Objectives: to investigate the immunoexpression of epidermal growth factor receptor (EGFR) in a sample of oral leukoplakias (OL) and to determine the receptor’s association with dysplasia, tobacco consumption, lesion site, and proliferation rate. Although EGFR should be overexpressed in some oral leukoplakias, the factors that may interfere with this expression and the influence of this receptor on epithelial proliferation have yet to be investigated. Study Design: Samples of oral leukoplakias (48) and of normal oral epithelium (10) were immunohistologically examined for expression of EGFR. Immunohistochemistry for Ki-67, and p27 were also performed in leukoplakias. EGFR expression was associated with clinical and pathological features. Results: EGFR was positive in 62.5% of the leukoplakias and 50% of normal oral epithelium. The number of EGFR positive OL located in high-risk sites was significantly higher than EGFR positive OL located in low-risk sites. Most of the p27 negative leukoplakias were EGFR positive, and the p27 index in the parabasal layer was diminished in the presence of dysplasia. Positivity for EGFR was not associated with dysplasia, tobacco exposure, or Ki-67. Conclusion: EGFR is expressed in leukoplakia regardless of dysplasia, but EGFR positivity should be more frequent in lesions sited in areas of high cancer risk. The association between EGFR and p27 may represent an important mechanism in the control of cellular proliferation and malignant progression of oral epithelium and therefore warrants further investigation. Key words:Oral leukoplakia, EGFR, p27, Ki-67, epithelial dysplasia.

Background Fraudulent milk adulteration is a dangerous practice in the dairy industry that is harmful to consumers since milk is one of the most consumed food products. Milk quality can be assessed by Fourier Transformed Infrared Spectroscopy (FTIR), a simple and fast method for obtaining its compositional information. The spectral data produced by this technique can be explored using machine learning methods, such as neural networks and decision trees, in order to create models that represent the characteristics of pure and adulterated milk samples. Results Thousands of milk samples were collected, some of them were manually adulterated with five different substances and subjected to infrared spectroscopy. This technique produced spectral data from the milk samples composition, which were used for training different machine learning algorithms, such as deep and ensemble decision tree learners. The proposed method is used to predict the presence of adulterants in a binary classification problem and also the specific assessment of which of five adulterants was found through multiclass classification. In deep learning, we propose a Convolutional Neural Network architecture that needs no preprocessing on spectral data. Classifiers evaluated show promising results, with classification accuracies up to 98.76%, outperforming commonly used classical learning methods. Conclusions The proposed methodology uses machine learning techniques on milk spectral data. It is able to predict common adulterations that occur in the dairy industry. Both deep and ensemble tree learners were evaluated considering binary and multiclass classifications and the results were compared. The proposed neural network architecture is able to outperform the composition recognition made by the FTIR equipment and by commonly used methods in the dairy industry. Electronic supplementary material The online version of this article (10.1186/s13040-019-0200-5) contains supplementary material, which is available to authorized users.

The objective of this study was to analyze the presence of tumor-associated macrophage (TAM) subpopulations M1 and M2 in squamous cell carcinoma of the lower lip (SCCLL) by immunohistochemitry, and to evaluate the possible role of these subtypes in the development of regional lymph node metastasis and their association with clinical and pathological parameters. Forty-two cases of SCCLL were divided into two groups (21 with and 21 without regional lymph node metastasis). The histopathological grade of malignancy was determined and the material was submitted to double staining with anti-CD68/anti-CD163 and anti-CD68/anti-HLA-DR monoclonal antibodies. The results were analyzed statistically using the Wilcoxon signed-rank and Spearman correlation tests. The M1 and M2 subpopulations were observed in all cases studied. No significant difference was observed between the quantities of M1 and M2 TAMs regarding tumor size (p > 0.05). A significantly larger number of M2 compared to M1 TAMs was observed in tumors without regional lymph node metastasis, tumors in early stages, and low-grade tumors (p < 0.05). No significant difference between the numbers of M1 and M2 TAMs was observed in tumors with regional lymph node metastasis, tumors in advanced stages, and high-grade tumors (p > 0.05). There was a positive weak correlation between M1 and M2 TAMs (r = 0.361; p = 0.019). The results suggest a more important role of M2 TAMs in early stages than advanced stages of lip carcinogenesis. The progression of SCCLL does not seem to be related to an imbalance of macrophage polarization in the microenvironment of these tumors.

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