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Record W2902690248 · doi:10.3389/fimmu.2018.02737

CTLA-4 and PD-1 Control of T-Cell Motility and Migration: Implications for Tumor Immunotherapy

2018· review· en· W2902690248 on OpenAlexaff
Monika C. Brunner‐Weinzierl, Christopher E. Rudd

Bibliographic record

VenueFrontiers in Immunology · 2018
Typereview
Languageen
FieldMedicine
TopicCancer Immunotherapy and Biomarkers
Canadian institutionsHôpital Maisonneuve-RosemontUniversité de Montréal
FundersDeutsche Forschungsgemeinschaft
KeywordsBlockadeImmunotherapyCTLA-4Immune systemCancer researchAntibodyAutoimmunityMonoclonal antibodyEffectorImmune checkpointImmunologyMotilityT cellPeripheral toleranceReceptorBiologyCell biologyBiochemistry

Abstract

fetched live from OpenAlex

CTLA-4 is a co-receptor on T-cells that controls peripheral tolerance and the development of autoimmunity. Immune check-point blockade (ICB) uses monoclonal antibodies (MAbs) to block the binding of inhibitory receptors (IRs) to their natural ligands. A humanised antibody to CTLA- 4 [Ipilimumab] was first approved clinically followed by antibody blockade of PD-1 [Nivolumab and Pembrolizumab] and its ligand PD-L1 [Atezolizumab](Baumeister et al., 2016; Okazaki et al., 2013; Page et al., 2014; Sharma et al., 2011) The function and mechanisms of action of CTLA-4 involve cell intrinsic and cell extrinsic pathways. Effective anti-tumour immunity requires the activation of tumour-specific effector T cells, the blockade of regulatory cells and the migration of T-cells into the tumour. In this review, we review data implicating CTLA-4 and PD-1 in the motility of T-cells with a specific reference to the potential exploitation of theses pathways for more effective tumour infiltration and eradication.

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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.021
GPT teacher head0.305
Teacher spread0.284 · 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

Citations151
Published2018
Admission routes1
Has abstractyes

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