Impaired <scp>SIRT</scp> 1 activity leads to diminution in glomerular endowment without accelerating age‐associated <scp>GFR</scp> decline
Bibliographic record
Abstract
Glomerular filtration rate (GFR) declines with age such that the prevalence of chronic kidney disease is much higher in the elderly. SIRT1 is the leading member of the sirtuin family of NAD+-dependent lysine deacetylases that mediate the health span extending properties of caloric restriction. Since reduction in energy intake has also been shown to decrease age-related kidney disease in rodents, we hypothesized that a diminution in SIRT1 activity would accelerate the GFR decline and structural injury with age. To test this hypothesis, we compared changes in the kidney structure and function in control mice and mice that carry a point mutation at a conserved histidine (H355Y) of SIRT1 that renders the enzyme catalytically inactive. Taking advantage of this mouse model along with the disector/fractionator technique for glomerular counting and direct measurements of GFR by inulin clearance, we assessed the impact of SIRT1 inactivity on kidney aging. At 14 months of age, SIRT1 catalytically inactive (Sirt1Y/Y) mice had lower GFRs and fewer glomeruli than their wild-type (Sirt1+/+) counterparts. This was not, however, due to either accelerated GFR decline or increased glomerulosclerosis and loss, but rather to reduced glomerular endowment in Sirt1Y/Y mice. Moreover, the compensatory glomerular hypertrophy and elevated single nephron GFR that customarily accompany reduction in nephron number were absent in Sirt1Y/Y mice. These findings suggest a role for SIRT1 not only in determining nephron endowment but also in orchestrating the response to it.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".