Gold-Modified Covalent Organic Frameworks-Assisted Laser Desorption/Ionization Mass Spectrometry for Analysis of Metabolites Induced by Triclosan Exposure

ACS Applied Materials & Interfaces, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 17, 2025

Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry (MS) holds great promise for the rapid and sensitive detection of biomolecules, but its precise small molecule metabolites is hindered by severe background interference from organic matrix in low molecular weight range. To address this issue, nanomaterials have commonly been utilized as substrates LDI-MS. Among them, covalent frameworks (COFs), known their unique optical absorption structural properties, garnered significant attention. Despite these advantages, ionization efficiency remains a challenge. Herein, composite material COF-S@Au nanoparticles (NPs), incorporating Au NPs into sulfur-functionalized COF (COF-S) through postsynthetic modification, was designed adopted substrates. This hybrid leverages synergistic effects COF-S to improve minimize interference. The demonstrated 5-16-fold improvement MS signals biomolecules along with clean excellent resistance salt protein Their corresponding limits (LODs) were achieved at ∼pmol. Furthermore, applied analyze triclosan (TCS)-exposed mouse model, successfully identifying 10 differential associated TCS toxicity. work provides foundation developing advanced LDI-MS materials high-performance metabolic analysis offers valuable insights toxicity potential applications environmental toxicology.

Language: Английский

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Energy-Confinement 3D Flower-Shaped Cages for AI-Driven Decoding of Metabolic Fingerprints in Cardiovascular Disease Diagnosis

ACS Nano, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 7, 2025

Rapid and accurate detection plays a critical role in improving the survival prognosis of patients with cardiovascular disease, but traditional methods are far from ideal for those suspected conditions. Metabolite analysis based on nanomatrix-assisted laser desorption/ionization mass spectrometry (NMALDI-MS) is considered to be promising technique disease diagnosis. However, performance core nanomatrixes has limited its clinical application. In this study, we constructed 3D flower-shaped cages controllable structured metal-organic frameworks iron oxide nanoparticles low thermal conductivity significant photothermal effects. The elongation incident light path through multilayer reflection significantly enhances effective absorption area nanomatrixes. Concurrently, alternating layered structure confines energy, reducing losses. Moreover, increases affinity sites, expanding coverage. This approach effectively ionization desorption efficiency during LDI process. We applied technology analyze serum metabolomes myocardial infarction, heart failure, failure combined achieving cost-effective, high-throughput, highly accurate, user-friendly diseases. Subsequently, deep detected fingerprints via artificial intelligence models screens potential metabolic biomarkers, providing new paradigm diagnosis

Language: Английский

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From Nanozymes to Multi‐Purpose Nanomaterials: The Potential of Metal–Organic Frameworks for Proteomics Applications

Advanced Healthcare Materials, Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 9, 2024

Abstract Metal‐organic frameworks (MOFs) have the potential to revolutionize biotechnological and medical landscapes due their easily tunable crystalline porous structure. Herein, study presents MOFs' impact on proteomics, unveiling diverse roles MOFs can play boost it. Although are excellent catalysts in other scientific disciplines, role as proteomics applications remains largely underexplored, despite protein cleavage being of crucial importance protocols. Additionally, discusses evolving MOF materials that tailored for showcasing structural diversity functional advantages compared types used similar applications. be developed seamlessly integrate into workflows features, contributing separation, peptide enrichment, ionization mass spectrometry. This review is meant a guide help bridge gap between material scientists, engineers, chemists side researchers biology or bioinformatics working proteomics.

