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Record W4294225715 · doi:10.3389/fimmu.2022.986118

The potential roles of interleukin-25 in infectious diseases

2022· review· en· W4294225715 on OpenAlexaff
Jing Wu, Fang Zhang, Hongji Tao, Waqas Nawaz, Deyan Chen, Zhiwei Wu

Bibliographic record

VenueFrontiers in Immunology · 2022
Typereview
Languageen
FieldImmunology and Microbiology
TopicIL-33, ST2, and ILC Pathways
Canadian institutionsUniversité de MontréalHôpital Maisonneuve-Rosemont
FundersNational Natural Science Foundation of China
KeywordsImmunologyInnate lymphoid cellCytokineBiologyImmunityInterleukin 4Interleukin 9InterleukinInterleukin 15Interleukin 17MedicineImmune system

Abstract

fetched live from OpenAlex

Interleukin-25 (IL-25), also known as IL-17E, is a recently identified cytokine of the IL-17 family. Numerous studies illustrated that the expression of IL-25 is regulated by multiple pathogens, including parasitic, viral, and bacterial infections. IL-25 has a dual function in infectious diseases. On the one hand, IL-25 activates type 2 immunity via the relevant cytokines, including IL-4, IL-5, and IL-13, which are associated with the development of pathogenic infection-related allergic diseases. On the other hand, IL-25 involves in the recruitment of group 2 innate lymphoid cells (ILC2) to enhanced T helper 2 (Th2) cell differentiation, which are important to the clearance of pathogens. However, the precise roles of IL-25 in infectious diseases remain largely unknown. Thus, the current review will shed light on the pivotal roles of IL-25 in infectious diseases.

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 score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0000.001
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 head0.009
GPT teacher head0.238
Teacher spread0.228 · 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

Citations11
Published2022
Admission routes1
Has abstractyes

Explore more

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