Disease-associated oligodendrocyte responses across neurodegenerative diseases
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Oligodendrocyte dysfunction has been implicated in the pathogenesis of neurodegenerative diseases, so understanding oligodendrocyte activation states would shed light on disease processes. We identify three distinct activation states of oligodendrocytes from single-cell RNA sequencing (RNA-seq) of mouse models of Alzheimer's disease (AD) and multiple sclerosis (MS): DA1 (disease-associated1, associated with immunogenic genes), DA2 (disease-associated2, associated with genes influencing survival), and IFN (associated with interferon response genes). Spatial analysis of disease-associated oligodendrocytes (DAOs) in the cuprizone model reveals that DA1 and DA2 are established outside of the lesion area during demyelination and that DA1 repopulates the lesion during remyelination. Independent meta-analysis of human single-nucleus RNA-seq datasets reveals that the transcriptional responses of MS oligodendrocytes share features with mouse models. In contrast, the oligodendrocyte activation signature observed in human AD is largely distinct from those observed in mice. This catalog of oligodendrocyte activation states (http://research-pub.gene.com/OligoLandscape/) will be important to understand disease progression and develop therapeutic interventions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 it