ObjectiveTo investigate the effect of Qingrun prescription（QRP）-containing serum on improving insulin resistance in HepG2 cells and its potential mechanisms. MethodsAn insulin resistance model was established in HepG2 cells with 1×10^-6 mol·L^-1 insulin. Branched-chain α-keto acid dehydrogenase （BCKDH） gene silencing was achieved using siRNA， and the cells were divided into 8 groups： normal group， model group （1×10^-6 mol·L^-1 insulin）， metformin group （1 mmol·L^-1 metformin）， high-， medium-， and low-dose QRP groups （20%， 10%， and 5% QRP-containing serum， respectively）， QRP + siRNA-silenced BCKDH （si-BCKDH） group （10% QRP-containing serum + si-BCKDH）， and QRP + si-NC group （10% QRP-containing serum + si-NC）. Glucose levels in the supernatant were measured with a glucose assay kit， while glycogen content was assessed using a glycogen assay kit. Levels of branched-chain amino acids （BCAAs） and branched-chain keto acids （BCKAs） were determined using ultra-high performance liquid chromatography-tandem mass spectrometry （UHPLC-MS/MS）. mRNA transcription and protein expression levels of BCKDH， dishevelled， Egl-10， and pleckstrin （DEP） domain-containing mammalian target of rapamycin （mTOR）-interacting protein （DEPTOR）， mTOR， and ribosomal protein S6 kinase 1 （S6K1） were detected using real-time quantitative polymerase chain reaction （Real-time PCR） and Western blot. ResultsCompared to the normal group， the model group exhibited significantly decreased glucose consumption and glycogen content， increased levels of BCAAs and BCKAs， downregulated expression of BCKDH and DEPTOR， and upregulated mTOR and S6K1 expression （P<0.01）. In comparison to the model group， QRP treatment at all doses significantly enhanced glucose consumption and glycogen content while reducing BCAAs and BCKAs levels （P<0.01）. The high- and medium-dose QRP groups demonstrated significant upregulation of BCKDH mRNA transcription and protein expression， as well as DEPTOR mRNA transcription. Moreover， the DEPTOR protein expression level was significantly increased in high-， medium-， and low-dose QRP groups， while mTOR and S6K1 mRNA and protein expression levels were markedly downregulated （P<0.05， P<0.01）. Compared to the QRP + si-NC group， the QRP + si-BCKDH group exhibited increased BCAAs and BCKAs levels， significantly decreased BCKDH mRNA transcription and protein expression， downregulated DEPTOR mRNA and protein expression， and upregulated mTOR and S6K1 mRNA and protein expression （P<0.05， P<0.01）. ConclusionQRP may improve insulin resistance by reprogramming BCAAs metabolism. This effect involves upregulating BCKDH， reducing BCAAs and BCKAs levels， and suppressing the mTOR pathway activation.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