Language: Английский

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Template synthesis of CoFe-modified TiO2 for highly selective enrichment of phosphatides

Microchemical Journal, Journal Year: 2025, Volume and Issue: unknown, P. 113300 - 113300

Published: March 1, 2025

Language: Английский

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Cost‐Effective Identification of Hepatocellular Carcinoma from Cirrhosis or Chronic Hepatitis Virus Infection Using Eight Methylated Plasma DNA Markers

Advanced Science, Journal Year: 2025, Volume and Issue: unknown

Published: March 26, 2025

Early detection of hepatocellular carcinoma (HCC) in patients with liver cirrhosis (LC) and/or hepatitis virus B/C infection (HVI) improves survival, highlighting the need for accurate, affordable diagnostic tools. Here, 11 methylated DNA markers (MDMs) are identified during marker discovery. In phase I, each selected MDM is validated 175 plasma samples (HCC, n = 85; LC/HVI, 72) by CO-methylation aMplification rEal-Time PCR (COMET) assay. Of these, 8 MDMs qualified II study, where a logistic regression model (COMET-LR) trained and 336 211; 113; training vs validation, 2:1). COMET-LR achieved 90.0% sensitivity at 97.4% specificity. Notably, TNM stage diameter<3 cm, AFP-negative (<20 ng mL-1), PIVKA-II-negative (<40 mAU mL-1) 82.4%, 77.8%, 88.6%, 85.7%, respectively. The outperformed multiple protein (AFP, AFP-L3, PIVKA-II) published scores HCC screening (GALAD, Doylestown, ASAP), terms both assay represents significant advancement addressing unmet non-invasive, accessible, cost-effective early tools LC/HVI individuals. Further validation prospective cohort warranted.

Language: Английский

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Energy band engineered nanomatrix assisted mass spectrometry for metabolite detection

Journal of Colloid and Interface Science, Journal Year: 2025, Volume and Issue: unknown, P. 137499 - 137499

Published: April 1, 2025

Language: Английский

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Nanomaterials as Novel Matrices to Improve Biomedical Applications of MALDI-TOF/MS

Talanta, Journal Year: 2025, Volume and Issue: unknown, P. 128092 - 128092

Published: April 1, 2025

Language: Английский

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A deep learning framework for enhanced mass spectrometry data analysis and biomarker screening

Computer Methods in Biomechanics & Biomedical Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 13

Published: April 15, 2025

Mass spectrometry (MS) serves as a powerful analytical technique in metabolomics. Traditional MS analysis workflows are heavily reliant on operator experience and prone to be influenced by complex, high-dimensional data. This study introduces deep learning framework designed enhance the classification of complex data facilitate biomarker screening. The proposed integrates preprocessing, classification, selection, addressing challenges analysis. Experimental results demonstrate significant improvements tasks compared other machine approaches. Additionally, peak-preprocessing module is validated for its potential screening, identifying biomarkers from

Language: Английский

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An integrated platform for decoding hydrophilic peptide fingerprints of hepatocellular carcinoma using artificial intelligence and two-dimensional nanosheets

Journal of Materials Chemistry B, Journal Year: 2024, Volume and Issue: 12(31), P. 7532 - 7542

Published: Jan. 1, 2024

Hydrophilic peptides (HPs) play a critical role in the pathogenesis of hepatocellular carcinoma (HCC). However, comprehensive and in-depth high-throughput analysis specific changes HPs associated with HCC remains unrealized, due to complex nature biological fluids challenges mining patterns large data sets. The clinical diagnosis still lacks non-destructive accurate classification method, given limited specificity widely used biomarkers. To address these challenges, we have established multifunctional platform that integrates artificial intelligence computation, hydrophilic interaction extraction HPs, MALDI-MS testing. This aims achieve highly sensitive HP fingerprinting for HCC. method not only facilitates efficient detection but also achieves remarkable 100.00% diagnostic accuracy test cohort, supported by machine learning algorithms. By constructing panel 10 characteristic features, achieved 98% cohort rapid identified 62 deeply involved pathways related liver diseases. integrated strategy provides new research directions future biomarker studies as well early individualized treatment

Language: Английский

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Laser Desorption/Ionization on Au@TiO2 Core@Shell Nanostars for Mass Spectrometric Analysis of Small Molecules

Nanomaterials, Journal Year: 2024, Volume and Issue: 14(23), P. 1946 - 1946

Published: Dec. 4, 2024

The core@shell nanostars composed of star-like Au nanocores with TiO

Language: Английский

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