Spatially and Temporally Directed Noise Cancellation Using Federated Learning

Machine learning models can be trained to cancel noise of diverse types or spectral characteristics, e.g. traffic noise, background chatter, etc. Such models are trained by feeding training data that includes labeled noise waveforms, which is an expensive and time-consuming procedure. Further, the effectiveness of such machine learning models is limited in canceling types of noise absent from training data. Trained models occupy significant amounts of memory which limits their use in consumer devices. This disclosure describes the use of federated learning techniques to train noise canceling models locally at diverse device locations and times. With user permission, the trained models are tagged with timestamp and location, such that when a user device has time or location matching a particular noise cancellation model, the particular model is provided to the user device. Noise cancellation on the user device is then performed with a compact machine learning model that is suited to the time and location of the user device

MUC1 O-glycosylation contributes to anoikis resistance in epithelial cancer cells

Anoikis is a fundamental cellular process for maintaining tissue homeostasis. Resistance to anoikis is a hallmark of oncogenic epithelial–mesenchymal transition and is a pre-requisite for metastasis. Previous studies have revealed that the heavily glycosylated mucin protein MUC1, which is overexpressed in all types of epithelial cancer cells, prevents anoikis initiation in response to loss of adhesion. This effect of MUC1 is largely attributed to its extracellular domain that provides cell surface anoikis-initiating molecules with a ‘homing’ microenvironment. The present study investigated the influence of O-glycosylation on MUC1 extracellular domain on MUC1-mediated cell resistance to anoikis. It shows that stable suppression of the Core 1Gal-transferase (C1GT) by shRNA substantially reduces O-glycosylation in MUC1-positively transfected human colon cancer HCT116 cells and in high MUC1-expressing SW620 cells. Suppression of C1GT significantly increased anoikis of the MUC1-positive, but not MUC1-negative, cells in response to suspended culture. This effect was shown to be associated with increased ligand accessibility to cell surface anoikis-initiating molecules such as E-cadherin, integrinβ1 and Fas. These results indicate that the extensive O-glycosylation on MUC1 extracellular domain contributes to MUC1-mediated cell resistance to anoikis by facilitating MUC1-mediated prohibition of activation of the cell surface anoikis-initiating molecules in response to loss of cell adhesion. This provides insight into the molecular mechanism of anoikis regulation and highlights the importance of cellular glycosylation in cancer progression and metastasis

Complex-based analysis of dysregulated cellular processes in cancer

Background: Differential expression analysis of (individual) genes is often used to study their roles in diseases. However, diseases such as cancer are a result of the combined effect of multiple genes. Gene products such as proteins seldom act in isolation, but instead constitute stable multi-protein complexes performing dedicated functions. Therefore, complexes aggregate the effect of individual genes (proteins) and can be used to gain a better understanding of cancer mechanisms. Here, we observe that complexes show considerable changes in their expression, in turn directed by the concerted action of transcription factors (TFs), across cancer conditions. We seek to gain novel insights into cancer mechanisms through a systematic analysis of complexes and their transcriptional regulation. Results: We integrated large-scale protein-interaction (PPI) and gene-expression datasets to identify complexes that exhibit significant changes in their expression across different conditions in cancer. We devised a log-linear model to relate these changes to the differential regulation of complexes by TFs. The application of our model on two case studies involving pancreatic and familial breast tumour conditions revealed: (i) complexes in core cellular processes, especially those responsible for maintaining genome stability and cell proliferation (e.g. DNA damage repair and cell cycle) show considerable changes in expression; (ii) these changes include decrease and countering increase for different sets of complexes indicative of compensatory mechanisms coming into play in tumours; and (iii) TFs work in cooperative and counteractive ways to regulate these mechanisms. Such aberrant complexes and their regulating TFs play vital roles in the initiation and progression of cancer.Comment: 22 pages, BMC Systems Biolog

Some Phenomenology of Intersecting D-Brane Models

We present some phenomenology of a new class of intersecting D-brane models. Soft SUSY breaking terms for these models are calculated in the u - moduli dominant SUSY breaking approach (in type IIA). In this case, the dependence of the soft terms on the Yukawas and Wilson lines drops out. These soft terms have a different pattern compared to the usual heterotic string models. Phenomenological implications for dark matter are discussed.Comment: 29 pages, 1 figure, References adde

