VORTEX: Physics-Driven Data Augmentations Using Consistency Training for Robust Accelerated MRI Reconstruction

Deep neural networks have enabled improved image quality and fast inference times for various inverse problems, including accelerated magnetic resonance imaging (MRI) reconstruction. However, such models require a large number of fully-sampled ground truth datasets, which are difficult to curate, and are sensitive to distribution drifts. In this work, we propose applying physics-driven data augmentations for consistency training that leverage our domain knowledge of the forward MRI data acquisition process and MRI physics to achieve improved label efficiency and robustness to clinically-relevant distribution drifts. Our approach, termed VORTEX, (1) demonstrates strong improvements over supervised baselines with and without data augmentation in robustness to signal-to-noise ratio change and motion corruption in data-limited regimes; (2) considerably outperforms state-of-the-art purely image-based data augmentation techniques and self-supervised reconstruction methods on both in-distribution and out-of-distribution data; and (3) enables composing heterogeneous image-based and physics-driven data augmentations. Our code is available at https://github.com/ad12/meddlr.Comment: Accepted to MIDL 202

Solving the strong CP problem with supersymmetry

We propose a new solution to the strong CP problem based on supersymmetric non-renormalization theorems. CP is broken spontaneously and it's breaking is communicated to the MSSM by radiative corrections. The strong CP phase is protected by a susy non-renormalization theorem and remains exactly zero while loops can generate a large CKM phase from wave function renormalization. We present a concrete model as an example but stress that our framework is general. We also discuss constraints on susy breaking and point out experimental signatures.Comment: 12 pages, 2 figures, references adde

Theta Vacua, QCD Sum Rules, and the Neutron Electric Dipole Moment

We present a detailed study of the electric dipole moment of the neutron induced by a vacuum theta angle within the framework of QCD sum rules. At next-to-next-to leading order in the operator product expansion, we find the result d_n(\theta) = 2.4 x 10^{-16} \theta e cm, to approximately 40% precision. With the current experimental bound this translates into a limit on the theta parameter of |\theta| < 3 x 10^{-10}. We compare this result with the long-standing estimates obtained within chiral perturbation theory, and observe a numerical similarity, but also significant differences in the source of the dominant contribution.Comment: 23 pages, latex; v3: references added; v4: missing overall factor of two reinstate

Theta angle versus CP violation in the leptonic sector

Assuming that the axion mechanism of solving the strong CP problem does not exist and the vanishing of theta at tree level is achieved by some model-building means, we study the naturalness of having large CP-violating sources in the leptonic sector. We consider the radiative mechanisms which transfer a possibly large CP-violating phase in the leptonic sector to the theta parameter. It is found that large theta cannot be induced in the models with one Higgs doublet as at least three loops are required in this case. In the models with two or more Higgs doublets the dominant source of theta is the phases in the scalar potential, induced by CP violation in leptonic sector. Thus, in the MSSM framework the imaginary part of the trilinear soft-breaking parameter A_l generates the corrections to the theta angle already at one loop. These corrections are large, excluding the possibility of large phases, unless the universality in the slepton sector is strongly violated.Comment: 5 pages, 2 figure

Self-Supervised Discovery of Anatomical Shape Landmarks

Statistical shape analysis is a very useful tool in a wide range of medical and biological applications. However, it typically relies on the ability to produce a relatively small number of features that can capture the relevant variability in a population. State-of-the-art methods for obtaining such anatomical features rely on either extensive preprocessing or segmentation and/or significant tuning and post-processing. These shortcomings limit the widespread use of shape statistics. We propose that effective shape representations should provide sufficient information to align/register images. Using this assumption we propose a self-supervised, neural network approach for automatically positioning and detecting landmarks in images that can be used for subsequent analysis. The network discovers the landmarks corresponding to anatomical shape features that promote good image registration in the context of a particular class of transformations. In addition, we also propose a regularization for the proposed network which allows for a uniform distribution of these discovered landmarks. In this paper, we present a complete framework, which only takes a set of input images and produces landmarks that are immediately usable for statistical shape analysis. We evaluate the performance on a phantom dataset as well as 2D and 3D images.Comment: Early accept at MICCAI 202

Strong-weak CP hierarchy from non-renormalization theorems

We point out that the hierarchy between the measured values of the CKM phase and the strong CP phase has a natural origin in supersymmetry with spontaneous CP violation and low energy supersymmetry breaking. The underlying reason is simple and elegant: in supersymmetry the strong CP phase is protected by an exact non-renormalization theorem while the CKM phase is not. We present explicit examples of models which exploit this fact and discuss corrections to the non-renormalization theorem in the presence of supersymmetry breaking. This framework for solving the strong CP problem has generic predictions for the superpartner spectrum, for CP and flavor violation, and predicts a preferred range of values for electric dipole moments.Comment: 36 pages, 3 figure

NF-kappaB Mediated Transcriptional Repression of Acid Modifying Hormone Gastrin

Helicobacter pylori is a major pathogen associated with the development of gastroduodenal diseases. It has been reported that H. pylori induced pro-inflammatory cytokine IL1B is one of the various modulators of acid secretion in the gut. Earlier we reported that IL1B-activated NFkB down-regulates gastrin, the major hormonal regulator of acid secretion. In this study, the probable pathway by which IL1B induces NFkB and affects gastrin expression has been elucidated. IL1B-treated AGS cells showed nine-fold activation of MyD88 followed by phosphorylation of TAK1 within 15 min of IL1B treatment. Furthermore, it was observed that activated TAK1 significantly up-regulates the NFkB subunits p50 and p65. Ectopic expression of NFkB p65 in AGS cells resulted in about nine-fold transcriptional repression of gastrin both in the presence and absence of IL1B. The S536A mutant of NFkB p65 is significantly less effective in repressing gastrin. These observations show that a functional NFkB p65 is important for IL1B-mediated repression of gastrin. ChIP assays revealed the presence of HDAC1 and NFkB p65 along with NCoR on the gastrin promoter. Thus, the study provides mechanistic insight into the IL1B-mediated gastrin repression via NFk

