A white dwarf merger as progenitor of the anomalous X-ray pulsar 4U 0142+61?

It has been recently proposed that massive fast-rotating highly-magnetized white dwarfs could describe the observational properties of some of Soft Gamma-Ray Repeaters (SGRs) and Anomalous X-Ray Pulsars (AXPs). Moreover, it has also been shown that high-field magnetic (HFMWDs) can be the outcome of white dwarf binary mergers. The products of these mergers consist of a hot central white dwarf surrounded by a rapidly rotating disk. Here we show that the merger of a double degenerate system can explain the characteristics of the peculiar AXP 4U 0142+61. This scenario accounts for the observed infrared excess. We also show that the observed properties of 4U 0142+6 are consistent with an approximately 1.2 M_{\sun} white dwarf, remnant of the coalescence of an original system made of two white dwarfs of masses 0.6\, M_{\sun} and 1.0\, M_{\sun}. Finally, we infer a post-merging age $\tau_{\rm WD}\approx 64$ kyr, and a magnetic field $B\approx 2\times 10^8$ G. Evidence for such a magnetic field may come from the possible detection of the electron cyclotron absorption feature observed between the $B$ and $V$ bands at $\approx 10^{15}$ Hz in the spectrum of 4U 0142+61.Comment: to appear in ApJ Letter

TREX-DM: a low background Micromegas-based TPC for low-mass WIMP detection

Dark Matter experiments are recently focusing their detection techniques in low-mass WIMPs, which requires the use of light elements and low energy threshold. In this context, we describe the TREX-DM experiment, a low background Micromegas-based TPC for low-mass WIMP detection. Its main goal is the operation of an active detection mass $\sim$0.3 kg, with an energy threshold below 0.4 keVee and fully built with previously selected radiopure materials. This work describes the commissioning of the actual setup situated in a laboratory on surface and the updates needed for a possible physics run at the Canfranc Underground Laboratory (LSC) in 2016. A preliminary background model of TREX-DM is also presented, based on a Geant4 simulation, the simulation of the detector's response and two discrimination methods: a conservative muon/electron and one based on a neutron source. Based on this background model, TREX-DM could be competitive in the search for low-mass WIMPs. In particular it could be sensitive, e.g., to the low-mass WIMP interpretation of the DAMA/LIBRA and other hints in a conservative scenario.Comment: Proceedings of the XIV International Conference on Topics in Astroparticle and Underground Physics (TAUP 2015), 7-11 September 2015, Torino, Ital

TREX-DM: a low background Micromegas-based TPC for low mass WIMP detection

Dark Matter experiments are recently focusing their detection techniques in low-mass WIMPs, which requires the use of light elements and low energy threshold. In this context, we present the TREX-DM experiment, a low background Micromegas-based TPC for low-mass WIMP detection. Its main goal is the operation of an active detection mass $\sim$0.300 kg, with an energy threshold below 0.4 keVee and fully built with previously selected radiopure materials. This article describes the actual setup, the first results of the comissioning in Ar+2\%iC$_4$H$_{10}$ at 1.2 bar and the future updates for a possible physics run at the Canfranc Underground Laboratory in 2016. A first background model is also presented, based on Geant4 simulations and a muon/electron discrimination method. In a conservative scenario, TREX-DM could be sensitive to DAMA/LIBRA and other hints of positive WIMPs signals, with some space for improvement with a neutron/electron discrimination method or the use of other light gases.Comment: Proceedings of the 7th Symposium on Large TPCs for Low-Energy Rare Event Detectio

Computational modelling of epithelial cell monolayers during infection with Listeria monocytogenes

Intracellular bacterial infections alter the normal functionality of human host cells and tissues. Infection can also modify the mechanical properties of host cells, altering the mechanical equilibrium of tissues. In order to advance our understanding of host–pathogen interactions, simplified in vitro models are normally used. However, in vitro studies present certain limitations that can be alleviated by the use of computer-based models. As complementary tools these computational models, in conjunction with in vitro experiments, can enhance our understanding of the mechanisms of action underlying infection processes. In this work, we extend our previous computer-based model to simulate infection of epithelial cells with the intracellular bacterial pathogen Listeria monocytogenes. We found that forces generated by host cells play a regulatory role in the mechanobiological response to infection. After infection, in silico cells alter their mechanical properties in order to achieve a new mechanical equilibrium. The model pointed the key role of cell–cell and cell–extracellular matrix interactions in the mechanical competition of bacterial infection. The obtained results provide a more detailed description of cell and tissue responses to infection, and could help inform future studies focused on controlling bacterial dissemination and the outcome of infection processes. © 2022 The Author(s

