Dynamic cytokine gene expression characterized by increased IL-1 and IL-27 but decreased IL-8 occurs during development of bovine neonatal immunity.
Bibliographic record
Abstract
Abstract We analyzed 18 RNA-seq libraries from 3 bovine calves at day 0, 7, 14 and 28, together with their dams (day 0 and 7) for cytokine gene expression. Expression of IL7, required for B- and T-cell development, significantly increases from day 0 to day 28 post-birth (LogFC 1.98, FDR 0.0054). By contrast IL7R gene expression significantly declined from day 0 to day 7 (LogFC −1.22, FDR 6.1E-08). The IL21 was expressed at low levels but IL21R gene expression increased day 0 vs day 7 (LogFC 1.17, FDR 0.000140). IL12B expression, a subunit of IL-12, increased from day 0 vs day 7 (LogFC1.14, FDR 0.016) and then declined. In parallel, IL12RB1 expression increased from day 0 to day 7 to achieve adult levels (LogFC1.31, FDR 5.5E-10). By contrast, IL12RB2 declined significantly within 7 days post-birth (LogFC −1.46, FDR 3.1E-05). Both IL12RB1 and IL12RB2 constitute IL12 receptor complex involved in T cell differentiation. The IL27 was expressed at low levels at birth but reached adult levels by day 7 (LogFC 1,66, FDR 0.006). The IL1B expression increased post-birth by day 7 (LogFC 1.44, FDR 0.0083) whereas IL1R2 gene was highly expressed at birth but declined by day 7 (LogFC −3.22, FDR 5.9E-34). Expression of chemokine IL8 that encodes CXCL8 declined day 0 vs day 7 post-birth (LogFC −1.13, FDR 0.00015). The pro-inflammatory cytokine TNFα gene expression increased by day 14 (LogFC 1.04, FDR 0.015). While various cytokines are expressed in a dynamic manner, an increase in IL-1B, IL-7, IL-12B and a decrease in IL-8 appears to be of functional significance in the development of neonatal immunity. These observations are in contrast to other species such as humans. [Supported by NSERC Discovery Grant]
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".