of 0.749 (95%CI: 0.732-0.767), a sensitivity of 0.610, and a specificity of 0.886, indicating good prediction performance of the model. Conclusion The preterm birth risk prediction model established in this study based on demographic and clinical characteristics of pregnant women can effectively predict the risk of preterm birth among pregnant women.