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1579 Publications visible to you, out of a total of 1579
Accretion disks, quasars and cosmology: meandering towards understanding

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Abstract As Setti and Woltjer noted back in 1973, one can use quasars to construct the Hubble diagram; however, the actual application of the idea was not that straightforward. It took years to implement …It took years to implement the proposition successfully. Most ways to employ quasars for cosmology now require an advanced understanding of their structure, step by step. We briefly review this progress, with unavoidable personal biases, and concentrate on bright unobscured sources. We will mention the problem of the gas flow character close to the innermost stable circular orbit near the black hole, as discussed five decades ago. This problem later led to the development of the slim disk scenario and is recently revived in the context of Magnetically Arrested Disks (MAD) and Standard and Normal Evolution (SANE) models. We also discuss the hot or warm corona issue, which is still under debate and complicates the analysis of X-ray reflection. We present the scenario of the formation of the low ionization part of the Broad Line Region as a failed wind powered by radiation pressure acting on dust (Failed Radiatively Driven Dusty Outflow – FRADO). Next, we examine the cosmological constraints currently achievable with quasars, primarily concentrating on light echo methods (continuum time delays and spectral-line time delays to the continuum) that are (or should be) incorporating the progress mentioned above. Finally, we briefly discuss prospects in this lively subject area.

Authors: Bożena Czerny, Shulei Cao, Vikram Kumar Jaiswal, Vladimír Karas, Narayan Khadka, Mary Loli Martínez-Aldama, Mohammad Hassan Naddaf, Swayamtrupta Panda, Francisco Pozo Nuñez, Raj Prince, Bharat Ratra, Marzena Sniegowska, Zhefu Yu, Michal Zajaček

Date Published: 1st Feb 2023

Publication Type: Journal

Machine Learning Methods Improve Specificity in Newborn Screening for Isovaleric Aciduria

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Isovaleric aciduria (IVA) is a rare disorder of leucine metabolism and part of newborn screening (NBS) programs worldwide. However, NBS for IVA is hampered by, first, the increased birth prevalence due …prevalence due to the identification of individuals with an attenuated disease variant (so-called “mild” IVA) and, second, an increasing number of false positive screening results due to the use of pivmecillinam contained in the medication. Recently, machine learning (ML) methods have been analyzed, analogous to new biomarkers or second-tier methods, in the context of NBS. In this study, we investigated the application of machine learning classification methods to improve IVA classification using an NBS data set containing 2,106,090 newborns screened in Heidelberg, Germany. Therefore, we propose to combine two methods, linear discriminant analysis, and ridge logistic regression as an additional step, a digital-tier, to traditional NBS. Our results show that this reduces the false positive rate by 69.9% from 103 to 31 while maintaining 100% sensitivity in cross-validation. The ML methods were able to classify mild and classic IVA from normal newborns solely based on the NBS data and revealed that besides isovalerylcarnitine (C5), the metabolite concentration of tryptophan (Trp) is important for improved classification. Overall, applying ML methods to improve the specificity of IVA could have a major impact on newborns, as it could reduce the newborns’ and families’ burden of false positives or over-treatment.

Authors: Elaine Zaunseder, Ulrike Mütze, Sven F. Garbade, Saskia Haupt, Patrik Feyh, Georg F. Hoffmann, Vincent Heuveline, Stefan Kölker

Date Published: 1st Feb 2023

Publication Type: Journal

Hierarchical Bayesian method for constraining the neutron star equation of state with an ensemble of binary neutron star postmerger remnants

Abstract

Not specified

Authors: Alexander W. Criswell, Jesse Miller, Noah Woldemariam, Theodoros Soultanis, Andreas Bauswein, Katerina Chatziioannou, Michael W. Coughlin, Galin Jones, Vuk Mandic

Date Published: 1st Feb 2023

Publication Type: Journal

Revised Extinctions and Radii for 1.5 Million Stars Observed by APOGEE, GALAH, and RAVE

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Abstract Asteroseismology has become widely accepted as a benchmark for accurate and precise fundamental stellar properties. It can therefore be used to validate and calibrate stellar parameters derived …eters derived from other approaches. Meanwhile, one can leverage large-volume surveys in photometry, spectroscopy, and astrometry to infer stellar parameters over a wide range of evolutionary stages, independently of asteroseismology. Our pipeline, SEDEX (https://github.com/Jieyu126/SEDEX), compares the spectral energy distribution predicted by the MARCS and BOSZ model spectra with 32 photometric bandpasses, combining data from nine major, large-volume photometric surveys. We restrict the analysis to targets with available spectroscopy from the APOGEE, GALAH, and RAVE surveys to lift the temperature−extinction degeneracy. The cross-survey atmospheric parameter and uncertainty estimates are homogenized with artificial neural networks. Validation of our results with CHARA interferometry, Hubble Space Telescope CALSPEC spectrophotometry, and asteroseismology shows that we achieve high precision and accuracy. We present a catalog of improved interstellar extinction (σAV≃0.14 mag) and stellar radii (σR/R≃ 7.4%) for ∼1.5 million stars in the low-to-high-extinction (AV≲ 6 mag) fields observed by the spectroscopic surveys. We derive global extinctions for 184 Gaia DR2 open clusters and confirm the differential extinction in NGC 6791 and NGC 6819, which have been subject to extensive asteroseismic analysis. Furthermore, we report 36,854 double-lined spectroscopic main-sequence binary candidates. This catalog will be valuable for providing constraints on detailed modeling of stars and for constructing 3D dust maps of the Kepler field, the TESS Continuous Viewing Zones, and the PLATO long-duration observation fields.

