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Carbapenem-Resistant Acinetobacter baumannii (CRAB) outbreak in intensive care units (ICUs) is a significant problem for healthcare facilities. In this study, we aimed to investigate the occurrence of CRAB isolates among ICU-admitted patients during the three waves of the COVID-19 pandemic in Iran using Multiple-Locus Variable Number Tandem-Repeat Analysis (MLVA). We obtained 50 (A) baumannii isolates from tracheal aspirate and blood culture samples. In the disc diffusion method, all isolates were cefotaxime, ceftriaxone, and cefepime-resistant, while 98% (49/50) of isolates were resistant to piperacillin, piperacillin-tazobactam, ceftazidime, and ciprofloxacin. Levofloxacin and tobramycin resistance was found in 76% (38/50) of isolates. In the microbroth dilution test all isolates were resistant to imipenem, 98% (49/50) to meropenem, 68% (34/50) to colistin, and 20% (10/50) to polymyxin (B) Based on the PCR findings, all isolates harbored blaOXA−40, ISAba-1, and int-2 genes. There were no isolates found that have the blaOXA−58, blaOXA−143, blaVEB−1, blaVIM, and int-3 genes. Among Extended-spectrum beta-lactamases (ESBL) genes, blaCTX−M, blaTEM, blaSHV, blaGES, and blaPER−1 have a prevalence of 42% (21/50), 84% (42/50), 58% (29/50), 78% (39/50), and 54% (27/50), respectively. 74% (37/50) of the isolates had the blaOXA−23 gene, while all of the isolates carried the blaOXA−40 gene. Among MBL genes, blaIPM, blaGIM, blaSIM, and blaNDM−1 have a prevalence of 20% (10/50), 8% (4/50), 22% (11/50), and 60% (30/50), respectively. The prevalence of int-1 was documented as 74% (37/50). Accordingly, all isolates were identified as CRAB. The co-existence of blaOXA−23/int-2 and blaOXA−23/isaba-1 was 74% (37/50). The co-existence of blaNDM−1/ISAba-1 was observed in 30 (60%) isolates. Using an 80% similarity threshold on the dendrogram constructed through MLVA typing, all isolates were grouped into two clusters: cluster A with 9 isolates from wave 3, and cluster B with 41 isolates from waves 3, 4, and 5. Our study confirms a clonal transmission of CRAB during the study period and suggests using molecular typing methods like MLVA in healthcare settings to identify dominant clones, antibiotic resistance patterns, and transmission routes. This will help to better manage the emergence and spread of antibiotic-resistant strains in future outbreaks. [ABSTRACT FROM AUTHOR]

Background: Candida auris is an opportunistic pathogen that has become widespread in recent years and shows resistance to multiple drugs. The aim of our study was to determine the antifungal susceptibilities of C. auris isolates, to perform a dendrogram from the mass spectra of strains obtained from matrix-assisted laser desorption ionization-time of flight mass spectrometry in order to evaluate the proteomic similarities of the strains and determine the geographical clade of C. auris strains in this study by the help of Multiplex RT-PCR. Methods: The samples yielded 58 C. auris isolates. MALDI TOF MS (BioMerieux, France) was used for identification of the isolates and Sensititre Yeast One (Thermoscientific) system was used for antifungal susceptibility testing. Dendrograms of strain's spectra were generated by using the RUO/Saramis (BioMerieux, France) database and evaluated through hierarchical clustering analysis. The selected nine strains were examined at the clade level by using Multiplex RT-PCR. Results The susceptibility profile of the strains revealed resistance to Fluconazole in 84% (MICs = 32) and resistance to Amphotericin B in 60% (MIC = 2). All strains were found to be sensitive to Anidulafungin and Micafungin. The dendrogram of the main spectra of C. auris isolates showed a similarity range of 35 - 100%. The nine strains studied were identified as clade 1 (South Asian). Conclusions: It was determined that C. auris strains were members of geographical clade 1, and the Amphotericin B resistance was found to be higher than expected. This situation poses a threat to critically ill patients. [ABSTRACT FROM AUTHOR]

