Aim To explore the effect of the classical famous prescription Dahuang Zhechong pill(DHZCP)on relieving liver cirrhosis by regulating the stress fiber remodeling mediated by mechanistic signaling pathway and to explore the underlying mechanism.Methods Mice were randomly divided into the control group,model group,DHZCP low-dose group,DHZCP high-dose group,and Colchicine-positive control group.The liver cirrhosis mouse model was constructed by intrap-eritoneal injection of olive oil-solubilized CCl4.HE staining and serologic markers were used to reflect liver injury.Masson staining was used to evaluate collagen deposition in liver tissue.ELISA was applied to detect vasoactive molecules and cancer indicators.Atomic force microscopy was employed to detect liver tissue stiffness.Color Doppler diagnostic instrument was used to assess portal blood flow velocity.Western blot was utilized to detect ROCK2 expression and phosphoryla-tion of YAP,Cofilin,and MLC.Results The liver tis-sues in the model group had obvious inflammatory cell infiltration and collagen deposition,accompanied by significant elevation of serum transaminases and fibrosis indexes.Similarly,vasoactive molecules and cancer in-dicators were elevated,and the mechanoregulatory pro-tein ROCK2 expression and phosphorylation of Cofilin and MLC were elevated,with YAP being strongly de-phosphorylated.Both low and high doses of DHZCP re-versed the pathological changes,serological indices,and inhibited the activation of the stress fiber(SF)re-modeling mechanistic signaling pathway.Conclusion DHZCP effectively ameliorates liver tissue lesions in mice with liver cirrhosis,and its mechanism may be re-lated to the inhibition of SF remodeling mechanistic signaling pathway.

Objective To propose a multiple regression-variational auto-encoders(MR-VAE)model to realize precise and non-invasive prediction of intra-abdominal pressure(IAP)in critically ill patients.Methods At first,a dataset was constructed by retrospectively analysing baseline characteristics and clinical indicators of 100 critically ill patients admitted to the Intensive Care Unit of Daping Hospital of Army Medical University between 30 August 2019 and 30 March 2021.Then,a MR-VAE prediction model was developed by integrating a feedforward neural network for supervised regression onto a variational autoencoder(VAE)framework and incorporating multiple regression strategies to mitigate feature interference.Finally,the MR-VAE model had its performance evaluated by its comparison with five classical models including support vector machines(SVM),convolutional neural networks(CNN),Scikit-learn integrated model(SIM),multi-layer perceptron(MLP)and K-nearest neighbors(KNN),and its prediction accuracy verified by testing the data of 10 randomly selected patients.Results The MR-VAE model behaved the best when compared with the five classical models,with a mean squared error(MSE)of 0.207,a root mean square error(RMSE)of 0.454,a mean absolute error(MAE)of 0.361,a median absolute deviation(MAD)of 0.243,an explained variance score(EVS)of 0.814 and a R2of 0.823,which also outperformed the five models in fitting performance,convergence and final loss.In random sample testing,the MR-VAE model exhibited high consistency between predicted and actual values.Conclusion The MR-VAE model proposed can accurately predict IAP,which has great potential in reducing the repeated measurements of IAP in critically ill patients and providing new ideas for the early diagnosis and treatment of IAH.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

In view of the characteristics of H5N6 subtype avian influenza virus(AIV)that it has both high pathogenicity and the risk of cross-species transmission,posing a serious threat to the poultry farming industry and public health security,in order to effectively prevent and control the spread of H5N6 avian influenza,a rapid,sensitive and specific detection technolo-gy was established in this study.The specific monoclonal antibodies against the neuraminidase N6 protein of avian influenza A virus subtype H5N6 were obtained through hybridoma and monoclonal antibody technology.These antibodies were coupled and labeled with carboxyl-functionalized fluorescent quantum dots,along with previously prepared specific antibodies against the hemagglutinin H5 protein.A rapid fluorescence immunochromatographic detection method for the H5N6 subtype of avian influ-enza virus was established according to the principle of double-antibody sandwich immunochromatography.This method a-chieved a detection sensitivity of 1 ng/mL for recombinant hemagglutinin H5 subtype protein and 0.1 ng/mL for recombinant neuraminidase N6 subtype protein.Moreover,the method exhibited no cross-reactivity with other influenza subtypes or patho-gens,such as Newcastle disease(ND),infectious bronchitis(IB),and infectious laryngotracheitis(ILT),thus demonstrating good specificity.The method effectively identified the highly pathogenic avian influenza virus H5 subtype and directly distin-guished the H5N6 subtype with good accuracy.The fluorescent quantum dot immunochromatographic typing detection method established herein met the sensitivity,specificity,and accuracy requirements for H5N6 subtype detection,and can be further used for rapid detection of the H5 and H5N6 subtypes of avian influenza virus.

