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Record W2515293382 · doi:10.1038/cddis.2016.210

Regulatory non-coding RNA: new instruments in the orchestration of cell death

2016· review· en· W2515293382 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCell Death and Disease · 2016
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicroRNA in disease regulation
Canadian institutionsLondon Health Sciences CentreLawson Health Research InstituteWestern University
FundersCanadian Institutes of Health Research
KeywordsNecroptosisBiologymicroRNANon-coding RNARNAProgrammed cell deathComputational biologyCell biologyRNA interferenceGene expressionGeneRegulation of gene expressionLong non-coding RNATranscription (linguistics)GeneticsApoptosis

Abstract

fetched live from OpenAlex

Non-coding RNA (ncRNA) comprises a substantial portion of primary transcripts that are generated by genomic transcription, but are not translated into protein. The possible functions of these once considered 'junk' molecules have incited considerable interest and new insights have emerged. The two major members of ncRNAs, namely micro RNA (miRNA) and long non-coding RNA (lncRNA), have important regulatory roles in gene expression and many important physiological processes, which has recently been extended to programmed cell death. The previous paradigm of programmed cell death only by apoptosis has recently expanded to include modalities of regulated necrosis (RN), and particularly necroptosis. However, most research efforts in this field have been on protein regulators, leaving the role of ncRNAs largely unexplored. In this review, we discuss important findings concerning miRNAs and lncRNAs that modulate apoptosis and RN pathways, as well as the miRNA-lncRNA interactions that affect cell death regulation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.939
Threshold uncertainty score0.810

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.023
GPT teacher head0.274
Teacher spread0.251 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it