ObjectiveTo investigate the intervention effects and mechanisms of the flavonoid hyperoside （Hyp） on lipopolysaccharide （LPS）-induced inflammation in the zebrafish model. MethodsZebrafish larvae were either microinjected with 0.5 g·L^-1 LPS or immersed in 1 g·L^-1 LPS for the modeling of inflammation. The larvae were then treated with Hyp at 25， 50， and 100 mg·L^-1 through immersion for four consecutive days. The inflammatory phenotypes were assessed by analyzing the mortality rate， malformation rate， body length， and yolk sac area ratio. Behavioral tests were conducted to evaluate the inflammatory stress responses， and macrophage migration was observed by fluorescence microscopy. Additionally， the mRNA levels of inflammation-related genes， including interleukin-1β （IL-1β）， interleukin-6 （IL-6）， chemokine C-C motif ligand 2 （CCL2）， chemokine C-X3-C motif receptor 1 （CX3CR1）， chemokine C-C motif receptor 2 （CCR2）， and genes associated with the Toll-like receptor 4 （TLR4）/myeloid differentiation factor 88 （MyD88）/nuclear factor-kappa B （NF-κB） signaling pathway， were measured by Real-time quantitative polymerase chain reaction（Real-time PCR）. ResultsCompared with the pure water injection group， the model group exhibited increased mortality， malformation rates and yolk sac area ratio （P0.01）， reduced body length （P0.01）， increased total swimming distance and high-speed swimming duration （P0.01）， and up-regulated mRNA levels of TLR4， MyD88， NF-κB， IL-1β， IL-6， CCL2， CX3CR1， and CCR2 （P0.01）. Hyp at low， medium and high doses， as well as aspirin， reduced the mortality and malformation rates （P0.05，P0.01）， increased the body length （P0.05，P0.01）， decreased the yolk sac area ratio （P0.01）， reduced the high-speed swimming duration （P0.01）， and down-regulated the mRNA levels of TLR4， MyD88， NF-κB， IL-1β， IL-6， CCL2， CX3CR1， and CCR2 （P0.05，P0.01） compared with the model group. ConclusionHyp may modulate the TLR4/MyD88/NF-κB pathway to ameliorate inflammatory phenotypes and alleviate stress conditions in zebrafish， thereby exerting the anti-inflammatory effect.

Objective To discuss the clinical application of self-radiopaque marker guiding physician modified fenestration technique in treating aortic arch diseases with insufficient proximal anchoring area.Methods From October 2021 to March 2023,a total of 8 patients with aortic dissection/aneurysm located in area Z0 received thoracic endovascular aortic repair(TEVAR)by using self-radiopaque marker guiding physician modified fenestration technique.The patients were followed up to observe the safety and efficacy of this technique.Results Successful TEVAR was accomplished in all the 8 patients.Type Ⅰ endoleak occurred in one patient,which disappeared within 6 months.No perioperative death,stroke or paraplegia occurred.Conclusion For the treatment of aortic arch diseases with insufficient proximal anchoring area,TEVAR by using self-radiopaque marker guiding physician modified fenestration technique is clinically safe and effective with satisfactory short-to-medium-term effect,although its long-term effect needs further observation.

Conducting local tolerance testing on parentaral drugs is of great significance for evaluating the clinical medication risks of drugs.Although relevant domestic and international guidelines provide detailed instructions on how to conduct local tolerance testing,it was found that some products still provide non-standard application materials,which affects the efficiency of drug development.This article summarizes the information on domestic and international guidance related to the local tolerance testing and elaborates on common problems based on specific application cases,with the aim of of providing reference for related work.

Objective To explore the effect of glioma stem cells with high expression of protein tyrosin phosphatase receptor type Z1 (PTPRZ1 )on the phenotypic polarization and phagocytosis of tumor-associated macrophages and its regulatory mechanism.Methods GSCs and non-stem tumor cells (NSTCs) were screened out from human glioblastoma (GBM) specimens using flow cytometry,and the PTPRZ1 expression in paired GSCs and NSTCs were detected.Human peripheral blood mononuclear cells (PBMC)-derived CD14+monocytes were exposed to the conditioned medium from glioma cells or recombinant chemokine C-C motif ligand 20 (CCL20)for TAM polarization.Stable PTPRZ1 knockout GSCs (PTPRZ1-KO GSCs) were constructed using CRISPR/Cas9. TAM phagocytosis to GSCs,NSTCs,PTPRZ1-Control GSCs (PTPRZ1-Ctrl GSCs)and PTPRZ1-KO GSCs and the expression of immunosuppressive phenotype (M2) polarization marker CD163 were examined using flow cytometry.Differentially expressed genes (DEGs ) between paired GSCs and NSTCs were determined using a bulk RNA-sequencing dataset (GSE54791 )from Gene Expression Omnibus (GEO).A gene set informing worse outcome of patients with GBM was generated using The Cancer Genome Atlas (TCGA)-GBM cohort.By intersecting the aforementioned gene set with the gene set that encodes for human membrance proteins,the PTPRZ1 gene is obtained.Gene set enrichment analysis (GSEA)was used for pathway enrichment analysis to compare the differentially regulated pathways between GBMs with high or low PTPRZ1 expression.Bulk RNA sequencing,qRT-PCR and Western blotting were used to identify the DEGs between PTPRZ1-KO GSCs and PTPRZ1-Ctrl GSCs.Results GSCs were more capable of escaping from TAM phagocytosis than NSTCs (P<0.05 )and had specifically up-regulated PTPRZ1 expression.PTPRZ1-KO significantly suppressed GSCs escaping from TAM phagocytosis (P<0.01 ). GBMs with high PTPRZ1 expression showed significant inhibition of pathways mediating phagocytosis (P<0.05).The expression of CCL20 as a M2 TAM polarization chemokine was significantly down-regulated in PTPRZ1-KO GSCs (P<0.05 ).Treatment with recombinant CCL20 up-regulated the expression of CD163 as a M2 TAM marker in TAM.Conclusion PTPRZ1+GSCs mediate M2 TAM polarization and inhibit TAM phagocytosis,which may be related to the up-regulation of CCL20 in PTPRZ1+GSCs.

