Kaempferol promotes non-small cell lung cancer cell autophagy via restricting Met pathway.

BACKGROUND: Kaempferol is extracted from Hedyotis diffusa, exerting an obvious anti-cancer effect. Here in the present study, we explored the anti-cancer effects and mechanism of kaempferol in non-small cell lung cancer cell (NSCLC). PURPOSE: Our objective is to figure out the molecular mechanism by which kaempferol promotes autophagy in NSCLC cells. STUDY DESIGN: A549 and H1299 NSCLC cell lines were used for in vitro experiments. And BALB/c nude mice of NSCLC were used to perform in vivo experiments. METHODS: For in vitro experiments, CCK-8 and EdU assay was used to observe the effect of kaempferol on NSCLC cell proliferation. Confocal microscopy of mCherry-EGFR-LC3 assay and electron microscopy assay were used to detect NSCLC cell autophagy. Protein expression was determined using Western blot, and mRNA expression was determined using qRT-PCR. Flow cytometry was performed to detect the cell apoptosis. For in vivo experiments, a subcutaneously implanted tumor model in BALB/C nude mice was performed using human NSCLC cell line A549-Luc. The kaempferol effect on NSCLC mice model was detected by measuring the tumor weight and bioluminescence intensity. Immunohistochemistry was done to measure the key protein expression from mice tumor tissues. RESULTS: Our results confirmed that kaempferol inhibited NSCLC cell proliferation significantly. And it promoted NSCLC cell autophagy, leading to NSCLC cell death. Interestingly, Met-was greatly inhibited at both protein and mRNA levels. Meanwhile, PI3K/AKT/mTOR signaling pathway was inhibited accordingly. Furthermore, overexpressing Met-reversed the effect of kaempferol on NSCLC cell viability and cell autophagy with significance. Finally, the above effect and pathway were validated using the xenograft model. CONCLUSION: Kaempferol may exert its anti-NSCLC effect by promoting NSCLC cell autophagy. Mechanistically, Met-and its downstream PI3K/AKT/mTOR signaling pathway were involved in the process, which provides a novel mechanism how kaempferol functions in inhibiting NSCLC.

Positive Role of Chinese Herbal Medicine in Cancer Immune Regulation.

Complementary and alternative medicine (CAM) plays a critical role in treating cancer patients. Traditional Chinese Medicine (TCM) is the main component of CAM. TCM, especially Chinese Herbal Medicine (CHM), has been increasingly used in China, some other Asian countries and European countries. It has been proven to enhance the efficacy of chemotherapy, radiotherapy, targeted-therapy, and immunotherapy. It lessens the damage caused by these therapies. CHM functions on cancer by inhibiting tumor progression and improving an organism's immune system. Increasing evidence has shown that many CHM exert favorable effects on the immune regulation. We will summarize the role of CHM on patient's immune system when treating cancer patients. Our evidence reveals that single herbs, including their extracts, compound formulations, and preparations, will provide current advances on CHM study, especially from the perspective of immune regulation and novel insights for CHM application in clinic. The main herbs used to treat cancer patients are health-strengthening (Fu-Zheng) herbs and pathogen eliminating (Qu-Xie) herbs. The key mechanism is regulating the immune system of cancer patients. Firstly, health-strengthening herbs are mainly functioned as immune regulatory effectors on cancer. Secondly, some of the compound formulations mainly strengthen the health of patients by regulating the immune system of cancer patients. Lastly, some Chinese medicine preparations are widely used to treat cancer for their properties of spiriting vital energy and anti-cancer effects, mainly by improving immunity. CHM plays a positive role in regulating patients' immune system, which helps cancer patients to fight against cancer itself and finally improves patients' life quality.

[Research on prediction method of fatty acid content in edible oil based on Raman spectroscopy and multi-output least squares support vector regression machine].

For the purpose of the rapid prediction of saturated fatty acid, oleic acid, linoleic acid content in edible vegetable oil, the Raman spectra of a batch of edible vegetable oils and their one-one mixtures with different ratios were measured in the range of 800-2 000 cm(-1), 91 samples were measured totally in this research, the obtained Raman spectra data were preprocessed by a new method proposed in this paper called auto-set fulcrums baseline fitting method based on peak-seeking algorithm, and 8 characteristic peak values (872 cm(-1) [v(C-C)], 972 cm(-1) [delta(C=C) trans], 1 082 cm(-1) [v(C-C)], 1 267 cm(-1) [delta(=C-H) cis], 1 303 cm(-1) [delta(CH2) twisting], 1 442 cm(-1) [delta(CH2) scissoring], 1 658 cm(-1) [v(C=C) cis], 1 748 cm(-1) [v(C=O)]) were extracted to be the eigenvalues for the whole spectra, among the 8 peaks there are three peaks (972, 1 267, 1 658 cm(-1)) that play an important role in the establishment of mathematical model, they are closely concerned with C=C band which distinguishes the three fatty acid types. By using these eigenvalues as inputs, and actual saturated fatty acid, oleic acid, linoleic acid contents of sample oils as outputs, a prediction mathematical model that predicts simultaneously the three fatty acid contents was established using multiple regression analysis: multi-output least squares support vector regression machine (MLS-SVR) and partial least squares (PLS). Results show that the MLS-SVR has better effects. The predicting results are compared with results of gas chromatography(GC), and the obtained root mean square error of prediction(RMSEP) for saturated fatty acid, oleic acid, linoleic acid are 0.496 7%, 0.840 0% and 1.019 9%, and the correlation coefficients (r) are 0.813 3, 0.999 2 and 0.998 1, respectively. When this model is applied in the detection of new unknown oil samples, the prediction error does not exceed 5%. Results show that the Raman spectra analysis technology based on MLS-SVR can be a convenient, fast, non-destructive, and precise new method for oil detection.