本研究基于三个具有代表性的理论模型:相对论连续谱Hartree-Bogoliubov (RCHB)理论,相对论平均场(RMF)理论,Skyrme-Hartree-Fock-Bogoliubov (SHFB)模型,首先介绍了人工神经网络(ANN)方法,计算出了三个模型的单核子分离能的理论预测值...本研究基于三个具有代表性的理论模型:相对论连续谱Hartree-Bogoliubov (RCHB)理论,相对论平均场(RMF)理论,Skyrme-Hartree-Fock-Bogoliubov (SHFB)模型,首先介绍了人工神经网络(ANN)方法,计算出了三个模型的单核子分离能的理论预测值。随后利用神经网络对单核子分离能的理论值进行了优化训练,降低了单核子分离能的理论预测值与实验值之间的均方根偏差(RMSD),并在此基础上进行了两种分区优化,分别为质子和中子的幻数分区,分区优化训练后进一步降低了RMSD。单核子分离能分区训练后的RMSD比整体直接训练的效果更好,特别能显著降低轻核区的RMSD,单中子分离能进行中子幻数分区训练的效果更好,单质子分离能进行质子幻数分区训练的效果更好。This research is based on three representative theoretical models: the Relativistic Continuum Hartree-Bogoliubov (RCHB) theory, Relativistic Mean Field (RMF) theory, and Skyrme-Hartree-Fock-Bogoliubov (SHFB) model. First, the Artificial Neural Network (ANN) method was introduced to calculate theoretical predictions of single-nucleon separation energies for these three models. Subsequently, the neural network was employed to optimize and train the theoretical values of single-nucleon separation energies, reducing the root mean square deviation (RMSD) between theoretical predictions and experimental values. Two partitioning optimization schemes were then implemented: proton magic number partitioning and neutron magic number partitioning. The partitioned optimization training further reduced RMSD values. The partitioned training of single-nucleon separation energies demonstrated better performance than direct global training, particularly in significantly reducing RMSD in the light nuclei region. Specifically, neutron magic number partitioning showed superior effectiveness for optimizing single-neutron separation energies, while proton magic number partitioning yielded better results for single-proton separation energies.展开更多
Doxorubicin(DOX)is a widely employed tumor therapy,yet its substantial toxic side effects pose a considerable challenge.Bletilla striata has demonstrated efficacy in preventing and treating these toxic side effects in...Doxorubicin(DOX)is a widely employed tumor therapy,yet its substantial toxic side effects pose a considerable challenge.Bletilla striata has demonstrated efficacy in preventing and treating these toxic side effects in clinical practice,with polysaccharides identified as the principal active component.In the present study,16 fractions of B.striata polysaccharides(BsPs)were extracted using diverse methods,including hot-water extraction(HWE),ultrasonic-assisted extraction(UAE),enzyme-assisted extraction(EAE),dilute acid-water extraction(ACWE),and dilute alkali-water extraction(ALWE).These extractions were subsequently precipitated at final ethanol concentrations of 80%and 95%,respectively.The investigation encompassed yields,total carbohydrate content(TCC),total protein content(TPC),preliminary structural properties,and anti-DOX myocardial cytotoxic activity.Results indicated that the extraction method significantly influenced the physicochemical properties,associated functional properties,and anti-DOX myocardial cytotoxic activity of BsPs.HWE and UAE yielded higher BsPs quantities.The relative molecular weight(RMW)distribution of BsPs differed notably between HWE or UAE,EAE,ACWE,and ALWE.The RMW of primary BsPs obtained from HWE and UAE(1.9×10^(7)-1.7×10^(7) Da)exceeded that from EAE(7.5×10^(3)-2.8×10^(4) Da)and ALWE(5.1×10^(4)-1.7×10^(4) Da),with smaller molecular weights primarily precipitated by higher ethanol concentrations.BsPs were composed of Man and Glu,with partial fractions containing small amounts of Gal or Ara,displaying varying molar ratios.Notably,BsPs from ACWE exhibited the most significant structural differences,lacking 1,4-α-D-Glcp and a triple-helical structure.Furthermore,BsPs obtained from HWE,UAE,and EAE demonstrated heightened anti-DOX myocardial cytotoxic activity compared to other methods.This study underscored the influence of extraction methods on BsPs’structure and myocardial protective activity,offering a foundation for exploring structural diversity and employing specific extraction methods to extract polysaccharides with robust myocardial protective properties efficiently.展开更多
