Double dissociation between the involvement of Gadd45α and Gadd45β/γ in the perirhinal cortex and hippocampus of male rats for object memory
Bibliographic record
Abstract
• Conflicting findings exist surrounding Gadd45α in object recognition memory. • siRNAs permitted regional evaluation of the Gadd45 family during consolidation. • Gadd45α was required in PRh; Gadd45α mRNA increased in PRh following learning. • Gadd45β/γ was required in HPC; Gadd45β mRNA increased in HPC following learning. • Results resolve conflict and demonstrate regional dissociations in Gadd45 necessity. The GADD45 family of proteins (GADD45α, GADD45β, GADD45γ) has been implicated in DNA demethylation and long-term memory formation. Recently, conflicting findings have emerged surrounding the involvement of Gadd45α in various object recognition tasks. These discrepancies could be due to differences in Gadd45α KO mouse models and/or task parameters. Further, the use of brain-wide KO models precludes our understanding of Gadd45α in specific brain regions such as the hippocampus (HPC), which processes the spatial location of objects, or the perirhinal cortex (PRh), which has a larger role in object identity memory. Here, using a single object recognition task reliant on both the PRh and HPC – the object-in-place (OiP) task – we show that siRNA knockdown of Gadd45β or Gadd45γ, but not Gadd45α, within the dorsal HPC (dHPC) impaired long-term, but not short-term, OiP memory. Further, OiP learning induced an upregulation of Gadd45β mRNA in the dentate gyrus subregion of the dHPC. Within the PRh, siRNA knockdown of Gadd45α, but not Gadd45β or Gadd45γ, impaired long-term, but not short-term, OiP memory, with a concomitant increase in learning induced PRh Gadd45α mRNA. These results clarify previous discrepancies in the literature by demonstrating a clear necessity for Gadd45α in the PRh, but not the dHPC, for the consolidation of long-term object memories.
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 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 | 0.001 |
| 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 | 0.001 |
| Research integrity | 0.000 | 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".