Identification of reference genes for real-time PCR cytokine gene expression studies in sheep experimentally infected with Fasciola hepatica
Bibliographic record
Abstract
The aim of this study was to validate reference genes for gene normalisation using qRT-PCR in hepatic lymph nodes (HLN) and livers from sheep infected with Fasciola hepatica during early and late stages of infection. To this end, a comprehensive statistical approach (RefFinder) encompassing four different methods of analysis (geNorm, BestKeeper, ΔCt method and NormFinder) was used to validate ten candidate reference genes. Stability analysis of gene expression followed by pairwise variation (Vn/Vn + 1) analysis revealed that PGK1, HSP90AA1 and GYPC were the most stable reference genes and suitable for qRT-PCR normalisation in both HLN and liver tissues. These three genes were validated against FoxP3, IL-10, TGF-β, TNF-α and IL-1β genes in the HLN tissue of sheep vaccinated with Cathepsin L1 from F. hepatica and unvaccinated infected and uninfected controls during early stages of infection. In the liver, the three reference genes were validated against TNF-α and IL-1β during chronic stages of infection with F. hepatica and in uninfected controls. Our study is the first to evaluate and validate sheep reference genes in order to provide tools for monitoring cytokines in Fasciola hepatica infected sheep target organs. Our results present an approach to elucidate the role of different cytokines in F. hepatica vaccinated and infected sheep.
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 | 0.001 | 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".