Altered <i>ex vivo</i> cytokine production in zinc-deficient, pair-fed and marginally zinc-deficient growing rats is independent of serum corticosterone concentrations
Bibliographic record
Abstract
The objective of the present study was to examine the effects of dietary Zn deficiency on the ex vivo cytokine production (IL-2, interferon-gamma (IFN-gamma), IL-6 and IL-10) of isolated thymocytes and splenocytes after mitogenic stimulation with concavalin A and to explore the role of corticosterone in this regulation. Weanling rats were assigned to one of four dietary treatments for 3 weeks: Zn-deficient (< 1mg Zn/kg diet, ad libitum), pair-fed (30 mg Zn/kg diet, limited to amount of feed as consumed by the Zn-deficient group), marginally Zn-deficient (10 mg Zn/kg diet, ad libitum) and control (30 mg Zn/kg diet, ad libitum). Thymocytes and splenocytes were isolated for cytokine stimulation and determination of T-cell phenotypes. Serum corticosterone concentrations were determined by ELISA. The Zn-deficient and pair-fed groups had 14-fold higher serum corticosterone concentrations compared with the marginally Zn-deficient and control groups (P<0.0001). The proportions of thymocyte subsets were not altered in the Zn-deficient, pair-fed or marginally Zn-deficient groups; however, thymocyte IL-2 and IL-6 production in these groups was 33-54% lower compared with the control group (P<0.05). The Zn-deficient group had an 18-28% lower proportion of new T-cells (TCRalphabeta+CD90+), but no difference in the proportion of new T-cells that were cytotoxic or helper. The Zn-deficient group had a 49-62% lower production of Th1 cytokines (IL-2), but no difference in the production of Th2 cytokines (IL-6, IL-10) by stimulated splenocytes compared with the pair-fed, marginally Zn-deficient and control groups (P<0.01). These results indicate that Zn status is associated with altered cytokine production, while in vivo corticosterone concentrations are not associated with ex vivo cytokine production.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".