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Record W4318920665 · doi:10.1242/dmm.049750

A hepatoprotective role of peritumoral non-parenchymal cells in early liver tumorigenesis

2023· article· en· W4318920665 on OpenAlexaff
Cheng Tian, Liyuan Li, Li Fan, Anthony Brown, Eric J. Norris, Michelle Morrison, Evan S. Glazer, Liqin Zhu

Bibliographic record

VenueDisease Models & Mechanisms · 2023
Typearticle
Languageen
FieldMedicine
TopicLiver physiology and pathology
Canadian institutionsStemcell Technologies
FundersSt. Jude Children's Research HospitalAmerican Cancer Society
KeywordsCarcinogenesisHepatic stellate cellParenchymaSpheroidIn vitroLiver cancerCancer researchLiver tumorPathologyBiologyLiver parenchymaMedicineCancerInternal medicineHepatocellular carcinomaBiochemistry

Abstract

fetched live from OpenAlex

Various 3D models of hepatocytes (HCs) have been established to assess liver functions in vitro. The contribution of the hepatic non-parenchymal cells (NPCs), however, is largely neglected in these models. Here, we report a comparative study of hepatic spheroids generated from freshly isolated mouse whole liver cells (WLCs) and HCs (referred to as SphWLC and SphHC, respectively). We found that HC differentiation was preserved better in SphWLC than in SphHC, and, when co-cultured with liver tumor spheroids (SphT), SphWLC showed more potent suppression of SphT growth compared to SphHC. Histological characterization revealed marked activation and accumulation of hepatic stellate cells (HSCs) at the SphWLC:SphT interface. We found that mixing HSCs in both 3D and 2D HC:tumor co-cultures provided potent protection to HCs against tumor-induced cell death. Activation of HSCs at the tumor border was similarly found in liver tumors from both mice and patients. Overall, our study suggests a hepatoprotective role of peritumoral HSCs in liver tumorigenesis and the potential application of SphWLC as a useful 3D model for dissecting the liver's response to tumorigenesis in vitro.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.705
Threshold uncertainty score0.762

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 head0.017
GPT teacher head0.234
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
Published2023
Admission routes1
Has abstractyes

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