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Record W2792093822 · doi:10.1111/jcmm.13501

Elevated mitochondrial activity distinguishes fibrogenic hepatic stellate cells and sensitizes for selective inhibition by mitotropic doxorubicin

2018· article· en· W2792093822 on OpenAlexaff
Priya Gajendiran, Leonel Iglesias Vega, Kie Itoh, Hiromi Sesaki, Mohammad Reza Vakili, Afsaneh Lavasanifar, Kelvin Hong, Esteban Mezey, Shanmugasundaram Ganapathy‐Kanniappan

Bibliographic record

VenueJournal of Cellular and Molecular Medicine · 2018
Typearticle
Languageen
FieldMedicine
TopicLiver physiology and pathology
Canadian institutionsUniversity of Alberta
FundersNational Institute on Alcohol Abuse and Alcoholism
KeywordsHepatic stellate cellBioenergeticsCell biologyExtracellular matrixFibrosisBiologySecretionLiver cytologyHepatic fibrosisMitochondrionEx vivoChemistryIn vitroPathologyEndocrinologyBiochemistryMedicine

Abstract

fetched live from OpenAlex

Activation of hepatic stellate cells (HSCs) is an integral component of the wound-healing process in liver injury/inflammation. However, uncontrolled activation of HSCs leads to constant secretion of collagen-rich extracellular matrix (ECM) proteins, resulting in liver fibrosis. The enhanced ECM synthesis/secretion demands an uninterrupted supply of intracellular energy; however, there is a paucity of data on the bioenergetics, particularly the mitochondrial (mito) metabolism of fibrogenic HSCs. Here, using human and rat HSCs in vitro, we show that the mito-respiration, mito-membrane potential (Δψm) and cellular 'bioenergetic signature' distinguish fibrogenic HSCs from normal, less-active HSCs. Ex vivo, HSCs from mouse and rat models of liver fibrosis further confirmed the altered 'bioenergetic signature' of fibrogenic HSCs. Importantly, the distinctive elevation in mito-Δψm sensitized fibrogenic HSCs for selective inhibition by mitotropic doxorubicin while normal, less-active HSCs and healthy human primary hepatocytes remained minimally affected if not, unaffected. Thus, the increased mito-Δψm may provide an opportunity to selectively target fibrogenic HSCs in liver fibrosis.

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 score0.010
Threshold uncertainty score0.547

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.246
Teacher spread0.239 · 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

Citations45
Published2018
Admission routes1
Has abstractyes

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