ANALYST
·
2026
·
IF 3.6
Yile Yu,Xiaoyan Zhong,Xi Yu,Jinhang Li,Huihui Liu,Xin Liu,Lixia Jiang,Zongxiu Nie
Tuberculosis (TB) remains a major global health burden. Here we report a rapid, noninvasive urine-based metabolomics approach using graphdiyne (GD)-assisted laser desorption ionization mass spectrometry (LDI-MS) combined with machine learning. We applied GD-assisted LDI-TOF MS to urine samples from healthy controls (HC) and active TB patients, generating rich metabolite fingerprints. Supervised classifiers trained on the GD-assisted LDI-TOF MS spectral features achieved excellent discrimination, consistent with previous reports of Matrix-Assisted Laser Desorption Ionization-Time-of-Flight Mass Spectrometry (MALDI-TOF MS) with machine learning as a powerful screening tool. Key discriminatory urine metabolites and pathways were putatively annotated and included markers of altered energy, nucleotide, and amino-acid metabolism in TB patients, reflecting a shift in cellular energy handling and immune-related nucleotide turnover. These biochemical insights underscore TB-associated inflammatory and energetic perturbations. Overall, the GD-assisted LDI-TOF MS platform enables fast, high-throughput metabolite profiling and, when coupled with machine learning, offers a patient-friendly, noninvasive screening strategy for early TB detection and monitoring.
✓ 已验证
产品关联
DOI
PubMed
高影响因子
Journal of Pharmaceutical Analysis
·
2025
·
IF 8.9
Zhilong Chu,Xi Yu,Xiao Wang,Wenqiang Zhang,Yuming Li,Xinfeng Yan,Weining Yan,Hongzheng Meng,Lingyu Li,Guanhua Zhang,Ruya Wang,Miaomiao Li,Jun Li,Weiqiang Liang,Chunxia Ma
Worldwide, rheumatoid diseases account for approximately 37.57/100,000 disability-adjusted life years (DALYs). Early diagnosis of rheumatoid arthritis (RA) can effectively reduce associated risks and improve quality of life. To achieve this, accurate and rapid advanced tools are required. Herein, TiVCrMoC 3 , a novel high-entropy two-dimensional (2D) carbide MXene that exhibits excellent electrical conductivity, is prepared and applied to surface-assisted laser desorption ionization mass spectrometry (SALDI-MS) analysis for the first time. TiVCrMoC 3 demonstrates superior performance in small-molecule detection compared with typical inorganic and organic substrates. Moreover, its exhibits ultrahigh sensitivity (limit of detection (LOD) at the 10 pg/mL level), excellent repeatability (coefficient of variation (CV) <4%), excellent quantitative detection capability (coefficient of determination = 0.99987), clean background, and broad analyte coverage. Results showed that TiVCrMoC 3 -assisted laser desorption ionization mass spectrometry (LDI-MS) is efficient in screening RA diseases, with the advantages of high throughput and low cost. It enables accurate and quantitative analysis of various low-concentration metabolites in 1 μL of biological fluid within seconds. Combined with machine learning, TiVCrMoC 3 -assisted LDI-MS is used to accurately diagnose multiple RA samples. A total of 8 potential different small-molecule metabolites between individuals with osteoarthritis (OA) and RA were identified based on relative quantification methods, and their associated metabolic changes were discussed. TiVCrMoC 3 -assisted LDI-MS provides a potential tool for the rapid diagnosis of RA and may pave the way for precision medicine.
