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Record W2559903720 · doi:10.1155/2016/2148129

How Does Interleukin-22 Mediate Liver Regeneration and Prevent Injury and Fibrosis?

2016· review· en· W2559903720 on OpenAlexaff
Muhammad Babar Khawar, Fareeha Azam, Nadeem Sheikh, Khawaja Abdul Mujeeb

Bibliographic record

VenueJournal of Immunology Research · 2016
Typereview
Languageen
FieldImmunology and Microbiology
TopicPsoriasis: Treatment and Pathogenesis
Canadian institutionsCentennial College
FundersUniversity of the Punjab
KeywordsInterleukin 22CytokineImmune systemImmunologyFibrosisInterleukinRegeneration (biology)InflammationInterleukin 15Liver regenerationBiologyCancer researchCell biologyMedicinePathology

Abstract

fetched live from OpenAlex

Interleukin-22 (IL-22) is a pluripotent T cell-derived cytokine which is a member of IL-10 cytokine family. It is the only interleukin produced by immune cells but does not target immune system components. IL-22 is mainly produced by dendritic cells (DCs) and TH17, TH22, NK, and NKT cells and targets a number of body tissues including liver, pancreas, and other epithelial tissues. It provokes a series of downstream signaling pathways upon binding with IL-22R complex which protects liver damage through STAT3 activation. IL-22BP is an inhibitor of IL-22 which has 20-1000x more affinity to bind with IL-22 compared to IL-22R1 that inhibits IL-22 activity. Its level was found to be positively correlated with the severity of liver damage and fibrosis. So, the present review is an effort to reveal the exact mechanism lying in the hepatoprotective activity of IL-22 and some of its future therapeutic implications.

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 score0.008

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 studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.002

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 head0.348
Teacher spread0.294 · 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

Citations36
Published2016
Admission routes1
Has abstractyes

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