Information-statistical approach to inverse optical problem solution for 3D disperse systems with nano- and micro particles

Multiparameter analysis of simultaneous optical data for 3D disperse systems (consisted from nano- and/or microparticles of different nature) by information-statistical methods can help to estimate the share of different types of particles in mixtures. At the solution of inverse optical problem for unknown poly-component 3D DS, the comparison of measured parameters with the known ones from the set of mono-component 3D DS can help to identify the component content of the system under study. The approach was tested on the biomineral water mixtures of kaolin clay and bacterium coli bacillus with the help of the program based on the information-statistical theory. To solve the impurity optical recognition tasks, the Base of optical data for 3D DS is needed.

Daily Fluctuations in the Isotope and Elemental Composition of Tap Water in Ljubljana, Slovenia

The isotope and elemental composition of tap water reflects its multiple distinct inputs and provides a link between infrastructure and the environment over a range of scales. For example, on a local scale, they can be helpful in understanding the geological, hydrogeological, and hydrological conditions and monitor the proper functioning of the water supply system (WSS). However, despite this, studies examining the urban water system remain limited. This study sought to address this knowledge gap by performing a 24 h multiparameter analysis of tap water extracted from a region where the mixing of groundwater between two recharge areas occurs. This work included measurements of temperature and electrical conductivity, as well as pH, δ2H, δ18O, d, δ13CDIC, and 87Sr/86Sr ratios and major and trace elements at hourly intervals over a 24 h period. Although the data show only slight variations in the measured parameters, four groups were distinguishable using visual grouping, and multivariate analysis (Spearman correlation coefficient analysis, hierarchical cluster analysis, and principal components analysis). Finally, changes in the mixing ratios of the two sources were estimated using a linear mixing model. The results confirm that the relative contribution from each source varied considerably over 24 h.

The potential of proliferative and apoptotic parameters in clinical flow cytometry of myeloid malignancies

Standardization of the detection and quantification of leukocyte differentiation markers by the EuroFlow Consortium has led to a major step forward in the integration of flow cytometry into classification of leukemia and lymphoma. In our opinion, this now enables introduction of markers for more dynamic parameters, such as proliferative and (anti)apoptotic markers, which have proven their value in the field of histopathology in the diagnostic process of solid tumors and lymphoma. Although use of proliferative and (anti)apoptotic markers as objective parameters in the diagnostic process of myeloid malignancies was studied in the past decades, this did not result in the incorporation of these biomarkers into clinical diagnosis. This review addresses the potential of these markers for implementation in the current, state-of-the-art multiparameter analysis of myeloid malignancies. The reviewed studies clearly recognize the importance of proliferation and apoptotic mechanisms in the pathogenesis of bone marrow (BM) malignancies. The literature is, however, contradictory on the role of these processes in myelodysplastic syndrome (MDS), MDS/myeloproliferative neoplasms, and acute myeloid leukemia. Furthermore, several studies underline the need for the analysis of the proliferative and apoptotic rates in subsets of hematopoietic BM cell lineages and argue that these results can have diagnostic and prognostic value in patients with myeloid malignancies. Recent developments in multiparameter flow cytometry now allow quantification of proliferative and (anti)apoptotic indicators in myeloid cells during their different maturation stages of separate hematopoietic cell lineages. This will lead to a better understanding of the biology and pathogenesis of these malignancies.

Simulation Analysis of CO2-EOR Process and Feasibility of CO2 Storage during EOR

In this study, oil production and retention were observed and compared in 72 reservoir simulation cases, after which an economic analysis for various CO2 and oil prices was performed. Reservoir simulation cases comprise different combinations of water alternating gas (WAG) ratios, permeabilities, and well distances. These models were set at three different depths; thus different pressure and temperature conditions, to see the impact of miscibility on oil production and CO2 sequestration. Those reservoir conditions affect oil production and CO2 retention differently. The retention trend dependence on depth was not monotonic—optimal retention relative to the amount of injected CO2 could be achieved at middle depths and mediocre permeability as well. Results reflecting different reservoir conditions and injection strategies are shown, and analysis including the utilization factor and the net present value was conducted to examine the feasibility of different scenarios. The analysis presented in this paper can serve as a guideline for multiparameter analysis and optimization of CO2-enhanced oil recovery (EOR) with a WAG injection strategy.

Genetic Bias, Diversity Indices, Physiochemical Properties and CDR3 Motifs Divide Auto-Reactive from Allo-Reactive T-Cell Repertoires

The distinct properties of allo-reactive T-cell repertoires are not well understood. To investigate whether auto-reactive and allo-reactive T-cell repertoires encoded distinct properties, we used dextramer enumeration, enrichment, single-cell T-cell receptor (TCR) sequencing and multiparameter analysis. We found auto-reactive and allo-reactive T-cells differed in mean ex vivo frequency which was antigen dependent. Allo-reactive T-cells showed clear differences in TCR architecture, with enriched usage of specific T-cell receptor variable (TRBJ) genes and broader use of T-cell receptor variable joining (TRBJ) genes. Auto-reactive T-cell repertoires exhibited complementary determining regions three (CDR3) lengths using a Gaussian distribution whereas allo-reactive T-cell repertoires exhibited distorted patterns in CDR3 length. CDR3 loops from allo-reactive T-cells showed distinct physical-chemical properties, tending to encode loops that were more acidic in charge. Allo-reactive T-cell repertoires differed in diversity metrics, tending to show increased overall diversity and increased homogeneity between repertoires. Motif analysis of CDR3 loops showed allo-reactive T-cell repertoires differed in motif preference which included broader motif use. Collectively, these data conclude that allo-reactive T-cell repertoires are indeed different to auto-reactive repertoires and provide tangible metrics for further investigations and validation. Given that the antigens studied here are overexpressed on multiple cancers and that allo-reactive TCRs often show increased ligand affinity, this new TCR bank also has translational potential for adoptive cell therapy, soluble TCR-based therapy and rational TCR design.

Spatial geoecological modeling of the natural-agrarian potential of the region landscapes

The article describes the scientific and methodological foundations of spatial geoecological modeling of the natural and agricultural potential of the region’s landscapes, the theoretical basis of which is the methodology of multiparameter analysis of complex objects, implemented in the form of two methods: summary indicators and randomized summary indicators. The essence of modeling is in mathematical-cartographic spatial analysis in the GIS environment of the favorableness of natural landscapes for environmentally friendly agricultural production. It is based on the principles of consistency, priority of the assessed indicators, continuity, regionality, emergence, scale, visibility of the display of results. During the development of the scientific and methodological foundations, the following methods of geographical research were used: ranking the properties of landscapes by their impact on the natural and agricultural potential, building model-classifications for assessing the natural-agricultural potential, convolution of multi-parameter information in conditions of information deficit. The developed method includes six blocks. The method has been tested in the Leningrad Region. The results of approbation do not contradict the data of other researchers obtained for the studied region. The developed method can be applied in land management and territorial planning.