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Record W2012759189 · doi:10.1155/2013/137509

Expression of the H19 Oncofetal Gene in Premalignant Lesions of Cervical Cancer: A Potential Targeting Approach for Development of Nonsurgical Treatment of High-Risk Lesions

2013· article· en· W2012759189 on OpenAlexaff
Tomer Feigenberg, Ofer N. Gofrit, Galina Pizov, Avraham Hochberg, Abraham Benshushan

Bibliographic record

VenueISRN Obstetrics and Gynecology · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer-related gene regulation
Canadian institutionsPrincess Margaret Cancer CentreUniversity of Toronto
Fundersnot available
KeywordsOncofetal antigenCervical cancerCancerGenePremalignant lesionCancer researchBiologyGene expressionMedicinePathologyGeneticsImmunotherapy

Abstract

fetched live from OpenAlex

Background. Recent data suggest a role for H19 gene in promoting cancer transformation and progression. Cervical cancer, progresses from high-grade lesions (CIN3). At present, it is unclear if CIN lesions express H19. Objectives. To determine H19 expression in patient samples of CIN3 as well as the ability of a construct in which the promoter from the H19 gene drives expression of the diphtheria toxin A chain (DTA) to inhibit cervical cancer cell growth in vitro. Methods. H19 transcript levels were evaluated on 10 biopsies of CIN3 using in situ hybridization. PCR was used to examine H19 expression in cervical cancer cell lines and in two samples from a patient with cervical carcinoma. Cell lines were transfected with H19-DTA to determine its impact on cell number. Results. H19 gene was expressed in the area of CIN3 in 9 out of 10 samples. RT-PCR indicated expression of H19 in cervical cancer samples and in one of the three cell lines examined. Transfection of all cell lines with H19-DTA vector resulted in inhibited cell growth. Conclusions. H19 is expressed in the majority of CIN3 samples. These results suggest that most CIN3 lesions could be targeted by H19-DTA. Further in vivo preclinical studies are thus warranted.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.082
Threshold uncertainty score0.339

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 head0.013
GPT teacher head0.243
Teacher spread0.231 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations15
Published2013
Admission routes1
Has abstractyes

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