ObjectiveTo investigate the effects of Shengui Jiangtang Formula on insulin resistance and glucose-lipid metabolism in spontaneous type 2 diabetic db/db mice based on the phosphatidylinositol 3-kinase （PI3K）/protein kinase B （Akt）/forkhead box protein O1 （FoxO1） signaling pathway， and to provide theoretical foundation for its clinical application through fundamental experiments. MethodsA randomized controlled design was employed in this study. Thirty spontaneous type 2 diabetic db/db mice meeting the inclusion criteria （fasting blood glucose >7.0 mmol·L^-1 and random blood glucose on a different day≥11.1 mmol·L^-1） were selected as the subjects. After stratified block randomization by body weight and blood glucose levels， they were randomly assigned to a model group， a metformin group， and a Shengui Jiangtang formula group， with n=10 per group. Ten db/m mice were used as the normal group. During the 5-week intervention， general indicators （including general condition， fasting blood glucose （FBG）， body weight， and food intake） were recorded weekly. An oral glucose tolerance test （OGTT） was performed at week 5. After 5 weeks， serum was collected to measure glucose-lipid metabolism parameters. Liver tissues were analyzed as follows： Histopathology was observed through hematoxylin and eosin （HE） staining， periodic acid-Schiff （PAS） staining， and Oil red O staining. The expression of proteins and genes related to the PI3K/Akt/FoxO1 signaling pathway was quantitatively analyzed using Western blotting （Western blot） and real-time quantitative polymerase chain reaction （Real-time PCR）. ResultsGeneral observations： The mice in the normal group were generally healthy， exhibited agile responses and had smooth and glossy fur. Compared with the normal group， the mice in the model group displayed typical symptoms of polydipsia， polyphagia， and polyuria， along with listlessness and rough fur. Their food intake， initial body weight， liver weight， and liver index were all significantly higher than those in the normal group （P<0.01）. After 5 weeks of drug intervention， neither the Shengui Jiangtang Formula group nor the metformin group significantly affected the food intake of the model mice. Compared with the model group， no statistically significant difference was observed in liver weight or liver index in the Shengui Jiangtang formula group. Serum biochemical indicators： Compared with the normal group， the model group showed significantly elevated levels of FBG， fasting insulin， homeostatic model assessment of insulin resistance （HOMA-IR）， glycosylated serum protein， and blood lipids. After drug intervention， compared with the model group， the Shengui Jiangtang formula group significantly reduced FBG in the model mice （P<0.01）. The blood glucose levels at all time points during the OGTT in the Shengui Jiangtang Formula group were lower than those in the model group， with statistically significant differences in the 0 min blood glucose and the area under the curve for glucose compared to the model group （P<0.05）. Furthermore， the formula significantly reduced fasting insulin levels， HOMA-IR， and glycosylated serum protein levels （P<0.05）. It also showed a tendency to decrease blood lipids， liver enzymes （aspartate aminotransferase， alanine aminotransferase）， and blood urea nitrogen levels， and a tendency to increase creatinine levels， although these differences were not statistically significant. Liver histomorphology： HE staining indicated that Shengui Jiangtang formula improved the morphological structure of hepatocytes and attenuated steatosis in diabetic mice. Liver PAS staining showed that it increased hepatic glycogen content and promoted hepatic glycogen synthesis in diabetic mice. Oil red O staining demonstrated that it reduced lipid deposition within hepatocytes. Western blot： Compared with the normal group， the model group showed decreased protein expression of PI3K， Akt， p-Akt， and p-FoxO1， and increased FoxO1 protein expression. Compared with the model group， both the metformin and Shengui Jiangtang Formula groups showed increased protein expression of PI3K， Akt， p-Akt， and p-FoxO1， and decreased FoxO1 protein expression. Real-time PCR： Compared with the normal group， the mRNA expression of PI3K and Akt was downregulated （P<0.05）， and the mRNA expression of FoxO1 was downregulated （P<0.05） in the model group. ConclusionShengui Jiangtang Formula can improve insulin resistance and glucose-lipid metabolic disorders in db/db mice. It alleviates hepatic steatosis， promotes hepatic glycogen synthesis， and reduces lipid deposition in these mice. The mechanism by which Shengui Jiangtang Formula improves insulin resistance may be associated with the PI3K/Akt/FoxO1 signaling pathway.