We analyzed literature data on the composition of 479 glasses used to stabilize radioactive wastes, covering a wide range and including 51 oxides and few fluorides. The most common glass constituents included SiO2, B2O3, Na2O, and Fe2O3 in varying amounts, with a predominance of borosilicate glasses. Seven families of waste radioactive glasses were observed, including borosilicates, silicates, boroaluminosilicates, iron phosphates, aluminosilicates, sodium iron phosphates, and boroaluminates. These data were used to estimate an average composition associated with a sodium borosilicate glass. Multivariate exploratory methods were used to analyze and classify the compositions of the waste radioactive glasses using multidimensional scaling and hierarchical clustering. Four main clusters were observed, the largest with 417 glasses, mainly silicates, borosilicates, aluminosilicates, and boroaluminosilicates. The results of this work have shown that it is possible to map radioactive waste glasses according to their composition, promoting a road map for future applications with specific properties. [ABSTRACT FROM AUTHOR]

Genetic similarity determines the extent to which two genotypes share common genetic material. It can be measured in various ways, such as by comparing DNA sequences, proteins, or other genetic markers. The significance of genetic similarity is multifaceted and encompasses various fields, including evolutionary biology, medicine, forensic science, animal and plant breeding, and anthropology. Genetic similarity is an important concept with wide application across different scientific disciplines. The research material included 21 rapeseed genotypes (ten interspecific Brassicaceae hybrids of F2 generation and 11 of their parental forms) and 146 alleles obtained using 21 ISSR molecular markers. In the presented study, six measures for calculating genetic similarity were compared: Euclidean, Jaccard, Kulczyński, Sokal and Michener, Nei, and Rogers. Genetic similarity values were estimated between all pairs of examined genotypes using the six measures proposed above. For each genetic similarity measure, the average, minimum, maximum values, and coefficient of variation were calculated. Correlation coefficients between the genetic similarity values obtained from each measure were determined. The obtained genetic similarity coefficients were used for the hierarchical clustering of objects using the unweighted pair group method with an arithmetic mean. A multiple regression model was written for each method, where the independent variables were the remaining methods. For each model, the coefficient of multiple determination was calculated. Genetic similarity values ranged from 0.486 to 0.993 (for the Euclidean method), from 0.157 to 0.986 (for the Jaccard method), from 0.275 to 0.993 (for the Kulczyński method), from 0.272 to 0.993 (for the Nei method), from 0.801 to 1.000 (for the Rogers method) and from 0.486 to 0.993 (for the Sokal and Michener method). The results indicate that the research material was divided into two identical groups using any of the proposed methods despite differences in the values of genetic similarity coefficients. Two of the presented measures of genetic similarity (the Sokal and Michener method and the Euclidean method) were the same. [ABSTRACT FROM AUTHOR]

For most landslides, several destabilising processes act simultaneously, leading to relative sliding along the soil or rock mass surface over time. A number of machine learning approaches have been proposed recently for accurate relative and cumulative landside displacement prediction, but researchers have limited their studies to only a few indicators of displacement. Determining which influencing factors are the most important in predicting different stages of failure is an ongoing challenge due to the many influencing factors and their inter-relationships. In this study, we take a data-driven approach to explore correlations between various influencing factors triggering slope movement to perform dimensionality reduction, then feature selection and extraction to identify which measured factors have the strongest influence in predicting slope movements via a supervised regression approach. Further, through hierarchical clustering of the aforementioned selected features, we identify distinct types of displacement. By selecting only the most effective measurands, this in turn informs the subset of sensors needed for deployment on slopes prone to failure to predict imminent failures. Visualisation of the important features garnered from correlation analysis and feature selection in relation to displacement show that no one feature can be effectively used in isolation to predict and characterise types of displacement. In particular, analysis of 18 different sensors on the active and heavily instrumented Hollin Hill Landslide Observatory in the north west UK, which is several hundred metres wide and extends two hundred metres downslope, indicates that precipitation, atmospheric pressure and soil moisture should be considered jointly to provide accurate landslide prediction. Additionally, we show that the above features from Random Forest-embedded feature selection and Variational Inflation Factor features (Soil heat flux, Net radiation, Wind Speed and Precipitation) are effective in characterising intermittent and explosive displacement. [ABSTRACT FROM AUTHOR]

