DOLPHIn - Dictionary Learning for Phase Retrieval

We propose a new algorithm to learn a dictionary for reconstructing and sparsely encoding signals from measurements without phase. Specifically, we consider the task of estimating a two-dimensional image from squared-magnitude measurements of a complex-valued linear transformation of the original image. Several recent phase retrieval algorithms exploit underlying sparsity of the unknown signal in order to improve recovery performance. In this work, we consider such a sparse signal prior in the context of phase retrieval, when the sparsifying dictionary is not known in advance. Our algorithm jointly reconstructs the unknown signal - possibly corrupted by noise - and learns a dictionary such that each patch of the estimated image can be sparsely represented. Numerical experiments demonstrate that our approach can obtain significantly better reconstructions for phase retrieval problems with noise than methods that cannot exploit such "hidden" sparsity. Moreover, on the theoretical side, we provide a convergence result for our method

New molecular and cellular aspects of mutant calreticulin in Myeloproliferative Neoplasms

Calreticulin (CALR) is an endoplasmic reticulum (ER) protein that plays an important role as a calcium (Ca2+) buffering chaperone. Mutations in CALR exon 9 have been identified in essential thrombocythemia and primary myelofibrosis, two myeloproliferative neoplasms (MPNs) characterised by megakaryocyte hyperplasia. Despite the large body of research built around CALR mutations, many aspects of the oncogenic mechanisms of CALR in MPNs remain unanswered. This investigation aims to investigate whether CALR mutations affect the nature of the C-terminal domain of this protein, its sub-cellular compartmentalisation and its Ca2+ buffering activity during megakaryocyte hyperplasia. Additionally, this study establishes a new cellular model to investigate megakaryocyte differentiation in presence of CALR mutations. In silico analysis of the structural characteristics of CALR mutant C-terminal domain revealed that CALR mutations lead to changes in its secondary structure, its protein binding properties and changes the acidity of CALR mutant´s C-terminal domain. These physical alterations could affect CALR cellular behaviour by leading to inefficient ER Ca2+ buffering activity and lead to a novel oncogenic network of protein interactions. This study revealed that MARIMO leukemic cell line, which harbours a CALR mutation, has in vitro megakaryocyte differentiation potential. Importantly, this discovery was useful for further studies aiming to analyse CALR mutant cells during megakaryocyte commitment. Moreover, study of CALR mutant cellular localisation showed that this protein is localised within the ER, but it is also mislocalised within the cytoplasm and cell membrane, where it co-localised with thrombopoietin receptor. Interestingly, CALR cell surface expression increased during megakaryocyte commitment in CALR mutant cells, showing a dynamic process of CALR compartmentalisation during megakaryocyte differentiation. One of the more significant findings shown in this study is the emergence of intracellular Ca2+ concentrations ([Ca2+I]) as an important element during megakaryopoiesis. Importantly, CALR mutations impaired the cellular ER Ca2+ buffering activity and led to changes in the [Ca2+I] during the process of megakaryocyte differentiation. In addition, initial experimentsrevealed that physical manipulation of [Ca2+I] leads to the emergence of a megakaryocyte phenotype in leukemic cells, showing the relevance of this factor during megakaryocyte commitment. All together, these findings elucidate novel effects of CALR mutations into the physical and functional characteristics of CALR mutant in MPNs, describing new aspects of this driver mutation during the oncogenesis of these diseases. Finally, the current data highlight the importance of studying the effects of CALR mutations during the process of megakaryocyte differentiation, as CALR mutant sub-cellular compartmentalisation and ER Ca2+ buffering activity variate during the process of megakaryopoiesis

Short and Longer-term Psychological Consequences of Operation Cast Lead: documentation from a Mental Health program in the Gaza Strip

