Publications by authors named "A Matteo"

Rheumatoid arthritis (RA) is an autoimmune inflammatory condition that primarily affects the joints and periarticular soft tissue. The development of joint swelling is traditionally regarded as the starting point of the disease. Emerging evidence indicates that RA patients often experience a preclinical stage characterized by immunological and inflammatory changes before developing the disease.

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Objective: To describe an intensive and multimodal ultrasound (US) training program focused on Achilles enthesitis and to illustrate the learning curve of trainees without experience.

Methods: Three medical students (trainees) and two rheumatologists experienced in musculoskeletal US (trainers) were involved in the training program, which encompassed one preliminary theoretical-practical meeting and five scanning sessions (two patients per session). The students and one expert performed the US examination of the Achilles enthesis bilaterally.

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Toxoplasmosis persists as a prevalent disease, facing challenges from parasite resistance and treatment side effects. Consequently, identifying new drugs by exploring novel protein targets is essential for effective intervention. Cyclosporin A (CsA) possesses antiparasitic activity against Toxoplasma gondii, with cyclophilins identified as possible targets.

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Rheumatoid arthritis (RA) is a chronic, systemic, autoimmune condition that primarily affects the joints and periarticular soft tissues. In the past two decades, the discovery of new biomarkers has contributed to advances in the understanding of the pathogenesis and natural history of RA. These biomarkers, including genetic, clinical, serological and imaging biomarkers, play a key role in the different stages and aspects of RA, from the so called 'pre-clinical RA', which is characterized by subclinical pathological events, such as autoimmunity and inflammation, to diagnosis (including differential diagnosis), treatment decision making and disease monitoring.

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Brain-computer interfaces (BCIs) are pivotal in translating neural activities into control commands for external assistive devices. Non-invasive techniques like electroencephalography (EEG) offer a balance of sensitivity and spatial-temporal resolution for capturing brain signals associated with motor activities. This work introduces MOVING, a Multi-Modal dataset of EEG signals and Virtual Glove Hand Tracking.

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