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We use the IllustrisTNG100 hydrodynamical simulation to study the dependence of the galaxy two-point correlation function on a broad range of secondary subhalo and galactic properties. We construct galaxy mock catalogues adopting a standard subhalo abundance matching scheme coupled with a secondary assignment between galaxy colour or specific star formation rate and the following subhalo properties: starvation redshift zstarve, concentration at infall, overdensity $\delta _R^{\rm env}$, tidal anisotropy αR, and tidal overdensity δR. The last two quantities allow us to fully characterize the tidal field of our subhaloes, acting as mediators between their internal and large-scale properties. The resulting mock catalogues overall return good agreement with the IllustrisTNG100 measurements. The accuracy of each model strongly depends on the correlation between the secondary galaxy and subhalo properties employed. Among all the subhalo proxies tested, we find that zstarve and cinfall are the ones that best trace the large-scale structure, producing robust clustering predictions for different samples of red/blue and quenched/star-forming galaxies.

Context. We present a novel approach to the construction of mock galaxy catalogues for large-scale structure analysis based on the distribution of dark matter halos obtained with effective bias models at the field level. Aims. We aim to produce mock galaxy catalogues capable of generating accurate covariance matrices for a number of cosmological probes that are expected to be measured in current and forthcoming galaxy redshift surveys (e.g. two- and three-point statistics). The construction of the catalogues shown in this paper is part of a mock-comparison project within the Dark Energy Spectroscopic Instrument (DESI) collaboration., Methods. We use the bias assignment method (BAM) to model the statistics of halo distribution through a learning algorithm using a few detailed N-body simulations, and approximated gravity solvers based on Lagrangian perturbation theory. We introduce cosmic-web-dependent corrections to modelling redshift-space distortions at the N-body level - both in the halo and galaxy distributions -, as well as a multi-scale approach for accurate assignment of halo properties. Using specific models of halo occupation distributions to populate halos, we generate galaxy mocks with the expected number density and central-satellite fraction of emission-line galaxies, which are a key target of the DESI experiment., Results. BAM generates mock catalogues with per cent accuracy in a number of summary statistics, such as the abundance, the twoand three-point statistics of halo distributions, both in real and redshift space. In particular, the mock galaxy catalogues display similar to 3%-10% accuracy in the multipoles of the power spectrum up to scales of k similar to 0.4 h(-1)Mpc. We show that covariance matrices of two- and three-point statistics obtained with BAM display a similar structure to the reference simulation., Conclusions. BAM o ffers an efficient way to produce mock halo catalogues with accurate two- and three-point statistics, and is able to generate a variety of multi-tracer catalogues with precise covariance matrices of several cosmological probes. We discuss future developments of the algorithm towards mock production in DESI and other galaxy-redshift surveys.

“Amyloid Aggregation” is an Italian Space Agency (ASI)-granted project designed to investigate if and how beta amyloid peptides aggregation is affected by microgravity, in the light of a possible professional risk in astronauts on long-lasting space missions. Researchers of the Istituto Zooprofilattico Sperimentale del Piemonte Liguria e Valle d'Aosta (IZSPLV) and the Istituto Superiore di Sanita (Ist.Sup.San) conceived the project while the Aerospace Logistics Technology Engineering Company (ALTEC) developed the payload. ARGOTEC/Telespazio (UTISS Team) supported safety evaluation, payload manifesting and qualification processes for a safe and efficient delivery, utilization, and integration on board the International Space Station (ISS), and finally recovery of the experimental hardware once returned to Earth. The hardware consisted of 48 special jars containing 6 different time period experimental groups and 2 control groups. In August 2019, during the “BEYOND” mission on board the ISS, astronaut Luca Parmitano activated individual jars according to a defined protocol. At the end of each Incubation Time Periods (ITPs), the samples were transferred in the cold stowage system to stop the aggregation reaction until the analysis after re-entry. Forty-eight identical samples have been prepared and activated in November 2019 on Earth. ALTEC developed jars and packaging for space transportation, qualified and delivered the flight hardware, according to requirements. We here provide an update on the optimization of analytical techniques described in the project specifically intended to warrant an up-to-date, robust and reliable examination of samples that we plan to accomplish in the next months within the proposed timeframe of the project.

