A Subfield Lattice Attack on Overstretched NTRU Assumptions:Cryptanalysis of Some FHE and Graded Encoding Schemes

International audienc

Hematological Changes in Dogs with Visceral Leishmaniasis Are Associated with Increased IFN-γ and TNF Gene Expression Levels in the Bone Marrow

Visceral leishmaniasis is associated with a variety of hematological abnormalities. In this study, we correlated the hematological changes in the peripheral blood of dogs naturally infected with Leishmania infantum (L. infantum) with the distribution of cell lineages and cytokine gene expression patterns in the bone marrow. Samples from 63 naturally semidomiciled dogs living in an endemic area of visceral leishmaniasis were analyzed. L. infantum infection was detected in 50 dogs (79.3%). Among those, 18 (32%) had positive splenic cultures and showed more clinical signs. They also had lower red blood cell counts and leukocytosis with an increased number of neutrophils and monocytes in peripheral blood compared to dogs negative to this test. L. infantum DNA was detected in the bone marrow of 8/14 dogs with positive splenic culture. Dogs with L. infantum infection in the bone marrow presented with histiocytosis (p = 0.0046), fewer erythroid cell clusters (p = 0.0127) and increased gene expression levels of IFN-γ (p = 0.0015) and TNF (p = 0.0091). The data shown herein suggest that inflammatory and cytokine gene expression changes in bone marrow may contribute to the peripheral blood hematological changes observed in visceral leishmaniasis.V.A. was supported by a scholarship from CNPq (Conselho Nacional de Desenvolvimento Científico e Tecnológico), FIOCRUZ and Instituto de Salud Carlos III (ISC-III).S

The triggering receptor expressed on myeloid cells (TREM) in inflammatory bowel disease pathogenesis

The Triggering Receptors Expressed on Myeloid cells (TREM) are a family of cell-surface molecules that control inflammation, bone homeostasis, neurological development and blood coagulation. TREM-1 and TREM-2, the best-characterized receptors so far, play divergent roles in several infectious diseases. In the intestine, TREM-1 is highly expressed by macrophages, contributing to inflammatory bowel disease (IBD) pathogenesis. Contrary to current understanding, TREM-2 also promotes inflammation in IBD by fueling dendritic cell functions. This review will focus specifically on recent insights into the role of TREM proteins in IBD development, and discuss opportunities for novel treatment approaches

Classification of glomerular hypercellularity using convolutional features and support vector machine

Glomeruli are histological structures of the kidney cortex formed by interwoven blood capillaries, and are responsible for blood filtration. Glomerular lesions impair kidney filtration capability, leading to protein loss and metabolic waste retention. An example of lesion is the glomerular hypercellularity, which is characterized by an increase in the number of cell nuclei in different areas of the glomeruli. Glomerular hypercellularity is a frequent lesion present in different kidney diseases. Automatic detection of glomerular hypercellularity would accelerate the screening of scanned histological slides for the lesion, enhancing clinical diagnosis. Having this in mind, we propose a new approach for classification of hypercellularity in human kidney images. Our proposed method introduces a novel architecture of a convolutional neural network (CNN) along with a support vector machine, achieving near perfect average results with the FIOCRUZ data set in a binary classification (lesion or normal). Our deep-based classifier outperformed the state-of-the-art results on the same data set. Additionally, classification of hypercellularity sub-lesions was also performed, considering mesangial, endocapilar and both lesions; in this multi-classification task, our proposed method just failed in 4\% of the cases. To the best of our knowledge, this is the first study on deep learning over a data set of glomerular hypercellularity images of human kidney.Comment: 26 page

Predicting the seasonal evolution of southern African summer precipitation in the DePreSys3 prediction system

We assess the ability of the DePreSys3 prediction system to predict austral summer precipitation (DJF) over southern Africa, defined as the African continent south of 15°S. DePresys3 is a high resolution prediction system (at a horizontal resolution of ~ 60 km in the atmosphere in mid-latitudes and of the quarter degree in the Ocean) and spans the long period 1959–2016. We find skill in predicting interannual precipitation variability, relative to a long-term trend; the anomaly correlation skill score over southern Africa is greater than 0.45 for the first summer (i.e. lead month 2–4), and 0.37 over Mozambique, Zimbabwe and Zambia for the second summer (i.e. lead month 14–16). The skill is related to the successful prediction of the El-Nino Southern Oscillation (ENSO), and the successful simulation of ENSO teleconnections to southern Africa. However, overall skill is sensitive to the inclusion of strong La-Nina events and also appears to change with forecast epoch. For example, the skill in predicting precipitation over Mozambique is significantly larger for the first summer in the 1990–2016 period, compared to the 1959–1985 period. The difference in skill in predicting interannual precipitation variability over southern Africa in different epochs is consistent with a change in the strength of the observed teleconnections of ENSO. After 1990, and consistent with the increased skill, the observed impact of ENSO appears to strengthen over west Mozambique, in association with changes in ENSO related atmospheric convergence anomalies. However, these apparent changes in teleconnections are not captured by the ensemble-mean predictions using DePreSys3. The changes in the ENSO teleconnection are consistent with a warming over the Indian Ocean and modulation of ENSO properties between the different epochs, but may also be associated with unpredictable atmospheric variability

Fooling primality tests on smartcards

We analyse whether the smartcards of the JavaCard platform correctly validate primality of domain parameters. The work is inspired by the paper Prime and prejudice: primality testing under adversarial conditions, where the authors analysed many open-source libraries and constructed pseudoprimes fooling the primality testing functions. However, in the case of smartcards, often there is no way to invoke the primality test directly, so we trigger it by replacing (EC)DSA and (EC)DH prime domain parameters by adversarial composites. Such a replacement results in vulnerability to Pohlig-Hellman style attacks, leading to private key recovery. Out of nine smartcards (produced by five major manufacturers) we tested, all but one have no primality test in parameter validation. As the JavaCard platform provides no public primality testing API, the problem cannot be fixed by an extra parameter check, %an additional check before the parameters are passed to existing (EC)DSA and (EC)DH functions, making it difficult to mitigate in already deployed smartcards