Co-design and refinement for safety critical systems

International audienc

The Eclectic User Experience of Combined On-Screen and On-Wrist Vibrotactile Feedback in Touchscreen Input

International audienc

The local linear functional kNN estimator of the conditional expectile: uniform consistency in number of neighbors

International audienc

Compressed indexing of (ultra) large viral alignments

National audienceThe analysis of MSAs allows for the evaluation of evolutionary distances and position-specific and other higher-order statistics. In particular, in the context of viruses whose genetic material consists of single-stranded nucleic acids (ssRNA viruses), evolutionary constraints at the structural level can be revealed by covariation analysis. Such analyses motivate the analysis of the joint content of columns pairs, to assess the propensity of genomic positions to form a base pair mediated by hydrogen bonds. Ultimately, they enable a reconstruction of RNA architecture(s), potentially revealing targets for future drugs [1].In this work, we introduce a new compressed index, called CREMSA (Column-wise Runlength Encoding for Multiple Sequence Alignments) which both greatly reduces the storage required to store column-wise redundant MSAs. Contrasting with earlier efforts, solely focusing on the file-level compression of an MSA [2], our index enabling direct and efficient access to column-wise statistics (no decompression needed). Our index processes columns independently, and replaces each column content with a compressed bit vector [ 3] storing the offsets where a new nucleotide occurs (storing the new nucleotide in a separate array). Doing so, it exploits the presence of long runs of nucleotides (or gap) that are frequent in viral alignments, saving space while speeding-up queries. The data structure enables access to individual sequences of length n in O(n) time, and (multiple) column-wise statistics in O(r) time, where r is the total number of runs in the column(s). We performed a preliminary analysis of a dataset of 106 SARS-CoV 2 genomes from the NCBI to demonstrate the usability of the approach. The method directly reduces the disk space from 30 GB to 53 MB (99.8% deflation), an impressive feat of compression, even if compared to a baseline gzip compression (2.7GB/98% deflation; 51× larger than CREMSA). In principle, the compression ratio could further benefit from a custom sort procedure, minimizing the sum of Hamming distances over consecutive genomes/rows, but we unfortunately proved the associated problem to be NP-hard. As a practical tradeoff, we sorted rows according to an accepted phylogenetic tree (ordering genomes by their Pango lineage, to contiguously present genomes of a given clade), leading to a substantial improvement (30MB, a further 44% reduction). From the CREMSA representation, we compute the popular RNAalifold [4 ] conservation score between every pair of MSA columns (66M pairs of 1Mbp columns) within 7h and 100MB RAM on a desktop computer (Intel i7-12700, 64GB RAM), and found 251 pairs of columns associated with a conservation score greater than 0.5, indicating potential evolutionarily-pressured base pairs

The colibactin-producing Escherichia coli alters the tumor microenvironment to immunosuppressive lipid overload facilitating colorectal cancer progression and chemoresistance

International audienceIntratumoral bacteria flexibly contribute to cellular and molecular tumor heterogeneity for supporting cancer recurrence through poorly understood mechanisms. Using spatial metabolomic profiling technologies and 16SrRNA sequencing, we herein report that right-sided colorectal tumors are predominantly populated with Colibactin-producing Escherichia coli (CoPEC) that are locally establishing a high-glycerophospholipid microenvironment with lowered immunogenicity. It coincided with a reduced infiltration of CD8+ T lymphocytes that produce the cytotoxic cytokines IFN-γ where invading bacteria have been geolocated. Mechanistically, the accumulation of lipid droplets in infected cancer cells relied on the production of colibactin as a measure to limit genotoxic stress to some extent. Such heightened phosphatidylcholine remodeling by the enzyme of the Land’s cycle supplied CoPEC-infected cancer cells with sufficient energy for sustaining cell survival in response to chemotherapies. This accords with the lowered overall survival of colorectal patients at stage III-IV who were colonized by CoPEC when compared to patients at stage I-II. Accordingly, the sensitivity of CoPEC-infected cancer cells to chemotherapies was restored upon treatment with an acyl-CoA synthetase inhibitor. By contrast, such metabolic dysregulation leading to chemoresistance was not observed in human colon cancer cells that were infected with the mutant strain that did not produce colibactin (11G5∆ClbQ). This work revealed that CoPEC locally supports an energy trade-off lipid overload within tumors for lowering tumor immunogenicity. This may pave the way for improving chemoresistance and subsequently outcome of CRC patients who are colonized by CoPEC

