Myelin gene expression across murine post-natal brain development: Validating reliable QPCR methods
Bibliographic record
Abstract
Myelination is essential for proper conduction across all neural networks. Myelination in the central nervous system is performed by glial cells called oligodendrocytes. Mature, myelinating glia develop from progenitor cells through distinct differentiation steps, and gene expression markers have been established that are unique to oligodendrocyte lineage cells. This study aims to establish a reliable RT-qPCR protocol to quantify oligodendrocyte-specific gene expression according to the MIQE guidelines. Primers specific to the progenitor, immature, and myelinating stages of oligodendrocyte differentiation were validated, showing 90-100% efficiency. Reference gene primers were also validated, and their stability was determined to make recommendations for those to use as normalization factors. The expression pattern of oligodendrocyte-specific genes across stages of postnatal development was similar to previously defined RNA-seq profiles in isolated cell types. The validated RT-qPCR assays developed build a framework for future investigation on myelination during development and remyelination in disease.,
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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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
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".