Dasatinib in combination with BMS-754807 induce synergistic cytotoxicity in lung cancer cells through inhibiting lung cancer cell growth, and inducing autophagy as well as cell cycle arrest at the G1 phase

Lung cancer is the leading cause of cancer-related deaths worldwide. Combination of drugs targeting independent signaling pathways would effectively block the proliferation of cancer cells with lower concentrations and stronger synergy effects. Dasatinib, a multi-targeted protein tyrosine kinase inhibitor targeting BCR-ABL and kinases of SRC family, has been successfully applied in the treatment of chronic myeloid leukemia (CML). BMS-754807, an inhibitor targeting the insulin-like growth factor 1 receptor (IGF-IR) and insulin receptor (IR) family kinases, has been in phase I development for the treatment of a variety of human cancers. Herein, we demonstrated that dasatinib in combination with BMS-754807 inhibited lung cancer cell growth, while induced autophagy as well as cell cycle arrest at the G1 phase. Dasatinib in combination with BMS-754807 suppressed the expression of cell cycle marker proteins, Rb, p-Rb, CDK4, CDK6 and Cyclin D1, and the PI3K/Akt/mTOR signaling pathway. Dasatinib in combination with BMS-754807 induced autophagy in lung cancer cells, evidenced by the upregulation of LC3B II and beclin-1, the downregulation of LC3B I and SQSTM1/p62, and the autophagic flux observed with a confocal fluorescence microscopy. Furthermore, dasatinib (18 mg/kg) in combination with BMS-754807 (18 mg/kg) inhibited the growth of tumors in NCI-H3255 xenografts without changing the bodyweight. Overall, our results suggest that dasatinib in combination with BMS-754807 inhibits the lung cancer cell proliferation in vitro and tumor growth in vitro, which indicates promising evidence for the application of the drug combination in lung cancer therapy.

In vivo experimental study on the resistance and stiffness of orbital suspension tissues with/without the extraocular muscles

BACKGROUND

The accuracy of the surgical amount of extraocular muscle (EOM) is key to the success of strabismus surgery. To establish an accurate eye movement model, it is of great theoretical value and clinical significance to determine the surgical amount of EOM. At present, only resistance and stiffness data of orbital suspension tissues with EOMs exist, while those of orbital suspension tissues without EOMs, which is critical information for eye movement modeling, have not been reported. The aim of this research is to study the resistance and stiffness of orbital suspension tissues with/without EOMs.

METHODS

Fifteen healthy New Zealand white rabbits with body weights of 2.41 ± 0.13 kg were used in the study. Two recti (two horizontal recti of the left eye or two vertical recti of the right eye) or all EOMs were detached from each eye under general anesthesia. Then, a 5-0 silk suture was attached to the stump of the detached rectus insertion (two horizontal recti insertions of the left eye and two vertical recti insertions of the right eye) on the isolated eyeball. The 5-0 silk suture was connected to the INSTRON 5544 tester to facilitate the horizontal rotations of the left eyes and the vertical rotations of the right eyes, respectively.

RESULTS

The resistance and stiffness of orbital suspension tissues with superior rectus, inferior rectus, superior oblique, and inferior oblique EOMs were obtained during horizontal eye movement. Similarly, the resistance and stiffness of orbital suspension tissues with lateral rectus, medial rectus, superior oblique, and inferior oblique EOMs were obtained during vertical eye movement. Then, the resistance and stiffness of orbital suspension tissues without EOMs were obtained during horizontal and vertical eye movements. The resistance and stiffness data of orbital suspension tissues with EOMs were compared with those of orbital suspension tissues without EOMs. The comparison results showed no significant difference in the resistance values between these two cases. In addition, the stiffness values of these two cases statistically differed.

CONCLUSIONS

The two horizontal recti play a major role in passive horizontal eye movement. In addition, when the eye is passively moved vertically, the two vertical recti play major roles. The stiffness of orbital suspension tissues with EOMs, which has been used in eye movement modeling, is not accurate. The results of this work may serve as a reference for improving the accuracy in eye movement modeling, and then it will be beneficial for determining the surgical amount of EOMs in clinical surgery.

Extraction of Sensitive Bands for Monitoring the Winter Wheat (Triticum aestivum) Growth Status and Yields Based on the Spectral Reflectance

To extract the sensitive bands for estimating the winter wheat growth status and yields, field experiments were conducted. The crop variables including aboveground biomass (AGB), soil and plant analyzer development (SPAD) value, yield, and canopy spectra were determined. Statistical methods of correlation analysis, partial least squares (PLS), and stepwise multiple linear regression (SMLR) were used to extract sensitive bands and estimate the crop variables with calibration set. The predictive model based on the selected bands was tested with validation set. The results showed that the crop variables were significantly correlated with spectral reflectance. The major spectral regions were selected with the B-coefficient and variable importance on projection (VIP) parameter derived from the PLS analysis. The calibrated SMLR model based on the selected wavelengths demonstrated an excellent performance as the R2, TC, and RMSE were 0.634, 0.055, and 843.392 for yield; 0.671, 0.017, and 1.798 for SPAD; and 0.760, 0.081, and 1.164 for AGB. These models also performed accurately and robustly by using the field validation data set. It indicated that these wavelengths retained in models were important. The determined wavelengths for yield, SPAD, and AGB were 350, 410, 730, 1015, 1185 and 1245 nm; 355, 400, 515, 705, 935, 1090, and 1365 nm; and 470, 570, 895, 1170, 1285, and 1355 nm, respectively. This study illustrated that it was feasible to predict the crop variables by using the multivariate method. The step-by-step procedure to select the significant bands and optimize the prediction model of crop variables may serve as a valuable approach. The findings of this study may provide a theoretical and practical reference for rapidly and accurately monitoring the crop growth status and predicting the yield of winter wheat.