Newly-Discovered Neural Features Expand the Pathobiological Knowledge of Blastic Plasmacytoid Dendritic Cell Neoplasm
Bibliographic record
Abstract
Blastic plasmacytoid dendritic cell neoplasm (BPDCN) is a rare and highly aggressive hematologic malignancy originating from plasmacytoid dendritic cells (pDCs). The microRNA expression profile of BPDCN was compared to that of normal pDCs and the impact of miRNA dysregulation on the BPDCN transcriptional program was assessed. MiRNA and gene expression profiling data were integrated to obtain the BPDCN miRNA-regulatory network. The biological process mainly dysregulated by this network was predicted to be neurogenesis, a phenomenon raising growing interest in solid tumors. Neurogenesis was explored in BPDCN by querying different molecular sources (RNA sequencing, Chromatin immunoprecipitation-sequencing, and immunohistochemistry). It was shown that BPDCN cells upregulated neural mitogen genes possibly critical for tumor dissemination, expressed neuronal progenitor markers involved in cell migration, exchanged acetylcholine neurotransmitter, and overexpressed multiple neural receptors that may stimulate tumor proliferation, migration and cross-talk with the nervous system. Most neural genes upregulated in BPDCN are currently investigated as therapeutic targets.
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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 | 0.001 | 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".