Examining Ubiquitinated Protein Aggregates in Tissue Sections
Bibliographic record
Abstract
In the cell, the binding of ubiquitin to abnormal or misfolded proteins marks them for degradation by the proteasome or lysosome via autophagy. Ubiquitinated-protein aggregates form when an increase in protein misfolding exceeds the degradation capacity of the cell. Many cellular stresses can cause an increase in the amount of ubiquitinated misfolded protein and failure to eliminate these proteins can disrupt cellular homeostasis and cause cellular toxicity. Ubiquitinated-protein aggregates accumulate in the cytosol and can be detected in tissues of patients with a variety of diseases, including Alzheimer's, Parkinson's, and Huntington's. Using a diabetic rat model, we have shown that ubiquitinated-protein aggregates form in pancreatic beta cells during diabetes-induced oxidative stress. Aggregates were also evident in the hippocampus, kidney, and liver of these animals. Our detailed protocol is provided here. Mounted tissue sections were first deparaffinized, then boiled in sodium citrate buffer to expose the antigen, followed by a specific staining procedure that allows for detection of ubiquitinated-protein aggregates. The ability to visualize ubiquitinated-protein aggregates in tissue sections can provide further understanding of the pathobiology of diseases associated with misfolded protein.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".