Next Generation Cosmology: Constraints from the Euclid Galaxy Cluster Survey

We study the characteristics of the galaxy cluster samples expected from the European Space Agency's Euclid satellite and forecast constraints on cosmological parameters describing a variety of cosmological models. The method used in this paper, based on the Fisher Matrix approach, is the same one used to provide the constraints presented in the Euclid Red Book (Laureijs et al.2011). We describe the analytical approach to compute the selection function of the photometric and spectroscopic cluster surveys. Based on the photometric selection function, we forecast the constraints on a number of cosmological parameter sets corresponding to different extensions of the standard LambdaCDM model. The dynamical evolution of dark energy will be constrained to Delta w_0=0.03 and Delta w_a=0.2 with free curvature Omega_k, resulting in a (w_0,w_a) Figure of Merit (FoM) of 291. Including the Planck CMB covariance matrix improves the constraints to Delta w_0=0.02, Delta w_a=0.07 and a FoM=802. The amplitude of primordial non-Gaussianity, parametrised by f_NL, will be constrained to \Delta f_NL ~ 6.6 for the local shape scenario, from Euclid clusters alone. Using only Euclid clusters, the growth factor parameter \gamma, which signals deviations from GR, will be constrained to Delta \gamma=0.02, and the neutrino density parameter to Delta Omega_\nu=0.0013 (or Delta \sum m_\nu=0.01). We emphasise that knowledge of the observable--mass scaling relation will be crucial to constrain cosmological parameters from a cluster catalogue. The Euclid mission will have a clear advantage in this respect, thanks to its imaging and spectroscopic capabilities that will enable internal mass calibration from weak lensing and the dynamics of cluster galaxies. This information will be further complemented by wide-area multi-wavelength external cluster surveys that will already be available when Euclid flies. [Abridged]Comment: submitted to MNRA

The palliative-supportive care unit in a comprehensive cancer center as crossroad for patients' oncological pathway

Aim The aim of this study was to assess how an admission to an acute palliative-supportive care unit (APSCU), may influence the therapeutic trajectory of advanced cancer patients. Methods A consecutive sample of advanced cancer patients admitted to APCU was assessed. The following parameters were collected: patients demographics, including age, gender, primary diagnosis, marital status, and educational level, performance status and reasons for and kind of admission, data about care-givers, recent anticancer treatments, being on/off treatment or uncertain, the previous care setting, who proposed the admission to APSCU. Physical and psychological symptoms were evaluated at admission and at time of discharge. The use of opioids was also recorded. Hospital staying was also recorded. At time of discharge the parameters were recorded and a follow-up was performed one month after discharge. Results314 consecutive patients admitted to the APSCU were surveyed. Pain was the most frequent reason for admission. Changes of ESAS were highly significant, as well as the use of opioids and breakthrough pain medications (p lt;0.0005). A significant decrease of the number of [[ampi]]on therapy[[ampi]] patients was reported, and concomitantly a significant number of [[ampi]]offtherapy[[ampi]] patients increased. At one month follow-up, 38.9% patients were at home, 19.7% patients were receiving palliative home care, and 1.6% patients were in hospice. 68.5% of patients were still living. Conclusion Data of this study suggest that the APSCU may have a relevant role for managing the therapeutic trajectory of advanced cancer patients, limiting the risk of futile and aggressive treatment while providing an appropriate care setting

Impact of N-tau on adult hippocampal neurogenesis, anxiety, and memory.

