Characterization of the Hepatic Transcriptome for Divergent Immune-Responding Sheep Following Natural Exposure to Gastrointestinal Nematodes
Bibliographic record
Abstract
Infections with gastrointestinal nematodes (GINs) reduce the economic efficiency of sheep operations and compromise animal welfare. Understanding the host’s response to GIN infection can help producers identify animals that are naturally resistant to infection. The objective of this study was to characterize the hepatic transcriptome of sheep that had been naturally exposed to GIN parasites. The hepatic transcriptome was studied using RNA-Sequencing technology in animals characterized as high (n = 5) or medium (n = 6) based on their innate immune acute-phase (AP) response phenotype compared with uninfected controls (n = 4), and with biased antibody-mediated (AbMR, n = 5) or cell-mediated (CMR, n = 5) adaptive immune responsiveness compared to uninfected controls (n = 3). Following the assessment of sheep selected for innate responses, 0, 136, and 167 genes were differentially expressed (DE) between high- and medium-responding animals, high-responding and uninfected control animals, and medium-responding and uninfected control animals, respectively (false discovery rate (FDR) < 0.05, and fold change |FC| > 2). When adaptive immune responses were assessed, 0, 53, and 57 genes were DE between antibody- and cell-biased animals, antibody-biased and uninfected control animals, and cell-biased and uninfected control animals, respectively (FDR < 0.05, |FC| > 2). Functional analyses identified enriched gene ontology (GO) terms and metabolic pathways related to the innate immune response and energy metabolism. Six functional candidate genes were identified for further functional and validation studies to better understand the underlying biological mechanisms of host responses to GINs. These, in turn, can potentially help improve decision making and management practices to increase the overall host immune response to GIN infection.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".