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Mendeley readers
Attention Score in Context
| Title |
Characterization of ovarian cancer cells and tissues by Fourier transform infrared spectroscopy
|
|---|---|
| Published in |
Journal of Ovarian Research, August 2018
|
| DOI | 10.1186/s13048-018-0434-8 |
| Pubmed ID | |
| Authors |
Lei Li, Xiaoning Bi, Hengzi Sun, Simiao Liu, Mei Yu, Ying Zhang, Shifu Weng, Limin Yang, Yanan Bao, Jinguang Wu, Yizhuang Xu, Keng Shen |
| Abstract |
Ovarian cancer is the most lethal of gynecological malignancies. Fourier Transform Infrared (FTIR) spectroscopy has gradually developed as a convenient, inexpensive and non-destructive technique for the study of many diseases. In this study, FTIR spectra of normal and several heterogeneous ovarian cancer cell lines as well as ovarian cancer tissue samples were compared in the spectral region of 4000 cm- 1 - 600 cm- 1. Cell samples were collected from human ovarian surface epithelial cell line (HOSEpiC) and five ovarian cancer cell lines (ES2, A2780, OVCAR3, SKOV3 and IGROV1). Validation spectra were performed on normal and cancerous tissue samples from 12 ovarian cancer patients. FTIR spectra were collected from a NICOLET iN10 MX spectrometer and the spectral data were analyzed by OMNIC 8.0 software. Spectral features discriminating malignant tissues from normal tissues were integrated by cell line data and tissue data. In particular changes in cancerous tissues, the decrease in the amount of lipids and nucleic acids were observed. Protein conformation and composition were also altered in some cancer cells. The band intensity ratio of 1454/1400 was higher in normal cells/tissues and lower in cancer cells/tissues. The spectral features revealed the important molecular characteristics about ovarian cancer cells/tissues. These findings demonstrate the possible diagnostic use of FTIR spectroscopy, providing the research model and evidences, and supporting the future study on more tissue samples to establish a data bank of spectra features for the possible discrimination of ovarian cancers. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 44 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 44 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 7 | 16% |
| Researcher | 6 | 14% |
| Student > Master | 6 | 14% |
| Student > Bachelor | 3 | 7% |
| Student > Doctoral Student | 3 | 7% |
| Other | 3 | 7% |
| Unknown | 16 | 36% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 6 | 14% |
| Engineering | 5 | 11% |
| Chemistry | 4 | 9% |
| Agricultural and Biological Sciences | 2 | 5% |
| Chemical Engineering | 2 | 5% |
| Other | 7 | 16% |
| Unknown | 18 | 41% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 04 August 2018.
All research outputs
#20,529,173
of 23,098,660 outputs
Outputs from Journal of Ovarian Research
#441
of 604 outputs
Outputs of similar age
#288,972
of 331,122 outputs
Outputs of similar age from Journal of Ovarian Research
#18
of 20 outputs
Altmetric has tracked 23,098,660 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 604 research outputs from this source. They receive a mean Attention Score of 3.2. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 331,122 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 20 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.