High expression of genes encoding signaling molecules (<i>LAX1</i>, <i>BLK</i>) and transcriptional factors (ICOS, GATA3) characterizes 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 cell signaling and transcription factors gene expression. LAX1, lymphocyte transmembrane adaptor 1 is consistently expressed at higher levels post-birth. Similarly, BLK, a cell signaling tyrosine kinase required for from pro- to pre-B cell transition is expressed at high levels 4 weeks post-birth. A trend for increased expression of Igα (CD79A) and Igβ (CD79B) in neonatal B cells is noted day 0 to day 28 (LogFC 0.8 and P-value< 0.05 FDR <0.15). The CD40 expression is also significantly increased day 0 versus day 14 (LogFC 1.05, FDR .00039) to achieve steady levels. A lack of increase in T-cell signaling molecules CD3G and CD3D expression suggests neonatal T cell quiescence, but is higher than the dams (FDR<0.05). However, the ICOS (CD278) expression is increased from day 0 to day 7 post-birth (LogFC 1.11, FDR 0.00027). Similarly, an increased expression of FOXP3, relevant to the development of regulatory T cells, occurs in bovine neonates day 0 vs day 7 (LogFc 1.23, FDR 0.00063). The expression of GATA3 transcription factor, regulator of innate and adaptive immunity associated with TH2 differentiation, is high in neonates as compared to the adults (FDR<0.001). As would be expected, various transcriptional factors and cell signaling molecules contribute towards T and B cell proliferation and expansion, but a lack of increased expression of CD3G and CD3D genes suggests T cell quiescence early during ontogeny. [Supported by NSERC Canada 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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.004 | 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".