Evidence map›Paper›PMID 40301448›Full record

ArticleScientific reports2025

Analytical validation of total mucin concentration assay using SEC MALLS dRI for diagnosing and monitoring mucoobstructive lung diseases.

Esin Ozkan, Stephanie Sue Livengood, Amina Ahmad Ford, Jade Kathryn Macdonald, Sophia Samir, Ian William Klevans, Mehmet Kesimer

Abstract readValidation Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. 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

7 authors.

Esin Ozkan *Department of Pathology and Laboratory Medicine, Marsico Lung Institute, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27517-7248, USA.
Stephanie Sue Livengood *Department of Pathology and Laboratory Medicine, Marsico Lung Institute, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27517-7248, USA.
Amina Ahmad FordDepartment of Pathology and Laboratory Medicine, Marsico Lung Institute, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27517-7248, USA.
Jade Kathryn MacdonaldDepartment of Pathology and Laboratory Medicine, Marsico Lung Institute, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27517-7248, USA.
Sophia SamirDepartment of Pathology and Laboratory Medicine, Marsico Lung Institute, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27517-7248, USA.
Ian William KlevansDepartment of Pathology and Laboratory Medicine, Marsico Lung Institute, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27517-7248, USA.
Mehmet KesimerDepartment of Pathology and Laboratory Medicine, Marsico Lung Institute, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27517-7248, USA. kesimer@med.unc.edu.

Funding

SPIROMICS II: Biological underpinnings of COPD heterogeneity and progressionU01HL137880 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI WOODRUFF, PRESCOTT G · 2017 to 2021
$27.9M
Project 4: Biophysical and structural characterization of airway submucosal gland mucus in health and diseaseP01HL164320 · NHLBI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Richard Charles Boucher, Michael Rubinstein · 2022 to 2026
$13.9M
Airway mucus/mucin composition and proteome in COPD: A SPIROMICS ancillary studyR01HL110906 · NHLBI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI KESIMER, MEHMET · 2011 to 2014
$1.4M
NHLBI NIH HHS P01 HL164320NHLBI NIH HHS R01 HL110906NHLBI NIH HHS U01 HL137880
6 · The paper itself

Abstract

Mucins play a pivotal role in the pathophysiology of mucoobstructive lung diseases. Accurate quantification of total mucin concentrations in clinical sputum samples is critical for developing objective biomarkers for diagnosis, prognosis, and therapeutic monitoring. By using sputum samples and mucin standards, the analytical performance of the measurements of total mucin concentration by Size Exclusion Chromatography coupled with Multi-Angle Laser Light Scattering and Differential Refractometer [SEC-(MALLS)-dRI] method was assessed using universal validation metrics, including precision, accuracy, recovery, parallelism, specificity, linearity, and sample stability. Possible sample contamination sources, such as saliva, blood, and DNA, were also evaluated. The method demonstrated excellent precision across low, medium, and high concentrations (CV% ≤ 2.6%) and high recovery (116%). It exhibited strong linearity over a broad dynamic range (~30-15,000 µg/mL) and stability for up to 12 months at - 20 °C in naïve samples and 4 °C in 4 M GuHCl. Measurement interference was negligible, up to 20% saliva, 2% blood, and 2% DNA. This study validates the SEC-(MALLS)-dRI method as a robust, reliable approach for quantifying total mucin concentrations in clinical sputum samples. The demonstrated analytical validity establishes its use as a biomarker platform for clinical and research applications, aiding in the diagnosis and management of hypersecretory/mucoobstructive lung diseases.

Indexed as

Chromatography, GelLung DiseasesLung Diseases, ObstructiveMucinsBiomarkersHumansRefractometryReproducibility of ResultsSputumBiomarkersMucinsAnalytical validationMeasurement methodMucinsMucusSputum

Identifiers

PMID40301448
PMCPMC12041582

What Socratic 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 Socratic graph.