ObjectiveTo decipher the mechanism by which Zuoguiwan （ZGW） treat hyperthyroidism in rats with kidney-Yin deficiency based on the dopamine receptor D4 （DRD4）/nicotinamide adenine dinucleotide phosphate （NADPH） oxidase 4 （NOX4） signaling pathway. MethodsThe rat model of kidney-Yin deficiency was induced by unilateral intramuscular injection of dexamethasone （0.35 mg·kg^-1）. After successful modeling， the rats were randomized into model， methimazole （positive control， 5 mg·kg^-1）， low-， medium-， and high-dose （1.85， 3.70， 7.40 g·kg^-1， respectively） ZGW， and normal control groups. After 21 days of continuous gavage， the behavioral indexes and body weight changes of rats were evaluated. The pathological changes of the renal tissue were observed by hematoxylin-eosin staining. The serum levels of thyroid hormones ［triiodothyronine （T₃）， thyroxine （T₄）， thyroid-stimulating hormone （TSH）］， renal function indexes ［serum creatine （Scr） and blood urea nitrogen （BUN）］， energy metabolism markers ［cyclic adenosine monophosphate （cAMP） and cyclic guanosine monophosphate （cGMP）］， and oxidative stress-related factors ［superoxide dismutase （SOD）， malondialdehyde （MDA）， and NADPH）］ were measured by enzyme-linked immunosorbent assay （ELISA）. Western blot was employed to analyze the expression of DRD4， NOX4， mitochondrial respiratory chain complex proteins ［NADH：ubiquinone oxidoreductase subunit S4 （NDUFS4） and cytochrome C oxidase subunit 4 （COX4）］， and inflammation-related protein ［tumor necrosis factor-alpha （TNF-α）， interleukin-6 （IL-6）， p38 mitogen-activated protein kinase （MAPK）］ pathway in the renal tissue. ResultsCompared with the normal group， the model group showed mental malaise， body weight decreases （P<0.01）， inflammatory cell infiltration in the renal tissue， a few residual parotid glands in the thyroid， elevations in serum levels of T₃， T₄， Scr， BUN， cAMP， cAMP/cGMP， MDA， and NADPH （P<0.01）， down-regulation in protein levels of TSH， SOD， and DRD4 （P<0.05， P<0.01）， and up-regulation in expression of NOX4， p-p38 MAPK/p38 MAPK， and inflammatory factors （P<0.01）. Compared with the model group， ZGW increased the body weight （P<0.05， P<0.01）， reduced the infiltration of renal interstitial inflammatory cells， restored the thyroid structure and follicle size， lowered the serum levels of T₃， T₄， Scr， BUN， cAMP， cAMP/cGMP， MDA and NADPH （P<0.05， P<0.01）， up-regulated the expression of TSH， SOD and DRD4 （P<0.05， P<0.01）， and down-regulated the expression of NOX4， p-p38 MAPK/p38 MAPK， and inflammatory factors （P<0.05， P<0.01）. Moreover， high-dose ZGW outperformed methimazole （P<0.05）. ConclusionBy activating DRD4， ZGW can inhibit the expression of NOX4 mediated by the p38 MAPK pathway， reduce oxidative stress and inflammatory response， thereby ameliorating the pathological state of hyperthyroidism due to kidney-Yin deficiency. This study provides new molecular mechanism support for the clinical application of ZGW.

Prescription optimization is a crucial aspect in the study of traditional Chinese medicine （TCM） compounds. In recent years， the introduction of mathematical methods， data mining techniques， and artificial neural networks has provided new tools for elucidating the compatibility rules of TCM compounds. The study of TCM compounds involves numerous variables， including the proportions of different herbs， the specific extraction parts of each ingredient， and the interactions among multiple components. These factors together create a complex nonlinear dose-effect relationship. In this context， it is essential to identify methods that suit the characteristics of TCM compounds and can leverage their advantages for effective application in new drug development. This paper provided a comprehensive review of the cutting-edge optimization experimental design methods applied in recent studies of TCM compound compatibilities. The key technical issues， such as the optimization of source material selection， dosage optimization of compatible herbs， and multi-objective optimization indicators， were discussed. Furthermore， the evaluation methods for component effects were summarized during the optimization process， so as to provide scientific and practical foundations for innovative research in TCM and the development of new drugs based on TCM compounds.

