Hydrocortisone-modulated Immune Response and Altered Amino Acid Pool in Vitro
Bibliographic record
Abstract
Background : Dietary deficiencies, from macro- to micronutrients, are often associated with dysfunction of the immune system. The aim for this study was to assess changes in amino acid metabolism and immune response in a modeled “stress” environment. Methods : Heparinized blood samples from healthy donors were collected by venipuncture. Peripheral blood mononuclear cells were isolated and then incubated with a mixture of LPS and PHA in RPMI-1640 medium. Cell cultures were treated with hydrocortisone at physiological ( 10 -8 M) and “stress” (10 -6 M) concentrations. Surface expression of CD25 by the CD3 + lymphocytes was analyzed by flow cytometry. Levels of the cytokines IL-2, IFN-gamma , IL-4, and IL-10 were measured with ELISA. Quantification of IL-2- and IFN-gamma- secreting T cells was performed in cell cultures treated with PMA, ionomycin, and brefeldin A. Results : The number of CD3 + CD25 + cells was significantly lower in cultures treated with 10 -6 M of hydrocortisone than in control cultures. Treatment of cell cultures with 10 -8 M hydrocortisone significantly increased levels of IFN-gamma and IL-10, but not IL-2 and IL-4. Treatment with 10 -6 M of hydrocortisone significantly suppressed secretion of all studied cytokines. Treatment with 10 -8 M hydrocortisone produced a consistent unidirectional effect on amino acids in the supernatant medium: increased concentrations of almost all amino acids. Treatment with 10 -6 M hydrocortisone significantly decreased the level of asparagine while it increased levels of serine and tyrosine compared to control cultures. Conclusion : Data suggest that the stress-dose of cortisol modulated amino acid metabolism in mitogen-stimulated immunocompetent cells in vitro. Also, observed differences in amino acid concentrations between cultures suggest that supplementation with low doses of endocrine mediators may create a more physiological environment for culturing PBMCs. doi:10.4021/jem49w
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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 | 0.001 |
| 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".