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Record W3194373827 · doi:10.3390/ani11082437

Cystinuria in Dogs and Cats: What Do We Know after Almost 200 Years?

2021· review· en· W3194373827 on OpenAlexaboutno aff
Simona Kovaříková, Petr Maršálek, Kateřina Vrbová

Bibliographic record

VenueAnimals · 2021
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAmino Acid Enzymes and Metabolism
Canadian institutionsnot available
Fundersnot available
KeywordsCystinuriaCystineOrnithineAminoaciduriaUrineLysineChemistryInternal medicineMedicineAmino acidArginineBiologyBiochemistryCysteine

Abstract

fetched live from OpenAlex

The purpose of this review is to summarize current knowledge on canine and feline cystinuria from available scientific reports. Cystinuria is an inherited metabolic defect characterized by abnormal intestinal and renal amino acid transport in which cystine and the dibasic amino acids ornithine, lysine, and arginine are involved (COLA). At a normal urine pH, ornithine, lysine, and arginine are soluble, but cysteine forms a dimer, cystine, which is relatively insoluble, resulting in crystal precipitation. Mutations in genes coding COLA transporter and the mode of inheritance were identified only in some canine breeds. Cystinuric dogs may form uroliths (mostly in lower urinary tract) which are associated with typical clinical symptoms. The prevalence of cystine urolithiasis is much higher in European countries (up to 14% according to the recent reports) when compared to North America (United States and Canada) where it is approximately 1-3%. Cystinuria may be diagnosed by the detection of cystine urolithiasis, cystine crystalluria, assessment of amino aciduria, or using genetic tests. The management of cystinuria is aimed at urolith removal or dissolution which may be reached by dietary changes or medical treatment. In dogs with androgen-dependent cystinuria, castration will help. In cats, cystinuria occurs less frequently in comparison with dogs.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.995
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.015
GPT teacher head0.300
Teacher spread0.285 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations13
Published2021
Admission routes1
Has abstractyes

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