MALDI-TOF Mass Spectrometry in Clinical Analysis and Research

ACS Measurement Science Au, Journal Year: 2022, Volume and Issue: 2(5), P. 385 - 404

Published: July 27, 2022

In the decade after being awarded Nobel Prize in Chemistry 2002, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) has been widely used as an analytical chemistry tool for detection of large and small molecules (e.g., polymers, proteins, peptides, nucleic acids, amino lipids, etc.) clinical analysis research pathogen identification, genetic disorders screening, cancer diagnosis, etc.). view fast development MALDI-TOF MS usage, this review systematically summarizes most important applications by analyzing MALDI TOF MS-related reviews collected Web Science database. On basis keyword co-occurrence over 2000 articles, four themes consisting "pathogen identification", "disease diagnosis", "nucleic acids analysis", "small analysis" were found. For each theme, further outlined their application implications, methods, systems well limitations that need to be addressed. Overall, elaborates on MS, providing a comprehensive picture researchers embarking research.

Language: Английский

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Human metabolite detection by surface-enhanced Raman spectroscopy

Materials Today Bio, Journal Year: 2022, Volume and Issue: 13, P. 100205 - 100205

Published: Jan. 1, 2022

Metabolites are important biomarkers in human body fluids, conveying direct information of cellular activities and physical conditions. Metabolite detection has long been a research hotspot the field biology medicine. Surface-enhanced Raman spectroscopy (SERS), based on molecular "fingerprint" spectrum enormous signal enhancement (down to single-molecule level) by plasmonic nanomaterials, proven be novel powerful tool for metabolite detection. SERS provides favorable properties such as ultra-sensitive, label-free, rapid, specific, non-destructive processes. In this review, we summarized progress recent 10 years SERS-based sensing endogenous metabolites at level, tissues, biofluids, well drug biofluids. We made detailed discussions challenges optimization methods technique The combination with modern biomedical technology were also anticipated.

Language: Английский

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Laccase-mimicking Mn–Cu hybrid nanoflowers for paper-based visual detection of phenolic neurotransmitters and rapid degradation of dyes

Journal of Nanobiotechnology, Journal Year: 2022, Volume and Issue: 20(1)

Published: Aug. 2, 2022

Laccase-based biosensors are efficient for detecting phenolic compounds. However, the instability and high cost of laccases have hindered their practical utilization.In this study, we developed hierarchical manganese dioxide-copper phosphate hybrid nanoflowers (H-Mn-Cu NFs) as excellent laccase-mimicking nanozymes. To synthesize H-Mn-Cu NFs, dioxide (MnO2 were first synthesized by rapidly reducing potassium permanganate using citric acid. The MnO2 NFs then functionalized with amine groups, followed incubation copper sulfate three days at room temperature to drive coordination interaction between moieties ions induce anisotropic growth petals composed crystals, consequently yielding NFs. Compared those free laccase, same mass concentration, exhibited lower Km (~ 85%) considerably higher Vmax 400%), well significantly enhanced stability in ranges pH, temperature, ionic strength, periods evaluated. also catalyzed decolorization diverse dyes faster than laccase. Based on these advantageous features, a paper microfluidic device incorporating was constructed convenient visual detection neurotransmitters, including dopamine epinephrine. enabled rapid sensitive quantification target neurotransmitters an image acquired smartphone.These results clearly show that could be potential candidates replace natural wide range applications biosensing, environmental protection, biotechnology.

