Early pathogenesis of ischemia-reperfusion(I/R)-induced acute kidney injury(AKI)is dominated by intracellular calcium overload,which induces oxidative stress,intracellular energy metabolism disorder,inflammatory activ...Early pathogenesis of ischemia-reperfusion(I/R)-induced acute kidney injury(AKI)is dominated by intracellular calcium overload,which induces oxidative stress,intracellular energy metabolism disorder,inflammatory activation,and a series of pathologic cascaded reactions that are closely intertwined with self-amplifying and interactive feedback loops,ultimately resulting in cell damage and kidney failure.Currently,most nanomedicines originate from the perspective of antioxidant stress,which can only quench existing reactive oxide species(ROS)but cannot prevent the continuous production of ROS,resulting in insufficient efficacy.As a safe and promising drug,BAPTA-AM is hydrolyzed into BAPTA by intracellular esterase upon entering cells,which can rapidly chelate with overloaded Ca^(2+),restoring intracellular calcium homeostasis,thus inhibiting ROS regeneration at the source.Here,we designed a KTP-targeting peptide-modified yolk-shell structure of liposome–poly(ethylene glycol)methyl ether-block-poly(L-lactide-co-glycolic)(mPLGA)hybrid nanoparticles(<100 nm),with the characteristics of high encapsulation rate,high colloid stability,facile modification,and prolonged blood circulation time.Once the BA/mPLGA@Lipo-KTP was targeted to the site of kidney injury,the cholesteryl hemisuccinate(CHEMS)in the phospholipid bilayer,as an acidic cholesterol ester,was protonated in the simulated inflammatory slightly acidic environment(pH 6.5),causing the liposomes to rupture and release the BA/mPLGA nanoparticles,which were then depolymerized by intracellular esterase.The BAPTA-AM was diffused and hydrolyzed to produce BAPTA,which can rapidly cut off the malignant loop of calcium overload/ROS generation at its source,blocking the endoplasmic reticulum(ER)apoptosis pathway(ATF4–CHOP–Bax/Bcl-2,Casp-12–Casp-3)and the inflammatory pathway(TNF-α–NF-κB–IL-6 axes),thus alleviating pathological changes in kidney tissue,thereby inhibiting the expression of renal tubular marker kidney injury molecule 1(Kim-1)(reduced by 82.9%)and also exhibiting prominent anti-apoptotic capability(TUNEL-positive ratio decreased from 40.2%to 8.3%),significantly restoring renal function.Overall,this research holds huge potential in the treatment of I/R injury-related diseases.展开更多
Coal spontaneous combustion fires threaten personal safety,increase carbon emissions,release toxic and harmful gases,and cause serious environmental pollution.The study of intelligent early warnings for coal spontaneo...Coal spontaneous combustion fires threaten personal safety,increase carbon emissions,release toxic and harmful gases,and cause serious environmental pollution.The study of intelligent early warnings for coal spontaneous combustion can advance fire prevention and control measures,making a meaningful contribution to the ecological and environmental protection in mining areas.To address the limitations in selecting characteristic index gases for coal spontaneous combustion and the low accuracy of traditional temperature prediction and discrimination models,an intelligent identification system was developed.The system integrates laboratory research and analysis,intelligent algorithm optimization,index rationality verification,and field measurement and application,all based on characteristic index gases.By constructing a dynamic discriminant model of coal self-gas temperature,the composite index of coal spontaneous combustion characteristics is further optimized and verified.Model performance was evaluated using root mean square error(RMSE),decision coefficient(R^(2)),mean absolute error(MAE),and mean absolute percentage error(MAPE).The prediction results for three,four,and five parameters were obtained.The results indicate that the R^(2) value was 0.9975 under the conditions of O_(2),CO,C_(2)H_(4),and CH_(4)/C_(2)H_(6),demonstrating the best model performance.The MAE was 1.9272,the RMSE was 2.5114,and the MAPE was 2.0830%.These findings enable optimal selection of self-ignition warning indicators for coal.A comparative analysis of the improved whale optimization(MSWOA-BP),gray wolf optimization(GWO-BP),standard whale optimization(WOA-BP),and particle swarm optimization(PSO-BP)models was performed to verify the universality of preferred feature indicators and the accuracy of prediction models.A comparative analysis between on-site measured temperatures and model-predicted temperatures demonstrated that the model exhibited high accuracy.This research provides a valuable reference for developing on-site coal spontaneous combustion warning systems,enabling efficient prediction and early warning,which are crucial for coal resource safety,efficient mining,and fire prevention.展开更多
基金supported by the Taishan Scholar Foundation of Shandong Province(No.tsqn202211065)Hainan Provincial Joint Project of Sanya Yazhou Bay Science and Technology City(No.2021JJLH0037)+1 种基金the Natural Science Foundation of China(No.82003673)the Fundamental Research Funds for the Central Universities(No.202113049)。
