The small heat shock protein Hsp27 protects cortical neurons against the toxic effects of β‐amyloid peptide
Bibliographic record
Abstract
Neurofibrillary tangles and amyloid plaques are considered to be hallmarks of Alzheimer's disease (AD), and the toxic effects of amyloid-beta peptide (A beta) lead to activation of stress-related signaling and neuronal loss. The small heat shock protein Hsp27 is reported to be increased in AD brains and to accumulate in plaques, but whether this represents a potentially protective response to stress or is part of the disease process is not known. We hypothesized that increased expression of Hsp27 in neurons can promote neuronal survival and stabilize the cytoskeleton in the face of A beta exposure. By using neonatal rat cortical neurons, we investigated the potential role of Hsp27 in neuronal cultures in the presence or absence of A beta. We initially tested whether a heat stress (HS) would be sufficient to induce endogenous Hsp27 expression. HS not only did not result in neuronal Hsp27 up-regulation but made the cells more vulnerable to A beta exposure. We then used cDNA transfection to overexpress EGFP-Hsp27 (or the empty vector) in cultures and then assessed neuronal survival and growth. Transfected neurons appeared healthy and had robust neuritic outgrowth. A beta treatment induced significant cell death by 48-72 hr in nontransfected and empty-vector-expressing cultures. In contrast, cultures expressing Hsp27 did not display significant apoptosis. Our results show that Hsp27-expressing neurons were selectively protected against the deleterious effects of A beta treatment; neuronal degeneration was prevented, and A beta-induced alterations in mitochondrial size were attenuated. We also demonstrate that Hsp27 expression can enhance neurite growth in cortical neurons compared with control vector-transfected cells. Overall, our study provides new evidence that Hsp27 can provide a protective influence in primary cortical neurons in the face of toxic concentrations of amyloid.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".