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Record W2073778036 · doi:10.1007/s00147-004-0698-3

Resistance to anti-CD45RB-induced tolerance in NOD mice: mechanisms involved

2004· article· en· W2073778036 on OpenAlexaff
Daniel J. Moore, Xiaolun Huang, MajorK. Lee, Moh‐Moh Lian, Meredith Chiaccio, Haiying Chen, Brigitte Koeberlein, Robert Zhong, JamesF. Markmann, Shaoping Deng

Bibliographic record

VenueTransplant International · 2004
Typearticle
Languageen
FieldMedicine
TopicPancreatic function and diabetes
Canadian institutionsWestern University
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institutes of HealthAmerican Diabetes Association
KeywordsNodMedicineNOD miceImmunologyImmune toleranceLymphocyteTransplantationCentral toleranceMechanism (biology)Clonal deletionAntibodyImmune systemAutoimmunityT cellDiabetes mellitusInternal medicineT-cell receptorEndocrinology

Abstract

fetched live from OpenAlex

While great advances have been made in the success of islet transplantation to cure autoimmune diabetes, this protocol remains limited by our inability to induce donor-specific tolerance within the recipient. The profound resistance of the NOD mouse to tolerance-inducing regimens that are routinely successful in other strains further defines the imposing barriers that must be surmounted. Herein, we have assessed the utility of anti-CD45RB therapy to induce tolerance to allografts in C57BL/6 and NOD-strain mice. We find that, as with other therapies, NOD mice are also resistant to this manipulation, despite robust tolerance induction in the comparison strain. Analysis of cell surface markers revealed a number of changes within the B lymphocyte compartment following contact with antibody and alloantigen in the B6 strain. The absence of reciprocal changes within the NOD lymphocyte compartment suggests that B cells might contribute to the mechanism of action of this therapy and to the resistance to immunological tolerance noted in the NOD strain.

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 score0.217
Threshold uncertainty score0.495

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 studies0.0000.000
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 head0.019
GPT teacher head0.260
Teacher spread0.241 · 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

Citations20
Published2004
Admission routes1
Has abstractyes

Explore more

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