卵巢癌患者血清的拉曼光谱研究初探

目的:探究拉曼光谱技术应用于卵巢癌研究的可能性。方法:收集卵巢癌患者血清及健康人血清各20例,用激光共聚焦显微拉曼光谱仪进行检测。结果:两组血清的平均拉曼光谱形态和谱峰基本相似,但在约1010、1158、1283、1520、1646、2307和2661cm-17个拉曼频移附近,卵巢癌患者血清的拉曼光谱谱峰强度明显低于健康对照组,而在其余大部分波段,卵巢癌患者血清的拉曼光谱强度均高于健康对照组。结论:拉曼光谱技术可以初步区分卵巢癌及健康人血清,值得进一步研究和探讨其临床应用价值。     

胃癌与萎缩性胃炎的血清拉曼光谱数据分析

利用激光诱导拉曼光谱技术,测定了萎缩性胃炎患者、胃癌患者血清的拉曼光谱。采用主成分分析法和判别分析法对拉曼光谱数据进行了分析和处理,得到辨别胃癌和萎缩性胃炎的准确率为92％。     

胃癌患者手术前后血清的激光拉曼光谱研究

为了探讨胃癌患者血清光谱在手术前后的变化及临床应用价值,用光谱法分别检测了30例胃癌细胞培养液、20例健康人血清和41例胃癌患者手术前、后血清的激光拉曼光谱。结果表明细胞培养液的拉曼光谱与空白对照有明显不同,且峰值与培养时间增成正相关;胃癌患者血清的拉曼光谱与健康人有显著差异;手术后胃癌患者血清的拉曼光谱峰值比术前明显降低。研究表明拉曼光谱可以作为胃癌细胞体外研究的检测手段,并有潜力成为胃癌筛查、预后监测及疗效判断的新方法。     

利用主成分分析法分析乳腺癌术后患者的血清表面增强拉曼光谱

为了探寻一种利用血清光谱检测诊断乳腺癌术后复发转移的方法,研究分析了10例乳腺癌术后复发转移患者与10例乳腺癌术后复查正常患者的血清表面增强拉曼光谱特征。首先从两组血清表面增强拉曼光谱特征峰的位移与峰强的变化上进行比较,发现其分子结构发生变化,脂类的有序性,糖质环境都发生了改变。然后基于Matlab,采用主成分分析法（Principal Component Analysis,PCA）,对上述两组患者血清的表面增强拉曼光谱的13个指标进行分析,发现区分两组患者的效果可以达到95%左右。     

胃癌血清的表面增强拉曼光谱研究

表面增强拉曼光谱技术在癌症诊断领域已经有了广泛的研究和应用,本文利用金纳米溶胶为增强基底,采用便携式近红外拉曼光谱系统,对89例胃癌患者及正常人血清样本进行了SERS光谱探测。结果表明,血清的特征峰主要归属于氨基酸,其次是核酸、糖类及脂类。相比于正常人血清SERS光谱,胃癌血清中归属于核酸的特征峰强度都较高,大部分归属于蛋白质的特征峰强度较低,与医学研究结论相符。说明SERS技术可以有效地反映胃癌患者和正常人血清的差异,为后期SERS技术快速诊断胃癌提供了实验基础。     

拉曼光谱检测胃癌变信号的研究

利用激光拉曼光谱对胃癌患者血清及非胃癌患者血清进行对比检测,并结合对体外培养胃癌细胞分泌物的检测,对胃癌特征拉曼峰作初步探讨。得出一种有重要临床应用价值的癌症辅助快速诊断方法。     

拉曼光谱技术在肿瘤检测中的应用

癌症是威胁人类健康和生命的严重疾病之一,早期诊断与及时治疗是提高癌症患者生存率的最有效途径。激光拉曼光谱技术作为一种非侵入性的检测技术,可以无损伤地提供丰富的分子结构特征和物质成分信息,从分子水平上反映癌变组织与正常组织之间的结构差异,从而可用于癌症的早期诊断。综述了激光拉曼光谱技术在皮肤癌、鼻咽癌、肺癌、胃癌、结肠癌、乳腺癌及前列腺癌诊断中的研究进展,并对拉曼光谱技术在癌症诊断中的发展方向和应用前景作了进一步的展望,为癌症的早期检测和诊断技术的应用研究提供参考依据。     

拉曼光谱在胃癌诊断中的应用与研究进展

拉曼光谱是一种分子振动光谱技术,具有分子水平的肿瘤检测和诊断能力.胃癌是常见恶性肿瘤,经常到晚期才得到诊断,死亡率较高,而早期胃癌预后较好,因此胃癌早期检测和诊断显得尤为重要.文章介绍了拉曼光谱用于胃癌早期检测和诊断的应用,并综述其研究进展,结果认为拉曼光谱探针与内镜整合,将实现胃癌活体检测和诊断,极具临床应用价值.     

