Andrea Tancredi

Double immunohistochemistry to detect transglutaminase 2-IgA deposits in celiac children: a multicentre study

Carla Giordano, Monica Montuori, Paola Parente, A. Pisano et autres

BACKGROUND: Intestinal transglutaminase 2 (TGM2)-IgA deposits represent an early marker of celiac disease (CeD). OBJECTIVE: This multicentre retrospective study aimed to assess the usefulness of a double immunohistochemistry technique for detecting TGM2-IgA deposits in formalin-fixed, paraffin-embedded duodenal biopsies from patients with CeD. …

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Dirichlet process multi-state mixture models

Rosario Barone, Andrea Tancredi

A Bayesian nonparametric framework is introduced for modeling discretely observed trajectories of continuous-time multi-state processes. By employing Dirichlet Process Mixtures with Markov, inhomogeneous Markov, and semi-Markov kernels, the approach flexibly captures unobserved heterogeneity in the process dynamics. Crucially, the mixture structure induces …

Modeling Late Graduations: An Hidden Markov Model Approach

Edoardo Pandolfo, Nina Deliu, Brunero Liseo, Andrea Tancredi

A Bayesian Parametric Approach to Capture–Recapture with Misidentification

Davide Di Cecco, Andrea Tancredi

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Forecasting the climate-conflict risk in Africa along climate-related scenarios and multiple socio-economic drivers

Caterina Conigliani, Valeria Costantini, Elena Paglialunga, Andrea Tancredi

This study investigates how climate change might impact economic development in the future through its effects on violence, addressing the gap in research on long-term conflict risk assessment. Using geocoded data (1°resolution) on climate and socio-economic indicators covering 1990–2050, we employ a …

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From diverticulosis to complicated diverticular disease: Progression of myogenic alterations and oxidative imbalance

Lucia Pallotta, Annalinda Pisano, Rosa Vona, Martina Cappelletti et autres

BACKGROUND: The natural history and pathophysiology of diverticular disease (DD) are still uncertain. An ex-vivo human complicated DD (cDD) model has recently shown a predominant transmural oxidative imbalance. The present study aims to evaluate whether the previously described alterations may precede the …

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m6A modification inhibits miRNAs’ intracellular function, favoring their extracellular export for intercellular communication

Sabrina Garbo, Daniel D’Andrea, Alessio Colantoni, Francesco Paolo Fiorentino et autres

Epitranscriptomics represents a further layer of gene expression regulation. Specifically, N6-methyladenosine (m6A) regulates RNA maturation, stability, degradation, and translation. Regarding microRNAs (miRNAs), while it has been reported that m6A impacts their biogenesis, the functional effects on mature miRNAs remain unclear. Here, we …

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Semi-parametric Bayesian approach for population size estimation modelling the excess of singletons

Davide Di Cecco, Andrea Tancredi, Tiziana Tuoto

Abstract The phenomenon of one-inflation has received increasing attention in the recent literature on capture–recapture analysis. When data consist of frequencies of number of captures, the phenomenon manifests as an excess of units captured exactly once. We distinguish two possible causes for …

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Estimating the number of sequencing errors in microbial diversity studies

Davide Di Cecco, Andrea Tancredi

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Bayesian inference for discretely observed continuous time multi‐state models

Rosario Barone, Andrea Tancredi

Multi-state models are frequently applied to represent processes evolving through a discrete set of states. Important classes of multi-state models arise when transitions between states may depend on the time passed since entry into the current state or on the time elapsed …

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Bayesian analysis of one‐inflated models for elusive population size estimation

Tiziana Tuoto, Davide Di Cecco, Andrea Tancredi

The identification and treatment of "one-inflation" in estimating the size of an elusive population has received increasing attention in capture-recapture literature in recent years. The phenomenon occurs when the number of units captured exactly once clearly exceeds the expectation under a baseline …

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Bayesian inference for discretely observed continuous time multi-state models

Rosario Barone, Andrea Tancredi

Multi-state models are frequently applied for representing processes evolving through a discrete set of state. Important classes of multi-state models arise when transitions between states may depend on the time since entry into the current state or on the time elapsed from …