Publications by authors named "M Del Core"
The protein, essential amino acid, and fatty acid composition of European pilchard (), European hake (), surmullet (), red mullet (), and deep water rose shrimp () from the central Mediterranean Sea were investigated. All the species showed an essential amino acid content of about 50% of total amino acids, while the protein and total fatty acids content varied from 19.9 to 24.
View Article and Find Full Text PDFArticle Synopsis
- The study evaluates the nutritional composition and safety of lab-produced snail flour from herbivorous snails, focusing on essential nutrients like moisture, protein, and fat.
- Contaminant analysis showed no detectable levels of harmful substances like PAHs and PCBs, with heavy metal concentrations comparable to or lower than existing data, indicating the flour's safety for consumption.
- The findings highlight a significant presence of polyunsaturated fatty acids and essential amino acids, supporting the use of snail flour as a sustainable protein source for both human and animal diets.
Clinical Implementation of an AI Early Warning System Algorithm: Lessons Learned.
Stud Health Technol Inform
January 2024
The Deterioration Index (DI) is an automatic early warning system that utilizes a machine learning algorithm integrated into the electronic health record and was implemented to improve risk stratification of inpatients. Our pilot implementation showed superior diagnostic accuracy than standard care. A score >60 had a specificity of 88.
View Article and Find Full Text PDFArticle Synopsis
- Threshold-based early warning systems (EWS) help predict adverse events in hospitalized patients, and machine learning (ML) algorithms using EWS scores could enhance prediction accuracy.
- The study utilized the deterioration index (DI) to assess patient risk and developed a new ML model, achieving improved performance compared to traditional threshold models, with the top classifier significantly predicting adverse events.
- Time-based analysis indicated the best predictive accuracy occurs within the hour before an event, but the model still performs well up to 12 hours in advance, demonstrating its reliability across multiple clinical sites.
To date, remediation, protection, and restoration of contaminated sites is a global concern. The current technologies to restore sediments characterized by heterogeneous characteristics, several pollutants, fine grains, and low hydraulic permeability are poorly effective; hence their remediation is still challenging. A promising approach for the sediment's remediation could be the electrochemical route since it is a not-expensive, effective and noninvasive in situ technology.
View Article and Find Full Text PDF