Transcriptional Modulation in a Leukocyte-Depleted Splenic Cell Population During Prion Disease
Bibliographic record
Abstract
Prion replication in the periphery precedes neuroinvasion in many experimental rodent scrapie models, and in natural sheep scrapie and chronic wasting disease (CWD) in cervids. Prions propagate in the germinal centers of secondary lymphoid organs and are strongly associated with follicular dendritic cells (FDC) and possibly circulating dendritic cells and macrophages. Given the importance of lymphoid organs in prion disease transmission and pathogenesis, gene expression studies may reveal host factors or biological pathways related to prion replication and accumulation. A procedure was developed to enrich for FDC, dendritic cells, and macrophages prior to the investigation of transcriptional alterations in murine splenic cells during prion pathogenesis. In total, 1753 transcripts exhibited fold changes greater than three (false discovery rates less than 2%) in this population isolated from spleens of prion-infected versus uninfected mice. The gene for the small leucine-rich proteoglycan decorin (DCN) was one of the genes most overexpressed in infected mice, and the splenic protein levels mirrored this in mice infected with scrapie as well as bovine spongiform encephalopathy (BSE) and variant Creutzfeldt-Jakob disease (vCJD). A number of groups of functionally related genes were also significantly decreased in infected spleens. These included genes related to iron metabolism and homeostasis, pathways that have also been implicated in prion pathogenesis in the brain. These gene expression alterations provide insights into the molecular mechanisms underlying prion disease pathogenesis and may serve as a pool of potential surrogate markers for the early detection and diagnosis of some prion diseases.
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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 | 0.000 | 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".