Objective:To investigate the effects of curcumin,berberine,and puerarin combination therapy on lipid levels in hyperlipidemic mice.Methods:A total of 40 male C57BL/6J mice were randomly divided into eight groups:normal control group(A),high-fat control group(B),curcumin group(C),berberine group(D),puerarin group(E),low-dose combination group of curcumin,berberine,and puerarin(F),high-dose combination group of curcumin,berberine,and puerarin(G),and positive control group(H),with 5 mice in each group.The normal control group was fed a standard diet,while the other groups were given a high-fat diet.After establishing the hyperlipidemic model,the mice were administered with physiological saline,curcumin(200 mg/kg),berberine(200 mg/kg),puerarin(300 mg/kg),low-dose combination of curcumin(50 mg/kg),berberine(50 mg/kg),and puerarin(100 mg/kg),high-dose combination of curcumin(200 mg/kg),berberine(200 mg/kg),and puerarin(300 mg/kg),or simvastatin(6 mg/kg)via gavage for three weeks.After treatment,serum was collected from the mice for biochemical analysis of lipid levels and liver function.Liver tissues were subjected to HE staining,Western blot analysis and real-time quantitative PCR.Results:Curcumin,berberine,and puerarin,whether administered individually or in combination,can reduce the body weight of hyperlipidemic mice(P＜0.01).Treatment with curcumin,berberine,and puerarin individually significantly reduced lipid levels in hyperlipidemic mice(P＜0.05)and alleviated liver damage caused by hyperlipidemia(P＜0.05).Furthermore,the high-dose combination of curcumin,berberine,and puerarin exhibited a more pronounced effect on improving lipid levels(P＜0.01)and provided greater protective effects on the liver compared to the positive control group(P＜0.05).Additionally,curcumin,berberine,and puerarin administered individually can each promote the expression of the LDLR gene in high-fat diet mice(increased by 90％,85％,and 98％,respectively)and reduce the expression of the ACC gene(decreased by 42％,45％,and 43％,respectively).The combination of all three compounds enhances the expression of the LDLR gene in high-fat diet mice(increased by 90％with low-dose combination and 169％with high-dose combination)and reduces the expression of the ACC gene(decreased by 38％with low-dose combination and 42％with high-dose combination).Conclusion:The combination of curcumin,berberine,and puerarin significantly improves lipid levels in hyperlipidemic mice and mitigates liver damage associated with hyperlipidemia.

Aim To explore the effect of the classical famous prescription Dahuang Zhechong pill(DHZCP)on relieving liver cirrhosis by regulating the stress fiber remodeling mediated by mechanistic signaling pathway and to explore the underlying mechanism.Methods Mice were randomly divided into the control group,model group,DHZCP low-dose group,DHZCP high-dose group,and Colchicine-positive control group.The liver cirrhosis mouse model was constructed by intrap-eritoneal injection of olive oil-solubilized CCl4.HE staining and serologic markers were used to reflect liver injury.Masson staining was used to evaluate collagen deposition in liver tissue.ELISA was applied to detect vasoactive molecules and cancer indicators.Atomic force microscopy was employed to detect liver tissue stiffness.Color Doppler diagnostic instrument was used to assess portal blood flow velocity.Western blot was utilized to detect ROCK2 expression and phosphoryla-tion of YAP,Cofilin,and MLC.Results The liver tis-sues in the model group had obvious inflammatory cell infiltration and collagen deposition,accompanied by significant elevation of serum transaminases and fibrosis indexes.Similarly,vasoactive molecules and cancer in-dicators were elevated,and the mechanoregulatory pro-tein ROCK2 expression and phosphorylation of Cofilin and MLC were elevated,with YAP being strongly de-phosphorylated.Both low and high doses of DHZCP re-versed the pathological changes,serological indices,and inhibited the activation of the stress fiber(SF)re-modeling mechanistic signaling pathway.Conclusion DHZCP effectively ameliorates liver tissue lesions in mice with liver cirrhosis,and its mechanism may be re-lated to the inhibition of SF remodeling mechanistic signaling pathway.