This is a pre-copyedited, author-produced PDF of an article accepted for publication in Monthly Notices of the Royal Astronomical Society following peer review. The version of record Monthly Notices of the Royal Astronomical Society 510.4 (2022): 5392-5407 is available online at: https://academic.oup.com/mnras/article-abstract/510/4/5392/6505155?redirectedFrom=fulltext, New surv e ys such as European Space Agenc ys (ESA's) Euclid mission are planned to map with unprecedented precision the large-scale structure of the Universe by measuring the 3D positions of tens of millions of galaxies. It is necessary to develop theoretically modelled galaxy catalogues to estimate the expected performance and to optimize the analysis strategy of these surv e ys. We populate two pairs of (1 h -1 Gpc) 3 volume dark matter-only simulations from the UNIT project with galaxies using the Semi-Analytic Galaxy Evolution semi-analytic model of galaxy formation, coupled to the photoionization model GET EMLINES to estimate their H αemission. These catalogues represent a unique suite that includes galaxy formation physics and -thanks to the fixed-pair technique used -an ef fecti ve volume of ∼(5 h -1 Gpc ) 3 , which is several times larger than the Euclid surv e y. We present the performance of these data and create five additional emission-line galaxy (ELG) catalogues by applying a dust-attenuation model as well as adjusting the flux threshold as a function of redshift in order to reproduce Euclid-forecast d N /d z values. As a first application, we study the abundance and clustering of those model H αELGs: For scales greater than ∼5 h -1 Mpc, we find a scale- independent bias with a value of b ∼1 at redshift z ∼0.5, that can increase nearly linearly to b ∼4 at z ∼2, depending on the ELG catalogue. Model galaxy properties, including their emission-line fluxes (with and without dust extinction) are publicly available

SkyPy is an open-source Python package for simulating the astrophysical sky. It comprises a library of physical and empirical models across a range of observables and a command-line script to run end-to-end simulations. The library provides functions that sample realisations of sources and their associated properties from probability distributions. Simulation pipelines are constructed from these models using a YAML-based configuration syntax, while task scheduling and data dependencies are handled internally and the modular design allows users to interface with external software. SkyPy is developed and maintained by a diverse community of domain experts with a focus on software sustainability and interoperability. By fostering development, it provides a framework for correlated simulations of a range of cosmological probes including galaxy populations, large scale structure, the cosmic microwave background, supernovae and gravitational waves. Version 0.4 implements functions that model various properties of galaxies including luminosity functions, redshift distributions and optical photometry from spectral energy distribution templates. Future releases will provide additional modules, for example, to simulate populations of dark matter halos and model the galaxy-halo connection, making use of existing software packages from the astrophysics community where appropriate., Published by JOSS. The package is available at https://github.com/skypyproject/skypy. Comments, issues and pull requests are welcome

Aim: Early onset of psychopathology is often an index of a more severe clinical course and worse prognosis. This review examined the course of bipolar disorder (BD) with onset in childhood and adolescence, with a focus on persistence of symptoms, severity of illness, comorbidity, and functional impairment. Methods: The databases of PubMed, Embase, and PsycInfo were systematically searched for publications since 1990 reporting on long-term (12 months or longer) assessments of patients with early onset BD. Results: Forty-two relevant publications were identified, which reported on data derived from 15 different patient cohorts, including 7 prospective research psychopathology studies, 4 medical record reviews, 2 follow-ups of clinical trial samples, 1 managed care database, and 1 nationwide registry, for a total of 10,187 patients. The length of follow-ups ranged from 1.0 to 15 years. Diagnostic stability of BD ranged from 73% to 100% over ten years. Recovery rate from an index episode was 81.5–100% and recurrence rate was 35–67%. Suicide attempt cumulative prevalence in five years was 18–20%. Earlier age at the first episode predicted a more severe clinical course. Conclusions: Early onset BD persists over time through adolescence, with homotypic diagnostic continuity over the years, but heterogeneity in the severity of the clinical course. Whether early identification and treatment improves distal prognosis remains to be further investigated.

Halo assembly bias is the secondary dependence of the clustering of dark-matter haloes on their assembly histories at fixed halo mass. This established dependence is expected to manifest itself on the clustering of the galaxy population, a potential effect commonly known as galaxy assembly bias. Using the IllustrisTNG300 magnetohydrodynamical simulation, we analyse the dependence of the properties and clustering of galaxies on the shape of the specific mass accretion history of their hosting haloes (sMAH). We first show that several halo and galaxy properties strongly correlate with the slope of the sMAH ($\beta$) at fixed halo mass. Namely, haloes with increasingly steeper $\beta$ increment their halo masses faster at early times, and their hosted galaxies present larger stellar-to-halo mass ratios, lose their gas faster, reach the peak of their star formation histories at higher redshift, and become quenched earlier. We also demonstrate that $\beta$ is more directly connected to these key galaxy formation properties than other broadly employed halo proxies, such as formation time. Finally, we measure the secondary dependence of galaxy clustering on $\beta$ at fixed halo mass as a function of redshift. By tracing back the evolution of individual haloes, we show that the amplitude of the galaxy assembly bias signal for the progenitors of $z=0$ galaxies increases with redshift, reaching a factor of 2 at $z = 1$ for haloes of $M_\mathrm{halo}=10^{11.5}-10^{12}$ $h^{-1}\mathrm{M}_\odot$. The measurement of the evolution of assembly bias along the merger tree provides a new theoretical perspective to the study of secondary bias. Our findings, which show a tight relationship between halo accretion and both the clustering and the observational properties of the galaxy population, have also important implications for the generation of mock catalogues for upcoming cosmological surveys., Comment: 10 pages, 6 figures. Submitted to MNRAS

