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Record W2966365653 · doi:10.3390/cancers11081080

Regulation of Immunity in Breast Cancer

2019· review· en· W2966365653 on OpenAlexafffund
Chidalu A. Edechi, Nnamdi Ikeogu, Jude E. Uzonna, Yvonne Myal

Bibliographic record

VenueCancers · 2019
Typereview
Languageen
FieldMedicine
TopicCancer Immunotherapy and Biomarkers
Canadian institutionsUniversity of Manitoba
FundersUniversity of ManitobaNatural Sciences and Engineering Research Council of CanadaCancerCare Manitoba FoundationResearch Manitoba
KeywordsBreast cancerImmune systemImmunotherapyTumor microenvironmentCancerCarcinogenesisMedicineImmunityCancer immunotherapyImmunologyCancer researchInternal medicine

Abstract

fetched live from OpenAlex

Breast cancer affects millions of women worldwide, leading to many deaths and significant economic burden. Although there are numerous treatment options available, the huge potentials of immunotherapy in the management of localized and metastatic breast cancer is currently being explored. However, there are significant gaps in understanding the complex interactions between the immune system and breast cancer. The immune system can be pro-tumorigenic and anti-tumorigenic depending on the cells involved and the conditions of the tumor microenvironment. In this review, we discuss current knowledge of breast cancer, including treatment options. We also give a brief overview of the immune system and comprehensively highlight the roles of different cells of the immune system in breast tumorigenesis, including recent research discoveries. Lastly, we discuss some immunotherapeutic strategies for the management of breast cancer.

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)0.001
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 score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0000.001
Research integrity0.0010.001
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 head0.054
GPT teacher head0.361
Teacher spread0.307 · 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

Citations70
Published2019
Admission routes2
Has abstractyes

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