Marika Vezzoli

• Ph.D in Methodological and Applied Statistics
• Researcher at University of Brescia

Face tuning is vital for adaptive and effective social cognition and interaction. This capability is impaired in a wide range of mental conditions including autism spectrum disorder (ASD). Yet the origins of this deficit are largely unknown. Here, an eye-tracking methodology had been implemented in adolescents with high-functioning ASD and in typic...

Background/Objectives: Adenoid Cystic Carcinoma (AdCC) is a rare malignant salivary gland tumor, with high rates of recurrence and distant metastasis. This study aims to stratify patients Relapse-Free Survival (RFS) using a combined model of clinical and radiomic features from preoperative MRI. Methods: This retrospective study included patients wi...

Using machine learning techniques, we detect clusters with high tail dependence obtained through a flexible threshold copula model applied pairwise to the Eurozone sovereign bond yields and credit default swap spreads. Our approach is also useful to inspect the evolution of the loss distribution, as we prove by computing a theoretical portfolio bas...

OBJECTIVE The oculomotor cistern (OMC) is a meningeal cuff filled with CSF that contains the oculomotor nerve (cranial nerve [CN] III) at the level of the lateral wall of the cavernous sinus. Only a few studies have investigated the involvement of the OMC by pituitary adenomas (pituitary neuroendocrine tumors [PitNETs]), mainly with relatively smal...

Background: Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD), a novel term for Non-Alcoholic Fatty Liver Disease (NAFLD), is associated with liver mitochondrial dysfunction. We previously demonstrated that mitochondrial respiratory capacity in peripheral blood mononuclear cells (PBMCs) was significantly reduced in patients with MASL...

Objectives: This study aimed to determine the impacts of upper and lower limb (UL and LL) spasticity and impairment on spinal alignment in chronic post-stroke patients. Methods: A total of 45 consecutive chronic post-stroke patients, 18 women and 27 men, from 18 to 70 years old who presented post-stroke hemiparesis were recruited in this cross-sect...

Background: This study evaluates the repeatability and reproducibility of fat-fraction percentage (FF%) in whole-body magnetic resonance imaging (WB-MRI) of prostate cancer patients with bone metastatic hormone naive disease. Methods: Patients were selected from the database of a prospective phase-II trial. The treatment response was assessed using...

Purpose Gender stereotypes refer to consensual or cultural shared beliefs about the attributes of men and women, influencing society behaviors, interpersonal relationships, education, and workplace. The literature has shown the existence of gender stereotypes on career choices, internalization of roles, and school and social experiences and demonst...

Background Allogeneic stem cell transplantation (allo-SCT) is widely regarded as the most effective consolidation treatment for patients with intermediate to high-risk ELN AML. However, despite its potential curative benefits, many elderly patients (aged ≥60) are unable to undergo this procedure due to comorbidities and/or inability to tolerate int...

Aim To investigate the prevalence and clinical manifestations of reading, writing, and mathematics disorders in children with cerebral palsy (CP). We explored how the clinical profile of these children differed from those with specific learning disorders (SLDs), taking into account several factors, particularly IQ scores, neuropsychological aspects...

Purpose The objective of our retrospective study was to assess the prognostic value of texture analysis and histopathological features in surgically resected lung cancer patients. Materials and methods In total, 70 patients with lung cancer stage IC to IIIA were included in this study. Tumor sections were morphologically evaluated on the basis of t...

The most common conditions with symptomatic joint hypermobility are hypermobile Ehlers‐Danlos syndrome (hEDS) and hypermobility spectrum disorders (HSD). Diagnosing these overlapping connective tissue disorders remains challenging due to the lack of established causes and reliable diagnostic tests. hEDS is diagnosed applying the 2017 diagnostic cri...

Non-alcoholic fatty liver disease (NAFLD) is a health emergency worldwide due to its high prevalence and the lack of specific therapies. Noninvasive biomarkers supporting NAFLD diagnosis are urgently needed. Liver mitochondrial dysfunction is a central NAFLD pathomechanism that changes throughout disease progression. Blood-cell bioenergetics reflec...

Background The research of new biomarkers is still an unmet need in the field of rheumatoid arthritis (RA), especially for patients (pts) without rheumatoid factor and/or anti-citrullinated peptides positivity (seronegative RA), and for those without the elevation of inflammatory markers, such as the C-reactive protein (CRP) [1]. Calprotectin (CLP)...

Although Parkinson's disease (PD) key neuropathological hallmarks are well known, the underlying pathogenic mechanisms of the disease still need to be elucidated to identify innovative disease-modifying drugs and specific biomarkers. NF-κB transcription factors are involved in regulating several processes associated with neurodegeneration, such as...

