Kraków, Poland
Kraków, Poland

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Banas A.,Polish Academy of Sciences | Banas A.,National University of Singapore | Kwiatek W.M.,Polish Academy of Sciences | Banas K.,Polish Academy of Sciences | And 4 more authors.
Journal of Biological Inorganic Chemistry | Year: 2010

The causes of prostate cancer are still obscure but some evidence indicates that there is a close connection between several trace elements and processes which may lead to malignant cells. In our study the microbeam synchrotron radiation X-ray fluorescence emission (micro-SRIXE) technique was applied for quantitative analysis of selected elements. For the first time, we correlate the concentrations of Mn, Fe, Cu, and Zn with the clinical stage of the prostate cancer at the time of operation (described by Gleason grade). Serial sections of prostate tissues were collected from patients undergoing radical prostatectomy. One section, stained with hematoxylin and eosin, was prepared for histopathological analysis; a second, adjacent unstained section was used in micro-SRIXE experiments. All experiments were performed at beamline L at HASYLAB, DESY, Germany. Our results seem to be valuable in light of the determination of the changes in the concentrations of trace elements as a potential diagnostic marker and their etiological involvement in the different stages of prostate diseases. © 2010 The Author(s).

Banas K.,National University of Singapore | Banas A.,National University of Singapore | Gajda M.,Jagiellonian University | Kwiatek W.M.,Polish Academy of Sciences | And 2 more authors.
Analytical Chemistry | Year: 2014

Assessment of the performance and up-to-date diagnostics of scientific equipment is one of the key components in contemporary laboratories. Most reliable checks are performed by real test experiments while varying the experimental conditions (typically, in the case of infrared spectroscopic measurements, the size of the beam aperture, the duration of the experiment, the spectral range, the scanner velocity, etc.). On the other hand, the stability of the instrument response in time is another key element of the great value. Source stability (or easy predictable temporal changes, similar to those observed in the case of synchrotron radiation-based sources working in non top-up mode), detector stability (especially in the case of liquid nitrogen- or liquid helium-cooled detectors) should be monitored. In these cases, recorded datasets (spectra) include additional variables such as time stamp when a particular spectrum was recorded (in the case of time trial experiments). A favorable approach in evaluating these data is building hyperspectral object that consist of all spectra and all additional parameters at which these spectra were recorded. Taking into account that these datasets could be considerably large in size, there is a need for the tools for semiautomatic data evaluation and information extraction. A comprehensive R archive network-the open-source R Environment-with its flexibility and growing potential, fits these requirements nicely. In this paper, examples of practical implementation of methods available in R for real-life Fourier transform infrared (FTIR) spectroscopic data problems are presented. However, this approach could easily be adopted to many various laboratory scenarios with other spectroscopic techniques. © 2014 American Chemical Society.

Banas K.,National University of Singapore | Banas A.M.,National University of Singapore | Gajda M.,Jagiellonian University | Kwiatek W.M.,Polish Academy of Sciences | And 2 more authors.
Radiation Physics and Chemistry | Year: 2013

Life sciences have seen a huge increase in the amount and complexity of data being collected with every experiment. Scientists today are faced with increasingly difficult task to extract vital information from the vast amount of numbers. Software used for this purpose should be sufficiently powerful and flexible to handle large and complex data sets. On the other hand it should allow the user to exactly follow what is being calculated, black-box type of software should be avoided. R platform (R Development Core Team, 2011), open-source environment for statistical analysis nicely fits these requirements. With its rapidly expanding user community it is quickly becoming the most important tool in statistical analysis of data in broad range of applications. The most important feature of R is the package system, allowing users to address specific problems with dedicated package and even for more advanced users to contribute software for their own fields. In this paper multivariate analysis and data treatment of spectral data by using R environment is presented. © 2013 Elsevier Ltd.

