Performance of soluble Klotho assays in clinical samples of kidney disease
Bibliographic record
Abstract
BACKGROUND: Soluble Klotho has multiple systemic salutary effects. In animals, both acute and chronic kidney disease models display systemic Klotho deficiency. As such, there is considerable interest in investigating soluble Klotho as a biomarker in patients with different types and severity of kidney diseases. Unfortunately, there remains uncertainty regarding the best method to measure soluble Klotho in human serum samples. METHODS: Using human serum samples obtained from several clinical cohorts with a wide range of kidney function, we measured soluble Klotho using a commercial enzyme-linked immunosorbent assay (ELISA) as well as with an immunoprecipitation-immunoblot (IP-IB) assay utilizing a synthetic antibody with high affinity and specificity for Klotho. Recovery of spiking with a known amount of exogenous Klotho was tested. A subset of samples was analyzed with and without the addition of a protease inhibitor cocktail at the time of collection or after the first freeze-thaw cycle to determine if these maneuvers influenced performance. RESULTS: = 0.18, P = 0.12). Use of a protease inhibitor cocktail neither improved nor impaired performance of the IP-IB assay; however, subsequent freeze-thaw cycle resulted in a significant reduction in Klotho recovery and dissipated the correlation between Klotho levels and eGFR. With the ELISA, the use of protease inhibitor cocktail resulted in an increase in intrasubject variability. CONCLUSIONS: The IP-IB assay is preferable to the commercial ELISA to measure soluble Klotho concentrations in never-thawed serum samples of humans with varying severity of kidney disease. However, due to the labor-intensive nature of the IP-IB assay, further research is needed to secure an assay suitable for high-throughput work.
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 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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".