Rodent management is essential for health and economic issues. This management is very often based on the use of rodenticide anticoagulants (AR) facing 2 major problems, i / the resistance phenomena due to mutations of the target enzyme of the ARs, VKORC1, and ii / their ecotoxicity due to their long persistence and their non-specificity of action. Because of these 2 problems, authorities are sometimes without solution against rodent outbreaks. The development of new rodenticides is therefore essential. The specifications of such molecules are complex: the molecules must have a delayed effect to prevent food aversion, an antidote must be available in case of accidental ingestion, they must be specific to species in order to avoid ecotoxicity problems. Targeting the enzyme VKORC1 is a good way to meet these specifications. Its inhibition allows a delayed effect and this inhibition can be quickly countered by the use of vitamin K. Recent advances in the structural and functional understanding of VKORC1 now allow the development of effective, species-specific VKORC1 inhibitors that can overcome resistance problems. These new molecules could target the catalytic site of VKORC1 or prevent the activation of VKORC1. The ROC project is a multi-disciplinary drug-design study aiming at: -identifying the redox partner of VKORC1 to propose new toxicological targets based on cellular, molecular and enzymatic studies -characterizing the 2 interaction sites of VKORC1 that may be targeted by inhibitors and determining the differences between VKORC1 sites of the target and non-target species in order to design species-specific inhibitors by molecular modeling, enzymatic and biophysical studies -determining the structural and functional consequences of VKORC1 mutations on these sites in order to obtain consensus pockets - designing, on the basis of these consensus pockets, new inhibitors by virtual chemical library screening, de novo synthesis and activity structure study - testing the efficacy of these new inhibitors by in vitro, ex vivo and in vivo studies. The project relies on the high complementarity and synergy between four research teams and one industrial partner with optimal complementarity in their respective scientific expertise. V. Lattard (USC1233, coordinator), a biochemist and molecular biologist, has a strong expertise on VKORC1 enzymes and AR resistance. L. Tchertanov (CMLA-ENS) is a physicist specialized in molecular modelling and numerical simulation of membrane enzymes. Sophie Rahuel-Clermont (IMOPA-CNRS) is an enzymologist and biophysicist with strong expertise in Cys-dependent redox enzymes, Florence Popowycz (ICBMS-INSA) is an organic chemist, and Hervé Caruel (Liphatech) has a unique expertise in production rodent bait. Scientifically, this project will allow i / a better structural and functional understanding of the enzyme VKORC1, ii / an understanding of the structural consequences of mutations and iii / an exploration of a new VKORC1 inhibition strategy. This project will provide the society with new environmentally friendly solutions for the rodent management. Liphatech, partner of this project will produce and distribute via its global distribution network the new molecules-based products developed in this project, after evaluation of the technical- and economic-feasibility, international patents filings and registration.

This research program deals with the quality enhancement of digital images. Specifically, we consider the increasingly common situations where several acquisitions of the same scene are available, possibly through a video sequence. An issue of growing importance is to fuse these images in order to get a single enhanced image. Another crucial question concerns the joint restoration of several images of the same sequence. Such an approach has two great advantages. First, going beyond the physical limitations of sensors becomes possible, in terms of dynamic range, resolution or signal- to-noise ratio. Second, the classical limitations of single shot imaging (blur, specular reflections, over or under-exposure, etc.) may be strongly attenuated. As a counterpart, multi-image restoration faces specific difficulties, the toughest of which are related to change detection, motion detection, outliers (aberrant pixels or regions) detection, inpainting, contrast and colour corrections. The proposed work program gathers several classical problems from image processing together with complex issues in image analysis and comparisons. It builds on various mathematical tools, mainly statistical estimation, optimization, stochastic modeling, variational approaches and optimal transport. Within this program, our main goal will be to develop reliable and efficient numerical algorithms for each of the studied restoration modalities.

