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Exposure of the human placental primary cells to nanoplastics induces cytotoxic effects, an inflammatory response and endocrine disruption
No full textInternational audienceHumans are inevitably exposed to micro- and nanoplastics (MP/NP). These particles are able to cross the biological barriers and enter the bloodstream with levels close to 1.6 µg mL−1; MP/NP have been detected in placentas and meconium of newborns. However, the consequences of this exposure on the integrity, development and functions of the human placenta are not documented. In this study, trophoblasts purified from human placentas at term were exposed for 48 h, to two different sizes of polystyrene nanoparticles (PS-NP) of 20 nm (PS-NP20) and 100 nm (PS-NP100), at environmental and supra-environmental concentrations (0.01–100 µg mL−1). Cell viability, oxidative stress, mitochondrial dynamics, lysosomal degradation processes, autophagy, inflammation/oxidative responses and consequences for placental endocrine and angiogenic functions were assessed. PS-NP size determines their internalization rate and their behavior in trophoblasts. Indeed, PS-NP20 are more rapidly translocated, and accumulated in lysosomes as shown by confocal and TEM imaging. They induce higher cytotoxicity than PS-NP100, as early as 1 µg mL−1 (p < 0.05). In addition, they induce a pro-inflammatory cytokines response: IL-1ß is induced from 0.01 µg mL−1 for the both nanoparticle sizes; IL-6, and TNF-α are overexpressed at 100 µg mL−1 only for PS-NP20 (p < 0.05). For the first time, we report that PS-NP disrupt endocrine function, as observed by a decreased hCG release at concentrations found in human blood. This work, provides an in-depth in vitro assessment of the effects of PS-NP on the human placenta
Exploring mercury and selenium dynamics in Amazonian human populations: Insights from urine, blood, and plasma analyses
No full textInternational audienceThe Amazonian riverside population is one of the most impacted by mercury, interestingly, with distinct selenium values in blood, generally among the highest worldwide. The interaction between Hg and Se remains to be thoroughly investigated and could provide insights into the fate of these elements and the potential for selenium-mediated detoxification. The current study explores the levels of both elements, determined by inductively coupled plasma mass spectrometry (ICP-MS), in blood, plasma, and urine, of 1089 adult individuals from communities of Tapajós and Amazon River. A large inter-individual variability was found for Hg levels (0.2–139; 0.2–27; 0.1–19 μg Hg.L−1 respectively in blood, plasma, and urine), while Se contents show rather homogenous status in blood (arithmetic mean = 183 ± 78 μg Se.L−1) and plasma (AM = 103 ± 34 μg Se.L−1). Hg content in blood was positively correlated with Hg level in plasma, both increasing with the frequency of fish intake. In contrast, Se levels remained stable in blood regardless of how often fish was consumed. However, a positive correlation was observed between Hg and Se excreted in urine. This work represents the largest human cohort in the region, pioneering the evaluation of the levels of both elements simultaneously in blood, plasma, and urine, laying the foundations for understanding the dynamics of Hg and Se in Amazonian riverside populations
GEOMAPLEARN 1.2: detecting structures from geological maps with machine learning – the case of geological folds
No full textInternational audienceThe increasing availability of large geological datasets and modern methods of data analysis facilitate a data science approach to geology in which inferences are drawn from geological data using automated methods based on statistics and machine learning. Such methods offer the potential for faster and less subjective interpretations of geological data than are possible from a human interpreter, but translating the understanding of a trained geologist to an algorithm is not straightforward. In this paper, we present automated workflows for detecting geological folds from map data using both unsupervised and supervised machine learning. For the unsupervised case, we use regular expression matching to identify map patterns suggestive of folds along lines crossing the map. We then use the HDBSCAN clustering algorithm to cluster these possible fold identifications into a smaller number of distinct folds. This clustering algorithm is chosen because it does not require the number of clusters to be known a priori. For the supervised learning case, we use synthetic models of folds to train a convolutional neural network to identify folds using map and topographic data. We test both methods on synthetic and real datasets, where they both prove capable of identifying folds. We also find that distinguishing folds from similar map patterns produced by topography is a major issue that must be accounted for with both methods. The unsupervised method has advantages, including the explainability of its results, and provides clearly better results in one of the two real-world test datasets, while the supervised learning method is more fully automated and likely more easily extensible to other structures. Both methods demonstrate the ability of machine learning to interpret folds on geological maps and have potential for further development targeting a wider range of structures and datasets
Morphology, Growth Kinetics, and Porous Structure of Surfactant-Promoted Gas Hydrates: Roles of Subcooling and Surfactant Formulation
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Flux-equilibrated based a posteriori error analysis for an interface problem with CutFEM
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Assessment of a novel alcohol-in-biopolymer emulsion for enhanced remediation of diesel-contaminated soils
