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Record W2330003363 · doi:10.1097/mpa.0000000000000603

Inducing Specific Immune Tolerance to Prevent Type 1 Diabetes in NOD Mice

2016· article· en· W2330003363 on OpenAlexaff
Fang Liu, Zhong Yao, Qibin Jiao, Longlei Cao, Haijun Feng, Shaohua Yao, Yiqing Li, Ping Lü

Bibliographic record

VenuePancreas · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDiabetes and associated disorders
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsNodImmune systemType 1 diabetesImmune toleranceNOD miceImmunologyMedicineDiabetes mellitusAutoimmunityEndocrinology

Abstract

fetched live from OpenAlex

OBJECTIVES: Proinsulin is the first autoantigen in type 1 diabetes (T1D). We reasoned that coupling hematopoietic stem cells (HSCs) transplantation with ex vivo transduction of syngeneic HSCs with lentiviral vectors to express proinsulin II could prevent T1D in nonobese diabetic (NOD) mice. METHODS: Hematopoietic stem cells were isolated from 6- to 8-week-old NOD female mice and transduced in vitro with lentiviral vectors encoding proinsulin II. Preconditioned 3- to 4-week-old female NOD mice were transplanted with transduced or nontransduced HSCs and compared with age-matched unmanipulated control. The insulitis, T1D development, and immune reconstitution were assessed. RESULTS: The mean (SD) insulitis score was significantly reduced (1.156 [0.575] vs 2.156 [0.892] or 3.043 [0.728], P = 0.009 or <0.001), and diabetes was nearly completely prevented (1/13 vs 5/12 or 4/9, P = 0.031 or 0.013) in recipients of transduced HSCs expressing proinsulin II as compared with recipients of nontransduced HSCs or unmanipulated control. Sialitis, reconstitution of peripheral blood leukocytes, and in vitro recall responses to ovalbumin were not different between 3 groups of mice. CONCLUSIONS: Syngeneic transplantation of HSCs transduced ex vivo with lentiviral vectors to encode proinsulin II is a novel strategy to prevent T1D.

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 score0.165
Threshold uncertainty score0.356

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 head0.006
GPT teacher head0.214
Teacher spread0.208 · 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

Citations1
Published2016
Admission routes1
Has abstractyes

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