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Record W2241690807 · doi:10.1002/ppul.22896

Symposium Session Summaries

2013· article· en· W2241690807 on OpenAlexaff
Shyam Ramachandran, Philip H. Karp, Samantha R. Osterhaus, Mark A. Behlke, Michael J. Welsh, Paul B. McCray, Daniela Rotin, Agata M. Trzcińska-Daneluti, Dana Carroll, Mitchell L. Drumm, Leigh Henderson, Shuyu Hao, Ilya Bederman, Jean Eastman, Aura Perez, Craig A. Hodges, Jeffrey M. Beekman

Bibliographic record

VenuePediatric Pulmonology · 2013
Typearticle
Languageen
FieldMedicine
TopicCystic Fibrosis Research Advances
Canadian institutionsHospital for Sick Children
FundersNational Institutes of HealthGilead Sciences
KeywordsSession (web analytics)CitationMedicineSalt lakeLibrary scienceConventionWorld Wide WebComputer sciencePolitical scienceLaw

Abstract

fetched live from OpenAlex

The expression of functional proteins requires multiple steps including gene transcription and post-translational processing. MicroRNAs (miRNA) can regulate individual stages of these processes. We hypothesized that events in CFTR biogenesis are regulated in part by miRNA. We profiled miRNA expression in human airway epithelia to identify candidates for additional studies. MiRNA-138, which has highly conserved target sequences in the transcriptional regulatory gene product SIN3A, emerged as a candidate of interest. SIN3A is known to interact with the DNA binding protein CTCF and serve in the recruitment of transcriptional regulatory proteins to the promoter regions of many genes, including CFTR. We found that miRNA-138 regulates CFTR expression through its interactions with SIN3A. The treatment of human airway epithelia with a miRNA-138 mimic decreased SIN3A and increased CFTR mRNA and also increased CFTR abundance and transepithelial Cl -permeability independently of elevated mRNA levels. A miRNA-138 anti-miR had the opposite effects.

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 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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.054
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.002

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 head0.010
GPT teacher head0.277
Teacher spread0.267 · 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; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

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

Citations2
Published2013
Admission routes1
Has abstractyes

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