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1703 Publications visible to you, out of a total of 1703
Astrophysics with the Laser Interferometer Space Antenna

Abstract

Not specified

Authors: Pau Amaro-Seoane, Jeff Andrews, Manuel Arca Sedda, Abbas Askar, Quentin Baghi, Razvan Balasov, Imre Bartos, Simone S. Bavera, Jillian Bellovary, Christopher P. L. Berry, Emanuele Berti, Stefano Bianchi, Laura Blecha, Stéphane Blondin, Tamara Bogdanović, Samuel Boissier, Matteo Bonetti, Silvia Bonoli, Elisa Bortolas, Katelyn Breivik, Pedro R. Capelo, Laurentiu Caramete, Federico Cattorini, Maria Charisi, Sylvain Chaty, Xian Chen, Martyna Chruślińska, Alvin J. K. Chua, Ross Church, Monica Colpi, Daniel D’Orazio, Camilla Danielski, Melvyn B. Davies, Pratika Dayal, Alessandra De Rosa, Andrea Derdzinski, Kyriakos Destounis, Massimo Dotti, Ioana Dutan, Irina Dvorkin, Gaia Fabj, Thierry Foglizzo, Saavik Ford, Jean-Baptiste Fouvry, Alessia Franchini, Tassos Fragos, Chris Fryer, Massimo Gaspari, Davide Gerosa, Luca Graziani, Paul Groot, Melanie Habouzit, Daryl Haggard, Zoltan Haiman, Wen-Biao Han, Alina Istrate, Peter H. Johansson, Fazeel Mahmood Khan, Tomas Kimpson, Kostas Kokkotas, Albert Kong, Valeriya Korol, Kyle Kremer, Thomas Kupfer, Astrid Lamberts, Shane Larson, Mike Lau, Dongliang Liu, Nicole Lloyd-Ronning, Giuseppe Lodato, Alessandro Lupi, Chung-Pei Ma, Tomas Maccarone, Ilya Mandel, Alberto Mangiagli, Michela Mapelli, Stéphane Mathis, Lucio Mayer, Sean McGee, Barry McKernan, M. Coleman Miller, David F. Mota, Matthew Mumpower, Syeda S. Nasim, Gijs Nelemans, Scott Noble, Fabio Pacucci, Francesca Panessa, Vasileios Paschalidis, Hugo Pfister, Delphine Porquet, John Quenby, Angelo Ricarte, Friedrich K. Röpke, John Regan, Stephan Rosswog, Ashley Ruiter, Milton Ruiz, Jessie Runnoe, Raffaella Schneider, Jeremy Schnittman, Amy Secunda, Alberto Sesana, Naoki Seto, Lijing Shao, Stuart Shapiro, Carlos Sopuerta, Nicholas C. Stone, Arthur Suvorov, Nicola Tamanini, Tomas Tamfal, Thomas Tauris, Karel Temmink, John Tomsick, Silvia Toonen, Alejandro Torres-Orjuela, Martina Toscani, Antonios Tsokaros, Caner Unal, Verónica Vázquez-Aceves, Rosa Valiante, Maurice van Putten, Jan van Roestel, Christian Vignali, Marta Volonteri, Kinwah Wu, Ziri Younsi, Shenghua Yu, Silvia Zane, Lorenz Zwick, Fabio Antonini, Vishal Baibhav, Enrico Barausse, Alexander Bonilla Rivera, Marica Branchesi, Graziella Branduardi-Raymont, Kevin Burdge, Srija Chakraborty, Jorge Cuadra, Kristen Dage, Benjamin Davis, Selma E. de Mink, Roberto Decarli, Daniela Doneva, Stephanie Escoffier, Poshak Gandhi, Francesco Haardt, Carlos O. Lousto, Samaya Nissanke, Jason Nordhaus, Richard O’Shaughnessy, Simon Portegies Zwart, Adam Pound, Fabian Schussler, Olga Sergijenko, Alessandro Spallicci, Daniele Vernieri, Alejandro Vigna-Gómez

Date Published: 1st Dec 2023

Publication Type: Journal

Simulations of common-envelope evolution in binary stellar systems: physical models and numerical techniques

