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Record W2004223380 · doi:10.1042/bj20140066

Hypoxia-inducible regulation of placental BOK expression

2014· article· en· W2004223380 on OpenAlexafffund
Daochun Luo, Isabella Caniggia, Martin Post

Bibliographic record

VenueBiochemical Journal · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicroRNA in disease regulation
Canadian institutionsLunenfeld-Tanenbaum Research InstituteUniversity of TorontoMount Sinai HospitalHospital for Sick Children
FundersCanadian Institutes of Health Research
KeywordsBiologyGene knockdownAntisense RNACell biologyIntronTrophoblastApoptosisMolecular biologyGeneHypoxia (environmental)Gene expressionCancer researchPlacentaGeneticsChemistryFetus

Abstract

fetched live from OpenAlex

BOK (BCL-2-related ovarian killer) is a member of the pro-apoptotic BCL-2 family that is highly expressed in the human placenta. BOK excess causes increased trophoblast autophagy and apoptosis in pre-eclampsia, a pathological condition of hypoxia and oxidative stress. In the present study, we identified an HRE (hypoxia-response element) at the junction of exon-1 and intron-1 (+229 to +279) in the human BOK gene, as well as an antisense transcript driven by a promoter located in intron-2. The isolated BOK-HRE bound hypoxia-inducible HIF (hypoxia-inducible factor) proteins in vitro as well as in trophoblastic JEG3 cells and was functional in its natural position as well as in front of a heterologous promoter. Being a reverted repeat, the BOK-HRE functioned in both orientations. This directionless feature of the BOK-HRE facilitates hypoxia regulation via HIF of both BOK and its antisense transcript as demonstrated by RNAi knockdown of the HIF system. Although the antisense transcript was expressed in several human carcinoma cell lines, including choriocarcinoma-derived JEG3 cells, no antisense-regulated mechanism for BOK expression was noted. Taken together, these findings indicate that hypoxia-induced expression of BOK in placental cells is regulated via HIF and is not affected by its antisense transcript.

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 score0.007
Threshold uncertainty score0.388

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 head0.008
GPT teacher head0.234
Teacher spread0.226 · 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

Citations12
Published2014
Admission routes2
Has abstractyes

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