研究目的
To explore the potential of Raman spectroscopy for quantitatively monitoring changes in high molecular weight proteins in liquid plasma for disease diagnostics, optimizing measurement protocols, and addressing challenges like scattering from poorly soluble proteins.
研究成果
Raman spectroscopy, combined with appropriate pre-processing and separation techniques, can accurately detect subtle changes in protein concentrations in aqueous solutions, showing promise for early disease diagnostics. The method offers advantages over traditional assays in speed and sample volume, but further validation with real clinical samples is needed.
研究不足
The study uses simulated plasma mixtures, not real human plasma, which may not fully capture clinical complexities. Scattering from fibrinogen remains a challenge, and the ion exchange method is protein-specific, not universal. Sample volumes and preparation steps could be optimized for broader applicability.
1：Experimental Design and Method Selection:
The study used Raman spectroscopy with multivariate regression (PLSR) and ion exchange chromatography for protein separation. Pre-processing methods like rubberband and EMSC were applied to handle background signals.
2：Sample Selection and Data Sources:
Simulated plasma protein mixtures were prepared with albumin, fibrinogen, cytochrome c, and vitamin B12 at physiologically relevant concentrations.
3：List of Experimental Equipment and Materials:
Equipment includes a Horiba Jobin-Yvon LabRam HR800 spectrometer, Sonics VCX-750 Vibra Cell Ultra Sonic Processor, and materials like proteins from Sigma Aldrich.
4：Experimental Procedures and Operational Workflow:
Samples were analyzed in an inverted geometry with a water immersion objective. Spectra were recorded, pre-processed, and analyzed using PLSR. Ion exchange chromatography and sonication were used for separation and dispersion improvement.
5：Data Analysis Methods:
PLSR was used for regression modeling, with cross-validation (RMSECV) to assess model performance. Pre-processing techniques were evaluated for effectiveness.
独家科研数据包，助您复现前沿成果，加速创新突破
获取完整内容
