Heat shock protein 27 is involved in neurite extension and branching of dorsal root ganglion neurons in vitro
Bibliographic record
Abstract
Alteration of the cytoskeleton in response to growth factors and extracellular matrix proteins is necessary for neurite growth. The cytoskeletal components, such as actin and tubulin, can be modified through interaction with other cellular proteins, including the small heat shock protein Hsp27. Our previous work suggested that Hsp27 influences neurite growth, potentially via its phosphorylation state interactions with actin. To investigate further the role of Hsp27 in neurite outgrowth of adult dorsal root ganglion (DRG) neurons, we have both down-regulated endogenous Hsp27 and expressed exogenous Hsp27. Down-regulation of Hsp27 with Hsp27 siRNA resulted in a decrease of neuritic tree length and complexity. In contrast, expression of exogenous Hsp27 in these neurons resulted in an increase in neuritic tree length and branching. Collectively, these results demonstrate that Hsp27 may play a role in neuritic growth via modulation of the actin cytoskeleton.
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 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".