研究领域:
分析化学
·
代谢组学
·
风湿病学
·
转化医学
·
生物标记物
·
精准医学
·
质谱分析
✓ 已验证
产品关联
DOI
高影响因子
TALANTA
·
2021
·
IF 6.057
Tao Wang,Xingyue Liu,Xuetong Qu,Yuexin Li,Xiao Liang,Jianmin Wu
High heterogeneity of hepatocellular carcinoma (HCC) tumor has become an obstacle to select effective therapy for the treatment of HCC patients. Methods that can guide the decision on therapy choice for HCC treatment are highly demanded. Evaluating the drug response of heterogeneous tumor cells at the molecular level can help to reveal the toxicity mechanism of anticancer drugs and provide more information than current cell-based chemosensitivity assays. In the present work, nanostructure-assisted laser desorption/ionization mass spectrometry (NALDI-MS) was used to investigate the lipid response of HCC cells to anticancer drugs. Three types of HCC cells (LM3, Hep G2, Huh7) were treated with sorafenib , doxorubicin hydro-chloride, and cisplatin . We found that the lipid profiles of HCC cells changed a lot after the drug treatment, and the degree of lipid changes was related to the cell viability . Two pairs of fatty acids C16:1/C16:0 and C18:1/C18:0 were found to be strongly related to the viability of HCC cells after drug treatment, and were more sensitive than Methyl-thiazolyl tetrazolium (MTT) assay. Accordingly, they can act as sensitive and comprehensive indexes to evaluate the drug susceptibility of HCC cells. In addition, the peak ratio of several neighboring phospholipids displayed high correlation with drug response of specific cell subtype to specific drug. The ratio of neighboring lipids may be traced back to the activity of enzyme and gene expression which regulate the lipidomic pathway. This method provides drug response of heterogenous tumor cells at molecular level and could be a potential candidate to precise tumor chemosensitivity assay.
研究领域:
肿瘤学
·
分析化学
·
分子生物学
·
质谱分析
·
癌症治疗
✓ 已验证
产品关联
DOI
PubMed
高影响因子
ANALYTICAL CHEMISTRY
·
2022
·
IF 8.008
Liuying He,Xiao Wang,Junyu Chen,Yuze Li,Liping Wang,Caiqiao Xiong,Zongxiu Nie
Liver cancer (LC) is the third frequent cause of death worldwide, so early diagnosis of liver cancer patients is crucial for disease management. Herein, we applied NH2-coated polystyrene@Fe3O4 magnetic beads (PS@Fe3O4–NH2 MBs) as a matrix material in laser desorption/ionization mass spectrometry (LDI-MS). Rapid, sensitive, and selective metabolic profiling of the native biofluids was achieved without any inconvenient enrichment or purification. Then, based on the selected m/z features, LC patients were discriminated from healthy controls (HCs) by machine learning, with the high area under the curve (AUC) values for urine and serum assessments (0.962 and 0.935). Moreover, initial-diagnosed and subsequent-visited LC patients were also differentiated, which indicates potential applications of this method in early diagnosis. Furthermore, among these identified compounds by FT-ICR MS, the expression level of some metabolites changed from HCs to LCs, including 29 and 12 characteristic metabolites in human urine and serum samples, respectively. These results suggest that PS@Fe3O4–NH2 MBs-assisted LDI-MS coupled with machine learning is feasible for LC clinical diagnosis.
研究领域:
医学
·
分析化学
·
肿瘤学
✓ 已验证
产品关联
DOI
PubMed
高影响因子
ANALYTICA CHIMICA ACTA
·
2022
·
IF 6.911
Yuanqing Luo,Xiaoyong Zhao,Zhan Gao,Huiwen Wang,Yaqing Liu,Cheng Guo,Yuanjiang Pan
Oligosaccharides play a key role in many biological functions, and the accurate identification of oligosaccharide structures is an important prerequisite for a comprehensive understanding of the biological functions of oligosaccharides. MALDI-TOF/TOF tandem mass spectrometry has been considered as a potential technique for the structural characterization of oligosaccharides. In this work, palladium nanoparticles decorated thiol-functionalized metal organic framework nanocomposite (UiO-66-(SH) 2 @Pd NPs) was fabricated as an efficient matrix to assist laser desorption/ionization mass spectrometry (LDI-MS) for oligosaccharides analysis. The ionization efficiency of oligosaccharides was significantly improved owning to the synergistic effect of MOF and Pd nanoparticles, which is favorable for further oligosaccharide structure identification. By combining LDI-LIFT-TOF/TOF, 24 oligosaccharide isomers including disaccharides, trisaccharides and tetrasaccharides, were effectively distinguished. In addition, the relative quantification curves for isomeric oligosaccharides were established with good linear correlations. The method was successfully applied to the identification and quantification of sucrose and maltose in three batches of Asian ginseng and American ginseng respectively, showing potentiality of MOF materials and metal nanomaterials assisted structural analysis of oligosaccharide isomers.
