Live Cell Imaging of Neuronal Growth Cone Motility and Guidance In Vitro
Bibliographic record
Abstract
The neuronal growth cone, a highly motile structure at the tip of neuronal processes, is an excellent model system for studying directional cell movements. While biochemical and genetic approaches unveiled molecular interactions between ligand, receptor, signaling, and cytoskeleton-associated proteins controlling axonal growth and guidance, in vitro live cell imaging has emerged as a crucial approach for dissecting cellular mechanisms of growth cone motility and guidance. Important insights into these mechanisms have been gained from studies using the large growth cones elaborated by Aplysia californica neurons, an outstanding model system for live cell imaging for a number of reasons. Identified neurons can be isolated and imaged at room temperature. Aplysia growth cones are five to ten times larger than growth cones from other species, making them suitable for quantitative high-resolution imaging of cytoskeletal protein dynamics and biophysical approaches. Lastly, protein, RNA, fluorescent probes, and small molecules can be microinjected into the neuronal cell body for localization and functional studies. This chapter describes culturing of Aplysia bag cell neurons, live cell imaging of neuronal growth cones using differential interference contrast and fluorescent speckle microscopy as well as the restrained bead interaction assay to induce adhesion-mediated growth cone guidance in vitro.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".