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1702 Publications visible to you, out of a total of 1702
ACSEG: AUTOMATED 3D CYTOPLASM SEGMENTATION IN SOFT X-RAY TOMOGRAPHY

Abstract (Expand)

The structure of cells is a key to understanding cellular function, diagnosis of pathological conditions, and development of new treatments. Soft X-ray tomography (SXT) is a unique tool to image cellular … structure without fixation or labeling at high spatial resolution and throughput. Ongoing improvements in faster acquisition times increase demand for accelerated image analysis. Currently, the automatic segmentation of cellular structures is a major bottleneck in the SXT data analysis pipeline. In this paper, we introduce an automated 3D cytoplasm segmentation model - ACSeg - by use of semi-automatically segmented labels and 3D U-Net, implemented in the online platform Biomedisa. The segmentation model is trained on semi-automatically labeled datasets and shows rapid convergence to high-accuracy segmentation, therefore reducing time and labor. ACSeg trained on 43 SXT tomograms of human immune T cells, the model successfully segmented unseen SXT tomograms of human hepatocyte-derived carcinoma cells, mouse microglia, and embryonic fibroblast cells. Furthermore, we could diversify the model by adding only 6 specific SXT tomograms, showing the potential for the development of an optimal experimental design. The ACSeg is published on the open image segmentation platform Biomedisa, enabling high-throughput analysis of cell volume and structure of cytoplasm in diverse cell types. The approach can be expanded for automatic segmentation of other organelles visualized by SXT, providing means for structural analysis of cell remodeling under different pathogens at statistically significant sizes, therefore enabling the development of novel drug treatments.

Authors: Ayse Erozan, Philipp Lösel, Vincent Heuveline, Venera Weinhardt

Date Published: 5th Apr 2023

Publication Type: Journal

DOPA Residues Endow Collagen with Radical Scavenging Capacity

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Here we uncover collagen, the main structural protein of all connective tissues, as a redox-active material. We identify dihydroxyphenylalanine (DOPA) residues, post-translational oxidation products … of tyrosine residues, to be common in collagen derived from different connective tissues. We observe that these DOPA residues endow collagen with substantial radical scavenging capacity. When reducing radicals, DOPA residues work as redox relay: they convert to the quinone and generate hydrogen peroxide. In this dual function, DOPA outcompetes its amino acid precursors and ascorbic acid. Our results establish DOPA residues as redox-active side chains of collagens, probably protecting connective tissues against radicals formed under mechanical stress and/or inflammation.

Authors: Markus Kurth, Uladzimir Barayeu, Hassan Gharibi, Andrei Kuzhelev, Kai Riedmiller, Jennifer Zilke, Kasimir Noack, Vasyl Denysenkov, Reinhard Kappl, Thomas F. Prisner, Roman A. Zubarev, Tobias P. Dick, Frauke Gräter

Date Published: 3rd Apr 2023

Publication Type: Journal

Encompassing tests for value at risk and expected shortfall multistep forecasts based on inference on the boundary

Abstract

Not specified

Authors: Timo Dimitriadis, Xiaochun Liu, Julie Schnaitmann

Date Published: 1st Apr 2023

Publication Type: Journal

On testing equal conditional predictive ability under measurement error

Abstract

Not specified

Authors: Yannick Hoga, Timo Dimitriadis

Date Published: 1st Apr 2023

Publication Type: Journal

Applications of AI in Astronomy

Abstract (Expand)

We provide a brief, and inevitably incomplete overview of the use of Machine Learning (ML) and other AI methods in astronomy, astrophysics, and cosmology. Astronomy entered the big data era with the … first digital sky surveys in the early 1990s and the resulting Terascale data sets, which required automating of many data processing and analysis tasks, for example the star-galaxy separation, with billions of feature vectors in hundreds of dimensions. The exponential data growth continued, with the rise of synoptic sky surveys and the Time Domain Astronomy, with the resulting Petascale data streams and the need for a real-time processing, classification, and decision making. A broad variety of classification and clustering methods have been applied for these tasks, and this remains a very active area of research. Over the past decade we have seen an exponential growth of the astronomical literature involving a variety of ML/AI applications of an ever increasing complexity and sophistication. ML and AI are now a standard part of the astronomical toolkit. As the data complexity continues to increase, we anticipate further advances leading towards a collaborative human-AI discovery.

Authors: S. G. Djorgovski, Ashish Mahabal, M. J. Graham, Kai L. Polsterer, Alberto Krone-Martins

Date Published: 1st Apr 2023

Publication Type: InCollection

Jupiter’s interior from Juno: Equation-of-state uncertainties and dilute core extent

Abstract (Expand)

Context: The Juno mission has provided measurements of Jupiter’s gravity field with an outstanding level of accuracy, leading to better constraints on the interior of the planet. Improving our knowledge … of the internal structure of Jupiter is key to understanding its formation and evolution but is also important in the framework of exoplanet exploration. Aims: In this study, we investigated the differences between the state-of-the-art equations of state and their impact on the properties of interior models. Accounting for uncertainty on the hydrogen and helium equation of state, we assessed the span of the interior features of Jupiter. Methods: We carried out an extensive exploration of the parameter space and studied a wide range of interior models using Markov chain Monte Carlo simulations. To consider the uncertainty on the equation of state, we allowed for modifications of the equation of state in our calculations. Results: Our models harbour a dilute core and indicate that Jupiter’s internal entropy is higher than what is usually assumed from the Galileo probe measurements. We obtain solutions with extended dilute cores, but contrary to other recent interior models of Jupiter, we also obtain models with small dilute cores. The dilute cores in such solutions extend to ~20% of Jupiter’s mass, leading to better agreement with formation–evolution models. Conclusions: We conclude that the equations of state used in Jupiter models have a crucial effect on the inferred structure and composition. Further explorations of the behaviour of hydrogen–helium mixtures at the pressure and temperature conditions in Jupiter will help to constrain the interior of the planet, and therefore its origin.

Authors: S. Howard, T. Guillot, M. Bazot, Y. Miguel, D. J. Stevenson, E. Galanti, Y. Kaspi, W. B. Hubbard, B. Militzer, R. Helled, N. Nettelmann, B. Idini, S. Bolton

Date Published: 1st Apr 2023

Publication Type: Journal

Gravitational wave emission from dynamical stellar interactions

Abstract

Not specified

Authors: Javier Morán-Fraile, Fabian R. N. Schneider, Friedrich K. Röpke, Sebastian T. Ohlmann, Rüdiger Pakmor, Theodoros Soultanis, Andreas Bauswein

Date Published: 1st Apr 2023

Publication Type: Journal

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