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NADPH oxidase 2 activity modulates antigen processing and epitope repertoires (P5186)

2013· article· en· W4313349587 on OpenAlexaff
Jason C.M. Lemmon, Dale R. Balce, Joanna M. Rybicka, Robin M. Yates

Bibliographic record

VenueThe Journal of Immunology · 2013
Typearticle
Languageen
FieldImmunology and Microbiology
TopicNeutrophil, Myeloperoxidase and Oxidative Mechanisms
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsEpitopeAntigen processingNADPH oxidaseAntigenPhagosomeImmune systemCell biologyBiologyAntigen presentationChemistryImmunologyIntracellularT cellReactive oxygen species

Abstract

fetched live from OpenAlex

Abstract Phagocytes such as macrophages and dendritic cells are essential to both the innate and acquired immune systems of mammals. To produce effective immune responses, material antigens must first be processed and presented by phagocytes. The importance of antigen processing is often overlooked, which is exemplified by current therapies focusing on downstream immune processes in T cells and B cells. However, these therapies often result in modulation of the immune system as a whole. Instead, it would be ideal to modulate antigen processing to prevent the generation of epitopes able to stimulate and re-stimulate specific T cells. Antigen processing within phagosomes is a dynamic process influenced by several environmental factors such as pH and oxidative burst. Of particular importance to our lab is the oxidative burst generated by the protein complex NADPH oxidase 2. Our lab has previously published data showing that regulation of NADPH oxidase 2 activity results in modulation of phagosomal proteolysis through modulation of cysteine cathepsin activity. We further hypothesize that protein antigen processing and epitope repertoire generation can be predicted and more importantly influenced by changing the activity of NADPH oxidase 2. Using a combination of fluorometric data, HPLC, and mass spectrometry we have begun to show, through preliminary data, that epitope repertoires can indeed be influenced without knocking down antigen processing and presentation as a whole.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.011
GPT teacher head0.223
Teacher spread0.211 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2013
Admission routes1
Has abstractyes

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