Language: Английский

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Designed Concave Octahedron Heterostructures Decode Distinct Metabolic Patterns of Epithelial Ovarian Tumors

Advanced Materials, Journal Year: 2023, Volume and Issue: 35(18)

Published: Feb. 10, 2023

Epithelial ovarian cancer (EOC) is a polyfactorial process associated with alterations in metabolic pathways. A high-performance screening tool for EOC high demand to improve prognostic outcome but still missing. Here, concave octahedron Mn2 O3 /(Co,Mn)(Co,Mn)2 O4 (MO/CMO) composite heterojunction, rough surface, hollow interior, and sharp corners developed record patterns of tumors by laser desorption/ionization mass spectrometry (LDI-MS). The MO/CMO composites multiple physical effects induce enhanced light absorption, preferred charge transfer, increased photothermal conversion, selective trapping small molecules. shows ≈2-5-fold signal enhancement compared mono- or dual-enhancement counterparts, ≈10-48-fold the commercialized products. Subsequently, serum fingerprints are revealed MO/CMO-assisted LDI-MS, achieving reproducibility direct detection without treatment. Furthermore, machine learning distinguishes malignant from benign controls area under curve value 0.987. Finally, seven metabolites progression screened as potential biomarkers. approach guides future depiction state-of-the-art matrix intensive MS accelerates growth nanomaterials-based platforms toward precision diagnosis scenarios.

Language: Английский

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Host–Guest Self‐Assembled Interfacial Nanoarrays for Precise Metabolic Profiling

Small, Journal Year: 2023, Volume and Issue: 19(51)

Published: Jan. 26, 2023

Abstract Accurate and rapid metabolic profiling of cerebrospinal fluid (CSF) is urgently needed but remains challenging for clinical diagnosis central nervous system diseases biomarker discovery. Matrix‐assisted laser desorption ionization mass spectrometry (MALDI‐MS) holds promise analysis. Its low signal reproducibility, however, severely restricts acquisition quantitative MS data in practice. Herein, a multifunctional self‐assembled AuNPs array (MSANA)‐based LDI‐MS platform direct amino acids analysis patient CSF samples developed. MSANA featuring highly ordered closely packed two‐dimensional nanostructure permits capture aromatic by with high selectivity micromolar sensitivity. Meanwhile, the MSANA‐based exhibits excellent reproducibility (RSD < 10%), largely outperforming matrix spotting approach widely used now 44%). The successfully (1 µL) within minutes discrimination medulloblastoma patients from non‐tumor controls. Taken together, shows potential values toward large‐scale diagnostics pathogenic mechanism study.

Language: Английский

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Self-Assembled Hyperbranched Gold Nanoarrays Decode Serum United Urine Metabolic Fingerprints for Kidney Tumor Diagnosis

ACS Nano, Journal Year: 2024, Volume and Issue: 18(3), P. 2409 - 2420

Published: Jan. 8, 2024

Serum united urine metabolic analysis comprehensively reveals the disease status for kidney diseases in particular. Thus, precise and convenient acquisition of molecular information from biofluids is vitally important clinical diagnosis biomarker discovery. Laser desorption/ionization mass spectrometry (LDI-MS) presents various advantages analysis; however, there remain challenges ionization efficiency MS signal reproducibility. Herein, we constructed a self-assembled hyperbranched black gold nanoarray (HyBrAuNA) assisted LDI-MS platform to profile serum fingerprints (S-UMFs) early stage renal cell carcinoma (RCC). The closely packed HyBrAuNA afforded strong electromagnetic field enhancement high photothermal conversion efficacy, enabling effective low abundant metabolites S-UMF collection. With uniform nanoarray, presented excellent reproducibility ensure accuracy S-UMFs obtained seconds. When it was combined with automated machine learning S-UMFs, RCC patients were discriminated healthy controls an area under curve (AUC) > 0.99. Furthermore, screened out panel 9 (4 5 urine) related pathways toward tumor. In view its high-throughput, fast analytical speed, sample consumption, our possesses potential profiling pathogenic mechanism exploration.

