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Record W1999473606 · doi:10.1515/bc.2008.068

microRNAs: a new frontier in kallikrein research

2008· review· en· W1999473606 on OpenAlex
George M. Yousef

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.

Bibliographic record

VenueBiological Chemistry · 2008
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicroRNA in disease regulation
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsKallikreinmicroRNABiologyProteasesGeneIn silicoComputational biologyGene expressionRegulation of gene expressionGeneticsEnzymeBiochemistry

Abstract

fetched live from OpenAlex

microRNAs (miRNAs) are a recently discovered class of small non-coding RNAs that regulate gene expression. Rapidly accumulating evidence has revealed that miRNAs are associated with cancer. The human tissue kallikrein gene family is the largest contiguous family of proteases in the human genome, containing 15 genes. Many kallikreins have been reported as potential tumor markers. In this review, recent bioinformatics and experimental evidence is presented indicating that kallikreins are potential miRNA targets. The available experimental approaches to investigate these interactions and the potential diagnostic and therapeutic applications are also discussed. miRNAs represent a possible regulatory mechanism for controlling kallikrein expression at the post-transcriptional level. Many miRNAs were predicted to target kallikreins and a single miRNA can target more than one kallikrein. Recent evidence suggests that miRNAs can also exert 'quantitative' control of kallikreins by utilizing multiple targeting sites in the kallikrein mRNA. More research is needed to experimentally verify the in silico predictions and to investigate the possible role in tumor initiation and/or progression.

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 categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.805
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0020.001
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 head0.131
GPT teacher head0.384
Teacher spread0.253 · 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