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Record W2903498998 · doi:10.1101/483289

Serum-dependent and independent regulation of PARP2

2018· preprint· en· W2903498998 on OpenAlexafffund
Qizhi Sun, Mohamed I. Gatie, Gregory M. Kelly

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2018
Typepreprint
Languageen
FieldMedicine
TopicPARP inhibition in cancer therapy
Canadian institutionsChildren’s Health Research InstituteWestern University
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of RochesterUniversité Laval
KeywordsCell biologyBiologyChromatinUbiquitin ligaseKLF4UbiquitinTranscription factorGeneGenetics

Abstract

fetched live from OpenAlex

Abstract PARP2 belongs to a family of proteins involved in cell differentiation, DNA damage repair, cellular energy expenditure, chromatin modeling and cell differentiation. In addition to these overlapping functions with PARP1, PARP2 participates in spermatogenesis, T-cell maturation, extraembryonic endoderm formation and adipogenesis. The function(s) of PARP2 is far from complete, and the mechanism(s) by which the gene and protein are regulated are unknown. In this study, we found that two different mechanisms are used in vitro to regulate PARP2 levels. In the presence of serum, PARP2 is degraded through the ubiquitin-proteasome pathway, however, when serum is removed, PARP2 is rapidly sequestered into an SDS- and urea-insoluble fraction. This sequestration is relieved by serum in a dose-dependent manner, and again PARP2 is detected by immunoblotting. Furthermore, and despite the presence of a putative serum response element in the PARP2 gene, transcription is not affected by serum deprivation. These observations that PARP2 is tightly regulated by distinct pathways highlights the critical roles PARP2 plays under different physiological conditions.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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)0.0020.001

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 head0.019
GPT teacher head0.255
Teacher spread0.236 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2018
Admission routes2
Has abstractyes

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Same venuebioRxiv (Cold Spring Harbor Laboratory)Same topicPARP inhibition in cancer therapyFrench-language works237,207