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Record W2105163615 · doi:10.1139/bcb-2013-0117

Hydrodynamic tail vein injection of SOCS3 eukaryotic expression vector in vivo promoted liver lipid metabolism and hepatocyte apoptosis in mouse

2014· article· en· W2105163615 on OpenAlexvenueno aff
Zhenjiang Liu, Lu Gan, Xiaobo Yang, Zhenzhen Zhang, Chao Sun

Bibliographic record

VenueBiochemistry and Cell Biology · 2014
Typearticle
Languageen
FieldMedicine
TopicCytokine Signaling Pathways and Interactions
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsSOCS3Lipid metabolismApoptosisSignal transductionBiologyCell biologyHepatocyteSTAT3TUNEL assayBiochemistryIn vitro

Abstract

fetched live from OpenAlex

Suppressor of cytokine signaling 3 (SOCS3), a signal transduction cytokine, is involved in lipid metabolism as well as in cell proliferation, differentiation, apoptosis, and so on. To explore the effects of SOCS3 on apoptosis and lipid metabolism in liver, we used a simple effective method named hydrodynamic tail vein injection to overexpress SOCS3. Then orbital blood was obtained for the assessment of blood lipid after injection. Lipid metabolism related genes were detected by Western blot after the determination of serum lipids. Meanwhile, liver cell apoptosis was observed by Hoechst and TUNEL staining and the expression of apoptosis related proteins Bax, Bcl-2, and Caspase3 were detected as well as the JAK2/STAT3 signaling pathway. In addition, we also demonstrated the effect of SOCS3 in prime hepatocyte by overexpression or interference of SOCS3 along with SD1008, which is a specific inhibitor of the JAK2/STAT3 signaling pathway. Taken together, all the results indicated that SOCS3 promoted lipid synthesis in mice liver and promoted hepatocyte apoptosis by inhibiting the activation of the JAK2/STAT3 signaling pathway, however the detailed regulation mechanism had not yet been fully understood and needs further study.

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 score0.004
Threshold uncertainty score0.431

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 head0.225
Teacher spread0.216 · 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

Citations5
Published2014
Admission routes1
Has abstractyes

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