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Record W4379966448 · doi:10.1111/pcmr.13101

Trained immunity in the pathogenesis of vitiligo

2023· review· en· W4379966448 on OpenAlex
Nicoline F. Post, Greta Ginski, Rens Peters, N. van Uden, Marcel W. Bekkenk, Albert Wolkerstorfer, Mihai G. Netea, Rosalie M. Luiten

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePigment Cell & Melanoma Research · 2023
Typereview
Languageen
FieldImmunology and Microbiology
TopicImmune responses and vaccinations
Canadian institutionsInstitute of Infection and Immunity
Fundersnot available
KeywordsVitiligoInnate immune systemImmunologyImmune systemEpigeneticsBiologyImmunityAcquired immune systemInnate lymphoid cellGeneticsGene

Abstract

fetched live from OpenAlex

Vitiligo is caused by an autoimmune reaction against melanocytes leading to melanocyte loss. The cause of vitiligo is an interaction between genetic susceptibility and environmental factors. Both the adaptive immune system-through cytotoxic CD8+ T cells and melanocyte specific antibodies-and the innate immune system are involved in these immune processes in vitiligo. While recent data stressed the importance of innate immunity in vitiligo, the question remains why vitiligo patients' immune response becomes overly activated. Could a long-term increase in innate memory function, described as trained immunity after vaccination and in other inflammatory diseases, play a role as an enhancer and continuous trigger in the pathogenesis of vitiligo? After exposure to certain stimuli, innate immune system is able to show an enhanced immunological response to a secondary trigger, indicating a memory function of the innate immune system, a concept termed trained immunity. Trained immunity is regulated by epigenetic reprogramming, including histone chemical modifications and changes in chromatin accessibility that cause sustained changes in the transcription of specific genes. In responses to an infection, trained immunity is beneficial. However, there are indications of a pathogenic role of trained immunity in inflammatory and autoimmune diseases, with monocytes presenting features of a trained phenotype, resulting in increased cytokine production, altered cell metabolism through mTOR signaling, and epigenetic modifications. This hypothesis paper focusses on vitiligo studies that have shown these indications, suggesting the involvement of trained immunity in vitiligo. Future studies focusing on metabolic and epigenetic changes in innate immune cell populations in vitiligo could help in elucidating the potential role of trained immunity in vitiligo pathogenesis.

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.

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)0.006
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.990
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.191
GPT teacher head0.424
Teacher spread0.233 · 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