Human and rat brain lipofuscin proteome
Bibliographic record
Abstract
The accumulation of an autofluorescent pigment called lipofuscin in neurons is an invariable hallmark of brain aging. So far, this material has been considered to be waste material without particular relevance for cellular pathology. However, two lines of evidence argue that lipofuscin may play a yet unidentified role for pathological cellular functions: (i) Genetic forms of premature accumulation of similar autofluorescent material in neuronal ceroid lipofuscinosis indicate a direct disease-associated link to lipofuscin; (ii) Retinal pigment epithelium cell lipofuscin is mechanistically linked to age-associated macular degeneration. Here, we purified autofluorescent material from the temporal and hippocampal cortices of three different human individuals by a two-step ultracentrifugation on sucrose gradients. For human brain lipofuscin, we could identify a common set of 49 (among > 200 total) proteins that are mainly derived from mitochondria, cytoskeleton, and cell membrane. This brain lipofuscin proteome was validated in an interspecies comparison with whole brain rat lipofuscin (total > 300 proteins), purified by the same procedure, yielding an overlap of 32 proteins (64%) between lipofuscins of both species. Our study is the first to characterize human and rat brain lipofuscin and identifies high homology, pointing to common cellular pathomechanisms of age-associated lipofuscin accumulation despite the huge (40-fold) difference in the lifespan of these species. Our identification of these distinct proteins will now allow research in disturbed molecular pathways during age-associated dysfunctional lysosomal degradation.
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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 | 0.001 | 0.001 |
| 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) | 0.002 | 0.001 |
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".