Rationale: Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOFMS) is frequently used to analyze homo- and copolymers, i.e. for computing copolymer fingerprints. However, the oligomer abundances are influenced by mass discrimination, i.e. mass- and composition-dependent ionization. We have developed a computational method to correct the abundance bias caused by the mass discrimination.

Methods: MALDI-TOFMS in combination with computational methods was used to investigate three random copolymers with different ratios of styrene and isoprene. Furthermore, equimolar high- and low-mass styrene and isoprene homopolymers (2500 and 4200 Da) were mixed and also analyzed by MALDI-TOFMS. The abundances of both copolymers and homopolymers were corrected for mass discrimination effects with our new method.

Results: The novel computational method was integrated into the existing COCONUT software. The method was demonstrated using the measured styrene and isoprene co- and homopolymers. First, the method was applied to homopolymer spectra. Subsequently, the copolymer fingerprint was computed from the copolymer MALDI mass spectra and the correcting function applied. The changes in the composition are plausible, indicating that correction of copolymer abundances was reasonable.

Conclusions: Our computational method may help to avoid erroneous conclusions when analyzing copolymer MS spectra. The software is freely available and represents a step towards comprehensive computational support in polymer science. Copyright © 2016 John Wiley & Sons, Ltd.

Download full-text PDF

Source
http://dx.doi.org/10.1002/rcm.7553DOI Listing

Publication Analysis

Top Keywords

mass discrimination
12
computational method
12
styrene isoprene
12
discrimination effects
8
mass spectra
8
mass
7
copolymer
5
computational
5
method
5
abundance correction
4

Similar Publications

Spontaneous intracranial artery dissection (sIAD) is the leading cause of stroke in young individuals. Identifying high-risk sIAD cases that exhibit symptoms and are likely to progress is crucial for treatment decision-making. This study aimed to develop a model relying on circulating biomarkers to discriminate symptomatic sIADs.

View Article and Find Full Text PDF

Chronic kidney disease (CKD) is expected to become the fifth leading cause of death globally by 2040. Cardiovascular disease (CVD), particularly heart failure (HF), is a severe complication in CKD patients on hemodialysis. This study aimed to develop a nomogram to predict the risk of heart failure hospitalization in hemodialysis patients, providing a valuable tool for clinical decision-making.

View Article and Find Full Text PDF

Background Feeding and growth during infancy have been associated with later life body mass index and early excessive weight gain is associated with obesity later on. This study aimed to assess the effect of feeding in the first two years of life on the body composition of children at the preschool age and detect the importance of using bioelectrical impedance (BIA) analysis in identifying individuals at risk of overweight and obesity. Methods A cross-sectional study included 160 children.

View Article and Find Full Text PDF

Electronic circular dichroism (ECD) spectra contain key information about molecular chirality by discriminating the absolute configurations of chiral molecules, which is crucial in asymmetric organic synthesis and the drug industry. However, existing predictive approaches lack the consideration of ECD spectra owing to the data scarcity and the limited interpretability to achieve trustworthy prediction. Here we establish a large-scale dataset for chiral molecular ECD spectra and propose ECDFormer for accurate and interpretable ECD spectrum prediction.

View Article and Find Full Text PDF

Exhaled Breath Analysis Using a Novel Electronic Nose for Different Respiratory Disease Entities.

Lung

January 2025

Department of Internal Medicine, National Taiwan University Hospital, No.7, Chung Shan S. Rd., Zhongzheng District, Taipei City, 100225, Taiwan.

Purpose: Electronic noses (eNose) and gas chromatography mass spectrometry (GC-MS) are two important breath analysis approaches for differentiating between respiratory diseases. We evaluated the performance of a novel electronic nose for different respiratory diseases, and exhaled breath samples from patients were analyzed by GC-MS.

Materials And Methods: Patients with lung cancer, pneumonia, structural lung diseases, and healthy controls were recruited (May 2019-July 2022).

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!