Expression Patterns of Retinoblastoma Protein in Parkinson Disease
Bibliographic record
Abstract
Cellular mechanisms implicated in Parkinson disease (PD) include oxidative stress, inflammatory response, excess dopamine, DNA damage, and loss of trophic support. These stimuli have been observed to induce changes in cell cycle proteins in several cell types. One of the key regulators of cell cycle progression is the retinoblastoma protein (pRb); therefore, we assessed the staining for pRb and its inactive hyperphosphorylated isoform, ppRb, in autopsy tissue from patients with PD. In PD we found abundant pRb staining in neuronal cytoplasm of the substantia nigra, mid-frontal cortex, and hippocampus by immunohistochemistry. In controls, pRb weakly stained nucleoli of neurons in the substantia nigra and exhibited no detectable staining in mid-frontal cortex and hippocampus. Staining for ppRb resulted in a shift from weak cytoplasmic staining in neurons from control cases to strong nuclear staining in PD cases, especially within the substantia nigra, mid-frontal cortex, and hippocampus. In the substantia nigra, ppRb also co-localized to Lewy bodies, which are a pathologic feature of PD. Lewy bodies are also found in diffuse Lewy body disease (DLBD) that do not consistently exhibit changes in pRb or ppRb. These results indicate that there are changes in pRb and its inactive phospho-isoform in neurons responding to neurodegenerative stimuli associated with PD.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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".