Objective To screen for key genes and important pathways common for different etiologies of acute kidney injury(AKI)by pathway-associated deep neural network and multiple machine learning algorithms.Methods AKI microarray datasets GSE30718,GSE37838,GSE53769,GSE108113,GSE125779,GSE99325,and GSE174020 downloaded from the Gene Expression Omnibus(GEO)database were merged,including 60 kidney samples from AKI patients and 79 kidney samples from healthy controls.They were divided(8∶2)into training sets and test sets,and were used to train and evaluate pathway-associated deep neural network and 4 machine learning algorithms,including least absolute shrinkage and selection operator(LASSO),random forest(RF),support vector machine-recursive feature elimination(SVM-RFE),and extreme gradient boosting(XgBoost),to screen for common key genes and pathways of different etiologies of AKI.The downloaded datasets GSE99340 and GSE1563 were merged,including 43 kidney samples from AKI patients and 36 kidney samples from healthy controls,which were used as external validation sets for LASSO model and nomogram performance test based on the final screened genes.The pathway-associated deep neural network and machine learning algorithms were evaluated using receiver operating characteristic curves,precision,recall,accuracy,and F1-score.The immune cell infiltration characteristics were explored in AKI via cell-type identification by estimating relative subsets of RNA transcripts(CIBERSORT),and Pearson correlation coefficients were used to evaluate the correlation between the final screened common key genes and immune cell infiltration levels.Results The pathway-associated deep neural network trained by 5-fold cross validation produced an area under curve(AUC)of 0.914 5±0.007 0,a precision of 0.750 0±0.044 0,a recall of 0.923 1±0.048 0,an accuracy of 0.838 7±0.016 0,and an F1-score of 0.827 6±0.020 0 in the test set,yielding a robust and highly accurate classification performance for AKI,and identified key pathways and a subset of candidate genes.The 4 machine learning algorithms all achieved high discriminative performance for AKI in the test set with AUC≥0.860,precision≥0.750,recall≥0.800,and F1-score≥0.774,and screened 7 common key genes for AKI with different etiologies,including CD86,C-X-C motif chemokine ligand 10(CXCL10),dynamin 2(DNM2),proto-oncogene FOS,transcription factor 12(TCF12),VGF nerve growth factor inducible(VGF),and A kinase anchoring protein 5(AKAP5).Based on the final screened common key genes,the LASSO model had an AUC of 0.940 4 for the test set and an AUC of 0.944 4 for the external validation,and the model showed a very high discriminatory ability for the AKI,which demonstrated the overall regulatory performance of the genes.The nomogram constructed based on the screened 7 genes demonstrated the highest classification performance with an AUC of 0.928 9,validating the outstanding contribution and overall action performance of the screened individual genes.Immune cell infiltration analysis showed that there were significant differences in B cells na?ve,mast cells activated,monocytes,macrophages M1,B cells memory,and dendritic cells activated between AKI samples and healthy control samples(all P＜0.05).Macrophages M1 and monocytes were positively correlated with CD86 and CXCL10,mast cells activated were positively correlated with FOS,and B cells na?ve were negatively correlated with CD86 and CXCL10(all P＜0.01).Mast cells activated were positively correlated with VGF and negatively correlated with CD86 and TCF12,while memory B cells were positively correlated with CD86(all P＜0.05).Conclusion Strategy combining pathway-associated deep neural network and multiple machine learning classifiers can mine high-value key genes from high-dimensional,complex and heterogeneous transcriptomic data as potential targets for therapeutic interventions in AKI.