Different pathological tau species are involved in memory loss in Alzheimer’s disease, the most common cause of dementia among older people. However, little is known about how tau pathology directly affects adult hippocampal neurogenesis, a unique form of structural plasticity implicated in hippocampusdependent spatial learning and mood-related behavior. To this aim, we generated a transgenic mouse model conditionally expressing a pathological tau fragment (26e230 aa of the longest human tau isoform, or N-tau) in nestin-positive stem/progenitor cells. We found that N-tau reduced the proliferation of progenitor cells in the adult dentate gyrus, reduced cell survival and increased cell death by a caspase- 3eindependent mechanism, and recruited microglia. Although the number of terminally differentiated neurons was reduced, these showed an increased dendritic arborization and spine density. This resulted in an increase of anxiety-related behavior and an impairment of episodic-like memory, whereas less complex forms of spatial learning remained unaltered. Understanding how pathological tau species directly affect neurogenesis is important for developing potential therapeutic strategies to direct neurogenic instructive cues for hippocampal function repair

Joint halo-mass function for modified gravity and massive neutrinos - I. Simulations and cosmological forecasts

We present a halo-mass function accurate over the full relevant Hu-Sawicki f(R) parameter space based on spherical collapse calculations and calibrated to a suite of modified gravity N-body simulations that include massive neutrinos. We investigate the ability of current and forthcoming galaxy cluster observations to detect deviations from general relativity while constraining the total neutrino mass and including systematic uncertainties. Our results indicate that the degeneracy between massive neutrino and modify gravity effects is a limiting factor for the current searches for new gravitational physics with clusters of galaxies, but future surveys will be able to break the degeneracy

Cosmological constraints from the abundance, weak lensing, and clustering of galaxy clusters: Application to the SDSS

Aims. The clustering of galaxy clusters is a powerful cosmological tool. When it is combined with other cosmological observables, it can help to resolve parameter degeneracies and improve constraints, especially on Ωm and Ï8. We aim to demonstrate its potential in constraining cosmological parameters and scaling relations when combined with cluster counts and weak-lensing mass information. As a case study, we use the redMaPPer cluster catalog derived from the Sloan Digital Sky Survey (SDSS). Methods. We extended a previous analysis of the number counts and weak-lensing signal by the two-point correlation function. We derived cosmological and scaling relation posteriors for all possible combinations of the three observables to assess their constraining power, parameter degeneracies, and possible internal tensions. Results. We find no evidence for tensions between the three data sets we analyzed. We demonstrate that the constraining power of the sample can be greatly improved by including the clustering statistics because this can break the Ωmâ â â Ï8 degeneracy that is characteristic of cluster abundance studies. In particular, for a flat Î CDM model with massive neutrinos, we obtain Ωmâ =â 0.28â ±â 0.03 and Ï 8â =â 0.82â ±â 0.05, which is an improvement of 33% and 50% compared to the posteriors derived by combining cluster abundance and weak-lensing analyses. Our results are consistent with cosmological posteriors from other cluster surveys, and also with Planck results for the cosmic microwave background (CMB) and DES-Y3 galaxy clustering and weak-lensing analysis

Neutrino cosmology and Planck

Relic neutrinos play an important role in the evolution of the Universe, modifying some of the cosmological observables. We summarize the main aspects of cosmological neutrinos and describe how the precision of present cosmological data can be used to learn about neutrino properties. In particular, we discuss how cosmology provides information on the absolute scale of neutrino masses, complementary to beta decay and neutrinoless double-beta decay experiments. We explain why the combination of Planck temperature data with measurements of the baryon acoustic oscillation angular scale provides a strong bound on the sum of neutrino masses, 0.23 eV at the 95% confidence level, while the lensing potential spectrum and the cluster mass function measured by Planck are compatible with larger values. We also review the constraints from current data on other neutrino properties. Finally, we describe the very good perspectives from future cosmological measurements, which are expected to be sensitive to neutrino masses close the minimum values guaranteed by flavour oscillations

The Role of Structural Biology Task Force: Validation of the Binding Mode of Repurposed Drugs Against SARS-CoV-2 Protein Targets: Focus on SARS-CoV-2 Main Protease (Mpro): A Promising Target for COVID-19 Treatment

