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Plasma membrane interactions that determine presentation of antigens by Antigen-presenting cells. (P5022)

2013· article· en· W4313354691 on OpenAlexaff
Aswin Hari, Yan Shi

Bibliographic record

VenueThe Journal of Immunology · 2013
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmunotherapy and Immune Responses
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMajor histocompatibility complexAntigenAntigen processingAntigen presentationImmune systemMHC restrictionCell biologyAcquired immune systemBiologyMHC class IAntigen-presenting cellT cellImmunology

Abstract

fetched live from OpenAlex

Abstract Antigen presentation is a critical process in host defense for initiating adaptive immune responses. The APC loads peptides derived from antigens onto major histocompatibility complex (MHC) molecules and exports them to the surface for T cells sampling. If the primary interaction between an APC and T cell is successful, i.e. the TCR binds an appropriate MHC-peptide complex, this leads to an adaptive immune response. Peptide antigens are presented on two types of MHC molecules, MHC I and MHC II via several distinct processing pathways. In turn, the MHC molecule dictates which type of T cell can be activated and thereby the nature of the adaptive immune response. Therefore, antigen loading onto MHC molecules is a critical determinant of the adaptive immune responses. Exogenous antigens can be presented on MHC I and II molecules. Antigen processing mechanisms have been elucidated in great detail, but the fundamental reason behind why an antigen is directed into a specific pathway is not known. One of the foremost aims for this project is to determine why particulate antigens are presented more often on MHC I and why soluble antigens are more efficiently presented on MHC II, by deciphering the interactions of plasma membrane with particulate versus soluble antigen. This fundamental sensing mechanism of the human body when elucidated can help in generating an antiviral response in diseases like HIV and in field of preventative medicine.

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 score0.008
Threshold uncertainty score0.027

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0080.004

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 head0.252
Teacher spread0.237 · 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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