Objective: To evaluate the diagnostic performance of magnetic resonance (MR) with surface coils in assessing cartilage invasion in recurrent laryngeal carcinoma after carbon dioxide transoral laser microsurgery (CO2 TOLMS). Methods: Two expert head and neck radiologists assessed cartilage invasion (infiltrated or non-infiltrated) in submucosal r...

In pediatric rhabdomyosarcoma (RMS), elevated Akt signaling is associated with increased malignancy. Here, we report that expression of a constitutively active, myristoylated form of Akt1 (myrAkt1) in human RMS RD cells led to hyperactivation of the mammalian target of rapamycin (mTOR)/70-kDa ribosomal protein S6 kinase (p70S6K) pathway, resulting...

Background: Several risk factors have been identified to predict worse outcomes in patients affected by SARS-CoV-2 infection. Machine learning algorithms represent a novel approach to identifying a prediction model with a good discriminatory capacity to be easily used in clinical practice. The aim of this study was to obtain a risk score for in-ho...

Background The prevalence of overweight and obesity in childhood makes intervention imperative, and schools provide a privileged setting in which to undertake this work. Teachers have the potential to influence children’s eating behaviour through nutrition education and by acting as positive role models. We conducted a case–control study in 14 prim...

Despite extensive research on COVID-19’s impact on healthcare workers, few studies have targeted mental health workers (MHWs) and none have investigated previous traumatic events. We investigated psychological distress in MHWs after the first lockdown in Italy to understand which COVID-19, sociodemographic, and professional variables represented gr...

Background Lombardy was the most affected Italian region by the first phase of the COVID-19 pandemic and underwent urgent reorganization for the management of emergencies, including subarachnoid hemorrhage from a ruptured cerebral aneurysm (aSAH). The aim of the study was to define demographics, clinical, and therapeutic features of aSAH during the...

An early-warning model to predict in-hospital mortality on admission of COVID-19 patients at an emergency department (ED) was developed and validate using a Machine-Learning model. In total, 2782 patients were enrolled between March 2020 and December 2020, including 2106 patients (first wave) and 676 patients (second wave) in the COVID-19 outbreak...

Background: To develop and validate an early-warning model to predict in-hospital mortality on admission of COVID-19 patients at an emergency department (ED). Methods: In total, 2782 patients were enrolled between March 2020 and December 2020, including 2106 patients (first wave) and 676 patients (second wave) in the COVID-19 outbreak in Italy. The...

Early diagnosis of Alzheimer’s disease (AD) is a crucial starting point in disease management. Blood-based biomarkers could represent a considerable advantage in providing AD-risk information in primary care settings. Here, we report new data for a relatively unknown blood-based biomarker that holds promise for AD diagnosis. We evaluate a p53-misfo...

Objective: The COVID-19 pandemic has forced many countries into lockdown and has led to the postponement of nonurgent neurosurgical procedures. Although stress has been investigated during this pandemic, there are no reports on anxiety in neurosurgical patients undergoing nonurgent surgical procedures. Methods: Neurosurgical patients admitted to h...

Several theories have been postulated, trying to explain why and how living organisms age. Despite some controversies and still huge open questions, a growing body of evidence suggest alterations of mitochondrial functionality and redox-homeostasis occur during the ageing process. Oxidative damage and mitochondrial dysfunction do not represent the...

Background and purpose: The incidence of oropharyngeal squamous cell carcinoma (OPSCC) has increased in the period from the 1970s to 2004, due to increase of infection with human papilloma virus (HPV). This study aimed to examine the role of histogram analysis of the ADC in treatment response and survival prediction of patients with oropharyngeal...

Importance There are limited data on mortality and complications rates in patients with coronavirus disease 2019 (COVID-19) who undergo surgery. Objective To evaluate early surgical outcomes of patients with COVID-19 in different subspecialties. Design, Setting, and Participants This matched cohort study conducted in the general, vascular and tho...

The use of combination anti-retroviral therapy (cART) correlates with longer and healthier life and with nearly normal life expectancy in people living with HIV. However, cART does not completely restore health. Chronic immune activation and inflammation persist in treated patients and have been described as predictors for clinical events and morta...

After the publication of the above paper, the authors noted that the names of a couple of the authors listed on the paper were associated with the wrong affliation: Specifically, the eighth and ninth listed authors, Francesca Antonaros and Allison Piovesan, are located at DIMES at the University of Florence (fourth affiliation address), not at CSGI...

Down syndrome (DS) is caused by the presence of part or all of a third copy of chromosome 21. DS is associated with several phenotypes, including intellectual disability, congenital heart disease, childhood leukemia and immune defects. Specific microRNAs (miRNAs/miR) have been described to be associated with DS, although none of them so far have be...

