Publications by authors named "V Economou"

Extended-spectrum-β-lactamase (ESBL) and carbapenemase-producing , and spp. are associated with hospital-acquired infections and are commonly isolated across the poultry food production chain. Comprehensive data regarding the prevalence, spatiotemporal variations, and characterization of β-lactam-resistant bacteria in poultry farms and slaughterhouses is scarce.

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  • Beef is primarily produced from beef cattle, but dairy calves can also be raised for meat; this study focuses on how oregano oil in diets affects meat quality in Holstein bulls.
  • A total of 50 Holstein bulls were split into two groups: one received a standard diet, while the other’s diet was enriched with oregano oil for 90 days.
  • The results showed that the oregano oil group had better meat color and flavor scores, lower malondialdehyde levels, and higher nutritional value, indicating that oregano oil can enhance the quality of meat from Holstein bulls.
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  • Extended-spectrum-β-lactamase (ESBL) and carbapenemase-producing Enterobacterales in hospital kitchens are associated with antibiotic resistance, presenting risks for patient infections.
  • This study aimed to evaluate the prevalence and characteristics of β-lactam-resistant strains from kitchen environments and hospital staff in two Greek hospitals.
  • Findings show a notable prevalence of resistant strains in kitchens and a connection between kitchen and patient strains, indicating that kitchen environments may act as reservoirs for these harmful pathogens.
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  • This research explores 3D-printed antifungal buccal films (BFs) made from a zein-PVP polymer blend as a possible substitute for traditional antifungal oral gels, highlighting their ease of manufacturing and suitability for children.
  • The films provide sustained release, with 80% of the drug miconazole being released over 2 hours, and disintegrate in under 10 minutes while adhering to buccal tissue.
  • Comprehensive evaluations confirm the films' physicochemical stability, mucoadhesion, and effective antifungal activity, making them a promising option for treating fungal infections in the oral cavity.
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Predictive tools provide a unique opportunity to explain the observed differences in outcome between patients of the COVID-19 pandemic. The aim of this study was to associate individual demographic and clinical characteristics with disease severity in COVID-19 patients and to highlight the importance of machine learning (ML) in disease prognosis. The study enrolled 344 unvaccinated patients with confirmed SARS-CoV-2 infection.

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