FGF-1 and FGF-2 Require the Cytosolic Chaperone Hsp90 for Translocation into the Cytosol and the Cell Nucleus
Bibliographic record
Abstract
Similarly to many protein toxins, the growth factors fibroblast growth factor 1 (FGF-1) and FGF-2 translocate from endosomes into the cytosol. It was recently found that certain toxins are dependent on cytosolic Hsp90 for efficient translocation across the endosomal membrane. We therefore investigated the requirement for Hsp90 in FGF translocation. We found that low concentrations of the specific Hsp90 inhibitors, geldanamycin and radicicol, completely blocked the translocation of FGF-1 and FGF-2 to the cytosol and the nucleus. The drugs did not interfere with the initial binding of FGF-1 to the growth factor receptors at the cell-surface or with the subsequent internalization of the growth factors into endosomes. The activation of known signaling cascades downstream of the growth factor receptors was also not affected by the drugs. The data indicate that the drugs block translocation from endosomes to the cytosol implying that Hsp90 is required for translocation of FGF-1 and FGF-2 across the endosomal membrane.
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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".