Transcriptional regulation of SPROUTY 2 by MYB influences myeloid cell proliferation and stem cell properties by enhancing responsiveness to IL-3.

Myeloproliferative neoplasms (MPN), which overproduce blood cells in the bone marrow, have recently been linked with a genetically determined decrease in expression of the MYB transcription factor. Here, we use a mouse MYB knockdown model with an MPN-like phenotype to show how lower levels of MYB lead to stem cell characteristics in myeloid progenitors. The altered progenitor properties feature elevated cytokine responsiveness, especially to IL-3, which results from increased receptor expression and increased MAPK activity leading to enhanced phosphorylation of a key regulator of protein synthesis, ribosomal protein S6. MYB acts on MAPK signaling by directly regulating transcription of the gene encoding the negative modulator SPRY2. This mechanistic insight points to pathways that might be targeted therapeutically in MPN.Leukemia accepted article preview online, 17 October 2016. doi:10.1038/leu.2016.289

Case report: C-reactive protein apheresis in cardiogenic shock: case series from the C-reactive protein apheresis in acute myocardial infarction-registry

C-reactive protein (CRP) apheresis may preserve myocardial tissue after acute myocardial infarction with delayed revascularization. Ten consecutive patients with cardiogenic shock were graded using the Society of Cardiovascular Angiography and Interventions shock classification and treated with CRP apheresis. All patients tolerated CRP apheresis well and were discharged in good clinical condition

Current density inhomogeneity throughout the thickness of superconducting films and its effect on their irreversible magnetic properties

We calculate the distribution of the current density $j$ in superconducting films along the direction of an external field applied perpendicular to the film plane. Our analysis reveals that in the presence of bulk pinning $j$ is inhomogeneous on a length scale of order the inter vortex distance. This inhomogeneity is significantly enhanced in the presence of surface pinning. We introduce new critical state model, which takes into account the current density variations throughout the film thickness, and show how these variations give rise to the experimentally observed thickness dependence of $$ and magnetic relaxation rate.Comment: RevTex, 9 PS figures. To appear in Phys. Rev.

Quantum FHE (Almost) As Secure As Classical

Fully homomorphic encryption schemes (FHE) allow to apply arbitrary efficient computation to encrypted data without decrypting it first. In Quantum FHE (QFHE) we may want to apply an arbitrary quantumly efficient computation to (classical or quantum) encrypted data. We present a QFHE scheme with classical key generation (and classical encryption and decryption if the encrypted message is itself classical) with comparable properties to classical FHE. Security relies on the hardness of the learning with errors (LWE) problem with polynomial modulus, which translates to the worst case hardness of approximating short vector problems in lattices to within a polynomial factor. Up to polynomial factors, this matches the best known assumption for classical FHE. Similarly to the classical setting, relying on LWE alone only implies leveled QFHE (where the public key length depends linearly on the maximal allowed evaluation depth). An additional circular security assumption is required to support completely unbounded depth. Interestingly, our circular security assumption is the same assumption that is made to achieve unbounded depth multi-key classical FHE. Technically, we rely on the outline of Mahadev (arXiv 2017) which achieves this functionality by relying on super-polynomial LWE modulus and on a new circular security assumption. We observe a connection between the functionality of evaluating quantum gates and the circuit privacy property of classical homomorphic encryption. While this connection is not sufficient to imply QFHE by itself, it leads us to a path that ultimately allows using classical FHE schemes with polynomial modulus towards constructing QFHE with the same modulus

Systems Biology in ELIXIR: modelling in the spotlight

info:eu-repo/semantics/publishedVersio

Maritime Heritage in the Sultanate of Oman

With over 1700 km of coastline, the inhabitants of Oman have had a deep and enduring relationship with the sea for millennia. Located between the Arabian Gulf and the western Indian Ocean, its fishermen have relied on the sea for sustenance. Its mariners were involved in developing long-distance maritime trade from at least the Bronze Age and continued sailing the monsoonal trade routes well into the twentieth century. Periodically, its rulers have established maritime polities extending to Zanzibar and the Makran coast, creating sea-based migrations in the process. With such a rich and enduring seafaring past, it is therefore not surprising that the modern nation-state of Oman has had an active interest in studying and preserving its MUCH.This chapter explores the historical sources, archaeological finds and experimental activities that have allowed researchers to understand Oman’s maritime past and contribute to its current efforts to conserve and showcase its rich maritime connections

Building an Efficient Lattice Gadget Toolkit: Subgaussian Sampling and More

Many advanced lattice cryptography applications require efficient algorithms for inverting the so-called gadget matrices, which are used to formally describe a digit decomposition problem that produces an output with specific (statistical) properties. The common gadget inversion problems are the classical (often binary) digit decomposition, subgaussian decomposition, Learning with Errors (LWE) decoding, and discrete Gaussian sampling. In this work, we build and implement an efficient lattice gadget toolkit that provides a general treatment of gadget matrices and algorithms for their inversion/sampling. The main contribution of our work is a set of new gadget matrices and algorithms for efficient subgaussian sampling that have a number of major theoretical and practical advantages over previously known algorithms. Another contribution deals with efficient algorithms for LWE decoding and discrete Gaussian sampling in the Residue Number System (RNS) representation. We implement the gadget toolkit in PALISADE and evaluate the performance of our algorithms both in terms of runtime and noise growth. We illustrate the improvements due to our algorithms by implementing a concrete complex application, key-policy attribute-based encryption (KP-ABE), which was previously considered impractical for CPU systems (except for a very small number of attributes). Our runtime improvements for the main bottleneck operation based on subgaussian sampling range from 18x (for 2 attributes) to 289x (for 16 attributes; the maximum number supported by a previous implementation). Our results are applicable to a wide range of other advanced applications in lattice cryptography, such as GSW-based homomorphic encryption schemes, leveled fully homomorphic signatures, key-hiding PRFs and other forms of ABE, some program obfuscation constructions, and more

Shear wave velocity prediction using seismic attributes and well log data

Formation’s properties can be estimated indirectly using joint analysis of compressional and shear wave velocities. Shear wave data isnot usually acquired during well logging, which is most likely for costsaving purposes. Even if shear data is available, the logging programs provide only sparsely sampled one-dimensional measurements: this informationis inadequate to estimate reservoir rock properties. Thus, if the shear wave data can be obtained using seismic methods, the results can be used across the field to estimate reservoir properties. The aim of this paper is to use seismic attributes for prediction of shear wave velocity in a field located in southern part of Iran. Independent component analysis(ICA) was used to select the most relevant attributes to shear velocity data. Considering the nonlinear relationship between seismic attributes and shear wave velocity, multi-layer feed forward neural network was used for prediction of shear wave velocity and promising results were presented

phenix.model_vs_data: a high-level tool for the calculation of crystallographic model and data statistics

Application of phenix.model_vs_data to the contents of the Protein Data Bank shows that the vast majority of deposited structures can be automatically analyzed to reproduce the reported quality statistics. However, the small fraction of structures that elude automated re-analysis highlight areas where new software developments can help retain valuable information for future analysis