Automatic ham classification method based on support vector machine model increases accuracy and benefits compared to manual classification.

The thickness of the subcutaneous fat (SFT) is a very important parameter in the ham, since determines the process the ham will be submitted. This study compares two methods to predict the SFT in slaughter line: an automatic system using an SVM model (Support Vector Machine) and a manual measurement of the fat carried out by an experienced operator, in terms of accuracy and economic benefit. These two methods were compared to the golden standard obtained by measuring SFT with a ruler in a sample of 400 hams equally distributed within each SFT class. The results show that the SFT prediction made by the SVM model achieves an accuracy of 75.3%, which represents an improvement of 5.5% compared to the manual measurement. Regarding economic benefits, SVM model can increase them between 12 and 17%. It can be concluded that the classification using SVM is more accurate than the one performed manually with an increase of the economic benefit for sorting.

On-line Ham Grading using pattern recognition models based on available data in commercial pig slaughterhouses.

The thickness of the subcutaneous fat in hams is one of the most important factors for the dry-curing process and largely determines its final quality. This parameter is usually measured in slaughterhouses by a manual metrical measure to classify hams. The aim of the present study was to propose an automatic classification method based on data obtained from a carcass automatic classification equipment (AutoFom) and intrinsic data of the pigs (sex, breed, and weight) to simulate the manual classification system. The evaluated classification algorithms were decision tree, support vector machines (SVM), k-nearest neighbour and discriminant analysis. A total of 4000 hams selected by breed and sex were classified as thin (0-10 mm), standard (11-15 mm), semi-fat (16-20 mm) and fat (>20 mm). The most reliable model, with a percentage of success of 73%, was SVM with Gaussian kernel, including all data available. These results suggest that the proposed classification method can be a useful online tool in slaughterhouses to classify hams.

Inhibition of c-Myc down-regulation by sustained extracellular signal-regulated kinase activation prevents the antimetabolite methotrexate- and gemcitabine-induced differentiation in non-small-cell lung cancer cells.

Non-small-cell lung cancer (NSCLC) is characterized by severe resistance to chemotherapy. Here, we demonstrate that A549 adenocarcinoma cells permanently differentiate with the antimetabolites methotrexate (MTX) and gemcitabine (GE) when blocking the resistance mechanism that normally counteracts this process. MTX (1-10 microM) and GE (1 microM) induced growth arrest accompanied by sustained extracellular signal-regulated kinase (ERK1/2) phosphorylation and moderate reduction of c-Myc levels after 96 h, whereas only a low percentage of the cells differentiated. Combination with the mitogen-activated protein kinase kinase (MEK) inhibitor 1,4-diamino-2,3-dicyano-1,4-bis-(methylthio)butadiene (U0126) reduced MTX- or GE-induced ERK1/2 over-phosphorylation, nearly abolished c-Myc expression, and provoked radical morphological changes in all cells. Besides the appearance of multilamellar bodies and intracellular cytokeratin reorganization, modulation of molecular markers occurred in a manner consistent with differentiation (gelsolin, +300%; surfactant protein A and C, -70%). Similar to U0126, c-Myc inactivation with specific small interfering RNA initiated differentiation only in the presence of MTX, demonstrating that inhibition of the mitogen-activated protein kinase/ERK pathway alone or down-regulation of c-Myc is not sufficient to induce this process. It is noteworthy that withdrawal of antitumoral drugs and U0126 neither reversed differentiation nor reactivated proliferation. Our results reveal that maintenance of a certain threshold of c-Myc expression through sustained ERK1/2 activation represents a molecular mechanism that confers resistance to antimetabolite-induced differentiation in A549 cells, and provide a novel molecular basis for therapeutic strategies based on irreversible differentiation of cancer cells using conventional chemotherapeutic antimetabolites in combination with inhibitors of the MEK/ERK pathway or c-Myc.