Impact de la colchicine sur l'inflammation vasculaire

Contexte : Des études récentes suggèrent que la colchicine permettrait de diminuer le risque d’événements cardiovasculaires. L’étude COLPET évaluait l’impact de la colchicine sur l’inflammation vasculaire mesurée par TEP/TDM chez des patients souffrant de MCAS stable. Méthodes : Dans cette étude randomisée à double insu de phase II, les patients étaient traités pendant 24 semaines avec 1 comprimé quotidien de colchicine 0.6 mg ou de placebo. L’inflammation vasculaire était évaluée par la captation de 18F-FDG dans l’aorte ascendante et les carotides à la TEP/TDM au début et à la fin de la thérapie. L’issue d’intérêt primaire était la variation de la moyenne du target-to-background ratio maximal des coupes d’images de l’aorte ascendante (Mean MAX TBR). Les issues d’intérêt secondaires incluaient plusieurs paramètres additionnels de TEP/TDM, ainsi que des mesures sériées de biomarqueurs inflammatoires sériques, dont la hs-CRP. Résultats : Cent-onze patients étaient randomisés dans l’étude, dont 56 au groupe placebo et 55 au groupe colchicine. La colchicine n’avait aucun impact significatif sur l’issue d’intérêt primaire (variation de la moyenne: 0.051; IC95% : -0.016 à 0.117; p=0.1346) ou sur les issues d’intérêt secondaires de TEP/TDM. Cependant, les patients traités à la colchicine présentaient une diminution de 28% de leurs niveaux de hs-CRP (p=0.0026). Conclusion : La thérapie à la colchicine pendant 24 semaines n’a eu aucun impact significatif sur la captation de 18F-FDG par l’aorte ascendante et les carotides. Cependant, une réduction de 28 % des niveaux de hs-CRP était observée chez les patients du groupe colchicine. L’étude randomisée multicentrique de phase III Colchicine Cardiovascular Outcomes Trial (COLCOT) est en cours pour évaluer les bénéfices cardiovasculaires à long terme de la colchicine (0.5 mg par jour), lorsque débutée pendant les trente jours suivant un infarctus du myocarde.Background : Recent studies suggest that colchicine reduces cardiovascular risk. The COLPET Study evaluated the impact of colchicine on vascular inflammation, as measured by PET/CT, in patients with stable CAD. Methods: In this randomized, double-blind, placebo-controlled, phase II clinical trial, patients were treated for 24 weeks with a daily tablet of colchicine 0.6 mg or placebo. Vascular inflammation was assessed by uptake of 18F-FDG in the ascending aorta and carotid arteries on PET/CT at baseline and at the end of study drug therapy. The primary outcome was the change in the mean of maximal target-to-background ratio of the image slices of the ascending aorta (Mean MAX TBR). Secondary outcomes included various PET/CT parameters, as well as serial measures of inflammatory biomarkers, such as hs-CRP. Results: A total of 111 patients were randomized, with 56 in the placebo group and 55 in the colchicine group. Colchicine had no significant impact on the primary outcome (change in mean: 0.051; IC95% : -0.016 à 0.117; p=0.1346) or any of the PET/CT secondary outcomes. In contrast, patients treated with colchicine presented a decrease of 28% in hs-CRP levels (p=0.0026). Conclusion: Colchicine therapy for 24 weeks had no significant impact on vascular uptake of 18F-FDG in the ascending aorta or carotid arteries. However, a reduction of 28% in hs-CRP was observed in the colchicine group. The Colchicine Cardiovascular Outcomes Trial (COLCOT) is a multicenter randomized phase III trial, currently under way, evaluating the long-term cardiovascular benefits of therapy with colchicine (0.5 mg daily) when begun less than thirty days following acute myocardial infarction