ObjectiveTo investigate the efficacy and underlying mechanisms of Gynostemma pentaphyllum alcohol extract in improving glucose and lipid metabolism disorders in db/db mice through transcriptomics and gut microbiota analysis. MethodsEighteen db/db mice were randomly assigned to the model（DM） group， metformin（MET） group， and G. pentaphyllum alcohol extract（GP） group， with six mice in each group， based on stratification of fasting blood glucose and body weight. An additional six db/m mice were selected as the normal control（NC） group. Mice in the NC and DM groups were administered deionized water （10 mL·kg^-1） daily. The MET group received metformin （0.195 g·kg^-1） by gavage. The GP group was treated with G. pentaphyllum alcohol extract （3.9 g·kg^-1） by gavage for six weeks. Fasting blood glucose was measured every two weeks. After six weeks of intervention， serum levels of total cholesterol （TC）， triglycerides （TG）， low-density lipoprotein cholesterol （LDL-C）， high-density lipoprotein cholesterol （HDL-C）， aspartate aminotransferase （AST）， alanine aminotransferase （ALT）， creatinine （CREA）， and blood urea nitrogen （BUN） were assessed. Enzyme-linked immunosorbent assay （ELISA） was used to measure insulin （FINS）， adiponectin （ADP）， and tumor necrosis factor-α （TNF-α）. Hematoxylin-eosin （HE） staining was used to observe liver histomorphology， periodic acid-Schiff （PAS） staining was employed to assess hepatic glycogen synthesis， and Oil Red O staining was used to detect hepatic lipid deposition. Liver transcriptomic data were used to identify differentially expressed genes in the liver and conduct enrichment analysis. Real-time PCR was employed to verify the expression levels of adiponectin gene （Adipoq）， peroxisome proliferator-activated receptor gamma coactivator-1α （PGC-1α）， AMP-activated protein kinase （AMPK）， peroxisome proliferator-activated receptor α （PPARα）， glucokinase （GCK）， forkhead box （Fox）O1， FoxO3， phosphoenolpyruvate carboxykinase （PEPCK）， and glucose-6-phosphatase （G6PC）. Metagenomic sequencing was conducted to analyze changes in gut microbiota composition. ResultsCompared with the NC group， the DM group exhibited significantly elevated fasting blood glucose （P<0.01）， serum AST， ALT， TC， TG， LDL-C， and HDL-C （P<0.01）. FINS， homeostatic model assessment for insulin resistance （HOMA-IR）， and the inflammatory cytokine TNF-α were significantly increased （P<0.01）， while ADP was significantly decreased （P<0.05）. Histological analysis confirmed severe hepatic steatosis and excessive lipid accumulation in the DM group， along with markedly reduced glycogen synthesis. Compared with the DM group， the GP group showed significantly decreased fasting blood glucose （P<0.01）， reduced serum TC， LDL-C， and HDL-C levels （P<0.05）， significantly decreased serum TG and AST levels （P<0.01）， significantly reduced FINS， HOMA-IR， and TNF-α levels （P<0.01）， and significantly increased ADP （P<0.01）. Hepatic steatosis and lipid deposition were significantly alleviated， while glycogen synthesis was markedly enhanced. Transcriptomic differential and enrichment analyses suggested that the mechanisms by which G. pentaphyllum alcohol extract improved hepatic glucose and lipid metabolism in db/db mice may involve regulation of the AMPK and FoxO signaling pathways. Real-time PCR results confirmed that expression of PGC-1α， PEPCK， G6PC， FoxO1， and FoxO3 was significantly downregulated following treatment with G. pentaphyllum alcohol extract （P<0.05， P<0.01）， whereas mRNA expression of Adipoq， PPARα， GCK， and AMPK was significantly upregulated （P<0.05， P<0.01）. Metagenomic analysis showed that the relative abundance of Lactobacillus， Alistipes， and Akkermansia species was higher in the GP group than in the DM group. ConclusionG. pentaphyllum alcohol extract may improve glucose and lipid metabolism disorders in db/db mice by regulating the hepatic AMPK/PPARα pathway to suppress lipid deposition and alleviate hepatic steatosis， by inhibiting gluconeogenesis through the AMPK/PGC-1α and FoxO pathways to lower fasting blood glucose， and by increasing the abundance of beneficial gut bacteria such as Lactobacillus， Alistipes， and Akkermansia to restore gut microbiota balance.

