EVALUATING THE ACCURACY OF TAIL RISK FORECASTS FOR SYSTEMIC RISK MEASUREMENT

In this paper we address how to evaluate tail risk forecasts for systemic risk measurement. We propose two loss functions, the Tail Tick Loss and the Tail Mean Square Error, to evaluate, respectively, CoVaR and MES forecasts. We then analyse CoVaR and MES forecasts for a panel of top US financial institutions between 2000 and 2012 constructed using a set of bivariate DCC-GARCH-type models. The empirical results highlight the importance of using an appropriate loss function for the evaluation of such forecasts. Among other findings, the analysis confirms that the DCC-GJR specification provides accurate predictions for both CoVaR and MES, in particular for the riskiest group of institutions in the panel (Broker-Dealers)

Inequalities in maternal health and pregnancy outcome among Nigerian women migrated to Italy

Among migrant women, unfavourable health conditions and adverse obstetric events are observed more often than in native-born parturients. This observational retrospective study evaluated selected pregnancy outcomes in a Nigerian population giving birth at the University Hospital of Verona. Compared to national controls, being Nigerian was associated with preterm birth (aOR 1.6, 95% CI 1.1-2.2) and Cesarean section (aOR 2.2, 95% CI 1.5-2.7). No differences were found in rates of instrumental delivery and the immigrant group had half the risk of genital tears (aOR 0.6, 95% CI 1.1-2.2) with a higher likelihood of undamaged genitals (aOR 1.5, 95% CI 1.3-2.1). Perinatal indicators of neonatal distress were increased among Nigerians, namely a low Apgar score (aOR 2.6, 95% CI 1.4-4.9), NICU admission (aOR 1.7, 95% CI 1.1-2.8), and stillbirth (aOR 4.0, 95% CI 1.3-12.8). In conclusion, sub-Saharan African women of Nigerian origin appeared more vulnerable and exposed to several adverse pregnancy outcomes. These disparities call for the improvement of obstetric care in this immigrant group. Parmis les femmes migrantes, des conditions de santé défavorables et des événements obstétricaux indésirables sont observés plus souvent que chez les parturientes natives. Cette étude rétrospective observationnelle a analysé certaines issues de la grossesse sélectionnées dans une population nigériane accouchant à l'Hôpital Universitaire de Vérone. Par rapport aux témoins nationaux, le fait d'être nigérian était associé à la prématurité (aOR 1.6, 95% CI 1.1-2.2) et à la césarienne (aOR 2.2, 95% CI 1.5-2.7). Aucune différence n'a été trouvée dans les taux d'accouchements instrumentaux et le groupe d'immigrants avait la moitié du risque de déchirures génitales (aOR 0.6, 95% CI 1.1-2.2) avec une probabilité plus élevée d'organes génitaux intacts (aOR 1.5, 95% CI 1.3-2.1). Les indicateurs périnatals de détresse néonatale ont été trouvés augmenté chez les nigérians, à savoir un faible score d'Apgar (aOR 2.6, 95% CI 1.4-4.9), l’admission en soins intensifs néonatals (aOR 1.7, 95% CI 1.1-2.8) et la mortinatalité (aOR 4.0, 95% CI 1.3-12.8). En conclusion, les femmes africaines subsahariennes d'origine nigériane semblaient plus vulnérables et exposées à plusieurs issues défavorables de la grossesse. Ces disparités appellent l'amélioration des soins obstétricaux dans ce groupe d'immigré

Correlation between olfactory function, age, sex, and cognitive reserve index in the Italian population

Purpose: Loss of smell decreases the quality of life and contributes to the failure in recognizing hazardous substances. Given the relevance of olfaction in daily life, it is important to recognize an undiagnosed olfactory dysfunction to prevent these possible complications. Up to now, the prevalence of smell disorders in Italy is unknown due to a lack of epidemiological studies. Hence, the primary aim of this study was to evaluate the prevalence of olfactory dysfunction in a sample of Italian adults. Methods: Six hundred and thirty-three participants (347 woman and 286 men; mean age 44.9 years, SD 17.3, age range 18-86) were recruited from 10 distinct Italian regions. Participants were recruited using a convenience sapling and were divided into six different age groups: 18-29 years (N = 157), 30-39 years (N = 129), 40-49 years (N = 99), 50-59 years (N = 106), > 60 years (N = 142). Olfactory function, cognitive abilities, cognitive reserve, and depression were assessed, respectively, with: Sniffin' Sticks 16-item Odor Identification Test, Montreal Cognitive Assessment, Cognitive Reserve Index, and the Beck Depression Inventory. Additionally, socio-demographic data, medical history, and health-related lifestyle information were collected. Results: About 27% of participants showed an odor identification score < 12 indicating hyposmia. Multiple regression analysis revealed that OI was significantly correlated with age, sex, and cognitive reserve index, and young women with high cognitive reserve index showing the highest olfactory scores. Conclusion: This study provides data on the prevalence of olfactory dysfunction in different Italian regions

Pathological mitophagy disrupts mitochondrial homeostasis in Leber's hereditary optic neuropathy

Leber's hereditary optic neuropathy (LHON), a disease associated with a mitochondrial DNA mutation, is characterized by blindness due to degeneration of retinal ganglion cells (RGCs) and their axons, which form the optic nerve. We show that a sustained pathological autophagy and compartment-specific mitophagy activity affects LHON patient-derived cells and cybrids, as well as induced pluripotent-stem-cell-derived neurons. This is variably counterbalanced by compensatory mitobiogenesis. The aberrant quality control disrupts mitochondrial homeostasis as reflected by defective bioenergetics and excessive reactive oxygen species production, a stress phenotype that ultimately challenges cell viability by increasing the rate of apoptosis. We counteract this pathological mechanism by using autophagy regulators (clozapine and chloroquine) and redox modulators (idebenone), as well as genetically activating mitochondrial biogenesis (PGC1-α overexpression). This study substantially advances our understanding of LHON pathophysiology, providing an integrated paradigm for pathogenesis of mitochondrial diseases and druggable targets for therapy

