This study investigated hypoxia-inducible factor(HIF)-1α-mediated proteomic changes in post-slaughter Tan sheep skeletal muscle and identified energy metabolism biomarkers using the competitive adaptive reweighted sa...This study investigated hypoxia-inducible factor(HIF)-1α-mediated proteomic changes in post-slaughter Tan sheep skeletal muscle and identified energy metabolism biomarkers using the competitive adaptive reweighted sampling(CARS)algorithm.HIF-1αinhibition during early storage attenuated pH decline and significantly increased total colour change(ΔE)(P<0.05)while reducing myofibril fragmentation compared with controls.Proteomic profiling identified 257 differentially expressed proteins enriched in adenosine 5’-monophosphate(AMP)-activated protein kinase(AMPK),glycolysis,and HIF-1 signalling pathways.CARS analysis highlighted lactate dehydrogenase A(LDHA),phosphoglycerate kinase 1(PGK1;glycolytic enzyme),heat shock protein beta-6(HSPB6),and heat shock protein 90 kDa beta 1(HSP90B1)as key energy metabolism biomarkers.The results suggested that HIF-1 stabilised ATP production under hypoxia conditions by suppressing glycogen synthesis,enhancing glycolysis,modulating HSP activity to preserve cellular homeostasis,and influencing cytoskeletal proteins,thereby affecting meat quality.These results provide novel insights into post-mortem muscle energy metabolism regulation and potential targets for meat quality optimisation.展开更多
In this study,eight different varieties of maize seeds were used as the research objects.Conduct 81 types of combined preprocessing on the original spectra.Through comparison,Savitzky-Golay(SG)-multivariate scattering...In this study,eight different varieties of maize seeds were used as the research objects.Conduct 81 types of combined preprocessing on the original spectra.Through comparison,Savitzky-Golay(SG)-multivariate scattering correction(MSC)-maximum-minimum normalization(MN)was identified as the optimal preprocessing technique.The competitive adaptive reweighted sampling(CARS),successive projections algorithm(SPA),and their combined methods were employed to extract feature wavelengths.Classification models based on back propagation(BP),support vector machine(SVM),random forest(RF),and partial least squares(PLS)were established using full-band data and feature wavelengths.Among all models,the(CARS-SPA)-BP model achieved the highest accuracy rate of 98.44%.This study offers novel insights and methodologies for the rapid and accurate identification of corn seeds as well as other crop seeds.展开更多
近红外光谱技术(near infrared spectroscopy,NIRS)结合波段筛选方法及建模算法可以实现中药生产过程分析的快速、无损检测。该文针对银参通络胶囊关键工艺银杏叶大孔树脂纯化过程,实现对洗脱液中槲皮素、山柰酚和异鼠李素3种成分含量...近红外光谱技术(near infrared spectroscopy,NIRS)结合波段筛选方法及建模算法可以实现中药生产过程分析的快速、无损检测。该文针对银参通络胶囊关键工艺银杏叶大孔树脂纯化过程,实现对洗脱液中槲皮素、山柰酚和异鼠李素3种成分含量的快速测定。通过马氏距离算法剔除异常光谱,联合X-Y距离样本集划分(sample set partitioning based on joint X-Y distances,SPXY)方法划分数据集,基于协同区间偏最小二乘法(synergy interval partial least squares,siPLS)筛选的关键信息波段,在此基础上实施竞争自适应加权重采样方法(competitive adaptive reweighted sampling,CARS)、连续投影算法(successive projections algorithm,SPA)和蒙特卡洛无信息变量消除法(Monte Carlo uninformation variable elimination,MC-UVE)筛选波长以得到更少但更关键的变量数据,将其作为输入变量建立遗传算法优化的极限学习机(genetic algorithm joint extreme learning machine,GA-ELM)定量分析模型,并将模型性能与偏最小二乘回归(partial least squares regression,PLSR)方法建立的模型进行比较,结果表明siPLS-CARS-GA-ELM算法联用可实现以最少变量数达到最优的模型性能。槲皮素、山柰酚、异鼠李素的校正集相关系数Rc和验证集相关系数Rp均达到0.98以上,校正集误差均方根(root mean square error of calibration,RMSEC)、验证集误差均方根(root mean square error of prediction,RMSEP)和验证集相对偏差(relative standard errors of prediction,RSEP)分别为0.0300,0.0292,8.88%;0.0414,0.0348,8.46%;0.0293,0.0271,10.10%,相较于传统PLSR方法,所建立GA-ELM模型性能有较大提升,证明NIRS结合GA-ELM方法实现中药有效成分快速测定具有很大潜力。展开更多
基金supported by the Innovation Research Group Project of the National Natural Science Foundation of China(No.32260555).