A Micromegas-based low-background x-ray detector coupled to a slumped-glass telescope for axion research

We report on the design, construction and operation of a low background x-ray detection line composed of a shielded Micromegas (micromesh gaseous structure) detector of the microbulk technique. The detector is made from radiopure materials and is placed at the focal point of a $\sim$~5 cm diameter, 1.3 m focal-length, cone-approximation Wolter I x-ray telescope (XRT) comprised of thermally-formed (or "slumped") glass substrates deposited with multilayer coatings. The system has been conceived as a technological pathfinder for the future International Axion Observatory (IAXO), as it combines two of the techniques (optic and detector) proposed in the conceptual design of the project. It is innovative for two reasons: it is the first time an x-ray optic has been designed and fabricated specifically for axion research, and the first time a Micromegas detector has been operated with an x-ray optic. The line has been installed at one end of the CERN Axion Solar Telescope (CAST) magnet and is currently looking for solar axions. The combination of the XRT and Micromegas detector provides the best signal-to-noise ratio obtained so far by any detection system of the CAST experiment with a background rate of 5.4$\times$10$^{-3}\;$counts per hour in the energy region-of-interest and signal spot area.Comment: 21 pages, 16 figure

Collective cell durotaxis emerges from long-range intercellular force transmission

The ability of cells to follow gradients of extracellular matrix stiffness-durotaxis-has been implicated in development, fibrosis, and cancer. Here, we found multicellular clusters that exhibited durotaxis even if isolated constituent cells did not. This emergent mode of directed collective cell migration applied to a variety of epithelial cell types, required the action of myosin motors, and originated from supracellular transmission of contractile physical forces. To explain the observed phenomenology, we developed a generalized clutch model in which local stick-slip dynamics of cell-matrix adhesions was integrated to the tissue level through cell-cell junctions. Collective durotaxis is far more efficient than single-cell durotaxis; it thus emerges as a robust mechanism to direct cell migration during development, wound healing, and collective cancer cell invasion

Balance of mechanical forces drives endothelial gap formation and may facilitate cancer and immune-cell extravasation

The formation of gaps in the endothelium is a crucial process underlying both cancer and immune cell extravasation, contributing to the functioning of the immune system during infection, the unfavorable development of chronic inflammation and tumor metastasis. Here, we present a stochastic-mechanical multiscale model of an endothelial cell monolayer and show that the dynamic nature of the endothelium leads to spontaneous gap formation, even without intervention from the transmigrating cells. These gaps preferentially appear at the vertices between three endothelial cells, as opposed to the border between two cells. We quantify the frequency and lifetime of these gaps, and validate our predictions experimentally. Interestingly, we find experimentally that cancer cells also preferentially extravasate at vertices, even when they first arrest on borders. This suggests that extravasating cells, rather than initially signaling to the endothelium, might exploit the autonomously forming gaps in the endothelium to initiate transmigration

A multiscale orchestrated computational framework to reveal emergent phenomena in neuroblastoma

Neuroblastoma is a complex and aggressive type of cancer that affects children. Current treatments involve a combination of surgery, chemotherapy, radiotherapy, and stem cell transplantation. However, treatment outcomes vary due to the heterogeneous nature of the disease. Computational models have been used to analyse data, simulate biological processes, and predict disease progression and treatment outcomes. While continuum cancer models capture the overall behaviour of tumours, and agent-based models represent the complex behaviour of individual cells, multiscale models represent interactions at different organisational levels, providing a more comprehensive understanding of the system. In 2018, the PRIMAGE consortium was formed to build a cloud-based decision support system for neuroblastoma, including a multi-scale model for patient-specific simulations of disease progression. In this work we have developed this multi-scale model that includes data such as patient's tumour geometry, cellularity, vascularization, genetics and type of chemotherapy treatment, and integrated it into an online platform that runs the simulations on a high-performance computation cluster using Onedata and Kubernetes technologies. This infrastructure will allow clinicians to optimise treatment regimens and reduce the number of costly and time-consuming clinical trials. This manuscript outlines the challenging framework's model architecture, data workflow, hypothesis, and resources employed in its development