Search

The French Flooding Prevention Action Program of Saint-Malo, France, requires the assessment of coastal flooding risks and the development of a local flood warning system. The first prerequisite is knowledge of the topography and bathymetry of the bay of Saint-Malo; the acquisition of new multibeam bathymetric data was performed in 2018 and 2019 to increase the resolution of the existing topo-bathymetric datasets and to produce two high-resolution (20 and 5 m) topo-bathymetric digital terrain models. Second, the hydrodynamics associated with coastal flooding were investigated through a dense and extensive oceanographic field experiment conducted during winter 2018–2019 using a network of 22 moorings with 37 sensors: the network included 2 directional buoys, 2 pressure tide gauges, 18 wave pressure gauges, 4 single-point current meters, 7 current profilers, and 4 acoustic wave current profilers from mid-depth (25 m) up to the upper beach and the dike system. The oceanographic dataset thus provides an extended overview of the hydrodynamics and wave processes in the bay of Saint-Malo from the coast up to over-flooding and over-topping areas. This dataset helps to identify the physical drivers of the coastal flooding and provides a quantification of their respective contributions. In particular, the wave processes at the foot of the protection structures can be observed: in this macro-tidal environment, during high spring tides, short and infragravity waves propagate up to the protection structures, while the wave set-up remains negligible, and over-topping by sea packs can occur. The combination of high-resolution topo-bathymetric and oceanographic datasets allows the construction, calibration and validation of a wave and hydrodynamic coupled model that is used to investigate flooding processes more deeply and might be integrated into a future local warning system by means of Saint-Malo inter-communality. The topo-bathymetric and oceanographic datasets are available freely at https://doi.org/10.17183/MNT_COTIER_GNB_PAPI_SM_20m_WGS84, https://doi.org/10.17183/MNT_COTIER_PORT_SM_PAPI_SM_5m_WGS84 and https://doi.org/10.17183/CAMPAGNE_OCEANO_STMALO (Shom, 2020a, b, 2021).

This work considers an industrial production site partially powered by a decentralised energy system based on intermittent renewable energy sources. Our objective is to simultaneous plan the industrial production and the energy supply in this site so as to minimise the total cost. A new way of modelling this combinatorial optimisation problem is proposed: it relies on the extension of a multi-product single-resource small-bucket lot-sizing model called the proportional lot-sizing and scheduling problem. This extension involves among others sequence-dependent changeover times overlapping multiple periods and energy-related constraints. Our numerical results show that the resulting mixed-integer linear programming model enables to obtain good-quality production and energy supply plans with a computational effort much smaller than the one required by a previously published large-bucket lot-sizing model. [ABSTRACT FROM AUTHOR]

Pancreatic ductal adenocarcinoma (PDA) tumor cells are deprived of oxygen and nutrients and therefore must adapt their metabolism to ensure proliferation. In some physiological states, cells rely on ketone bodies to satisfy their metabolic needs, especially during nutrient stress. Here, we show that PDA cells can activate ketone body metabolism and that β-hydroxybutyrate (βOHB) is an alternative cell-intrinsic or systemic fuel that can promote PDA growth and progression. PDA cells activate enzymes required for ketogenesis, utilizing various nutrients as carbon sources for ketone body formation. By assessing metabolic gene expression from spontaneously arising PDA tumors in mice, we find HMG-CoA lyase (HMGCL), involved in ketogenesis, to be among the most deregulated metabolic enzymes in PDA compared to normal pancreas. In vitro depletion of HMGCL impedes migration, tumor cell invasiveness, and anchorage-independent tumor sphere compaction. Moreover, disrupting HMGCL drastically decreases PDA tumor growth in vivo, while βOHB stimulates metastatic dissemination to the liver. These findings suggest that βOHB increases PDA aggressiveness and identify HMGCL and ketogenesis as metabolic targets for limiting PDA progression.

Paracetamol/acetaminophen (N-acetyl-p-aminophenol, APAP) is a top selling analgesic used in more than 600 prescription and non-prescription pharmaceuticals. To study efficiently some of the potential undesirable effects associated with increasing APAP consumption (e.g., developmental disorders, drug-induced liver injury), there is a need to improve current APAP biomonitoring methods that are limited by APAP short half-life. Here, we demonstrate using high-resolution mass spectrometry (HRMS) in several human studies that APAP thiomethyl metabolite conjugates (S-methyl-3-thioacetaminophen sulfate and S-methyl-3-thioacetaminophen sulphoxide sulfate) are stable biomarkers with delayed excretion rates compared to conventional APAP metabolites, that could provide a more reliable history of APAP ingestion in epidemiological studies. We also show that these biomarkers could serve as relevant clinical markers to diagnose APAP acute intoxication in overdosed patients, when free APAP have nearly disappeared from blood. Using in vitro liver models (HepaRG cells and primary human hepatocytes), we then confirm that these thiomethyl metabolites are directly linked to the toxic N-acetyl-p-benzoquinone imine (NAPQI) elimination, and produced via an overlooked pathway called the thiomethyl shunt pathway. Further studies will be needed to determine whether the production of the reactive hepatotoxic NAPQI metabolites is currently underestimated in human. Nevertheless, these biomarkers could already serve to improve APAP human biomonitoring, and investigate, for instance, inter-individual variability in NAPQI production to study underlying causes involved in APAP-induced hepatotoxicity. Overall, our findings demonstrate the potential of exposomics-based HRMS approach to advance towards a better precision for human biomonitoring.

Road crashes are the first cause of mortality for young adults aged 18–25 years and the human factor contributes to 90–95% of events. The present study was carried out to determine the efficacity of the ECARR2 recurrence prevention program among adolescents and young adults at high risk of having a new traffic crash in the following months. A total of 288 participants having had a traffic crash that required going to the emergency room, at high risk of accident recurrence (ECARR≥5) were randomly allocated to either the intervention group (n = 144) or the control group (n = 144). Results: revealed that the risk of recurrence was highest during the first 6 months (66% of recurrences). In per-protocol analysis population, at 6 months after inclusion, the accident recurrence rate was 14.2% ± 3.3% in the intervention group, and 23.5% ± 4.0% in the control group. The intervention had an effect per se, independently of the other predictors (p = 0.020). This effect was mediated by the three interaction variables: BDI, Impulsive Behavior Scale lack of perseverance, and Orientation to Happiness engagement. It was therefore through these dimensions that the intervention had an effect. In conclusion, the ECARR score predicts the risk of recurrence, risk which is the highest during the first 6 months. Finally, results confirm the predictive validity of the ECARR scale. The ECARR score had an effect on the risk of recurrence regardless of group (p = 0.045) and was predictive of recurrence (p = 0.045).A brief psychological intervention such as ECARR2 program, offered to young people ar hight risk of having a new crash, just after the crash, seems to halve the risk of recurrence at 6 months. Future research should improve the brief psychological intervention and its access via a mobile application or few hours in high school or in a driving school given.