Common and tartary buckwheat are important cultivated species of the genus Fagopyrum. Genetic polymorphism of thirty-five genotypes of common buckwheat (Fagopyrum esculentum Moench) and tartary buckwheat (Fagopyrum tataricum Gaertn.) was analyzed using 10 random amplified polymorphic DNA (RAPD) primers. A total of 119 DNA fragments were amplified using ten RAPD primers with an average of 11.9 fragments per primer. The number of amplified fragments ranged from 6 (OPB-08) to 16 (SIGMA-D-01). PIC values ranged from 0.782 (OPC-08) to 0.919 (SIGMA-D-01) with an average of 0.871 per primer. The marker index (10.364) and diversity detecting index (2.961) were high and presented the utility of used marker technique. To evaluate the genetic relationships among buckwheat genotypes a phylogenetic tree based on UPGMA algorithm was constructed. The genotypes of common and tartary buckwheat were separated independently into cluster I and II. Cluster I separated 14 genotypes of tartary buckwheat into two subclusters (Ia, Ib). Genotype 903016, which originated in Pakistan, was separated individually into the subcluster Ia. Cluster II included genotypes of common buckwheat and was further subdivided into subcluster IIa and IIb. Two genotypes of subcluster IIb (Bamby and Hruszowska) were genetically the closest. Bamby and Hruszowska reflected the maximum similarity value (0.605) according to Jaccard's coefficient of similarity. Based on the presented data it is suggested that the RAPD technique is suitable for differentiation among genotypes of common and tartary buckwheat. RAPD primers have proven to be reliable and useful method for studying genetic variability of buckwheat genotypes. [ABSTRACT FROM AUTHOR]

Identification of orchid species is important in orchid conservation. Diversity in orchids can be studied from morphological and anatomical aspects. Observation of morphological characters is easier because it can be done on all plant parts, including stems, flowers, leaves, roots, seeds, and fruit. This research was conducted to study the morphological diversity quantitatively between hybrid Phalaenopsis orchid varieties. The research aims to identify the morphological characteristics of 15 hybrid genotype/accession of Phalaenopsis orchids, followed by descriptor for ornamental orchid plants. Observation variables, including 19 quantitative parameters from leaf characterization and flower characterization. Data analysis was performed using the NTYSYS (Numerical Taxonomy and Multivariate Analysis System) version 2.02i to determine genetic distance; Grouping (cluster) using the UPGMA (Unpair Group of Mean Arithmetic) method. The results of the grouping dendrogram showed that based on the quantitative morphological characters of 15 species of Phalaenopsis hybrid orchids, there were three major groups at 0.92 Dist, namely group I consist of 8 hybrid Phalaenopsis orchids, group II consisted of 6 hybrid Phalaenopsis orchids, and group III only had the P. Shu Long Beauty orchid. P. Shu Long Beauty had the greatest diversity of 1.44 Dist with the other 14 accessions. Taisuko kaaladian "v3" and Dtps. Fullers C-Plus 3790 has a diversity of 0.07. Whereas Dtps. Fullers Sunset has a diversity of 0.90 with the accessions Taisuko kaaladian" v3", Dtps. Fullers C-Plus 3790, P. Red Shoe Ox1408, and P. Ox Black Face Ox1647. [ABSTRACT FROM AUTHOR]