Objective To explore the molecular mechanism of miR-16-5p promoting apoptosis and inflammatory response by targeting GPR30 expression in an in vitro ischemic stroke microglia model(BV-2).Methods An ischemic stroke cell model was established by subjecting BV-2 cells to oxygen-glucose deprivation(OGD).qRT-PCR was utilized to assess the levels of miR-16-5p and GPR30 mRNA in OGD cells.A miR-16-5p inhibitor was transfected into OGD cells to silence miR-16-5p expression,and alterations in inflammatory response and apoptosis were measured using ELISA kits and Annexin V-FITC/PI staining.Starbase was employed to predict interactions,and dual-luciferase reporter gene assays were conducted to confirm that miR-16-5p targets the 3'-untranslated region(UTR)sequence of GPR30.Changes in cellular inflammatory response and apoptosis were evaluated by knocking down miR-16-5p and/or GPR30 in OGD cells.Results miR-16-5p expression was significantly elevated(P<0.01),while GPR30 expression was notably decreased(P<0.01)in OGD-induced cells.Knockdown of miR-16-5p reduced the expression levels of inflammatory factors and the cell apoptosis ratio(P<0.01).Inhibition of miR-16-5p expression led to an upregulation of GPR30 mRNA and protein levels(P<0.01).Simultaneous silencing of both miR-16-5p and GPR30 partially enhanced inflammatory factor expression levels and the cell apoptosis ratio compared to cells transfected solely with the miR-16-5p inhibitor(P<0.05).Conclusion In the microglia OGD model,miR-16-5p triggers inflammatory responses and enhances apoptosis by inhibiting GPR30 expression.

Objective: The American Heart Association released the Life s Essential 8 (LE 8) for the overall evaluation of cardiovascular health (CVH) on individual level. The present study aimed to describe the overall CVH in Chinese school aged children using LE 8 metrics. Methods: Data of the present analysis came from a national representative multicentered cross sectional study conducted in 7 provinces of China in 2013. The original study used a multistage cluster sampling method. A total of 10 326 children aged 5 to 19 years with complete data of health behaviors and health outcomes were included in the study. Children s health behavior indicators included diet, physical activity, nicotine exposure and sleep health. Health outcome factors included body mass index, fast blood glucose, lipid profile and blood pressure. Results: The median CVH score was 73.3 ( IQR =14.4) in boys and 73.4 ( IQR = 13.5) in girls. Compared to children aged ≤9 years, the health behavior scores were lowest in the 13-15 age group, with boys scoring 7.73 lower (95% CI =-8.35--7.12, P <0.01) and girls scoring 9.15 (95% CI =-9.83--8.48, P <0.01) lower. The ≥16 age group had the lowest health outcome scores, with boys scoring 7.85 (95% CI =-9.07--6.63, P <0.01) lower and girls scoring 6.11 (95% CI =-7.12--5.09, P <0.01) lower. Conclusions Chinese school aged children are generally at a moderate level of cardiovascular health. Specific LE 8 components vary substantially between groups and therefore require targeted intervention strategies.

Objective To construct a machine learning prediction model for postoperative liver injury in patients with non-liver surgery based on preoperative and intraoperative medication indicators.Methods A case-control study was conducted on 315 patients with liver injury after non-liver surgery selected from the databases developed by 3 large general hospitals from January 2014 to September 2022.With the positive/negative ratio of 1 ∶3,928 cases in corresponding period with non-liver surgery and without liver injury were randomly matched as negative control cases.These 1243 patients were randomly divided into the modeling group(n=869)and the validation group(n=374)in a ratio of 7∶3 using the R language setting code.Preoperative clinical indicators(basic information,medical history,relevant scale score,surgical information and results of laboratory tests)and intraoperative medication were used to construct the prediction model for liver injury after non-liver surgery based on 4 machine learning algorithms,k-nearest neighbor(KNN),support vector machine linear(SVM),logic regression(LR)and extreme gradient boosting(XGBoost).In the validation group,receiver operating characteristic(ROC)curve,precision-recall curve(P-R),decision curve analysis(DCA)curve,Kappa value,sensitivity,specificity,Brier score,and F1 score were applied to evaluate the efficacy of model.Results The model established by 4 machine learning algorithms to predict postoperative liver injury after non-liver surgery was optimal using the XGBoost algorithm.The area under the receiver operating characteristic curve(AUROC)was 0.916(95%CI:0.883～0.949),area under the precision-recall curve(AUPRC)was 0.841,Brier score was 0.097,and sensitivity and specificity was 78.95%and 87.10%,respectively.Conclusion The postoperative liver injury prediction model for non-liver surgery based on the XGBoost algorithm has effective prediction for the occurrence of postoperative liver injury.

