MétaCan
Menu
Back to cohort
Record W3212703149 · doi:10.1098/rsob.210194

Maintenance and loss of endocytic organelle integrity: mechanisms and implications for antigen cross-presentation

2021· review· en· W3212703149 on OpenAlexaff
Eleanor Childs, Conor M. Henry, Johnathan Canton, Caetano Reis e Sousa

Bibliographic record

VenueOpen Biology · 2021
Typereview
Languageen
FieldImmunology and Microbiology
TopicComplement system in diseases
Canadian institutionsUniversity of Calgary
FundersH2020 Marie Skłodowska-Curie ActionsMedical Research CouncilLouis-Jeantet FoundationEuropean CommissionFederation of European Biochemical SocietiesWellcome TrustFrancis Crick InstituteCancer Research UK
KeywordsBiologyEndocytic cycleAntigen presentationAntigenOrganelleCell biologyAntigen processingComputational biologyImmunologyImmune systemGeneticsEndocytosisCellT cell

Abstract

fetched live from OpenAlex

The membranes of endosomes, phagosomes and macropinosomes can become damaged by the physical properties of internalized cargo, by active pathogenic invasion or by cellular processes, including endocytic maturation. Loss of membrane integrity is often deleterious and is, therefore, prevented by mitigation and repair mechanisms. However, it can occasionally be beneficial and actively induced by cells. Here, we summarize the mechanisms by which cells, in particular phagocytes, try to prevent membrane damage and how, when this fails, they repair or destroy damaged endocytic organelles. We also detail how one type of phagocyte, the dendritic cell, can deliberately trigger localized damage to endocytic organelles to allow for major histocompatibility complex class I presentation of exogenous antigens and initiation of CD8 + T-cell responses to viruses and tumours. Our review highlights mechanisms for the regulation of endocytic organelle membrane integrity at the intersection of cell biology and immunology that could be co-opted for improving vaccination and intracellular drug delivery.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.002

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 head0.106
GPT teacher head0.435
Teacher spread0.329 · 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 designNot applicable
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

Citations18
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueOpen BiologySame topicComplement system in diseasesFrench-language works237,207