ObjectiveQi deficiency and phlegm dampness syndrome is a common type of clinical traditional Chinese medicine（TCM） syndrome. However， there is no standard， scientific， and accurate report on the construction of animal models of Qi deficiency and phlegm dampness syndrome. This study aims to construct a mouse model of Qi deficiency and phlegm dampness syndrome by using a multi-factor composite modeling method and to evaluate the model. MethodsTwenty-one C57BL/6 mice were randomly divided into three groups with seven mice in each group， which were the normal group， model group， and Shenling Baizhusan （SLBZ） group. The control group was fed with ordinary diet and kept in a normal environment. The model group and SLBZ group were fed with a high-fat diet in a high-humidity environment. Swimming with heavy weights until exhaustion and gavage with cold water or lard were used to establish the mouse model of Qi deficiency and phlegm dampness syndrome. In order to test the syndrome by prescription， mice in the SLBZ group were treated with SLBZ for 14 days after model construction. The exhaustive swimming time， body weight， serum lipid levels， tongue changes， "Qi deficiency and phlegm dampness" assessment scale score， and cecal index of mice in each group were measured. The feces of each group of mice were sent for metagenomics and metabolome sequencing， and the changes in intestinal flora and metabolites were analyzed. ResultsAfter the modeling of Qi deficiency and phlegm dampness syndrome， the exhaustive swimming time of mice was obviously shortened （P<0.01）. The serum total cholesterol， low density lipoprotein cholesterol， and non-high density lipoprotein cholesterol of mice were significantly increased （all P<0.01）. The tongue of mice was significantly different from that of the normal group， and the score of the assessment scale was significantly higher than that of the control group （P<0.01）. Cecal index decreased significantly （P<0.01）. The serum lipid level， tongue image， assessment scale score， and cecal index were reversed in the SLBZ group. Metagenomic and metabolome sequencing results showed that intestinal flora and fecal metabolites were significantly changed in mice with Qi deficiency and phlegm dampness syndrome. Akkermansia_muciniphila， Faecalibaculum_rodentium， Eubacterium_plexicaudatum， Eubacterium sp 14_2， Candida glabrata， Romboutsia_ilealis， Turicibacter sp TS3， and other bacteria had significant changes， and the expressions of intestinal metabolites such as chenodeoxycholic acid， choline， L-phenylalanine betaine， and 2-phenylbutyric acid were significantly changed. Related metabolic pathways such as linoleic acid metabolism， primary bile acid biosynthesis， lysine degradation， arginine biosynthesis， and alpha-linolenic acid metabolism were affected. ConclusionThe Qi deficiency and phlegm dampness model of mice can be constructed by the multi-factor composite modeling method of high-fat diet feeding， high-humidity environment feeding， exhaustive swimming with heavy weight， and intragastric administration with cold water or lard. The blood lipid level， tongue change， score of "Qi deficiency and phlegm dampness assessment scale"， cecal index， and changes in related intestinal flora and metabolites of mice can be used as key indicators for model evaluation.

Erchentang is a classic formula widely used by medical practitioners throughout history. In this paper，ancient and modern literature of Erchentang were collected， and bibliometrics was employed to analyze its historic evolution，prescription meaning，herbs origin， processing method，preparation methods， and clinical application. A total of 84 pieces of data were collected， and 58 pieces of data involving 53 ancient medical Chinese books were screened， sorted， and processed. Combined with research of modern scholars，the research has found that the Erchentang originated from the Taiping Huimin Huiye Shijie Fang compiled by the Imperial Medical Bureau of the Song Dynasty. The basic information about the origin of the drugs is quite clear. Pinelliae rhizoma in the formula is the dried tuber of Pinellia ternata. Citri exocarpium rubrum is the dried mature peel of Citrus reticulata and its cultivated varieties， with the inner white membrane removed. Poria is the whitest dry sclerotia of Poria cocos； Glycyrrhizae radix et rhizoma is the dried root and rhizome of the Glycyrrhiza uralensis. The dosage is 5.70 g Pinelliae rhizome and Citri exocarpium rubrum， 3.43 g Poria， and 1.69 g Glycyrrhizae radix et rhizoma praeparata cum melle. During the decoction process， the above-mentioned herbs should be chopped， with 300 mL water， 7 g ginger in thick slices， and 2 g Mume fructus added， and it was then simmered together to 180 mL. After removing the medicinal residue， it can be taken warmly. Erchentang has the effect of drying dampness and resolving phlegm， regulating Qi and harmonizing the middle. It can be used in treating the syndrome of phlegm and dampness，as well as symptoms such as frequent cough，white phlegm，fullness in chest and diaphragm，nausea and vomiting，limb drowsiness，anorexia，dizziness，palpitations，white and greasy tongue coating， and slippery pulse. The above results provide reference for future research and development of Erchentang.

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.

A growing body of research points out that gut microbiota plays a key role in tumor immunotherapy. By optimizing the composition of intestinal microbiota, it is possible to effectively improve immunotherapy resistance and enhance its therapeutic effect. This article comprehensively analyzes the mechanism of intestinal microbiota influencing tumor immunotherapy resistance, expounds the current strategies for targeted regulation of intestinal microbiota, such as traditional Chinese medicine and plant components, fecal microbiota transplantation, probiotics, prebiotics and dietary therapy, and explores the potential mechanisms of these strategies to improve patients' resistance to tumor immunotherapy. At the same time, the article also briefly discusses the prospects and challenges of targeting intestinal microbiota to improve tumor immunotherapy resistance, which provides a reference for related research to help the strategy research of reversing tumor immunotherapy resistance.