ObjectiveTo investigate the efficacy and underlying mechanisms of Gynostemma pentaphyllum alcohol extract in improving glucose and lipid metabolism disorders in db/db mice through transcriptomics and gut microbiota analysis. MethodsEighteen db/db mice were randomly assigned to the model（DM） group， metformin（MET） group， and G. pentaphyllum alcohol extract（GP） group， with six mice in each group， based on stratification of fasting blood glucose and body weight. An additional six db/m mice were selected as the normal control（NC） group. Mice in the NC and DM groups were administered deionized water （10 mL·kg^-1） daily. The MET group received metformin （0.195 g·kg^-1） by gavage. The GP group was treated with G. pentaphyllum alcohol extract （3.9 g·kg^-1） by gavage for six weeks. Fasting blood glucose was measured every two weeks. After six weeks of intervention， serum levels of total cholesterol （TC）， triglycerides （TG）， low-density lipoprotein cholesterol （LDL-C）， high-density lipoprotein cholesterol （HDL-C）， aspartate aminotransferase （AST）， alanine aminotransferase （ALT）， creatinine （CREA）， and blood urea nitrogen （BUN） were assessed. Enzyme-linked immunosorbent assay （ELISA） was used to measure insulin （FINS）， adiponectin （ADP）， and tumor necrosis factor-α （TNF-α）. Hematoxylin-eosin （HE） staining was used to observe liver histomorphology， periodic acid-Schiff （PAS） staining was employed to assess hepatic glycogen synthesis， and Oil Red O staining was used to detect hepatic lipid deposition. Liver transcriptomic data were used to identify differentially expressed genes in the liver and conduct enrichment analysis. Real-time PCR was employed to verify the expression levels of adiponectin gene （Adipoq）， peroxisome proliferator-activated receptor gamma coactivator-1α （PGC-1α）， AMP-activated protein kinase （AMPK）， peroxisome proliferator-activated receptor α （PPARα）， glucokinase （GCK）， forkhead box （Fox）O1， FoxO3， phosphoenolpyruvate carboxykinase （PEPCK）， and glucose-6-phosphatase （G6PC）. Metagenomic sequencing was conducted to analyze changes in gut microbiota composition. ResultsCompared with the NC group， the DM group exhibited significantly elevated fasting blood glucose （P<0.01）， serum AST， ALT， TC， TG， LDL-C， and HDL-C （P<0.01）. FINS， homeostatic model assessment for insulin resistance （HOMA-IR）， and the inflammatory cytokine TNF-α were significantly increased （P<0.01）， while ADP was significantly decreased （P<0.05）. Histological analysis confirmed severe hepatic steatosis and excessive lipid accumulation in the DM group， along with markedly reduced glycogen synthesis. Compared with the DM group， the GP group showed significantly decreased fasting blood glucose （P<0.01）， reduced serum TC， LDL-C， and HDL-C levels （P<0.05）， significantly decreased serum TG and AST levels （P<0.01）， significantly reduced FINS， HOMA-IR， and TNF-α levels （P<0.01）， and significantly increased ADP （P<0.01）. Hepatic steatosis and lipid deposition were significantly alleviated， while glycogen synthesis was markedly enhanced. Transcriptomic differential and enrichment analyses suggested that the mechanisms by which G. pentaphyllum alcohol extract improved hepatic glucose and lipid metabolism in db/db mice may involve regulation of the AMPK and FoxO signaling pathways. Real-time PCR results confirmed that expression of PGC-1α， PEPCK， G6PC， FoxO1， and FoxO3 was significantly downregulated following treatment with G. pentaphyllum alcohol extract （P<0.05， P<0.01）， whereas mRNA expression of Adipoq， PPARα， GCK， and AMPK was significantly upregulated （P<0.05， P<0.01）. Metagenomic analysis showed that the relative abundance of Lactobacillus， Alistipes， and Akkermansia species was higher in the GP group than in the DM group. ConclusionG. pentaphyllum alcohol extract may improve glucose and lipid metabolism disorders in db/db mice by regulating the hepatic AMPK/PPARα pathway to suppress lipid deposition and alleviate hepatic steatosis， by inhibiting gluconeogenesis through the AMPK/PGC-1α and FoxO pathways to lower fasting blood glucose， and by increasing the abundance of beneficial gut bacteria such as Lactobacillus， Alistipes， and Akkermansia to restore gut microbiota balance.