The goal of the project is to define the complete algorithmic chain that, starting with sets of stereo pairs or triplets of images of the Earth obtained by satellite, recreates the evolution of the ground relief at high resolution, detects its significant changes, gives by fusion the most plausible relief a each time, and finally projects back on this common 3D reference all images taken by satellite, merging them when they are synchronic, and equalizing them for a better time comparison when they are diachronic. The result will be what we shall call a “movie of the Earth”. Its use is contemplated at two very different scales. In the immediate future we will of course not be aiming at a global coverage. The tool should be able to respond to requests localized in time and space. The goal is that public and private operators get an automatic answer to any query : “see what happened”, on a fixed time range and on a specific site. The advantage of satellite imaging in this field is threefold : it allows access at any time and in any area without geographical or political restrictions. The rapidly increasing number of satellites promises daily coverage of any landmark. Finally, the observation of the Earth has a history of forty years, and the “Earth” movie will permit a resumption of images acquired in this period. An objection to the project is the excessive price of a “movie of the Earth”, considering the significant price of each satellite image. But this price is expected to decline very quickly thanks to the massive use of these data when they democratize, through channels including internet. The reason why we’re launching this project with a great economy of means, is that we think we can do it. Indeed the CMLA team has been working for fifteen years with CNES on the reconstruction of the relief of the Earth and on the design of stereoscopic satellites. This collaboration has led the team to produce two years ago a first fully automatic chain processing stereo pairs and triplets, S2P ( it satellite stereo pipeline). We detail in this project the tools that will permit to expand this chain into a diachronic monitoring of the Earth, and we give evidence of its feasibility. The important thing is that the whole chain should be completely automatic, and therefore allow a diachronic synthesis for relief Earth on demand and within a reasonable time, in particular for military and civil uses requiring the detection of significant relief changes and a common visualization for all images of the same site. This is particularly important for the damage assessment after disasters (landslides, floods, earthquakes), in the stages of military operations, in the analysis of the evolution of sensitive sites, and finally for all economic and organizational applications where the monitoring of the evolution of the construction of large areas is required. The team gathered around CMLA can do that in three years using the current dynamics of the team and its existing partnerships. Three key partners are involved in the project, by funding other parts of the project and by feeding data to it : CNES, SERTIT, and CESBIO. The requested contribution will fund the work of a postdoc and a research engineer for three years.

Pulmonary arterial hypertension (PAH) is a rare, severe, and devastating pulmonary vascular disease characterized by chronic increase in pulmonary artery pressure, ultimately leading to right heart failure and death. In PAH, right heart failure is secondary to remodeling of small pulmonary arteries, a complex and multifactor process. Endothelial cell dysfunction (EC) and smooth muscle cell proliferation (SMC) are thought to mediate structural changes of the pulmonary vasculature, yet it is increasingly evident that chronic inflammation plays a central role in PAH pathogenesis. There is unfortunately no cure of PAH. Despite therapeutic progress addressing EC dysfunction, that improves quality of life and survival, median survival remains <5 years and refractory cases are candidates for heart-lung transplantation. Therefore new therapeutic avenues are required for PAH patient management. The general goal of P1 is to better understand PAH pathogenesis and exploit the knowledge on the disease to identify potential innovative therapeutic targets in PAH. On the basis of a unique biobank with pulmonary tissues collected during transplantation, thinking “out of the box”, P1 has recently pointed the NMDA receptor (NMDAR) as a novel actor in the pathophysiology of PAH. The NMDAR thus represents an unexpected future therapeutic target in PAH. The innovative concept is that glutamate signaling through NMDARs is involved in the 3 tissues interacting to cause PAH: the heart, the lung and the immune system. Thus, new compounds that would target peripheral NMDARs in the 3 systems involved in PAH, without central effects, would be of great value to treat PAH. To date, most NMDAR antagonists that reached clinical development to treat neurodegenerative diseases (e.g. dizocilpine/MK-801 and memantine) cannot be used in the periphery without major secondary effects. Accordingly, NUTS emerged as a multidisciplinary project gathering the complementary expertise of 3 partners from the laboratory of excellence Labex LERMIT: P1 (INSERM UMR S999), P2 (CNRS- UMR 8076 Biocis), and P3 (CNRS- UMR 8536 CMLA), respectively in the fields of Biology/Medicine (Pathophysiology of PAH), Medicinal Chemistry (Conception and synthesis of therapeutic molecules) and Structural Biology (Modelisation and