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.

PURPOSE: Septic shock is associated with high mortality and poor outcomes among sepsis patients with coagulopathy. Although traditional statistical methods or machine learning (ML) algorithms have been proposed to predict septic shock, these potential approaches have never been systematically compared. The present work aimed to develop and compare models to predict septic shock among patients with sepsis. METHODS: It is a retrospective cohort study based on 484 patients with sepsis who were admitted to our intensive care units between May 2018 and November 2022. Patients from the 908th Hospital of Chinese PLA Logistical Support Force and Nanchang Hongdu Hospital of Traditional Chinese Medicine were respectively allocated to training (n=311) and validation (n=173) sets. All clinical and laboratory data of sepsis patients characterized by comprehensive coagulation indexes were collected. We developed 5 models based on ML algorithms and 1 model based on a traditional statistical method to predict septic shock in the training cohort. The performance of all models was assessed using the area under the receiver operating characteristic curve and calibration plots. Decision curve analysis was used to evaluate the net benefit of the models. The validation set was applied to verify the predictive accuracy of the models. This study also used Shapley additive explanations method to assess variable importance and explain the prediction made by a ML algorithm. RESULTS: Among all patients, 37.2% experienced septic shock. The characteristic curves of the 6 models ranged from 0.833 to 0.962 and 0.630 to 0.744 in the training and validation sets, respectively. The model with the best prediction performance was based on the support vector machine (SVM) algorithm, which was constructed by age, tissue plasminogen activator-inhibitor complex, prothrombin time, international normalized ratio, white blood cells, and platelet counts. The SVM model showed good calibration and discrimination and a greater net benefit in decision curve analysis. CONCLUSION The SVM algorithm may be superior to other ML and traditional statistical algorithms for predicting septic shock. Physicians can better understand the reliability of the predictive model by Shapley additive explanations value analysis.
Humans ; Shock, Septic/blood* ; Machine Learning ; Male ; Female ; Retrospective Studies ; Middle Aged ; Aged ; Sepsis/complications* ; ROC Curve ; Cohort Studies ; Adult ; Intensive Care Units ; Algorithms ; Blood Coagulation ; Critical Illness

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 establish a method for determining the contents of clopidogrel （CLP）， clopidogrel carboxylate （CLP-C）， clopidogrel acyl-β-D-glucuronide （CLP-G） and contents of clopidogrel active metabolite （CAM） in rat plasma， and to investigate their in vivo pharmacokinetic characteristics. METHODS The Shisedo CAPCELL ADME column was used with a mobile phase consisting of water and acetonitrile （both containing 0.1% formic acid） in a gradient elution. The flow rate was 0.4 mL/min， and the column temperature was maintained at 20 ℃. The injection volume was 2 μL. The analysis was performed in positive ion mode using electrospray ionization with multiple reaction monitoring. The ion pairs for quantitative analysis were m/z 322.1→211.9 （for CLP）， m/z 308.1→197.9 （for CLP-C）， m/z 322.1→154.8 （for CLP-G）， m/z 504.1→154.9 [for racemic CAM derivative （CAMD）]. Six rats were administered a single intragastric dose of CLP （10 mg/kg）. Blood samples were collected before medication and at 0.08， 0.33， 0.66， 1， 2， 4， 6， 10， 23 and 35 hours after medication. The established method was used to detect the serum contents of various components in rats. Pharmacokinetic parameters were then calculated using WinNonlin 6.1 software. RESULTS The linear ranges for CLP， CLP-C and CAMD were 0.08-20.00， 205.00-8 000.00， and 0.04-25.00 ng/mL， respectively （r≥0.990）. The relative standard deviations for both intra-day and inter-day precision tests were all less than 15%， and the relative errors for accuracy ranged from －11.68% to 14.40%. The coefficients of variation for the matrix factors were all less than 15%， meeting the requirements for bioanalytical method validation. The results of the pharmacokinetic study revealed that， following a single intagastric administration of CLP in rats， the exposure to the parent CLP in plasma was extremely low. Both the area under the drug concentration-time curve （AUC0-35 h） and the peak concentration of the parent CLP were lower than those of its metabolites. The AUC0-35 h of the active metabolite CAM was approximately 43 times that of CLP， though it had a shorter half-life （2.53 h）. The inactive metabolite CLP-C exhibited the highest exposure level， but it reached its peak concentration the latest and was eliminated slowly. The AUC0-35 h of CLP-G was about four times that of CAM， and its half-life was similar to that of CLP-C. CONCLUSIONS This study successfully established an liquid chromatography-tandem mass spectrometry method for the determination of CLP and its three metabolites， and revealed their pharmacokinetic characteristics in rats. Specifically， the parent drug CLP was rapidly eliminated， while the inactive metabolites CLP-C and CLP-G exhibited long half-lives， and active metabolite CAM displayed a transient exposure pattern.