No full textInternational audienceConventional pump-and-treat technologies have demonstrated limited effectiveness in remediating soils contaminated with light non-aqueous phase liquids (LNAPLs), such as petroleum hydrocarbons. Non-conventional in-situ flushing with shear-thinning fluids, such as polymers, offers a promising alternative. However, even with polymer flushing, residual LNAPL ganglia may remain trapped in porous media, requiring further improvement of the flushing fluid to enhance remediation efficiency.In this study, we present a novel alcohol-in-biopolymer emulsion developed to enhance the recovery of residual diesel oil from porous media. Batch experiments were conducted to evaluate the partitioning behavior of fifteen different alcohols between the aqueous and diesel phases. The results revealed that 1-pentanol preferentially partitions into the diesel phase rather than the aqueous phase, leading to an increase in diesel oil volume via a swelling mechanism. Furthermore, 1-pentanol forms a stable and homogeneous emulsion when combined with an aqueous solution of the biopolymer xanthan gum, and the surfactant sodium dodecyl sulfate. The emulsion demonstrated stability over 30 d, ensuring its suitability for prolonged remediation processes. Rheological experiments confirmed the emulsion's shear-thinning behavior, which ensures stable and uniform displacement within porous media.A two-dimensional cell packed with silica sand was used to evaluate the efficiency of the emulsion in removing residual diesel oil. The results demonstrated that the emulsion propagates uniformly throughout the porous media, effectively achieving complete removal of residual diesel within 1.15 pore volumes of injection. Pore-scale visualizations revealed the swelling and subsequent mobilization of entrapped diesel ganglia induced by the emulsion, further confirming its efficacy. These findings highlight the potential of this novel alcohol-in-biopolymer emulsion to significantly improve diesel oil recovery from contaminated soils
Martin Hapart - Édition, traduction et notes d'après le manuscrit BnF fr. 12483
No full textÉdition, traduction et notes de Martin Hapart d'après le manuscrit BnF fr. 1248
Para-Fluoro-Thiol Reaction: Powerful Tool for the Versatile Functionalization of Microporous Materials
No full textInternational audienceHyper-cross-linked polystyrene-like polymers (HCPs) represent a cost-effective, highly stable, and scalable class of porous materials with significant potential for environmental remediation, catalysis, gas storage, and separation applications. Herein, we demonstrate that the introduction of pentafluorostyrene in the precursor HCP formulation and the subsequent para-fluoro-thiol reaction is an efficient and energy-saving strategy to functionalize these materials. The important quantity of thiol compounds available in the market offers a wide variety of chemical functions accessible for microporous materials and tailors the properties of HCPs to the specific sorption application. In this study, the proportion of the three building blocks used in the polymerization is first optimized to obtain HCPs exhibiting high microporosity, large Brunauer-Emmett-Teller surface areas, and pore volumes independent of the incorporated functional groups (hexyl, alcohol, amine, or sulfonate). The efficiency and versatility of the para-fluoro-thiol coupling reaction are then demonstrated. Finally, the HCPs′ CO2 adsorption capacity was accessed, as an analyte example, using a manometric setup. At ambient pressure, uptake capacity is predominantly governed by surface chemistry alongside textural properties, while at higher pressure, the uptake capacity is correlated with pore volume, with a probable influence of the swelling of the material upon adsorption
Core-shell gelatin-chitosan nanoparticles with lysozyme responsiveness formed via pH-drive and transglutaminase cross-linking
No full textInternational audienceLysozyme-responsive nanoparticles were fabricated using a hydrophilic protein (gelatin type A) as the core and a hydrophobic polysaccharide (chitosan) as the shell. In this study, curcumin was used as a model molecule for encapsulation and promoted the aggregation of gelatin nanoparticles. Transglutaminase catalyzed both intramolecular cross-linking within gelatin and inter-molecular cross-linking between gelatin and chitosan. The formation mechanism of gelatin nanoparticles was investigated by molecular docking simulations, circular dichroism spectroscopy, UV-vis spectroscopy, turbidity analysis, and dynamic light scattering. Results indicated that pH-driven processes can induce molecular conformational changes of gelatin. However, these alone are insufficient to induce nanoparticle formation. Hydrogen bonding, Pi-alkyl interactions, Pi-Pi interactions, and van der Waals forces between gelatin and curcumin are crucial for the core formation. The coating mechanism of chitosan involved covalent bonds catalyzed by transglutaminase and electrostatic interactions, verified by dynamic light scattering and Fourier transform infrared spectroscopy. Physicochemical properties characterization revealed that the core-shell nanoparticles exhibited a maximum encapsulation efficiency of 97.2 ± 0.3 % and an average particle size of 120 ± 21 nm. The core-shell nanoparticles exhibited high thermal and pH stability, with curcumin retention rates exceeding 80 % under acidic, neutral, and weakly alkaline conditions, and detained thermal degradation up to 90 • C. Additionally, lysozyme responsiveness was evaluated by controlled curcumin release with varying lysozyme concentrations, through which enzymatic hydrolysis of chitosan by lysozyme triggered an increased release rate. In summary, core-shell nanoparticles synthesized from gelatin and chitosan may be effective target delivery systems for curcumin
