An adaptive functional regression framework for spatially heterogeneous signals in spectroscopy

The attention towards food products characteristics, such as nutritional properties and traceability, has risen substantially in the recent years. Consequently, we are witnessing an increased demand for the development of modern tools to monitor, analyse and assess food quality and authenticity. Within this framework, an essential set of data collection techniques is provided by vibrational spectroscopy. In fact, methods such as Fourier near infrared and mid infrared spectroscopy have been often exploited to analyze different foodstuffs. Nonetheless, existing statistical methods often struggle to deal with the challenges presented by spectral data, such as their high dimensionality, paired with strong relationships among the wavelengths. Therefore, the definition of proper statistical procedures accounting for the peculiarities of spectroscopy data is paramount. In this work, motivated by two dairy science applications, we propose an adaptive functional regression framework for spectroscopy data. The method stems from the trend filtering literature, allowing the definition of a highly flexible and adaptive estimator able to handle different degrees of smoothness. We provide a fast optimization procedure that is suitable for both Gaussian and non Gaussian scalar responses, and allows for the inclusion of scalar covariates. Moreover, we develop inferential procedures for both the functional and the scalar component thus enhancing not only the interpretability of the results, but also their usability in real world scenarios. The method is applied to two sets of MIR spectroscopy data, providing excellent results when predicting milk chemical composition and cows' dietary treatments. Moreover, the developed inferential routine provides relevant insights, potentially paving the way for a richer interpretation and a better understanding of the impact of specific wavelengths on milk features.Comment: 20 pages, 3 figure

TextWiller @ SardiStance, HaSpeede2: Text or Con-text? A Smart Use of Social Network Data in Predicting Polarization

In this contribution we describe the system (i.e. a statistical model) used to participate in Evalita conference 2020, SardiStance (Tasks A and B) and Haspeede2 (Tasks A and B). We first developed a classifier by extracting features from the texts and the social network of users. Then, we fit the data through an extreme gradient boosting, with cross-validation tuning of the hyper-parameters. A key factor for a good performance in SardiStance Task B was the features extraction by using Multidimensional Scaling of the distance matrix (minimum path, undirected graph) applied on each network. The second system exploits the same features above, but it trains and performs predictions in two-steps. The performances proved to be lower than those of the single-step model

Overweight/obesity affects histological features and inflammatory gene signature of synovial membrane of Rheumatoid Arthritis

Overweight/obesity influence disease burden and clinical outcome of Rheumatoid Arthritis (RA). The impact of overweight/obesity on synovial tissue (ST) inflammation is largely unknown. Here, we investigated the histological and transcriptional signature of ST obtained from RA in different disease phases (disease onset, failure to first-line conventional DMARDs and in sustained clinical and ultrasound remission) finding that overweight/obese DMARDs naive RA showed higher likelihood of follicular synovitis, higher IHC scores for sublining inflammatory cells (CD68+, CD21+ and CD20+) and higher IL-1RA plasma levels than normal weight RA. Regardless to the synovitis pattern, overweight/obese DMARDs naive RA showed a worse clinical response to "Treat-to-target" (T2T) than normal weight RA at 6 and 12 months follow-up. Conversely, MTX-IR RA did not show significant differences in synovial inflammation based on BMI category. Overweight/obese RA in stable clinical and US remission showed higher degree of residual synovitis in terms of sublining CD68+, CD20+ cells and lining and sublining CD3+ compared to normal weight RA. Finally, gene expression profile analysis revealed that ST of overweight/obese DMARDs naive RA is enriched by CCL3 and MyD88 compared to normal weight RA in sustained disease remission, the latter correlating with BMI and IHC scores for synovial CD68+ cells. These findings suggest that indeed overweight/obese RA show higher degree of synovitis at disease onset and after remission achievement that influences the response rate to T2T and should be considered within the management of patients with RA

Differential synovial tissue biomarkers among psoriatic arthritis and rheumatoid factor/anti-citrulline antibody-negative rheumatoid arthritis

