Methyl-Rotation Dynamics in Metal-Organic Frameworks Probed with Terahertz Spectroscopy

In ZIF-8 and its cobalt analogue ZIF-67, the imidazolate methyl-groups, which point directly into the void space, have been shown to freely rotate - even down to cryogenic temperatures. Using a combination of experimental terahertz time-domain spectroscopy, low-frequency Raman spectroscopy, and state-of-the-art ab initio simulations, the methyl-rotor dynamics in ZIF-8 and ZIF-67 are fully characterized within the context of a quantum-mechanical hindered-rotor model. The results lend insight into the fundamental origins of the experimentally observed methyl rotor dynamics, and provide valuable insight into the nature of the weak interactions present within this important class of materials

Long-Range Four-body Interactions in Structured Nonlinear Photonic Waveguides

Multi-photon dynamics beyond linear optical materials are of significant fundamental and technological importance in quantum information processing. However, it remains largely unexplored in nonlinear waveguide QED. In this work, we theoretically propose a structured nonlinear waveguide in the presence of staggered photon-photon interactions, which supports two branches of gaped bands for doublons (i.e., spatially bound-photon-pair states). In contrast to linear waveguide QED systems, we identify two important contributions to its dynamical evolution, i.e., single-photon bound states (SPBSs) and doublon bound states (DBSs). Most remarkably, the nonlinear waveguide can mediate the long-range four-body interactions between two emitter pairs, even in the presence of disturbance from SPBS. By appropriately designing system's parameters, we can achieve high-fidelity four-body Rabi oscillations mediated only by virtual doublons in DBSs. Our findings pave the way for applying structured nonlinear waveguide QED in multi-body quantum information processing and quantum simulations among remote sites.Comment: 18 pages; 9 figure

Metabolic interactions between dynamic bacterial subpopulations

Individual microbial species are known to occupy distinct metabolic niches within multi-species communities. However, it has remained largely unclear whether metabolic specialization can similarly occur within a clonal bacterial population. More specifically, it is not clear what functions such specialization could provide and how specialization could be coordinated dynamically. Here, we show that exponentially growing Bacillus subtilis cultures divide into distinct interacting metabolic subpopulations, including one population that produces acetate, and another population that differentially expresses metabolic genes for the production of acetoin, a pH-neutral storage molecule. These subpopulations exhibit distinct growth rates and dynamic interconversion between states. Furthermore, acetate concentration influences the relative sizes of the different subpopulations. These results show that clonal populations can use metabolic specialization to control the environment through a process of dynamic, environmentally-sensitive state-switching

China and the WTO: Progress, Perils, and Prospects

In November 2001, member states of the World Trade Organization (WTO) approved the proposal to admit China to the international trading body. After fifteen years of exhaustive negotiations, China finally became the 143rd member of the WTO on December 11, 2001. To reflect on this event, this panel brings together six China experts to explore the ramifications of China\u27s accession to the WTO. Among the issues addressed are whether China is making progress in its compliance with the WTO requirements, whether China is suffering setbacks in the socio-economic arena, whether there are any prospects for democratic reforms and stronger human rights and environmental protection in the country, and what the WTO accession means to China\u27s neighbors and the global community

DeepsmirUD: Prediction of Regulatory Effects on microRNA Expression Mediated by Small Molecules Using Deep Learning

Aberrant miRNA expression has been associated with a large number of human diseases. Therefore, targeting miRNAs to regulate their expression levels has become an important therapy against diseases that stem from the dysfunction of pathways regulated by miRNAs. In recent years, small molecules have demonstrated enormous potential as drugs to regulate miRNA expression (i.e., SM-miR). A clear understanding of the mechanism of action of small molecules on the upregulation and downregulation of miRNA expression allows precise diagnosis and treatment of oncogenic pathways. However, outside of a slow and costly process of experimental determination, computational strategies to assist this on an ad hoc basis have yet to be formulated. In this work, we developed, to the best of our knowledge, the first cross-platform prediction tool, DeepsmirUD, to infer small-molecule-mediated regulatory effects on miRNA expression (i.e., upregulation or downregulation). This method is powered by 12 cutting-edge deep-learning frameworks and achieved AUC values of 0.843/0.984 and AUCPR values of 0.866/0.992 on two independent test datasets. With a complementarily constructed network inference approach based on similarity, we report a significantly improved accuracy of 0.813 in determining the regulatory effects of nearly 650 associated SM-miR relations, each formed with either novel small molecule or novel miRNA. By further integrating miRNA–cancer relationships, we established a database of potential pharmaceutical drugs from 1343 small molecules for 107 cancer diseases to understand the drug mechanisms of action and offer novel insight into drug repositioning. Furthermore, we have employed DeepsmirUD to predict the regulatory effects of a large number of high-confidence associated SM-miR relations. Taken together, our method shows promise to accelerate the development of potential miRNA targets and small molecule drugs

