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Record W2091872525 · doi:10.1182/blood-2011-01-329359

Myeloid dysplasia and bone marrow hypocellularity in adenosine deaminase-deficient severe combined immune deficiency

2011· article· en· W2091872525 on OpenAlexaff
Robert Sokolic, Irina Marić, Chimene Kesserwan, Elizabeth Garabedian, I. Celine Hanson, Margaret Dodds, Rebecca H. Buckley, Andrew C. Issekutz, Naynesh Kamani, Kit L. Shaw, Ben Tan, Pawan Bali, Michael S. Hershfield, Donald B. Kohn, Alan S. Wayne, Fabio Candotti

Bibliographic record

VenueBlood · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVirus-based gene therapy research
Canadian institutionsUniversity of SaskatchewanDalhousie University
FundersNational Institutes of Health
KeywordsMedicineBone marrowAdenosine deaminaseAdenosine deaminase deficiencyImmune systemDysplasiaMyeloidPathologyImmunologyInternal medicineAdenosine

Abstract

fetched live from OpenAlex

Genetic deficiency of adenosine deaminase (ADA) can cause profound lymphopenia and result in the clinical presentation of severe combined immune deficiency (SCID). However, because of the ubiquitous expression of ADA, ADA-deficient patients often present also with nonimmunologic clinical problems, affecting the skeletal, central nervous, endocrine, and gastrointestinal systems. We now report that myeloid dysplasia features and bone marrow hypocellularity are often found in patients with ADA-SCID. As a clinical correlate to this finding, we have observed vulnerability to antibiotic-induced myelotoxicity and prolonged neutropenia after nonmyeloablative chemotherapy. We have also noted that, in the absence of enzyme replacement therapy, absolute neutrophil counts of patients with ADA deficiency vary inversely with the accumulation of deoxynucleotides. These data have significant implications for the application of standard and investigational therapies to patients with ADA-SCID and support further studies to investigate the possibility that ADA deficiency is associated with a stem cell defect. These trials were registered at www.clinicaltrials.gov as #NCT00018018 and #NCT00006319.

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 score0.022
Threshold uncertainty score0.835

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 head0.016
GPT teacher head0.232
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

Citations47
Published2011
Admission routes1
Has abstractyes

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