Devlopment of experimental tools to analyze the function of the TGF-beta-activated Kinase (TAK1) in neurons «in vivo and in vitro»
Bibliographic record
Abstract
The development of the nervous system requires the spatial and temporally controlled elimination of supernumerary neurons and their precursors. A balance between pro-survival and pro-death signals tightly regulates this programmed cell death, termed apoptosis. These signals can be executed by the c-Jun amino-terminal kinase (JNK) and nuclear factor-kappaB (NF-kappaB) pathways, which either inhibit or activate the apoptotic machinery. An important activator of both JNK and NF-?B in the immune system is the TGF-beta-activated kinase (TAK1). To test whether TAK1 plays a similar role in the developing nervous system, we developed a genetic strategy to generate embryos with a neuron-specific deletion in Tak1. We also developed molecular tools to suppress TAK1 function in neurons in vitro and in vivo. By immunohistochemistry (IHC), we determined that TAK1 is expressed in all neuronal layers of the postnatal day (P)9 cerebellum. We also tested and optimized IHC protocols on paraffin-embedded embryos for different antibodies that could be useful for the analysis of the nervous system of mutant embryos.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.020 | 0.008 |
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".