Intramitochondrial co-assembly between ATP and nucleopeptides induces cancer cell apoptosis

Mitochondria are essential intracellular organelles involved in many cellular processes, especially adenosine triphosphate (ATP) production. Since cancer cells require high ATP levels for proliferation, ATP elimination can be a unique target for cancer growth inhibition. We describe a newly developed mitochondria-targeting nucleopeptide (MNP) that sequesters ATP by self-assembling with ATP inside mitochondria. MNP interacts strongly with ATP through electrostatic and hydrogen bonding interactions. MNP exhibits higher binding affinity for ATP (−637.5 kJ mol⁻¹) than for adenosine diphosphate (ADP) (−578.2 kJ mol⁻¹). To improve anticancer efficacy, the small-sized MNP/ADP complex formed large assemblies with ATP inside cancer cell mitochondria. ATP sequestration and formation of large assemblies of the MNP/ADP–ATP complex inside mitochondria caused physical stress by large structures and metabolic disorders in cancer cells, leading to apoptosis. This work illustrates a facile approach to developing cancer therapeutics that relies on molecular assemblies.

Mitochondria-targeting nucleopeptide (MNP) can sequester ATP by self-assembling with ATP. A small nanosized MNP/ADP complex forms a large assembly with ATP. Thus, intramitochondrial co-assembly causes stress by large structures and apoptosis.     

Syntheses,Structures and Photocatalytic Degradation Properties of Two Copper(Ⅱ)Coordination Polymers with Flexible Bis(imidazole)Ligand

Two copper(Ⅱ)coordination polymers{[Cu(bib)(nip)]·1.5H2O}n(1)and[Cu2(bib)(glu)2]n(2)(bib= 1,4-bis(2-methyl-imidazol-1-yl)butane,H2nip = 5-nitroisophthalic acid,...     

Amphotericin B and Curcumin Co-Loaded Porous Microparticles as a Sustained Release System against Candida albicans

Amphotericin B (AMB) is an antifungal drug used for serious fungal infections. However, AMB has adverse reactions such as nephrotoxicity, which limit the clinical application of AMB alone or in combination with other antifungal drugs. Nano or micro drug delivery systems (DDS) have been proven to be effective in reducing the toxic and side effects of drugs. Further, the combination of AMB with other compounds with antifungal activity, such as curcumin (CM), may enhance the synergistic effects. Herein, AMB and CM were co-loaded into porous poly (lactic-co-glycolic acid) (PLGA) microparticles (MPs) to prepare AMB/CM-PLGA MPs. The AMB/CM-PLGA MPs showed a remarkably reduced hemolysis (62.2 ± 0.6%) compared to AMB (80.9 ± 1.1%). The nephrotoxicity of AMB/CM-PLGA MPs is significantly lower than that of AMB. In vitro, AMB/CM-PLGA MPs had better inhibitory effects on the adhesion and biofilm formation of Candida albicans compared with AMB. Experiments on mice infected with C. albicans showed that AMB/CM-PLGA MPs have a better therapeutic effect than AMB in vivo. In summary, AMB/CM-PLGA MPs may be a novel and promising therapeutic candidate for fungal infection.     

基于T2FCM-FE-HMMs的隐马氏模型参数估计算法

把2型模糊集的思想引入到了基于模糊聚类的离散HMM参数训练中,提出了改进的T 2FCM-FE-HMM s算法。     

Carbene-catalyzed activation of cyclopropylcarbaldehydes for mannich reaction and δ-lactam formation: remote enantioselecitvity control and dynamic kinetic asymmetric transformation

An N-heterocyclic carbene(NHC)-catalyzed enantioselective Mannich reaction of the remote γ-carbon of cyclopropylcarbaldehydes is disclosed for the first time. Diastereo-and enantiomerically enriched multicyclic δ-lactam compound is afforded as the main product from 8 possible stereo-specific isomers through dynamic kinetic asymmetric transformation(DYKAT) processes. Multiple chiral functional molecules can be afforded from the lactam products through simple protocols with retentions of the optical purities.     

Sufficient Conditions for Amalgamated 3-Manifolds to be ∂-Irreducible∗

In this paper, the authors give some sufficient conditions for an amalgamated 3-manifold along a compact connected surface F with boundary to be ?-irreducible in terms of distances between some kinds of vertex subsets of the curve complex and the arc complex of F.     

Growth regulation of luminescent gold nanoparticles directed from amphiphilic block copolymers:highly-controlled nanoassemblies toward tailored in-vivo transport

The understanding of amphiphilic block copolymers(ABC)in encapsulation and transport of inorganic nanomedicines is highly desired.Still,it remains limited due to the challenges in the fabrication of nanoassemblies(NAs)with highly-controlled shape and loading of nanoparticles.Herein,through growth regulation of luminescent gold nanoparticles(Au NPs)by different reductants with ABC pluronic F127 as a template,a straightforward strategy is reported for in-situ fabrication of three wellcontrolled gold NAs(Au NAs)that display tunable shapes from spherical to elongated nanostructures and controllable surface chemistry and loading of Au NPs with distinct emissions but identical individual Au NP size.The three Au NAs exhibit tailored invivo transport behaviours:those with spherical shape and more hydrophilic surface show longer blood retention with higher tumor-targeting efficiency(~25.3%injection dose/g)and excellent long-term near-infrared tumor imaging even after 96 h postinjection.These findings provide a useful guidance in designing specific nanostructures for future nanomedicine transport.     

埋地热油管道正常运行的数值模拟研究

对高凝原油管道输送的水力热力问题进行分析研究,掌握管线运行规律,保证管线安全经济运行有着重要意义.本文建立了埋地热油管道正常运行的数学模型,采用非结构化网格和有限容积法对该问题进行了研究,计算结果与实验测量值吻合良好.     

Domain Adaptation with Data Uncertainty Measure Based on Evidence Theory

Domain adaptation aims to learn a classifier for a target domain task by using related labeled data from the source domain. Because source domain data and target domain task may be mismatched, there is an uncertainty of source domain data with respect to the target domain task. Ignoring the uncertainty may lead to models with unreliable and suboptimal classification results for the target domain task. However, most previous works focus on reducing the gap in data distribution between the source and target domains. They do not consider the uncertainty of source domain data about the target domain task and cannot apply the uncertainty to learn an adaptive classifier. Aimed at this problem, we revisit the domain adaptation from source domain data uncertainty based on evidence theory and thereby devise an adaptive classifier with the uncertainty measure. Based on evidence theory, we first design an evidence net to estimate the uncertainty of source domain data about the target domain task. Second, we design a general loss function with the uncertainty measure for the adaptive classifier and extend the loss function to support vector machine. Finally, numerical experiments on simulation datasets and real-world applications are given to comprehensively demonstrate the effectiveness of the adaptive classifier with the uncertainty measure.