Molecular Crosstalk between Chromatin Remodeling and Tumor Microenvironment in Multiple Myeloma
Bibliographic record
Abstract
Multiple myeloma (MM) is a complex disease driven by numerous genetic and epigenetic alterations that are acquired over time. Despite recent progress in the understanding of MM pathobiology and the availability of innovative drugs, which have pronounced clinical outcome, this malignancy eventually progresses to a drug-resistant lethal stage and, thus, novel therapeutic drugs/models always play an important role in effective management of MM. Modulation of tumor microenvironment is one of the hallmarks of cancer biology, including MM, which affects the myeloma genomic architecture and disease progression subtly through chromatin modifications. The bone marrow niche has a prime role in progression, survival, and drug resistance of multiple myeloma cells. Therefore, it is important to develop means for targeting the ecosystem between multiple myeloma bone marrow microenvironment and chromatin remodeling. Extensive gene expression profile analysis has indeed provided the framework for new risk stratification of MM patients and identifying novel molecular targets and therapeutics. However, key tumor microenvironment factors/immune cells and their interactions with chromatin remodeling complex proteins that drive MM cell growth and progression remain grossly undefined.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".