<p>Abstract</p> <p>Background</p> <p>There is growing recognition of the psychological impact of adversity associated with armed conflict on exposed civilian populations. Yet there is a paucity of evidence on the value of mental health programs in these contexts, and of the chronology of psychological sequelae, especially in prolonged conflicts with repeated cycles of extreme violence. Here, we describe changes in the psychological profile of new patients in a mental health program after the military offensive Cast Lead, in the context of the prolonged armed conflict involving the Gaza Strip.</p> <p>Methods</p> <p>This study analyses routinely collected program data from a Médecins Sans Frontières mental health program in the Gaza Strip spanning 2007–2011. Data consist of socio-demographic as well as clinical baseline and follow-up data on new patients entering the program. Comparisons were made through Chi square and Fisher’s exact tests, univariate and multivariate logistic and linear regression.</p> <p>Results</p> <p>PTSD, depression and other anxiety disorders were the most frequent psychopathologies, with 21% having multiple diagnoses. With a median of nine sessions, clinical improvement was recorded for 83% (1122/1357), and more common for those with separation anxiety, acute and posttraumatic disorders as principal diagnosis (855/1005), compared to depression (141/183, p<0.01). Noted changes proximal to Operation Cast Lead were: a doubling in patient case load with a broader socio-economic background, shorter interval from an identified traumatic event to seeking care, and a rise in diagnoses of acute and posttraumatic stress disorders. Sustained changes included: high case load, more distal triggering events, and increase in diagnoses of other anxiety disorders (especially for children 15 years and younger) and depression (especially for patients 16 years and older).</p> <p>Conclusion</p> <p>Evolving changes in patient volume, diagnoses and recall period to triggering events suggest a lengthy and durable effect of an intensified exposure to violence in a context of prolonged conflict. Our findings suggest that mental health related humanitarian relief in protracted conflicts might need to prepare for an increase in patients with changing profiles over an extended period following an acute flare-up in violence.</p

Generative discriminative models for multivariate inference and statistical mapping in medical imaging

This paper presents a general framework for obtaining interpretable multivariate discriminative models that allow efficient statistical inference for neuroimage analysis. The framework, termed generative discriminative machine (GDM), augments discriminative models with a generative regularization term. We demonstrate that the proposed formulation can be optimized in closed form and in dual space, allowing efficient computation for high dimensional neuroimaging datasets. Furthermore, we provide an analytic estimation of the null distribution of the model parameters, which enables efficient statistical inference and p-value computation without the need for permutation testing. We compared the proposed method with both purely generative and discriminative learning methods in two large structural magnetic resonance imaging (sMRI) datasets of Alzheimer's disease (AD) (n=415) and Schizophrenia (n=853). Using the AD dataset, we demonstrated the ability of GDM to robustly handle confounding variations. Using Schizophrenia dataset, we demonstrated the ability of GDM to handle multi-site studies. Taken together, the results underline the potential of the proposed approach for neuroimaging analyses.Comment: To appear in MICCAI 2018 proceeding

Fully Trainable and Interpretable Non-Local Sparse Models for Image Restoration

Non-local self-similarity and sparsity principles have proven to be powerful priors for natural image modeling. We propose a novel differentiable relaxation of joint sparsity that exploits both principles and leads to a general framework for image restoration which is (1) trainable end to end, (2) fully interpretable, and (3) much more compact than competing deep learning architectures. We apply this approach to denoising, jpeg deblocking, and demosaicking, and show that, with as few as 100K parameters, its performance on several standard benchmarks is on par or better than state-of-the-art methods that may have an order of magnitude or more parameters.Comment: ECCV 202

Aptamers against the β-conglutin allergen: Insights into the behavior of the shortest multimeric (intra)molecular dna gquadruplex

In previous work, a 93-mer aptamer was selected against the anaphylactic allergen, β-conglutin and truncated to an 11-mer, improving the affinity by two orders of magnitude, whilst maintaining the specificity. This 11-mer was observed to fold in a G-quadruplex, and preliminary results indicated the existence of a combination of monomeric and higher-order structures. Building on this previous work, in the current study, we aimed to elucidate a deeper understanding of the structural forms of this 11-mer and the effect of the structure on its binding ability. A battery of techniques including polyacrylamide gel electrophoresis, high-performance liquid chromatography in combination with electrospray ionization time-of-flight mass spectrometry, matrix-assisted laser desorption/ionization time-of-flight, thermal binding analysis, circular dichroism and nuclear magnetic resonance were used to probe the structure of both the 11-mer and the 11-mer flanked with TT- at either the 5′ or 3′ end or at both ends. The TT-tail at the 5′ end hinders stacking effects and effectively enforces the 11-mer to maintain a monomeric form. The 11-mer and the TT- derivatives of the 11-mer were also evaluated for their ability to bind its cognate target using microscale thermophoresis and surface plasmon resonance, and biolayer interferometry confirmed the nanomolar affinity of the 11-mer. All the techniques utilized confirmed that the 11-mer was found to exist in a combination of monomeric and higher-order structures, and that independent of the structural form present, nanomolar affinity was observed

