Functionally Relevant Differences in Plasma Fatty Acid Composition and Expression of Cytotoxic and Inhibitory NK Cell Receptors between Healthy Young and Healthy Elder Adults
Bibliographic record
Abstract
(1) Background: In the healthy ageing, NK cell number is not modified; however, their spontaneous cytotoxicity decreases. We postulated that the age-dependent decline in metabolic activities might be responsible for this effect. (2) Methods: The fatty acid profile of 30 healthy young males (23 ± 4 years old, BMI 22.1 ± 1.3) and 30 older males (63 ± 5 years old, BMI 22.9 ± 2.5) donors were evaluated along with the expression of killing (KR) and inhibitory NK receptors (KIR) at basal level and after cultivation with fatty acids for 24 h. (3) Results: Significantly higher levels of oleic (p < 0.01), arachidonic (p < 0.001), lignoceric (p < 0.001), and nervonic acids (p < 0.0001) and significantly lower levels of docosapentaenoic and docosahexaenoic acids (p < 0.01) were found in elders as compared to young adults. At basal levels, significant (p < 0.005) differences in KR and KIR expression were encountered; 12/16 antigens. Treatment of cells with saturated fatty acids or arachidonic acid (AA) significantly enhanced KR expressions (p < 0.001). AA treatment decreased inhibitory KIR expression while docosahexaenoic, and eicosapentaenoic acid increased them. (4) Conclusions: Changes in fatty acids blood levels, and KR and KIR expression in NK cell, are age-dependent. Supplementation of NK cells with eicosapentaenoic or docosahexaenoic acid enhanced inhibitory KIR receptors’ expression which may improve their cell function.
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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) | 0.000 | 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) | 0.002 | 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".