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Record W4380423265 · doi:10.1002/ptr.7916

A comprehensive insight into the molecular effect of theobromine on cardiovascular‐related risk factors: A systematic review of in vitro and in vivo studies

2023· review· en· W4380423265 on OpenAlexaff
Elham Sharifi‐Zahabi, Fatemeh Hajizadeh‐Sharafabad, Seyed Mostafa Nachvak, Soheila Mirzaian, Sahar Darbandi, Farzad Shidfar

Bibliographic record

VenuePhytotherapy Research · 2023
Typereview
Languageen
FieldMedicine
TopicAdipokines, Inflammation, and Metabolic Diseases
Canadian institutionsUniversity of WinnipegUniversity of Manitoba
Fundersnot available
KeywordsTheobromineLipid profileMedicineAnimal studiesPharmacologyIn vivoTriglycerideCholesterolCaffeineInternal medicineBiologyBiotechnology

Abstract

fetched live from OpenAlex

Theobromine may have beneficial effects on cardiovascular risk factors. This study aimed to find molecular effects of theobromine on lipid profile, glycemic status, inflammatory factors, and vascular function through a comprehensive assessment of all in vitro and in vivo studies. The search process was started at 18 July 2022. Databases including PubMed, Scopus, and Web of Science were searched to find all articles published up to 18 July 2022. Nineteen studies were included in this study. In vitro studies showed the improving effects of theobromine on inflammatory markers. Of four animal studies assessing the effect of theobromine on inflammatory markers, two reported favorable effects. Among five animal studies assessing the effects of theobromine on lipid profile, three reported improving effects on either triglyceride, total cholesterol, low- or high-density lipoprotein cholesterol. Of the three human studies, two revealed that theobromine had improving effects on lipid profile. A favorable effect of theobromine on augmentation index was also reported in two RCTs. The results for other outcomes were inconclusive. Theobromine may have favorable effects on inflammatory factors, lipid profile, and vascular function markers. However, studies with a longer duration and lower, dietary-relevant doses are required for future confirmation.

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)0.005
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.026
Threshold uncertainty score0.892

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0060.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
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 head0.078
GPT teacher head0.414
Teacher spread0.336 · 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 designSystematic review
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

Citations9
Published2023
Admission routes1
Has abstractyes

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