Organizing an Interdisciplinary Platform for Knowledge Sharing on a Class of Compounds of Natural Origin.

Sesterterpenoids, a subset of the terpene family, exhibit notable biological activities. These natural compounds are present in a variety of organisms such as plants, fungi, bacteria, insects and marine life. The therapeutic potential and structural diversity of sesterterpenoids have attracted considerable interest in pharmacological and chemical research.

Impact of S-PRG/Giomer and Bulk-fill technologies on the hygroscopic profile of resin composites under erosive condition.

Objective: The emergence of new resin composites (RCs) incorporating bioactive ingredients and/or used as bulk-fill materials aims to enhance restorative potential beyond just the mechanical properties. However, this innovation may affect their performance under clinically simulated conditions, such as erosive challenges (EC). This study evaluated the impact of different technologies on the hygroscopic properties of RCs.

Effectiveness of self-etching bonding systems on dentin after radiotherapy: perspectives on microtensile and microshear bond strength.

Objective: Self-etching dental adhesives bond with dentin through chemical reactions with calcium. This study assessed bond strength (BS) using microtensile (µTBS) and microshear (µSBS) tests on sound and post-radiotherapy dentin, with dental adhesives containing different functional monomers.

Methods: Sound dentin (SD) and post-radiotherapy irradiated dentin (ID) were tested with two adhesive systems: Clearfil SE Bond (SE, 10-MDP-based) and FL Bond II (FL, containing carboxylic and phosphonic monomers with S-PRG bioactive particles).

Impact of functional monomers, bioactive particles, and HEMA, on the adhesive performance of self-etch adhesive systems applied to simulated altered dentin.

Objectives: This study aimed to evaluate how self-etching/universal dental adhesive systems (DASs) with differing compositions interact with sound (S), post-radiotherapy (irradiated; I), and artificially eroded (E) dentin in terms of bonding properties.

Methods: The DASs tested were Adper Scotchbond Multipurpose (MP; control), Clearfil SE Bond (SE), FL Bond II (FL), Adper Single Bond Universal (SU) and BeautiBond Xtreme (BX). They were analyzed for initial and 6-month microtensile bond strength (µTBS, n = 12), mode of failure (40 x), scanning electron microscopy (SEM), surface wettability (W, n = 10), and degree of conversion (DC, n = 3) via Fourier-transform infrared spectroscopy (FTIR).

Optimizing Integration with the Italian EHR: The Use of LOINC Codes.

According to the regulation "Decreto del Presidente del Consiglio dei Ministri" (DPCM) of September 29, 2015, n.178, the Logical Observation Identifiers Names and Codes (LOINC) system is included among the coding systems adopted in the Italian Electronic Health Record (EHR). As part of the Digital Health Solutions in Community Medicine (DHEAL-COM) project, one key goal is to categorize parameters using international classification systems.

Developing an Open-Source, User-Friendly, OWASP-Compliant Architecture for Healthcare Web Application Testing.

Nowadays, web applications are fundamental in the healthcare sector. However, with the widespread use of this technology, risks related to cybersecurity attacks also increase. To mitigate this phenomenon, every 3-4 years, the nonprofit foundation Open Worldwide Application Security Project (OWASP) compiles a top 10 ranking of the most critical web application security risks.

COVID-19 throughout pandemic waves and virus variants: a real-life experience in an Italian hospital.

New therapies and vaccines changed the management of COVID-19. The aim of this retrospective study was to describe characteristics, in-hospital mortality and its predictors in patients with moderate/severe COVID-19, considering the 4 different pandemic waves and viral variants' prevalence from February 2020 to January 2022. Among 1135 patients included, 873 (77%) had at least one comorbidity, 177 (16%) were immunocompromised.

Artificial intelligence and prescription of antibiotic therapy: present and future.

Introduction: In the past few years, the use of artificial intelligence in healthcare has grown exponentially. Prescription of antibiotics is not exempt from its rapid diffusion, and various machine learning (ML) techniques, from logistic regression to deep neural networks and large language models, have been explored in the literature to support decisions regarding antibiotic prescription.

Areas Covered: In this narrative review, we discuss promises and challenges of the application of ML-based clinical decision support systems (ML-CDSSs) for antibiotic prescription.

Prediction of candidemia with machine learning techniques: state of the art.

In this narrative review, we discuss studies assessing the use of machine learning (ML) models for the early diagnosis of candidemia, focusing on employed models and the related implications. There are currently few studies evaluating ML techniques for the early diagnosis of candidemia as a prediction task based on clinical and laboratory features. The use of ML tools holds promise to provide highly accurate and real-time support to clinicians for relevant therapeutic decisions at the bedside of patients with suspected candidemia.

