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Record W3171979335 · doi:10.1002/dmrr.3480

Innate immunity in latent autoimmune diabetes in adults

2021· review· en· W3171979335 on OpenAlexaff
Juan Huang, James A. Pearson, F. Susan Wong, Wen Li, Zhiguang Zhou

Bibliographic record

VenueDiabetes/Metabolism Research and Reviews · 2021
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDiabetes and associated disorders
Canadian institutionsInstitute of Infection and Immunity
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute of Diabetes and Digestive and Kidney DiseasesNational Natural Science Foundation of ChinaNational Center for Advancing Translational SciencesYale University
KeywordsInnate immune systemImmune systemImmunologyImmunityAcquired immune systemDiabetes mellitusType 1 diabetesDiseaseMedicinePathogenesisAutoimmune diabetesAutoimmune diseaseAutoimmunityAntibodyInternal medicineEndocrinology

Abstract

fetched live from OpenAlex

Abstract Latent autoimmune diabetes in adults (LADA) is an autoimmune disease that shares some genetic, immunological and clinical features with both type 1 diabetes and type 2 diabetes. Immune cells including CD4 + T cells, CD8 + T cells, B cells, macrophages and dendritic cells (DCs) have been detected in the pancreas of patients with LADA and a rat model of LADA. Therefore, similar to type 1 diabetes, the pathogenesis of LADA may be caused by interactions between islet β‐cells and innate and adaptive immune cells. However, the role of the immunity in the initiation and progression of LADA remains largely unknown. In this review, we have summarized the potential roles of innate immunity and immune‐modulators in LADA development. Furthermore, we have examined the evidence and discussed potential innate immunological reasons for the slower development of LADA compared with type 1 diabetes. More in‐depth mechanistic studies are needed to fully elucidate the roles of innate immune‐associated genes, molecules and cells in their contributions to LADA pathogenesis. Undertaking these studies will greatly enhance the development of new strategies and optimization of current strategies for the diagnosis and treatment of the disease.

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.981
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.002
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 head0.044
GPT teacher head0.351
Teacher spread0.307 · 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 designOther design
Domainnot available
GenreReview

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

Citations16
Published2021
Admission routes1
Has abstractyes

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