Multiple filtering devices for the estimation of cyclical DSGE models

We propose a method to estimate time invariant cyclical DSGE models using the information provided by a variety of filters. We treat data filtered with alternative procedures as contaminated proxies of the relevant model-based quantities and estimate structural and non-structural parameters jointly using a signal extraction approach. We employ simulated data to illustrate the properties of the procedure and compare our conclusions with those obtained when just one filter is used. We revisit the role of money in the transmission of monetary business cycles.DSGE models, Filters, Structural estimation, Business cycles

The dynamics of US inflation: Can monetary policy explain the changes?

We investigate the relationship between monetary policy and inflation dynamics in the US using a medium scale structural model. The specification is estimated with Bayesian techniques and fits the data reasonably well. Policy shocks account for a part of the decline in inflation volatility; they have been less effective in triggering inflation responses over time and qualitatively account for the rise and fall in the level of inflation. A number of structural parameter variations contribute to these patterns.New Keynesian model, Bayesian methods, Monetary policy, Inflation dynamics.

Numerical analysis of temperature stratification in the CIRCE pool facility

In the framework of Heavy Liquid Metal (HLM) GEN IV Nuclear reactor development, the focus is in the combination of security and performance. Numerical simulations with Computational Fluid Dynamics (CFD) or system codes are useful tools to predict the main steady-state phenomena and how transitional accidents could unfold in GEN IV reactors. In this paper, to support the validation of CFD as a valid tool for the design, the capability of ANSYS CFX v15.0 to simulate and reproduce mixed natural convection and thermal stratification phenomena inside a pool is investigated. The 3D numerical model is based on the CIRCE facility, located in C.R. ENEA Brasimone. It is a pool facility, structured with all the components necessary to simulate the behavior of an HLM reactor, where LBE flows into the primary circuit. For the analysis, the LBE physical properties are implemented in CFX by using recent NEA equations [2]. Previously published RELAP5-3D© results [1] are employed to derive accurate boundary conditions for the simulation of the steady-state conditions in the pool and for CFX validation. The analysis focuses on the pool natural circulation with the presence of thermal structures in contact with LBE, considered as constant temperature sources. The development of thermal stratification in the pool is observed and evaluated with a mesh sensitivity analysis

Risk Assessment for Venous Thromboembolism in Chemotherapy-Treated Ambulatory Cancer Patients: A Machine Learning Approach

OBJECTIVE: To design a precision medicine approach aimed at exploiting significant patterns in data, in order to produce venous thromboembolism (VTE) risk predictors for cancer outpatients that might be of advantage over the currently recommended model (Khorana score). DESIGN: Multiple kernel learning (MKL) based on support vector machines and random optimization (RO) models were used to produce VTE risk predictors (referred to as machine learning [ML]-RO) yielding the best classification performance over a training (3-fold cross-validation) and testing set. RESULTS: Attributes of the patient data set ( n = 1179) were clustered into 9 groups according to clinical significance. Our analysis produced 6 ML-RO models in the training set, which yielded better likelihood ratios (LRs) than baseline models. Of interest, the most significant LRs were observed in 2 ML-RO approaches not including the Khorana score (ML-RO-2: positive likelihood ratio [+LR] = 1.68, negative likelihood ratio [-LR] = 0.24; ML-RO-3: +LR = 1.64, -LR = 0.37). The enhanced performance of ML-RO approaches over the Khorana score was further confirmed by the analysis of the areas under the Precision-Recall curve (AUCPR), and the approaches were superior in the ML-RO approaches (best performances: ML-RO-2: AUCPR = 0.212; ML-RO-3-K: AUCPR = 0.146) compared with the Khorana score (AUCPR = 0.096). Of interest, the best-fitting model was ML-RO-2, in which blood lipids and body mass index/performance status retained the strongest weights, with a weaker association with tumor site/stage and drugs. CONCLUSIONS: Although the monocentric validation of the presented predictors might represent a limitation, these results demonstrate that a model based on MKL and RO may represent a novel methodological approach to derive VTE risk classifiers. Moreover, this study highlights the advantages of optimizing the relative importance of groups of clinical attributes in the selection of VTE risk predictors

A developmental stage- and Kidins220-dependent switch in astrocyte responsiveness to brain-derived neurotrophic factor

Astroglial cells are key to maintain nervous system homeostasis. Neurotrophins are known for their pleiotropic effects on neuronal physiology but also exert complex functions to glial cells. Here, we investigated (i) the signaling competence of mouse embryonic and postnatal primary cortical astrocytes exposed to brain-derived neurotrophic factor (BDNF) and, (ii) the role of kinase D-interacting substrate of 220 kDa (Kidins220), a transmembrane scaffold protein that mediates neurotrophin signaling in neurons. We found a shift from a kinase-based response in embryonic cells to a response predominantly relying on intracellular Ca2+ transients [Ca2+]i within postnatal cultures, associated with a decrease in the synthesis of full-length BDNF receptor TrkB, with Kidins220 contributing to the BDNF-activated kinase and [Ca2+]i pathways. Finally, Kidins220 participates in the homeostatic function of astrocytes by controlling the expression of the ATP-sensitive inward rectifier potassium channel 10 (Kir4.1) and the metabolic balance of embryonic astrocytes. Overall, our data contribute to the understanding of the complex role played by astrocytes within the central nervous system, and identify Kidins220 as a novel actor in the increasing number of pathologies characterized by astrocytic dysfunctions. This article has an associated First Person interview with the first authors of the paper

