Identification of <i>BERP</i> (brain-expressed RING finger protein) as a p53 target gene that modulates seizure susceptibility through interacting with GABA <sub>A</sub> receptors
Bibliographic record
Abstract
p53 is a central player in responses to cellular stresses and a major tumor suppressor. The identification of unique molecules within the p53 signaling network can reveal functions of this important transcription factor. Here, we show that brain-expressed RING finger protein (BERP) is a gene whose expression is up-regulated in a p53-dependent manner in human cells and in mice. We generated BERP-deficient mice by gene targeting and demonstrated that they exhibit increased resistance to pentylenetetrazol-induced seizures. Electrophysiological and biochemical studies of cultured cortical neurons of BERP-deficient mice showed a decrease in the amplitude of GABA(A) receptor (GABA(A)R)-mediated miniature inhibitory postsynaptic currents as well as reduced surface protein expression of GABA(A)Rs containing the gamma2-subunit. However, BERP deficiency did not decrease GABA(A)Rgamma2 mRNA levels, raising the possibility that BERP may act at a posttranscriptional level to regulate the intracellular trafficking of GABA(A)Rs. Our results indicate that BERP is a unique p53-regulated gene and suggest a role for p53 within the central nervous system.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".