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Record W4388946636 · doi:10.3389/fphys.2023.1256440

Association between “cluster of differentiation 36 (CD36)” and adipose tissue lipolysis during exercise training: a systematic review

2023· review· en· W4388946636 on OpenAlexaff
El Mokhtar El Ouali, Laurent Bosquet, Boutaina Elgharbaoui, Fatiha Laziri, Ismail Laher, Anthony C. Hackney, Azeddine Ibrahimi, Bouchra Taïb, Sanae El Harane, Katja Weiss, Beat Knechtle, Abdelhalem Mesfioui, Hassane Zouhal

Bibliographic record

VenueFrontiers in Physiology · 2023
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle metabolism and nutrition
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCD36Adipose tissueLipolysisInternal medicineEndocrinologyFatty acidMedicineBiologyBiochemistryReceptor

Abstract

fetched live from OpenAlex

Fatty acid translocase (FAT/CD36) is a transmembrane glycoprotein belonging to the scavenger class B receptor family and is encoded by the cluster of differentiation 36 (CD36) gene. This receptor has a high affinity for fatty acids and is involved in lipid metabolism. An abundance of FAT/CD36 during exercise occurs in mitochondria and solitary muscles. As such, we aimed to systematically review the evidence for the relationship FAT/CD36 and adipose tissue lipolysis during exercise training. Five electronic databases were selected for literature searches until June 2022: PubMed, Web of Science, Scopus, science direct, and Google Scholar. We combined the different synonyms and used the operators (“AND”, “OR”, “NOT”): (CD36 gene) OR (CD36 polymorphism) OR (cluster of differentiation 36) OR (FAT/CD36) OR (fatty acid translocase) OR (platelet glycoprotein IV) OR (platelet glycoprotein IIIb) AND (adipose tissue lipolysis) OR (fatty acids) OR (metabolism lipid) OR (adipocytes) AND (physical effort) OR (endurance exercise) OR (high-intensity training). All published cross-sectional, cohort, case-control, and randomized clinical trials investigating CD36 polymorphisms and adipose tissue lipolysis during exercise in subjects (elite and sub-elite athletes, non-athletes, sedentary individuals and diabetics), and using valid methods to measure FAT/CD36 expression and other biomarkers, were considered for inclusion in this review. We initially identified 476 publications according to the inclusion and exclusion criteria, and included 21 studies investigating FAT/CD36 and adipose tissue lipolysis during exercise in our systematic review after examination of titles, abstracts, full texts, and quality assessments using the PEDro scale. There were nine studies with male-only participants, three with female-only participants, and nine studies included both female and male participants. There were 859 participants in the 21 selected studies. Studies were classified as either low quality (n = 3), medium quality (n = 13), and high quality (n = 5). In general, the data suggests an association between FAT/CD36 and adipose tissue lipolysis during exercise training. Improvements in FAT/CD36 were reported during or after exercise in 6 studies, while there were no changes reported in FAT/CD36 in 4 studies. An association between fat oxidation and FAT/CD36 expression during exercise was reported in 7 studies. No agreement was reached in 5 studies on FAT/CD36 content after dietary changes and physical interventions. One study reported that FAT/CD36 protein expression in muscle was higher in women than in men, another reported that training decreased FAT/CD36 protein in insulin-resistant participants, while another study reported no differences in FAT/CD36 in young, trained individuals with type 2 diabetes. Our analysis shows an association between FAT/CD36 expression and exercise. Furthermore, an association between whole-body peak fat oxidation and FAT/CD36 expression during exercise training was demonstrated. Systematic Review Registration: [PROSPERO], identifier [CRD42022342455]

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)0.021
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.012
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.021
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0080.006
Bibliometrics0.0120.014
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.020
GPT teacher head0.279
Teacher spread0.258 · 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 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

Citations7
Published2023
Admission routes1
Has abstractyes

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