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Record W3129081724 · doi:10.3389/fcell.2021.612830

Vedolizumab: Potential Mechanisms of Action for Reducing Pathological Inflammation in Inflammatory Bowel Diseases

2021· review· en· W3129081724 on OpenAlexafffund
Matthew Luzentales-Simpson, Y Pang, Ada Zhang, James A. Sousa, Laura M. Sly

Bibliographic record

VenueFrontiers in Cell and Developmental Biology · 2021
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsBC Children's HospitalUniversity of British Columbia
FundersCanadian Institutes of Health ResearchCrohn's and Colitis CanadaMichael Smith Health Research BC
KeywordsVedolizumabMedicineNatalizumabInflammatory bowel diseaseInfliximabImmunologyUlcerative colitisInflammationAdalimumabProgressive multifocal leukoencephalopathyTumor necrosis factor alphaInternal medicineDiseaseMultiple sclerosis

Abstract

fetched live from OpenAlex

Inflammatory bowel diseases (IBD), encompassing ulcerative colitis (UC), and Crohn's disease (CD), are a group of disorders characterized by chronic, relapsing, and remitting, or progressive inflammation along the gastrointestinal tract. IBD is accompanied by massive infiltration of circulating leukocytes into the intestinal mucosa. Leukocytes such as neutrophils, monocytes, and T-cells are recruited to the affected site, exacerbating inflammation and causing tissue damage. Current treatments used to block inflammation in IBD include aminosalicylates, corticosteroids, immunosuppressants, and biologics. The first successful biologic, which revolutionized IBD treatment, targeted the pro-inflammatory cytokine, tumor necrosis factor alpha (TNFα). Infliximab, adalimumab, and other anti-TNF antibodies neutralize TNFα, preventing interactions with its receptors and reducing the inflammatory response. However, up to 40% of people with IBD become unresponsive to anti-TNFα therapy. Thus, more recent biologics have been designed to block leukocyte trafficking to the inflamed intestine by targeting integrins and adhesins. For example, natalizumab targets the α4 chain of integrin heterodimers, α4β1 and α4β7, on leukocytes. However, binding of α4β1 is associated with increased risk for developing progressive multifocal leukoencephalopathy, an often-fatal disease, and thus, it is not used to treat IBD. To target leukocyte infiltration without this life-threatening complication, vedolizumab was developed. Vedolizumab specifically targets the α4β7 integrin and was approved to treat IBD based on the presumption that it would block T-cell recruitment to the intestine. Though vedolizumab is an effective treatment for IBD, some studies suggest that it may not block T-cell recruitment to the intestine and its mechanism(s) of action remain unclear. Vedolizumab may reduce inflammation by blocking recruitment of T-cells, or pro-inflammatory monocytes and dendritic cells to the intestine, and/or vedolizumab may lead to changes in the programming of innate and acquired immune cells dampening down inflammation.

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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
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 head0.015
GPT teacher head0.265
Teacher spread0.250 · 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

Citations79
Published2021
Admission routes2
Has abstractyes

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