Les techniques de diagraphies sont un moyen privilégié pour étudier les formations géologiques profondes, inaccessibles à l'observation directe. Elles mesurent en continu et in situ de nombreux paramètres pétrophysiques, ainsi que les concentrations en 7 éléments majeurs (Si, Ca, Fe, Al, S, K, Ti) et 3 éléments traces (U, Th et Gd). Une connaissance préalable des différents modes de fonctionnement des outils et de leur calibration permet d'évaluer la précision de la mesure. Celle-ci est surtout fonction des conditions de mesure (diamètre et rugosité du puits, vitesse de mesure). Lorsque les données sont de bonne qualité, les méthodes de classification multivariée, comme la méthode des nuées dynamiques ou le k-means, sont employées comme premier outil de visualisation des grandeurs mesurées par diagraphie. En parallèle ou en complément, à l'aide de méthodes d'inversion linéaire ou non-linéaire, il est possible de calculer une minéralogie en continu avec une précision suffisante pour être utilisée dans des modèles pétrophysiques et géologiques. Les zones de convergence de plaques lithosphériques sont des environnements géologiques instables, dans lesquels les techniques de diagraphie par cable, classiquement utilisée dans les forages scientifiques océaniques ou continentaux, ne permettent pas d'obtenir des données de bonne qualité. La nouvelle méthode de Logging-While-Drilling, ne laisse pas à l'environnement de mesure le temps de se déteriorer et donne une mesure utilisable. L'interprétation géologique, minéralogique et faciologique des données de diagraphies apportent des indications précieuses sur la dynamique sédimentaire, ainsi que sur les éventuelles transformations minéralogiques. Le caractère in situ de la mesure rend possible la modélisation de la dynamique des fluides ou de la variation et de l'orientation des champs de contrainte, dont les environnements étudiés sont souvent le siège.

Graphene-directed two-dimensional (2D) nitrogen-doped porous carbon frameworks (GPF) as the hosts for sulfur were constructed via the ionothermal polymerization of 1,4-dicyanobenzene directed by the polyacrylonitrile functionalized graphene nanosheets. As cathodes for lithium–sulfur (Li–S) batteries, the prepared GPF/sulfur nanocomposites exhibited a high capacity up to 962 mA h g⁻¹ after 120 cycles at 2 A g⁻¹. A high reversible capacity of 591 mA h g⁻¹ was still retained even at an extremely large current density of 20 A g⁻¹. Such impressive electrochemical performance of GPF should benefit from the 2D hierarchical porous architecture with an extremely high specific surface area, which could facilitate the efficient entrapment of sulfur and polysulfides and afford rapid charge transfer, fast electronic conduction as well as intimate contact between active materials and the electrolyte during cycling.

<p>Urine-based biomarkers offer numerous advantages for clinical analysis, including non-invasive collection, a suitable sample source for longitudinal disease monitoring, a better screenshot of disease heterogeneity, higher sample volumes, faster processing times, and lower rejection rates and costs. They will be extremely useful in a clinical trial context, which can be applied alone or in combination with other methods as long as they demonstrate clear reproducibility across cohorts. While biofluids such as urine present enormous challenges with a wide dynamic range and extreme complex typically dominated by a few highly abundant proteins, we have demonstrated that the analytical issue can be efficiently addressed by focusing on extracellular vesicles (EVs), tiny packages released by all kinds of cells. These tiny packages contain different kinds of molecules from inside the cells. Here, we established a robust EV isolation and characterization platform to screen and validate Parkinson’s Disease (PD) and Renal Cell Carcinoma (RCC) biomarkers from urine. PD is a progressive neurological disorder affecting body movement because some brain cells stop producing dopamine. PD is often not diagnosed until it has advanced, making early detection crucial. We investigated urinary EVs from 138 individuals to enable early detection and found several proteins involved in PD development that could be biological indicators for early disease detection. Several biochemical techniques were applied to verify our findings. In the second project, we attempted to develop a novel diagnostic technique for early intervention of RCC. Here, we made our efforts to develop a quantitative method based on data-independent acquisition (DIA) mass spectrometry to analyze urinary EV phosphoproteomics for non-invasive RCC biomarker screening. Combined with our in-house EVtrap method for EV isolation and PolyMAC enrichment of phosphopeptides, we quantified 2,584 unique phosphosites. We observed unique upregulated phosphosites and pathways differentiating healthy control (HC), chronic kidney disease (CKD), low-grade, and high-grade clear cell RCC. These applications have a significant promise for early PD and RCC diagnosis and monitoring based on actual functional proteins with urine as the source. These studies might provide a viable path to developing urinary EV-based disease diagnosis.</p>