研究领域:
分析化学
·
质谱学
·
纳米技术
·
生物化学
✓ 已验证
产品关联
DOI
PubMed
高影响因子
JOURNAL OF PROTEOME RESEARCH
·
2021
·
IF 4.466
Xinrong Jiang,Fengbin Gao,Xiaoming Chen,Yanlan Yu,Guoqing Ding,Jianmin Wu
More and more evidence has proved that urinary metabolites can instantly reflect disease state. Therefore, ultra-sensitive and reproducible detection of urinary metabolites in a high-throughput way is urgently desirable for clinical diagnosis. Matrix-free laser desorption/ionization mass spectrometry (LDI-MS) is a high-throughput platform for metabolites detection, but it is encountered by severe interference from numerous salts in urine samples, because the crystallized urine salt on dried samples could result in poor reproducibility in LDI-MS detection. The present work proposed a tip–contact extraction (TCE) technique to eliminate interference from the urine salt. Vertical silicon nanowire arrays decorated with the fluorinated ethylene propylene film (FEP@VSiNWs) could effectively extract metabolites from the urine sample dropping on its surface. High salt tolerance was observed in the subsequent LDI-MS detection of the metabolites extracted on the tip of FEP@VSiNWs even in the presence of 1 M urea. Stable and reproducible mass spectra for non-target metabolic analysis were obtained in real urine samples with different dilution folds. Urinary metabolites collected from bladder cancer (BC) patients were reliably profiled by the TCE method coupled with negative LDI-MS. Based on this platform, potential metabolic biomarkers that can distinguish BC patients and normal controls were uncovered.
研究领域:
分析化学
·
医学诊断
·
质谱技术
✓ 已验证
DOI
高影响因子
ANALYTICAL AND BIOANALYTICAL CHEMISTRY
·
2019
·Vol. 411
·期 30
·8081-8089
·
IF 3.286
Ma Yankai,Nie Bei
Correlated spectroscopic analysis can provide complementary chemical insights that are often unattainable by either approach used in isolation. We distinguished the different self-assembling behavior of isomeric aminothiophenols (ATPs) on Ag dendrite by the correlation of surface-enhanced Raman spectroscopy and laser-induced desorption ionization mass spectrometry, demonstrating that steric effect impinged significantly upon surface molecular density and plasmon-driven catalytic reaction yield, which led to drastic variations in the resulting SERS spectra. The correlative measurement shows that ortho -substitute barely formed a self-assemble monolayer, relative to the para -isomer, which can form a close-packed self-assembled monolayer and perform a decent azo-coupling reaction. Comparison between normal and SERS spectra of ATP isomers supports the fact that additional disulfide- or hydrogen-bonding interactions are established in para -ATP solid crystal, but neither of ortho - nor meta -isomers. This work is expected to create a significant impact on the development of an orthogonally correlated spectroscopic tool in deciphering chemical insights and underlying reaction mechanism.
