Showing papers by "ParisTech published in 2022"

MUNICH v2.0: a street-network model coupled with SSH-aerosol (v1.2) for multi-pollutant modelling

Abstract: Abstract. A new version of a street-network model, the Model of Urban Network of Intersecting Canyons and Highways version 2.0 (MUNICH v2.0), is presented. The comprehensive aerosol model SSH-aerosol is implemented in MUNICH v2.0 to simulate the street concentrations of multiple pollutants, including secondary aerosols. The implementation uses the application programming interface (API) technology so that the SSH-aerosol version may be easily updated. New parameterisations are also introduced in MUNICH v2.0, including a non-stationary approach to model reactive pollutants, particle deposition and resuspension, and a parameterisation of the wind at roof level. A test case over a Paris suburb is presented for model evaluation and to illustrate the impact of the new functionalities. The implementation of SSH-aerosol leads to an increase of 11 % in PM10 concentration because of secondary aerosol formation. Using the non-stationary approach rather than the stationary one leads to a decrease in NO2 concentration of 16 %. The impact of particle deposition on built surfaces and road resuspension on pollutant concentrations in the street canyons is low.

Knockout of high-mobility group box 1 in B16F10 melanoma cells induced host immunity-mediated suppression of in vivo tumor growth

Abstract: High-mobility group box 1 (HMGB1) has been reported as a damage-associated molecular pattern (DAMP) molecule that is released from damaged or dead cells and induces inflammation and subsequent innate immunity. However, the role of HMGB1 in the anti-tumor immunity is unclear since inflammation in the tumor microenvironment also contributes to tumor promotion and progression. In the present study, we established HMGB1-knockout clones from B16F10 and CT26 murine tumors by genome editing using the CRISPR/Cas9 system and investigated the role of HMGB1 in anti-tumor immunity. We found that (1) knockout of HMGB1 in the tumor cells suppressed in vivo, but not in vitro, tumor growth, (2) the suppression of the in vivo tumor growth was mediated by CD8 T cells, and (3) infiltration of CD8 T cells, macrophages and dendritic cells into the tumor tissues was accelerated in HMGB1-knockout tumors. These results demonstrated that knockout of HMGB1 in tumor cells converted tumors from poor infiltration of immune cells called "cold" to "immune-inflamed" or "hot" and inhibited in vivo tumor growth mediated by cytotoxic T lymphocytes. Infiltration of immune cells to the tumor microenvironment is an important step in the series known as the cancer immunity cycle. Thus, manipulation of tumor-derived HMGB1 might be applicable to improve the clinical outcomes of cancer immunotherapies, including immune checkpoint blockades and cancer vaccine therapies.

Parameterizing the aerodynamic effect of trees in street canyons for the street network model MUNICH using the CFD model Code_Saturne

Abstract: Abstract. Trees provide many ecosystem services in cities such as urban heat island reduction, water runoff limitation, and carbon storage. However, the presence of trees in street canyons reduces the wind velocity in the street and limits pollutant dispersion. Thus, to obtain accurate simulations of pollutant concentrations, the aerodynamic effect of trees should be taken into account in air quality models at the street level. The Model of Urban Network of Intersecting Canyons and Highways (MUNICH) simulates the pollutant concentrations in a street network, considering dispersion and physico-chemical processes. It can be coupled to a regional-scale chemical transport model to simulate air quality over districts or cities. The aerodynamic effect of the tree crown is parameterized here through its impact on the average wind velocity in the street direction and the vertical transfer coefficient associated with the dispersion of a tracer. The parameterization is built using local-scale simulations performed with the computational fluid dynamics (CFDs) code Code_Saturne. The two-dimensional CFD simulations in an infinite street canyon are used to quantify the effect of trees, depending on the tree characteristics (leaf area index, crown volume fraction, and tree height to street height ratio) using a drag porosity approach. The tree crown slows down the flow and produces turbulent kinetic energy in the street, thus impacting the tracer dispersion. This effect increases with the leaf area index and the crown volume fraction of the trees, and the average horizontal velocity in the street is reduced by up to 68 %, while the vertical transfer coefficient by up to 23 % in the simulations performed here. A parameterization of these effects on horizontal and vertical transfers for the street model MUNICH is proposed. Existing parameterizations in MUNICH are modified based on Code_Saturne simulations to account for both building and tree effects on vertical and horizontal transfers. The parameterization is built to obtain similar tree effects (quantified by a relative deviation between the cases without and with trees) between Code_Saturne and MUNICH. The vertical wind profile and mixing length depend on leaf area index, crown radius, and tree height to street height ratio. The interaction between the trees and the street aspect ratio is also considered.

Comparative analysis of the caecal tonsil transcriptome in two hen lines experimentally infected with <i>Salmonella</i> Enteritidis

Abstract: Abstract Managing Salmonella enterica Enteritidis (SE) carriage in chicken is necessary to ensure human food safety and enhance chicken breeding viability. Salmonella can contaminate poultry products, causing human foodborne disease and economic losses for farmers. Both genetic selection for a decreased carriage and gut microbiota modulation strategies could reduce Salmonella propagation in farms. Two-hundred and twenty animals from the White Leghorn inbred lines N and 6 1 were raised together on floor, infected by SE at 7 days of age, transferred into isolators to prevent oro-fecal recontamination and euthanized at 19 days. Caecal content DNA was used to measure individual Salmonella counts (ISC) by droplet digital PCR. A RNA sequencing approach was used to measure gene expression levels in caecal tonsils after infection of 48 chicks with low or high ISC. The analysis between lines identified 7516 differentially expressed genes (DEGs) corresponding to 62 enriched Gene Ontology (GO) Biological Processes (BP) terms. A comparison between low and high carriers allowed us to identify 97 DEGs and 23 enriched GO BP terms within line 6 1 , and 1034 DEGs and 288 enriched GO BP terms within line N. Among these genes, we identified several candidate genes based on their putative functions, including FUT2 or MUC4 , which could be involved in the control of SE infection, maybe through interactions with commensal bacteria. Altogether, we were able to identify several genes and pathways associated with differences in SE carriage level. These results are discussed in relation to individual caecal microbiota compositions, obtained for the same animals in a previous study, which may interact with host gene expression levels for the control of the caecal SE load.

