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Record W2236119727 · doi:10.18433/j3f61f

Non-Alcoholic Steatohepatitis: Clinical and Translational Research

2016· review· en· W2236119727 on OpenAlexaffvenue
Manuela G. Neuman, M Voiculescu, Radu M. Nanau, Ehud Melzer, Lawrence B. Cohen, Mihai Opris, Stephen Malnick

Bibliographic record

VenueJournal of Pharmacy & Pharmaceutical Sciences · 2016
Typereview
Languageen
FieldMedicine
TopicLiver Disease Diagnosis and Treatment
Canadian institutionsHealth Sciences CentreSunnybrook Health Science CentrePetro-CanadaUniversity of Toronto
Fundersnot available
KeywordsSteatohepatitisMedicineTranslational researchEnvironmental healthFatty liverInternal medicinePathologyDisease

Abstract

fetched live from OpenAlex

UNLABELLED: The present review includes translational and clinical research that characterize non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH). Clinical and experimental evidence led to the recognition of the key toxic role played by lipotoxicity in the pathogenesis of NAFLD. The current understanding of lipotoxicity suggests that organ injury is initiated by the generation of oxidative metabolites and the translocation of gut-derived endotoxin. These processes lead to cellular injury and stimulation of the inflammatory responses mediated through a variety of molecules. The injury progresses through impairment of tissue regeneration and extracellular matrix turnover, leading to fibrogenesis and cirrhosis. Several cell types are involved in this process, predominantly stellate cells, macrophages and parenchymal cells. In response to inflammation, cytokines activate many signaling cascades that regulate fibrogenesis. This examination brings together research focusing on the underlying mechanisms of injury. It highlights the various processes and molecules that are likely involved in inflammation, immune modulation, and fibrogenesis in the liver. We searched electronic databases (Medline, Embase) for this review. This integrative work investigates different aspects of liver damage and possible repair. We aim to (1) determine the immuno-pathology of liver damage due to steatosis, (2) suggest diagnostic markers of NASH, (3) examine the role of behaviour in the development of NASH, and (4) develop common tools to study steatosis-induced effects in clinical studies. Special accent is put on co-morbidities with renal and neuropsychological disorders. Moreover, we review the evidence in literature on the role of moderate alcohol consumption in individuals that present NAFLD/NASH. KEY WORDS: behavior, diet, imaging, non-alcoholic fatty liver, nonalcoholic steatohepatitis, laboratory markers.This article is open to POST-PUBLICATION REVIEW. Registered readers (see "For Readers") may comment by clicking on ABSTRACT on the issue's contents page.

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)0.006
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 score0.013
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0040.008
Science and technology studies0.0000.001
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0130.002

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 head0.490
GPT teacher head0.624
Teacher spread0.134 · 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

Citations7
Published2016
Admission routes2
Has abstractyes

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