RESUMO
Basing on the wavelengths with consistent and stable spectral signals between spectrometers, wavelength combinations were screened by different methods to obtain robust and simple near infrared spectra (NIR) calibration models that can be shared by slave spectrometers directly. Firstly, the wavelength set of Usc, at which the spectral signals between spectrometers are consistent and stable, was obtained by the method of screening the wavelengths with consistent and stable signals between spectrometers (SWCSS for short). Then, the wavelength set of Uscr whose spectral responses are correlated with dependent variables strongly was selected from Usc. Basing on Uscr, the methods of uninformative variable elimination (UVE), variable importance in projection (VIP) and selectivity ratio (SR) were applied to further screen optimal wavelength sets to obtain better NIR calibration models. These sets were recorded as UscrUVE, UscrVIP and UscrSR, respectively. The NIR partial least squares (PLS) models for predicting total alkaloids content of tobacco leaves were built on the three optimal wavelength sets, and named as UscrUVE-PLS, UscrVIP-PLS, UscrSR-PLS, respectively. Both UscrUVE-PLS and UscrVIP-PLS give satisfactory prediction errors for master and slave samples, and work better than the PLS model built on the whole wavelengths (WW-PLS) after piecewise direct standardization (PDS) calibration. The results show that further optimizing wavelength combinations based on consistent and stable spectral information cannot only simplify PLS models and improve the models' efficiency, but also ensure the models' accuracy when they are transferred to slave spectrometers. Wavelength selection based on the whole wavelengths without considering spectra consistency between spectrometers can improve the performance of the calibration models on the master spectrometer but cannot ensure the prediction accuracy of the slave samples.
RESUMO
BACKGROUND: Carcinoembryonic antigen related cell adhesion molecule 6 (CEACAM6) is a versatile glycoprotein and a member of the CEACAM family. Studies suggested that it served as a diagnostic and prognostic biomarker in some malignancies. In addition, it is involved in tumorigenesis by stimulating proliferation, suppressing apoptosis, facilitating migration and invasion, promoting angiogenesis, and inducing drug resistance. In the present study, we demonstrated the oncogenic effects of CEACAM6 in clear cell renal cell carcinoma (ccRCC). METHODS: CEACAM6 expression was detected by quantitative real-time PCR (qRT-PCR), immunohistochemical staining and western blot in ccRCC tumor tissues and cell lines. Survival analysis was performed using the data of TCGA database. Cell proliferation and migration were detected by CCK-8 and transwell assays with the overexpression or silencing of CEACAM6. LY294002 was used to block the activation of PI3K/AKT pathway. Associated pathway proteins were detected by western blot. RESULTS: CEACAM6 was upregulated in ccRCC cell lines and tumor tissues. Longer overall survival was observed in patients with relatively low CEACAM6 levels. Furthermore, overexpression of CEACAM6 promoted the proliferation and migration of ccRCC cells. Conversely, shRNA-mediated CEACAM6 depletion modulated those changes. Further investigation demonstrated that the ERK/AKT signaling pathway activation played a pivotal role. In addition, PI3K/AKT pathway blockade abrogated the effects of CEACAM6 overexpression. CONCLUSIONS: Aberrantly high expression of CEACAM6 is a stimulus for the formation and progression of ccRCC.