The diagnosis of hematological disorders is currently established from the combined results of different tests, including those assessing morphology (M), immunophenotype (I), cytogenetics (C), and molecular biology (M) (collectively known as the MICM classification). In this workflow, most of the results are interpreted manually (i.e., by a human, without automation), which is expertise-dependent, labor-intensive, time-consuming, and with inherent interobserver variability. Also, with advances in instruments and technologies, the data is gaining higher dimensionality and throughput, making additional challenges for manual analysis. Recently, artificial intelligence (AI) has emerged as a promising tool in clinical hematology to ensure timely diagnosis, precise risk stratification, and treatment success. In this review, we summarize the current advances, limitations, and challenges of AI models and raise potential strategies for improving their performance in each sector of the MICM pipeline. Finally, we share perspectives, highlight future directions, and call for extensive interdisciplinary cooperation to perfect AI with wise human-level strategies and promote its integration into the clinical workflow.

Objective To investigate the relationship between the serum FMS-like tyrosine kinase 3 ligand(Flt3L),progranulin(PGRN)levels and the disease risk and disease outcome of patients with acute lympho-blastic leukemia(ALL).Methods A total of 104 patients with ALL admitted to the hospital from September 2019 to September 2021 were selected as the research subjects.ALL patients were divided into the low-risk group(n=34),the medium-risk group(n=39),and the high-risk group(n=31)according to the disease risk.The levels of serum Flt3L and PGRN of the patients at admission were detected by enzyme-linked immu-nosorbent assay.Pearson correlation analysis was used to analyze the relationship between serum Flt3L,PGRN in ALL patients and the risk of ALL disease.According to the follow-up results of ALL patients,they were divided into the good prognosis group(n=81)and the poor prognosis group(n=23).The receiver oper-ating characteristic curve and the area under the curve(AUC)were used to analyze the evaluation value of se-rum Flt3L and PGRN for the prognosis of ALL patients,and multivariate Cox regression was used to analyze the prognostic risk factors of ALL patients.Results The serum Flt3L levels in the low-risk group and the medium-risk group were higher than those in the high-risk group,and the difference was statistically signifi-cant(P＜0.05).The serum PGRN levels in the low-risk group and the medium-risk group were lower than those in the high-risk group,and the difference was statistically significant(P＜0.05).Serum Flt3L in ALL patients was negatively correlated with the risk of ALL disease(r=-0.461,0.593,P＜0.05).Serum PGRN in ALL patients was positively correlated with the risk of ALL disease(r=0.593,P＜0.05).The proportions of white blood cell count ≥50 × 109/L,hemoglobin＜90 g/L,and serum PGRN level in the poor prognosis group were higher than those in the good prognosis group,while the serum Flt3L level was lower than that in the good prognosis group,and the differences were statistically significant(P＜0.05).The AUC of serum Flt3L and PGRN in evaluating the prognosis of ALL patients were 0.762(95％CI:0.717-0.816),0.815(95％CI:0.764-0.863),and 0.915(95％CI:0.866-0.964),respectively.White blood cell count ≥50 × 109/L,hemoglobin＜90 g/L,Flt3L＜92.07 pg/mL,and PGRN≥335.14 pg/mL were risk factors affecting the prognosis of ALL patients(P＜0.05).Conclusion The levels of serum Flt3L and PGRN in ALL patients are related to the disease risk and disease outcome of ALL.The combined detection of the two has a good eval-uation value for the prognosis of adult ALL patients.

At present,thoracic endovascular aortic repair(TEVAR)is the preferred treatment for acute complicated Stanford type B aortic dissection.The long-term risk assessment of patients after receiving TEVAR is directly related to the treatment decisions and long-term benefits.Traditional methods used for assessment of prognosis have certain limitations in dealing with the complex data and individualized differences,while artificial intelligence(AI)technology such as machine learning,based on its ability of analyzing multidimensional data,has great potential in predicting the postoperative complications,re-intervention risk,and long-term survival rate.This article aims to make a brief introduction about the development history from traditional prediction model to AI-assisted prediction model,and the clinical research and application of AI in predicting the prognosis of aortic dissection.