Tuneable resolution as a systems biology approach for multi-scale, multi-compartment computational models

The use of multi-scale mathematical and computational models to study complex biological processes is becoming increasingly productive. Multi-scale models span a range of spatial and/or temporal scales and can encompass multi-compartment (e.g., multi-organ) models. Modeling advances are enabling virtual experiments to explore and answer questions that are problematic to address in the wet-lab. Wet-lab experimental technologies now allow scientists to observe, measure, record, and analyze experiments focusing on different system aspects at a variety of biological scales. We need the technical ability to mirror that same flexibility in virtual experiments using multi-scale models. Here we present a new approach, tuneable resolution, which can begin providing that flexibility. Tuneable resolution involves fine- or coarse-graining existing multi-scale models at the user's discretion, allowing adjustment of the level of resolution specific to a question, an experiment, or a scale of interest. Tuneable resolution expands options for revising and validating mechanistic multi-scale models, can extend the longevity of multi-scale models, and may increase computational efficiency. The tuneable resolution approach can be applied to many model types, including differential equation, agent-based, and hybrid models. We demonstrate our tuneable resolution ideas with examples relevant to infectious disease modeling, illustrating key principles at work. WIREs Syst Biol Med 2014, 6:225–245. doi:10.1002/wsbm.1270 How to cite this article: WIREs Syst Biol Med 2014, 6:289–309. doi:10.1002/wsbm.127

Deciphering the modulation of gene expression by type I and II interferons combining 4sU-tagging, translational arrest and in silico promoter analysis

Interferons (IFN) play a pivotal role in innate immunity, orchestrating a cell-intrinsic anti-pathogenic state and stimulating adaptive immune responses. The complex interplay between the primary response to IFNs and its modulation by positive and negative feedback loops is incompletely understood. Here, we implement the combination of high-resolution gene-expression profiling of nascent RNA with translational inhibition of secondary feedback by cycloheximide. Unexpectedly, this approach revealed a prominent role of negative feedback mechanisms during the immediate (≤60 min) IFNα response. In contrast, a more complex picture involving both negative and positive feedback loops was observed on IFNγ treatment. IFNγ-induced repression of genes associated with regulation of gene expression, cellular development, apoptosis and cell growth resulted from cycloheximide-resistant primary IFNγ signalling. In silico promoter analysis revealed significant overrepresentation of SP1/SP3-binding sites and/or GC-rich stretches. Although signal transducer and activator of transcription 1 (STAT1)-binding sites were not overrepresented, repression was lost in absence of STAT1. Interestingly, basal expression of the majority of these IFNγ-repressed genes was dependent on STAT1 in IFN-naïve fibroblasts. Finally, IFNγ-mediated repression was also found to be evident in primary murine macrophages. IFN-repressed genes include negative regulators of innate and stress response, and their decrease may thus aid the establishment of a signalling perceptive milieu.Fil: Trilling, Mirko. Universitat Duisburg - Essen; AlemaniaFil: Bellora, Nicolás. Parque de Investigación Biomédica de Barcelona; España. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Patagonia Norte. Instituto de Investigación en Biodiversidad y Medioambiente; ArgentinaFil: Rutkowski, Andrzej J.. University of Cambridge; Reino UnidoFil: de Graaf, Miranda. University of Cambridge; Reino UnidoFil: Dickinson, Paul. University Of Edinburgh; Reino UnidoFil: Robertson, Kevin. University Of Edinburgh; Reino UnidoFil: Da Costa, Olivia Prazeres. Universitat Technical Zu Munich; AlemaniaFil: Ghazal, Peter. University Of Edinburgh; Reino UnidoFil: Friedel, Caroline C.. Ludwig-Maximilians-University Munich; AlemaniaFil: Albà, M. Mar. Institució Catalana de Recerca I Estudis Avancats; España. Parque de Investigación Biomédica de Barcelona; EspañaFil: Dölken, Lars. University of Cambridge; Reino Unid

Transcriptional Analysis of Shewanella oneidensis MR-1 with an Electrode Compared to Fe(III)Citrate or Oxygen as Terminal Electron Acceptor

Shewanella oneidensis is a target of extensive research in the fields of bioelectrochemical systems and bioremediation because of its versatile metabolic capabilities, especially with regard to respiration with extracellular electron acceptors. The physiological activity of S. oneidensis to respire at electrodes is of great interest, but the growth conditions in thin-layer biofilms make physiological analyses experimentally challenging. Here, we took a global approach to evaluate physiological activity with an electrode as terminal electron acceptor for the generation of electric current. We performed expression analysis with DNA microarrays to compare the overall gene expression with an electrode to that with soluble iron(III) or oxygen as the electron acceptor and applied new hierarchical model-based statistics for the differential expression analysis. We confirmed the differential expression of many genes that have previously been reported to be involved in electrode respiration, such as the entire mtr operon. We also formulate hypotheses on other possible gene involvements in electrode respiration, for example, a role of ScyA in inter-protein electron transfer and a regulatory role of the cbb3-type cytochrome c oxidase under anaerobic conditions. Further, we hypothesize that electrode respiration imposes a significant stress on S. oneidensis, resulting in higher energetic costs for electrode respiration than for soluble iron(III) respiration, which fosters a higher metabolic turnover to cover energy needs. Our hypotheses now require experimental verification, but this expression analysis provides a fundamental platform for further studies into the molecular mechanisms of S. oneidensis electron transfer and the physiologically special situation of growth on a poised-potential surface