scholarly journals Gold Nanorods for Ovarian Cancer Detection with Photoacoustic Imaging and Resection GuidanceviaRaman Imaging in Living Mice

ACS Nano ◽  
2012 ◽  
Vol 6 (11) ◽  
pp. 10366-10377 ◽  
Author(s):  
Jesse V. Jokerst ◽  
Adam J. Cole ◽  
Dominique Van de Sompel ◽  
Sanjiv S. Gambhir
Author(s):  
Diana Žilovič ◽  
Rūta Čiurlienė ◽  
Ieva Vaicekauskaitė ◽  
Rasa Sabaliauskaitė ◽  
Sonata Jarmalaitė

Tumor Biology ◽  
1999 ◽  
Vol 20 (2) ◽  
pp. 88-98 ◽  
Author(s):  
Hirotoshi Tanimoto ◽  
Lowell J. Underwood ◽  
Kazushi Shigemasa ◽  
Tim H. Parmley ◽  
Yinxiang Wang ◽  
...  

2016 ◽  
Vol 2016 ◽  
pp. 1-6 ◽  
Author(s):  
Jiang Wu ◽  
Yanju Ji ◽  
Ling Zhao ◽  
Mengying Ji ◽  
Zhuang Ye ◽  
...  

Background. Surfaced-enhanced laser desorption-ionization-time of flight mass spectrometry (SELDI-TOF-MS) technology plays an important role in the early diagnosis of ovarian cancer. However, the raw MS data is highly dimensional and redundant. Therefore, it is necessary to study rapid and accurate detection methods from the massive MS data.Methods. The clinical data set used in the experiments for early cancer detection consisted of 216 SELDI-TOF-MS samples. An MS analysis method based on probabilistic principal components analysis (PPCA) and support vector machine (SVM) was proposed and applied to the ovarian cancer early classification in the data set. Additionally, by the same data set, we also established a traditional PCA-SVM model. Finally we compared the two models in detection accuracy, specificity, and sensitivity.Results. Using independent training and testing experiments 10 times to evaluate the ovarian cancer detection models, the average prediction accuracy, sensitivity, and specificity of the PCA-SVM model were 83.34%, 82.70%, and 83.88%, respectively. In contrast, those of the PPCA-SVM model were 90.80%, 92.98%, and 88.97%, respectively.Conclusions. The PPCA-SVM model had better detection performance. And the model combined with the SELDI-TOF-MS technology had a prospect in early clinical detection and diagnosis of ovarian cancer.


2020 ◽  
Vol 159 ◽  
pp. 79-80
Author(s):  
M. Mikami ◽  
K. Tanabe ◽  
K. Matsuo ◽  
M. Ikeda ◽  
M. Hayashi ◽  
...  

Molecules ◽  
2020 ◽  
Vol 25 (19) ◽  
pp. 4471
Author(s):  
Lara G. Freidus ◽  
Pradeep Kumar ◽  
Thashree Marimuthu ◽  
Priyamvada Pradeep ◽  
Viness Pillay ◽  
...  

Synthesis of a novel theranostic molecule for targeted cancer intervention. A reaction between curcumin and lawsone was carried out to yield the novel curcumin naphthoquinone (CurNQ) molecule (2,2′-((((1E,3Z,6E)-3-hydroxy-5-oxohepta-1,3,6-triene-1,7-diyl) bis(2-methoxy-4,1-phenylene))bis(oxy))bis(naphthalene-1,4-dione). CurNQ’s structure was elucidated and was fully characterized. CurNQ was demonstrated to have pH specific solubility, its saturation solubility increased from 11.15 µM at pH 7.4 to 20.7 µM at pH 6.8. This pH responsivity allows for cancer targeting (Warburg effect). Moreover, CurNQ displayed intrinsic fluorescence, thus enabling imaging and detection applications. In vitro cytotoxicity assays demonstrated the chemotherapeutic properties of CurNQ as CurNQ reduced cell viability to below 50% in OVCAR-5 and SKOV3 ovarian cancer cell lines. CurNQ is a novel theranostic molecule for potential targeted cancer detection and treatment.


RSC Advances ◽  
2019 ◽  
Vol 9 (29) ◽  
pp. 16863-16868 ◽  
Author(s):  
Yui Umehara ◽  
Toki Kageyama ◽  
Aoi Son ◽  
Yu Kimura ◽  
Teruyuki Kondo ◽  
...  

Tumor-selective accumulation of gold nanorods (GNR) has been demonstrated for visualization of tumor hypoxia by photoacoustic imaging.


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