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Record W2121157109 · doi:10.5539/jfr.v3n6p36

The Role of Plasminogen Activator Inhibitor-1 in the Metabolic Syndrome and Its Regulation

2014· article· en· W2121157109 on OpenAlexvenueno aff
Martha Phelan, David Kerins

Bibliographic record

VenueJournal of Food Research · 2014
Typearticle
Languageen
FieldMedicine
TopicAdipokines, Inflammation, and Metabolic Diseases
Canadian institutionsnot available
Fundersnot available
KeywordsFibrinolysisPlasminogen activator inhibitor-1EndocrinologyMetabolic syndromeInternal medicinePlasminogen activatorAdipose tissueTissue plasminogen activatorObesityMedicineDiabetes mellitus

Abstract

fetched live from OpenAlex

<p>Obesity is a major risk factor for cardiovascular disease (CVD). Lipid abnormalities, hypertension, impaired glucose tolerance or diabetes, are cardiovascular risk factors that are frequently present in patients with obesity. Haemostatic and fibrinolytic disturbances are also considered to be important risk factors for CVD hence, a potential link between CVD, obesity and the metabolic syndrome arises. Regulation of the fibrinolytic system can occur at the level of plasminogen activators and plasminogen activator inhibitor-1 (PAI-1). PAI-1, a glycoprotein, is one of the most important inhibitors of fibrinolysis. Regulation of this serine protease inhibitor may have a beneficial effect on other conditions associated with the metabolic syndrome. Human adipose tissue is a source of PAI-1. PAI-1 production may in turn be controlled by a number of hormones and cytokines which are secreted by adipose tissue in addition to dietary factors. In this review we summarise the current knowledge regarding the role of altered fibrinolytic function in obesity, CVD and hence the metabolic syndrome. Regulatory factors including different dietary components, weight loss and dietary intervention will also be discussed.</p>

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.693
Threshold uncertainty score0.174

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.033
GPT teacher head0.320
Teacher spread0.287 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations9
Published2014
Admission routes1
Has abstractyes

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