Protein concentrations and activities of fatty acid desaturase and elongase enzymes in liver, brain, testicle, and kidney from mice: Substrate dependency
Bibliographic record
Abstract
The synthesis rates of n-3 and n-6 polyunsaturated fatty acids (PUFAs) in rodents and humans are not agreed upon and depend on substrate availability independently of the capacity for synthesis. Therefore, we aimed to assess the activities of the enzymes for n-3 and n-6 PUFA synthesis pathways in liver, brain, testicle, kidney, heart, and lung, in relation to their protein concentration levels. Eight-week-old Balb/c mice (n = 8) were fed a standard chow diet (6.2% fat, 18.6% protein, and 44.2% carbohydrates) until 14 weeks of age, anesthetized with isoflurane and tissue samples were collected (previously perfused) and stored at -80°C. The protein concentration of the enzymes (Δ-6D, Δ-5D, Elovl2, and Elovl5) were assessed by ELISA kits; their activities were assayed using specific PUFA precursors and measuring the respective PUFA products as fatty acid methyl esters by gas chromatographic analysis. The liver had the highest capacity for PUFA biosynthesis, with limited activity in the brain, testicles, and kidney, while we failed to detect activity in the heart and lung. The protein concentration and activity of the enzymes were significantly correlated. Furthermore, Δ-6D, Δ-5D, and Elovl2 have a higher affinity for n-3 PUFA precursors compared to n-6 PUFA. The capacity for PUFA synthesis in mice mainly resides in the liver, with enzymes having preference for n-3 PUFAs.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".