Co-design and refinement for safety critical systems

International audienc

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

International audienc

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

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

The Colibactin-Producing Escherichia coli alters the tumor microenvironmentto immunosuppressive lipid overload facilitating colorectal cancer progressionand chemoresistance.

International audienc

Strong consistency rate in functional single index expectile model for spatial data

International audienceAnalyzing the real impact of spatial dependency in financial time series data is crucial to financial risk management. It has been a challenging issue in the last decade. This is because most financial transactions are performed via the internet and the spatial dependency between different international stock markets is not standard. The present paper investigates functional expectile regression as a spatial financial risk model. Specifically, we construct a nonparametric estimator of this functional model for the functional single index regression (FSIR) structure. The asymptotic properties of this estimator are elaborated over general spatial settings. More precisely, we establish Borel-Cantelli consistency (BCC) of the constructed estimator. The latter is obtained with the precision of the convergence rate. A simulation investigation is performed to show the easy applicability of the constructed estimator in practice. Finally, real data analysis about the financial data (Euro Stoxx-50 index data) is used to illustrate the effectiveness of our methodology

2D versus 3D Convolutional Spiking Neural Networks Trained with Unsupervised STDP for Human Action Recognition

National audienc

18F]FDG PET/CT for predicting triple-negative breast cancer outcomes after neoadjuvant chemotherapy with or without pembrolizuma

International audiencePurpose: To determine if pretreatment [18F]FDG PET/CT could contribute to predicting complete pathological complete response (pCR) in patients with early-stage triple-negative breast cancer (TNBC) undergoing neoadjuvant chemotherapy with or without pembrolizumab. Methods: In this retrospective bicentric study, we included TNBC patients who underwent [18F]FDG PET/CT before neoadjuvant chemotherapy (NAC) or chemo-immunotherapy (NACI) between March 2017 and August 2022. Clinical, biological, and pathological data were collected. Tumor SUVmax and total metabolic tumor volume (TMTV) were measured from the PET images. Cut-off values were determined using ROC curves and a multivariable model was developed using logistic regression to predict pCR. Results: N = 191 patients were included. pCR rates were 53 and 70% in patients treated with NAC (N = 91) and NACI (N = 100), respectively (p 12.3), and low TMTV (≤ 3.0 cm3) were predictors of pCR in the NAC cohort while tumor staging classification ( 17.2), and low TMTV (≤ 7.3 cm3) correlated with pCR in the NACI cohort. In multivariable analysis, only high tumor SUVmax (NAC: OR 8.8, p < 0.01; NACI: OR 3.7, p = 0.02) and low TMTV (NAC: OR 6.6, p < 0.01; NACI: OR 3.5, p = 0.03) were independent factors for pCR in both cohorts, albeit at different thresholds. Conclusion: High tumor metabolism (SUVmax) and low tumor burden (TMTV) could predict pCR after NAC regardless of the addition of pembrolizumab. Further studies are warranted to validate such findings and determine how these biomarkers could be used to guide neoadjuvant therapy in TNBC patients