Background: Colorectal adenocarcinoma cells (Caco-2) are a widely used model of intestinal barrier to study cancer development, toxicological assessments, absorption and metabolism in food science or drug discovery. Caco-2 spontaneously differentiate into a monolayer expressing several specific characteristics, typically showed by mature enterocyt...

We employ a machine learning approach to build a European sovereign risk stratification using macroeconomic fundamentals and contagion measures, proxied by copula-based credit default swap (CDS) dependencies over the period 2008–2017, for France, Germany, Greece, Ireland, Italy, Portugal, and Spain. By adopting a recursive partitioning strategy, we...

This appendix complements the paper in a number of ways. Section II gives details of the data used. Section IV analyzes the MCMC technical details and Section III is a short guide to the codes used to implement the paper. Finally, Section IV provides in details the results of our threshold copula model and the importance of both the contagion measu...

Using a flexible threshold copula model, we investigate the pairwise tail dependence of Eurozone sovereign credit default swap spreads during the period 2008-2013 and we detect clusters of credit default swaps with high tail dependence. Our approach is also useful to inspect the evolution of the loss distribution, as we prove by computing a theoret...

We employ a machine learning approach to build a European sovereign risk stratification using macroeconomic fundamentals and contagion measures, proxied by copula-based credit default swap (CDS) dependencies over the period 2008-2017, for France, Germany, Greece, Ireland, Italy, Portugal, and Spain. By adopting a recursive partitioning strategy we...

Background Anemia is frequent during HIV infection and is predictive of mortality. Although cART has demonstrated to reduce its prevalence, several patients still experience unresolved anemia. We aimed to characterize iron homeostasis and inflammation in HIV-infected individuals with mild anemia in relation to cART. Methods In this retrospective co...

Some aspects of endometrial cancer (EC) preoperative work-up are still controversial, and debatable are the roles played by lymphadenectomy and radical surgery. Proper preoperative EC staging can help design a tailored surgical treatment, and this study aims to propose a new algorithm able to predict extrauterine disease diffusion. 293 EC patients...

Caveolae are cholesterol enriched invaginations of the plasma membrane involved in a variety of processes, including glucose and fatty acids absorption, cell transduction and mechanoprotection. The biogenesis and function of caveolae depend on the activity of Caveolin (Cav-1, -2 and -3) and Cavin (Cavin-1, -2, -3 and -4) protein families. Since Cav...

Objective The pathogenesis of abdominal aortic aneurysm (AAA) is complex and different factors, including calcification, are linked to increased complications. This study was conducted in order to verify if classical risk factors for AAA and cell blood count parameter could help in the identification of calcification progression of the aneurysm. D...

The identification of ancillary biomarkers useful to improve diagnosis is a major challenge for adipocytic liposarcoma (LPS), the most common type among soft tissue sarcomas affecting adulthood. Recent findings have reported the expression of some proteins belonging to Caveolin and Cavin families as a critical hallmark distinctive of the least aggr...

Caveolins (Cav-1, −2 and −3) and Cavins (Cavin-1, −2, −3 and −4) are two protein families controlling the biogenesis and function of caveolae, plasma membrane omega-like invaginations representing the primary site of important cellular processes like endocytosis, cholesterol homeostasis and signal transduction. Caveolae are especially abundant in f...

This paper proposes a novel framework identifying sovereign systemic risk zones. We first explore the cross-dynamics of sovereign CDS in terms of time-changing contagion measures based on copulas and then assemble these measures togetherwith country-specific fundamentals through recursive partitioning, thereby producing important leading indicators...

This paper employs a recently developed statistical algorithm in order to build an early warning model for banking crises in emerging markets. The procedure creates many ‘artificial’ samples by iteratively perturbing the original data set and estimates many models from these samples. The final model is constructed by aggregation, so that, by constr...

Presented jointly by Veni Arakelian and Marika Vezzoli

Focusing on credit risk modelling, this paper introduces a novel approach for ensemble modelling based on a normative linear pooling. Models are first classified as dominant and competitive, and the pooling is run using the competitive models only. Numerical experiments based on parametric (logit, Bayesian model averaging) and nonparametric (classi...

This paper proposes a novel framework identifying sovereign systemic risk zones. We first explore the cross-dynamics of sovereign CDS in terms of time-changing contagion measures based on copulas and then assemble these measures together with country-specific fundamentals through recursive partitioning, thereby producing important leading indicator...

The purpose of this study was to investigate whether MURC/cavin-4, a plasma membrane and Z-line associated protein exhibiting an overlapping distribution with Caveolin-3 (Cav-3) in heart and muscle tissues, may be expressed and play a role in rhabdomyosarcoma (RMS), an aggressive myogenic tumor affecting childhood. We found MURC/cavin-4 to be expre...

