Evidence map›Paper›PMID 36837816›Full record

ArticleMetabolites2023

Capacity of HDL to Efflux Cellular Cholesterol from Lipid-Loaded Macrophages Is Reduced in Patients with Familial Hypercholesterolemia.

Shiva Ganjali, Susan Hosseini, Manfredi Rizzo, Anatol Kontush, Amirhossein Sahebkar

Open access · goldAbstract read
In one paragraph

Article in Metabolites, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
3.5field-weighted citation impact, top 8% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 3 institutions in 3 countries.

Shiva GanjaliDepartment of Medical Biotechnology and Nanotechnology, Mashhad University of Medical Sciences, Mashhad, Iran.
Susan HosseiniMedical Genetics Research Center, Mashhad University of Medical Sciences, Mashhad, Iran.
Manfredi RizzoDepartment of Health Promotion, Mother and Child Care, Internal Medicine and Medical Specialties, School of Medicine, University of Palermo, 90133 Palermo, Italy.ORCID 0000-0002-9549-8504
Anatol KontushCardiovascular Diseases Research Unit, National Institute of Health and Medical Research (INSERM), Metabolism and Nutrition, ICAN, Sorbonne University, F-75013 Paris, France.
Amirhossein SahebkarBiotechnology Research Center, Pharmaceutical Technology Institute, Mashhad University of Medical Sciences, Mashhad, Iran.
Mashhad University of Medical Sciences · IRInserm · FRUniversity of Palermo · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aimed to evaluate the high-density lipoprotein (HDL) capacity to efflux cellular cholesterol from lipid-loaded macrophages to find a reliable and low-cost biomarker with the purpose of better evaluating the risk of premature cardiovascular (CV) events in FH patients. This case-controlled study comprised 16 homozygous (HOFH) and 18 heterozygous (HEFH) FH patients, as well as 20 healthy subjects recruited as controls. Two main subfractions of HDL (HDL2 (d = 1.063-1.125 g/mL) and HDL3 (d = 1.125-1.210 g/mL)) were isolated from the patients' serum samples using sequential ultracentrifugation. After compositional characterization, the capacity of HDL to efflux cholesterol (CEC%) from lipid-laden macrophages was measured. The HDL2 and HDL3 subfractions showed some differences in lipid and protein composition between the studied groups. In addition, both HDL subfractions (

Indexed as

familial hypercholesterolemiaHDL cholesterol effluxmacrophage

Identifiers

PMID36837816
PMCPMC9961594
OpenAlexW4318476681

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.