Hydrolytic kinetic model predicting embrittlement in thermoplastic elastomers

A hydrolytic kinetic model predicting chains scissions of a polyurethane elastomer (TPU) containing an anti-hydrolysis agent (stabilization via carbodiimide) was developed. This model is based on four components: uncatalysed hydrolysis, acid-catalysed hydrolysis, carboxylic acid dissociation and competitive carbodiimide-based deactivation of acid. Protons were considered as the key catalyst responsible for the hydrolysis. Model parameters were determined by fitting experimental data measured on unstabilized and stabilized TPUs, aged in immersion from 40 to 90 °C. Scission kinetics were predicted for immersion and 50% relative humidity conditions, from 10 to 100 °C. Structure-failure property relationships were also investigated, between molar mass and elongation at break. A master curve was established for elongation at break with molar mass, including both TPUs at four ageing temperatures. By combining predictions for scission kinetics with the molar mass-elongation at break master curve and an embrittlement molar mass as the end-of-life criterion, non-Arrhenian lifetime predictions are proposed for all exposure conditions considered

Multiple colonization with highly resistant bacteria: carbapenemase-producing Enterobacteriaceae, carbapenemase-producing Pseudomonas aeruginosa, carbapenemase-producing Acinetobacter baumannii, and glycopeptide-resistant Enterococcus faecium

The dissemination of carbapenemase-producing bacteria worldwide is an important source of concern because carbapenemase producers are multidrug resistant (Nordmann and Poirel, 2014). National guidelines increasingly recommend a systematic screening of at least carbapenemase-producing Enterobacteriaceae (CPE) and glycopeptide-resistant enterococci (GRE) in patients admitted to hospitals who have been hospitalized aboard during the preceding 12 months (Lepelletier et al., 2011). We have investigated the occurrence of colonization and infection with multiple highly resistant bacteria of more than 4 different genus in 2 patients directly transferred from a foreign country.In June 2014, a 33-year-old French man (patient A) was admitted for a suicide attempt in a Vietnamese hospital where he was treated during 10 days for pneumonia with piperacillin + tazobactam before his transfer to Necker-Enfants Malades University Hospital in Paris, France. At the day of his hospitalization in France, distal protected pulmonary samples were collected, and imipenem was administered subsequently to a persistent fever. In addition, systematic screening to detect carbapenemase producers and GRE was also performed. Screening of extended spectrum β-lactamase (ESBL) producing Enterobacteriaceae, carbapenemase producers, and GRE was done on selective media (bioMérieux, La Balme-les-Grottes, France) ChromID ESBL, ChromID Carba Smart, and VRE medium, respectively. Carbapenemase production was identified using the Carba NP test for Enterobacteriaceae (Dortet et al., 2014a) and Pseudomonas aeruginosa ( Dortet et al., 2012) and CarbAcineto NP test for Acinetobacter baumannii ( Dortet et al., 2014b). Definitive identifications of resistance determinant were done by PCR amplifications followed by sequencing. Pulmonary samples grew an OXA-23–producing A. baumannii isolate and an IMP-1–producing P. aeruginosa ( Table 1). Screening identified also that the patient was colonized with a KPC-2–producing Klebsiella pneumoniae, a CTX-M-15–producing K. pneumoniae, and a VanA-positive glycopeptide-resistant Enterococcus faecium ( Table 1)

HER3 as biomarker and therapeutic target in pancreatic cancer: new insights in pertuzumab therapy in preclinical models.

