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Record W6991190277

FLOTAC FOR URO-MICROSCOPIC DIAGNOSIS OF CAPILLARIA PLICA IN DOGS

2013· article· en· W6991190277 on OpenAlexaboutno aff

Bibliographic record

VenueCINECA IRIS Institutional Research Information System (University of Bari Aldo Moro) · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMollusks and Parasites Studies
Canadian institutionsnot available
Fundersnot available
KeywordsUrineCapillariaErythrocyte sedimentation rateUrinary systemUrinary sedimentSedimentation
DOInot available

Abstract

fetched live from OpenAlex

Capillaria plica (Syn. Pearsonema plica), commonly known as the “bladderworm” is a nematode that resides in the urinary bladder and rarely in ureters or in the kidney pelvis of various wild carnivores, especially foxes and dogs (Bork‐Mimm and Rinder, 2011). Urinary sedimentation technique is actually the only diagnostic tool that permits the identification of C. plica eggs. The aim of this study was to compare two innovative techniques, FLOTAC and Mini‐FLOTAC, with the “classical” technique of sedimentation for the diagnosis of C. plica in dog urine. A 4‐year‐old Labrador Retriever, male, from the Apulia Region (southern Italy) was presented to the referring clinician with macrohaematuria. A first examination of urinary sediment revealed the presence of several C. plica eggs. Two aliquots of 200 ml of urine were collected from the dog infected by C. plica. Each aliquot of urine was accurately homogenized and divided in 18 tubes each filled with 10 ml of urine, to have 6 replicates for each diagnostic method. The tubes were randomly assigned to the following techniques: FLOTAC (Cringoli et al., 2010), Mini‐FLOTAC (Cringoli et al., 2013) and sedimentation (WHO, 1991). A sodium chloride‐based flotation solution (FS2, specific gravity= 1.20) was used for the FLOTAC and Mini‐FLOTAC techniques. The analytic sensitivity of each technique was 1 egg per 10 ml of urine. All the three techniques were capable to detect C. plica eggs. For aliquot 1, the mean number of C. plica detected with FLOTAC was significantly higher than those detected by Mini‐FLOTAC and sedimentation (40.7 eggs per 10 ml of urine vs 28.3 and 20.7, respectively); however, the CV% detected with FLOTAC was lower (5.5 vs 12.8 and 36.0, respectively). Also for the aliquot 2, FLOTAC gave higher mean than the other two techniques (99.8 eggs per 10 ml of urine vs 52.3 and 44.8, respectively) and lower CV% (6.8 vs 14.0 and 29.7, respectively). The findings of the present study suggested that FLOTAC is the best method for the diagnosis of C. plica in dog urine. An alternative diagnostic method is Mini‐FLOTAC that can be used in place of FLOTAC in laboratories where the centrifugation step cannot be performed.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.238
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.054
GPT teacher head0.265
Teacher spread0.211 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2013
Admission routes1
Has abstractyes

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