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Record W2502610014 · doi:10.1038/icb.2016.64

CD137‐CRDI is not necessary in the role of contacting its natural ligand

2016· article· en· W2502610014 on OpenAlexfundno aff
Ling Yi, Zhuohong Yan, Hongyan Jia, Xiaojue Wang, Yanlin Zhao, Hongtao Zhang

Bibliographic record

VenueImmunology and Cell Biology · 2016
Typearticle
Languageen
FieldMedicine
TopicPeptidase Inhibition and Analysis
Canadian institutionsnot available
FundersNational Natural Science Foundation of ChinaInternational Development Research Centre
KeywordsChemistryCancer researchBiology

Abstract

fetched live from OpenAlex

Immune checkpoint inhibitors result in impressive clinical responses and are expanding to treat a wide variety of tumors. One common problem is low responses from current clinical trials that only benefit a fraction of patients. One key promising direction is combination therapy to increase clinical benefit. CD137, a well-defined antitumor target, can cause strong co-stimulating activity and break immune tolerance. In this study, the role of CD137-CRDI (cysteine rich domain I) in the binding of CD137-CD137L was further investigated based on our previous work. The results revealed that CRDI-mediated limited CD137 assembly without relying on CD137L. Furthermore, CRDI was not involved in direct contact with CD137L in either mice or humans. Isolated mouse CRDII and human CRDII+CRDIII were proven to be the minimum unit for interface with their respective ligands. Fine-tuning of this signaling may improve CD137-targeting strategy.

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 score0.003
Threshold uncertainty score0.010

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 integrity0.0000.001
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 head0.008
GPT teacher head0.246
Teacher spread0.238 · 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

Citations5
Published2016
Admission routes1
Has abstractyes

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