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Record W1859448372 · doi:10.1080/15384101.2015.1021520

<i>HMGA1</i>-pseudogene expression is induced in human pituitary tumors

2015· article· en· W1859448372 on OpenAlex

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

VenueCell Cycle · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer-related molecular mechanisms research
Canadian institutionsCanadian Nautical Research Society
Fundersnot available
KeywordsBiologyCarcinogenesisPseudogeneCancer researchPituitary tumorsDownregulation and upregulationCancerGeneEndocrinologyGenetics

Abstract

fetched live from OpenAlex

Numerous studies have established that High Mobility Group A (HMGA) proteins play a pivotal role on the onset of human pituitary tumors. They are overexpressed in pituitary tumors, and, consistently, transgenic mice overexpressing either the Hmga1 or the Hmga2 gene develop pituitary tumors. In contrast with HMGA2, HMGA1 overexpression is not related to any rearrangement or amplification of the HMGA1 locus in these tumors. We have recently identified 2 HMGA1 pseudogenes, HMGA1P6 and HMGA1P7, acting as competitive endogenous RNA decoys for HMGA1 and other cancer related genes. Here, we show that HMGA1 pseudogene expression significantly correlates with HMGA1 mRNA levels in growth hormone and nonfunctioning pituitary adenomas likely inhibiting the repression of HMGA1 through microRNAs action. According to our functional studies, these HMGA1 pseudogenes enhance the proliferation and migration of the mouse pituitary tumor cell line, at least in part, through their upregulation. Our results point out that the overexpression of HMGA1P6 and HMGA1P7 could contribute to increase HMGA1 levels in human pituitary tumors, and then to pituitary tumorigenesis.

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 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 score0.009
Threshold uncertainty score0.733

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 head0.023
GPT teacher head0.284
Teacher spread0.261 · 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