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Record W7144657847

Editorial: Mesenchymal and immune cell crosstalk in fibrotic diseases

2023· other· en· W7144657847 on OpenAlexfundno aff
欣治 朝比奈, Kinji Asahina, Ilangumaran SUBBURAJ

Bibliographic record

VenueInstitutional Repositories DataBase (IRDB) · 2023
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
FundersJapan Society for the Promotion of ScienceCanadian Institutes of Health ResearchJapan Agency for Medical Research and Development
KeywordsMesenchymal stem cellImmune systemCrosstalkCellDiseaseFibrosis
DOInot available

Abstract

fetched live from OpenAlex

Mesenchymal and immune cell crosstalk in fibrotic diseasesFibroblasts, a type of mesenchymal cells, are a source of myofibroblasts and are key players in organ fibrosis.Upon organ injury, tissue-resident fibroblasts are activated to differentiate into myofibroblasts (1).Myofibroblasts express extracellular matrix proteins and participate in progression of fibrosis in the liver, lungs, skin, and other organs.Myofibroblasts produce pro-inflammatory cytokines and chemokines, and induce recruitment of inflammatory immune cells to the fibrotic area.Although fibrosis is recognized as a wound healing process, excessive accumulation of extracellular matrix proteins and myofibroblasts in tissues results in severe fibrosis, which is considered irreversible.Currently, there are no approved drugs for reversal of severe organ fibrosis.In liver fibrosis, hepatic stellate cells are the major source of myofibroblasts (2).Hepatic stellate cells store vitamin A lipids and reside in the space of Disse between hepatocytes and sinusoidal endothelial cells.Following liver injury, damaged hepatocytes release damageassociated molecular patterns and induce activation of hepatic stellate cells.The activated hepatic stellate cells synthesize extracellular matrix proteins, pro-inflammatory cytokines, and chemokines to induce inflammation.In this Research Topic, Liu et al. have reviewed recent findings on the role of exosomes in liver fibrosis.Exosomes derived from hepatocytes or macrophages induce activation of hepatic stellate cells in liver fibrosis.In contrast, exosomes derived from mesenchymal stem cells exert antifibrotic effects on the activated hepatic stellate cells.Exosomes may serve as biomarkers for diagnosis of liver diseases, including fibrosis.Tissue-resident macrophages are derived from myeloid progenitor cells present in the embryonic yolk sac (3).In the liver, resident macrophages, called Kupffer cells, play an important role in protecting the liver from microorganisms that are transported from the intestine through the portal vein.Kupffer cells communicate with hepatic stellate cells and hepatocytes via soluble factors to control liver homeostasis, response to injury, and regeneration.In addition to Kupffer cells, monocyte-derived macrophages are recruited to the injured liver tissue to elicit inflammatory responses (4).Hassan et al. have reviewed the roles of resident Kupffer cells and monocyte-derived macrophages in liver injury.Both the cell types exhibit distinct phenotypes and contribute toward inflammation, Frontiers in Immunology frontiersin.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.085
Threshold uncertainty score0.283

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.022
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0060.002
Science and technology studies0.0030.002
Scholarly communication0.0090.004
Open science0.0040.002
Research integrity0.0210.013
Insufficient payload (model declined to judge)0.0850.048

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 head0.009
GPT teacher head0.254
Teacher spread0.245 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEditorial

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

Citations0
Published2023
Admission routes1
Has abstractno

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