Parameterizing the aerodynamic effect of trees in street canyons for the street-network model MUNICH using the CFD model Code_Saturne

Abstract: Abstract. Trees provide many ecosystem services in cities such as urban heat island reduction, water runoff limitation and carbon storage. However, the presence of trees in street canyons reduces the wind velocity in the street and limits pollutant dispersion. Thus, to get accurate simulations of pollutant concentrations, the aerodynamic effect of trees should be taken into account in air-quality models at the street level. The Model of Urban Network of Intersecting Canyons and Highways (MUNICH) simulates the pollutant concentrations in a street-network, considering dispersion and physico-chemical processes. It can be coupled to a regional-scale chemical-transport model to simulate air quality over districts or cities. The aerodynamic effect of tree crown is parameterized here, through their impacts on the average wind velocity in the street direction and the vertical transfer coefficient associated with the dispersion of a tracer. The parameterization is built using local-scale simulations performed with the Computational Fluid Dynamics (CFD) code Code_Saturne. Two-dimensional CFD simulations in an infinite street canyon are used to quantify the effect of trees depending on the tree characteristics (Leaf Area Index, crown volume fraction and tree height to street height ratio) using a drag-porosity approach. The tree crown slows down the flow and produces turbulent kinetic energy in the street, thus impacting the tracer dispersion. This effect increases with the Leaf Area Index and the crown volume fraction of the trees: the average horizontal velocity in the street is reduced up to 68 % and the vertical transfer coefficient up to 23 % in the simulations performed here. A parameterization of these effects on horizontal and vertical transfers for the street model MUNICH is proposed. Existing parameterizations in MUNICH are modified based on Code_Saturne simulations to account for both building and tree effects on vertical and horizontal transfers. The parameterization is built to get similar tree effects (quantified by a relative deviation between the cases without and with trees) between Code_Saturne and MUNICH. The vertical wind profile and mixing length depend on Leaf Area Index, crown radius and tree height to street height ratio. The interaction between the trees and the street aspect ratio is also considered.

Usefulness of Breath-Hold Fat-Suppressed T2-Weighted Images With Deep Learning–Based Reconstruction of the Liver

Abstract: The aim of this study was to evaluate the usefulness of breath-hold turbo spin echo with deep learning-based reconstruction (BH-DL-TSE) in acquiring fat-suppressed T2-weighted images (FS-T2WI) of the liver by comparing this method with conventional free-breathing turbo spin echo (FB-TSE) and breath-hold half Fourier single-shot turbo spin echo with deep learning-based reconstruction (BH-DL-HASTE).The study cohort comprised 111 patients with suspected liver disease who underwent 3 T magnetic resonance imaging. Fifty-eight focal solid liver lesions ≥10 mm were also evaluated. Three sets of FS-T2WI were acquired using FB-TSE, prototypical BH-DL-TSE, and prototypical BH-DL-HASTE, respectively. In the qualitative analysis, 2 radiologists evaluated the image quality using a 5-point scale. In the quantitative analysis, we calculated the lesion-to-liver signal intensity ratio (LEL-SIR). Friedman test and Dunn multiple comparison test were performed to assess differences among 3 types of FS-T2WI with respect to image quality and LEL-SIR.The mean acquisition time was 4 minutes and 43 seconds ± 1 minute and 21 seconds (95% confidence interval, 4 minutes and 28 seconds to 4 minutes and 58 seconds) for FB-TSE, 40 seconds for BH-DL-TSE, and 20 seconds for BH-DL-HASTE. In the qualitative analysis, BH-DL-HASTE resulted in the fewest respiratory motion artifacts ( P < 0.0001). BH-DL-TSE and FB-TSE exhibited significantly less motion-related signal loss and clearer intrahepatic vessels than BH-DL-HASTE ( P < 0.0001). Regarding the edge sharpness of the left lobe, BH-DL-HASTE scored the highest ( P < 0.0001), and BH-DL-TSE scored higher than FB-TSE ( P = 0.0290). There were no significant differences among 3 types of FS-T2WI with respect to the edge sharpness of the right lobe ( P = 0.1290), lesion conspicuity ( P = 0.5292), and LEL-SIR ( P = 0.6026).BH-DL-TSE provides a shorter acquisition time and comparable or better image quality than FB-TSE, and could replace FB-TSE in acquiring FS-T2WI of the liver. BH-DL-TSE and BH-DL-HASTE have their own advantages and may be used complementarily.

Pesticide fate in soils

Abstract: Pesticide molecules in soils undergo different processes of biological, physical and physico-chemical origin, and occurring over different time (minutes to decades) and spatial (nm to km) scales. Pesticides are represented by a diversity of molecules having contrasting physico-chemical properties inducing various kinds of behavior in terms of persistence, sorption, transport with the potential for contamination of water, uptake by plants, and possible impacts on soil biota and microbial processes. This chapter proposes an update of current available knowledge on the main processes and current state of the art of knowledge integration in pesticide fate models at the plot and watershed scales for environmental risk assessment.