Mouse G-protein gamma3 expression in the developing CNS and neural crest cell derivatives
Bibliographic record
Abstract
Heterotrimeric G-protein signaling, involving alpha, beta and gamma subunits, plays a number of roles in differentiation and development. Individual gamma subunits interact with a beta subunit and as a heterodimer, is responsible for modulating many G protein-mediated cellular responses. The 12 gamma subunits in mammals have highly variable distribution and expression patterns in adult tissues. gamma3 is abundantly and widely expressed in the brain and when its expression is knocked-out, the mice show increased susceptibility to seizures, reduced body weights and decreased adiposity compared to the wild-type littermates (Schwindinger et al., 2004). Recent evidence has shown the Gng3 gene being strongly induced in activated CD4+ T-cells (Dubeykovskiy et al., 2006) and its involvement in the developing mammalian enteric nervous system (Heanue and Pachnis, 2006). Given this diversity in expression and interest in finding models of human disease, and to extend our previous investigation with zebrafish gamma3 (Kelly et al., 2001), we undertook an analysis to report the temporal and spatial expression patterns of gamma3 mRNA during mouse embryogenesis. Analysis reveals that gamma3 transcripts were first expressed in mid-late embryonic stages. Specifically, signals were predominant in the CNS and in neural crest cell derivatives including but not limited to the trigeminal and dorsal root (spinal) ganglia, and in cells of the adrenal medulla. These data indicate that G protein coupled signaling involving gamma3 participates in a number of physiological roles, not only in the CNS, but also in numerous cells derived from the neural crest.
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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 | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".