ABINIT: Overview and focus on selected capabilities

Paper published as part of the special topic on Electronic Structure SoftwareABINIT is probably the first electronic-structure package to have been released under an open-source license about 20 years ago. It implements density functional theory, density-functional perturbation theory (DFPT), many-body perturbation theory (GW approximation and Bethe–Salpeter equation), and more specific or advanced formalisms, such as dynamical mean-field theory (DMFT) and the “temperaturedependent effective potential” approach for anharmonic effects. Relying on planewaves for the representation of wavefunctions, density, and other space-dependent quantities, with pseudopotentials or projector-augmented waves (PAWs), it is well suited for the study of periodic materials, although nanostructures and molecules can be treated with the supercell technique. The present article starts with a brief description of the project, a summary of the theories upon which ABINIT relies, and a list of the associated capabilities. It then focuses on selected capabilities that might not be present in the majority of electronic structure packages either among planewave codes or, in general, treatment of strongly correlated materials using DMFT; materials under finite electric fields; properties at nuclei (electric field gradient, Mössbauer shifts, and orbital magnetization); positron annihilation; Raman intensities and electro-optic effect; and DFPT calculations of response to strain perturbation (elastic constants and piezoelectricity), spatial dispersion (flexoelectricity), electronic mobility, temperature dependence of the gap, and spin-magnetic-field perturbation. The ABINIT DFPT implementation is very general, including systems with van der Waals interaction or with noncollinear magnetism. Community projects are also described: generation of pseudopotential and PAW datasets, high-throughput calculations (databases of phonon band structure, second-harmonic generation, and GW computations of bandgaps), and the library LIBPAW. ABINIT has strong links with many other software projects that are briefly mentioned.This work (A.H.R.) was supported by the DMREF-NSF Grant No. 1434897, National Science Foundation OAC-1740111, and U.S. Department of Energy DE-SC0016176 and DE-SC0019491 projects. N.A.P. and M.J.V. gratefully acknowledge funding from the Belgian Fonds National de la Recherche Scientifique (FNRS) under Grant No. PDR T.1077.15-1/7. M.J.V. also acknowledges a sabbatical “OUT” grant at ICN2 Barcelona as well as ULiège and the Communauté Française de Belgique (Grant No. ARC AIMED G.A. 15/19-09). X.G. and M.J.V. acknowledge funding from the FNRS under Grant No. T.0103.19-ALPS. X.G. and G.-M. R. acknowledge support from the Communauté française de Belgique through the SURFASCOPE Project (No. ARC 19/24-057). X.G. acknowledges the hospitality of the CEA DAM-DIF during the year 2017. G.H. acknowledges support from the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences, Materials Sciences and Engineering Division under Contract No. DE-AC02-05-CH11231 (Materials Project Program No. KC23MP). The Belgian authors acknowledge computational resources from supercomputing facilities of the University of Liège, the Consortium des Equipements de Calcul Intensif (Grant No. FRS-FNRS G.A. 2.5020.11), and Zenobe/CENAERO funded by the Walloon Region under Grant No. G.A. 1117545. M.C. and O.G. acknowledge support from the Fonds de Recherche du Québec Nature et Technologie (FRQ-NT), Canada, and the Natural Sciences and Engineering Research Council of Canada (NSERC) under Grant No. RGPIN-2016-06666. The implementation of the libpaw library (M.T., T.R., and D.C.) was supported by the ANR NEWCASTLE project (Grant No. ANR-2010-COSI-005-01) of the French National Research Agency. M.R. and M.S. acknowledge funding from Ministerio de Economia, Industria y Competitividad (MINECO-Spain) (Grants Nos. MAT2016-77100-C2-2-P and SEV-2015-0496) and Generalitat de Catalunya (Grant No. 2017 SGR1506). This work has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 Research and Innovation program (Grant Agreement No. 724529). P.G. acknowledges support from FNRS Belgium through PDR (Grant No. HiT4FiT), ULiège and the Communauté française de Belgique through the ARC project AIMED, the EU and FNRS through M.ERA.NET project SIOX, and the European Funds for Regional Developments (FEDER) and the Walloon Region in the framework of the operational program “Wallonie-2020.EU” through the project Multifunctional thin films/LoCoTED. The Flatiron Institute is a division of the Simons Foundation. A large part of the data presented in this paper is available directly from the Abinit Web page www.abinit.org. Any other data not appearing in this web page can be provided by the corresponding author upon reasonable request.Peer reviewe

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

ABINIT: Overview and focus on selected capabilities

Abinit is probably the first electronic-structure package to have been released under an open-source license about 20 years ago. It implements density functional theory, density-functional perturbation theory (DFPT), many-body perturbation theory (GW approximation and Bethe–Salpeter equation), and more specific or advanced formalisms, such as dynamical mean-field theory (DMFT) and the “temperature-dependent effective potential” approach for anharmonic effects. Relying on planewaves for the representation of wavefunctions, density, and other space-dependent quantities, with pseudopotentials or projector-augmented waves (PAWs), it is well suited for the study of periodic materials, although nanostructures and molecules can be treated with the supercell technique. The present article starts with a brief description of the project, a summary of the theories upon which abinit relies, and a list of the associated capabilities. It then focuses on selected capabilities that might not be present in the majority of electronic structure packages either among planewave codes or, in general, treatment of strongly correlated materials using DMFT; materials under finite electric fields; properties at nuclei (electric field gradient, Mössbauer shifts, and orbital magnetization); positron annihilation; Raman intensities and electro-optic effect; and DFPT calculations of response to strain perturbation (elastic constants and piezoelectricity), spatial dispersion (flexoelectricity), electronic mobility, temperature dependence of the gap, and spin-magnetic-field perturbation. The abinit DFPT implementation is very general, including systems with van der Waals interaction or with noncollinear magnetism. Community projects are also described: generation of pseudopotential and PAW datasets, high-throughput calculations (databases of phonon band structure, second-harmonic generation, and GW computations of bandgaps), and the library libpaw. abinit has strong links with many other software projects that are briefly mentioned