ObjectiveTo investigate the efficacy and mechanism of saffron floral bio-residues（SFB） in the treatment of hyperuricemia（HUA） combined with gouty arthritis（GA） in a compound compatibility setting. MethodScreening candidate control Chinese medicines for compound and SFB based on network target distance calculation and data analysis. After adaptive feeding of 80 SD rats for 7 days， 10 rats were randomly selected as the blank group， while the remaining 70 rats were intraperitoneally injected with 3% potassium oxonate and orally administered with 1% adenine for 14 consecutive days. On the 13^th day， rats were injected with 2.5% sodium urate solution into the right ankle joint cavity to induce swelling of the joint capsule on the opposite side， inducing a HUA combined with GA model. At the same time， the modeling rats were randomly divided into 7 groups， including the model group， benzbromarone group（positive drug， 0.02 g·kg^-1）， Tongfengshu tablets group（9 g·kg^-1）， Tongfengshu granules group（9 g·kg^-1）， SFB granules group（3.6 g·kg^-1）， Plantaginis Semen granules group（3.6 g·kg^-1）， and new formula group（SFB replacing Plantaginis Semen in Tongfengshu granules， 9 g·kg^-1）， with 10 rats in each group. Each treatment group was orally administered with the corresponding drugs according to body weight， while the control and model groups were given equal volume of distilled water by gavage once a day for 14 consecutive days. After 14 days of synchronous administration and modeling， changes in gait， ankle joint swelling and mechanical pain threshold in rats were observed， and serum uric acid， creatinine， urea nitrogen and xanthine oxidase（XOD） were measured. Enzyme-linked immunosorbent assay（ELSIA） was used to detect the levels of tumor necrosis factor（TNF）-α， interleukin（IL）-1β and IL-6 in rat serum， hematoxylin-eosin（HE） staining was used to observe the pathological changes in the liver， kidney and ankle joints of rats， Western blot was used to detect the expression levels of uric acid transporter 1（URAT1）， glucose transporter 9 （GLUT9）， organic anion transporter 1（OAT1）， adenosine triphosphate（ATP） binding cassette transporter G2（ABCG2）， and liver XOD proteins. ResultThrough network pharmacology analysis， Plantaginis Semen was selected as a candidate control herb， and Tongfengshu tablets was used as a compound compatibility environment to explore the efficacy of SFB in reducing blood uric acid levels and treating GA. Animal experiments showed that compared with the blank group， the gait score and joint swelling degree of the model group were significantly increased， and the mechanical pain threshold was significantly decreased（P<0.01）. Compared with the model group， the gait score， joint swelling degree and mechanical pain threshold of rats in each medication group were improved to varying degrees. Biochemical indicators showed that compared with the blank group， the serum uric acid， creatinine， urea nitrogen and XOD levels of the model group were significantly increased（P<0.01）. Compared with the model group， the serum uric acid and XOD levels of rats in each treatment group were significantly decreased（P<0.01）. ELISA results showed that compared with the blank group， the levels of serum TNF-α， IL-1β and IL-6 in the model group were significantly increased（P<0.01）. Compared with the model group， the levels of TNF-α， IL-1β and IL-6 in the benzbromarone group， Tongfengshu tablets group， Tongfengshu granules group and new formula group were significantly reduced（P<0.05，P<0.01）. Western blot results showed that compared with the blank group， the expression levels of URAT1 and GLUT9 proteins in renal tissue and OXD protein in liver tissue of the model group were significantly increased， while the expression levels of renal OAT1 and ABCG2 were significantly decreased（P<0.01）. Compared with the model group， the expression levels of renal URAT1 and GLUT9 in the SFB granules group， Tongfengshu granules group and new formula group were significantly decreased， while the expression levels of renal OAT1 and ABCG2 were significantly increased， and the expression of XOD protein in liver tissue was significantly decreased（P<0.05， P<0.01）. Pathological analysis showed that focal infiltration of neutrophils， cell necrosis and nuclear fragmentation were observed in the liver tissue of the model group， sodium urate deposition crystals and tubular dilation appeared in renal tissue， synovial hyperplasia and inflammatory cell infiltration appeared in ankle joint. Compared with the model group， the abnormal degrees of liver， kidney and ankle joint tissue of rats in each treatment group were alleviated. ConclusionThe new formula of SFB replacing Plantaginis Semen has the same effect in the treatment of HUA combined with GA. This study proposes a new strategy to investigate the efficacy of new resources of Chinese medicine in a compound compatibility environment， which can provide a new demonstration for the research and development of new resources of Chinese medicine.

