mRNA expression analysis of the hippocampus in a Vervet monkey model of FASD
Bibliographic record
Abstract
The vervet monkey (Chlorocebus aethiops) has proven to be an invaluable tool for researching voluntary alcohol ingestion and the sequelae that can arise from such behaviour. In this study, a vervet monkey model for fetal alcohol spectrum disorder was generated by providing a cohort of alcohol preferring, pregnant dams the option to ingest alcohol between gestational days 90-165 with a corresponding sucrose matched control group. Subsequently, gene expression analysis of the hippocampus was contrasted at 5 months and 2 years using the GeneChip Rhesus Macaque Genome Array in a 2x2 study design which interrogated two independent variables, Age and Alcohol consumption. The analysis identified a global downregulation of expression when interrogating Alcohol as a main effect with a relative balance of upregulation and downregulation using Age as a main effect. Functional annotation of both independent variables was performed with Alcohol generating broad functional annotation clusters which could implicate an epigenetic role in downregulation, while Age reliably produced functional annotation clusters predominantly related to development. Furthermore, our data reveal a novel connection between EFNB1 and FASD which is highly plausible given its role in development as well as its central role in craniofrontal nasal syndrome (CFNS).
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".