Banas K.,Singapore Synchrotron Light Source | Banas A.,Singapore Synchrotron Light Source | Gajda M.,Jagiellonian University | Pawlicki B.,Gabriel Narutowicz Hospital | And 3 more authors.
Analyst | Year: 2015

Pre-processing of Fourier transform infrared (FTIR) spectra is typically the first and crucial step in data analysis. Very often hyperspectral datasets include the regions characterized by the spectra of very low intensity, for example two-dimensional (2D) maps where the areas with only support materials (like mylar foil) are present. In that case segmentation of the complete dataset is required before subsequent evaluation. The method proposed in this contribution is based on a multivariate approach (hierarchical cluster analysis), and shows its superiority when compared to the standard method of cutting-off by using only the mean spectral intensity. Both techniques were implemented and their performance was tested in the R statistical environment - open-source platform - that is a favourable solution if the repeatability and transparency are the key aspects. This journal is © The Royal Society of Chemistry 2015.

Banas A.,Polish Academy of Sciences | Banas A.,National University of Singapore | Banas K.,National University of Singapore | Kwiatek W.M.,Polish Academy of Sciences | And 3 more authors.
Journal of Biological Inorganic Chemistry | Year: 2011

The prostate gland is the most common site of neoplastic disorders in men. The pathogenesis of inflammatory cells, prostatic intraepithelial neoplasia (PIN) lesions, and prostate cancer is still under investigation. Inflammatory cells by producing free radicals are considered as major and universal contributors to cancerogenesis. PIN is regarded as a precursor lesion to prostate cancer or a marker signaling the vulnerability of the epithelium to neoplastic transformation [1]. Differentiation markers that are frequently changed in early invasive carcinoma are also changed in PIN lesions. In this study, prostate tissue samples obtained during surgical operation and classified as various disease states (inflammation, PIN lesions, and cancer) were examined. The samples were measured by means of microbeam synchrotron-radiation- induced X-ray emission (micro-SRIXE). Special attention was paid to examine the relationship between the earlier-mentioned disorders and changes in relative concentrations of S, K, Ca, Fe, Cu, and Zn. Applying the image-processing program ImageJ enabled us to select the areas of interest from two-dimensional maps of various prostate samples according to the histopathologist's evaluation. Detailed analysis of micro-SRIXE spectra based on multivariate methods shows significant differences between elemental concentrations in inflammatory cells, PIN lesions, and cancerous tissues, which confirms that this method can be used to distinguish various pathological states in prostate tissues. Information obtained in this way may provide better understanding of the biochemistry of unhealthy prostate tissues, thus opening the way to find new medicines/treatments to prevent or slow down some harmful intracellular processes. © 2011 The Author(s).

Banas A.,National University of Singapore | Banas K.,National University of Singapore | Furgal-Borzych A.,Jagiellonian University | Kwiatek W.M.,Polish Academy of Sciences | And 2 more authors.
Analyst | Year: 2015

The pituitary gland is a small but vital organ in the human body. It is located at the base of the brain and is often described as the master gland due to its multiple functions. The pituitary gland secretes and stores hormones, such as the thyroid-stimulating hormone (TSH), adrenocorticotropic hormone (ACTH), growth hormone (hGH), prolactin, gonadotropins, and luteinizing hormones, as well as the antidiuretic hormone (ADH). A proper diagnosis of pituitary disorders is of utmost importance as this organ participates in regulating a variety of body functions. Typical histopathological analysis provides much valuable information, but it gives no insight into the biochemical background of the changes that occur within the gland. One approach that could be used to evaluate the biochemistry of tissue sections obtained from pituitary disorders is Fourier Transform Infra-Red (FTIR) spectromicroscopy. In order to collect diagnostically valuable information large areas of tissue must be investigated. This work focuses on obtaining a unique and representative FTIR spectrum characteristic of one type of cell architecture within a sample. The idea presented is based on using hierarchical cluster analysis (HCA) for data evaluation to search for uniform patterns within samples from the perspective of FTIR spectra. The results obtained demonstrate that FTIR spectromicroscopy, combined with proper statistical evaluation, can be treated as a complementary method for histopathological analysis and ipso facto can increase the sensitivity and specificity for detecting various disorders not only for the pituitary gland, but also for other human tissues. © The Royal Society of Chemistry 2015.

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