Background: Differential diagnosis among psoriatic arthritis (PsA) and seronegative rheumatoid arthritis (Ab neg RA) can be challenging particularly in the clinical setting of peripheral phenotype and autoantibodies seronegativity. The aim of the study was to identify synovial tissue (ST) biomarkers differentially expressed in PsA and Ab neg RA and test their predictive value of therapeutic response. Methods: Thirty-four PsA patients [12 DMARD naive and 22 non-responder to methotrexate (MTX-IR)] with peripheral joint involvement and 55 Ab neg RA (27 DMARD naive and 28 MTX-IR) underwent US-guided ST biopsy and immunohistochemistry (IHC) for CD68 + , CD3 + , CD20 + , CD21 + , CD117 + , and CD138 + cells. After study entry, each DMARD-naive patient started MTX therapy and was followed in an outpatient setting for at least 6 months to define the achievement of Minimal Disease Activity (PsA) and DAS remission (Ab neg RA) status respectively. Each IR-MTX patient was treated according to EULAR recommendations. Results: At study entry, IHC analysis revealed that PsA patients had comparable levels of lining and sublining CD68 + and sublining CD21 + , CD20 + , and CD3 + cells than Ab neg RA, despite the therapeutic regimen. Moreover, regardless of the therapeutic scheme, PsA patients showed higher IHC score of CD117 + cells (p = 0.0004 and p = 0.0005 for naive and MTX-IR patients respectively) compared to Ab neg RA patients. Conversely, Ab neg RA patients showed higher IHC score of CD138 + cells, irrespective to the therapeutic scheme (p = 0.04 and p = 0.002 for naive and MTX-IR patients respectively). Analyzing the response rate to the therapeutic scheme, naive PsA patients reaching MDA status at 6 months follow-up, showed, at the study entry, lower IHC score of CD3 + cells compared to PsA patients not reaching this outcome (p = 0.02); conversely, naive Ab neg RA patients reaching DAS remission status at 6 months follow-up, showed, at the study entry, lower IHC score of sublining CD68 + cells compared to Ab neg RA patients not reaching this outcome (p < 0.001). Conclusions: CD117 + and CD138 + cells are differentially distributed among PsA and Ab neg RA. Histological analysis of ST may help to solve the clinical overlap between the two diseases and provides prognostic data about the therapy success

Synovial features of patients with rheumatoid arthritis and psoriatic arthritis in clinical and ultrasound remission differ under anti-TNF therapy: A clue to interpret different chances of relapse after clinical remission?

Objective To define the synovial characteristics of patients with rheumatoid arthritis (RA) and psoriatic arthritis (PsA) in clinical and ultrasound remission achieved by combination therapy with methotrexate (MTX) and tumour necrosis factor (TNF) blockers. Methods Patients with RA in remission (n=25) (disease activity score (DAS)<1.6 for at least 6 months), patients with RA in low disease activity (LDA) (n=10) (1.6<2.4 for at least 6 months) and patients with PsA in remission (n=18) (DAS<1.6 and Psoriasis Area Severity Index (PASI)=0 for at least 6 months) achieved by MTX+anti-TNF (adalimumab 40 mg or etanercept 50 mg) with power Doppler (PDUS)-negative synovial hypertrophy underwent synovial tissue biopsy. Patients with RA with high/moderate disease na\uefve to treatment (n=50) were included as a comparison group. Immunostaining for cluster designation (CD)68, CD21, CD20, CD3, CD31 and collagen was performed. Results PDUS-negative patients with RA in remission showed lower histological scores for synovial CD68+, CD20+, CD3+ cells and CD31+ vessels and collagen deposition (p<0.05 for both lining and sublining) compared with PDUS-positive patients with RA with high/moderate disease. In addition, there was no significant difference in terms of lining and sublining CD68+, CD20+, CD3+, CD31+ cells and collagen comparing PDUS-negative patients with RA in remission and in LDA, respectively. On the contrary, PDUS-negative patients with PsA in remission showed higher histological scores for sublining CD68+ (p=0.02) and CD3+ cells (p=0.04) as well as CD31+ vessels (p<0.001) than PDUS-negative patients with RA in remission. Conclusions PDUS-negative patients with RA in remission have comparable synovial histological features than PDUS-negative patients with RA in LDA. However, patients with PsA in remission are characterised by a higher degree of residual synovial inflammation than patients with RA in remission, despite PDUS negativity under TNF inhibition

Synovial predictors of differentiation to definite arthritis in patients with seronegative undifferentiated peripheral inflammatory arthritis: MicroRNA signature, histological, and ultrasound features

