On soft capacities, quasi-stationary distributions and the pathwise approach to metastability

Motivated by the study of the metastable stochastic Ising model at subcritical temperature and in the limit of a vanishing magnetic field, we extend the notion of ($\kappa$, $\lambda$)-capacities between sets, as well as the associated notion of soft-measures, to the case of overlapping sets. We recover their essential properties, sometimes in a stronger form or in a simpler way, relying on weaker hypotheses. These properties allow to write the main quantities associated with reversible metastable dynamics, e.g. asymptotic transition and relaxation times, in terms of objects that are associated with two-sided variational principles. We also clarify the connection with the classical "pathwise approach" by referring to temporal means on the appropriate time scale.Comment: 29 pages, 1 figur

Tihonov theory and center manifolds for inhibitory mechanisms in enzyme kinetics

Abstract In this paper we study the chemical reaction of inhibition, determine the appropriate parameter ε for the application of Tihonov's Theorem, compute explicitly the equations of the center manifold of the system and find sufficient conditions to guarantee that in the phase space the curves which relate the behavior of the complexes to the substrates by means of the tQSSA are asymptotically equivalent to the center manifold of the system. Some numerical results are discussed

ochratoxin a as possible factor trigging autism and its male prevalence via epigenetic mechanism

The role of dysbiosis causing leaky gut with xenobiotic production and absorption is increasingly demonstrated in autism spectrum disorder (ASD) pathogenesis. Among xenobiotics, we focused on ochratoxin A (one of the major food contaminating mycotoxin), that in vitro and in vivo exerts a male-specific neurotoxicity probably via microRNA modulation of a specific target gene. Among possible targets, we focused on neuroligin4X. Interestingly, this gene carries some single nucleotide polymorphisms (SNPs) already correlated with the disease and with illegitimate microRNA binding sites and, being located on X-chromosome, could explain the male prevalence. In conclusion, we propose a possible gene–environment interaction triggering ASD explaining the epigenetic neurotoxic mechanism activated by ochratoxin A in genetically predisposed children. This mechanism offers a clue for male prevalence of the disease and may have an important impact on prevention and cure of ASD

A Soft-Voting Ensemble Classifier for Detecting Patients Affected by COVID-19

COVID-19 is an ongoing global pandemic of coronavirus disease 2019, which may cause severe acute respiratory syndrome. This disease highlighted the limitations of health systems worldwide regarding managing the pandemic. In particular, the lack of diagnostic tests that can quickly and reliably detect infected patients has contributed to the spread of the virus. Reverse Transcriptase-Polymerase Chain Reaction (RT-PCR) and antigen tests, which are the main diagnostic tests for COVID-19, showed their limitations during the pandemic. In fact, RT-PCR requires several hours to provide a diagnosis and is not properly accurate, thus generating a high number of false negatives. Unlike RT-PCR, antigen tests provide rapid diagnosis but are less accurate in detecting COVID-19 positive patients. Medical imaging is an alternative diagnostic test for COVID-19. In particular, chest computed tomography allows detecting lung infections related to the disease with high accuracy. However, visual analysis of a chest scan generated by computed tomography is a demanding activity for radiologists, making widespread use of this test unfeasible. Therefore, it is essential to lighten their work with automated tools able to provide accurate diagnosis in a short time. To deal with this challenge, in this work, an approach based on 3D Inception CNNs is proposed. Specifically, 3D Inception-V1 and Inception-V3 models have been built and compared. Then, soft-voting ensemble classifier models have been separately built on these models to boost the performance. As for the individual models, results showed that Inception-V1 outperformed Inception-V3 according to different measures. As for the ensemble classifier models, the outcome of experiments pointed out that the adopted voting strategy boosted the performance of individual models. The best results have been achieved enforcing soft voting on Inception-V1 models

Effects of natural and seminatural elements on the composition and dispersion of carabid beetles inhabiting an agroecosystem in Northern Italy

