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Record W4226205771 · doi:10.1016/j.crimmu.2022.03.001

Loss of thymic function promotes EAE relapse in anti-CD52-treated mice

2022· article· en· W4226205771 on OpenAlexafffund
Adeolu Adegoke, Jiaxin Lin, Colin C. Anderson

Bibliographic record

VenueCurrent Research in Immunology · 2022
Typearticle
Languageen
FieldImmunology and Microbiology
TopicT-cell and B-cell Immunology
Canadian institutionsUniversity of Alberta
FundersCanadian Institutes of Health ResearchSanofi Genzyme
KeywordsCD52MedicineMultiple sclerosisExperimental autoimmune encephalomyelitisImmunologyThymectomyT cellInternal medicineAntibodyAlemtuzumabImmune system

Abstract

fetched live from OpenAlex

Anti-CD52 treatment creates a long-lasting CD4 T cell lymphopenia and reduces multiple sclerosis (MS) relapses in humans. In contrast, anti-CD52 therapy at disease onset more fully suppresses experimental autoimmune encephalomyelitis (EAE) in mice, and T cell repopulation is rapid. To test whether prolonged T cell lymphopenia promotes relapses, we thymectomized mice prior to EAE induction and anti-CD52 treatment. Thymectomy greatly reduced the number of recent thymic emigrant T cells and was associated with a prolonged reduction in CD4 T cells in peripheral blood. Two-thirds of thymectomized C57BL/6 mice had an EAE relapse post anti-CD52 treatment, while no surgery and sham surgery euthymic controls remained relapse-free. These data demonstrate that thymus function can alter the effectiveness of anti-CD52 treatment.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
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 score0.335
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.004
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 head0.051
GPT teacher head0.323
Teacher spread0.272 · 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.

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

Citations2
Published2022
Admission routes2
Has abstractyes

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