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Record W4309840121 · doi:10.3389/fimmu.2022.1093318

Editorial: Innate lymphocytes in tumor surveillance

2022· editorial· en· W4309840121 on OpenAlexaff
Jörg H. Fritz, Dagmar Stoiber

Bibliographic record

VenueFrontiers in Immunology · 2022
Typeeditorial
Languageen
FieldImmunology and Microbiology
TopicImmune Cell Function and Interaction
Canadian institutionsMcGill University
Fundersnot available
KeywordsInnate immune systemCancer immunotherapyImmunologyMedicineImmunotherapyImmunityCancerInternal medicineImmune system

Abstract

fetched live from OpenAlex

Innate lymphocytes in tumor surveillanceThe multifaceted roles of Innate Lymphoid Cells (ILC) have been widely interrogated in tumor immunity.Whereas Natural Killer (NK) cells possess tumor-suppressive properties across multiple types of cancer, the other ILC family members can either promote or inhibit tumor growth depending on the environmental conditions.The differential effects of ILCs on tumor outcome have been attributed to the high degree of heterogeneity and plasticity within the ILC family members.However, it is now becoming clear that ILC responses are shaped by their dynamic crosstalk with the different components of the tumor microenvironment (TME) (1).Recent years have witnessed a significant development in the current understanding of ILCs and their roles in the innate immune system, where they regulate tissue homeostasis, inflammation, as well as tumor surveillance and tumorigenesis (2).ILCs may be classified into three subgroups depending on their phenotypic and functional characteristics: Group 1 ILCs, which include NK cells and ILC1s (3); Group 2 ILCs, which only contain ILC2s (4), and Group 3 ILCs, which comprise of LTi cells and ILC3s (5).This Research Topic features several review and original research articles on the different facets of innate lymphocytes in the context of cancer.This includes basic underlying mechanisms of anti-tumor action as well as translational and clinical advances in this area of research.The topic spans different areas of NK cell as well as ILC research with emphasis on their role during tumor development and progression.NK cells are the prototype innate lymphoid cells exhibiting potent cytolytic function that provide host defense against infection and tumors.They are able to kill tumor cells if these show surface markers associated with oncogenic transformation.Due to this property NK cells control tumor growth at least in the early phase of tumor development and thus they are essential in tumor surveillance.Once target cells are recognized the balance of activating and inhibitory receptor signaling regulates their effector function against tumor targets (6).These properties and their capacity to enhance antibody and T cell responses highlight the role for NK cells as anticancer agents (7, 8).Current

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)0.004
metaresearch head score (Gemma)0.007
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: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.019
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0050.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0020.001
Science and technology studies0.0020.002
Scholarly communication0.0050.004
Open science0.0030.001
Research integrity0.0100.015
Insufficient payload (model declined to judge)0.0190.014

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 head0.004
GPT teacher head0.214
Teacher spread0.210 · 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
GenreEditorial

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

Citations2
Published2022
Admission routes1
Has abstractyes

Explore more

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