New information-theoretic foundations for quantum statistics

When the state of a physical system is not fully determined by available data, it should be possible nevertheless to make a systematic guess concerning the unknown state by applying the principles of information theory. The resulting theoretical blend of informational and mechanical constructs should then constitute a modern structure for statistical physics. Such a program has been attempted by a number of authors, most notably Jaynes, with seeming success. However, we demonstrated in a recent publication that the standard list of so-called mutually exclusive and exhaustive quantum states that is commonly employed by these authors is in fact not exhaustive. It follows that the information-theoretic foundations of quantum statistics must be reformulated. The present paper discusses the fundamental problems involved and establishes a format for the correct application of information theory to quantum mechanical situations.Work supported by a grant from Research Corporation.     

A general electron donor–acceptor complex for photoactivation of arenes via thianthrenation

General photoactivation of electron donor–acceptor (EDA) complexes between arylsulfonium salts and 1,4-diazabicyclo[2.2.2]octane with visible light or natural sunlight was discovered. This practical and efficient mode enables the production of aryl radicals under mild conditions, providing an unrealized opportunity for two-step para-selective C–H functionalization of complex arenes. The novel mode for generating aryl radicals via an EDA complex was well supported by UV-vis absorbance measurements, nuclear magnetic resonance titration experiments, and density functional theory (DFT) calculations. The method was applied to the regio- and stereo-selective arylation of various N-heterocycles under mild conditions, yielding an assembly of challengingly linked heteroaryl–(hetero)aryl products. Remarkably, the meaningful couplings of bioactive molecules with structurally complex drugs or agricultural pharmaceuticals were achieved to display favorable in vitro antitumor activities, which will be of great value in academia or industry.

General photoactivation of EDA complexes between arylsulfonium salts and 1,4-diazabicyclo[2.2.2]octane was discovered. This practical mode enables the generation of aryl radicals for C–H functionalization of arenes.     

Enhancing cell membrane phase separation for inhibiting cancer metastasis with a stimuli-responsive DNA nanodevice

Phase separation in cell membranes promotes the assembly of transmembrane receptors to initiate signal transduction in response to environmental cues. Many cellular behaviors are manipulated by promoting membrane phase separation through binding to multivalent extracellular ligands. However, available extracellular molecule tools that enable manipulating the clustering of transmembrane receptors in a controllable manner are rare. In the present study, we report a DNA nanodevice that enhances membrane phase separation through the clustering of dynamic lipid rafts. This DNA nanodevice is anchored in the lipid raft region of the cell membrane and initiated by ATP. In a tumor microenvironment, this device could be activated to form a long DNA duplex on the cell membrane, which not only enhances membrane phase separation, but also blocks the interaction between the transmembrane surface adhesion receptor and extracellular matrix, leading to reduced migration. We demonstrate that the ATP-activated DNA nanodevice could inhibit cancer cell migration both in vitro and in vivo. The concept of using DNA to regulate membrane phase separation provides new possibilities for manipulating versatile cell functions through rational design of functional DNA structures.

A DNA nanodevice is developed to enhance the cell membrane phase separation in a tumor microenvironment to weaken the formation of focal adhesion. As a result, the migration of cancer cells is inhibited both in vitro and in vivo.     

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.     

Quantum Information Entropies on Hyperbolic Single Potential Wells

In this work, we study the quantum information entropies for two different types of hyperbolic single potential wells. We first study the behaviors of the moving particle subject to two different hyperbolic potential wells through focusing on their wave functions. The shapes of these hyperbolic potentials are similar, but we notice that their momentum entropy densities change along with the width of each potential and the magnitude of position entropy density decreases when the momentum entropy magnitude increases. On the other hand, we illustrate the behaviors of their position and momentum entropy densities. Finally, we show the variation of position and momentum entropies Sx and Sp with the change of the potential well depth u and verify that their sum still satisfies the BBM inequality relation.     

Surface Functionalized Magnetic Nanoparticles as a Selective Sorbent for Affinity Fishing of PPAR-γ Ligands from Choerospondias axillaris

Coronary heart disease (CHD), which has developed into one of the major diseases, was reported to be treated by the target of peroxisome proliferators-activate receptor γ (PPAR-γ). As a natural medicine long used in the treatment of CHD, there are few studies on how to screen the target active compounds with high specific activity from Choerospondias axillaris. To advance the pace of research on target-specific active compounds in natural medicines, we have combined magnetic ligand fishing and functionalized nano-microspheres to investigate the active ingredients of PPAR-γ targets in Choerospondias axillaris. The PPAR-γ functionalized magnetic nano-microspheres have been successfully synthesized and characterized by vibrating sample magnetometer (VSM), scanning electron microscopy (SEM), and transmission electron microscopy (TEM). The specificity, reusability, and reproducibility of the nano-microspheres were investigated with the help of the specific binding of rosiglitazone to PPAR-γ. In addition, the incubation temperature and the pH of the buffer solution in the magnetic ligand fishing were optimized to improve the specific adsorption efficiency of the analytes. Finally, with the aid of ultraperformance liquid chromatography plus Q-Exactive Orbitrap tandem mass spectrometry (UHPLC-Q-Exactive Orbitrap-MS/MS), the 16 active ligands including 9 organic acids, 5 flavonoids, and 2 phenols were found in the ethanolic extracts of Choerospondias axillaris. Therefore, the study can provide a successful precedent for realizing the designated extraction and rapid isolation of target-specific active ingredient groups in the complex mixtures.     

