Specific activity of mouse liver desaturases and elongases: Time course effects using n-3 and n-6 PUFA substrates and inhibitory responses of delta-6 desaturase
Bibliographic record
Abstract
The synthesis of n-3 and n-6 polyunsaturated acids (PUFAs) is associated with physiological functions in mammals, being catalyzed by Δ-5D and Δ-6D desaturases and elongases Elovl-2 and Elovl-5. In this context, we aimed to study the chief kinetic features of PUFA liver anabolism, looking upon (i) the time-dependency for the specific activity of Δ-6D, Δ-5D, Elovl2, Elovl2/5 and Elovl5, using n-3 and n-6 precursors between 0 and 240 min ex vivo in mouse liver.; and (ii) the specific activity-substrate (α-linolenic acid; ALA) concentration responses of Δ-6D in the absence and presence of linoleic acid (LA), arachidonic acid (ARA), eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), an enzyme regarded as the rate-limiting step in PUFA anabolism. Mouse liver was obtained from eight-week-old Balb/c mice fed a chow diet (expressed as % of total calories: 18 % fat, 24 % protein, and 58 % carbohydrate, with a caloric value of 3.1 kcal/g) for eight weeks, and used for preparation of the microsomal fraction. Enzymatic activities assayed under the addition of specific PUFA precursors or LA, ARA, EPA and DHA, identifying the respective PUFA products as fatty acid methyl esters by gas chromatographic analysis. Data described corroborate that (i) PUFA metabolism mainly occurs in the liver, with the participating enzymes preferring n-3 than n-6 substrates; and show that (ii) the rate-limiting step of PUFA metabolism relies on the second reaction of Δ-6D (24:5n-3 transformed to 24:6n-3); and (iii) LA, ARA, EPA and DHA act as non-competitive inhibitors with respect to ALA in the reaction catalyzed by Δ-6D. These results are relevant for future studies concerning the metabolic and nutritional implications of changes in desaturation and elongation of 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 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".