The demonstration of αKlotho deficiency in human chronic kidney disease with a novel synthetic antibody
Bibliographic record
Abstract
BACKGROUND: αKlotho is the prototypic member of the Klotho family and is most highly expressed in the kidney. αKlotho has pleiotropic biologic effects, and in the kidney, its actions include regulation of ion transport, cytoprotection, anti-oxidation and anti-fibrosis. In rodent models of chronic kidney disease (CKD), αKlotho deficiency has been shown to be an early biomarker as well as a pathogenic factor. The database for αKlotho in human CKD remains controversial even after years of study. METHODS: We used a synthetic antibody library to identify a high-affinity human antigen-binding fragment that recognizes human, rat and mouse αKlotho primarily in its native, rather than denatured, form. RESULTS: Using an immunoprecipitation-immunoblot (IP-IB) assay, we measured both serum and urinary levels of full-length soluble αKlotho in humans and established that human CKD is associated with αKlotho deficiency in serum and urine. αKlotho levels were detectably lower in early CKD preceding disturbances in other parameters of mineral metabolism and progressively declined with CKD stages. We also found that exogenously added αKlotho is inherently unstable in the CKD milieu suggesting that decreased production may not be the sole reason for αKlotho deficiency. CONCLUSION: Synthetic antibody libraries harbor tremendous potential for a variety of biomedical and clinical applications. Using such a reagent, we furnish data in support of αKlotho deficiency in human CKD, and we set the foundation for the development of diagnostic and therapeutic applications of anti-αKlotho antibodies.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".