Objective:To investigate the effects of curcumin,berberine,and puerarin combination therapy on lipid levels in hyperlipidemic mice.Methods:A total of 40 male C57BL/6J mice were randomly divided into eight groups:normal control group(A),high-fat control group(B),curcumin group(C),berberine group(D),puerarin group(E),low-dose combination group of curcumin,berberine,and puerarin(F),high-dose combination group of curcumin,berberine,and puerarin(G),and positive control group(H),with 5 mice in each group.The normal control group was fed a standard diet,while the other groups were given a high-fat diet.After establishing the hyperlipidemic model,the mice were administered with physiological saline,curcumin(200 mg/kg),berberine(200 mg/kg),puerarin(300 mg/kg),low-dose combination of curcumin(50 mg/kg),berberine(50 mg/kg),and puerarin(100 mg/kg),high-dose combination of curcumin(200 mg/kg),berberine(200 mg/kg),and puerarin(300 mg/kg),or simvastatin(6 mg/kg)via gavage for three weeks.After treatment,serum was collected from the mice for biochemical analysis of lipid levels and liver function.Liver tissues were subjected to HE staining,Western blot analysis and real-time quantitative PCR.Results:Curcumin,berberine,and puerarin,whether administered individually or in combination,can reduce the body weight of hyperlipidemic mice(P＜0.01).Treatment with curcumin,berberine,and puerarin individually significantly reduced lipid levels in hyperlipidemic mice(P＜0.05)and alleviated liver damage caused by hyperlipidemia(P＜0.05).Furthermore,the high-dose combination of curcumin,berberine,and puerarin exhibited a more pronounced effect on improving lipid levels(P＜0.01)and provided greater protective effects on the liver compared to the positive control group(P＜0.05).Additionally,curcumin,berberine,and puerarin administered individually can each promote the expression of the LDLR gene in high-fat diet mice(increased by 90％,85％,and 98％,respectively)and reduce the expression of the ACC gene(decreased by 42％,45％,and 43％,respectively).The combination of all three compounds enhances the expression of the LDLR gene in high-fat diet mice(increased by 90％with low-dose combination and 169％with high-dose combination)and reduces the expression of the ACC gene(decreased by 38％with low-dose combination and 42％with high-dose combination).Conclusion:The combination of curcumin,berberine,and puerarin significantly improves lipid levels in hyperlipidemic mice and mitigates liver damage associated with hyperlipidemia.

In view of the characteristics of H5N6 subtype avian influenza virus(AIV)that it has both high pathogenicity and the risk of cross-species transmission,posing a serious threat to the poultry farming industry and public health security,in order to effectively prevent and control the spread of H5N6 avian influenza,a rapid,sensitive and specific detection technolo-gy was established in this study.The specific monoclonal antibodies against the neuraminidase N6 protein of avian influenza A virus subtype H5N6 were obtained through hybridoma and monoclonal antibody technology.These antibodies were coupled and labeled with carboxyl-functionalized fluorescent quantum dots,along with previously prepared specific antibodies against the hemagglutinin H5 protein.A rapid fluorescence immunochromatographic detection method for the H5N6 subtype of avian influ-enza virus was established according to the principle of double-antibody sandwich immunochromatography.This method a-chieved a detection sensitivity of 1 ng/mL for recombinant hemagglutinin H5 subtype protein and 0.1 ng/mL for recombinant neuraminidase N6 subtype protein.Moreover,the method exhibited no cross-reactivity with other influenza subtypes or patho-gens,such as Newcastle disease(ND),infectious bronchitis(IB),and infectious laryngotracheitis(ILT),thus demonstrating good specificity.The method effectively identified the highly pathogenic avian influenza virus H5 subtype and directly distin-guished the H5N6 subtype with good accuracy.The fluorescent quantum dot immunochromatographic typing detection method established herein met the sensitivity,specificity,and accuracy requirements for H5N6 subtype detection,and can be further used for rapid detection of the H5 and H5N6 subtypes of avian influenza virus.

Objective To propose a multiple regression-variational auto-encoders(MR-VAE)model to realize precise and non-invasive prediction of intra-abdominal pressure(IAP)in critically ill patients.Methods At first,a dataset was constructed by retrospectively analysing baseline characteristics and clinical indicators of 100 critically ill patients admitted to the Intensive Care Unit of Daping Hospital of Army Medical University between 30 August 2019 and 30 March 2021.Then,a MR-VAE prediction model was developed by integrating a feedforward neural network for supervised regression onto a variational autoencoder(VAE)framework and incorporating multiple regression strategies to mitigate feature interference.Finally,the MR-VAE model had its performance evaluated by its comparison with five classical models including support vector machines(SVM),convolutional neural networks(CNN),Scikit-learn integrated model(SIM),multi-layer perceptron(MLP)and K-nearest neighbors(KNN),and its prediction accuracy verified by testing the data of 10 randomly selected patients.Results The MR-VAE model behaved the best when compared with the five classical models,with a mean squared error(MSE)of 0.207,a root mean square error(RMSE)of 0.454,a mean absolute error(MAE)of 0.361,a median absolute deviation(MAD)of 0.243,an explained variance score(EVS)of 0.814 and a R2of 0.823,which also outperformed the five models in fitting performance,convergence and final loss.In random sample testing,the MR-VAE model exhibited high consistency between predicted and actual values.Conclusion The MR-VAE model proposed can accurately predict IAP,which has great potential in reducing the repeated measurements of IAP in critically ill patients and providing new ideas for the early diagnosis and treatment of IAH.