Reconstruction of the Dark Energy equation of state from latest data: the impact of theoretical priors

We reconstruct the Equation of State of Dark Energy (EoS) from current data using a non-parametric approach where, rather than assuming a specific time evolution of this function, we bin it in time. We treat the transition between the bins with two different methods, i.e. a smoothed step function and a Gaussian Process reconstruction, investigating whether or not the two approaches lead to compatible results. Additionally, we include in the reconstruction procedure a correlation between the values of the EoS at different times in the form of a theoretical prior that takes into account a set of viability and stability requirements that one can impose on models alternative to $\Lambda$CDM. In such case, we necessarily specialize to broad, but specific classes of alternative models, i.e. Quintessence and Horndeski gravity. We use data coming from CMB, Supernovae and BAO surveys. We find an overall agreement between the different reconstruction methods used; with both approaches, we find a time dependence of the mean of the reconstruction, with different trends depending on the class of model studied. The constant EoS predicted by the $\Lambda$CDM model falls anyway within the $1\sigma$ bounds of our analysis.Comment: 17 pages, 5 figures. Prepared for submission to JCA

Unbiased likelihood-free inference of the Hubble constant from light standard sirens

Multi-messenger observations of binary neutron star mergers offer a promising path towards resolution of the Hubble constant ($H_0$) tension, provided their constraints are shown to be free from systematics such as the Malmquist bias. In the traditional Bayesian framework, accounting for selection effects in the likelihood requires calculation of the expected number (or fraction) of detections as a function of the parameters describing the population and cosmology; a potentially costly and/or inaccurate process. This calculation can, however, be bypassed completely by performing the inference in a framework in which the likelihood is never explicitly calculated, but instead fit using forward simulations of the data, which naturally include the selection. This is Likelihood-Free Inference (LFI). Here, we use density-estimation LFI, coupled to neural-network-based data compression, to infer $H_0$ from mock catalogues of binary neutron star mergers, given noisy redshift, distance and peculiar velocity estimates for each object. We demonstrate that LFI yields statistically unbiased estimates of $H_0$ in the presence of selection effects, with precision matching that of sampling the full Bayesian hierarchical model. Marginalizing over the bias increases the $H_0$ uncertainty by only $6\%$ for training sets consisting of $O(10^4)$ populations. The resulting LFI framework is applicable to population-level inference problems with selection effects across astrophysics.Comment: 19 pages, 8 figures, comments welcom

Blockchain Framework in Digital Government for the Certification of Authenticity, Timestamping and Data Property

In an ever more digitized world where information and data are increasingly dematerialized, the question of how to certify intellectual property and define when a document has been created or modified without the presence of any third-party guarantor inevitably arises. This document proposes a decentralized method that, by exploiting blockchain technology and distributed peer-to-peer (P2P) networks, makes it possible to historicize information in such a way that it is not possible for a user to alter its dating, attribute ownership or modify it by impersonating the author. The data certification (document, image, film, data archive, etc.) takes place through the creation of an immutable relationship between the owner and the data. At the legal level, many countries are beginning to regulate blockchain technology so that it can be used in many areas, such as the production chain, the Internet of Things or Public Administration. In this paper we present a solution to promote digital government and greater transparency, through the use of a framework based on the Ethereum blockchain, smart contracts and a decentralized application

Optimal data compression for Lyman-α\alpha forest cosmology

The Lyman-$\alpha$ (Ly$\alpha$) three-dimensional correlation functions have been widely used to perform cosmological inference using the baryon acoustic oscillation (BAO) scale. While the traditional inference approach employs a data vector with several thousand data points, we apply near-maximal score compression down to tens of compressed data elements. We show that carefully constructed additional data beyond those linked to each inferred model parameter are required to preserve meaningful goodness-of-fit tests that guard against unknown systematics, and to avoid information loss due to non-linear parameter dependencies. We demonstrate, on suites of realistic mocks and DR16 data from the Extended Baryon Oscillation Spectroscopic Survey, that our compression framework is lossless and unbiased, yielding a posterior that is indistinguishable from that of the traditional analysis. As a showcase, we investigate the impact of a covariance matrix estimated from a limited number of mocks, which is only well-conditioned in compressed space.Comment: Submitted to MNRA

