Achieving increasingly finely targeted drug delivery to organs,tissues,cells,and even to intracellular biomacromolecules is one of the core goals of nanomedicines.As the delivery destination is refined to cellular and...Achieving increasingly finely targeted drug delivery to organs,tissues,cells,and even to intracellular biomacromolecules is one of the core goals of nanomedicines.As the delivery destination is refined to cellular and subcellular targets,it is essential to explore the delivery of nanomedicines at the molecular level.However,due to the lack of technical methods,the molecular mechanism of the intracellular delivery of nanomedicines remains unclear to date.Here,we develop an enzyme-induced proximity labeling technology in nanoparticles(nano-EPL)for the real-time monitoring of proteins that interact with intracellular nanomedicines.Poly(lactic-co-glycolic acid)nanoparticles coupled with horseradish peroxidase(HRP)were fabricated as a model(HRP(+)-PNPs)to evaluate the molecular mechanism of nano delivery in macrophages.By adding the labeling probe biotin-phenol and the catalytic substrate H_(2)O_(2)at different time points in cellular delivery,nano-EPL technology was validated for the real-time in situ labeling of proteins interacting with nanoparticles.Nano-EPL achieves the dynamic molecular profiling of 740 proteins to map the intracellular delivery of HRP(+)-PNPs in macrophages over time.Based on dynamic clustering analysis of these proteins,we further discovered that different organelles,including endosomes,lysosomes,the endoplasmic reticulum,and the Golgi apparatus,are involved in delivery with distinct participation timelines.More importantly,the engagement of these organelles differentially affects the drug delivery efficiency,reflecting the spatial–temporal heterogeneity of nano delivery in cells.In summary,these findings highlight a significant methodological advance toward understanding the molecular mechanisms involved in the intracellular delivery of nanomedicines.展开更多
The fidelity of financial market simulation is restricted by the so-called“non-identifiability”difficulty when calibrating high-frequency data.This paper first analyzes the inherent loss of data information in this ...The fidelity of financial market simulation is restricted by the so-called“non-identifiability”difficulty when calibrating high-frequency data.This paper first analyzes the inherent loss of data information in this difficulty,and proposes to use the Kolmogorov-Smirnov test(K-S)as the objective function for high-frequency calibration.Empirical studies verify that K-S has better identifiability of calibrating high-frequency data,while also leads to a much harder multi-modal landscape in the calibration space.To this end,we propose the adaptive stochastic ranking based negatively correlated search algorithm for improving the balance between exploration and exploitation.Experimental results on both simulated data and real market data demonstrate that the proposed method can obtain up to 36.0%improvement in high-frequency data calibration problems over the compared methods.展开更多
基金supported by Natural Science Foundation of Beijing Municipality(L212013)National Key Research and Development Program of China(No.2022YFA1206104)+2 种基金AI+Health Collaborative Innovation Cultivation Project(Z211100003521002)National Natural Science Foundation of China(81971718,82073786,81872809,U20A20412,81821004)Beijing Natural Science Foundation(7222020).
文摘Achieving increasingly finely targeted drug delivery to organs,tissues,cells,and even to intracellular biomacromolecules is one of the core goals of nanomedicines.As the delivery destination is refined to cellular and subcellular targets,it is essential to explore the delivery of nanomedicines at the molecular level.However,due to the lack of technical methods,the molecular mechanism of the intracellular delivery of nanomedicines remains unclear to date.Here,we develop an enzyme-induced proximity labeling technology in nanoparticles(nano-EPL)for the real-time monitoring of proteins that interact with intracellular nanomedicines.Poly(lactic-co-glycolic acid)nanoparticles coupled with horseradish peroxidase(HRP)were fabricated as a model(HRP(+)-PNPs)to evaluate the molecular mechanism of nano delivery in macrophages.By adding the labeling probe biotin-phenol and the catalytic substrate H_(2)O_(2)at different time points in cellular delivery,nano-EPL technology was validated for the real-time in situ labeling of proteins interacting with nanoparticles.Nano-EPL achieves the dynamic molecular profiling of 740 proteins to map the intracellular delivery of HRP(+)-PNPs in macrophages over time.Based on dynamic clustering analysis of these proteins,we further discovered that different organelles,including endosomes,lysosomes,the endoplasmic reticulum,and the Golgi apparatus,are involved in delivery with distinct participation timelines.More importantly,the engagement of these organelles differentially affects the drug delivery efficiency,reflecting the spatial–temporal heterogeneity of nano delivery in cells.In summary,these findings highlight a significant methodological advance toward understanding the molecular mechanisms involved in the intracellular delivery of nanomedicines.
基金supported by the National Natural Science Foundation of China(Nos.62272210,62250710682,and 62331014).
文摘The fidelity of financial market simulation is restricted by the so-called“non-identifiability”difficulty when calibrating high-frequency data.This paper first analyzes the inherent loss of data information in this difficulty,and proposes to use the Kolmogorov-Smirnov test(K-S)as the objective function for high-frequency calibration.Empirical studies verify that K-S has better identifiability of calibrating high-frequency data,while also leads to a much harder multi-modal landscape in the calibration space.To this end,we propose the adaptive stochastic ranking based negatively correlated search algorithm for improving the balance between exploration and exploitation.Experimental results on both simulated data and real market data demonstrate that the proposed method can obtain up to 36.0%improvement in high-frequency data calibration problems over the compared methods.