Rhabdomyosarcoma (RMS) is a childhood soft tissue tumor with broad expression of markers that are typically found in skeletal muscle. Cavin-1 is a recently discovered protein actively cooperating with Caveolin-1 (Cav-1) in the morphogenesis of caveolae and whose role in cancer is drawing increasing attention. Using a combined in silico and in vitro...

Using data from OECD economies over the period 1981-2010 together with the Reinhart-Rogoff financial crises database, in this chapter we shed some light on the inner mechanism of the systemic risk by combining bank-, currency-, inflation-, and sovereign-type crisis. Through a novel recursive partitioning introduced in Vezzoli and Stone (2007) combi...

In this article, we try to realize the best compromise between in-sample goodness of fit and out-of-sample predictability of sovereign defaults. To do this, we use a new regression-tree based approach that signals impending sovereign debt crises whenever pre-selected indicators exceed specific thresholds. Using data from emerging markets and Greece...

Weighted Rank Correlation indices are useful for measuring the agreement of two rankings when the top ranks are considered more important than the lower ones. This paper investigates, from a descriptive perspective, the behaviour of i) five existing indices that introduce suitable weights in the simplified formula of the Spearman’s rho and ii) an a...

This paper employs a recent statistical algorithm (CRAGGING) in order to build an early warning model for banking crises in emerging markets. We perturb our data set many times and create “artificial” samples from which we estimated our model, so that, by construction, it is flexible enough to be applied to new data for out-of-sample prediction. We...

When cluster analysis is performed on ranking or rating data, methods requiring quantitative variables commonly used to characterize the obtained groups, such as the cluster profile plots, are not appropriate. Instead, the bipolar mean, originally introduced in the literature in 2005 to deal with such kind of data, can be useful to interpret the re...

A user who chooses a weighted rank correlation index certainly requires that this gives the right emphasis to the exchanges on the most important ranks and does not return the same value of the related unweighted measure. In 2005, Pinto da Costa and Soares proposed an index introducing linear weights in the simplified formula of the Spearman’s ρ. W...

By focusing on sovereign defaults, this paper introduces a multidimensional distance-to-collapse point based on a two-step procedure. The first step is nonparametric and provides an early warning system that signals a potential crisis whenever preselected leading indicators exceed specific thresholds. The second is parametric and incorporates the f...

Workers' well-being appears to be strongly influenced by fairness concerns. A key question is how such a relationship could be dissected in order to get a picture where different dimensions of Job Satisfaction (Intrinsic, Extrinsic and Overall) are connected to each of the main fairness facets. Using a large dataset of about 4,100 workers belonging...

This paper aims at measuring the contribution of each item used to construct composite indicators of unobservable variables when data come from multi-item scales and have a hierarchical structure. To this end, we combine the MultiLevel NonLinear Principal Components Analysis with the CRAGGING algorithm, and then extracting its MultiLevel Mean Decre...

This paper focuses on algorithmic Variable Importance measurement when hierarchically structured data sets are used. Ensemble learning algorithms (such as Random Forest or Gradient Boosting Machine), which are frequently used to assess the Variable Importance, are unsuitable for exploring hierarchical data. For this reason an ensemble learning algo...

Innovation virtuously impacts on the degree of international growth, which in turn positively influences innovation activities and then firms�™ performance (Filipescu et al., 2009). Many authors have tried to identify and explain the relationship between these two phenomena at firm level. Only recently, few empirical studies investigate...

The aim of this work is to understand the relationship between the overall Job Satisfaction and the facet Job Satisfaction, using a comprehensive dataset of Italian Social Cooperatives workers. On this issue, recent works explored how ensemble learning like Random Forest and TreeBoost can be used to assess the importance of potential predictors in...

Variable importance measurement within a structured database has been recently under scrutiny due to many scientific areas in which such data typology occurs. In such situations common ensemble learning like Random Forest or Gra-dient Boosting Machine, frequently used to assess variable importance, could be sub-optimal. In this paper we modify stan...

This paper focuses on predictability of sovereign debt crisis proposing a two-step procedure centered on the idea of a multidimensional distance-to-collapse point. The first step is non-parametric and devoted to constructing a generalized early warning system that signals a potential crisis. The second is parametric and tries to contextualize the c...

Using a comprehensive Italian social cooperatives workers dataset, in this paper we explore the Job Satisfaction (JS) relative to the main fairness facets. Combining Rasch Analysis with the Rating Scale Models and Random Forest technique, our main findings are that non-monetary components of fairness play a key role in the JS and that the importanc...