Direct cosmological inference from three-dimensional correlations of the Lyman-α\alpha forest

When performing cosmological inference, standard analyses of the Lyman-$\alpha$ (Ly$\alpha$) three-dimensional correlation functions only consider the information carried by the distinct peak produced by baryon acoustic oscillations (BAO). In this work, we address whether this compression is sufficient to capture all the relevant cosmological information carried by these functions. We do this by performing a direct fit to the full shape, including all physical scales without compression, of synthetic Ly$\alpha$ auto-correlation functions and cross-correlations with quasars at effective redshift $z_{\rm{eff}}=2.3$, assuming a DESI-like survey, and providing a comparison to the classic method applied to the same dataset. Our approach leads to a $3.5\%$ constraint on the matter density $\Omega_{\rm{M}}$, which is about three to four times better than what BAO alone can probe. The growth term $f \sigma_{8} (z_{\rm{eff}})$ is constrained to the $10\%$ level, and the spectral index $n_{\rm{s}}$ to $\sim 3-4\%$. We demonstrate that the extra information resulting from our `direct fit' approach, except for the $n_{\rm{s}}$ constraint, can be traced back to the Alcock-Paczy\'nski effect and redshift space distortion information.Comment: Submitted to MNRA

Parasitic infections in dogs involved in animal-assisted interventions

Animal Assisted Interventions (AAIs) programmes have been considered useful in different settings, such as hospital, therapeutic, educational and assisted living environments. In these contexts, all animals, and particularly dogs, should be subjected to appropriate health controls to prevent a potential risk of transmission of zoonotic agents. Domestic dogs are reservoirs of many zoonotic pathogens including several gastrointestinal parasites (protozoa and helminths). Therefore, the aim of the present study was to investigate the presence of the protozoan Giardia duodenalis and zoonotic gastrointestinal nematodes (geohelminths) in dogs hosted in a dog educational centre in the city of Naples (southern Italy) where the animals were trained to AAI. Between April and June 2016, 74 dog faecal samples were analysed using the FLOTAC dual technique to detect G. duodenalis cysts and other parasitic elements. Out of the 74 faecal samples examined, 18 (24.3%; 95% CI = 15.4–35.9) were positive for parasitic elements. Specifically, 8 were positive for G. duodenalis (44.4%; 95% CI = 22.4–68.7). In addition, some co-infections were also found: one sample (5.6%; 95% CI = 0.3–29.4) resulted positive to both Toxocara canis and Trichuris vulpis and two samples (11.1%; 95% CI = 1.9–36.1) were positive to both G. duodenalis and Ancylostomidae. Given that children, young adults and immunocompromised individuals are among the main users of the AAIs, specific guidelines targeting G. duodenalis and other gastrointestinal zoonotic parasites should be formulated in order to develop effective control and prevention strategies and reduce the zoonotic risk favoured by the human-dog interaction

Inflammatory role of dendritic cells in Amyotrophic Lateral Sclerosis revealed by an analysis of patients’ peripheral blood

Chronic inflammation is one of the causes of neurodegeneration in Amyotrophic lateral sclerosis (ALS). Here we examined whether circulating dendritic cells (DCs) can contribute to disease progression. We found ALS patients show a significant reduction in the number of circulating DCs. Also, patients’ DCs present an increased expression of CD62L and a tendency to overexpress CCR2 compared with healthy donors. Moreover, DCs derived from a subpopulation of ALS patients produced higher levels of IL-8 and CCL-2 upon lipopolysaccharide (LPS)-stimulation. Finally, we found a significant inverse correlation between the time from onset of the pathology to its diagnosis and the levels of IL-6 secretion induced by LPS. Our data support the hypothesis, in a subpopulation of patients, DCs recruited at the diseased tissue produce high levels of CCL-2 and IL-8 and contribute to the inflammatory process promoting the recruitment of other inflammatory cells. An increased efficiency of IL-6 production may accelerate only the initial phases of disease progression. Blood DC analysis can be used to identify ALS patients with an altered course of inflammatory cell recruitment at the diseased central nervous system (CNS). The high levels of CD62L expression suggests this molecule could be a target for treatment of CNS inflammation

