Screening of Serum Biomarkers and Establishment of a Decision Tree in Silica-Exposed Populations by Surface-Enhanced Laser Desorption Ionization Time-of-Fly Mass Spectrometry

Wang, Shixin; Zhao, Xue-Feng; Wei, Minxin; Wu, You Na; Zeng, Jiawei; Liang, Xian-Cai; Yi, Jianhua; He, Bing; Tu, Zi-Guang

doi:10.1097/jom.0b013e318058aa16

Journal of Occupational &Amp; Environmental Medicine

2007

DOI: 10.1097/jom.0b013e318058aa16

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Screening of Serum Biomarkers and Establishment of a Decision Tree in Silica-Exposed Populations by Surface-Enhanced Laser Desorption Ionization Time-of-Fly Mass Spectrometry

Shixin Wang

Xue-Feng Zhao²,

Minxin Wei³

et al.

Abstract: Special proteins/peptides may change in silica-exposed workers and these changes may be used to distinguish silica-exposed populations from the control with the proper discriminant analytical method.

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Cited by 4 publications

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Integrating routine blood biomarkers and artificial intelligence for supporting diagnosis of silicosis in engineered stone workers

Sanchez‐Morillo,

León‐Jiménez,

Guerrero‐Chanivet

et al. 2024

Bioengineering & Transla Med

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Engineered stone silicosis (ESS), primarily caused by inhaling respirable crystalline silica, poses a significant occupational health risk globally. ESS has no effective treatment and presents a rapid progression from simple silicosis (SS) to progressive massive fibrosis (PMF), with respiratory failure and death. Despite the use of diagnostic methods like chest x‐rays and high‐resolution computed tomography, early detection of silicosis remains challenging. Since routine blood tests have shown promise in detecting inflammatory markers associated with the disease, this study aims to assess whether routine blood biomarkers, coupled with machine learning techniques, can effectively differentiate between healthy individuals, subjects with SS, and PMF. To this end, 107 men diagnosed with silicosis, ex‐workers in the engineered stone (ES) sector, and 22 healthy male volunteers as controls not exposed to ES dust were recruited. Twenty‐one primary biochemical markers derived from peripheral blood extraction were obtained retrospectively from clinical hospital records. Relief‐F features selection technique was applied, and the resulting subset of 11 biomarkers was used to build five machine learning models, demonstrating high performance with sensitivities and specificities in the best case greater than 82% and 89%, respectively. The percentage of lymphocytes, the angiotensin‐converting enzyme, and lactate dehydrogenase indexes were revealed, among others, as blood biomarkers with significant cumulative importance for the machine learning models. Our study reveals that these biomarkers could detect a chronic inflammatory status and potentially serve as a supportive tool for the diagnosis, monitoring, and early detection of the progression of silicosis.

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Integrating routine blood biomarkers and artificial intelligence for supporting diagnosis of silicosis in engineered stone workers

Sanchez‐Morillo,

León‐Jiménez,

Guerrero‐Chanivet

et al. 2024

Bioengineering & Transla Med

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Current literature in mass spectrometry

2008

J. Mass Spectrom.

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In order to keep subscribers up‐to‐date with the latest developments in their field, John Wiley & Sons are providing a current awareness service in each issue of the journal. The bibliography contains newly published material in the field of mass spectrometry. Each bibliography is divided into 11 sections: 1 Reviews; 2 Instrumental Techniques & Methods; 3 Gas Phase Ion Chemistry; 4 Biology/Biochemistry: Amino Acids, Peptides & Proteins; Carbohydrates; Lipids; Nucleic Acids; 5 Pharmacology/Toxicology; 6 Natural Products; 7 Analysis of Organic Compounds; 8 Analysis of Inorganics/Organometallics; 9 Surface Analysis; 10 Environmental Analysis; 11 Elemental Analysis. Within each section, articles are listed in alphabetical order with respect to author (4 Weeks journals ‐ Search completed at 30th. Jan. 2008)

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Effect of NaCl and sucrose tastants on protein composition of oral fluid analysed by SELDI-TOF-MS

Silletti

Bult

Stieger

2012

Archives of Oral Biology

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Screening of Serum Biomarkers and Establishment of a Decision Tree in Silica-Exposed Populations by Surface-Enhanced Laser Desorption Ionization Time-of-Fly Mass Spectrometry

Abstract: Special proteins/peptides may change in silica-exposed workers and these changes may be used to distinguish silica-exposed populations from the control with the proper discriminant analytical method.

Cited by 4 publications

References 17 publications

Integrating routine blood biomarkers and artificial intelligence for supporting diagnosis of silicosis in engineered stone workers

Integrating routine blood biomarkers and artificial intelligence for supporting diagnosis of silicosis in engineered stone workers

Current literature in mass spectrometry

Effect of NaCl and sucrose tastants on protein composition of oral fluid analysed by SELDI-TOF-MS

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