Cold three-body collisions in hydrogen-hydrogen-alkali atomic system

We have studied hydrogen-hydrogen-alkali three-body systems in the adiabatic hyperspherical representation. For the spin-stretched case, there exists a single $X$H molecular state when $X$ is one of the bosonic alkali atoms: $^7$Li, $^{23}$Na, $^{39}$K, $^{87}$Rb and $^{133}$Cs. As a result, the {\em only} recombination process is the one that leads to formation of $X$H molecules, H+H+$X$$\rightarrow$$X$H+H, and such molecules will be stable against vibrational relaxation. We have calculated the collision rates for recombination and collision induced dissociation as well as the elastic cross-sections for H+$X$H collisions up to a temperature of 0.5 K, including the partial wave contributions from $J^\Pi$=$0^+$ to $5^-$. We have also found that there is just one three-body bound state for such systems for $J^\Pi$=$0^+$ and no bound states for higher angular momenta.Comment: 10 pages, 5 figures, 4 table

A Screen for Genetic Modifiers of Protein Phosphatase 1 Function in Drosophila Collective Cell Cohesion and Migration

Cells can migrate collectively in tightly or loosely-associated groups during tissue and organ formation, during embryonic development, in tumor metastases, and in wound healing. Drosophilaborder cellsserve as an excellent genetic model of collective cell migration inside a developing tissue. During ovarian development, 6-8 cells form the border cell cluster and migrate together as a cohesive group to reach the large oocyte. Previous experiments have shown that Nuclear inhibitor of Protein Serine Threonine Phosphatase 1 (NiPP1) causes border cells to separate into single cells, rather than stay in a group, and limits their ability to migrate. NiPP1 inhibits the activity of the Protein Phosphatase 1 (PP1) enzyme. Therefore, overexpressing NiPP1, though a modifier screen, will allows us identify genes that work with PP1 to promote the adhesion and collective migration of border cells. To carry out this genetic screen, females expressing NiPP1 in border cells are crossed to a collection of mutant strains, called deficiencies, that remove a number of genes. Ovaries from the resulting progeny are assayed for cohesion and migration of the border cell cluster by fluorescent microscopy. In this project, larger deficiencies have been shown to suppress (“revert to wild type”), or enhance (“make worse”) the mutant phenotype. The goal is to identify the exact gene required for this suppression or enhancement, using smaller deficiency mutant strains that delete only a few genes. Such mutant deficiencies represent candidate NiPP1 modifying genes. The candidate genes will be knocked out by RNAi one by one to definitively determine the genes required for PP1 function in cell-to-cell adhesion and collective migration. Because many Drosophilagenes have human homologs, these studies of PP1 have implications for collective cell migration in humans

Towards Understanding and Mitigating Dimensional Collapse in Heterogeneous Federated Learning

Federated learning aims to train models collaboratively across different clients without the sharing of data for privacy considerations. However, one major challenge for this learning paradigm is the {\em data heterogeneity} problem, which refers to the discrepancies between the local data distributions among various clients. To tackle this problem, we first study how data heterogeneity affects the representations of the globally aggregated models. Interestingly, we find that heterogeneous data results in the global model suffering from severe {\em dimensional collapse}, in which representations tend to reside in a lower-dimensional space instead of the ambient space. Moreover, we observe a similar phenomenon on models locally trained on each client and deduce that the dimensional collapse on the global model is inherited from local models. In addition, we theoretically analyze the gradient flow dynamics to shed light on how data heterogeneity result in dimensional collapse for local models. To remedy this problem caused by the data heterogeneity, we propose {\sc FedDecorr}, a novel method that can effectively mitigate dimensional collapse in federated learning. Specifically, {\sc FedDecorr} applies a regularization term during local training that encourages different dimensions of representations to be uncorrelated. {\sc FedDecorr}, which is implementation-friendly and computationally-efficient, yields consistent improvements over baselines on standard benchmark datasets. Code: https://github.com/bytedance/FedDecorr.Comment: camera ready version of ICLR 202

Open-source genomic analysis of Shiga-toxin–producing E. coli O104:H4

An outbreak caused by Shiga-toxin–producing Escherichia coli O104:H4 occurred in Germany in May and June of 2011, with more than 3000 persons infected. Here, we report a cluster of cases associated with a single family and describe an open-source genomic analysis of an isolate from one member of the family. This analysis involved the use of rapid, bench-top DNA sequencing technology, open-source data release, and prompt crowd-sourced analyses. In less than a week, these studies revealed that the outbreak strain belonged to an enteroaggregative E. coli lineage that had acquired genes for Shiga toxin 2 and for antibiotic resistance

