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Record W2768243200 · doi:10.1111/jvim.14871

In vitro Inhibition of Canine Complement-Mediated Hemolysis

2017· article· en· W2768243200 on OpenAlexfundno aff
Dayand Marín Hernández, Robert Goggs, Erica Behling‐Kelly

Bibliographic record

VenueJournal of Veterinary Internal Medicine · 2017
Typearticle
Languageen
FieldImmunology and Microbiology
TopicComplement system in diseases
Canadian institutionsnot available
FundersInstitute of Musculoskeletal Health and ArthritisCollege of Veterinary Medicine, Cornell University
KeywordsHemolysisMedicineComplement systemHemolytic anemiaIn vitroImmune systemPharmacologyHaemolysisImmunologyChemistryBiochemistry

Abstract

fetched live from OpenAlex

BACKGROUND: Immune-mediated hemolytic anemia (IMHA) is the most common hematologic immune-mediated disease in dogs. Complement fixation on erythrocytes causes hemolysis. Complement inhibition decreases hemolysis in people with the hemolytic disease and also may prove effective in treating IMHA in dogs. HYPOTHESIS/OBJECTIVES: Evaluate the in vitro efficacy of 2 complement inhibitors used in humans against canine complement. METHODS: The inhibitory activity of the C3-inhibitor compstatin and recombinant human C1-esterase inhibitor (C1-INH) was evaluated using an in vitro hemolytic assay and spectrophotometric measurement of released hemoglobin. Dose-response curves for each inhibitor were generated. RESULTS: Compstatin decreased approximately 50% of canine complement-mediated hemolysis in initial experiments. This inhibition largely was lost when a new lot of drug was purchased. C1-INH showed a dose-dependent inhibition. The highest concentration of C1-INH tested (500 μg/mL) decreased >80% of canine complement-mediated hemolysis, and the lowest concentration tested (31.25 μg/mL) decreased hemolysis >60%. CONCLUSIONS AND CLINICAL IMPORTANCE: Human C1-INH is a robust inhibitor of canine complement-mediated hemolysis, whereas compstatin was minimally and variably effective. Human C1-INH may substantially decrease complement-mediated hemolysis in dogs with IMHA and warrants further investigation.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.407
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0020.000

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 head0.044
GPT teacher head0.341
Teacher spread0.296 · 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 designBench or experimental
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

Citations8
Published2017
Admission routes1
Has abstractyes

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