TGF-β<sub>1</sub> gene-race interactions for resting and exercise blood pressure in the HERITAGE Family Study
Bibliographic record
Abstract
We examined the possible association between a transforming growth factor (TGF)-beta(1) gene polymorphism in codon 10 and blood pressure (BP) at rest, in acute response to exercise in the pretrained (sedentary) and trained states, as well as in its training response (Delta) to 20 wk of endurance exercise. Subjects were 257 black and 480 white, healthy sedentary normotensive subjects from the HERITAGE Family Study. The polymorphism was detected by polymerase chain reaction and digestion with the Msp A1 I endonuclease yielding a wild (leucine-10) and a mutant (proline-10) allele. Resting and exercise [50 W plus 60, 80, and 100% maximal oxygen consumption (VO(2)(max))] BP were determined before and after training. Significant (P < 0.05) race-genotype interactions were found for systolic (S) BP in both the sedentary and trained states. Among whites but not in blacks, the TGF-beta(1) genotypes were significantly (P < 0.05) associated with sedentary-state SBP at rest, at 50 W, and at 60 and 100% VO(2)(max)as well as with trained-state SBP at rest and at 80 and 100% VO(2)(max). The leucine-10 homozygotes had significantly (P < 0.05) lower SBP than proline-10 homozygotes. DeltaBP was not significantly associated with genotype. These results support the hypothesis of an association between the TGF-beta(1) marker in codon 10 and SBP at rest and in response to acute exercise in whites but not in blacks.
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 | 0.000 | 0.001 |
| 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) | 0.003 | 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".