Transforming Ontology Web Language Elements into Common Terminology Service 2 Terminology Resources.

Communication and cooperation are fundamental for the correct deployment of P5 medicine, and this can be achieved only by correct comprehension of semantics so that it can aspire to medical knowledge sharing. There is a hierarchy in the operations that need to be performed to achieve this goal that brings to the forefront the complete understanding of the real-world business system by domain experts using Domain Ontologies, and only in the last instance acknowledges the specific transformation at the pure information and communication technology level. A specific feature that should be maintained during such types of transformations is versioning that aims to record the evolution of meanings in time as well as the management of their historical evolution.

Towards the automatic calculation of the EQUAL Candida Score: Extraction of CVC-related information from EMRs of critically ill patients with candidemia in Intensive Care Units.

Objectives: Candidemia is the most frequent invasive fungal disease and the fourth most frequent bloodstream infection in hospitalized patients. Its optimal management is crucial for improving patients' survival. The quality of candidemia management can be assessed with the EQUAL Candida Score.

Education in Health Informatics: Perspectives from the Italian Society for Biomedical Informatics (SIBIM).

The evolution of socio-technological habits together with the widespread demand of post-acute and chronic treatments outside hospital boundaries drove the increased demand of medical informatics experts to develop tools for and support healthcare professionals. The recent COVID-19 pandemic further highlighted the need of physicians able to manage diseases virtually and remotely. Moreover, healthcare professionals need to access to innovative techniques and procedures to manage biomedical data, cloud-based communication, and data sharing procedures, often connected to innovative devices to support an effective precision in the health treatments.

Pilot Study for a Model for the Collection of Waiting Lists Data.

The analysis of data on waiting lists in Italy is regulated by the PNGLA (National Plan for the Governance of Waiting Lists). However, the Plan does not specify the characteristics of the data to be returned by the Regions for the purposes of monitoring, with the result that it is frequently either in aggregate form, unreadable, or incomplete, and therefore cannot be analysed in any meaningful way. Fondazione the Bridge and AGENAS, with the University of Genoa and the University of Pavia, conducted a pilot study on a methodological model for the collection of waiting lists data.

The Representational Challenge for Designing and Managing 5P Medicine Ecosystems.

Health and social care systems around the globe currently undergo a transformation towards personalized, preventive, predictive, participative precision medicine (5PM), considering the individual health status, conditions, genetic and genomic dispositions, etc., in personal, social, occupational, environmental and behavioral context. This transformation is strongly supported by technologies such as micro- and nanotechnologies, advanced computing, artificial intelligence, edge computing, etc.

IDO1 correlates with the immune landscape of head and neck squamous cell carcinoma: a study based on bioinformatics analyses.

Background: Head and neck squamous cell carcinoma (HNSCCs) is a common cancer type with a high mortality rate and poor prognosis. Recent studies have focused on the role of immune checkpoints in HNSCC progression and in their potential use as prognostic markers and immunotherapeutic candidates. Some immune checkpoints, such as PD-1 and PD-L1, have been studied thoroughly in HNSCC.

Autonomous artificial intelligence versus teleophthalmology for diabetic retinopathy.

To assess the role of artificial intelligence (AI) based automated software for detection of Diabetic Retinopathy (DR) compared with the evaluation of digital retinography by two double masked retina specialists. Two-hundred one patients (mean age 65 ± 13 years) with type 1 diabetes mellitus or type 2 diabetes mellitus were included. All patients were undergoing a retinography and spectral domain optical coherence tomography (SD-OCT, DRI 3D OCT-2000, Topcon) of the macula.

Weight Gain in Overweight and Obese People with HIV-The OBHIV Cohort.

Background: HIV and non-HIV-related factors have been related to weight gain (WG); however, their specific impact on people with HIV (PWH) who are overweight or obese remains unclear.

Methods: This is a single-center observational study enrolling PWH with a BMI > 25 kg/m. A generalized linear model was used to assess variables related to greater WG during 12 years of observation.

Generalized Joint Hypermobility: A Statistical Analysis Identifies Non-Axial Involvement in Most Cases.

Context: Joint hypermobility (JH) represents the extreme of the normal range of motion or a condition for a group of genetically determined connective tissue disorders. Generalized joint hypermobility (GJH) is suspected when present in all four limbs and the axial skeleton, scored in prepubescent children and adolescents by a Beighton Score (BS) ≥ 6. Parameters are also used to identify GJH in hypermobile Ehlers-Danlos syndrome (hEDS) and hypermobility spectrum disorders (HSDs).