Gene ontology analysis of expanded porcine blastocysts from gilts fed organic or inorganic selenium combined with pyridoxine
Bibliographic record
Abstract
Gene ontology analysis using the microarray database generated in a previous study by this laboratory was used to further evaluate how maternal dietary supplementation with pyridoxine combined with different sources of selenium (Se) affected global gene expression of expanded porcine blastocysts. Data were generated from 18 gilts randomly assigned to one of three experimental diets ( n = 6 per treatment): i) basal diet without supplemental Se or pyridoxine (CONT); ii) CONT + 0.3 mg/kg of Na-selenite and 10 mg/kg of HCl-pyridoxine (MSeB 6 10); and iii) CONT + 0.3 mg/kg of Se-enriched yeast and 10 mg/kg of HCl-pyridoxine (OSeB 6 10). All gilts were inseminated at their fifth post-pubertal estrus and euthanized 5 days later for embryo harvesting. Differential gene expression between MSeB 6 10 vs CONT, OSeB 6 10 vs CONT and OSeB 6 10 vs MSeB 6 10 was performed using a porcine embryo-specific microarray. There were 559, 2458, and 1547 differentially expressed genes for MSeB 6 10 vs CONT, OSeB 6 10 vs CONT and OSeB 6 10 vs MSeB 6 10, respectively. MSeB 6 10 vs CONT stimulated 13 biological processes with a strict effect on RNA binding and translation initiation. OSeB 6 10 vs CONT and OSeB 6 10 vs MSeB 6 10 impacted 188 and 66 biological processes, respectively, with very similar effects on genome stability, ceramide biosynthesis, protein trafficking and epigenetic events. The stimulation of genes related with these processes was confirmed by quantitative real-time RT-PCR. Gene expression of embryos from OSeB 6 10 supplemented gilts was more impacted than those from MSeB 6 10 supplemented gilts. Whereas maternal OSeB 6 10 supplementation influenced crucial aspects of embryo development, maternal MSeB 6 10 supplementation was restricted to binding activity.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".