Neural Network Scalable Spiking Simulator

One of the most promising approaches to overcome the end of Moore's law is neuromorphic computing. Indeed, neural networks already have a great impact on machine learning applications and offer very nice properties to cope with the problems of nanoelectronics manufacturing, such as a good tolerance to device variability and circuit defects, and a low activity, leading to low energy consumption. We present here N2S3 (for Neural Network Scalable Spiking Simulator), an open-source simulator that is built to help design spiking neuromorphic circuits based on nanoelectronics. N2S3 is an event-based simulator and its main properties are flexibility, extensibility, and scalability. One of our goals with the release of N2S3 as open-source software is to promote the reproducibility of research on neuromorphic hardware. We designed N2S3 to be used as a library, to be easily extended with new models and to provide a user-friendly special purpose language to describe the simulations.L'une des approches les plus prometteuses pour surmonter la fin de la loi de Moore est l'informatique neuromorphique. En effet, les réseaux neuronaux ont déjà un impact considérable sur les applications d'apprentissage machine et offrent des propriétés très intéressantes pour faire face aux problèmes de fabrication de nanotechnologies électroniques, tels qu'une bonne tolérance à la variabilité des dispositifs et aux défauts de circuit, ainsi qu'une faible activité, conduisant à une faible consommation d'énergie. Nous présentons ici N2S3 (pour Neural Network Scalable Spiking Simulator), un simulateur open source conçu pour aider à concevoir des circuits neuromorphiques à impulsions basés sur les nanotechnologies électroniques. N2S3 est un simulateur basé sur des événements et ses principales propriétés sont la flexibilité, l'extensibilité et la scalabilité. Un de nos objectifs avec la publication de N2S3 en tant que logiciel open source est de promouvoir la reproductibilité de la recherche sur le matériel neuromorphique. Nous avons conçu N2S3 pour qu'il soit utilisé comme une bibliothèque, facilement extensible avec de nouveaux modèles, et fournissant un langage spécialisé convivial pour décrire les simulations

Trpv6 channel targeting using monoclonal antibody induces prostate cancer cell apoptosis and tumor regression

International audienceAbstract TRPV6 calcium channel is a prospective target in prostate cancer (PCa) since it is not expressed in healthy prostate while its expression increases during cancer progression. Despite the role of TRPV6 in PCa cell survival and apoptotic resistance has been already established, no reliable tool to target TRPV6 channel in vivo and thus to reduce tumor burden is known to date. Here we report the generation of mouse monoclonal antibody mAb82 raised against extracellular epitope of the pore region of the channel. mAb82 inhibited TRPV6 currents by 90% at 24 µg/ml in a dose-dependent manner while decreasing store-operated calcium entry to 56% at only 2.4 µg/ml. mAb82 decreased PCa survival rate in vitro by 71% at 12 µg/ml via inducing cell death through the apoptosis cascade via activation of the protease calpain, following bax activation, mitochondria enlargement, and loss of cristae, Cyt C release, pro-caspase 9 cleavage with the subsequent activation of caspases 3/7. In vivo, mice bearing either PC3M$^{trpv6+/+}$ or PC3M$^{trpv6+/-}$ +pTRPV6 tumors were successfully treated with mAb82 at the dose as low as 100 µg/kg resulting in a significant reduction tumor growth by 31% and 90%, respectively. The survival rate was markedly improved by 3.5 times in mice treated with mAb82 in PC3M$^{trpv6+/+}$ tumor group and completely restored in PC3M$^{trpv6-/-}$ +pTRPV6 tumor group. mAb82 showed a TRPV6-expression dependent organ distribution and virtually no toxicity in the same way as mAbAU1, a control antibody of the same Ig2a isotype. Overall, our data demonstrate for the first time the use of an anti-TRPV6 monoclonal antibody in vitro and in vivo in the treatment of the TRPV6-expressing PCa tumors

Motion Consistency Map for Facial Expression Spotting

International audienc

Autour de l’attribution fonctionnelle : réemploi ou multifonctionnalité ? L’exemple de la céramique domestique de Tell el-Herr (Ve – IVe s. av. n. è.)

International audienc

Convolutional Spiking Neural Network Simulator (CSNN)

A simulator dedicated to run multi-layered spiking neural network in C++ . This tool is designed to optimize the time simulation of such architectures on CPU, by providing SIMD implementation of spiking convolution and pooling layer. Moreover, every experimentation configuration is automatically saved in a file, which helps to keep a track of previous results, and allows to easily reload past experimentation