The Primacy of High b-Value 3T-DWI Radiomics in the Prediction of Clinically Significant Prostate Cancer

Predicting clinically significant prostate cancer (csPCa) is crucial in PCa management. 3T-magnetic resonance (MR) systems may have a novel role in quantitative imaging and early csPCa prediction, accordingly. In this study, we develop a radiomic model for predicting csPCa based solely on native b2000 diffusion weighted imaging (DWIb2000) and debate the effectiveness of apparent diffusion coefficient (ADC) in the same task. In total, 105 patients were retrospectively enrolled between January–November 2020, with confirmed csPCa or ncsPCa based on biopsy. DWIb2000 and ADC images acquired with a 3T-MRI were analyzed by computing 84 local first-order radiomic features (RFs). Two predictive models were built based on DWIb2000 and ADC, separately. Relevant RFs were selected through LASSO, a support vector machine (SVM) classifier was trained using repeated 3-fold cross validation (CV) and validated on a holdout set. The SVM models rely on a single couple of uncorrelated RFs (ρ < 0.15) selected through Wilcoxon rank-sum test (p ≤ 0.05) with Holm–Bonferroni correction. On the holdout set, while the ADC model yielded AUC = 0.76 (95% CI, 0.63–0.96), the DWIb2000 model reached AUC = 0.84 (95% CI, 0.63–0.90), with specificity = 75%, sensitivity = 90%, and informedness = 0.65. This study establishes the primary role of 3T-DWIb2000 in PCa quantitative analyses, whilst ADC can remain the leading sequence for detection

Graphene Oxide Upregulates the Homeostatic Functions of Primary Astrocytes and Modulates Astrocyte-to-Neuron Communication

Graphene-based materials are the focus of intense research efforts to devise novel theranostic strategies for targeting the central nervous system. In this work, we have investigated the consequences of long-term exposure of primary rat astrocytes to pristine graphene (GR) and graphene oxide (GO) flakes. We demonstrate that GR/GO interfere with a variety of intracellular processes as a result of their internalization through the endolysosomal pathway. Graphene-exposed astrocytes acquire a more differentiated morphological phenotype associated with extensive cytoskeletal rearrangements. Profound functional alterations are induced by GO internalization, including the upregulation of inward-rectifying K+ channels and of Na+-dependent glutamate uptake, which are linked to the astrocyte capacity to control the extracellular homeostasis. Interestingly, GO-pretreated astrocytes promote the functional maturation of co-cultured primary neurons by inducing an increase in intrinsic excitability and in the density of GABAergic synapses. The results indicate that graphene nanomaterials profoundly affect astrocyte physiology in vitro with consequences for neuronal network activity. This work supports the view that GO-based materials could be of great interest to address pathologies of the central nervous system associated with astrocyte dysfunctions

An Increase in Membrane Cholesterol by Graphene Oxide Disrupts Calcium Homeostasis in Primary Astrocytes

The use of graphene nanomaterials (GNMs) for biomedical applications targeted to the central nervous system is exponentially increasing, although precise information on their effects on brain cells is lacking. In this work, the molecular changes induced in cortical astrocytes by few-layer graphene (FLG) and graphene oxide (GO) flakes are addressed. The results show that exposure to FLG/GO does not affect cell viability or proliferation. However, proteomic and lipidomic analyses unveil alterations in several cellular processes, including intracellular Ca2+ ([Ca2+ ]i ) homeostasis and cholesterol metabolism, which are particularly intense in cells exposed to GO. Indeed, GO exposure impairs spontaneous and evoked astrocyte [Ca2+ ]i signals and induces a marked increase in membrane cholesterol levels. Importantly, cholesterol depletion fully rescues [Ca2+ ]i dynamics in GO-treated cells, indicating a causal relationship between these GO-mediated effects. The results indicate that exposure to GNMs alters intracellular signaling in astrocytes and may impact astrocyte-neuron interactions

Virtual energy sharing and energy communities for the Municipality of Milan: The case of the Chiaravalle area

The development of virtual energy sharing in complex realities such as the territory of the Municipality of Milan requires the integration of political and social strategies, technical analyses and the use of more advanced urban modelling techniques. This work aims to describe the strategy developed by the Municipality of Milan for the implementation of energy communities and virtual energy sharing, on the basis of current legislation, with reference to the case study of the Chiaravalle area. In order to carry out studies on the area, UBEM (Urban Energy Modelling) models were developed and various intervention scenarios were analysed. The results of the analysis and the technical and strategic evaluations developed are presented