MétaCan
Menu
Back to cohort

Inflammatory Molecular Mediators and Pathways Involved inVascular Aging and Stroke: A Comprehensive Review

2021· review· en· W3198754973 on OpenAlexaff
Amro M. Soliman, Srijit Das, Pasuk Mahakkanukrauh

Bibliographic record

VenueCurrent Medicinal Chemistry · 2021
Typereview
Languageen
FieldImmunology and Microbiology
TopicAtherosclerosis and Cardiovascular Diseases
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPathogenesisInflammationStroke (engine)MedicineBioinformaticsExtant taxonSignal transductionMyocardial infarctionVascular diseaseMechanism (biology)NeuroscienceImmunologyBiologyInternal medicineGenetics

Abstract

fetched live from OpenAlex

There is an increase in the incidence of cardiovascular diseases with aging and it is one of the leading causes of death worldwide. The main cardiovascular pathologies include atherosclerosis, myocardial infarction, hypertension and stroke. Chronic inflammation is one of the significant contributors to the age-related vascular diseases. Therefore, it is important to understand the molecular mechanisms of the persistent inflammatory conditions occurring in the blood vessels as well as the signaling pathways involved. Herein, we performed an extant search of literature involving PubMed, ISI, WoS and Scopus databases for retrieving all relevant articles with the most recent findings illustrating the potential role of various inflammatory mediators along with their proposed activated pathways in the pathogenesis and progression of vascular aging. We also highlight the major pathways contributing to age-related vascular disorders. The outlined molecular mechanisms, pathways and mediators of vascular aging represent potential drug targets that can be utilized to inhibit and/or slow the pathogenesis and progression of vascular aging.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.876
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.037
GPT teacher head0.288
Teacher spread0.251 · 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 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

Citations5
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueCurrent Medicinal ChemistrySame topicAtherosclerosis and Cardiovascular DiseasesFrench-language works237,207