Graphical abstract
研究领域:
分析化学
·
物理化学
·
材料科学
✓ 已验证
产品关联
DOI
PubMed
高影响因子
ANALYTICA CHIMICA ACTA
·
2026
·
IF 6.1
Jialiang Wu,Junyi Hu,Jingchang Tian,Xinyi Li,Nan Wang,Yinghua Yan,Fangying Shi,Chuan-Fan Ding
Au/TOHFHs enable reproducible LDI-MS metabolic fingerprinting of cattle. • Serum metabolic signatures reveal zoonotic infection-associated changes. • Machine learning accurately classifies BTB and BRU from healthy cattle. • The strategy supports livestock surveillance and food safety monitoring. Rapid analytical methods capable of discriminating livestock diseases are highly desirable for early animal health surveillance and food-chain risk control. Herein, a gold nanoparticle-modified ternary metal oxide hierarchical flower-like heterostructures (Au/TOHFHs) was developed as a high-performance matrix for laser desorption/ionization mass spectrometry (LDI-MS)-based metabolic fingerprinting. The hierarchical architecture and plasmon-enhanced interface synergistically improved metabolite enrichment, energy utilization, and ion efficiency. Using standard metabolite solutions, the Au/TOHFHs matrix exhibited good analytical reproducibility, with coefficients of variation of 5.24−14.95% for intra-spot replicate measurements and 6.71−14.90% for inter-spot spatial sampling. Using 178 bovine serum samples, including 96 samples from cattle with bovine tuberculosis, 31 from cattle with brucellosis, and 51 healthy controls, the platform accurately distinguished bovine tuberculosis and brucellosis from healthy cattle, achieving receiver operating characteristic curve areas under the curve of 0.983 and 0.899, respectively, in independent validation. Furthermore, simplified nine-metabolite and seven-metabolite biomarker panels for bovine tuberculosis and brucellosis, respectively, retained robust predictive performance, with independent-validation areas under the curve of 0.983 and 0.958, respectively, while reducing model complexity. This strategy enables rapid, label-free, and high-throughput livestock screening from minimal serum volumes, providing a practical tool for large-scale herd surveillance and strengthening food safety management through source-level risk control. Download: Download high-res image (295KB) Download: Download full-size image
✓ 已验证
DOI
高影响因子
ANALYTICAL CHEMISTRY
·
2026
·Vol. 98
·期 29
·21399-21410
·
IF 7.3
Wang Chaoqi,Shi Mengdan,Peng Peilin,Qu Yijiao,Yu Xi,Bu Yuyin,Fu Huihui,Jin Zhean,Zhang Xiaoyong,Chen Junyu,Nie Zongxiu
Esophageal cancer represents a global
health challenge with a notably
high incidence and poor prognosis, necessitating the development of
rapid, noninvasive diagnostic methodologies. In this study, we present
a high-throughput metabolomics platform leveraging a hollow-structured
Co 3 O 4 @Au nanocomposite as a matrix for laser
desorption/ionization mass spectrometry (LDI-MS) to diagnose esophageal
cancer and differentiate it from benign esophagitis. Synthesized via
a metal–organic framework (MOF) derivation strategy followed
by the in situ reduction of gold nanoparticles, the Co 3 O 4 @Au matrix exhibits strong photoelectric properties,
high charge separation efficiency, and robust tolerance to complex
biological environments. This enables the direct, rapid extraction
of serum metabolic profiles with low background interference. Leveraging
this platform, serum metabolic profiles were acquired from a clinical
cohort of 278 participants, including 116 healthy controls, 80 patients
with esophagitis, and 82 patients with esophageal cancer. Integrated
machine learning algorithms, notably the Random Forest model, demonstrated
robust diagnostic performance, achieving a high AUC value for distinguishing
diseased individuals from healthy controls and an AUC of 0.989 for
differentiating esophageal cancer from esophagitis. Furthermore, a
streamlined diagnostic panel comprising 10 core m / z features was selected, which sustained a high
predictive accuracy (AUC = 0.978) and was biologically validated via
SHAP interpretability analysis. This work establishes a high-throughput
machine learning-driven strategy, offering a potential noninvasive
tool for the mass screening and precision differential diagnosis of
esophageal malignancies.
✓ 已验证
产品关联
DOI
PubMed
高影响因子
SmartMat
·
2026
·Vol. 7
·期 4
·e70097
·
IF 14.3
Dawei Qi,Jia Qi,Caiyun Fang,Huaqing Lin,Da Wu,Fangying Shi,Chunhui Deng
Engineering inorganic matrices with optimized photon absorption and interfacial energy transfer is pivotal for advancing laser desorption/ionization mass spectrometry (LDI-MS) toward high-fidelity metabolomic analysis. Here, we developed a metal-organic framework (MOF)-derived porous iron oxide (pFO) nanomatrix for LDI-MS-based metabolomics. The pFO exhibits strong UV absorption at 355 nm, a high specific surface area (59.7 m 2 /g), and a uniform mesoporous structure, which collectively afford low background noise, enhanced analyte signal intensity, and high analytical reproducibility (coefficient of variation < 9.2%). Using this platform, metabolic fingerprints were rapidly acquired from 269 tobacco leaf samples. Integrated with Random Forest, the approach achieved accurate discrimination of leaf stalk position (AUC = 0.962) and reliable differentiation between southwestern and southeastern production regions (AUC > 0.944). Furthermore, eight representative m / z features were identified to construct a reduced classification panel, which maintained robust predictive performance in the test set (AUC > 0.913). This study establishes MOF-derived pFO as a high-performance inorganic matrix for LDI-MS metabolomics and establishes a rapid and reproducible analytical strategy for digital classification and quality traceability of agricultural products.