Objective To investigate the effects of allergens on the expressions of IL-18,IL-18BPa and IL-18Rα protein in peripheral blood CD4+Th1 cells of healthy control subjects(HC)and patients with allergic rhi-nitis(AR),and on the expressions of IL-18,IL-18BPa and IL-18Rα mRNA in the peripheral blood CD4+T cells.Methods Blood samples were collected from patients with rhinitis for negative skin prick test(AR-),rhinitis for positive skin prick test(AR+)and HC.Flow cytometry was used to evaluate the effects of allergens on the expres-sions of IL-18,IL-18BPa and IL-18Rα protein in CD4+Th1 cells.The expressions of IL-18,IL-18BPa and IL-18Rα mRNA in CD4+T cells were determined by qPCR.Results Compared with HC,increased IL-18 while de-creased IL-18BPa expressions in Th1 cells of AR-and AR+patients were observed,increased IL-18Rα expression in Th1 cells of AR+patients was also found.Additionally,allergens induced elevated expression of IL-18Rα pro-tein in Th1 cells of HC,and induced elevated mRNA expressions of IL-18,IL-18BPa and IL-18Rα in isolated blood CD4+T cells of AR+patients and HC.Conclusion Allergens may be involved in the pathogenesis of AR by inducing the expressions of IL-18 and IL-18Rα in blood CD4+Th1 cells.

Objective This study aims to predict the coronavirus disease 2019(COVID-19)epidemic in Xi'an based on SEAIQR model and Dropout-LSTM model,and to provide a scientific basis for evaluating the effectiveness of the"dynamic zero-COVID policy".Methods Considering a large number of asymptomatic infections,the changing parameters,and control procedures,we developed a time-dependent susceptible-exposed-asymptomatic-infected-quarantined-removed(SEAIQR)model with stage-specific interventions.Considering the time-series characteristics of COVID-19 data and the nonlinear relationship between them,we constructed a deep learning Dropout-LSTM model.The data of newly confirmed cases in Xi'an from December 9th,2021 to January 31st,2022 were used to fit the model,and the data from February 1st,2022 to February 7th,2022 were used to evaluate the model performance of forecasting.We then calculated the effective reproduction number(Rt)and analyzed the sensitivity of the different measurement scenarios.Results The peak of newly confirmed cases predicted by the SEAIQR model would appear on December 26th,2021,with 176 cases,and the"dynamic zero-COVID policy"may be achieved in January 24th,2022,with R2=0.849.The Dropout-LSTM model can reflect the time-series and nonlinear characteristics of the data,and the predicted newly confirmed cases were highly consistent with the actual situation,with R2=0.937.The MAE and RMSE of the Dropout-LSTM model were lower than those of the SEAIQR model,indicating that the predicted results were more ideal.At the beginning of the outbreak,R0 was 5.63.Since the implementation of comprehensive control,Rt has shown a gradual downward trend,dropping to below 1.0 on December 27th,2021.With the reduction of effective contact rate,the early implementation of control measures and the improvement of immunity threshold,the peak of newly confirmed cases will continue to decrease.Conclusion The proposed Dropout-LSTM model forecasts the epidemic well,which can provide a reference for decision-making of the"dynamic zero-COVID policy."

Objective To observe the value of vector flow mapping(VFM)technique for assessing changes of left ventricular diastolic function in ovarian cancer(OC)patients who underwent postoperative chemotherapy.Methods Totally 37 OC patients who received postoperative chemotherapy were prospectively enrolled in chemotherapy group,while 40 healthy adults were taken as controls(control group).Routine echocardiography and VFM were performed for chemotherapy group before chemotherapy,after 3 and 6 cycles of chemotherapy,also for controls at enrollment,and comparison was performed between groups before chemotherapy,as well as among different time points within chemotherapy group,and the correlations of VFM results with hemoglobin and routine echocardiographic results in chemotherapy group were analyzed.Results No significant difference of age,body mass,body surface area(BSA),nor hemoglobin level,routine echocardiographic and VFM results before chemotherapy was found between groups(all P＞0.05).With the process of chemotherapy,hemoglobin level gradually decreased,the isovolumic relaxation period(IR),atrial systole period(AS)intraventricular pressure difference(IVPD)and intraventricular pressure gradient(IVPG)of the left ventricle gradually increased(adjusted P＜0.05),whereas routine echocardiography only showed that the left atrial volume index(LAVI)and the ratio of early mitral inflow velocity and the mean mitral annular early diastolic velocity(E/e')increased after 6 cycles of chemotherapy compared with those pre-chemotherapy(adjusted P＜0.05).In chemotherapy group,VFM results in all diastolic subphases were strongly correlated with hemoglobin levels(|r|=0.718 to 0.836,all P＜0.05),weakly to moderately correlated with LAVI(|r|=0.375 to 0.525,all P＜0.05)and moderately correlated with E/e'(|r|=0.424 to 0.537,all P＜0.05).Conclusion The diastolic function of left ventricle was probably damaged in early stage after postoperative chemotherapy in OC patients.VFM might detect slight changes of early diastolic function of left ventricle more sensitively than routine echocardiography.