AIM:The current study aims to investigate the protective effect of farrerol against sepsis-induced cardiomyopathy and its mechanisms in mice.METHODS:Eighteen male C57BL/6 mice were randomly divided into the control,lipopolysaccharide(LPS;10 mg/kg),and LPS+farrerol(40 mg/kg)groups,with 6 mice in each group.The car-diac function of the mice was assessed via ultrasonography.Myocardial pathological changes and mitochondrial damage were examined via hematoxylin and eosin staining and transmission electron microscopy,respectively.TUNEL staining was performed to evaluate myocardial apoptosis,and RT-qPCR and ELISA were conducted to assess cardiac tissue inflam-matory factor mRNA expression and the serum inflammatory factor levels.Furthermore,the malondialdehyde(MDA),glutathione(GSH),superoxide dismutase(SOD),Fe2+,and reactive oxygen species(ROS)levels in the myocardial tis-sues were evaluated using kits and immunofluorescence.Western blot analysis was performed to investigate the levels of key proteins associated with apoptosis,ferroptosis,and the nuclear factor E2-related facor 2(Nrf2)/heme oxygenase-1(HO-1)signaling pathway.RESULTS:Farrerol pretreatment prevented the reduction of cardiac function in mice with SIC(P<0.01).Further,it decreased myocardial tissue pathological damage,mitochondrial ultrastructural disruption,the inflammatory factor levels(P<0.01),cardiac oxidative stress and Fe2+content(P<0.01),the expression of apoptotic cardiomyocytes(P<0.01),and the level of Bax expression(P<0.01).Finally,it increased the protein expression of Bcl-2,glutathione peroxidase 4(GPX4),solute carrier family 7 member 11(SLC7A11),Nrf2,and HO-1(P<0.05 or P<0.01).The control,LPS,and LPS+farrerol groups did not significantly differ in terms of left ventricular anterior wall end-diastolic depth and left ventricular posterior wall end-diastolic depth(P>0.05).CONCLUSION:Farrerol reduces LPS-induced septic myocardial injury and inhibits the development of ferroptosis in the myocardial tissues of mice,which may be related to the Nrf2/HO-1 signaling pathway.

Objective To investigate the predictive efficacy of complete blood count(CBC)parameters for the prognosis of acute pancreatitis(AP),and to construct a machine learning model.Methods The clinical data of 120 patients with AP admitted from January 2021 to December 2024 were retrospectively analyzed.Based on the prognostic outcomes within 28 d of treatment,they were divided into the poor prognosis group and the good prognosis group.On the first day of admission,CBC parameters[red blood cell count,hemoglobin,hematocrit,white blood cell count,neutrophil count,lymphocyte count,monocyte count,red blood cell distribution width(RDW),platelet count,mean platelet volume,platelet distribution width,neutrophil/lymphocyte ratio(NLR),platelet/lymphocyte ratio(PLR),lymphocyte/monocyte ratio(LMR)were detected in the two groups.The general data and CBC parameters of the two groups were compared.The clinical variables were screened using the Lasso regression equation.Four models,namely Support Vector Machine(SVM),logistic regression(LR),deep neural network(DNN),and Random Forest(RF),were constructed for external validation.The predictive efficacy of the four models for the prognosis of AP was evaluated by using the receiver operating characteristic(ROC)curve,the precision-recall(PR)curve,the calibration curve and the clinical decision curve.Results The APACHE Ⅱ score,bedside severity index score,proportion of vasoactive drug use,and proportion of severe hypoproteinemia in the poor prognosis group were all higher than those in the good prognosis group(P<0.01).The levels of RDW,NLR and PLR in the poor prognosis group were all higher than those in the good prognosis group,while the level of LMR was lower than that in the good prognosis group(P<0.01).The Lasso regression equation ultimately screened out four non-zero coefficient variables:NLR,RDW,APACHE Ⅱ score,and severe hypoproteinemia.Based on the above variables,SVM,LR,RF and DNN machine learning models were constructed.The RF model had the highest area under the ROC curve(AUC),PR AUC,accuracy rate and F1 score for predicting the prognosis of AP,and had the optimal comprehensive performance.The calibration curve showed that the curve of the RF model for predicting the prognosis of AP was relatively close to the ideal curve.The decision curve showed that when the threshold probability value of the RF model was 15%to 100%,it had a significance clinical net benefit rate.External validation also showed that the RF model had the optimal predictive efficacy.The calibration curve indicated that the predictive curve of the RF model for the prognosis of AP highly coincided with the actually observed curve.The decision curve showed that the RF model provided clinical net benefits to patients across the decision threshold range of 0 to 100%.Conclusion Machine learning models constructed based on CBC parameters can make relatively accurate predictions about the prognosis of AP.Among them,the RF model has the optimal predictive efficiency,which can be used as an auxiliary tool for clinical prediction of AP prognosis,and can also provide reference for clinical treatment.

