Investigating the Mechanisms of Perinatal Neuron Degeneration, Survival, and their Differentiation from Neural Precursor Cells of the V-SVZ
Bibliographic record
Abstract
For the formation and maintenance of functional neuronal networks, the generation of neurons from their progenitors developmentally as well as their continued survival once the circuitry has been established are both crucial for nervous system homeostasis and plasticity, with disruptions resulting in neuropathologies. For the integrity of this process, first, cellular mechanisms need to temporally orchestrate the correct neuronal fate delineation from multipotent precursors and second, transduced pro-life signals need to suppress degeneration-promoting transcriptional programs to ensure continued survival. In this thesis, I describe a novel 4E-T-based translational regulation mechanism that “fine-tunes” the timing of neurogenesis, coordinating the correct emergence ofinterneurons from transcriptionally pre-fated early postnatal precursors (Chapter 5), in addition to characterizing a novel neuroprotectant promoting survival by suppressing the degeneration of peripheral neurons and potently protecting axonal mitochondria (Chapter 4). Postnatal precursors which possess multi-lineage potency and the ability to renew long-term, are a continuous source of neuronal progeny for tissue formation and repair, and must balance their maintenance through self-renewal, expansion of their pools through proliferation, and the need to generate progeny through differentiation. In Chapter 5 of this thesis, I demonstrate that postnatal precursors are “pre-fated”, expressing neuronal differentiation instructing specifier transcripts, and that a 4E-T-based regulatory mechanism involving translational repression modulates protein synthesis levels of these mRNA targets, controlling timely neurogenesis. Established peripheral neurons and their axonal projections need to then be preserved for the lifetime of the organism to ensure proper circuit function. One goal of the work presented in this thesis is to identify safe-in-man drugs that can block or delay axon degeneration, and to use these drugs to characterize new degeneration pathways. To this end, the work described in Chapter 4 describes and identifies the multikinase inhibitor Foretinib as being protective in sympathetic, sensory and motor neurons across multiple degeneration paradigms. Thus, my thesis traces the trajectory of neurons in two main aspects of neurobiology: from onset of fate commitment and appropriate neuronal lineage acquisition, to maintenance and protection in maturity once neurons integrate into circuits, highlighting the consequences to the organism in the case of aberration in either process.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".