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Record W4200440855 · doi:10.3390/curroncol28060438

The Role of Farnesoid X Receptor in Accelerated Liver Regeneration in Rats Subjected to ALPPS

2021· article· en· W4200440855 on OpenAlexvenueno aff
Noémi Daradics, Pim B. Olthof, András Budai, Michal Heger, Thomas M. van Gulik, András Fülöp, Attila Szíjártó

Bibliographic record

VenueCurrent Oncology · 2021
Typearticle
Languageen
FieldMedicine
TopicLiver physiology and pathology
Canadian institutionsnot available
Fundersnot available
KeywordsFarnesoid X receptorLiver regenerationHepatectomyRegeneration (biology)MedicineInternal medicineEndocrinologyBile acidNuclear receptorBiologyCell biologySurgeryTranscription factorBiochemistryGene

Abstract

fetched live from OpenAlex

BACKGROUND: the role of bile acid (BA)-induced farnesoid X receptor (Fxr) signaling in liver regeneration following associating liver partition and portal vein ligation for staged hepatectomy (ALPPS) was investigated in a rat model. METHODS: = 30). Animals were sacrificed pre-operatively and at 24, 48, 72, or 168 h after intervention. Regeneration rate, Ki67 index, hemodynamic changes in the hepatic circulation, and BA levels were assessed. Transcriptome analysis of molecular regulators involved in the Fxr signaling pathway, BA transport, and BA production was performed. RESULTS: < 0.05) than PVL. The mRNA levels of proteins participating in hepatic Fxr signaling were comparable between the intervention groups. More profound activation of the intestinal Fxr pathway was observed 24 h after ALPPS compared to PVL. CONCLUSION: Our study elaborates on a possible linkage between BA-induced Fxr signaling and accelerated liver regeneration induced by ALPPS in rats. ALPPS could trigger liver regeneration via intestinal Fxr signaling cascades instead of hepatic Fxr signaling, thereby deviating from the mechanism of BA-mediated regeneration following one-stage hepatectomy.

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 score0.353
Threshold uncertainty score0.294

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 head0.085
GPT teacher head0.374
Teacher spread0.288 · 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
Published2021
Admission routes1
Has abstractyes

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