Interplay Between Non-Coding RNAs and Programmed Cell Death Proteins
Bibliographic record
Abstract
Programmed cell death (PDCD) family of proteins includes at least 12 members, function of seven of them being more investigated. These members are PDCD1, PDCD2, PDCD4, PDCD5, PDCD6, PDCD7 and PDCD10. Consistent with the important roles of these proteins in the regulation of apoptosis, dysregulation of PDCDs is associated with diverse disorders ranging from intervertebral disc degeneration, amyotrophic lateral sclerosis, immune thrombocytopenia, type 1 diabetes, congenital hypothyroidism, Alzheimer's disease to different types of cancers. More recently, the interaction between non-coding RNAs and different members of PDCD family is being discovered. In the current study, we described the functional interactions between PDCDs and two classes of non-coding RNAs, namely microRNAs (miRNAs) and long non-coding RNAs (lncRNAs). miR-21 and miR-183 are two miRNAs whose interactions with PDCDs have been assessed in different contexts. The lncRNAs interaction with PDCDs is mainly assessed in the context of neoplasia indicating the role of MALAT1, MEG3, SNHG14 and LINC00473 in this process.
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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) | 0.001 | 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".