Objectives: To examine synovial tissue (ST) predictors of clinical differentiation in patients with seronegative undifferentiated peripheral inflammatory arthritis (UPIA). Methods: Fourty-two patients with IgA/IgM-Rheumatoid Factor and anti-citrullinated peptide antibodies negative UPIA, naive to Disease-Modifying Anti-Rheumatic Drugs, underwent Gray Scale (GSUS) and power Doppler (PDUS) evaluation and Ultrasound (US) guided ST biopsy. CD68, CD 3 , CD 21 , CD 20 , and CD 31 synovial expression was evaluated by immunohistochemistry. Whole ST microRNA expression was assessed using miScript miRNA PCR Array. Peripheral blood (PB) and synovial fluid (SF) IL-6, VEGF-A, and VEGF-D levels were measured by ELISA and ST TNF expression was assessed by RT-PCR. Each patient was prospectively monitored and classified at baseline and within 1 year as UPIA, Rheumatoid Arthritis (RA), Spondyloarthritis (SpA) or Psoriatic Arthritis (PsA), respectively. Results: At baseline, CD68 + cells were the most common cells within the lining layer (p < 0.001) in seronegative UPIA, directly correlating with GSUS (R = 0.36; p = 0.02) and PDUS (R = 0.55; p < 0.001). Synovial CD 31+ vessels count directly correlated with GSUS (R = 0.41; p = 0.01) and PDUS (R = 0.52; p < 0.001). During the follow-up, 6 (14.3%) UPIA reached a definite diagnosis (2 RA, 2 SpA and 2 PsA, respectively). At baseline, UPIA who differentiated had higher GSUS (p = 0.01), PDUS scores (p = 0.02) and higher histological scores for CD68+ (p = 0.005 and p = 0.04 for lining and sublining respectively), sublining CD 3+ cells (p = 0.002), CD 31+ vessels count (p < 0.001) and higher IL-6 PB levels (p = 0.01) than patients who remained as UPIA. MiRNA PCR Array showed that among the 86 tested miRNA species, at baseline, miR-346 and miR-214 were significantly down-regulated (p = 0.02 for both) in ST of UPIA who differentiated than in patients who remained as UPIA, inversely correlating with the lining CD68+ cells IHC score (R = -0.641; p = 0.048) and CD 31+ vessels count (R = -0.665; p = 0.036) and with higher baseline ST expression of TNF (p = 0.014). Finally, logistic regression analysis demonstrated that baseline GSUS and PDUS scores 651.5 [OR:22.93 (95%CI:0.98-534.30)] and CD 31+ vessels count 6524.3 [OR:23.66 (95%CI:1.50-373.02)] were independent factors associated with the development of definite arthritis. Conclusions: MiRNA signature, histological and US features of ST may help in the identification of seronegative UPIA with high likelihood of clinical differentiation toward definite seronegative arthritis

EVALITA Evaluation of NLP and Speech Tools for Italian - December 17th, 2020

Welcome to EVALITA 2020! EVALITA is the evaluation campaign of Natural Language Processing and Speech Tools for Italian. EVALITA is an initiative of the Italian Association for Computational Linguistics (AILC, http://www.ai-lc.it) and it is endorsed by the Italian Association for Artificial Intelligence (AIxIA, http://www.aixia.it) and the Italian Association for Speech Sciences (AISV, http://www.aisv.it)

Nonparametric methods for complex spatial domains: density estimation and hypothesis testing

The analysis of not only big, but increasingly complex data represents a thriving branch of statistics. Modern applications ranging from neuroscience, geo-sciences, astronomy and engineering pose stimulating challenges to classical statistics and require the development of novel methodologies. In this thesis we propose nonparametric approaches to density estimation and hypothesis testing over multidimensional domains with complex shapes. The synergy of ideas and techniques from applied mathematics, numerical analysis and statistics allows us to obtain flexible and efficient tools. The thesis is organized in three main threads. The first considers the problem of density estimation over multidimensional domains with complex shapes. Here we combine a nonparametric likelihood approach with a regularization involving partial differential operators. The second thread examines two sample hypothesis testing. Inspired by the first part, we take advantage of permutation procedures to develop high dimensional multinomial tests for distributions defined over complex domain. The last thread moves toward a parallel direction, that is the study of hypothesis testing procedures for semiparametric spatial regression models. After a careful analysis of their theoretical properties, we propose a nonparametric randomization approach to test the linear components of such models