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Practical guide for microscopic identification of infectious gastrointestinal nematode larvae in sheep from Sardinia, Italy, backed by molecular analysis.

Stephane KnollGiorgia DessìClaudia TamponiLuisa MeloniLia CavalloNaunain MehmoodPhilippe JacquietAntonio ScalaMaria Grazia CappaiAntonio Varcasia
Published in: Parasites & vectors (2021)
It is crucial for the microscopic identification of infectious GIN larvae to examine each larva in its entirety and thus to take multiple characteristics into account to obtain an accurate diagnosis. However, a preliminary classification based on sheathed tail length (resulting in three groups: A, short; B, medium; C, long) was found to be effective. Further identification within group A can be achieved based on the presence of a cranial inflexion, caudal tubercles and full body measurements (Trichostrongylus spp. < 720 µm, T. circumcincta ≥ 720 µm). Larvae within group B can be differentiated based on sheathed tail morphometry (H. contortus > 65 µm, C. curticei ≤ 65 µm), the presence of cranial refractile bodies, total body length measurements (H. contortus ≤ 790 µm, C. curticei > 790 µm) and shape of the cranial extremity. Finally, all characteristics proposed for the differentiation between Oesophagostomum spp. and C. ovina larvae (group C) were found to have considerable restrictions.
Keyphrases
  • aedes aegypti
  • drosophila melanogaster
  • bioinformatics analysis
  • machine learning
  • deep learning