MétaCan
Menu
Back to cohort
Record W1993911704 · doi:10.1080/10731190600683845

Comparative Analysis of Polymer and Linker Chemistries on the Efficacy of Immunocamouflage of Murine Leukocytes

2006· article· en· W1993911704 on OpenAlexaff
Audrey M. Chen, Mark D. Scott

Bibliographic record

VenueArtificial Cells Blood Substitutes and Biotechnology · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Interference and Gene Delivery
Canadian institutionsCanadian Blood ServicesUniversity of British Columbia
Fundersnot available
KeywordsAllorecognitionChemistryLinkerIn vitroMixed lymphocyte reactionCellCell biologyImmunologyBiologyImmune systemT cellBiochemistry

Abstract

fetched live from OpenAlex

Membrane grafting of methoxypoly(ethylene glycol) [mPEG] to allogeneic leukocytes attenuates allorecognition and significantly reduces the risk of graft-versus-host disease in mice. To optimize the immunological efficacy of polymer grafting, murine splenocytes were modified using three differing linker chemistries: CmPEG (5 kDa), BTCmPEG (5 and 20 kDa) and TmPEG (5 kDa). In vitro immunocamouflage efficacy was examined by flow cytometic analysis of leukocyte markers and mixed lymphocyte reactions (MLR). In contrast to CmPEG and BTCmPEG, TmPEG exerted significant cellular toxicity. Flow cytometric analysis demonstrated that both CmPEG and BTCmPEG were highly effective at camouflaging cell surface markers while TmPEG was ineffective. Furthermore, CmPEG and BTCmPEG dramatically blocked MLR allorecognition and cellular proliferation. Polymer length was the most critical factor in the immunocamouflage of cells with the BTCmPEG 20 kDa being the most effective. In contrast to other immunomodulatory approaches, immunocamouflage of leukocytes yields a multivalent effect globally interfering with attachment, allorecognition, presentation and costimulation pathways.

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 score0.003
Threshold uncertainty score0.360

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.012
GPT teacher head0.228
Teacher spread0.216 · 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

Citations30
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueArtificial Cells Blood Substitutes and BiotechnologySame topicRNA Interference and Gene DeliveryFrench-language works237,207