Multiwavelength Surface-Enhanced Raman Scattering Fingerprints of Human Urine for Cancer Diagnosis DOI
Yuqing Gu,

Jiayi Wang,

Zhewen Luo

et al.

ACS Sensors, Journal Year: 2024, Volume and Issue: 9(11), P. 5999 - 6010

Published: Oct. 18, 2024

Label-free surface-enhanced Raman spectroscopy (SERS) is capable of capturing rich compositional information from complex biosamples by providing vibrational spectra that are crucial for biosample identification. However, increasing complexity and subtle variations in biological media can diminish the discrimination accuracy traditional SERS excited a single laser wavelength. Herein, we introduce multiwavelength approach combined with machine learning (ML)-based classification to improve human urine specimens bladder cancer (BCa) diagnosis. This strategy leverages excitation-wavelength-dependent spectral profiles matrices, which mainly attributed wavelength-related changes individual analytes differences variation ratios intensity across different wavelengths among various analytes. By fingerprints under multiple excitation wavelengths, acquire more comprehensive unique chemical on samples. Further experimental examinations clinical specimens, supported ML algorithms, demonstrate effectiveness this diagnostic BCa staging its invasion numbers wavelengths. The holds promise as convenient, cost-effective, broadly applicable technique precise identification matrices diagnosis diseases based body fluids.

Language: Английский

Molecule-resolvable SERSome for metabolic profiling DOI

Xinyuan Bi,

Xiaohang Qian,

Bingsen XUE

et al.

Chem, Journal Year: 2025, Volume and Issue: unknown, P. 102528 - 102528

Published: April 1, 2025

Citations

0
Advancements in the Application of the Intersection of Medicine and Engineering in Cancer Research DOI Creative Commons
Haitao Chen,

Guan-Meng Zhang,

Yuping Qian

et al.

Published: April 7, 2025

ABSTRACT Cancer research predominantly centers on diagnosis, treatment, and elucidation of underlying mechanisms. Nevertheless, the intricate nature tumor genesis development has rendered early diagnostic therapeutic outcomes less than optimal, making conquest a formidable challenge. The interdisciplinary fusion medicine engineering, termed “intersection engineering”, emerged as groundbreaking paradigm, offering novel avenues for advancing cancer studies. As this approach evolves, it yielded numerous breakthroughs in mechanistic exploration. In review, we summarize how intersection engineering propels progress by leveraging combined strengths medicine, bioinformatics, materials science, artificial intelligence. This addresses limitations traditional diagnostics therapies, such low sensitivity, poor efficacy, significant side effects, challenges associated with Moreover, highlight global cutting‐edge advancements potential future directions field.

Language: Английский

Citations

0
Ultrafast Laser-Induced 1T′/2H-MoTe2 Nanopattern with Au-Nanoclusters for Raman Monitoring of Cellular Drug Metabolism DOI
Yao Yao, Yang Zhao, Huijuan Zhang

et al.

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

Published: April 17, 2025

The development of surface-enhanced Raman spectroscopy (SERS) as an ultrasensitive fingerprint analysis technique in precision medicine requires high-performance SERS substrates with controllable nanostructure (hot-spot) distribution, simple fabrication, superior stability, biocompatibility, and extraordinary optical responses. Unfortunately, fabrication arbitrary nanostructures high homogeneity on a large scale for is still challenging. Herein, we report ultrafast laser parallel protocol Au/2D-transition-metal dichalcogenide hybrid biosensors. leveraged photonic nanojets (PNJs) are generated by micron-sized microsphere monolayer to simultaneously trigger localized phase transition 2H-MoTe2, achieving 1T'-MoTe2 nanopattern array density 1 million per mm2 single shot. Au nanoparticle clusters (AuNCs) subsequently grown situ from the 1T' regions, creating AuNCs 1T'/2H-MoTe2 (AuNCs@1T'/2H-MoTe2) substrate. fabricated feature diameter overlay accuracy patterned 210.1 ± 3.4 9.2 1.7 nm, respectively. To eliminate background noise, designed dimer-AuNCs@1T'/2H-MoTe2 (dAuNCs@1T'/2H-MoTe2), detection limit 10-13 M enhancement factor 4.9 × 108 methylene blue (MB) analyte. strong surface plasmon resonances dAuNCs well efficient charge transfers between Au, MB contribute majority enhancement. multiscale dAuNCs@1T'/2H-MoTe2 provides powerful SERSome (comprising multiple spectra) platform therapeutic drug monitoring, which successfully identified metabolic behaviors living gastric adenocarcinoma cells administered two drugs, i.e., capecitabine, oxaliplatin, their combination. present work establishes opportunities highly ordered cell metabolism cancer therapy.

