Assessment of Patient Satisfaction Among Patients Treated With Intravenous vs Subcutaneous Insulin for Diabetic Ketoacidosis.

Objectives: We previously implemented the subcutaneous (SQ) insulin in diabetic ketoacidosis (DKA) (SQuID) protocol, demonstrating safe, effective treatment of low to moderate (LTM) severity DKA in a non-intensive care unit setting. SQuID replaces intravenous (IV) insulin with SQ injections and reduces glucose checks from hourly to every 2 hours. We are not aware of any data on patient satisfaction with treatment in DKA.

Evaluation of an N1 NA antibody-specific enzyme-linked lectin assay for detection of H5N1 highly pathogenic avian influenza virus infection in vaccinated birds.

Unprecedented H5N1 highly pathogenic avian influenza (HPAI) outbreaks are occurring around the world and there is growing interest in the use of vaccines in affected regions. Vaccination when properly applied can contribute to HPAI control by significantly reducing virus shedding and breaking the transmission chain, but it requires robust surveillance to ensure that international trade is not affected. Thus, it is imperative to establish a test to differentiate vaccinated only animals from vaccinated and then infected animals (DIVA).

First report of (Diptera, Tachinidae) for the Canary Islands.

Background: The genus Berthold, 1827 is distributed in the Neotropical and Nearctic Regions and some species are very important for biological control. During the last decades, the species Bigot, 1876 has received much attention. It is of Neotropical origin, but it has been introduced throughout the western Palaearctic, probably through exchanges that transported its main host, the 'southern green stink bug' .

Image-Based Detection and Classification of Malaria Parasites and Leukocytes with Quality Assessment of Romanowsky-Stained Blood Smears.

Malaria remains a global health concern, with 249 million cases and 608,000 deaths being reported by the WHO in 2022. Traditional diagnostic methods often struggle with inconsistent stain quality, lighting variations, and limited resources in endemic regions, making manual detection time-intensive and error-prone. This study introduces an automated system for analyzing Romanowsky-stained thick blood smears, focusing on image quality evaluation, leukocyte detection, and malaria parasite classification.

Enhanced Detection of Leishmania Parasites in Microscopic Images Using Machine Learning Models.

Cutaneous leishmaniasis is a parasitic disease that poses significant diagnostic challenges due to the variability of results and reliance on operator expertise. This study addresses the development of a system based on machine learning algorithms to detect spp. parasite in direct smear microscopy images, contributing to the diagnosis of cutaneous leishmaniasis.