Estimating the Replication Rate of Hematopoietic Stem Cells in Non-Human Primates: A Test of Hayflick’s Hypothesis.
Bibliographic record
Abstract
Abstract Because hematopoietic stem cells (HSC) cannot be directly observed, stochastic simulations in conjunction with competitive repopulation experiments have been used to estimate the replication rate of feline (1 rep per 8–10 wks) and murine (1 rep per 2.5 wks) HSC (model description and estimates in Nat Med2:190, 1996; Blood96:3399, 2001). These results could suggest that the HSC replication rate decreases with animal size and longevity, perhaps implying that the number of lifetime replications per HSC is limited and conserved in mammals. To test this, we analyzed retroviral vector gene marking and granulocyte telomere length data from baboons and rhesus macaques. Rhesus macaques are approximately the same size (weight 8 kg) as cats and have a similar lifespan (15–20 years); their hematopoietic demand, defined as the number of blood cells required per lifetime, is comparable. In contrast, baboons are larger (15 kg), live for 30 years, and have a hematopoietic demand more similar to humans. We simulated HSC dynamics for virtual baboons and macaques using specific HSC replication rates and then determined if observed data could be a random draw from 1000 simulated datasets. Compatibility of simulated and observed gene marking studies was determined by 3 formal criteria computed for both observed and simulated data: 1) the time after transplantation until the percent of marked cells stabilizes (measured using a change point model), 2) the presence or absence of drift after stabilization (drift is defined as a post-stabilization slope significantly different from 0 and estimated as at least 2% per 100 days), and 3) the amount of residual variation after stabilization (variation about a smoothed fit to the data -- transforming using the variance-stabilization transformation, arcsine of square root). Binomial probabilities were computed to evaluate Criterion 2 and Kolmogorov-Smirnov goodness of fit tests were used for evaluating Criteria 1 and 3, with p-values < 0.05 defining incompatibility. Mice and cat HSC parameters did not yield simulated data compatible with the observed baboon data. Rather, the analyses required that baboon HSC replicated less frequently, approximately once per 27–77 weeks (with 300 transplanted HSC (the estimated number infused); the range was robust to other modeling assumptions). In contrast, cat HSC parameters yielded simulated data compatible with the observed macaque data if 100–500 HSC were transplanted, whereas mice HSC parameters trended towards incompatibility (incompatible for 100 and 500 transplanted HSC; nearly incompatible for 300 transplanted HSC, p=0.07). Next, granulocyte telomere length data were simulated (methods in Exp Hematol32:1040; 2004) and preliminary data yielded best estimates for the replication rate of HSC in macaques and baboons of once per 18 weeks and once per 24 weeks, respectively. Our results (derived from 2 independent experimental approaches) demonstrate that the replication rate of macaque HSC is slower than mouse, whereas the replication rate of baboon HSC is slower than both cat and mouse; argue that the rate of HSC replication inversely correlates with longevity; and support Hayflick’s hypothesis that cells can only undergo a relatively constant finite number of lifetime replications. This apparent evolutionary constraint may extend to human HSC behavior.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".