It was demonstrated that statistical analysis of bacteria colonies Fresnel patterns recorded in the optical system with converging spherical wave illumination is suitable for highly effective bacteria species classification. The proposed method includes Fresnel patterns recording followed by image processing and the statistical analysis based on feature extraction, feature selection, classification and classification performance methods. Examination performed on various bacteria species (Salmonella enteritidis, Staphylococcus aureus, Staphylococcus intermedius, Escherichia coli, Proteus mirabilis, Pseudomonas aeruginosa and Citrobacter freundii) revealed that the proposed method achieved very high accuracy of over 98%.

The novel optical system based on converging spherical wave illumination for analysis of bacteria colonies diffraction patterns, is proposed. The complex physical model of light transformation on bacteria colonies in this system, is presented. Fresnel diffraction patterns of bacteria colonies Escherichia coli, Salmonella enteritidis, Staphylococcus aureus grown in various conditions, were examined. It was demonstrated that the proposed system enables the characterization of morphological changes of colony structures basing on the changes of theirs Fresnel diffraction patterns.

It is possible to identify bacteria species basing on their diffraction patterns followed by statistical analysis. The new approach exploits two steps: optimization of the recording conditions and introduction of new interpretable features for the identification. First, optimal diffraction registration plane, was determined. Next, results were verified by the analysis workflow based on ANOVA and Fisher divergence for feature selection, QDA and SVM models for classification and identification and CV with stratified sampling, sensitivity and specificity for performance assessment of the identification process. The proposed approach resulted in high sensitivity 0.9759 and specificity 0.9903 with very small identification error 1.34%.

Glioblastoma is one of the most aggressive tumours with a poor response to treatment and a poor prognosis for patients. One of the proteins expressed in glioblastoma tissue is CHI3L1 (YKL-40), which is upregulated and known for its angiogenesis-supporting and pro-tumour immunomodulatory effects in a variety of cancers. In this paper we present the anti-angiogenic, anti-migratory and immunomodulatory effects of the compound G721-0282, an inhibitor of CHI3L1. The inhibitor-induced changes were investigated using conventional techniques as well as the novel label-free digital holographic tomography (DHT), a quantitative phase imaging technique that allows the reconstruction of the refractive index (RI), which is used as an image contrast for 3D visualisation of living cells. DHT allowed digital staining of individual cells and intercellular structures based only on their specific RI. Quantitative spatially resolved analysis of the RI data shows that the concentration of G721-0282 leads to significant changes in the density of cells and their intracellular structures (in particular the cytoplasm and nucleus), in the volume of lipid droplets and in protein concentrations. Studies in the U-87 MG glioblastoma cell line, THP-1 monocytes differentiated into macrophages, human microvascular endothelial cells (HMEC-1) and in the spheroid model of glioblastoma composed of U-87 MG, HMEC-1 and macrophages suggest that inhibition of CHI3L1 may have potential in the antitumour treatment of glioblastoma. In this paper, we also propose a spheroid model for in vitro studies that mimics this type of tumour.

Three-dimensional (3D) imaging and quantitative analysis of extracellular vesicles (EVs) remain largely unexplored, mainly because of limitations in detection techniques. In this study, EVs from patients diagnosed with colorectal cancer (CRC) and ulcerative colitis were examined. To investigate the spatial heterogeneity and 3D refractive index (RI) distribution of single EVs, a label-free digital holographic tomography technique was used at a submicrometer spatial resolution. The presented image-processing algorithms were used in quantitative analysis with digital staining and 3D visualization, the determination of the EV size distribution and extraction of fractions with different RIs. Reconstructed 3D RI distributions revealed variations in the spatial heterogeneity of EVs related to tissue specificity, such as CRC, normal colonic mucosa, and ulcerative colitis, as well as the isolation procedures used. The RI values of EVs isolated from solid tissues of frozen CRC samples were also dependent on the tumor grade and cancer cell proliferation. The simultaneous examination of cell culture models confirmed the association of the RI of EVs with the tumor grade. 3D-RI data analysis generates new perspectives with the optical, contact-free, label-free examination of the individual EVs. Depending on the specific tissue and isolation method, EVs exhibit significant spatial heterogeneity. The optical parameters of single EVs enabled their classification into two unique subgroups with different RI values.