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Evaluation of water quality is crucial for managing surface water effectively, ensuring its suitability for human use, and sustaining the environment. In the lower Danube River basin, various methods were employed to assess surface water quality for irrigation, drinking, human health risk purposes and the main mechanism control the surface water chemistry. These methods included water quality indicators (WQIs), complex statistical analyses, geographic information systems (GIS), Monte Carlo simulation, and geochemical modeling. Physicochemical analyses of surface water samples revealed primarily Ca–Mg–HCO3− is the dominant water types. Principal component analysis (PCA), ionic ratios and piper, chloro alkaline index, Chadha, and Gibbs diagrams identified three distinct water characteristics influenced by water-rocks interaction, evaporation, ions exchange, and human activities. The geochemical modeling showed Danube River water's strong ability to dissolve gypsum, halite, and anhydrite (SI < 0) and precipitate aragonite, dolomite, and calcite with saturation index (SI) value greater than 0 along its flow path. The irrigation water quality index (IWQI = 99.6–107.6), sodium adsorption ratio (SAR = 0.37–0.68), sodium percentage (Na% = 13.7–18.7), soluble sodium percentage (SSP = 12.5–17.5), Potential Salinity (PS = 0.73–1.6), and Residual Sodium Carbonate (RSC = − 1.27–0.58) values were used, mainly indicating acceptable quality with some limitations. Danube River water was unsuitable for drinking based on WQI value (WQI = 81–104). Oral exposure of children to specific components showed a higher hazard index (HI > 1) compared to adults, indicating a 2.1 times higher overall non-carcinogenic risk hazard index. However, Monte Carlo simulation demonstrated negligible iron, manganese, and nitrate health hazards for both age groups. These findings are valuable for water quality management decisions, contributing to long-term resource sustainability. [ABSTRACT FROM AUTHOR]

Evaluation of water quality is crucial for managing surface water effectively, ensuring its suitability for human use, and sustaining the environment. In the lower Danube River basin, various methods were employed to assess surface water quality for irrigation, drinking, human health risk purposes and the main mechanism control the surface water chemistry. These methods included water quality indicators (WQIs), complex statistical analyses, geographic information systems (GIS), Monte Carlo simulation, and geochemical modeling. Physicochemical analyses of surface water samples revealed primarily Ca–Mg–HCO3− is the dominant water types. Principal component analysis (PCA), ionic ratios and piper, chloro alkaline index, Chadha, and Gibbs diagrams identified three distinct water characteristics influenced by water-rocks interaction, evaporation, ions exchange, and human activities. The geochemical modeling showed Danube River water's strong ability to dissolve gypsum, halite, and anhydrite (SI < 0) and precipitate aragonite, dolomite, and calcite with saturation index (SI) value greater than 0 along its flow path. The irrigation water quality index (IWQI = 99.6–107.6), sodium adsorption ratio (SAR = 0.37–0.68), sodium percentage (Na% = 13.7–18.7), soluble sodium percentage (SSP = 12.5–17.5), Potential Salinity (PS = 0.73–1.6), and Residual Sodium Carbonate (RSC = − 1.27–0.58) values were used, mainly indicating acceptable quality with some limitations. Danube River water was unsuitable for drinking based on WQI value (WQI = 81–104). Oral exposure of children to specific components showed a higher hazard index (HI > 1) compared to adults, indicating a 2.1 times higher overall non-carcinogenic risk hazard index. However, Monte Carlo simulation demonstrated negligible iron, manganese, and nitrate health hazards for both age groups. These findings are valuable for water quality management decisions, contributing to long-term resource sustainability. [ABSTRACT FROM AUTHOR]

The aim of the study was to assess the genetic diversity of 27 rye (Secale cereale L.) accessions by using multivariate statistical methods. The experiment was carried in the block method with 3 replications on plots of 2.5 m² during 2017/2018, 2018/2019 and 2019/2020 growing seasons. Nine qualitative and fifteen quantitative morpho-agronomical characters were evaluated. General Shannon-Weaver diversity index for all included in the study traits was moderate (H' = 0.631). The analysis of variance exhibited the presence of significant differences among the tested genotypes for all quantitative characters indicating the existence of variability. The high heritability with high genetic advance was recorded for leaf area of a flag leaf, leaf area of a sub-flag leaf, weight of the main spike, weight of the grain in the main spike, number of spikelets in the main spike and grain yield combined indicating that they are important characters to be considered for selection and improvement of Secale cereale L. Cluster analysis based on the Between groups linkage and Squared Euclidean Distance grouped the genotypes into six clusters. The highest distance values were measured for the following pair wise genotype combinations: B4000206-B7000123, B4000205-B7000123 and B4000210-B7000123. The first 8 principal components explained a very large proportion of the total variation (81.80%). The results of the study will be useful for the breeding improvement programs of rye. [ABSTRACT FROM AUTHOR]

The study was conducted in the period 2015-2017 in the experimental field of IRGR "K. Malkov" Sadovo. The elements of productivity of 24 varieties and lines of triticale (X. Triticosecale Wittmacks) were studied. The degree of variation of each of the indicators of productivity is determined by calculating a coefficient of variation. The results obtained show that the most variable indicator is the weight of grains in the central spike whereas the slightest variation is observed in the parameters of test weight and 1000 grains weight. Hierarchical cluster analysis and analysis of the main components (PC-analysis) are applied to assess the genetic similarity and distance between the different varieties. As a result of the clustering the studied samples were divided into six groups. The varieties Trit 32/6 and KS 60 are characterized with the greatest genetic proximity, followed by line BGR 30071 with the Bulgarian variety Rozhen. The largest genetic difference was reported between line BGR 30816 and variety KT 81. The applied analysis of the main components shows that the components PC 1, PC 2 and PC 3 explain 70.6% of the total variation of all traits by genotypes. The largest numbers of samples (9) belong to component 3, as four of them are located in the negative values of PC 3, and the other five genotypes are in the positive values of PC 3. Component 1 is represented by eight samples, and component 2 includes seven triticale genotypes. [ABSTRACT FROM AUTHOR]

