Proteasome Inhibitor Lactacystin Induces Cholinergic Degeneration
Bibliographic record
Abstract
OBJECTIVE: Ubiquitin proteasome system dysfunction is believed to play an important role in the development of Parkinson's disease (PD), and almost all studies till now have mainly focused on the susceptibility of dopaminergic neurons to proteasome inhibition. However, in fact, there are many other types of neurons such as cholinergic ones involved in PD. In our present study, we attempt to figure out what effect the failure of ubiquitin proteasome function would execute on cholinergic cells in culture. METHODS: We treated cholinergic cells in culture with various doses of lactacystin. Then MTT assay was used to evaluate the cellular viability and the AnnexinV-PI method was used to detect apoptosis. Both cellular soluble and insoluble polyubiquitinated proteins were detected by western blot. Furthermore, the mitochondrial membrane potential was analyzed using JC-1 and the intracellular production of reactive oxygen species (ROS) was determined using the fluorescent probe CM-H2DCFDA. RESULTS: We found that low doses of lactacystin were enough to induce significant apoptotic cell death, disturb the mitochondrial membrane potential, and cause oxidative stress. We also found that the amounts of polyubiquitinated proteins dramatically increased with high doses, although the loss of cells did not increase accordingly. CONCLUSIONS: Our results suggest that cholinergic cells are sensitive to ubiquitin proteasome system dysfunction, which exerts its toxic effect by causing mitochondrial dysfunction and subsequent oxidative stress, not through polyubiquitinated proteins accumulation.
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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) | 0.001 | 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) | 0.002 | 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".