MicroRNAs and exosomes: Small molecules with big actions in multiple myeloma pathogenesis
Bibliographic record
Abstract
Multiple myeloma (MM), an incurable hematologic malignancy of plasma cells increasing in the bone marrow (BM), has a complex microenvironment made to support proliferation, survival, and drug resistance of tumor cells. MicroRNAs (miRNAs), short non-coding RNAs regulating genes expression at posttranscriptional level, have been indicated to be functionally deregulated or abnormally expressed in MM cells. Moreover, by means of miRNAs, tumor microenvironment also modulates the function of MM cells. Consistently, it has been demonstrated that miRNA levels regulation impairs their interaction with the microenvironment of BM as well as create considerable antitumor feature even capable of overcoming the protective BM milieu. Communication between cancer stromal cells and cancer cells is a key factor in tumor progression. Finding out this interaction is important to develop effective approaches that reverse bone diseases. Exosomes, nano-vehicles having crucial roles in cell-to-cell communication, through targeting their cargos (i.e., miRNAs, mRNAs, DNAs, and proteins), are implicated in MM pathogenesis.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".