This study aimed to identify and evaluate the effects of single nucleotide polymorphisms (SNPs) within miR-9 and miR-27a genes and their promoters, as well as 3′UTR regions of KITLG and IGF1 genes on litter size in Markhoz goats. PCR-SSCP analysis revealed different band patterns and sequencing results confirmed four SNPs including a C/A, a A/G, a C/T and a A/G substitution located in the promoter region of miR-9 gene, 48 bp upstream of miR-9 seed region within the 3′UTR of KITLG gene, 37 bp downstream of miR-27a gene and 39 bp upstream of miR-9 seed region within the 3′UTR of IGF1 gene, respectively. The results of the least-square analyses indicated that AA genotype of miR-9 gene strongly and positively affects litter size in Markhoz goats (P < 0.01). Furthermore, the results of the logistic regression analyses confirmed that the A allele of miR-9 gene has a tremendous impact on litter size in Markhoz goats (P < 0.01). Scanning the promoter region of miR-9 gene showed that changing C allele to A may prevent HES1, HES2, NRF1 and TCFL5 transcription factors (TFs) from binding to the promoter, which can reduce the expression of miR-9 gene. Principle component analysis (PCA) showed that approximately 60% of the variation of the data set was explained by two of four SNPs. Also, the biplot from the PCA showed a strong association between litter size and C/A polymorphism of miR-9 promoter. Linkage disequilibrium analysis revealed a very slight linkage among investigated loci. • A novel variant within promoter of miR-9 gene have strong impact on litter size. • No polymorphism found within seed regions of KITLG and IGF1 genes. • Logistic regression showed the positive effect of A allele of miR-9 gene on litter size. • Principal component analysis showed a relationship among miR-9 gene and litter size. [ABSTRACT FROM AUTHOR]

The aim of this research was to evaluate the genetic variability of 18 wheat (Triticum aestivum L.) genotypes by quantitative agro-morphological traits, and to identify factors affecting the cultivars grain yield. A two years study (2017- 2019) was conducted at the Experimental Field of the Agricultural University of Tirana (altitude of 40 m above the sea level, Latitude 41°24'6.14"N and Longitude 19°44'9.93"E). Plant material used, is part of the 270 accessions of the base collection of the Institute of Plant Genetic Resources. During the growing crop years, the accessions were evaluated for different quantitative characters and morphological characterization of the accessions was conducted according to international standards. ANOVA, principal components and cluster analysis were carried out involving nine quantitative traits, such as tiller capacity, plant height, spike length, number of spikelet's per spike, number of seeds per spikelet, number of seeds per spike, weight of seeds per spike, weight of 1000 seeds and grain yield. According to PCA, three components exhibited about 75.51% of the variability within 18 wheat genotypes. Accessions were grouped into three major clusters based on Euclidean distance, suggesting that wheat genotypes with major level of dissimilarity between them were "Generozo" and "Ejesh". The results revealed that tiller capacity, number of seeds per spikelet, weight of seeds per spike/g and weight of 1000 seeds/g were the most important characters in differentiating the genotypes. Wheat genotypes used in this study reacted differently in the two growing seasons, giving high results in most of the traits that contribute directly in grain yield during 2017/2018 crop year. The use of principal component and correlation coefficient analysis in the wheat germplasm, simplify dependable classification of bread wheat germplasm, the identification of the superior genotypes and their relation with bio morphological traits with possibility expenditure in future breeding programs. [ABSTRACT FROM AUTHOR]

This study presents an improved technique for compression of electrocardiogram (ECG) signals, based on beat correlation of signal and principle component (PC) analysis, for ECG signal. For this purpose, two‐dimensional matrix of ECG signal based on temporal inter‐and intra‐beat correlation is constructed, and further compression is achieved using PC extraction. Beat correlation helps to generate very few PCs that increase the compression efficiency. A detailed analysis has been presented for ten signals having different rhythms, wave morphologies and abnormalities of Massachusetts Institute of Technology ‐ Beth Israel Hospital (MIT‐BIH) arrhythmia database. The effectiveness of the proposed method is examined with several attributes such as percentage root‐mean‐square difference, compression ratio, signal‐to‐noise ratio and correlation. Experimental results have shown that this method is very efficient for compression and suitable for different applications of telecardiology. [ABSTRACT FROM AUTHOR]

Inhibition of the p53–MDM2 interaction is a new therapeutic strategy to activate the wild-type function of p53 in tumors. Molecular dynamics (MD) simulations and calculations of binding free energies were performed to investigate the binding mechanisms of p53 and two inhibitors PMI and VZV to MDM2. The results show that van der Waals interaction is the main force to control the bindings of ligands to the hydrophobic cleft of MDM2, which basically agrees with the previous calculated and experimental studies. The results from the RMSF calculation, cross-correlation analysis and principal component (PC) analysis prove that the ligand bindings produce a significant effect on the conformation of the binding cleft of MDM2. In addition, the calculations of residue-based free energy decomposition suggest that the CH–CH, CH–π, and π–π interactions dominate the bindings of p53 and inhibitors to MDM2. This study can provide significant help for the design of potent inhibitors targeting the p53–MDM2 interaction. [ABSTRACT FROM AUTHOR]