The Prognostic Role of Baseline Eosinophils in HPV-Related Cancers: a Multi-institutional Analysis of Anal SCC and OPC Patients Treated with Radical CT-RT

Background and Aim Anal squamous cell carcinoma (SCC) and oropharyngeal cancer (OPC) are rare tumors associated with HPV infection. Bioumoral predictors of response to chemoradiation (CT-RT) are lacking in these settings. With the aim to find new biomarkers, we investigated the role of eosinophils in both HPV-positive anal SCC and HPV-related oropharyngeal cancer (OPC). Methods We retrieved clinical and laboratory data of patients with HPV-positive anal SCC treated with CT-RT in 5 institutions, and patients with locally advanced OPC SCC treated with CT-RT in 2 institutions. We examined the association between baseline eosinophil count (the best cutoff has been evaluated by ROC curve analysis: 100 x 109/L) and disease-free survival (DFS). Unadjusted and adjusted hazard ratios by baseline characteristics were calculated using the Cox proportional hazards model. Results Three hundred four patients with HPV-positive anal SCCs and 168 patients with OPCs (122 HPV-positive, 46 HPV-negative diseases) were analyzed. In anal SCC, low eosinophil count (9/L) correlates to a better DFS (HR = 0.59; p = 0.0392); likewise, in HPV-positive OPC, low eosinophil count correlates to a better DFS (HR = 0.50; p = 0.0428). In HPV-negative OPC, low eosinophil count confers worse DFS compared to high eosinophil count (HR = 3.53; p = 0.0098). After adjustment for age and sex, eosinophils were confirmed to be independent prognostic factors for DFS (HR = 4.55; p = 0.0139). Conclusion Eosinophil count could be used as a prognostic factor in anal HPV-positive SCC. The worse prognosis showed in HPV-positive patients with high eosinophil count is likely to derive from an unfavorable interaction between the HPV-induced immunomodulation and eosinophils, which may hamper the curative effect of RT

AA-amyloidosis in cats (Felis catus) housed in shelters.

Systemic AA-amyloidosis is a protein-misfolding disease characterized by fibril deposition of serum amyloid-A protein (SAA) in several organs in humans and many animal species. Fibril deposits originate from abnormally high serum levels of SAA during chronic inflammation. A high prevalence of AA-amyloidosis has been reported in captive cheetahs and a horizontal transmission has been proposed. In domestic cats, AA-amyloidosis has been mainly described in predisposed breeds but only rarely reported in domestic short-hair cats. Aims of the study were to determine AA-amyloidosis prevalence in dead shelter cats. Liver, kidney, spleen and bile were collected at death in cats from 3 shelters. AA-amyloidosis was scored. Shedding of amyloid fibrils was investigated with western blot in bile and scored. Descriptive statistics were calculated. In the three shelters investigated, prevalence of AA-amyloidosis was 57.1% (16/28 cats), 73.0% (19/26) and 52.0% (13/25), respectively. In 72.9% of cats (35 in total) three organs were affected concurrently. Histopathology and immunofluorescence of post-mortem extracted deposits identified SAA as the major protein source. The duration of stay in the shelters was positively associated with a histological score of AA-amyloidosis (B = 0.026, CI95% = 0.007-0.046; p = 0.010). AA-amyloidosis was very frequent in shelter cats. Presence of SAA fragments in bile secretions raises the possibility of fecal-oral transmission of the disease. In conclusion, AA-amyloidosis was very frequent in shelter cats and those staying longer had more deposits. The cat may represent a natural model of AA-amyloidosis