The main protease (Mpro) of SARS-CoV-2, a cysteine protease that plays a key role in generating the active proteins essential for coronavirus replication, is a validated drug target for treating COVID-19. The structure of Mpro has been elucidated by macromolecular crystallography, but owing to its conformational flexibility, finding effective inhibitory ligands was challenging. Screening libraries of ligands as part of EXaSCale smArt pLatform Against paThogEns (ExScalate4CoV) yielded several potential drug molecules that inhibit SARS-CoV-2 replication in vitro. We solved the crystal structures of Mpro in complex with repurposed drugs like myricetin, a natural flavonoid, and MG-132, a synthetic peptide aldehyde. We found that both inhibitors covalently bind the catalytic cysteine. Notably, myricetin has an unexpected binding mode, showing an inverted orientation with respect to that of the flavonoid baicalein. Moreover, the crystallographic model validates the docking pose suggested by molecular dynamics experiments. The mechanism of MG-132 activity against SARS-CoV-2 Mpro was elucidated by comparison of apo and inhibitor-bound crystals, showing that regardless of the redox state of the environment and the crystalline symmetry, this inhibitor binds covalently to Cys145 with a well-preserved binding pose that extends along the whole substrate binding site. MG-132 also fits well into the catalytic pocket of human cathepsin L, as shown by computational docking, suggesting that it might represent a good start to developing dual-targeting drugs against COVID-1

Treatment of neuromyelitis optica: state-of-the-art and emerging therapies.

Neuromyelitis optica (NMO) is an autoimmune disease of the CNS that is characterized by inflammatory demyelinating lesions in the spinal cord and optic nerve, potentially leading to paralysis and blindness. NMO can usually be distinguished from multiple sclerosis (MS) on the basis of seropositivity for IgG antibodies against the astrocytic water channel aquaporin-4 (AQP4). Differentiation from MS is crucial, because some MS treatments can exacerbate NMO. NMO pathogenesis involves AQP4-IgG antibody binding to astrocytic AQP4, which causes complement-dependent cytotoxicity and secondary inflammation with granulocyte and macrophage infiltration, blood-brain barrier disruption and oligodendrocyte injury. Current NMO treatments include general immunosuppressive agents, B-cell depletion, and plasma exchange. Therapeutic strategies targeting complement proteins, the IL-6 receptor, neutrophils, eosinophils and CD19--all initially developed for other indications--are under clinical evaluation for repurposing for NMO. Therapies in the preclinical phase include AQP4-blocking antibodies and AQP4-IgG enzymatic inactivation. Additional, albeit currently theoretical, treatment options include reduction of AQP4 expression, disruption of AQP4 orthogonal arrays, enhancement of complement inhibitor expression, restoration of the blood-brain barrier, and induction of immune tolerance. Despite the many therapeutic options in NMO, no controlled clinical trials in patients with this condition have been conducted to date

Detection and classification of man-made objects for the autonomy of underwater robots

Recent developments in marine technologies allow underwater vehicles to perform survey missions for data collection in an automatic way. The scientific community is now focusing on endowing these vehicles with strong perception capabilities, aiming at full autonomy and decision-making skills. Such abilities would bring benefits to a wide range of field applications, e.g. Inspection and Maintenance (I&M) of man-made structures, port security, and marine rescue. Indeed, most of these tasks are currently carried out employing remotely operated vehicles, making the presence of humans in water necessary. Projects like Metrological Evaluation and Testing of Robots in International CompetitionS (METRICS), funded by the European Commission, are promoting research on this field by organising events such as the Robotics for Asset Maintenance and Inspection (RAMI) competition. In particular, this competition requires participants to develop perception techniques capable of identifying a set of specific targets. Within such context, this paper presents an algorithm able to detect and classify Objects of Potential Interest (OPIs) in underwater camera images. First, the proposed solution compensates for the quality degradation of underwater images by applying color enhancement and restoration procedures. Then, it exploits deep-learning techniques, as well as color and shape based methods, to recognize and correctly label the predefined OPIs. Preliminary results of the implemented neural network using restored images are provided, and a mean Average Precision (mAP) of about 92% was achieved on the dataset provided to the RAMI competition participating teams by the NATO Science and Technology Organization Centre for Maritime Research and Experimentation (STO CMRE)