Quantitative MRI Harmonization to Maximize Clinical Impact: The RIN-Neuroimaging Network

Neuroimaging studies often lack reproducibility, one of the cardinal features of the scientific method. Multisite collaboration initiatives increase sample size and limit methodological flexibility, therefore providing the foundation for increased statistical power and generalizable results. However, multisite collaborative initiatives are inherently limited by hardware, software, and pulse and sequence design heterogeneities of both clinical and preclinical MRI scanners and the lack of benchmark for acquisition protocols, data analysis, and data sharing. We present the overarching vision that yielded to the constitution of RIN-Neuroimaging Network, a national consortium dedicated to identifying disease and subject-specific in-vivo neuroimaging biomarkers of diverse neurological and neuropsychiatric conditions. This ambitious goal needs efforts toward increasing the diagnostic and prognostic power of advanced MRI data. To this aim, 23 Italian Scientific Institutes of Hospitalization and Care (IRCCS), with technological and clinical specialization in the neurological and neuroimaging field, have gathered together. Each IRCCS is equipped with high- or ultra-high field MRI scanners (i.e., ≥3T) for clinical or preclinical research or has established expertise in MRI data analysis and infrastructure. The actions of this Network were defined across several work packages (WP). A clinical work package (WP1) defined the guidelines for a minimum standard clinical qualitative MRI assessment for the main neurological diseases. Two neuroimaging technical work packages (WP2 and WP3, for clinical and preclinical scanners) established Standard Operative Procedures for quality controls on phantoms as well as advanced harmonized quantitative MRI protocols for studying the brain of healthy human participants and wild type mice. Under FAIR principles, a web-based e-infrastructure to store and share data across sites was also implemented (WP4). Finally, the RIN translated all these efforts into a large-scale multimodal data collection in patients and animal models with dementia (i.e., case study). The RIN-Neuroimaging Network can maximize the impact of public investments in research and clinical practice acquiring data across institutes and pathologies with high-quality and highly-consistent acquisition protocols, optimizing the analysis pipeline and data sharing procedures

Measurement of χ c1 and χ c2 production with s√ = 7 TeV pp collisions at ATLAS

The prompt and non-prompt production cross-sections for the χ c1 and χ c2 charmonium states are measured in pp collisions at s√ = 7 TeV with the ATLAS detector at the LHC using 4.5 fb−1 of integrated luminosity. The χ c states are reconstructed through the radiative decay χ c → J/ψγ (with J/ψ → μ + μ −) where photons are reconstructed from γ → e + e − conversions. The production rate of the χ c2 state relative to the χ c1 state is measured for prompt and non-prompt χ c as a function of J/ψ transverse momentum. The prompt χ c cross-sections are combined with existing measurements of prompt J/ψ production to derive the fraction of prompt J/ψ produced in feed-down from χ c decays. The fractions of χ c1 and χ c2 produced in b-hadron decays are also measured

Differential diagnosis of neurodegenerative dementias with the explainable MRI based machine learning algorithm MUQUBIA

Biomarker-based differential diagnosis of the most common forms of dementia is becoming increasingly important. Machine learning (ML) may be able to address this challenge. The aim of this study was to develop and interpret a ML algorithm capable of differentiating Alzheimer's dementia, frontotemporal dementia, dementia with Lewy bodies and cognitively normal control subjects based on sociodemographic, clinical, and magnetic resonance imaging (MRI) variables. 506 subjects from 5 databases were included. MRI images were processed with FreeSurfer, LPA, and TRACULA to obtain brain volumes and thicknesses, white matter lesions and diffusion metrics. MRI metrics were used in conjunction with clinical and demographic data to perform differential diagnosis based on a Support Vector Machine model called MUQUBIA (Multimodal Quantification of Brain whIte matter biomArkers). Age, gender, Clinical Dementia Rating (CDR) Dementia Staging Instrument, and 19 imaging features formed the best set of discriminative features. The predictive model performed with an overall Area Under the Curve of 98%, high overall precision (88%), recall (88%), and F1 scores (88%) in the test group, and good Label Ranking Average Precision score (0.95) in a subset of neuropathologically assessed patients. The results of MUQUBIA were explained by the SHapley Additive exPlanations (SHAP) method. The MUQUBIA algorithm successfully classified various dementias with good performance using cost-effective clinical and MRI information, and with independent validation, has the potential to assist physicians in their clinical diagnosis

Combined Forward-Backward Asymmetry Measurements in Top-Antitop Quark Production at the Tevatron

The CDF and D0 experiments at the Fermilab Tevatron have measured the asymmetry between yields of forward- and backward-produced top and antitop quarks based on their rapidity difference and the asymmetry between their decay leptons. These measurements use the full data sets collected in proton-antiproton collisions at a center-of-mass energy of $\sqrt s =1.96$ TeV. We report the results of combinations of the inclusive asymmetries and their differential dependencies on relevant kinematic quantities. The combined inclusive asymmetry is $A_{\mathrm{FB}}^{t\bar{t}} = 0.128 \pm 0.025$. The combined inclusive and differential asymmetries are consistent with recent standard model predictions