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Giardiasis: Serum antibodies and coproantigens in brown rats (Rattus norvegicus) from Grenada, West Indies

2018· article· en· W2790111469 on OpenAlexfundno aff
Keshaw Tiwari, Camille Coomansingh Springer, Alfred Chikweto, Josephine Tang, Yvette Sepulveda, Amanda Leigh Smith, Nia Rametta, Ravindra Sharma

Bibliographic record

VenueVeterinary World · 2018
Typearticle
Languageen
FieldImmunology and Microbiology
TopicParasitic Infections and Diagnostics
Canadian institutionsnot available
FundersSt. George's, University of LondonOttawa Hospital Research Institute
KeywordsGiardiaCryptosporidiumAntibodyBiologyGiardia lambliaVeterinary medicineParasite hostingMicrobiologyMedicineImmunologyFeces

Abstract

fetched live from OpenAlex

Aim: Giardia is a serious zoonotic parasite, which causes diarrheal disease in humans and animals including rodents.The purpose of this study was to estimate the prevalence of Giardia spp. in brown rats (Rattus norvegicus) in Grenada. Materials and Methods:Intestinal contents from 99 and serum samples from 169 brown rats (R. norvegicus) from Grenada were collected.These samples were examined for the Giardia coproantigens using Cryptosporidium/Giardia Quik Chek assay (Tech lab ® Inc., USA), and the serum was screened through an enzyme-linked immunosorbent assay (ELISA) test kit for Giardia antibody (anti-GD) ELISA kit (MyBioSource, San Diego, CA, USA).Results: Giardia coproantigens were positive in 17.17% (95% confidence interval [CI]; 10.33-26.06%)rats, whereas 55% (95% CI: 47.20-62.68)were positive with serum antibodies (anti-GD) to Giardia.Conclusion: The prevalence of Giardia spp. in brown rats in Grenada was moderate based on the presence of coproantigens in the intestinal contents and antibody in serum.The findings of Giardia infections and prevalence in brown rats will help veterinarians and physicians to better plan diagnostic and preventative strategies.This is the first report of prevalence of Giardia in brown rats in Grenada.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.020
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.023
GPT teacher head0.270
Teacher spread0.247 · 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 source (direct Gemma or distilled Codex), 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

Citations2
Published2018
Admission routes1
Has abstractyes

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