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Record W4386523189 · doi:10.1126/science.abq5202

Kupffer cell–like syncytia replenish resident macrophage function in the fibrotic liver

2023· article· en· W4386523189 on OpenAlexaff
Moritz Peiseler, Bruna Araújo David, Joël Zindel, Bas G. J. Surewaard, Woo‐Yong Lee, Felix Heymann, Ysbrand Nusse, Fernanda V. S. Castanheira, Raymond Shim, Adrien Guillot, Alix Bruneau, Jawairia Atif, Cátia T. Perciani, Christina Ohland, Priyanka Mukherjee, Annika Niehrs, Roland Thuenauer, Marcus Altfeld, Mathias Amrein, Zhaoyuan Liu, Paul M. K. Gordon, Kathy D. McCoy, Justin Deniset, Sonya A. MacParland, Florent Ginhoux, Frank Tacke, Paul Kubes

Bibliographic record

VenueScience · 2023
Typearticle
Languageen
FieldMedicine
TopicLiver physiology and pathology
Canadian institutionsLibin Cardiovascular Institute of AlbertaUniversity Health NetworkUniversity of Calgary
Fundersnot available
KeywordsCirrhosisFibrosisBiologyMacrophageKupffer cellImmune systemCell biologySyncytiumLiver cytologyPathologyImmunologyMedicineVirus

Abstract

fetched live from OpenAlex

Kupffer cells (KCs) are localized in liver sinusoids but extend pseudopods to parenchymal cells to maintain their identity and serve as the body's central bacterial filter. Liver cirrhosis drastically alters vascular architecture, but how KCs adapt is unclear. We used a mouse model of liver fibrosis and human tissue to examine immune adaptation. Fibrosis forced KCs to lose contact with parenchymal cells, down-regulating "KC identity," which rendered them incapable of clearing bacteria. Commensals stimulated the recruitment of monocytes through CD44 to a spatially distinct vascular compartment. There, recruited monocytes formed large aggregates of multinucleated cells (syncytia) that expressed phenotypical KC markers and displayed enhanced bacterial capture ability. Syncytia formed via CD36 and were observed in human cirrhosis as a possible antimicrobial defense that evolved with 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 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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.021
GPT teacher head0.274
Teacher spread0.253 · 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 designObservational
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

Citations119
Published2023
Admission routes1
Has abstractyes

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