葡萄糖异构酶的纯化和拉曼光谱

采用Streptomyces rosechromagenusNo.336细胞丙酮干粉,经抽提、DEAE-纤维素和DEAE-Sephsdex A-50层析,Sephadex G-200凝胶过滤,得到了电泳纯的葡萄糖异构酶,以这种均一态酶测定了其激光拉曼光谱。     

体外联合使用指纹区及高波数区拉曼光谱诊断胃癌

目的:研究正常胃粘膜和胃癌组织在拉曼光谱指纹区(800-1 800 cm-1)和高波数区(2 800-3 000 cm-1)的光谱特征,并将其联合使用建立胃癌诊断模型。方法:收集38例正常胃粘膜和37例胃癌组织活检标本,采用785 nm激发光拉曼光谱仪进行拉曼光谱采集。比较正常胃粘膜和胃癌组织在指纹区和高波数区的拉曼光谱异同,使用偏最小二乘判别分析(PLS-DA)结合留一法交叉验证建立诊断模型。结果:1)胃癌组织在853 cm~(-1),879cm~(-1),1 003 cm~(-1),1 047 cm~(-1),1 173 cm-1,1 304 cm~(-1),1 319 cm~(-1),1 338 cm~(-1),1 374 cm-1、2 932 cm-1谱峰处与正常胃粘膜的拉曼峰强度差异有统计学意义(P0.05)2)将拉曼光谱指纹区和高波数区联合,利用PLS-DA建立胃癌诊断模型的敏感性为94.59%(35/37),特异性为86.84(33/38),正确率为90.6%(68/75)。结论:正常胃粘膜和胃癌组织在拉曼光谱指纹区和高波数区均有显著差异,将上述两区联合使用建立模型诊断胃癌能取得良好的诊断效果。     

Deciphering the finger Prints of Brain Cancer Astrocytoma in comparison to Astrocytes by using near infrared Raman Spectroscopy

To explore the biochemical differences between brain cancer cells Astrocytoma and normal cells Astrocyte, we investigated the Raman spectra of single cell from these two cell types and analyzed the difference in spectra and intensity. Raman spectrum shows the banding pattern of different compounds as detected by the laser. Raman intensity measures the intensity of these individual bands. The Raman spectra of brain cancer cells was similar to those of normal cells, but the Raman intensity of cancer cells was much higher than that of normal cells. The Raman spectra of brain cancer Astrocytoma shows that the structural changes of cancer cells happen so that many biological functions of these cells are lost. The results indicate that Raman spectra can offer the experimental basis for the cancer diagnosis and treatment.     

拉曼光谱检测微生物的研究方法和进展北大核心

快速准确地识别和鉴定微生物对于环境科、食品质量以及医学诊断等领域研究至关重要。拉曼光谱(Raman spectroscopy)已经被证明是一种能够实现微生物快速诊断的新技术,在提供微生物指纹图谱信息的同时,能够快速、非标记、无创、敏感地在固体和液体环境中实现微生物单细胞水平的检测。本文简单介绍了拉曼光谱的基本概念和原理,重点综述了拉曼光谱微生物检测应用中的样品处理方法及光谱数据处理方法。除此之外,本文概括了拉曼光谱在细菌、病毒和真菌中的应用,其中单独概括了拉曼在细菌快速鉴定和抗生素药敏检测中的应用。最后,本文阐述了拉曼光谱在微生物检测中的挑战和展望。     

Discrimination of normal, benign, and malignant breast tissues by Raman spectroscopy

Breast cancers are the leading cancers among females. Diagnosis by fine needle aspiration cytology (FNAC) is the gold standard. The widely practiced screening method, mammography, suffers from high false positive results and repeated exposure to harmful ionizing radiation. As with all other cancers survival rates are shown to heavily depend on stage of the cancers (Stage 0, 95%; Stage IV, 75%). Hence development of more reliable screening and diagnosis methodology is of considerable interest in breast cancer management. Raman spectra of normal, benign, and malignant breast tissue show significant differences. Spectral differences between normal and diseased breast tissues are more pronounced than between the two pathological conditions, malignant and benign tissues. Based on spectral profiles, the presence of lipids (1078, 1267, 1301, 1440, 1654, 1746 cm(-1)) is indicated in normal tissue and proteins (stronger amide I, red shifted DeltaCH2, broad and strong amide III, 1002, 1033, 1530, 1556 cm(-1)) are found in benign and malignant tissues. The major differences between benign and malignant tissue spectra are malignant tissues seem to have an excess of lipids (1082, 1301, 1440 cm(-1)) and presence of excess proteins (amide I, amide III, red shifted DeltaCH2, 1033, 1002 cm(-1)) is indicated in benign spectra. The multivariate statistical tool, principal components analysis (PCA) is employed for developing discrimination methods. A score of factor 1 provided a reasonable classification of all three tissue types. The analysis is further fine-tuned by employing Mahalanobis distance and spectral residuals as discriminating parameters. This approach is tested both retrospectively and prospectively. The limit test, which provides the most unambiguous discrimination, is also considered and this approach clearly discriminated all three tissue types. These results further support the efficacy of Raman spectroscopic methods in discriminating normal and diseased breast tissues.