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Baker, M. J.

Publications and source records attributed to Baker, M. J..

2 recordsLinked to original sources

Mechanisms of protein kinase C epsilon down-regulation by transforming growth factor-beta in lung cancer cells

Protein kinase C epsilon (PKC{varepsilon}), a diacylglycerol (DAG)/phorbol ester-regulated PKC isoform, has been widely linked to oncogenesis and metastasis. PKC{varepsilon} plays important roles in the regulation of motility and invasiveness in non-small cell lung cancer (NSCLC). We previously reported that this kinase becomes prominently down-regulated upon TGF-{beta}-induced epithelial-to-mesenchymal transition (EMT), which leads to prominent phenotypic changes. While the phorbol ester PMA causes down-regulation of PKC, {delta} and {varepsilon} within hours, TGF-{beta} requires at least 4 days to reduce the expression levels of PKC{varepsilon} without affecting the expression of other PKCs, an effect that parallels the acquisition of a mesenchymal phenotype. Despite the prominent transcriptional component involved in EMT, we found that PKC{varepsilon} down-regulation does not involve changes in PKC{varepsilon} mRNA levels and was entirely independent of transcriptional activation of the PRKCE gene. Further mechanistic analysis revealed that the reduction in PKC{varepsilon} expression is dependent on proteasomal and endolysosomal pathways, but independent of autophagy processing mechanisms. Site-directed mutagenesis of Lys312 and Lys321 in PKC{varepsilon} prevented its down-regulation in response to either TGF-{beta} or the phorbol ester PMA. The shift in PKC{varepsilon} isozyme levels depending on cell plasticity underscores relevant functional consequences by modulating the expression of this oncogenic/metastatic kinase and highlights key roles of protein stability mechanisms in the control of PKC{varepsilon} phenotypic outcomes.

cell biology

Salivary molecular spectroscopy: a rapid and non-invasive monitoring tool for diabetes mellitus during insulin treatment

Monitoring of blood glucose is an invasive, painful and costly practice in diabetes. Consequently, the search for a more cost-effective (reagent-free), non-invasive and specific diabetes monitoring method is of great interest. Attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy has been used in diagnosis of several diseases, however, applications in the monitoring of diabetic treatment are just beginning to emerge. Here, we used ATR-FTIR spectroscopy to evaluate saliva of non-diabetic (ND), diabetic (D) and diabetic 6U-treated of insulin (D6U) rats to identify potential salivary biomarkers related to glucose monitoring. The spectrum of saliva of ND, D and D6U rats displayed several unique vibrational modes and from these, two vibrational modes were pre-validated as potential diagnostic biomarkers by ROC curve analysis with significant correlation with glycemia. Compared to the ND and D6U rats, classification of D rats was achieved with a sensitivity of 100%, and an average specificity of 93.33% and 100% using bands 1452 cm-1 and 836 cm-1, respectively. Moreover, 1452 cm-1 and 836 cm-1 spectral bands proved to be robust spectral biomarkers and highly correlated with glycemia (R2 of 0.801 and 0.788, P < 0.01, respectively). Both PCA-LDA and HCA classifications achieved an accuracy of 95.2%. Spectral salivary biomarkers discovered using univariate and multivariate analysis may provide a novel robust alternative for diabetes monitoring using a non-invasive and green technology.

bioinformatics