The natural and seminatural components of agricultural landscapes play a key role in maintaining a high level of biodiversity. Being the Po Valley one of the most human-dominated and intensively cultivated landscapes in Europe, we investigated the effect of no-crop habitats on carabid richness and composition and evaluated the role of tree row as corridor for forest carabid dispersion. Carabids were sampled with 70 pitfall traps arranged in 35 sampling plots along three parallel transects (80, 100, and 140 m long) and encompassing five different habitats: tree row, tree row edge, grassland, forest edge, and forest. We found 5,615 individuals belonging to 55 species. Despite the similarity in species richness, all the habitats investigated showed a peculiar and distinct species assemblage. The main distinction was between the "open habitat" cluster composed of grassland and tree row edge and the “forest" cluster composed of forest, tree row, and forest edge. We found that forest species are able to penetrate the grassland matrix up to 30 m from the forest edge and that a distance of no more than 60 m between tree row and forest can allow the passage of up to 50% of the forest species. Beyond this distance, the grassland matrix becomes a barrier, preventing them from reaching other suitable habitats. Our findings confirm the importance of maintaining different types of natural habitats to significantly increase biodiversity in an intensively cultivated agroecosystem and demonstrated the role of linear elements as a corridor and “stepping stones” for many forest species

Hydraulic hazard mapping in alpine dam break prone areas: the Cancano dam case

Dam-break hazard assessment is of great importance in the Italian Alps, where a large number of medium and large reservoirs are present in valleys that are characterized by widespread urbanized zones on alluvial fans and along valley floors. Accordingly, there is the need to identify specific operative approaches in order to quantify hydraulic hazard which in mountain regions inevitably differ from the ones typically used in flat flood-prone areas. These approaches take advantage of: 1) specific numerical algorithms to pre-process the massive topographic information generally needed to describe very irregular bathymetries; 2) an appropriate mathematical model coupled with a robust numerical method which can deal in an effective way with variable geometries like the ones typical of natural alpine rivers; 3) suitable criteria for the hydraulic hazard assessment; 4) representative test cases to verify the accuracy of the overall procedure. This contribution presents some preliminary results obtained in the development of this complex toolkit, showing its application to the test case of the Cancano dam-break, for which the results from a physical model are available. This case was studied in 1943 by De Marchi, who investigated the consequences of the potential collapse of the Cancano dam in Northern Italy as a possible war target during the World War II. Although dated, the resulting report (De Marchi, 1945) is very interesting, since it mixes in a synergistic way theoretical, experimental and numerical considerations. In particular, the laboratory data set concerning the dam-break wave propagation along the valley between the Cancano dam and the village of Cepina provides an useful benchmark for testing the predictive effectiveness of mathematical and numerical models in mountain applications. Here we suggest an overall approach based on the 1D shallow water equations that proved particularly effective for studying dam-break wave propagation in alpine valleys, although this kind of problems is naturally subject to "substantial uncertainties and unavoidable arbitrarinesses" (translation from De Marchi, 1945). The equations are solved by means of a shock-capturing finite volume method involving the Pavia Flux Predictor (PFP) scheme proposed by Braschi and Gallati (1992). The comparison between numerical results and experimental data confirms that the mathematical model adopted is capable of capturing the main engineering aspects of the phenomenon modeled by De Marchi

POS0250 SIGNIFICANT DAMAGE OCCURS EARLY IN THE COURSE OF EOSINOPHILIC GRANULOMATOSIS WITH POLYANGIITIS AND IS MAINLY DUE TO DISEASE-RELATED SEQUELAE

