MétaCan
Menu
Back to cohort
Record W3177613958 · doi:10.3389/fonc.2021.681576

Non-Coding RNAs in Invadopodia: New Insights Into Cancer Metastasis

2021· review· en· W3177613958 on OpenAlexafffund
Feiya Li, Burton B. Yang

Bibliographic record

VenueFrontiers in Oncology · 2021
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Research and Splicing
Canadian institutionsUniversity of TorontoSunnybrook Health Science Centre
FundersCanadian Institutes of Health Research
KeywordsInvadopodiaMetastasisCarcinogenesisContext (archaeology)CancerBiologyCancer researchCancer metastasisMedicineComputational biologyBioinformaticsGenetics

Abstract

fetched live from OpenAlex

Invadopodia are actin-rich structures and their formation is implicated in cancer invasion and metastasis. Growing evidence has shown that noncoding RNAs (ncRNAs) play important roles in pathological conditions, including tumorigenesis and metastasis. Although this is still a new area of research, ncRNAs appear to be promising biomarkers and therapeutic targets for cancer metastasis. However, understanding the roles of ncRNAs in invadopodia is still in the early stages and far from clinical application. In this mini-review, we summarize the roles of ncRNAs in invadopodia functions and discuss them in a therapeutic context. The current challenges and gaps in this field are also raised, and we provide some open questions to facilitate new ideas in targeting invadopodia in anticancer therapy.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.002

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.

Opus teacher head0.039
GPT teacher head0.377
Teacher spread0.338 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations3
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueFrontiers in OncologySame topicRNA Research and SplicingFrench-language works237,207