Effects of amyloid peptides on cell viability and expression of neuropeptides in cultured rat dorsal root ganglion neurons: a role for free radicals and protein kinase C
Bibliographic record
Abstract
Chronic pain caused by nerve injury and inflammation is more common in the elderly. However, mechanisms underlying this phenomenon are unclear. Higher sensitivity of sensory neurons to free radicals has been suggested as one possibility. The production of free radicals can be induced by various agents, including the highly toxic protein beta-amyloid (A beta), which is found in higher amounts in the brains of Alzheimer's Disease patients. In dorsal root ganglion (DRG) cultures exposed to A beta, we examined cellular toxicity and peptide expression, in particular calcitonin gene-related peptide (CGRP), a peptide which is abundantly expressed by nociceptive afferents and is known to be involved in pain processes. Exposure of cultured rat DRG neurons to A beta(25--35) or A beta(1--40) (10 or 20 microM for 24--96 h) increased trypan blue-stained cells in a concentration- and time-dependent manner, thus, indicating cellular toxicity. These treatments also increased the number of CGRP immunoreactive (IR) neurons while decreasing the number of neuropeptide Y- and galanin-IR neurons. The free radical scavenger, superoxide dismutase, attenuated both the toxicity and neuropeptide changes induced by A beta, thus, suggesting that oxidative stress probably contributes to these effects. Exposure of cultured DRG neurons to A beta also increased the number of protein kinase C alpha (PKC alpha)-IR neurons. The PKC inhibitors, chelerythrine chloride and Gö6976, significantly augmented A beta-induced cellular toxicity while attenuating the increases in CGRP-and PKC alpha-IR cells, supporting the notion of a protective role for PKC in A beta insults. These in vitro data suggest that A beta peptides may, in addition to causing neurotoxicity, regulate neuropeptide expression in primary afferents. This finding could be relevant to the higher incidence of neuropathic pain that occurs with ageing.
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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) | 0.000 | 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 | 0.001 |
| 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".