Large Domain Motions in Ago Protein Controlled by the Guide DNA-Strand Seed Region Determine the Ago-DNA-mRNA Complex Recognition Process

The recognition mechanism and cleavage activity of argonaute (Ago), miRNA, and mRNA complexes are the core processes to the small non-coding RNA world. The 5′ nucleation at the ‘seed’ region (position 2–8) of miRNA was believed to play a significant role in guiding the recognition of target mRNAs to the given miRNA family. In this paper, we have performed all-atom molecular dynamics simulations of the related and recently revealed Ago-DNA:mRNA ternary complexes to study the dynamics of the guide-target recognition and the effect of mutations by introducing “damaging” C·C mismatches at different positions in the seed region of the DNA-RNA duplex. Our simulations show that the A-form-like helix duplex gradually distorts as the number of seed mismatches increases and the complex can survive no more than two such mismatches. Severe distortions of the guide-target heteroduplex are observed in the ruinous 4-sites mismatch mutant, which give rise to a bending motion of the PAZ domain along the L1/L2 “hinge-like” connection segment, resulting in the opening of the nucleic-acid-binding channel. These long-range interactions between the seed region and PAZ domain, moderated by the L1/L2 segments, reveal the central role of the seed region in the guide-target strands recognition: it not only determines the guide-target heteroduplex’s nucleation and propagation, but also regulates the dynamic motions of Ago domains around the nucleic-acid-binding channel

NNQS-Transformer: an Efficient and Scalable Neural Network Quantum States Approach for Ab initio Quantum Chemistry

Neural network quantum state (NNQS) has emerged as a promising candidate for quantum many-body problems, but its practical applications are often hindered by the high cost of sampling and local energy calculation. We develop a high-performance NNQS method for \textit{ab initio} electronic structure calculations. The major innovations include: (1) A transformer based architecture as the quantum wave function ansatz; (2) A data-centric parallelization scheme for the variational Monte Carlo (VMC) algorithm which preserves data locality and well adapts for different computing architectures; (3) A parallel batch sampling strategy which reduces the sampling cost and achieves good load balance; (4) A parallel local energy evaluation scheme which is both memory and computationally efficient; (5) Study of real chemical systems demonstrates both the superior accuracy of our method compared to state-of-the-art and the strong and weak scalability for large molecular systems with up to $120$ spin orbitals.Comment: Accepted by SC'2

Counterpart Fairness -- Addressing Systematic between-group Differences in Fairness Evaluation

When using machine learning (ML) to aid decision-making, it is critical to ensure that an algorithmic decision is fair, i.e., it does not discriminate against specific individuals/groups, particularly those from underprivileged populations. Existing group fairness methods require equal group-wise measures, which however fails to consider systematic between-group differences. The confounding factors, which are non-sensitive variables but manifest systematic differences, can significantly affect fairness evaluation. To mitigate this problem, we believe that a fairness measurement should be based on the comparison between counterparts (i.e., individuals who are similar to each other with respect to the task of interest) from different groups, whose group identities cannot be distinguished algorithmically by exploring confounding factors. We have developed a propensity-score-based method for identifying counterparts, which prevents fairness evaluation from comparing "oranges" with "apples". In addition, we propose a counterpart-based statistical fairness index, termed Counterpart-Fairness (CFair), to assess fairness of ML models. Empirical studies on the Medical Information Mart for Intensive Care (MIMIC)-IV database were conducted to validate the effectiveness of CFair. We publish our code at \url{https://github.com/zhengyjo/CFair}.Comment: 18 pages, 5 figures, 5 table

Advanced Biosensing towards Real-Time Imaging of Protein Secretion from Single Cells

Protein secretion of cells plays a vital role in intercellular communication. The abnormality and dysfunction of cellular protein secretion are associated with various physiological disorders, such as malignant proliferation of cells, aberrant immune function, and bone marrow failure. The heterogeneity of protein secretion exists not only between varying populations of cells, but also in the same phenotype of cells. Therefore, characterization of protein secretion from single cell contributes not only to the understanding of intercellular communication in immune effector, carcinogenesis and metastasis, but also to the development and improvement of diagnosis and therapy of relative diseases. In spite of abundant highly sensitive methods that have been developed for the detection of secreted proteins, majority of them fall short in providing sufficient spatial and temporal resolution for comprehensive profiling of protein secretion from single cells. The real-time imaging techniques allow rapid acquisition and manipulation of analyte information on a 2D plane, providing high spatiotemporal resolution. Here, we summarize recent advances in real-time imaging of secretory proteins from single cell, including label-free and labelling techniques, shedding light on the development of simple yet powerful methodology for real-time imaging of single-cell protein secretion

A Novel Train-to-Train Communication Model Design Based on Multihop in High-Speed Railway

Railway telematics applications are currently attracting attention and are under intense research. Reliable railway telematics applications increasingly tend to require a subsidiary means to help existent control system make train operation safer and more efficient. Since 2006, train-to-train communication has been studied to respond to such requirements. A key characteristic of train-to-train communication is that operation control to avoid possible accidents is conducted among trains without help of a base station. This paper proposes a novel train-to-train communication model in a physical layer based on multihop and cooperation, taking a high-speed railway propagation channel into account. The mechanism of this model lies in the idea that a source train uses trains on other tracks as relays to transmit signals to destination train on the same track. Based on occurrence of these potential relays, such mechanism can be divided into three cases. In each case, BER is applied to evaluate properties of the proposed communication model. Simulation results show that BER of the train-to-train communication model decreases to 10−6 when SNR is 10 dB and that the minimum receiving voltage of this model is −84 dBm, which is 8 dBm lower than the standards established by the International Union of Railways (UIC) in a high-speed railway scenario

