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Record W2754113524 · doi:10.1139/gen-2017-0033

Identification, expression analysis, and the regulating function on C/EBPs of KLF10 in Dalian purple sea urchin, <i>Strongylocentrotus nudus</i>

2017· article· en· W2754113524 on OpenAlexvenueno aff
Kaikai Wu, Zhiying Jia, Qi’ai Wang, Zhenlin Wei, Zunchun Zhou, Xiaolin Liu

Bibliographic record

VenueGenome · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicKruppel-like factors research
Canadian institutionsnot available
FundersNorthwest A and F UniversityNational Natural Science Foundation of China
KeywordsBiologyTranscription factorCcaat-enhancer-binding proteinsTranscription (linguistics)EnhancerPromoterGeneCell biologyGene expressionMolecular biologyGeneticsDNA-binding protein

Abstract

fetched live from OpenAlex

Accumulating evidence indicates that Krüppel-like factors (KLFs) play important roles in fat biology via the regulation of CCAAT/enhancer binding proteins (C/EBPs). However, KLFs and C/EBPs have not been identified from Strongylocentrotus nudus, and their roles in this species are not clear. In this study, the full-length cDNA of S. nudus KLF10 (SnKLF10) and three cDNA fragments of S. nudus C/EBPs (SnC/EBPs) were obtained. Examination of tissue distribution and expression patterns during gonadal development implied that SnKLF10 and SnC/EBPs play important roles in gonadal lipogenesis. The presence of transcription factor-binding sites (TFBSs) for KLFs in SnC/EBPs, and the results of an over-expression assay, revealed that SnKLF10 negatively regulates the transcription of SnC/EBPs. In addition, the core promoter regions of SnC/EBPs were determined, and multiple TFBSs for transcription factor (TFs) were identified, which are potential regulators of SnC/EBP transcription. Taken together, these results suggest that SnC/EBP genes are potential targets of SnKLF10, and that SnKLF10 plays a role in lipogenesis by repressing the transcription of SnC/EBPs. These findings provide information for further studies of KLF10 in invertebrates and provide new insight into the regulatory mechanisms of C/EBP transcription.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.682
Threshold uncertainty score0.306

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.009
GPT teacher head0.269
Teacher spread0.260 · 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

Citations1
Published2017
Admission routes1
Has abstractyes

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