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Addition of anti‐CD25 to thymoglobulin for induction therapy: delayed return of peripheral blood CD25‐positive population

2010· article· en· W1525242529 on OpenAlexaff
Junichiro Sageshima, Gaetano Ciancio, Jeffrey J. Gaynor, Linda Chen, Giselle Guerra, Warren Kupin, David Roth, Phillip Ruiz, George W. Burke

Bibliographic record

VenueClinical Transplantation · 2010
Typearticle
Languageen
FieldMedicine
TopicRenal Transplantation Outcomes and Treatments
Canadian institutionsPancreas Centre (Canada)
FundersNational Center for Theoretical Sciences
KeywordsThymoglobulinDaclizumabMedicineIL-2 receptorTransplantationPopulationKidneyKidney transplantationUrologyInternal medicineImmune systemImmunologyT cellTacrolimus

Abstract

fetched live from OpenAlex

Sageshima J, Ciancio G, Gaynor JJ, Chen L, Guerra G, Kupin W, Roth D, Ruiz P, Burke GW. Addition of anti‐CD25 to thymoglobulin for induction therapy: delayed return of peripheral blood CD25‐positive population. Clin Transplant 2011: 25: E132–E135. © 2010 John Wiley & Sons A/S. Abstract: An anti‐CD25 monoclonal antibody was added to thymoglobulin for induction therapy in simultaneous pancreas/kidney (SPK) recipients. T‐cell subsets including CD3 and CD25 were assessed by flow cytometry analysis in the peripheral blood of SPK (n = 88), and for comparison kidney transplant (KT) recipients were assessed. KT recipients were treated with daclizumab (anti‐CD25) alone (five doses; 1 mg/kg) (n = 27) or thymoglobulin alone (4–7 doses; 1 mg/kg) (n = 23). SPK recipients received daclizumab (two doses; 1 mg/kg) in addition to thymoglobulin (five doses; 1 mg/kg). The return of peripheral blood CD25+ cells was delayed for 45 d post‐transplantation in the SPK recipients where anti‐CD25 was added to thymoglobulin, compared to those KT recipients with thymoglobulin alone. This strategy may result in reduced allogeneic (donor‐specific) T effector cells at the time of solid organ transplantation.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.375
Threshold uncertainty score0.545

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 head0.043
GPT teacher head0.375
Teacher spread0.332 · 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 designObservational
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

Citations39
Published2010
Admission routes1
Has abstractyes

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