AIM:The current study aims to investigate the protective effect of farrerol against sepsis-induced cardiomyopathy and its mechanisms in mice.METHODS:Eighteen male C57BL/6 mice were randomly divided into the control,lipopolysaccharide(LPS;10 mg/kg),and LPS+farrerol(40 mg/kg)groups,with 6 mice in each group.The car-diac function of the mice was assessed via ultrasonography.Myocardial pathological changes and mitochondrial damage were examined via hematoxylin and eosin staining and transmission electron microscopy,respectively.TUNEL staining was performed to evaluate myocardial apoptosis,and RT-qPCR and ELISA were conducted to assess cardiac tissue inflam-matory factor mRNA expression and the serum inflammatory factor levels.Furthermore,the malondialdehyde(MDA),glutathione(GSH),superoxide dismutase(SOD),Fe2+,and reactive oxygen species(ROS)levels in the myocardial tis-sues were evaluated using kits and immunofluorescence.Western blot analysis was performed to investigate the levels of key proteins associated with apoptosis,ferroptosis,and the nuclear factor E2-related facor 2(Nrf2)/heme oxygenase-1(HO-1)signaling pathway.RESULTS:Farrerol pretreatment prevented the reduction of cardiac function in mice with SIC(P<0.01).Further,it decreased myocardial tissue pathological damage,mitochondrial ultrastructural disruption,the inflammatory factor levels(P<0.01),cardiac oxidative stress and Fe2+content(P<0.01),the expression of apoptotic cardiomyocytes(P<0.01),and the level of Bax expression(P<0.01).Finally,it increased the protein expression of Bcl-2,glutathione peroxidase 4(GPX4),solute carrier family 7 member 11(SLC7A11),Nrf2,and HO-1(P<0.05 or P<0.01).The control,LPS,and LPS+farrerol groups did not significantly differ in terms of left ventricular anterior wall end-diastolic depth and left ventricular posterior wall end-diastolic depth(P>0.05).CONCLUSION:Farrerol reduces LPS-induced septic myocardial injury and inhibits the development of ferroptosis in the myocardial tissues of mice,which may be related to the Nrf2/HO-1 signaling pathway.

Objective To investigate the predictive efficacy of complete blood count(CBC)parameters for the prognosis of acute pancreatitis(AP),and to construct a machine learning model.Methods The clinical data of 120 patients with AP admitted from January 2021 to December 2024 were retrospectively analyzed.Based on the prognostic outcomes within 28 d of treatment,they were divided into the poor prognosis group and the good prognosis group.On the first day of admission,CBC parameters[red blood cell count,hemoglobin,hematocrit,white blood cell count,neutrophil count,lymphocyte count,monocyte count,red blood cell distribution width(RDW),platelet count,mean platelet volume,platelet distribution width,neutrophil/lymphocyte ratio(NLR),platelet/lymphocyte ratio(PLR),lymphocyte/monocyte ratio(LMR)were detected in the two groups.The general data and CBC parameters of the two groups were compared.The clinical variables were screened using the Lasso regression equation.Four models,namely Support Vector Machine(SVM),logistic regression(LR),deep neural network(DNN),and Random Forest(RF),were constructed for external validation.The predictive efficacy of the four models for the prognosis of AP was evaluated by using the receiver operating characteristic(ROC)curve,the precision-recall(PR)curve,the calibration curve and the clinical decision curve.Results The APACHE Ⅱ score,bedside severity index score,proportion of vasoactive drug use,and proportion of severe hypoproteinemia in the poor prognosis group were all higher than those in the good prognosis group(P<0.01).The levels of RDW,NLR and PLR in the poor prognosis group were all higher than those in the good prognosis group,while the level of LMR was lower than that in the good prognosis group(P<0.01).The Lasso regression equation ultimately screened out four non-zero coefficient variables:NLR,RDW,APACHE Ⅱ score,and severe hypoproteinemia.Based on the above variables,SVM,LR,RF and DNN machine learning models were constructed.The RF model had the highest area under the ROC curve(AUC),PR AUC,accuracy rate and F1 score for predicting the prognosis of AP,and had the optimal comprehensive performance.The calibration curve showed that the curve of the RF model for predicting the prognosis of AP was relatively close to the ideal curve.The decision curve showed that when the threshold probability value of the RF model was 15%to 100%,it had a significance clinical net benefit rate.External validation also showed that the RF model had the optimal predictive efficacy.The calibration curve indicated that the predictive curve of the RF model for the prognosis of AP highly coincided with the actually observed curve.The decision curve showed that the RF model provided clinical net benefits to patients across the decision threshold range of 0 to 100%.Conclusion Machine learning models constructed based on CBC parameters can make relatively accurate predictions about the prognosis of AP.Among them,the RF model has the optimal predictive efficiency,which can be used as an auxiliary tool for clinical prediction of AP prognosis,and can also provide reference for clinical treatment.