Authors: Jie Yu, Shourya Khanna, Nathalie Themessl, Saskia Hekker, Guillaume Dréau, Laurent Gizon, Shaolan Bi

Date Published: 1st Feb 2023

Publication Type: Journal

Metal-Free Molecular Catalysts for the Oxygen Reduction Reaction: Electron Affinity as an Activity Descriptor

Abstract (Expand)

Heteroatom-doped polyaromatic hydrocarbons (or nanographenes) are promising molecular electrocatalysts for the oxygen reduction reaction (ORR). Here, we use density functional theory to investigate the … first step of the ORR pathway (chemisorption) for a set of molecules with experimentally determined catalytic activities. Weak chemisorption is found for only negatively charged catalysts, and a strong correlation is observed between the computed electron affinities and experimental catalytic activities for a range of B- and B,N-doped polyaromatic hydrocarbons. The electron affinity is put forward as a simple activity descriptor of charged (activated) catalysts on an electrode.

Authors: Christopher Ehlert, Anna Piras, Juliette Schleicher, Ganna Gryn’ova

Date Published: 19th Jan 2023

Publication Type: Journal

Locating Guest Molecules inside Metal–Organic Framework Pores with a Multilevel Computational Approach

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Molecular docking has traditionally mostly been employed in the field of protein–ligand binding. Here, we extend this method, in combination with DFT-level geometry optimizations, to locate guest … molecules inside the pores of metal–organic frameworks. The position and nature of the guest molecules tune the physicochemical properties of the host–guest systems. Therefore, it is essential to be able to reliably locate them to rationally enhance the performance of the known metal–organic frameworks and facilitate new material discovery. The results obtained with this approach are compared to experimental data. We show that the presented method can, in general, accurately locate adsorption sites and structures of the host–guest complexes. We therefore propose our approach as a computational alternative when no experimental structures of guest-loaded MOFs are available. Additional information on the adsorption strength in the studied host–guest systems emerges from the computed interaction energies. Our findings provide the basis for other computational studies on MOF–guest systems and contribute to a better understanding of the structure–interaction–property interplay associated with them.

Authors: Michelle Ernst, Tomasz Poręba, Lars Gnägi, Ganna Gryn’ova

Date Published: 12th Jan 2023

Publication Type: Journal

Multiscale molecular simulations to investigate adenylyl cyclase‐based signaling in the brain

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Abstract Adenylyl cyclases (ACs) play a key role in many signaling cascades. ACs catalyze the production of cyclic AMP from ATP and this function is stimulated or inhibited by the binding of their …ed by the binding of their cognate stimulatory or inhibitory Gα subunits, respectively. Here we used simulation tools to uncover the molecular and subcellular mechanisms of AC function, with a focus on the AC5 isoform, extensively studied experimentally. First, quantum mechanical/molecular mechanical free energy simulations were used to investigate the enzymatic reaction and its changes upon point mutations. Next, molecular dynamics simulations were employed to assess the catalytic state in the presence or absence of Gα subunits. This led to the identification of an inactive state of the enzyme that is present whenever an inhibitory Gα is associated, independent of the presence of a stimulatory Gα. In addition, the use of coevolution‐guided multiscale simulations revealed that the binding of Gα subunits reshapes the free‐energy landscape of the AC5 enzyme by following the classical population‐shift paradigm. Finally, Brownian dynamics simulations provided forward rate constants for the binding of Gα subunits to AC5, consistent with the ability of the protein to perform coincidence detection effectively. Our calculations also pointed to strong similarities between AC5 and other AC isoforms, including AC1 and AC6. Findings from the molecular simulations were used along with experimental data as constraints for systems biology modeling of a specific AC5‐triggered neuronal cascade to investigate how the dynamics of downstream signaling depend on initial receptor activation. This article is categorized under: Structure and Mechanism > Computational Biochemistry and Biophysics Molecular and Statistical Mechanics > Molecular Dynamics and Monte‐Carlo Methods Software > Molecular Modeling

Authors: Siri C. van Keulen, Juliette Martin, Francesco Colizzi, Elisa Frezza, Daniel Trpevski, Nuria Cirauqui Diaz, Pietro Vidossich, Ursula Rothlisberger, Jeanette Hellgren Kotaleski, Rebecca C. Wade, Paolo Carloni

Date Published: 2023

Publication Type: Journal

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