Urine Proteins Identified by Two-Dimensional Differential Gel Electrophoresis Facilitate the Differential Diagnoses of Scrapie
Bibliographic record
Abstract
The difficulty in developing a diagnostic assay for Creutzfeldt - Jakob disease (CJD) and other transmissible spongiform encephalopathies (TSEs) stems in part from the fact that the infectious agent is an aberrantly folded form of an endogenous cellular protein. This precludes the use of the powerful gene based technologies currently applied to the direct detection of other infectious agents. To circumvent this problem our research objective has been to identify a set of proteins exhibiting characteristic differential abundance in response to TSE infection. The objective of the present study was to assess the disease specificity of differentially abundant urine proteins able to identify scrapie infected mice. Two-dimensional differential gel electrophoresis was used to analyze longitudinal collections of urine samples from both prion-infected mice and a transgenic mouse model of Alzheimer's disease. The introduction of fluorescent dyes, that allow multiple samples to be co-resolved and visualized on one two dimensional gel, have increased the accuracy of this methodology for the discovery of robust protein biomarkers for disease. The accuracy of a small panel of differentially abundant proteins to correctly classify an independent naïve sample set was determined. The results demonstrated that at the time of clinical presentation the differential abundance of urine proteins were capable of identifying the prion infected mice with 87% sensitivity and 93% specificity. The identity of the diagnostic differentially abundant proteins was investigated by mass spectrometry.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".