Pre- and Post- Morris Water Maze Learning Comparison Expression of Transcription Factors NF-kB, CREB, and Egr-2
Bibliographic record
Abstract
The interactions between transcription factors (TF) and expressed genes are essential steps in memory formation. Some believed to be involved TFs in memory formation include CREB, NF-κB, and Egr-2. We hypothesized that there would be a difference among these TF expression levels, before and after learning, which might clarify other clues in memory formation. Twenty male CD1 mice, 29 to 32 days old, were selected. Group 1, 10 mice, was assigned as the control. Group 2 (10 mice) underwent 9 consecutive days of Morris Water maze (MWM) behavioral memory testing for spatial learning. Search strategies, escape latency, time spent in the target quadrant, and number of attempts passing the missing platform were measured. To evaluate the expression levels of CREB, NF-κB, and Egr-2 before vs after learning, the control group and the MWM group were killed at the end of MWM. Hippocampi were separated, and Western blots were done on the prepared protein samples. The escape latency was decreased toward the end of the acquisition phase, indicating mean improvement in the animals’ performance. Mice spent more time in the target quadrant in the first and third days of the retention phase. The number of passes over the missing platform had a peak on the first day of the retention phase. The swim pattern toward the end of the MWM showed that the mice used spatial strategies to learn the task. NF-κB, and CREB were expressed significantly higher in control vs trained mice (MWM) (P = .0205 and P = .0009). There was a trend of expression of the Egr-2 in MWM group vs the control group (P = .0544). We found in the CD1 mice a different level of expression of CREB, NF-κB, and Egr-2 following MWM compared with other strains. We assumed that other pathways might be involved in learning memory in a high stress test (MWM). Key words: Transcription factors, CREB, NF-κB, Egr-2, Morris Water maze, short-term memory, CD1 mouse.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".