文摘本研究基于三个具有代表性的理论模型:相对论连续谱Hartree-Bogoliubov (RCHB)理论,相对论平均场(RMF)理论,Skyrme-Hartree-Fock-Bogoliubov (SHFB)模型,首先介绍了人工神经网络(ANN)方法,计算出了三个模型的单核子分离能的理论预测值。随后利用神经网络对单核子分离能的理论值进行了优化训练,降低了单核子分离能的理论预测值与实验值之间的均方根偏差(RMSD),并在此基础上进行了两种分区优化,分别为质子和中子的幻数分区,分区优化训练后进一步降低了RMSD。单核子分离能分区训练后的RMSD比整体直接训练的效果更好,特别能显著降低轻核区的RMSD,单中子分离能进行中子幻数分区训练的效果更好,单质子分离能进行质子幻数分区训练的效果更好。This research is based on three representative theoretical models: the Relativistic Continuum Hartree-Bogoliubov (RCHB) theory, Relativistic Mean Field (RMF) theory, and Skyrme-Hartree-Fock-Bogoliubov (SHFB) model. First, the Artificial Neural Network (ANN) method was introduced to calculate theoretical predictions of single-nucleon separation energies for these three models. Subsequently, the neural network was employed to optimize and train the theoretical values of single-nucleon separation energies, reducing the root mean square deviation (RMSD) between theoretical predictions and experimental values. Two partitioning optimization schemes were then implemented: proton magic number partitioning and neutron magic number partitioning. The partitioned optimization training further reduced RMSD values. The partitioned training of single-nucleon separation energies demonstrated better performance than direct global training, particularly in significantly reducing RMSD in the light nuclei region. Specifically, neutron magic number partitioning showed superior effectiveness for optimizing single-neutron separation energies, while proton magic number partitioning yielded better results for single-proton separation energies.
基金Science and Technology Foundation of Guizhou Province(Grant No.QKHJC-ZK[2023]YB524)Science and Technology Plan Project of Guizhou,China(Grant No.QKPTRC[2019]035)+2 种基金Science and Technology Foundation of Guizhou Province(Grant No.QKH[2019]1346)Science and Technology Department of Zunyi city of Guizhou province of China(Grant No.[2020]7)Undergraduate Training Program for Innovation and Entrepreneurship of Zunyi Medical University(Grant No.S202310661248).
文摘Doxorubicin(DOX)is a widely employed tumor therapy,yet its substantial toxic side effects pose a considerable challenge.Bletilla striata has demonstrated efficacy in preventing and treating these toxic side effects in clinical practice,with polysaccharides identified as the principal active component.In the present study,16 fractions of B.striata polysaccharides(BsPs)were extracted using diverse methods,including hot-water extraction(HWE),ultrasonic-assisted extraction(UAE),enzyme-assisted extraction(EAE),dilute acid-water extraction(ACWE),and dilute alkali-water extraction(ALWE).These extractions were subsequently precipitated at final ethanol concentrations of 80%and 95%,respectively.The investigation encompassed yields,total carbohydrate content(TCC),total protein content(TPC),preliminary structural properties,and anti-DOX myocardial cytotoxic activity.Results indicated that the extraction method significantly influenced the physicochemical properties,associated functional properties,and anti-DOX myocardial cytotoxic activity of BsPs.HWE and UAE yielded higher BsPs quantities.The relative molecular weight(RMW)distribution of BsPs differed notably between HWE or UAE,EAE,ACWE,and ALWE.The RMW of primary BsPs obtained from HWE and UAE(1.9×10^(7)-1.7×10^(7) Da)exceeded that from EAE(7.5×10^(3)-2.8×10^(4) Da)and ALWE(5.1×10^(4)-1.7×10^(4) Da),with smaller molecular weights primarily precipitated by higher ethanol concentrations.BsPs were composed of Man and Glu,with partial fractions containing small amounts of Gal or Ara,displaying varying molar ratios.Notably,BsPs from ACWE exhibited the most significant structural differences,lacking 1,4-α-D-Glcp and a triple-helical structure.Furthermore,BsPs obtained from HWE,UAE,and EAE demonstrated heightened anti-DOX myocardial cytotoxic activity compared to other methods.This study underscored the influence of extraction methods on BsPs’structure and myocardial protective activity,offering a foundation for exploring structural diversity and employing specific extraction methods to extract polysaccharides with robust myocardial protective properties efficiently.