International audienceThe anti-HER2 antibody pertuzumab inhibits HER2 dimerization and affects HER2/HER3 dimer formation and signaling. As HER3 and its ligand neuregulin are implicated in pancreatic tumorigenesis, we investigated whether HER3 expression could be a predictive biomarker of pertuzumab efficacy in HER2low-expressing pancreatic cancer. We correlated in vitro and in vivo HER3 expression and neuregulin dependency with the inhibitory effect of pertuzumab on cell viability and tumor progression. HER3 knockdown in BxPC-3 cells led to resistance to pertuzumab therapy. Pertuzumab treatment of HER3-expressing pancreatic cancer cells increased HER3 at the cell membrane, whereas the anti-HER3 monoclonal antibody 9F7-F11 down-regulated it. Both antibodies blocked HER3 and AKT phosphorylation and inhibited HER2/HER3 heterodimerization but affected differently HER2 and HER3 homodimers. The pertuzumab/9F7-F11 combination enhanced tumor inhibition and the median survival time in mice xenografted with HER3-expressing pancreatic cancer cells. Finally, HER2 and HER3 were co-expressed in 11% and HER3 alone in 27% of the 45 pancreatic ductal adenocarcinomas analyzed by immunohistochemistry. HER3 is essential for pertuzumab efficacy in HER2low-expressing pancreatic cancer and HER3 expression might be a predictive biomarker of pertuzumab efficacy in such cancers. Further studies in clinical samples are required to confirm these findings and the interest of combining anti-HER2 and anti-HER3 therapeutic antibodies

Kartezio: Evolutionary Design of Explainable Pipelines for Biomedical Image Analysis

An unresolved issue in contemporary biomedicine is the overwhelming number and diversity of complex images that require annotation, analysis and interpretation. Recent advances in Deep Learning have revolutionized the field of computer vision, creating algorithms that compete with human experts in image segmentation tasks. Crucially however, these frameworks require large human-annotated datasets for training and the resulting models are difficult to interpret. In this study, we introduce Kartezio, a modular Cartesian Genetic Programming based computational strategy that generates transparent and easily interpretable image processing pipelines by iteratively assembling and parameterizing computer vision functions. The pipelines thus generated exhibit comparable precision to state-of-the-art Deep Learning approaches on instance segmentation tasks, while requiring drastically smaller training datasets, a feature which confers tremendous flexibility, speed, and functionality to this approach. We also deployed Kartezio to solve semantic and instance segmentation problems in four real-world Use Cases, and showcase its utility in imaging contexts ranging from high-resolution microscopy to clinical pathology. By successfully implementing Kartezio on a portfolio of images ranging from subcellular structures to tumoral tissue, we demonstrated the flexibility, robustness and practical utility of this fully explicable evolutionary designer for semantic and instance segmentation.Comment: 36 pages, 6 main Figures. The Extended Data Movie is available at the following link: https://www.youtube.com/watch?v=r74gdzb6hdA. The source code is available on Github: https://github.com/KevinCortacero/Kartezi

Towards IASI-New Generation (IASI-NG): impact of improved spectral resolution and radiometric noise on the retrieval of thermodynamic, chemistry and climate variables

Besides their strong contribution to weather forecast improvement through data assimilation, thermal infrared sounders onboard polar-orbiting platforms are now playing a key role for monitoring atmospheric composition changes. The Infrared Atmospheric Sounding Interferometer (IASI) instrument developed by the French space agency (CNES) and launched by Eumetsat onboard the Metop satellite series is providing essential inputs for weather forecasting and pollution/climate monitoring owing to its smart combination of large horizontal swath, good spectral resolution and high radiometric performance. EUMETSAT is currently preparing the next polar-orbiting program (EPS-SG) with the Metop-SG satellite series that should be launched around 2020. In this framework, CNES is studying the concept of a new instrument, the IASI-New Generation (IASI-NG), characterized by an improvement of both spectral and radiometric characteristics as compared to IASI, with three objectives: (i) continuity of the IASI/Metop series; (ii) improvement of vertical resolution; (iii) improvement of the accuracy and detection threshold for atmospheric and surface components. In this paper, we show that an improvement of spectral resolution and radiometric noise fulfill these objectives by leading to (i) a better vertical coverage in the lower part of the troposphere, thanks to the increase in spectral resolution; (ii) an increase in the accuracy of the retrieval of several thermodynamic, climate and chemistry variables, thanks to the improved signal-to-noise ratio as well as less interferences between the signatures of the absorbing species in the measured radiances. The detection limit of several atmospheric species is also improved. We conclude that IASI-NG has the potential for strongly benefiting the numerical weather prediction, chemistry and climate communities now connected through the European GMES/Copernicus initiative