Metabolic interactions between dynamic bacterial subpopulations

Individual microbial species are known to occupy distinct metabolic niches within multi-species communities. However, it has remained largely unclear whether metabolic specialization can similarly occur within a clonal bacterial population. More specifically, it is not clear what functions such specialization could provide and how specialization could be coordinated dynamically. Here, we show that exponentially growing Bacillus subtilis cultures divide into distinct interacting metabolic subpopulations, including one population that produces acetate, and another population that differentially expresses metabolic genes for the production of acetoin, a pH-neutral storage molecule. These subpopulations exhibit distinct growth rates and dynamic interconversion between states. Furthermore, acetate concentration influences the relative sizes of the different subpopulations. These results show that clonal populations can use metabolic specialization to control the environment through a process of dynamic, environmentally-sensitive state-switching

Meta-Learning with Dynamic-Memory-Based Prototypical Network for Few-Shot Event Detection

Event detection (ED), a sub-task of event extraction, involves identifying triggers and categorizing event mentions. Existing methods primarily rely upon supervised learning and require large-scale labeled event datasets which are unfortunately not readily available in many real-life applications. In this paper, we consider and reformulate the ED task with limited labeled data as a Few-Shot Learning problem. We propose a Dynamic-Memory-Based Prototypical Network (DMB-PN), which exploits Dynamic Memory Network (DMN) to not only learn better prototypes for event types, but also produce more robust sentence encodings for event mentions. Differing from vanilla prototypical networks simply computing event prototypes by averaging, which only consume event mentions once, our model is more robust and is capable of distilling contextual information from event mentions for multiple times due to the multi-hop mechanism of DMNs. The experiments show that DMB-PN not only deals with sample scarcity better than a series of baseline models but also performs more robustly when the variety of event types is relatively large and the instance quantity is extremely small.Comment: Accepted by WSDM 202

Transcript-indexed ATAC-seq for precision immune profiling.

T cells create vast amounts of diversity in the genes that encode their T cell receptors (TCRs), which enables individual clones to recognize specific peptide-major histocompatibility complex (MHC) ligands. Here we combined sequencing of the TCR-encoding genes with assay for transposase-accessible chromatin with sequencing (ATAC-seq) analysis at the single-cell level to provide information on the TCR specificity and epigenomic state of individual T cells. By using this approach, termed transcript-indexed ATAC-seq (T-ATAC-seq), we identified epigenomic signatures in immortalized leukemic T cells, primary human T cells from healthy volunteers and primary leukemic T cells from patient samples. In peripheral blood CD4+ T cells from healthy individuals, we identified cis and trans regulators of naive and memory T cell states and found substantial heterogeneity in surface-marker-defined T cell populations. In patients with a leukemic form of cutaneous T cell lymphoma, T-ATAC-seq enabled identification of leukemic and nonleukemic regulatory pathways in T cells from the same individual by allowing separation of the signals that arose from the malignant clone from the background T cell noise. Thus, T-ATAC-seq is a new tool that enables analysis of epigenomic landscapes in clonal T cells and should be valuable for studies of T cell malignancy, immunity and immunotherapy

Transport in three-dimensional topological insulators: theory and experiment

This article reviews recent theoretical and experimental work on transport due to the surface states of three-dimensional topological insulators. The theoretical focus is on longitudinal transport in the presence of an electric field, including Boltzmann transport, quantum corrections and weak localization, as well as longitudinal and Hall transport in the presence of both electric and magnetic fields and/or magnetizations. Special attention is paid to transport at finite doping, to the $\pi$-Berry phase, which leads to the absence of backscattering, Klein tunneling and half-quantized Hall response. Signatures of surface states in ordinary transport and magnetotransport are clearly identified. The review also covers transport experiments of the past years, reviewing the initial obscuring of surface transport by bulk transport, and the way transport due to the surface states has increasingly been identified experimentally. Current and likely future experimental challenges are given prominence and the current status of the field is assessed.Comment: Review article to appear in Physica