Precision evaluation of different flotation solutions in the results of four coprological techniques in ungulates : impact on detecting anthelmintic resistance
Bibliographic record
Abstract
Anthelmintic resistance (AHR) in gastrointestinal parasites of ruminants and horses has been continuously described all over the world in the last two decades. In order to delay, or even prevent, the further development of resistance to anthelmintics, a new deworming approach must be taken, considering the diagnostic tools available nowadays. This study aims to evidence the differential performances of four commonly employed coprological methods, using different flotation solutions, and make some practical recommendations on which technique seems better-suited to face this emerging problem in horse management. This thesis contains two parts. In the first one, three wild ungulate species were analyzed at ARTIS Amsterdam Royal Zoo to determine the repeatability of four common coprological methods – simple flotation (SF), centrifugal flotation (CF), McMaster (McM - sensitivity of 50 eggs per gram EPG) and Mini-FLOTAC (MF – sensitivity of 5 EPG) – in association with three flotation solutions with different specific gravities: salt (SG=1.20), magnesium sulphate (MgSO4) (SG=1.24) and sugar solution (SG=1.28); where each sample was analyzed 10 times. In the second part 17 fecal samples of Sorraia horses were collected in April 2019 (12 females on the pasture and five stabled males) and analyzed with the same methods but only with the salt and sugar solutions; each sample was analyzed in triplicates for SF and CF and in duplicates for McM and MF. As a semi-quantitative parameter, the number of eggs were counted in 10 fields of each slide and the mean was obtained for each replicate. In the first part of the study, CF was able to evidence a higher amount of total egg counts, especially with the denser solutions, with lower coefficients of variation (CV). MF performed with very good precision across the species, with different solutions apparently better for each one of them. In the second part of the study, SFsalt obtained the best results for detecting Triodontophorus spp. eggs, although not significantly (p>0.05). Yet, it showed lower CV than CF techniques, which makes it a more precise and reliable technique. High parasitic burdens (mean of 1825 EPG for all techniques) were registered and MFsugar performed more consistently as seen by its low variability. Through coprocultures, the prevalence of Cyathostomum s.l. type D (100%) and S. vulgaris (5.9%) were also detected. The results obtained here support the use of CF and MF methods in zoos as valid diagnostic tools. In general, MF was shown to be more precise and reliable across the study, urging the need to review current guidelines for the diagnosis of AHR, namely in horses. Unexpectedly, a clear association was evidenced, as salt solutions seem to be better suited for qualitative methods, whereas the sugar solutions better suited for quantitative ones instead.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".