Measuring Peripheral Tissue <scp>DHA</scp> Turnover Using a Novel <scp> <sup>13</sup> C </scp> Enrichment Technique
Bibliographic record
Abstract
ABSTRACT Recently, through the use of compound‐specific isotope analysis (CSIA), our lab validated the utility of 13 C enrichment ( δ 13 C) of docosahexaenoic acid (DHA) by using a very high δ 13 C in a diet switch study by measuring brain, liver, and plasma DHA turnover and half‐lives via high‐precision gas chromatography combustion isotope ratio mass spectrometry (GC/C/IRMS). Using this novel enrichment technique, the present study extends measures of DHA turnover in the peripheral tissues, including red blood cells (RBC), perirenal adipose tissue (PRAT), muscle, heart, and skin. Mice were fed a low δ 13 C diet (fish‐DHA control) for 3 months, then switched to either a high δ 13 C treatment diet (algal‐DHA) or a very high δ 13 C treatment diet ( 13 C enriched‐DHA), while some remained on the fish‐DHA control diet as a reference group for the remainder of the study time course. In mice fed the algal and 13 C enriched‐DHA diets, the RBC DHA half‐life was 22.8 and 19.5 days, the PRAT DHA half‐life was 6.0 and 8.2 days, the muscle DHA half‐life was 38.2 and 42.2 days, the heart DHA half‐life was 12.4 and 10.5 days, and the skin DHA half‐life was 13.6 and 13.0 days, respectively. Future studies could employ the 13 C enrichment method to examine how DHA metabolism is altered in peripheral tissues according to genetics, stress, and development.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".