Publications by authors named "F Mercuri"

Viral respiratory infection is associated with significant morbidity and mortality. The diversity of viruses implicated, coupled with their propensity for mutation, ignited an interest in host-directed antiviral therapies effective across a wide range of viral variants. Toll-like receptors (TLRs) are potential targets for the development of broad-spectrum antivirals given their central role in host immune defenses.

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Background: Local priming of the innate immune system with a Toll-like receptor (TLR)2/6 agonist may reduce morbidity and mortality associated with viral respiratory tract infections, particularly for the elderly and those with chronic diseases. The objectives of the present study were to understand the potential of prophylactic treatment with a TLR2/6 agonist as an enhancer of innate immunity pathways leading to accelerated respiratory virus clearance from the upper airways.

Methods: Two randomised, double-blind, placebo-controlled clinical trials were conducted in healthy adult participants.

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This perspective article explores the convergence of advanced digital technologies, including high-performance computing (HPC), artificial intelligence, machine learning, and sophisticated data management workflows. The primary objective is to enhance the accessibility of multiscale simulations and their integration with other computational techniques, thereby advancing the field of nanomaterials technologies. The proposed approach relies on key strategies and digital technologies employed to achieve efficient and innovative materials discovery, emphasizing a fully digital, data-centric methodology.

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Article Synopsis
  • GrapheNet is a deep learning framework that uses Inception-Resnet architecture to predict properties of nanographenes by translating structural features into image-like encodings.
  • The model has been tested on datasets related to graphene oxide and defected graphene nanoflakes, showcasing its effectiveness in property prediction.
  • GrapheNet efficiently handles large systems and outperforms traditional atom-level models in both numerical accuracy and computational efficiency, particularly for planar nanostructures.
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In the manufacture of ancient books, it was quite common to insert written scraps belonging to earlier library material into bookbindings. For scholars like codicologists and paleographers, it is extremely important to have the possibility of reading the text lying on such scraps without dismantling the book. In this regard, in this paper, we report on the detection of these texts by means of infrared (IR) pulsed thermography (PT), which, in recent years, has been specifically proven to be an effective tool for the investigation of Cultural Heritage.

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