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The number of patients with kidney stones worldwide is increasing, and it is particularly important to facilitate accurate diagnosis methods. Accurate analysis of the type of kidney stones plays a crucial role in the patient's follow-up treatment. This study used microscopic Raman spectroscopy to analyze and classify the different mineral components present in kidney stones. There were several Raman changes observed for the different types of kidney stones and the four types were oxalates, phosphates, purines and L-cystine kidney stones. We then combined machine learning techniques with Raman spectroscopy. KNN and SVM combinations with PCA (PCA-KNN, PCA-SVM) methods were implemented to classify the same spectral data set. The results show the diagnostic accuracies are 96.3% for the PCA-KNN and PCA-SVM methods with high sensitivity (0.963, 0.963) and specificity (0.995,0.985). The experimental Raman spectra results of kidney stones show the proposed method has high classification accuracy. This approach can provide support for physicians making treatment recommendations to patients with kidney stones

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BackgroundProstate cancer (PCa) is one of the most common cancers in male worldwide. Oxidative stress has been recognized as one of the driving signals pathologically linked to PCa progression. Nevertheless, the association of oxidative stress with PCa progression remains unclear.MethodsWestern blot, q-RT-PCR and bioinformatics analyses were used to examine PAGE4 expression. Comet assay and Annexin V/ PI dual staining assay were performed to investigate DNA damage and cell death under oxidative stress. Mouse xenograft model of PCa cells was established to verify the role of PAGE4 in vivo. Transcriptomic analysis was performed to investigate the underlying mechanism for the function of PAGE4 under oxidative stress. Western blot assay was conducted to determine the status of MAPK pathway. Immunohistochemistry was used to identify protein expression of PAGE4 in tumor tissues.ResultsIn this study, we found that PAGE4 expression was increased in PCa cells under oxidative stress condition. PAGE4 overexpression protected PCa cells from oxidative stress-inducing cell death by reducing DNA damage. PAGE4 overexpression promoted PCa cells growth in vivo. Mechanistically, PAGE4 promoted the survival of prostate cancer cells through regulating MAPK pathway which reflected in decreasing the phosphorylation of MAP2K4, JNK and c-JUN but increasing phosphorylation of ERK1/2.ConclusionOur findings indicate that PAGE4 protects PCa cells from DNA damage and apoptosis under oxidative stress by modulating MAPK signalling pathway. PAGE4 expression may serve as a prognostic biomarker for clinical applications.Electronic supplementary materialThe online version of this article (10.1186/s13046-019-1032-3) contains supplementary material, which is available to authorized users.