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Record W4281564783 · doi:10.1089/jir.2021.0236

The Role of Chemokine IL-7 in Tumor and Its Potential Antitumor Immunity

2022· review· en· W4281564783 on OpenAlexaff
Leilei Zhang, Kewen Zhou, Huang Biao, Fang Huang

Bibliographic record

VenueJournal of Interferon & Cytokine Research · 2022
Typereview
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsChemokineBiologyImmunologyCancer researchCytokineLymphomaImmunityTumor microenvironmentAcquired immune systemImmune system

Abstract

fetched live from OpenAlex

Interleukin-7 (IL-7) is a cytokine belonging to the chemokine family. It plays a key role in the differentiation, development, and maturation of T lymphocytes and B lymphocytes, which is pivotal to adaptive immunity. In addition to its role in lymphocyte development, recent studies have indicated the antitumor functions of IL-7 in the tumor microenvironment. In this review, we discuss the role of IL-7 in tumors and summarize its antitumor potential and clinical application in lymphoma, leukemia, breast cancer, colon cancer, and so on. Furthermore, the combinational strategies of IL-7 and other antitumor drugs have been also discussed.

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 score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.097
GPT teacher head0.422
Teacher spread0.325 · 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

Citations8
Published2022
Admission routes1
Has abstractyes

Explore more

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