Bibliographic record
Abstract
Manipulation of the cellular stress response offers strategies to protect brain cells from damage induced by ischemia and neurodegenerative diseases. Overexpression of Hsp70 reduced ischemic injury in the mammalian brain. Investigation of the domains within Hsp70 that confers ischemic neuroprotection revealed the importance of the carboxyl-terminal domain. Arimoclomol, a coinducer of heat shock proteins, delayed progression of amyotrophic lateral sclerosis (ALS) in a mouse model in which motor neurons in the spinal cord and motor cortex degenerate. Celastrol, a promising candidate as an agent to counter neurodegenerative diseases, induced expression of a set of Hsps in differentiated neurons grown in tissue culture. Heat shock "preconditioning" protected the nervous system at the functional level of the synapse and selective overexpression of Hsp70 enhanced the level of synaptic protection. Following hyperthermia, constitutively expressed Hsc70 increased in synapse-rich areas of the brain where it associates with Hsp40 to form a complex that can refold denatured proteins. Stress tolerance in neurons is not solely dependent on their own Hsps but can be supplemented by Hsps from adjacent glial cells. Hence, application of exogenous Hsps at neural injury sites is an effective strategy to maintain neuronal viability.
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 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".