Background:Following the introduction of effective immunosuppressive treatments, ANCA-associated vasculitides (AAV) have become chronic diseases with a remitting-relapsing course. Therefore, preventing chronic damage accrual during follow-up is critical, as relapses, treatment-related side effects, and comorbidities may significantly affect the long-term outcomes of AAV patients. At present, no study specifically evaluated the burden of damage in patients with eosinophilic granulomatosis with polyangiitis (EGPA).Objectives:To describe short-term (6 months) and long-term (5 years) damage accrual in patients with newly diagnosed EGPA.Methods:Patients diagnosed with EGPA, according to ACR criteria and/or Chapel Hill definitions and regularly followed-up in our vasculitis center for ≥5 years were included. Damage accrual was assessed with the Vasculitis Damage Index (VDI). Short-term and long-term damage accrual was defined by VDI at 6 months and at 5 years, respectively, and categorized as related to vasculitis or its treatment.Results:VDI data at 6 months were available for 45 EGPA patients: 24 (53.3%) female, mean age at diagnosis 51.6±13.0 years. ANCA were positive in 17 patients (37.8%), with MPO being the only detected enzyme immunoassay (EIA)-specificity. At 6 months mean VDI was 2.8±1.3; 25/45 (55.6%) and 6/45 patients (13.3%) presented ≥3 and ≥5 items, respectively, whilst only 1 patient (2.2%) showed no items of damage. VDI data at 5 years were available for 32/45 EGPA patients (71.1%): 16 (50%) female, mean age at diagnosis 51.5±13.1 years. MPO-ANCA were positive in 13 patients (40.6%). At 5 years mean VDI was 3.5±1.3, with 26/32 (81.3%) and 7/32 patients (21.9%) presenting ≥3 and ≥5 items, respectively; notably, no patients presented a VDI=0 at 5 years.The most frequent disease-related VDI items at 6 months and at 5 years were asthma, chronic sinusitis, peripheral neuropathy, cardiomyopathy, pulmonary function tests abnormalities and nasal blockage (Figure 1). Osteoporotic fractures, diabetes and systemic hypertension were the most commonly reported treatment-related items at 6 months and at 5 years (Figure 1). Damage accrual progressively rose during the 5-year follow-up (P=0.023), mainly due to disease-related items rather than treatment-related items both at 6 months (disease related VDI 2.6±1.2, treatment-related VDI 0.3±0.6) and at 5 years (disease related VDI 2.9±1.2, treatment-related VDI 0.6±0,7). No significant difference in terms of damage accrual was observed between ANCA-positive and ANCA-negative patients (P >0.5).Conclusion:In our cohort of EGPA patients damage accrual occurs early, with more than half of the patients displaying ≥3 VDI items already at 6 months. Poor control of previous disease activity, particularly ENT and respiratory manifestations, contributes to progressive damage accrual more than treatment side effects.Figure 1.Disease-related and treatment-related VDI items at 6 months and at 5 years in patients with EGPA.Disclosure of Interests:None declare

Frailness and resilience of gene networks predicted by detection of co-occurring mutations via a stochastic perturbative approach

In recent years complex networks have been identified as powerful mathematical frameworks for the adequate modeling of many applied problems in disparate research fields. Assuming a Master Equation (ME) modeling the exchange of information within the network, we set up a perturbative approach in order to investigate how node alterations impact on the network information flow. The main assumption of the perturbed ME (pME) model is that the simultaneous presence of multiple node alterations causes more or less intense network frailties depending on the specific features of the perturbation. In this perspective the collective behavior of a set of molecular alterations on a gene network is a particularly adapt scenario for a first application of the proposed method, since most diseases are neither related to a single mutation nor to an established set of molecular alterations. Therefore, after characterizing the method numerically, we applied as a proof of principle the pME approach to breast cancer (BC) somatic mutation data downloaded from Cancer Genome Atlas (TCGA) database. For each patient we measured the network frailness of over 90 significant subnetworks of the protein-protein interaction network, where each perturbation was defined by patient-specific somatic mutations. Interestingly the frailness measures depend on the position of the alterations on the gene network more than on their amount, unlike most traditional enrichment scores. In particular low-degree mutations play an important role in causing high frailness measures. The potential applicability of the proposed method is wide and suggests future development in the control theory context