NGF-Dependent and BDNF-Dependent DRG Sensory Neurons Deploy Distinct Degenerative Signaling Mechanisms
Bibliographic record
Abstract
Abstract The nerve growth factor (NGF) and brain-derived neurotrophic factor (BDNF) are trophic factors required by distinct population of sensory neurons during development of the nervous system. Neurons that fail to receive appropriate trophic support are lost during this period of naturally occurring cell death. In the last decade, our understanding of the signaling pathways regulating neuronal death following NGF deprivation has advanced substantially. However, the signaling mechanisms promoting BDNF deprivation-induced sensory neuron degeneration are largely unknown. Using a well-established in vitro culture model of dorsal root ganglion (DRG), we have examined degeneration mechanisms triggered on BDNF withdrawal in sensory neurons. Our results indicate differences and similarities between the molecular signaling pathways behind NGF and BDNF deprivation-induced death. For instance, we observed that the inhibition of Trk receptors (K252a), PKC (Gö6976), protein translation (cycloheximide; CHX), or caspases (zVAD-fmk) provides protection from NGF deprivation-induced death but not from degeneration evoked by BDNF-withdrawal. Interestingly, degeneration of BDNF-dependent sensory neurons requires BAX and appears to rely on reactive oxygen species (ROS) generation rather than caspases to induce degeneration. These results highlight the complexity and divergence of mechanisms regulating developmental sensory neuron death.
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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".