文摘Early pathogenesis of ischemia-reperfusion(I/R)-induced acute kidney injury(AKI)is dominated by intracellular calcium overload,which induces oxidative stress,intracellular energy metabolism disorder,inflammatory activation,and a series of pathologic cascaded reactions that are closely intertwined with self-amplifying and interactive feedback loops,ultimately resulting in cell damage and kidney failure.Currently,most nanomedicines originate from the perspective of antioxidant stress,which can only quench existing reactive oxide species(ROS)but cannot prevent the continuous production of ROS,resulting in insufficient efficacy.As a safe and promising drug,BAPTA-AM is hydrolyzed into BAPTA by intracellular esterase upon entering cells,which can rapidly chelate with overloaded Ca^(2+),restoring intracellular calcium homeostasis,thus inhibiting ROS regeneration at the source.Here,we designed a KTP-targeting peptide-modified yolk-shell structure of liposome–poly(ethylene glycol)methyl ether-block-poly(L-lactide-co-glycolic)(mPLGA)hybrid nanoparticles(<100 nm),with the characteristics of high encapsulation rate,high colloid stability,facile modification,and prolonged blood circulation time.Once the BA/mPLGA@Lipo-KTP was targeted to the site of kidney injury,the cholesteryl hemisuccinate(CHEMS)in the phospholipid bilayer,as an acidic cholesterol ester,was protonated in the simulated inflammatory slightly acidic environment(pH 6.5),causing the liposomes to rupture and release the BA/mPLGA nanoparticles,which were then depolymerized by intracellular esterase.The BAPTA-AM was diffused and hydrolyzed to produce BAPTA,which can rapidly cut off the malignant loop of calcium overload/ROS generation at its source,blocking the endoplasmic reticulum(ER)apoptosis pathway(ATF4–CHOP–Bax/Bcl-2,Casp-12–Casp-3)and the inflammatory pathway(TNF-α–NF-κB–IL-6 axes),thus alleviating pathological changes in kidney tissue,thereby inhibiting the expression of renal tubular marker kidney injury molecule 1(Kim-1)(reduced by 82.9%)and also exhibiting prominent anti-apoptotic capability(TUNEL-positive ratio decreased from 40.2%to 8.3%),significantly restoring renal function.Overall,this research holds huge potential in the treatment of I/R injury-related diseases.
基金supported by the National Natural Science Foundation of China(Nos.52374219,51904172,and 42107284)the Shandong Provincial Natural Science Foundation(No.ZR2023ME115)+2 种基金the Qing Chuang Science and Technology Program of Shandong Province University(Nos.2023KJ086 and 2021RW030)the Opening Foundation of Key Laboratory of Xinjiang Coal Resources Green Mining(Xinjiang Institute of Engineering),Ministry of Education(No.KLXGYKB2501)the Fundamental Research Funds for the Central Universities(No.2024–11044)
文摘Coal spontaneous combustion fires threaten personal safety,increase carbon emissions,release toxic and harmful gases,and cause serious environmental pollution.The study of intelligent early warnings for coal spontaneous combustion can advance fire prevention and control measures,making a meaningful contribution to the ecological and environmental protection in mining areas.To address the limitations in selecting characteristic index gases for coal spontaneous combustion and the low accuracy of traditional temperature prediction and discrimination models,an intelligent identification system was developed.The system integrates laboratory research and analysis,intelligent algorithm optimization,index rationality verification,and field measurement and application,all based on characteristic index gases.By constructing a dynamic discriminant model of coal self-gas temperature,the composite index of coal spontaneous combustion characteristics is further optimized and verified.Model performance was evaluated using root mean square error(RMSE),decision coefficient(R^(2)),mean absolute error(MAE),and mean absolute percentage error(MAPE).The prediction results for three,four,and five parameters were obtained.The results indicate that the R^(2) value was 0.9975 under the conditions of O_(2),CO,C_(2)H_(4),and CH_(4)/C_(2)H_(6),demonstrating the best model performance.The MAE was 1.9272,the RMSE was 2.5114,and the MAPE was 2.0830%.These findings enable optimal selection of self-ignition warning indicators for coal.A comparative analysis of the improved whale optimization(MSWOA-BP),gray wolf optimization(GWO-BP),standard whale optimization(WOA-BP),and particle swarm optimization(PSO-BP)models was performed to verify the universality of preferred feature indicators and the accuracy of prediction models.A comparative analysis between on-site measured temperatures and model-predicted temperatures demonstrated that the model exhibited high accuracy.This research provides a valuable reference for developing on-site coal spontaneous combustion warning systems,enabling efficient prediction and early warning,which are crucial for coal resource safety,efficient mining,and fire prevention.
