Evidence map›Paper›PMID 42737343›Full record

ArticleFoods (Basel, Switzerland)2026

Reliable Analytical Approach for the Quantification of the Cholesterol Adsorption Capacity of Artichoke Leaves.

Shahd Ali, Federica Ianni, Lina Cossignani

Abstract read
In one paragraph

Article in Foods (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Shahd AliDepartment of Pharmaceutical Sciences, University of Perugia, Via S. Costanzo, 06126 Perugia, Italy.
Federica IanniDepartment of Pharmaceutical Sciences, University of Perugia, Via S. Costanzo, 06126 Perugia, Italy.ORCID 0000-0003-4293-3100
Lina CossignaniDepartment of Pharmaceutical Sciences, University of Perugia, Via S. Costanzo, 06126 Perugia, Italy.ORCID 0000-0003-3433-604X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Reliable determination of cholesterol adsorption capacity (CAC) is essential for evaluating the hypocholesterolemic potential of dietary fibers; however, currently available analytical procedures lack methodological standardization and often rely on spectrophotometric assays susceptible to matrix interference. The present study aimed to develop and validate a simple and reliable procedure for the evaluation of CAC of fractionated artichoke leaves. In vitro assays were conducted under simulated gastrointestinal conditions, with residual cholesterol quantified using high-performance liquid chromatography and two different detection systems (UV-Vis spectrophotometric detector and light-scattering detector). The chromatographic method was validated in terms of linearity, sensitivity, precision, and accuracy, and its performance was compared with that of the conventional ortho-phthalaldehyde (OPA) spectrophotometric assay. Some pure commercial fibers were tested first; pectin and lignin showed the highest cholesterol adsorption capacity. Moreover, the results showed that all the investigated leaf fractions exhibited CAC, with the outer leaf fractions showing significantly higher values than the inner woody fractions. The proposed workflow provides a reliable and consistent analytical framework for CAC determination. Furthermore, the results provide new insights into the potential cholesterol-lowering properties of dietary fiber from artichoke leaves, supporting their further investigation as functional ingredients.

Indexed as

artichoke leavescholesterol adsorption capacitychromatographydietary fibersplant matricesspectrophotometry

Identifiers

PMID42737343
PMCPMC13564901

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.