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Record W4382984572 · doi:10.3389/fimmu.2023.1219907

TNF superfamily control of tissue remodeling and fibrosis

2023· review· en· W4382984572 on OpenAlexfundno aff
Hope Steele, Jason Cheng, Ashley Willicut, Garrison Dell, Joey Breckenridge, Erica Culberson, Andrew Ghastine, Virginie Tardif, Rana Herro

Bibliographic record

VenueFrontiers in Immunology · 2023
Typereview
Languageen
FieldMedicine
TopicInterstitial Lung Diseases and Idiopathic Pulmonary Fibrosis
Canadian institutionsnot available
FundersPraesperoCancerFree KIDSCincinnati Children's Hospital Medical Center
KeywordsFibrosisExtracellular matrixMedicineCancer researchInflammationClinical trialBioinformaticsImmunologyPathologyBiologyCell biology

Abstract

fetched live from OpenAlex

Fibrosis is the result of extracellular matrix protein deposition and remains a leading cause of death in USA. Despite major advances in recent years, there remains an unmet need to develop therapeutic options that can effectively degrade or reverse fibrosis. The tumor necrosis super family (TNFSF) members, previously studied for their roles in inflammation and cell death, now represent attractive therapeutic targets for fibrotic diseases. In this review, we will summarize select TNFSF and their involvement in fibrosis of the lungs, the heart, the skin, the gastrointestinal tract, the kidney, and the liver. We will emphasize their direct activity on epithelial cells, fibroblasts, and smooth muscle cells. We will further report on major clinical trials targeting these ligands. Whether in isolation or in combination with other anti-TNFSF member or treatment, targeting this superfamily remains key to improve efficacy and selectivity of currently available therapies for fibrosis.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.973
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.023
GPT teacher head0.299
Teacher spread0.276 · 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 teacher head, not a consensus.

Study designOther design
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

Citations73
Published2023
Admission routes1
Has abstractyes

Explore more

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