Induction of heat shock proteins in cerebral cortical cultures by celastrol
Bibliographic record
Abstract
Alzheimer's disease, Parkinson's disease and amyotrophic lateral sclerosis (ALS) are 'protein misfolding disorders' of the mature nervous system that are characterized by the accumulation of protein aggregates and selective cell loss. Different brain regions are impacted, with Alzheimer's affecting cells in the cerebral cortex, Parkinson's targeting dopaminergic cells in the substantia nigra and ALS causing degeneration of cells in the spinal cord. These diseases differ widely in frequency in the human population. Alzheimer's is more frequent than Parkinson's and ALS. Heat shock proteins (Hsps) are 'protein repair agents' that provide a line of defense against misfolded, aggregation-prone proteins. We have suggested that differing levels of constitutively expressed Hsps (Hsc70 and Hsp27) in neural cell populations confer a variable buffering capacity against 'protein misfolding disorders' that correlates with the relative frequencies of these neurodegenerative diseases. The high relative frequency of Alzheimer's may due to low levels of Hsc70 and Hsp27 in affected cell populations that results in a reduced defense capacity against protein misfolding. Here, we demonstrate that celastrol, but not classical heat shock treatment, is effective in inducing a set of neuroprotective Hsps in cultures derived from cerebral cortices, including Hsp70, Hsp27 and Hsp32. This set of Hsps is induced by celastrol at 'days in vitro' (DIV) 13 when cultured cortical cells reached maturity. The inducibility of a set of neuroprotective Hsps in mature cortical cultures at DIV13 suggests that celastrol is a potential agent to counter Alzheimer's disease, a neurodegenerative 'protein misfolding disorder' of the adult brain that targets cells in the cerebral cortex.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".