✓ 已验证
产品关联
DOI
高影响因子
Environmental Science-Processes & Impacts
·
2023
·Vol. 25
·期 8
·1311-1321
·
IF 5.5
Ke Min,Shenxi Deng,Zhao Shu,Yong Li,Bo Chen,Ming Ma,Qian Liu,Guibin Jiang
Elemental carbon (EC) and organic carbon (OC) exist ubiquitously and interact mutually in the environment. Simultaneous analysis of EC and OC will greatly advance our understanding of the behavior and fate of EC and OC, but is however still a great challenge due to the lack of suitable analytical tools. Here, we report a matrix-free laser desorption/ionization mass spectrometry (LDI-MS) method capable of simultaneous analysis of EC and OC by monitoring two independent groups of specific MS fingerprint peaks. We found that EC itself can generate carbon cluster peaks in the low mass range under laser excitation, and meanwhile it can also serve as a matrix to assist the ionization of OC in LDI-MS. By using per- and polyfluoroalkyl substances (PFASs) as a typical set of OC and carbon black (CB) as a model EC, we successfully monitored the adsorption process of PFASs on CB enabled by LDI-MS. We show that hydrophobic interaction dominates the sorption of PFASs to CB, which was affected by the functional groups and carbon chain length of PFASs. Furthermore, environmental substances in water such as humic acid (HA) and surfactants can significantly affect the adsorption of PFASs on CB probably by changing the adsorption sites of CB. Overall, we demonstrate that LDI-MS offers a versatile and high-throughput tool for simultaneous analysis of EC and OC species in real environmental samples, which makes it promising for investigating the environmental behaviors and ecological risks of pollutants.
研究领域:
环境科学
·
分析化学
✓ 已验证
产品关联
DOI
PubMed
高影响因子
ADVANCED FUNCTIONAL MATERIALS
·
2024
·
IF 18.5
Jiao Wu,Yingting Wei,Chunjing Shi,Yida Huang,Zubei Hong,Wanshan Liu,Liying Gu,Ruimin Wang,Yuling Li,Jing Cao,Wen Di,Xumin Hou,Jian Liu,Kun Qian,Lihua Qiu
Engineering of materials is crucial for the advanced detection of bio-molecules, particularly in laser desorption/ionization mass spectrometry (LDI-MS). However, effective screening with enhanced LDI performance remains challenging due to the lack of engineered substrate materials. Herein, thermally engineered ferric yolk-shells are designed for enhanced metabolic screening of cervical cancer (CC) using vaginal secretion. A facile thermal engineering strategy is developed to prepare amorphous ferric yolk-shells with integrated properties. Notably, the amorphous mesoporous yolk-shells offer signal amplification up to orders of magnitude in LDI-MS for standard metabolites and diverse bio-samples. High-performance CC screening (including identification of human papillomavirus (HPV) infection, high-grade squamous intraepithelial lesion (HSIL), and CC) is achieved, with the areas under the curve of 0.842–0.963. Finally, a metabolic panel for CC screening, covering the stages of HPV, HSIL, and CC, is established. This work elucidates the LDI-MS mechanism for enhanced metabolic detection and highlights potential applications in cancer screening.
研究领域:
材料科学
·
癌症筛查
·
质谱分析
·
生物医学工程
✓ 已验证
DOI
高影响因子
危险品化学品经营许可证（带存储）