Abstract

Not specified

Authors: Friedrich K. Röpke, Orsola De Marco

Date Published: 1st Dec 2023

Publication Type: Journal

Comparative analysis of drug-salt-polymer interactions by experiment and molecular simulation improves biopharmaceutical performance

Abstract (Expand)

Abstract The propensity of poorly water-soluble drugs to aggregate at supersaturation impedes their bioavailability. Supersaturated amorphous drug-salt-polymer systems provide an emergent approach to …r systems provide an emergent approach to this problem. However, the effects of polymers on drug-drug interactions in aqueous phase are largely unexplored and it is unclear how to choose an optimal salt-polymer combination for a particular drug. Here, we describe a comparative experimental and computational characterization of amorphous solid dispersions containing the drug celecoxib, and a polymer, polyvinylpyrrolidone vinyl acetate (PVP-VA) or hydroxypropyl methylcellulose acetate succinate, with or without Na + /K + salts. Classical models for drug-polymer interactions fail to identify the best drug-salt-polymer combination. In contrast, more stable drug-polymer interaction energies computed from molecular dynamics simulations correlate with prolonged stability of supersaturated amorphous drug-salt-polymer systems, along with better dissolution and pharmacokinetic profiles. The celecoxib-salt-PVP-VA formulations exhibit excellent biopharmaceutical performance, offering the prospect of a low-dosage regimen for this widely used anti-inflammatory, thereby increasing cost-effectiveness, and reducing side-effects.

Authors: Sumit Mukesh, Goutam Mukherjee, Ridhima Singh, Nathan Steenbuck, Carolina Demidova, Prachi Joshi, Abhay T. Sangamwar, Rebecca C. Wade

Date Published: 1st Dec 2023

Publication Type: Journal

Host–guest interactions in framework materials: Insight from modeling

Abstract (Expand)

The performance of metal–organic and covalent organic framework materials in sought-after applications—capture, storage, and delivery of gases and molecules, and separation of their mixtures—heavily …xtures—heavily depends on the host–guest interactions established inside the pores of these materials. Computational modeling provides information about the structures of these host–guest complexes and the strength and nature of the interactions present at a level of detail and precision that is often unobtainable from experiment. In this Review, we summarize the key simulation techniques spanning from molecular dynamics and Monte Carlo methods to correlate ab initio approaches and energy, density, and wavefunction partitioning schemes. We provide illustrative literature examples of their uses in analyzing and designing organic framework hosts. We also describe modern approaches to the high-throughput screening of thousands of existing and hypothetical metal–organic frameworks (MOFs) and covalent organic frameworks (COFs) and emerging machine learning techniques for predicting their properties and performances. Finally, we discuss the key methodological challenges on the path toward computation-driven design and reliable prediction of high-performing MOF and COF adsorbents and catalysts and suggest possible solutions and future directions in this exciting field of computational materials science.

Authors: Michelle Ernst, Jack D. Evans, Ganna Gryn'ova

Date Published: 1st Dec 2023

Publication Type: Journal

The young massive SMC cluster NGC 330 seen by MUSE. III. Stellar parameters and rotational velocities

Abstract

Not specified

Authors: J. Bodensteiner, H. Sana, P. L. Dufton, C. Wang, N. Langer, G. Banyard, L. Mahy, A. de Koter, S. E. de Mink, C. J. Evans, Y. Götberg, V. Hénault-Brunet, L. R. Patrick, F. R. N. Schneider

Date Published: 1st Dec 2023

Publication Type: Journal

Dominantly inherited micro-satellite instable cancer – the four Lynch syndromes - an EHTG, PLSD position statement

Abstract (Expand)