Fast shimming algorithm based on Bayesian optimization for magnetic resonance based dark matter search

The sensitivity and accessible mass range of magnetic resonance searches for axionlike dark matter depends on the homogeneity of applied magnetic fields. Optimizing homogeneity through shimming requires exploring a large parameter space which can be prohibitively time consuming. We have automated the process of tuning the shim-coil currents by employing an algorithm based on Bayesian optimization. This method is especially suited for applications where the duration of a single optimization step prohibits exploring the parameter space extensively or when there is no prior information on the optimal operation point. Using the Cosmic Axion Spin Precession Experiment (CASPEr)-gradient low-field apparatus, we show that for our setup this method converges after approximately 30 iterations to a sub-10 parts-per-million field homogeneity which is desirable for our dark matter search

Biomimetic Metal-Organic Nanoparticles Prepared with a 3D-Printed Microfluidic Device as a Novel Formulation for Disulfiram-Based Therapy Against Breast Cancer

Disulfiram (DSF) is currently tested in several clinical trials for cancer treatment in combination with cop-per (Cu) ions. Usually, DSF and Cu are administered in two separate formulations. In the body, DSF andCu ions form diethyldithiocarbamate copper complex [Cu(DDC)2] which has potent antitumor activities.However, the “two formulation” approach often achieved low Cu(DDC)2 concentration at tumor regions and resulted in compromised anticancer efficacy. Therefore, preformed Cu(DDC)2 complex administered in a single formulation will have better anticancer efficacy. However, the poor aqueous solubility of Cu(DDC)2 is a significant challenge for its clinical use. In this work, a biomimetic nanoparticle formulation of Cu(DDC)2 was produced with a novel SMILE (Stabilized Metal Ion Ligand complex) method developed in our laboratory to address the drug delivery challenges. The Metal-organic Nanoparticle (MON) is composed of Cu(DDC)2 metal-organic complex core and surface decorated bovine serum albumin (BSA). Importantly, we designed a 3D-printed microfluidic device to further improve the fabrication of BSA/Cu(DDC)2 MONs. This method could precisely control the MON preparation process and also has great potential for large scale production of Cu(DDC)2 MON formulations. We also used a computational modeling approach to simulate the MON formation process in the microfluidic device. The optimized BSA/Cu(DDC)2 MONs demonstrated good physicochemical properties. The MONs also showed potent antitumor activities in the breast cancer cell monolayers as well as the 3D-cultured tumor spheroids. The BSA/Cu(DDC)2 MONs also effectively inhibited the growth of tumors in an orthotopic 4T1 breast tumor model. This current study provided a novel method to prepare a biomimetic MON formulation for DSF/Cu cancer therapy .© 2019 Elsevier Ltd. All rights reserved

Deconfined quantum critical point lost in pressurized SrCu2(BO3)2

In the field of correlated electron materials, the relation between the resonating spin singlet and antiferromagnetic states has long been an attractive topic for understanding of the interesting macroscopic quantum phenomena, such as the ones emerging from magnetic frustrated materials, antiferromagnets and high-temperature superconductors. SrCu2(BO3)2 is a well-known quantum magnet, and it is theoretically expected to be the candidate of correlated electron material for clarifying the existence of a pressure-induced deconfined quantum critical point (DQCP), featured by a continuous quantum phase transition, between the plaquette-singlet (PS) valence bond solid phase and the antiferromagnetic (AF) phase. However, the real nature of the transition is yet to be identified experimentally due to the technical challenge. Here we show the experimental results for the first time, through the state-of-the-art high-pressure heat capacity measurement, that the PS-AF phase transition of the pressurized SrCu2(BO3)2 at zero field is clearly a first-order one. Our result clarifies the more than two-decade long debates about this key issue, and resonates nicely with the recent quantum entanglement understanding that the theoretically predicted DQCPs in representative lattice models are actually a first-order transition. Intriguingly, we also find that the transition temperatures of the PS and AF phase meet at the same pressure-temperature point, which signifies a bi-critical point as those observed in Fe-based superconductor and heavy-fermion compound, and constitutes the first experimental discovery of the pressure-induced bi-critical point in frustrated magnets. Our results provide fresh information for understanding the evolution among different spin states of correlated electron materials under pressure.Comment: 6 pages, 4 figure

Risk Information Disclosure and Work-Life Balance

　本稿では，長時間労働や，サービス残業など，ワークライフバランスを阻害する働き方の諸問題について，リスク情報の開示という観点から，企業がどのように情報開示を行っているかを考察する.まず第一に，企業によるリスク情報の開示（リスクマネジメントの組織体制，会社法規定に基づく「損失の管理に関する規定その他の体制」，内閣府令に基づく「事業等のリスク」）について概観する．第二に，ワークライフバランスを阻害する働き方をめぐる問題について検討し，ワークライフバランスについてどのようにWEBサイト上で情報開示が行われているかを考察する.考察を通じて，①ワークライフバランスの不全はリスク情報の開示項目の対象とはされていないこと，②ワークライフバランスについて記述する場合であっても，長時間労働防止について具体的な施策を開示している企業は多くないことが確認できた． This study analyzes how companies disclose information on poor work-life balance such as in the case of excessive work hours. First, we study whether the companies consider poor work-life balance problems as an object of risk information disclosure. Second, we discuss the way people work in Japanese society. The results of our survey suggest that companies should treat poor work-life balance issues as an object of risk information disclosure