A specific immunoassay for detection of feline kidney injury molecule 1
Bibliographic record
Abstract
OBJECTIVES: The aim of this study was to design and carry out a preliminary evaluation of a urine point-of-care test for kidney injury molecule 1 (KIM-1) in healthy and diseased cats. METHODS: gene was amplified, ligated into a plasmid with a signal peptide and monomeric human IgGFc, and transfected into a mammalian cell line. Supernatant was purified and tested for the fusion protein by gel electrophoresis and Western blot. Mice were immunized three times with purified proteins, and hybridomas were generated from splenocytes. Antibodies were tested by ELISA for detection of recombinant KIM-1 and naturally occurring KIM-1 in disease-state urine. Next, a lateral flow assay (LFA) with capture and detection antibodies was constructed, and tested with 34 urine samples from healthy and diseased cats. Antibodies were also tested for reactivity with formalin-fixed paraffin-embedded kidney tissue. RESULTS: Three antibodies were assessed. Antibodies detected between 0.4 and 60 ng/ml feline KIM-1 fusion protein in the LFA. Urine samples from healthy cats yielded faint bands in the LFA corresponding to optical density (OD) values of 4.8-8.8. Samples from cats with suspected or confirmed acute kidney injury (AKI) had OD values ranging from 1.6-20.5. Urine KIM-1 varied over multiple days in cats with sepsis or urethral obstruction despite normalizing serum creatinine concentration. In tissue sections, KIM-1 antibodies labeled tubular cells with morphological features of injury. CONCLUSIONS AND RELEVANCE: A practical patient-side assay for detection of KIM-1 in feline urine has been developed. Preliminary results show marked though transient increases in cats with sepsis and urethral obstruction-associated AKI, and expression in injured tubules. Although initial data indicating that the LFA is sensitive and specific for KIM-1 in cats with AKI are promising, values associated with different types of injury, urine collection, urine storage and specific gravity need to be investigated.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".