Abstract The recognition of dominantly inherited micro-satellite instable (MSI) cancers caused by pathogenic variants in one of the four mismatch repair ( MMR ) genes MSH2, MLH1, MSH6 and PMS2 has … MMR ) genes MSH2, MLH1, MSH6 and PMS2 has modified our understanding of carcinogenesis. Inherited loss of function variants in each of these MMR genes cause four dominantly inherited cancer syndromes with different penetrance and expressivities: the four Lynch syndromes. No person has an “average sex “or a pathogenic variant in an “average Lynch syndrome gene” and results that are not stratified by gene and sex will be valid for no one. Carcinogenesis may be a linear process from increased cellular division to localized cancer to metastasis. In addition, in the Lynch syndromes (LS) we now recognize a dynamic balance between two stochastic processes: MSI producing abnormal cells, and the host’s adaptive immune system’s ability to remove them. The latter may explain why colonoscopy surveillance does not reduce the incidence of colorectal cancer in LS, while it may improve the prognosis. Most early onset colon, endometrial and ovarian cancers in LS are now cured and most cancer related deaths are after subsequent cancers in other organs. Aspirin reduces the incidence of colorectal and other cancers in LS. Immunotherapy increases the host immune system’s capability to destroy MSI cancers. Colonoscopy surveillance, aspirin prevention and immunotherapy represent major steps forward in personalized precision medicine to prevent and cure inherited MSI cancer.

Authors: Pal Møller, Toni T. Seppälä, Aysel Ahadova, Emma J. Crosbie, Elke Holinski-Feder, Rodney Scott, Saskia Haupt, Gabriela Möslein, Ingrid Winship, Sanne W. Bajwa-ten Broeke, Kelly E. Kohut, Neil Ryan, Peter Bauerfeind, Laura E. Thomas, D. Gareth Evans, Stefan Aretz, Rolf H. Sijmons, Elizabeth Half, Karl Heinimann, Karoline Horisberger, Kevin Monahan, Christoph Engel, Giulia Martina Cavestro, Robert Fruscio, Naim Abu-Freha, Levi Zohar, Luigi Laghi, Lucio Bertario, Bernardo Bonanni, Maria Grazia Tibiletti, Leonardo S. Lino-Silva, Carlos Vaccaro, Adriana Della Valle, Benedito Mauro Rossi, Leandro Apolinário da Silva, Ivana Lucia de Oliveira Nascimento, Norma Teresa Rossi, Tadeusz Dębniak, Jukka-Pekka Mecklin, Inge Bernstein, Annika Lindblom, Lone Sunde, Sigve Nakken, Vincent Heuveline, John Burn, Eivind Hovig, Matthias Kloor, Julian R. Sampson, Mev Dominguez-Valentin

Date Published: 1st Dec 2023

Publication Type: Journal

In situ or accreted? Using deep learning to infer the origin of extragalactic globular clusters from observables

Abstract (Expand)

ABSTRACT Globular clusters (GCs) are powerful tracers of the galaxy assembly process, and have already been used to obtain a detailed picture of the progenitors of the Milky Way (MW). Using the E-MOSAICS … (MW). Using the E-MOSAICS cosmological simulation of a (34.4 Mpc)3 volume that follows the formation and co-evolution of galaxies and their star cluster populations, we develop a method to link the origin of GCs to their observable properties. We capture this complex link using a supervised deep learning algorithm trained on the simulations, and predict the origin of individual GCs (whether they formed in the main progenitor or were accreted from satellites) based solely on extragalactic observables. An artificial neural network classifier trained on ∼50 000 GCs hosted by ∼700 simulated galaxies successfully predicts the origin of GCs in the test set with a mean accuracy of 89 per cent for the objects with $\rm [Fe/H]\lt -0.5$ that have unambiguous classifications. The network relies mostly on the alpha-element abundances, metallicities, projected positions, and projected angular momenta of the clusters to predict their origin. A real-world test using the known progenitor associations of the MW GCs achieves up to 90 per cent accuracy, and successfully identifies as accreted most of the GCs in the inner Galaxy associated to the Kraken progenitor, as well as all the Gaia-Enceladus GCs. We demonstrate that the model is robust to observational uncertainties, and develop a method to predict the classification accuracy across observed galaxies. The classifier can be optimized for available observables (e.g. to improve the accuracy by including GC ages), making it a valuable tool to reconstruct the assembly histories of galaxies in upcoming wide-field surveys.

Authors: Sebastian Trujillo-Gomez, J M Diederik Kruijssen, Joel Pfeffer, Marta Reina-Campos, Robert A Crain, Nate Bastian, Ivan Cabrera-Ziri

Date Published: 1st Dec 2023

Publication Type: Journal

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