文摘This study investigated hypoxia-inducible factor(HIF)-1α-mediated proteomic changes in post-slaughter Tan sheep skeletal muscle and identified energy metabolism biomarkers using the competitive adaptive reweighted sampling(CARS)algorithm.HIF-1αinhibition during early storage attenuated pH decline and significantly increased total colour change(ΔE)(P<0.05)while reducing myofibril fragmentation compared with controls.Proteomic profiling identified 257 differentially expressed proteins enriched in adenosine 5’-monophosphate(AMP)-activated protein kinase(AMPK),glycolysis,and HIF-1 signalling pathways.CARS analysis highlighted lactate dehydrogenase A(LDHA),phosphoglycerate kinase 1(PGK1;glycolytic enzyme),heat shock protein beta-6(HSPB6),and heat shock protein 90 kDa beta 1(HSP90B1)as key energy metabolism biomarkers.The results suggested that HIF-1 stabilised ATP production under hypoxia conditions by suppressing glycogen synthesis,enhancing glycolysis,modulating HSP activity to preserve cellular homeostasis,and influencing cytoskeletal proteins,thereby affecting meat quality.These results provide novel insights into post-mortem muscle energy metabolism regulation and potential targets for meat quality optimisation.
基金supported by the Science and Technology Development Plan Project of Jilin Provincial Department of Science and Technology (No.20220203112S)the Jilin Provincial Department of Education Science and Technology Research Project (No.JJKH20210039KJ)。
文摘In this study,eight different varieties of maize seeds were used as the research objects.Conduct 81 types of combined preprocessing on the original spectra.Through comparison,Savitzky-Golay(SG)-multivariate scattering correction(MSC)-maximum-minimum normalization(MN)was identified as the optimal preprocessing technique.The competitive adaptive reweighted sampling(CARS),successive projections algorithm(SPA),and their combined methods were employed to extract feature wavelengths.Classification models based on back propagation(BP),support vector machine(SVM),random forest(RF),and partial least squares(PLS)were established using full-band data and feature wavelengths.Among all models,the(CARS-SPA)-BP model achieved the highest accuracy rate of 98.44%.This study offers novel insights and methodologies for the rapid and accurate identification of corn seeds as well as other crop seeds.
文摘近红外光谱技术(near infrared spectroscopy,NIRS)结合波段筛选方法及建模算法可以实现中药生产过程分析的快速、无损检测。该文针对银参通络胶囊关键工艺银杏叶大孔树脂纯化过程,实现对洗脱液中槲皮素、山柰酚和异鼠李素3种成分含量的快速测定。通过马氏距离算法剔除异常光谱,联合X-Y距离样本集划分(sample set partitioning based on joint X-Y distances,SPXY)方法划分数据集,基于协同区间偏最小二乘法(synergy interval partial least squares,siPLS)筛选的关键信息波段,在此基础上实施竞争自适应加权重采样方法(competitive adaptive reweighted sampling,CARS)、连续投影算法(successive projections algorithm,SPA)和蒙特卡洛无信息变量消除法(Monte Carlo uninformation variable elimination,MC-UVE)筛选波长以得到更少但更关键的变量数据,将其作为输入变量建立遗传算法优化的极限学习机(genetic algorithm joint extreme learning machine,GA-ELM)定量分析模型,并将模型性能与偏最小二乘回归(partial least squares regression,PLSR)方法建立的模型进行比较,结果表明siPLS-CARS-GA-ELM算法联用可实现以最少变量数达到最优的模型性能。槲皮素、山柰酚、异鼠李素的校正集相关系数Rc和验证集相关系数Rp均达到0.98以上,校正集误差均方根(root mean square error of calibration,RMSEC)、验证集误差均方根(root mean square error of prediction,RMSEP)和验证集相对偏差(relative standard errors of prediction,RSEP)分别为0.0300,0.0292,8.88%;0.0414,0.0348,8.46%;0.0293,0.0271,10.10%,相较于传统PLSR方法,所建立GA-ELM模型性能有较大提升,证明NIRS结合GA-ELM方法实现中药有效成分快速测定具有很大潜力。