Language: Английский

Citations

0
Monitoring kinetic processes of drugs and metabolites: Surface-enhanced Raman spectroscopy DOI

Zhewen Luo,

Hao Chen,

Xinyuan Bi

et al.

Advanced Drug Delivery Reviews, Journal Year: 2024, Volume and Issue: unknown, P. 115483 - 115483

Published: Dec. 1, 2024

Language: Английский

Citations

3
Transcriptome-aligned metabolic profiling by SERSome reflects biological changes following mesenchymal stem cells expansion DOI Creative Commons

Xinyuan Bi,

Bin Ma, Wei Liu

et al.

Stem Cell Research & Therapy, Journal Year: 2024, Volume and Issue: 15(1)

Published: Dec. 18, 2024

Mesenchymal stem cells (MSCs) are widely applied in the treatment of various clinical diseases and field medical aesthetics. However, MSCs exhibit greater heterogeneity limited stability, more complex molecular mechanistic characteristics compared to conventional drugs, making rapid precise monitoring challenging. Surface-enhanced Raman spectroscopy (SERS) is an ultrasensitive, tractable low-cost fingerprinting technique capable identifying a wide range molecules related biological processes. Here, we employed SERS for reproducible quantification ultralow concentrations utilized spectral sets, termed SERSomes, robust comprehensive intracellular multi-metabolite profiling. We revealed that with increasing passage number, there gradual decline cell expansion efficiency, accompanied by significant changes amino acids, purines, pyrimidines. By integrating these metabolic features detected transcriptomic data, established correlation between signals changes, as well differentially expressed genes. In this study, explore application provide across different passages donors. These results demonstrate effectiveness SERSome reflecting characteristics. Due its sensitivity, adaptability, low cost, feasibility miniaturized instrumentation throughout pretreatment, measurement, analysis, label-free suitable MSC offers advantages large-scale manufacturing.

Language: Английский

Citations

2
Enhancing Nanomaterial-Based Optical Spectroscopic Detection of Cancer through Machine Learning DOI
Célia Sahli,

Kenry Kenry

ACS Materials Letters, Journal Year: 2024, Volume and Issue: 6(10), P. 4697 - 4709

Published: Sept. 18, 2024

Language: Английский

Citations

1
Multiwavelength Surface-Enhanced Raman Scattering Fingerprints of Human Urine for Cancer Diagnosis DOI
Yuqing Gu,

Jiayi Wang,

Zhewen Luo

et al.

ACS Sensors, Journal Year: 2024, Volume and Issue: 9(11), P. 5999 - 6010

Published: Oct. 18, 2024

Label-free surface-enhanced Raman spectroscopy (SERS) is capable of capturing rich compositional information from complex biosamples by providing vibrational spectra that are crucial for biosample identification. However, increasing complexity and subtle variations in biological media can diminish the discrimination accuracy traditional SERS excited a single laser wavelength. Herein, we introduce multiwavelength approach combined with machine learning (ML)-based classification to improve human urine specimens bladder cancer (BCa) diagnosis. This strategy leverages excitation-wavelength-dependent spectral profiles matrices, which mainly attributed wavelength-related changes individual analytes differences variation ratios intensity across different wavelengths among various analytes. By fingerprints under multiple excitation wavelengths, acquire more comprehensive unique chemical on samples. Further experimental examinations clinical specimens, supported ML algorithms, demonstrate effectiveness this diagnostic BCa staging its invasion numbers wavelengths. The holds promise as convenient, cost-effective, broadly applicable technique precise identification matrices diagnosis diseases based body fluids.

Language: Английский

Citations

1