Towards domestic cooking efficiency: A case study on burger pan frying using experimental and computational results

It is well known that the use of efficient domestic cooking appliances and equipment can not only save energy, but also improve the quality of the food being prepared. This work raises the question of whether cooking procedures can also contribute to this energy efficiency. Focusing on burger pan frying, experimental data were used to develop a model able to predict cooking outcomes under different power levels supplied by an induction hob. The proposed model takes into account not only the heat consumed by water evaporation in the contact region but also the shrinkage process of the hamburger. A new formulation based on the multiplicative decomposition of the strain deformation gradient is proposed to describe the observed decoupling between weight and volume loss during the process. The model properly predicts temperature, moisture loss and shrinkage, and allows elucidation of the effects of supplying different amounts of energy on the final water content

Ultrasensitive, rapid and inexpensive detection of DNA using paper based lateral flow assay

Sensitive, specific, rapid, inexpensive and easy-to-use nucleic acid tests for use at the point-of-need are critical for the emerging field of personalised medicine for which companion diagnostics are essential, as well as for application in low resource settings. Here we report on the development of a point-of-care nucleic acid lateral flow test for the direct detection of isothermally amplified DNA. The recombinase polymerase amplification method is modified slightly to use tailed primers, resulting in an amplicon with a duplex flanked by two single stranded DNA tails. This tailed amplicon facilitates detection via hybridisation to a surface immobilised oligonucleotide capture probe and a gold nanoparticle labelled reporter probe. A detection limit of 1 7 10−11 M (190 amol), equivalent to 8.67 7 105 copies of DNA was achieved, with the entire assay, both amplification and detection, being completed in less than 15 minutes at a constant temperature of 37 \ub0C. The use of the tailed primers obviates the need for hapten labelling and consequent use of capture and reporter antibodies, whilst also avoiding the need for any post-amplification processing for the generation of single stranded DNA, thus presenting an assay that can facilely find application at the point of need

Altered Skeletal Muscle Lipase Expression and Activity Contribute to Insulin Resistance in Humans

International audienceOBJECTIVE: Insulin resistance is associated with elevated content of skeletal muscle lipids, including triacylglycerols (TAGs) and diacylglycerols (DAGs). DAGs are by-products of lipolysis consecutive to TAG hydrolysis by adipose triglyceride lipase (ATGL) and are subsequently hydrolyzed by hormone-sensitive lipase (HSL). We hypothesized that an imbalance of ATGL relative to HSL (expression or activity) may contribute to DAG accumulation and insulin resistance. RESEARCH DESIGN AND METHODS: We first measured lipase expression in vastus lateralis biopsies of young lean (n = 9), young obese (n = 9), and obese-matched type 2 diabetic (n = 8) subjects. We next investigated in vitro in human primary myotubes the impact of altered lipase expression/activity on lipid content and insulin signaling. RESULTS: Muscle ATGL protein was negatively associated with whole-body insulin sensitivity in our population (r = -0.55, P = 0.005), whereas muscle HSL protein was reduced in obese subjects. We next showed that adenovirus-mediated ATGL overexpression in human primary myotubes induced DAG and ceramide accumulation. ATGL overexpression reduced insulin-stimulated glycogen synthesis (-30%, P < 0.05) and disrupted insulin signaling at Ser1101 of the insulin receptor substrate-1 and downstream Akt activation at Ser473. These defects were fully rescued by nonselective protein kinase C inhibition or concomitant HSL overexpression to restore a proper lipolytic balance. We show that selective HSL inhibition induces DAG accumulation and insulin resistance. CONCLUSIONS: Altogether, the data indicate that altered ATGL and HSL expression in skeletal muscle could promote DAG accumulation and disrupt insulin signaling and action. Targeting skeletal muscle lipases may constitute an interesting strategy to improve insulin sensitivity in obesity and type 2 diabetes