次级源和误差传感器布放对带弹性障板的充液直管声振复合有源控制的影响*

针对充液管路系统噪声有源控制问题,研究了次级源和误差传感器布放对带弹性障板的充液直管管路系统有源消声与有源消振复合控制效果的影响。基于声固耦合方法建立了带弹性障板的充液直管管路系统的有限元模型,在声激励下对比了次级声源布放对系统有源消声性能的影响,并在组合激励下分析了次级力源、次级声源和误差传感器布放对系统复合有源控制的影响。结果表明,非对称分布的次级声源容易激起管壁振动,进而带动障板振动,导致有源消声效果不佳;采用对称分布的次级声源可使低频段的降噪量提高10 dB以上。复合有源控制可进一步提升全频段的控制效果。通过增加振动误差传感器数量,可使绝大多数频点的降噪量提高1~20 dB不等。此外,在管壁上布放的两圈次级力源的间距小于管壁振动波长的1/4,且都不位于管壁振动节点附近时控制效果更好。     

A Novel Strategy for Regulating mRNA’s Degradation via Interfering the AUF1’s Binding to mRNA

The study on the mechanism and kinetics of mRNA degradation provides a new vision for chemical intervention on protein expression. The AU enrichment element (ARE) in mRNA 3′-UTR can be recognized and bound by the ARE binding protein (AU-rich Element factor (AUF1) to recruit RNase for degradation. In the present study, we proposed a novel strategy for expression regulation that interferes with the AUF1-RNA binding. A small-molecule compound, JNJ-7706621, was found to bind AUF1 protein and inhibit mRNA degradation by screening the commercial compound library. We discovered that JNJ-7706621 could inhibit the expression of AUF1 targeted gene IL8, an essential pro-inflammatory factor, by interfering with the mRNA homeostatic state. These studies provide innovative drug design strategies to regulate mRNA homeostasis.     

Designable assembly of atomically precise Al4O4 cubane supported mesoporous heterometallic architectures

Heterometallic cluster-based framework materials are of interest in terms of both their porous structures and multi-metallic reactivity. However, such materials have not yet been extensively investigated because of difficulties in their synthesis and structural characterization. Herein, we reported the designable synthesis of atomically precise heterometallic cluster-based framework compounds and their application as catalysts in aldol reactions. By using the synergistic coordination protocol, we successfully isolated a broad range of compounds with the general formula, [Al₄M₄O₄(L)₁₂(DABCO)₂] (L = carboxylates; DABCO = 1,4-diazabicyclo[2.2.2]-octane; M²⁺ = Co²⁺, Mn²⁺, Zn²⁺, Fe²⁺, Cd²⁺). The basic heterometallic building blocks contain unprecedented main-group γ-alumina moieties and surrounding unsaturated transition metal centers. Interestingly, the porosity and interpenetration of these frameworks can be rationally regulated through the unprecedented strategy of increment of the metal radius in addition to general introduction of sterically bulky groups on the ligand. Furthermore, these porous materials are effective catalysts for aldol reactions. This work provides a catalytic molecular model platform with accurate molecular bonding between the supporters and catalytically active metal ions.

Mesoporous heterometallic architectures are designed by the incorporation of the Al₄O₄ cubane and interpenetration regulation.     

Multi-Classifier Fusion Based on MI–SFFS for Cross-Subject Emotion Recognition

With the widespread use of emotion recognition, cross-subject emotion recognition based on EEG signals has become a hot topic in affective computing. Electroencephalography (EEG) can be used to detect the brain’s electrical activity associated with different emotions. The aim of this research is to improve the accuracy by enhancing the generalization of features. A Multi-Classifier Fusion method based on mutual information with sequential forward floating selection (MI_SFFS) is proposed. The dataset used in this paper is DEAP, which is a multi-modal open dataset containing 32 EEG channels and multiple other physiological signals. First, high-dimensional features are extracted from 15 EEG channels of DEAP after using a 10 s time window for data slicing. Second, MI and SFFS are integrated as a novel feature-selection method. Then, support vector machine (SVM), k-nearest neighbor (KNN) and random forest (RF) are employed to classify positive and negative emotions to obtain the output probabilities of classifiers as weighted features for further classification. To evaluate the model performance, leave-one-out cross-validation is adopted. Finally, cross-subject classification accuracies of 0.7089, 0.7106 and 0.7361 are achieved by the SVM, KNN and RF classifiers, respectively. The results demonstrate the feasibility of the model by splicing different classifiers’ output probabilities as a portion of the weighted features.