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Record W2997751689 · doi:10.1186/s13041-019-0535-3

Transcriptional activation of USP16 gene expression by NFκB signaling

2019· article· en· W2997751689 on OpenAlexafffund
Shou Yang, Juelu Wang, Shipeng Guo, Daochao Huang, Isabel Bestard‐Lorigados, Xing Nie, Dandan Lou, Yanhua Li, Mingjing Liu, Yu Ri Kang, Weihui Zhou, Weihong Song

Bibliographic record

VenueMolecular Brain · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicUbiquitin and proteasome pathways
Canadian institutionsUniversity of British Columbia HospitalUniversity of British Columbia
FundersCanadian Institutes of Health ResearchNational Natural Science Foundation of China
KeywordsPsychopharmacologyGene expressionGeneSignal transductionNF-κBRegulation of gene expressionGeneticsCell biologyBiologyCancer researchPharmacology

Abstract

fetched live from OpenAlex

Ubiquitin Specific Peptidase 16 (USP16) has been reported to contribute to somatic stem-cell defects in Down syndrome. However, how this gene being regulated is largely unknown. To study the mechanism underlying USP16 gene expression, USP16 gene promoter was cloned and analyzed by luciferase assay. We identified that the 5' flanking region (- 1856 bp ~ + 468 bp) of the human USP16 gene contained the functional promotor to control its transcription. Three bona fide NFκB binding sites were found in USP16 promoter. We showed that p65 overexpression enhanced endogenous USP16 mRNA level. Furthermore, LPS and TNFα, strong activators of the NFκB pathway, upregulated the USP16 transcription. Our data demonstrate that USP16 gene expression is tightly regulated at transcription level. NFκB signaling regulates the human USP16 gene expression through three cis-acting elements. The results provide novel insights into a potential role of dysregulation of USP16 expression in Alzheimer's dementia in Down Syndrome.

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 score0.031
Threshold uncertainty score0.491

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 head0.223
Teacher spread0.215 · 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

Citations8
Published2019
Admission routes2
Has abstractyes

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