Detection of intestinal parasites in human faecal samples using dissolved air flotation.

OBJECTIVE: Ova and parasite (O&P) examination is recommended for the laboratory diagnosis of agents causing parasitic infections; however, this exam requires scientific and technological improvements to enhance its diagnostic validity. Dissolved air flotation (DAF) is an efficient technical principle separating suspended solids in a liquid medium. We aimed to develop and validate a new procedure for intestinal parasite detection with DAF. METHODS: In this study, we collected samples from 500 volunteers, screened them by direct examination, and transferred the material to tubes using the Three Faecal Test (TF-Test) for triplicate DAF tests. We evaluated physical-chemical parameters and DAF prototype components through quantifying parasites recovered from floated and non-floated regions of the flotation column. The DAF operation protocol was validated with the gold standard results. RESULTS: The 10% saturated volume proportion and cationic surfactant showed regularity and high parasite recovery (80%). Modifications of the needle device did not influence parasite recovery (p > 0.05). Sensitivity, specificity, accuracy and kappa agreement obtained with the DAF protocol were 91%, 100%, 93% and substantial (k = 0.64), respectively. CONCLUSION: The DAF principle could be used to process faecal samples in routine laboratory exams, enabling intestinal parasite detection.

Staining blindly: an update on coloring techniques for fecal smears in parasitology: a scoping review.

Dye application for parasite highlighting in the Ova and Parasite exam is a common practice in parasitology diagnosis. Methods: A scoping review investigated how staining solutions interact with parasite structures. After screening 1334 papers, 35 met eligibility criteria. Results: Differentiating background from foreground in the fecal smear under light microscopy is the core of the research on this topic. Refractivity, unevenness of staining, size and temperature were explored to enhance staining protocols. Cryptosporidium spp. and Microsporidia were the main studied species. Conclusion: Studies on diagnostic efficacy outperform those that elucidate the physical-chemical interaction between dyes and parasites. An alternative approach involves technicians using computational tools to reduce subjectivity in fecal smear interpretation, deviating from conventional methods.

What is this article about? Coloring parasites during fecal exams has been widely used to find parasites in human feces. We searched for articles that could help us to answer the question: 'How do dyes give color to parasites?'. Then, we filtered the information from a total of 1334 articles to 35.What were the results? Cryptosporidium spp. and Microsporidia are microbes that can be seen only through a microscope. Researchers were interested in these two species in the last 40 years. Differentiating parasites from dirt on a glass slide is the main problem researchers are trying to solve. The way the light goes through parasites under a microscope, variation of staining, size and temperature of dyes have been explored to identify what gives better results in coloring protocols.What do the results of the study mean? Little is known about the chemical interaction between dyes and parasites. On the other hand, there are many studies on how good coloring methods are and comparing protocols. An alternative to the conventional approaches in staining parasites is the use of computational tools to reduce doubt in the exam interpretation by technicians.

Toward automating the diagnosis of gastrointestinal parasites in cats and dogs.

Diagnosing gastrointestinal parasites by microscopy slide examination often leads to human interpretation errors, which may occur due to fatigue, lack of training and infrastructure, presence of artifacts (e.g., various types of cells, algae, yeasts), and other reasons. We have investigated the stages in automating the process to cope with the interpretation errors. This work presents advances in two stages focused on gastrointestinal parasites of cats and dogs: a new parasitological processing technique, named TF-Test VetPet, and a microscopy image analysis pipeline based on deep learning methods. TF-Test VetPet improves image quality by reducing cluttering (i.e., eliminating artifacts), which favors automated image analysis. The proposed pipeline can identify three species of parasites in cats and five in dogs, distinguishing them from fecal impurities with an average accuracy of 98,6%. We also make available the two datasets with images of parasites of dogs and cats, which were obtained by processing fecal smears with temporary staining using TF-Test VetPet.