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C-Reactive Protein (CRP) Enhances Murine Antibody-Mediated Transfusion Related Acute Lung Injury (TRALI)

2015· article· en· W4205723666 on OpenAlexaff
Rick Kapur, Michael Kim, Shanjee Shanmugabhavananthan, Edwin R. Speck, Rukhsana Aslam, Li Guo, Anne Zufferey, John W. Semple

Bibliographic record

VenueBlood · 2015
Typearticle
Languageen
FieldMedicine
TopicBlood transfusion and management
Canadian institutionsSt. Michael's Hospital
Fundersnot available
KeywordsTransfusion-related acute lung injuryImmunologyMedicinePulmonary edemaAntibodyIsotypeLungLipopolysaccharideAntigenDiffuse alveolar damageMonoclonal antibodyInternal medicine

Abstract

fetched live from OpenAlex

Abstract Transfusion-related acute lung injury (TRALI), a syndrome characterized by respiratory distress triggered by blood transfusions, is the leading cause of transfusion-related mortality. Mostly, TRALI has been attributed to passive infusion of human leucocyte antigen (HLA) and human neutrophil antigen (HNA) antibodies present in the transfused blood product. Several animal models have been developed to study the pathogenesis of antibody-mediated TRALI and various mechanisms for TRALI induction have been suggested, including involvement of endothelial cells, neutrophils and monocytes. In 2006, a murine of model of antibody-mediated TRALI was developed using a monoclonal MHC class I antibody (clone 34-1-2s). This antibody was shown to cause significant lung damage (excess lung water: pulmonary edema) within 2 hours of administration into BALB/c mice, which in follow-up studies was only reproducible after initial priming with the gram-negative endotoxin lipopolysaccharide (LPS). 34-1-2s was also shown to cause severe lung damage in severe combined immunodeficient (SCID) mice. We investigated 34-1-2s mediated TRALI in BALB/c mice, without LPS priming, and found no difference in TRALI severity when compared with injection with an control isotype antibody for 34-1-2s (Isotype Mouse IgG2a antibody), as examined by lung wet-to-dry ratios, a measure for pulmonary edema. Recently it was described that the acute phase protein C-reactive protein (CRP), heavily up-regulated during acute infections and also present at lower levels in healthy individuals, was able to enhance antibody-mediated platelet destruction both in vitro and in vivo via Fc-receptor mediated phagocytic responses. Considering the fact that TRALI has been shown to be mainly antibody-mediated, plus the fact that it has been suggested to be an Fc-dependent process as well, we investigated the effect of CRP in a murine antibody-mediated TRALI. We tested if CRP would be able to enhance antibody-mediated TRALI in the murine 34-1-2s based BALB/c TRALI model. For that purpose, we co-injected CRP together with 34-1-2s and compared that to co-injection of CRP together with control isotype mouse IgG2a or to injection with CRP alone. We found that CRP+34-1-2s injection resulted in significantly higher lung damage than CRP+isotype antibody, as well as than CRP alone, with at least 43% of the mice in the CRP+34-1-2s group having a lung wet-to-dry ratio of higher than 5, which is considered to represent severe lung damage. As the monocyte-derived neutrophil chemoattractant macrophage inflammatory protein 2 (MIP-2: murine equivalent of human IL-8) was recently shown to play a central role in murine (SCID) 34-1-2s-mediated TRALI induction, we measured MIP-2 values in our BALB/c TRALI model and found that CRP alone was capable of producing high levels of MIP-2, which were found to be even more increased when 34-1-2s was co-injected with CRP. We propose a mechanism in which CRP plays a synergistic role with 34-1-2s antibody to significantly increase the induction of antibody-mediated TRALI via enhanced stimulation of monocyte-derived MIP-2 secretion. Disclosures No relevant conflicts of interest to declare.

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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.011
GPT teacher head0.279
Teacher spread0.269 · 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".

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Citations1
Published2015
Admission routes1
Has abstractyes

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