The use of lacunarity for visual texture characterization of pre-sliced cooked pork ham surface intensities

Application of Lacunarity for Quantification of Single Molecule Localization Microscopy Images

The quantitative analysis of datasets achieved by single molecule localization microscopy is vital for studying the structure of subcellular organizations. Cluster analysis has emerged as a multi-faceted tool in the structural analysis of localization datasets. However, the results it produces greatly depend on the set parameters, and the process can be computationally intensive. Here we present a new approach for structural analysis using lacunarity. Unlike cluster analysis, lacunarity can be calculated quickly while providing definitive information about the structure of the localizations. Using simulated data, we demonstrate how lacunarity results can be interpreted. We use these interpretations to compare our lacunarity analysis with our previous cluster analysis-based results in the field of DNA repair, showing the new algorithm’s efficiency.

Comparison of the physico-chemical meat quality of the breeds Mangalitsa and Large white with regard to the slaughter weight

The aim of this study was to compare the quality of musculus longissimus dorsi in the breeds of Mangalitsa and Large White with regard to the slaughter weight. Large White (LW) breed and White Mangalitsa (Ma) breed were used in the experiment. The system of housing and feeding was the same in both of the monitored breeds. The pigs were fed with the same feeding mixture ad libitum. According to the slaughter weight, the pigs were divided into three groups: up to 100 kg, 101 – 110 kg and over 110 kg. The breed Ma had a significantly lower drip loss than the breed LW. Evaluating the color of the meat, the LW breed has showed significantly higher L* (lightness, white ±black) and lower a* (redness, red ± green) values than the Ma breed. Within the chemical meat composition, the Ma breed had a significantly higher water content in MLD compared to the LW breed. Generally, there were no major differences in the meat quality between the Mangalitsa and Large White breeds. Finally it can be concluded that the breed Mangalitsa showed more favorable values of the physico-chemical indicators. Comparing the quality of the meat with regard to the slaughter weight, there were no large differences between individual weight groups. A higher slaughter weight has positively influenced mainly the color of the meat, as pigs weighing more than 110 kg achieved a significantly lower value of L* and a higher value of a* in comparison to pigs of the lower weight. As a positive effect of a higher slaughter weight can be considered its effect on the protein content in the meat, as pigs weighing over 100 kg have a significantly higher protein content in the meat than pigs weighing below 100 kg.

Spatial intratumoral heterogeneity of proliferation in immunohistochemical images of solid tumors

PURPOSE

The interactions of neoplastic cells with each other and the microenvironment are complex. To understand intratumoral heterogeneity, subtle differences should be quantified. Main factors contributing to heterogeneity include the gradient ischemic level within neoplasms, action of microenvironment, mechanisms of intercellular transfer of genetic information, and differential mechanisms of modifications of genetic material/proteins. This may reflect on the expression of biomarkers in the context of prognosis/stratification. Hence, a rigorous approach for assessing the spatial intratumoral heterogeneity of histological biomarker expression with accuracy and reproducibility is required, since patterns in immunohistochemical images can be challenging to identify and describe.

METHODS

A quantitative method that is useful for characterizing complex irregular structures is lacunarity; it is a multiscale technique that exhaustively samples the image, while the decay of its index as a function of window size follows characteristic patterns for different spatial arrangements. In histological images, lacunarity provides a useful measure for the spatial organization of a biomarker when a sampling scheme is employed and relevant features are computed. The proposed approach quantifies the segmented proliferative cells and not the textural content of the histological slide, thus providing a more realistic measure of heterogeneity within the sample space of the tumor region. The aim is to investigate in whole sections of primary pancreatic neuroendocrine neoplasms (pNENs), using whole-slide imaging and image analysis, the spatial intratumoral heterogeneity of Ki-67 immunostains. Unsupervised learning is employed to verify that the approach can partition the tissue sections according to distributional heterogeneity.

RESULTS

The architectural complexity of histological images has shown that single measurements are often insufficient. Inhomogeneity of distribution depends not only on percentage content of proliferation phase but also on how the phase fills the space. Lacunarity curves demonstrate variations in the sampled image sections. Since the spatial distribution of proliferation in each case is different, the width of the curves changes too. Image sections that have smaller numerical variations in the computed features correspond to neoplasms with spatially homogeneous proliferation, while larger variations correspond to cases where proliferation shows various degrees of clumping. Grade 1 (uniform/nonuniform: 74%/26%) and grade 3 (uniform: 100%) pNENs demonstrate a more homogeneous proliferation with grade 1 neoplasms being more variant, while grade 2 tumor regions render a more diverse landscape (50%/50%). Hence, some cases show an increased degree of spatial heterogeneity comparing to others with similar grade. Whether this is a sign of different tumor biology and an association with a more benign/malignant clinical course needs to be investigated further. The extent and range of spatial heterogeneity has the potential to be evaluated as a prognostic marker.

CONCLUSIONS

The association with tumor grade as well as the rationale that the methodology reflects true tumor architecture supports the technical soundness of the method. This reflects a general approach which is relevant to other solid tumors and biomarkers. Drawing upon the merits of computational biomedicine, the approach uncovers salient features for use in future studies of clinical relevance.

Monitoring of color and pH in muscles of pork leg (m. adductor and m. semimembranosus)

In order to identify PSE pork meat, pH and color testing was performed directly in a cutting plant (72 hours post mortem) in this research. Specifically pork leg muscles musculi adductor (AD) and semimembranosus (SM) from five selected suppliers (A, B, C, D, E) were examined. Twenty samples of meat for each muscle were examined from each supplier. The measured pH values ranged from 5.43 to 5.63, and the L* values from 46.13 to 57.18. No statistically significant differences in pH values and color were detected among the various suppliers with the exception of the a* and b* parameters for two suppliers, namely A and B (p<0.01). On the contrary, a statistically significant difference (p<0.5) was recorded between individual muscles (AD/SM) across all the suppliers (A, B, C, D, E) with the exception of a* parameter from suppliers B, C, D, E, and pH values for the E supplier. Our results revealed that individual muscles differ in values of pH and color. In comparison with literature, pH and lightness L* values in musculus adductor point to PSE (pale, soft and exudative) meat, while the values of musculus semimebranosus to RFN (red, firm and non-exudative). Use of PSE meat in production of meat products can cause several problems. In particular, it causes light color, low water-holding capacity, poor fat emulsifying ability, lower yield, granular or crumbly texture and poor consistency of the finished product. Therefore classification of the meat directly cutting plant may be possible solution for this problem. The finished product pruduces from muscles of musculi semimembranosus can obtain better quality than the finished product from musculi adductor.