Near infrared spectroscopy(NIRS)technology combined with chemometrics algorithms has been widely used in quantitative and qualitative analysis of food and medicine.However,traditional chemometrics methods,especially linear classification methods,often yield unsatisfactory results when addressing multi-class classification problems.Convolutional neural network(CNN)is adept at extracting deep-level features from data and suitable for handling non-linear relationships.The modeling performance of CNN depends on the size and diversity of sample,while the collection and preprocessing of NIRS sample data is often time-consuming and labor-intensive.This study proposed a NIRS qualitative analysis method based on data augmentation strategies and CNN.The data augmentation strategy included two steps.Firstly,applying Bootstrap resampling and generative adversarial network(GAN)methods to augment three NIRS datasets(Medicine,coffee and grape).Secondly,combining the original samples(Y)with the Bootstrap augmented samples(B)and GAN augmented samples(G)to obtain three augmented datasets(Y-B,Y-G and Y-B-G).Based on this,a CNN model structure suitable for these datasets was designed,consisting of 2 one-dimensional convolutional layers,1 max-pooling layer,and 1 fully connected layer.The results showed that compared to the optimal models of partial least squares discriminant analysis(PLS-DA),support vector machine(SVM),and back propagation neural network(BP),the CNN model based on Y-B dataset achieved average accuracy improvements of 3.998%,9.364%,and 4.689%for medicine(Binary classification);the CNN model based on the Y-B-G dataset achieved average accuracy improvements of 6.001%,2.004%,and 7.523%for coffee(7-class classification);and the CNN model based on the Y-B dataset achieved average accuracy improvements of 33.408%,51.994%,and 34.378%for grapes(20-class classification).It was evident that the models established based on data augmentation strategies and CNN demonstrated better classification accuracy and generalization performance with different datasets and classification categories.

Endodontic diseases are a kind of chronic infectious oral disease.Common endodontic treatment concepts are based on the removal of inflamed or necrotic pulp tissue and the replacement by gutta-percha.However,it is very essential for endodontic treatment to debride the root canal system and prevent the root canal system from bacterial reinfection after root canal therapy(RCT).Recent research,encompassing bacterial etiology and advanced imaging techniques,contributes to our understanding of the root canal system's anatomy intricacies and the technique sensitivity of RCT.Success in RCT hinges on factors like patients,infection severity,root canal anatomy,and treatment techniques.Therefore,improving disease management is a key issue to combat endodontic diseases and cure periapical lesions.The clinical difficulty assessment system of RCT is established based on patient conditions,tooth conditions,root canal configuration,and root canal needing retreatment,and emphasizes pre-treatment risk assessment for optimal outcomes.The findings suggest that the presence of risk factors may correlate with the challenge of achieving the high standard required for RCT.These insights contribute not only to improve education but also aid practitioners in treatment planning and referral decision-making within the field of endodontics.