Explaining the Electroweak Scale and Stabilizing Moduli in M Theory

In a recent paper \cite{Acharya:2006ia} it was shown that in $M$ theory vacua without fluxes, all moduli are stabilized by the effective potential and a stable hierarchy is generated, consistent with standard gauge unification. This paper explains the results of \cite{Acharya:2006ia} in more detail and generalizes them, finding an essentially unique de Sitter (dS) vacuum under reasonable conditions. One of the main phenomenological consequences is a prediction which emerges from this entire class of vacua: namely gaugino masses are significantly suppressed relative to the gravitino mass. We also present evidence that, for those vacua in which the vacuum energy is small, the gravitino mass, which sets all the superpartner masses, is automatically in the TeV - 100 TeV range.Comment: 73 pages, 39 figures, Minor typos corrected, Figures and References adde

Origins of Hidden Sector Dark Matter I: Cosmology

We present a systematic cosmological study of a universe in which the visible sector is coupled, albeit very weakly, to a hidden sector comprised of its own set of particles and interactions. Assuming that dark matter (DM) resides in the hidden sector and is charged under a stabilizing symmetry shared by both sectors, we determine all possible origins of weak-scale DM allowed within this broad framework. We show that DM can arise only through a handful of mechanisms, lending particular focus to Freeze-Out and Decay and Freeze-In, as well as their variations involving late time re-annihilations of DM and DM particle anti-particle asymmetries. Much like standard Freeze-Out, where the abundance of DM depends only on the annihilation cross-section of the DM particle, these mechanisms depend only on a very small subset of physical parameters, many of which may be measured directly at the LHC. In particular, we show that each DM production mechanism is associated with a distinctive window in lifetimes and cross-sections for particles which may be produced in the near future. We evaluate prospects for employing the LHC to definitively reconstruct the origin of DM in a companion paper.Comment: 32 pages, 19 figures; v2: references added, published versio

An Application-Based Performance Evaluation of NASAs Nebula Cloud Computing Platform

The high performance computing (HPC) community has shown tremendous interest in exploring cloud computing as it promises high potential. In this paper, we examine the feasibility, performance, and scalability of production quality scientific and engineering applications of interest to NASA on NASA's cloud computing platform, called Nebula, hosted at Ames Research Center. This work represents the comprehensive evaluation of Nebula using NUTTCP, HPCC, NPB, I/O, and MPI function benchmarks as well as four applications representative of the NASA HPC workload. Specifically, we compare Nebula performance on some of these benchmarks and applications to that of NASA s Pleiades supercomputer, a traditional HPC system. We also investigate the impact of virtIO and jumbo frames on interconnect performance. Overall results indicate that on Nebula (i) virtIO and jumbo frames improve network bandwidth by a factor of 5x, (ii) there is a significant virtualization layer overhead of about 10% to 25%, (iii) write performance is lower by a factor of 25x, (iv) latency for short MPI messages is very high, and (v) overall performance is 15% to 48% lower than that on Pleiades for NASA HPC applications. We also comment on the usability of the cloud platform

Identification of Selective Inhibitors of Cancer Stem Cells by High-Throughput Screening

Screens for agents that specifically kill epithelial cancer stem cells (CSCs) have not been possible due to the rarity of these cells within tumor cell populations and their relative instability in culture. We describe here an approach to screening for agents with epithelial CSC-specific toxicity. We implemented this method in a chemical screen and discovered compounds showing selective toxicity for breast CSCs. One compound, salinomycin, reduces the proportion of CSCs by >100-fold relative to paclitaxel, a commonly used breast cancer chemotherapeutic drug. Treatment of mice with salinomycin inhibits mammary tumor growth in vivo and induces increased epithelial differentiation of tumor cells. In addition, global gene expression analyses show that salinomycin treatment results in the loss of expression of breast CSC genes previously identified by analyses of breast tissues isolated directly from patients. This study demonstrates the ability to identify agents with specific toxicity for epithelial CSCs.National Cancer Institute (U.S.). Initiative for Chemical GeneticsBreast Cancer Research FoundationRoot, DavidBroad Institute of MIT and Harvard (RNAi Platform