The concentration-mass (c-M) relation encodes the key information of the assembly history of the dark matter halos, however its behavior at the high mass end has not been measured precisely in observations yet. In this paper, we report the measurement of halo c-M relation with galaxy-galaxy lensing method, using shear catalog of the Dark Energy Camera Legacy Survey (DECaLS) Data Release 8, which covers a sky area of 9500 deg^2. The foreground lenses are selected from redMaPPer, LOWZ, and CMASS catalogs, with halo mass range from 10^{13} to 10^{15} M_sun and redshift range from z=0.08 to z=0.65. We find that the concentration decreases with the halo mass from 10^{13} to 10^{14} M_sun, but shows a trend of upturn after the pivot point of ~10^{14} M_sun. We fit the measured c-M relation with the concentration model c(M)=C_0 (M/(10^{12} M_sun/h)^{-��} [1+(M/M_0)^{0.4}], and get the values (C_0, ��, log(M_0) = (5.119_{-0.185}^{0.183}, 0.205_{-0.010}^{0.010}, 14.083_{-0.133}^{0.130}), and (4.875_{-0.208}^{0.209}, 0.221_{-0.010}^{0.010}, 13.750_{-0.141}^{0.142}) for halos with 0.08, 12 pages, 5 figures, accepted by ApJ

We test the history of structure formation from redshift 1 to today by matching galaxies from VIPERS and SDSS with dark matter haloes in the MultiDark SMDPL N-body simulation. We first show that the standard subhalo abundance matching (SHAM) recipe implemented with MultiDark characterizes the clustering of galaxies well both at redshift 0 for SDSS and at redshift 1 for VIPERS. This is an important validation of the SHAM model at high redshift. We then remap the simulation timesteps to test alternative growth histories and infer the growth index $\gamma=0.6\pm0.3$. This analysis demonstrates the power of using N-body simulations to forward model galaxy surveys for cosmological inference., Comment: Matches published version. Data and code to reproduce the analysis are available at https://github.com/darklight-cosmology/vipers-sham

Proteoglycans are macromolecules that are essential for the development of cells, human diseases and malignancies. In particular, chondroitin sulphate proteoglycans (CSPGs) accumulate in tumour stroma and play a key role in tumour growth and invasion by driving multiple oncogenic pathways in tumour cells and promoting crucial interactions in the tumour microenvironment (TME). These pathways involve receptor tyrosine kinase (RTK) signalling via the mitogen-activated protein kinase (MAPK) cascade and integrin signalling via the activation of focal adhesion kinase (FAK), which sustains the activation of extracellular signal-regulated kinases 1/2 (ERK1/2).Human CSPG4 is a type I transmembrane protein that is associated with the growth and progression of human brain tumours. It regulates cell signalling and migration by interacting with components of the extracellular matrix, extracellular ligands, growth factor receptors, intracellular enzymes and structural proteins. Its overexpression by tumour cells, perivascular cells and precursor/progenitor cells in gliomas suggests that it plays a role in their origin, progression and neo-angiogenesis and its aberrant expression in tumour cells may be a promising biomarker to monitor malignant progression and patient survival.The aim of this chapter is to review and discuss the role of CSPG4 in the TME of human gliomas, including its potential as a druggable therapeutic target.

Proteoglycans are macromolecules that are essential for the development of cells, human diseases and malignancies. In particular, chondroitin sulphate proteoglycans (CSPGs) accumulate in tumour stroma and play a key role in tumour growth and invasion by driving multiple oncogenic pathways in tumour cells and promoting crucial interactions in the tumour microenvironment (TME). These pathways involve receptor tyrosine kinase (RTK) signalling via the mitogen-activated protein kinase (MAPK) cascade and integrin signalling via the activation of focal adhesion kinase (FAK), which sustains the activation of extracellular signal-regulated kinases 1/2 (ERK1/2).Human CSPG4 is a type I transmembrane protein that is associated with the growth and progression of human brain tumours. It regulates cell signalling and migration by interacting with components of the extracellular matrix, extracellular ligands, growth factor receptors, intracellular enzymes and structural proteins. Its overexpression by tumour cells, perivascular cells and precursor/progenitor cells in gliomas suggests that it plays a role in their origin, progression and neo-angiogenesis and its aberrant expression in tumour cells may be a promising biomarker to monitor malignant progression and patient survival.The aim of this chapter is to review and discuss the role of CSPG4 in the TME of human gliomas, including its potential as a druggable therapeutic target.