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Record W2156918941 · doi:10.1677/jme.0.0320497

Phosphatidylserine receptor cooperates with high-density lipoprotein receptor in recognition of apoptotic cells by thymic nurse cells

2004· article· en· W2156918941 on OpenAlexaff
WM Cao, Koji Murao, Hitomi Imachi, Chiharu Hiramine, Hideki Abe, Xiao Yu, Hiroaki Dobashi, NC Wong, J Takahara, Toshihiko Ishida

Bibliographic record

VenueJournal of Molecular Endocrinology · 2004
Typearticle
Languageen
FieldImmunology and Microbiology
TopicPhagocytosis and Immune Regulation
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsApoptosisPhosphatidylserineCell biologyReceptorInflammationScavenger receptorBiologyCancer researchMedicineImmunologyInternal medicineEndocrinologyLipoproteinBiochemistryCholesterolPhospholipid

Abstract

fetched live from OpenAlex

The thymus contains many apoptotic cells that arise from the process of positive and negative selection. Both thymic macrophages and thymic nurse cells/nursing thymic epithelial cells (nursing TECs), non-professional phagocytes, recognize and ingest apoptotic cells without inflammation or tissue damage. Previously we reported that human scavenger receptor class B (SR-B1) is involved in recognition of apoptotic thymocytes by nursing TECs. In this study, we examined the expression and role of a phosphatidylserine receptor (PSR). This receptor is believed to participate in the clearance of apoptotic cells. PSR was strongly expressed in nursing TECs. Transforming growth factor-beta augmented the expression of PSR leading to enhanced binding of apoptotic cells to nursing TECs. In nursing TECs, suppressed expression of human SR-B1 with anti-PSR antibody decreased binding of apoptotic thymocytes to nursing TECs. Our results suggest that both PSR and SR-B1 are expressed in nursing TECs and these receptors appear to play a major role in the clearance of apoptotic cells from the thymus.

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 score0.007
Threshold uncertainty score0.850

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 head0.005
GPT teacher head0.198
Teacher spread0.193 · 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

Citations24
Published2004
Admission routes1
Has abstractyes

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