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442.3: The fibrinogen-like protein 2 molecule influences the development of thymic regulatory T Cells.

2024· article· en· W4402818352 on OpenAlexaff
Christina Lam, Sajad Moshkelgosha, S. Juvet

Bibliographic record

VenueTransplantation · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDiabetes and associated disorders
Canadian institutionsUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsFibrinogenCell biologyChemistryImmunologyBiologyBiochemistry

Abstract

fetched live from OpenAlex

Latner Thoracic Research Laboratories. Introduction: Transplantation is the primary treatment for patients with end-stage organ failure. However, long-term outcomes are limited by immunosuppressant toxicities and chronic graft rejection. Regulatory T cells (Tregs), with their immunoregulatory capability, hold great potential as a tolerance-inducing agent. As such, identifying factors involved in their development and commitment is required for realization of their therapeutic potential in solid organ transplantation. Fibrinogen-like protein 2 (Fgl2)- deficient Tregs are functionally defective, so we tested the hypothesis that Fgl2 is required for normal thymic Treg development. Method: We first generated reciprocal Fgl2 bone marrow chimeras by reconstituting B6 CD45.1 or CD45.2 female mice with bone marrow stem cells from either fgl2+/+ (WT) or fgl2-/- (KO) mice, producing WT->KO and KO->WT chimeras, along with their corresponding KO-> KO and WT->WT controls. Reconstitution was monitored by monthly tail bleed. Once it reached 90% or more, we collected their plasma and thymi for Fgl2 ELISA and flow cytometry (Fig.1a).Results: There was no significant difference in the plasma concentration of Fgl2 between WT->KO and KO->WT chimeras, suggesting that both radioresistant and radiosensitive cells can produce Fgl2 (Fig. 1b). Strikingly, the number of Tregs and the expression of Treg effector molecules (PD-L1, PD-1, LAG3, and TIGIT) differed dramatically between the 4 chimeric groups (Fig.2a). Complete absence of Fgl2 (KO->KO) increased thymic Treg cellularity and effector molecule expression but only Fgl2 from radioresistant cells (KO->WT), and not radiosensitive cells (WT->KO) was able to restore baseline levels (Fig.2a).Conclusion: Our data demonstrate that not only can radioresistant sources of Fgl2 contribute to its level in the circulation, but they can also influence Treg development. It appears that radioresistant cell-derived Fgl2 can act as a brake on thymic Treg cellularity and their effector molecule expression while radiosensitive cell-derived Fgl2 does not. The authors would like to thank the UHN Foundation for making this work possible, along with the staffs at UHN’s Animal and Flow Cytometry facilities.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.006
GPT teacher head0.216
Teacher spread0.211 · 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 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

Citations0
Published2024
Admission routes1
Has abstractyes

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