Objective:To investigate the effects of radiation dose to the host immune system during radiotherapy on disease progression and survival in patients with peripheral early-stage non-small cell lung cancer (ES-NSCLC) receiving stereotactic body radiation therapy (SBRT).Methods:Clinical data of pathologically confirmed ES-NSCLC patients who were treated with SBRT at Tianjin Medical University Cancer Institute and Hospital between January 2007 and December 2020 were retrospectively analyzed. The prognostic significance of the estimated dose of radiation to immune cells (EDRIC) in ES-NSCLC patients undergoing SBRT was cited and validated. EDRIC was calculated using the model developed by Kong et al. and improved by Ladbury et al. Kaplan-Meier method and Cox proportional hazards regression were adopted to estimate cancer-specific survival (CSS), progression-free survival (PFS), local progression-free survival (LPFS), and distant metastasis-free survival (DMFS). Pearson's correlation was used to assess the correlation between variables. Results:The median prescription dose/fraction was 60 Gy/5 fractions (range: 48-60 Gy in 3-10 fractions). The median follow-up time was 52.17 (1.17-154.77) months. The median gross tumor volume (GTV) and EDRIC were 10.98 (0.91-120.34) cm 3 and 2.064 (0.426-6.015) Gy, respectively. Person's correlation analysis showed that GTV was positively correlated with EDRIC ( r=0.712, P<0.001). In multivariate analysis, EDRIC was an important prognostic variable of CSS and DMFS. Higher EDRIC was significantly associated with worse CSS ( HR=1.763, P=0.004) and DMFS ( HR=1.902, P=0.004). Compared to patients with EDRIC ≤ 1.56 Gy, those with EDRIC > 2.64 Gy and EDRIC between <2.06-2.64 Gy exhibited significantly lower CSS ( P<0.001, P=0.049). There were significant differences in DMFS among the groups divided by quartiles of EDRIC (compared to EDRIC ≤1.56 Gy, the P values were <0.001, 0.004, and 0.022 respectively). Conclusions:EDRIC is an important predictor of CSS and DMFS in ES-NSCLC patients treated with SBRT, suggesting that radiation dose to the immune system is a critical determinant of treatment outcomes. EDRIC can be used to quantify the effects of radiation therapy on the host immune system.

Objective:To investigate the variations in peripheral lymphocyte count (PLC) and evaluate the impact of PLC on clinical prognosis of patients with early-stage non-small cell lung cancer (NSCLC) during stereotactic body radiation therapy (SBRT).Methods:Clinical data of early-stage NSCLC patients who received SBRT at Tianjin Medical University Cancer Institute and Hospital from January 2007 to January 2021 were retrospectively analyzed. The PLC of early-stage NSCLC patients was recorded at four different time points: 1 week before SBRT, 1 week after SBRT, 1 month after SBRT, and 3 months after SBRT. Kaplan-Meier method and Cox proportional hazards regression analysis were used to estimate cancer-specific survival (CSS), progression-free survival (PFS), local progression-free survival (LPFS), and distant metastasis-free survival (DMFS) and their influencing factors. Pearson correlation analysis was used to evaluate the correlation among different variables. The optimal cut-off value of nadir-PLC is determined using the 'maxstat package' in R language.Results:Throughout the treatment process, the nadir-PLC generally occurred approximately at 1 week after SBRT, and was gradually increased thereafter, and almost restored to the level before SBRT at approximately 3 months after SBRT. The median nadir-PLC was 1.03×10 9/L, significantly lower than the baseline value of 1.90×10 9/L before treatment ( P<0.001). The nadir-PLC in patients with central NSCLC was lower compared with that of patients with peripheral NSCLC ( P=0.030). The median survival for the entire group was 91.5 months, and 89.8%, 78.6%, 93.2%, and 82.5% for the 2-year CSS, PFS, LPFS, and DMFS rates, respectively. In multivariate analysis, nadir-PLC ≥1.01×10 9/L was an important favorable prognostic factor for CSS, PFS and DMFS. Pearson correlation analysis showed that gross tumor volume (GTV) was negatively correlated with nadir-PLC ( r=-0.55, P<0.001). Conclusions:In early-stage NSCLC patients treated with SBRT, PLC will decline after treatment. The nadir-PLC is an important favorable prognostic factor for CSS, PFS and DMFS.