Objective To investigate the protective effects of HTD4010 against lipopolysaccharide(LPS)-induced septic cardiomyopathy(SCM)in mice and explore the mechanisms mediating its effect.Methods Forty-five male ICR mice were randomized equally into control group,LPS(10 mg/kg)group,and LPS+HTD4010 group(in which 2.5 mg/kg HTD4010 was injected subcutaneously at 1 h and 6 h after LPS injection).Cardiac function of the mice was evaluated by ultrasound,and pathological changes in the myocardial tissues were observed with HE staining.The levels of IL-6 and TNF-α in serum and myocardial tissues were detected using ELISA,and apoptosis of the cardiomyocytes was detected with TUNEL staining.The expression levels of the key proteins associated with apoptosis,autophagy and the AMPK/mTOR pathway in the myocardial tissues were detected using Western blotting.The ultrastructural changes of cardiac myocardial mitochondria was observed with transmission electron microscopy.Results LPS exposure caused severe myocardial damage in mice,characterized by myocardial fiber rupture,structural disorder,inflammatory cell infiltration,and mitochondrial damage.The LPS-treated mice exhibited significantly decreased cardiac LVEF and FS values,elevated IL-6 and TNF-αlevels in serum and myocardial tissue,and an increased myocardial cell apoptosis rate with enhanced expressions of Bax,p-62 and p-mTOR and lowered expressions of Bcl-2,LC3 Ⅱ/I,Beclin-1 and p-AMPK(P<0.05 or 0.01).Treatment of the septic mice with HTD4010 significantly alleviated myocardial damage,increased LVEF and FS values,reduced IL-6 and TNF-α levels in serum and myocardial tissue,decreased cardiomyocyte apoptosis,lowered myocardial expressions of Bax,p-62 and p-mTOR,and increased Bcl-2,LC3 Ⅱ/I,Beclin-1 and p-AMPK expressions(P<0.05 or 0.01).Conclusion HTD4010 can attenuate myocardial injury in SCM mice possibly by promoting autophagy via modulating the AMPK/mTOR signaling pathway.

Objective To investigate the protective effects of HTD4010 against lipopolysaccharide(LPS)-induced septic cardiomyopathy(SCM)in mice and explore the mechanisms mediating its effect.Methods Forty-five male ICR mice were randomized equally into control group,LPS(10 mg/kg)group,and LPS+HTD4010 group(in which 2.5 mg/kg HTD4010 was injected subcutaneously at 1 h and 6 h after LPS injection).Cardiac function of the mice was evaluated by ultrasound,and pathological changes in the myocardial tissues were observed with HE staining.The levels of IL-6 and TNF-α in serum and myocardial tissues were detected using ELISA,and apoptosis of the cardiomyocytes was detected with TUNEL staining.The expression levels of the key proteins associated with apoptosis,autophagy and the AMPK/mTOR pathway in the myocardial tissues were detected using Western blotting.The ultrastructural changes of cardiac myocardial mitochondria was observed with transmission electron microscopy.Results LPS exposure caused severe myocardial damage in mice,characterized by myocardial fiber rupture,structural disorder,inflammatory cell infiltration,and mitochondrial damage.The LPS-treated mice exhibited significantly decreased cardiac LVEF and FS values,elevated IL-6 and TNF-αlevels in serum and myocardial tissue,and an increased myocardial cell apoptosis rate with enhanced expressions of Bax,p-62 and p-mTOR and lowered expressions of Bcl-2,LC3 Ⅱ/I,Beclin-1 and p-AMPK(P<0.05 or 0.01).Treatment of the septic mice with HTD4010 significantly alleviated myocardial damage,increased LVEF and FS values,reduced IL-6 and TNF-α levels in serum and myocardial tissue,decreased cardiomyocyte apoptosis,lowered myocardial expressions of Bax,p-62 and p-mTOR,and increased Bcl-2,LC3 Ⅱ/I,Beclin-1 and p-AMPK expressions(P<0.05 or 0.01).Conclusion HTD4010 can attenuate myocardial injury in SCM mice possibly by promoting autophagy via modulating the AMPK/mTOR signaling pathway.