The gamma-Protocadherins regulate the survival of GABAergic interneurons during developmentally-regulated cell death
Bibliographic record
Abstract
SUMMARY Inhibitory interneurons integrate into developing circuits in specific ratios and distributions. In the cortex, the formation of inhibitory networks occurs concurrently with the apoptotic elimination of a third of GABAergic interneurons. The molecular mechanisms that select GABAergic interneurons to survive or die are unknown. Here we report that the clustered Protocadherins regulate GABAergic cell survival in the developing brain. Deletion of the Pcdh-gamma genes (Pcdhgs) from GABAergic neurons in mice causes a severe loss of inhibitory neurons in multiple brain regions and results in motor deficits and seizure activities. By focusing on the neocortex and cerebellar cortex, we demonstrate that GABAergic interneuron loss results from elevated apoptosis during the postnatal wave of Bax- dependent programmed cell death. Pro-survival AKT signals are reduced in Pcdhg- deficient interneurons, diminishing the intrinsic capacity of interneurons to compete and incorporate into developing networks. We propose that the Pcdhgs mediate selective GABAergic interneuron survival to contribute to the formation of balanced inhibitory networks.
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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".