Quantum Liouville theory and BTZ black hole entropy

In this paper I give an explicit conformal field theory description of (2+1)-dimensional BTZ black hole entropy. In the boundary Liouville field theory I investigate the reducible Verma modules in the elliptic sector, which correspond to certain irreducible representations of the quantum algebra U_q(sl_2) \odot U_{\hat{q}}(sl_2). I show that there are states that decouple from these reducible Verma modules in a similar fashion to the decoupling of null states in minimal models. Because ofthe nonstandard form of the Ward identity for the two-point correlation functions in quantum Liouville field theory, these decoupling states have positive-definite norms. The explicit counting from these states gives the desired Bekenstein-Hawking entropy in the semi-classical limit when q is a root of unity of odd order.Comment: LaTeX, 33 pages, 4 eps figure

The convergence analysis and error estimation for unique solution of a p-Laplacian fractional differential equation with singular decreasing nonlinearity

© 2018, The Author(s). In this paper, we focus on the convergence analysis and error estimation for the unique solution of a p-Laplacian fractional differential equation with singular decreasing nonlinearity. By introducing a double iterative technique, in the case of the nonlinearity with singularity at time and space variables, the unique positive solution to the problem is established. Then, from the developed iterative technique, the sequences converging uniformly to the unique solution are formulated, and the estimates of the error and the convergence rate are derived

A Method for Rapid Screening of Anilide-Containing AMPK Modulators Based on Computational Docking and Biological Validation

Adenosine 5′-monophsphate-activated protein kinase (AMPK) is a crucial energy sensor for maintaining cellular homeostasis. Targeting AMPK may provide an alternative approach in treatment of various diseases like cancer, diabetes, and neurodegenerations. Accordingly, novel AMPK activators are frequently identified from natural products in recent years. However, most of such AMPK activators are interacting with AMPK in an indirect manner, which may cause off-target effects. Therefore, the search of novel direct AMPK modulators is inevitable and effective screening methods are needed. In this report, a rapid and straightforward method combining the use of in silico and in vitro techniques was established for selecting and categorizing huge amount of compounds from chemical library for targeting AMPK modulators. A new class of direct AMPK modulator have been discovered which are anilides or anilide-like compounds. In total 1,360,000 compounds were virtually screened and 17 compounds were selected after biological assays. Lipinski’s rule of five assessment suggested that, 13 out of the 17 compounds are demonstrating optimal bioavailability. Proton acceptors constituting the structure of these compounds and hydrogen bonds with AMPK in the binding site appeared to be the important factors determining the efficacy of these compounds

Noncoding deletions reveal a gene that is critical for intestinal function.

Large-scale genome sequencing is poised to provide a substantial increase in the rate of discovery of disease-associated mutations, but the functional interpretation of such mutations remains challenging. Here we show that deletions of a sequence on human chromosome 16 that we term the intestine-critical region (ICR) cause intractable congenital diarrhoea in infants1,2. Reporter assays in transgenic mice show that the ICR contains a regulatory sequence that activates transcription during the development of the gastrointestinal system. Targeted deletion of the ICR in mice caused symptoms that recapitulated the human condition. Transcriptome analysis revealed that an unannotated open reading frame (Percc1) flanks the regulatory sequence, and the expression of this gene was lost in the developing gut of mice that lacked the ICR. Percc1-knockout mice displayed phenotypes similar to those observed upon ICR deletion in mice and patients, whereas an ICR-driven Percc1 transgene was sufficient to rescue the phenotypes found in mice that lacked the ICR. Together, our results identify a gene that is critical for intestinal function and underscore the need for targeted in vivo studies to interpret the growing number of clinical genetic findings that do not affect known protein-coding genes

Knocking-Down Cyclin A2 by siRNA Suppresses Apoptosis and Switches Differentiation Pathways in K562 Cells upon Administration with Doxorubicin

Cyclin A2 is critical for the initiation of DNA replication, transcription and cell cycle regulation. Cumulative evidences indicate that the deregulation of cyclin A2 is tightly linked to the chromosomal instability, neoplastic transformation and tumor proliferation. Here we report that treatment of chronic myelogenous leukaemia K562 cells with doxorubicin results in an accumulation of cyclin A2 and follows by induction of apoptotic cell death. To investigate the potential preclinical relevance, K562 cells were transiently transfected with the siRNA targeting cyclin A2 by functionalized single wall carbon nanotubes. Knocking down the expression of cyclin A2 in K562 cells suppressed doxorubicin-induced growth arrest and cell apoptosis. Upon administration with doxorubicin, K562 cells with reduced cyclin A2 showed a significant decrease in erythroid differentiation, and a small fraction of cells were differentiated along megakaryocytic and monocyte-macrophage pathways. The results demonstrate the pro-apoptotic role of cyclin A2 and suggest that cyclin A2 is a key regulator of cell differentiation. To the best of our knowledge, this is the first report that knocking down expression of one gene switches differentiation pathways of human myeloid leukemia K562 cells