Language: Английский

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Early Diagnosis and Prognosis Prediction of Pancreatic Cancer Using Engineered Hybrid Core‐Shells in Laser Desorption/Ionization Mass Spectrometry

Advanced Materials, Journal Year: 2024, Volume and Issue: 36(18)

Published: Jan. 19, 2024

Abstract Effective detection of bio‐molecules relies on the precise design and preparation materials, particularly in laser desorption/ionization mass spectrometry (LDI‐MS). Despite significant advancements substrate performance single‐structured substrates remains suboptimal for LDI‐MS analysis complex systems. Herein, designer Au@SiO 2 @ZrO core‐shell are developed LDI‐MS‐based early diagnosis prognosis pancreatic cancer (PC). Through controlling Au core size ZrO shell crystallization, signal amplification metabolites up to 3 orders is not only achieved, but also synergistic mechanism LDI process revealed. The optimized enables a direct record serum metabolic fingerprints (SMFs) by LDI‐MS. Subsequently, SMFs employed distinguish PC (stage I/II) from controls, with an accuracy 92%. Moreover, prognostic prediction scoring system established enhanced efficacy predicting survival compared CA19‐9 (p < 0.05). This work contributes material‐based prognosis.

Language: Английский

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Multiscale Structured Trimetal Oxide Heterojunctions for Urinary Metabolic Phenotype‐Dependent Screening of Early and Small Hepatocellular Carcinoma

Small Methods, Journal Year: 2024, Volume and Issue: unknown

Published: March 22, 2024

Abstract Developing a standardized screening tool for the detection of early and small hepatocellular carcinoma (HCC) through urinary metabolic analysis poses challenging yet intriguing research endeavor. In this study, range intricately interlaced 2D rough nanosheets featuring well‐defined sharp edges is fabricated, with aim constructing diverse trimetal oxide heterojunctions exhibiting multiscale structures. By carefully engineering synergistic effects in composition structure, including improved adsorption, diffusion, other surface‐driven processes, optimized demonstrate substantial enhancement signal intensity compared to monometallic or bimetallic oxides, as well fragmented trimetallic oxides. Additionally, optimal enable extraction high‐quality fingerprints using high‐throughput mass spectrometry. Leveraging machine learning, discrimination HCC patients from high‐risk healthy populations achieves impressive performance, area under curve values 0.940 0.916 receiver operating characteristic precision‐recall curves, respectively. Six crucial metabolites are identified, enabling accurate early, small‐tumor, alpha‐fetoprotein‐negative (93.3%–97.3%). A comprehensive strategy tailored clinical reality yields precision metrics (accuracy, precision, recall, F1 score) exceeding 95.0%. This study advances application cutting‐edge matrices‐based phenotyping practical diagnostics.

Language: Английский

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Cross‐Referencing Multifluid Metabolic Profiles on Hollow Dodecahedral Nanocages for Enhanced Disease Status Identification

Small, Journal Year: 2025, Volume and Issue: 21(9)

Published: Feb. 5, 2025

Abstract The development of matrices has shown great potential for fluid metabolic analysis in disease detection. However, single‐fluid metabolomic been recognized as insufficient to fully capture the complexities diseases such liver disease, which limits detection accuracy. To this end, hollow dodecahedral nanocages‐based analytical tool is developed, featuring four‐high characteristics speed, throughput, efficiency, and patient compliance, enhance extraction multifluid profiles. cross‐referencing these profiles among different diseases, including hepatocellular carcinoma (HCC), chronic (CLD), healthy controls, enhances diagnosis particularly achieving near‐perfect discrimination HCC with an AUC value 0.990, significantly outperforming any single analysis. Additionally, dynamic changes expression levels key biomarkers throughout progression are explored, providing insights into their temporal evolution, highlighting role monitoring status. This work highlights that can comprehensively sensitively reflect status, enabling precise identification complex facilitating personalized treatment.

Language: Английский

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Dual-modal nanoplatform integrated with smartphone for hierarchical diabetic detection

Biosensors and Bioelectronics, Journal Year: 2022, Volume and Issue: 210, P. 114254 - 114254

Published: April 7, 2022

Language: Английский

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