molecular simulation). The general goals of NUTS are to investigate the novel paradigm of NMDAR involvement in the pathophysiology of PAH, to explore its potential as a novel therapeutic target of PAH and to propose a novel therapeutic class that blocks peripheral NMDARs. Preliminary results have been obtained paving the proof of concept that NMDAR are indeed involved in PAH, using known antagonists of the NMDAR such as MK-802 and memantine, to modulate the disease in a rat model of pulmonary hypertension. Our working hypothesis is that an early inflammatory event would lead to excessive glutamate release close to pulmonary vessels, thus inducing over-activation of NMDARs in pulmonary arterial ECs, leading to EC apoptosis, disorganization of tight junctions, opening of the EC barrier, uncontrolled angiogenesis, EC and SMC proliferation, resulting in pulmonary vascular remodeling The CNRS UMR 8076 team, founder of BioCIS-Biomolecules has a long lasting experience in the conception of therapeutic molecules. CNRS UMR 8536 CMLA is expert in molecular modeling and applied mathematics. The INSERM U999 team possesses well characterized in vitro and in vivo experimental models to explore PAH pathophysiology and more importantly has the unique possibility to work on pulmonary tissues collected during lung transplantation of severely affected patients, perfectly characterized in the PAH Referral Center. This multidisciplinary approach will provide a novel paradigm on the pathophysiology of PAH and has the ambition to propose in the near future innovative therapeutic avenues, with a new therapeutic class that would target the 3 systems (cardiac, pulmonary, immune) concerned in PAH.

The problem of image forgery detection concerns much broader lines of evidence than just tools from automatic image analysis. These include: the declared source of the image, the political, economic, legal conditions in which the image was produced, the supposition by the expert of malicious or intentional falsification, the information on the image source such as its EXIF file or the device that produced it. Finally the detection requires a semantic analysis of the photograph and of the likelihood of the scene. The expert’s eye is often crucial to detect inconsistencies in a scene. Hence the forensic analysis of an image cannot rely solely on automatic image processes. These are not able to translate the contextual cues that often make a forgery evident to an expert. Yet image processing and analysis can detect abnormalities that escape the human eye, and in addition can associate to them a quantitative certainty measure. Indeed, falsifying an image alters the parameters of its formation and processing model. These alterations are detectable as soon as one can estimate said parameters from the image itself. Nevertheless, we shall try to show that a complete cover up of a falsification is possible, though complicated. Suppose the forgers work directly on the raw image (raw) as follows. First they perform the copy-paste operations by involving a separate raw image having almost the same characteristics. Then the forged raw image is denoised, and new noise is simulated on it, according to a standard Poisson model. Finally the raw image undergoes a standard image processing chain with noise reduction, demosaicing, gamma correction, white balance, and JPEG compression. After this anti-forensic process, an expert could hardly detect any anomaly in the picture’s apparent processing and compression. Indeed, they would have been applied to a plausible raw image. And no repetition of texture or shape would be detected as well. Fortunately, the literature on forgery detection assumes skilled, but not that meticulous counterfeiters. This literature assumes that the falsification can leave behind traces, despite rough anti-forensic measures. Thus, to detect a forgery by image processing means, we must first reconstruct the image formation model simulated by the forger, to detect in continuation any anomaly to this alleged model. So our proposal is to develop algorithms applicable to any digital image. These algorithms will produce by reverse engineering a complete history of the image. Adequate visualization tools will also reveal potential anomalies in the image processing chain. We will develop statistical tools associating with these anomalies error probabilities or false alarm number, thus enabling quantitative decisions, free of subjectivity. So our proposal is in three phases, as it takes: -Establish a digital history of the image, ie the parameters of all operations that were performed on it from it, starting from the raw image, in particular chromatic and optical aberration correction, de-noising, de-mosaicking, gamma-correction, color balancing, de-blurring, interpolation, cropping, compression type and compression parameters, possibly a double compression. -Categorize, implement and take over the most promising image falsification algorithms for the addition or removal of local information (inpainting, Poisson editing,…) and do the same for the anti-forensic operations. -Finally develop automatic detection algorithms, which, based on the alleged history of the image, detect any anomaly in this history. Furthermore algorithms detecting and analyzing internal image suspicious repetitions. Most tools detailed in the proposal are new, but will rely on the image processing expertise of the CMLA image processing team, and on the forensic expertise of the National Scientific and Technical Police.