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Various types of neuromuscular diseases differ in symptoms, pathology, and clinical picture but one of their common elements is muscle weakness, which could lead to human motor activities impairment and in many cases to shortening of life span and even death due to respiratory failure. That is why it is very important to better understand the underlying causes of these diseases to be able to implement new methods of treatment more effectively. This paper presents the results of the elemental analysis of human muscular tissues affected by dystrophy and myopathy. For this purpose, the particle-induced X-ray emission method was used, which is perfectly suited for measuring light elements. The samples were analysed for differences in the elemental composition of Na, Mg, P, S, Cl, K, Fe, Zn, and Br. The results were presented in the form of elemental concentration maps and a thorough statistical analysis of the obtained data using the advanced statistical methods.

Neoplastic and healthy brain tissues were analysed to discern the changes in the spatial distribution and overall concentration of elements using micro X-ray fluorescence spectroscopy. High-resolution distribution maps of minor and trace elements such as P, S, Cl, K, Ca, Fe, Cu and Zn made it possible to distinguish between homogeneous cancerous tissue and areas where some structures could be identified, such as blood vessels and calcifications. Concentrations of the elements in the selected homogeneous areas of brain tissue were compared between tumours with various malignancy grades and with the controls. The study showed a decrease in the average concentration of Fe, P, S and Ca in tissues with high grades of malignancy as compared to the control group, whereas the concentration of Zn in these tissues was increased. The changes in the concentration were found to be correlated with the tumour malignancy grade. The efficacy of micro X-ray fluorescence spectroscopy to distinguish between various types of cancer based on the concentrations of studied elements was confirmed by multivariate discriminant analysis. Our analysis showed that the most important elements for tissue classification are Cu, K, Fe, Ca, and Zn. This method made it possible to correctly classify histopathological types in 99.93% of the cases used to build the model and in as much as 99.16% of new cases.

The process of carcinogenesis may influence normal biochemical reactions leading to alterations in the elemental composition of the tissue. Total reflection X-ray fluorescence analysis (TXRF) was applied to the elemental analysis of different brain tumors. The following elements were present in all the neoplastic tissues analyzed: K, Ca, Fe, Cu, Zn and Rb. The results of the analysis showed that the elemental composition of a relatively small fragment of tissue represents satisfactorily the biochemical “signature” of a cancer. On the basis of the element concentrations determined, it was possible to differentiate between some types of brain tumors.

The aims of this paper were to present a reliable morphometric procedure for glioma analysis for preliminary prognosis and to develop a semi-automatic procedure that is easy to use. The data presented are important to the extent that they verify the reliability of the results by showing that they are consistent with the findings from more complicated automatic analytical tools. The objects for analysis were digital images of haematoxylin-eosin stained glioma samples. The overall analysis consisted of digital image analysis and the determination of morphometric parameters. Interestingly, an increase in the mean values of aspect ratio with increasing malignancy grade was found. Moreover, the morphometric parameters in relation to the histological origin of gliomas were examined and it was found that, the cellular nuclei of glioblastoma multiforme reveal the biggest mean values of aspect ratio compared with other gliomas.