Diversity information mining about a crop for different attributes is an essential step for effective breeding programs. The present investigation evaluates the quantum of genetic variability and determines the relationship among the important agro-economic traits based on two years of phenotypic data of 210 accessions of linseed. The traits, capsule weight per plant, capsule per plant, husk weight per plant, and seed weight per plant exhibited comparatively higher genetic coefficient of variation (GCV) and phenotypic coefficient of variation (PCV). In contrast, oil content and seed per capsule exhibited a lower value. The high magnitude of broad sense heritability was observed for all traits except seeds per capsule and husk weight per plant. The trait, capsules per plant, plant height, and days to 50% flowering showed high genetic advance coupled with high heritability. Hierarchical cluster analysis grouped 210 accessions into six distinct clusters. Out of 210, 144 (68.57%) accessions were grouped into three clusters (I, II, and III), in which cluster-III was the largest, containing 64 accessions followed by cluster II and cluster-I. The highest inter-cluster distance was observed between clusters-I and V (127.85), while the lowest was between clusters-II and IV (27.09). The positive correlation of capsule weight per plant with the seed weight per plant and a negative correlation with the days to 50% flowering indicates that high yielding linseed varieties with early flowering/maturity could be developed through direct and indirect selection. Further, seed yield and oil content could be enhanced together as indicated by ghe positive association among these two important traits. In this study, high yielding accessions with moderate to high oil content such as GP36, GP31, GP14, GP54, GP26, GP24, GP34, GP21, GP37 and GP27 and early flowering (less than 70 days) accessions such as GP2, GP26, GP27, CG33, CG44, CG42, CG132, and CG31 identified as potential genetic materials that could be exploited for developing early maturing varieties with high yield. In addition, information's on various genetic parameters will help breeders to devise suitable breeding methodology for linseed genetic improvement for targeted traits. [ABSTRACT FROM AUTHOR]

Mediterranean olive cultivars (Olea europaea), including the historic cultivar 'Mehras,' were analyzed using ISSR to identify and study the genetic relationships among them. Three ISSR primers (UBC-807, ISSR 810, ISSR 825) generated 784 data entries (221 for present and 563 for absent bands), which were analyzed using SPSS and Structure software. Results showed that fragment size ranged between 250 to 1700 bp. The similarity among the fourteen cultivars ranged from 10% between cultivars 'Nabali Muhasan' and 'Arbosana' up to 59% between genotypes 'Qaisi' and 'Kafari Baladi.' When primers were evaluated for their discriminating power, it was found that all of them had a value equal to 1. Moreover, the primer PIC values were 0.29, 0.31, and 0.31 for ISSR 807, ISSR 810, and ISSR 825, respectively. The constructed dendrogram showed four main clades, while Nabali Muhasan did not cluster with any. The first clade clustered included five cultivars. The second clade included four cultivars. Both the third and fourth clades included two cultivars each. The genome structure confirms the dendrogram tree. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Agriculture & Nature / Kahramanmaraş Sütçü İmam Üniversitesi Tarım & Doğa Dergisi is the property of Kahramanmaras Sutcu Imam Universitesi and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The aim of this article is to study the degradation of a composite material under static pressure. The high pressure condition is similar to the one encountered inside hydrogen tanks. Damage modeling was used to evaluate the behavior of hydrogen tanks to high pressure. A practical approach, coupling a finite element method (FEM) simulation and machine learning (ML) algorithm, is suggested. The representative volume element (RVE) was used in association with a choice of a behavior law and a damage law as an input data. Algorithms for ML classification such as K‐nearest neighbors (k‐NN) and a special k‐NN with a dynamic time warping metric were used. The hierarchical clustering through dendrograms visualizations allowed to exhibit the impact of composite parameters in relation to fiber, matrix properties and fiber volume fraction on the strain degradation under external static pressure. Continuing this, the optimum RVE which shows a low degradation value will be exhibited. [ABSTRACT FROM AUTHOR]

Clustering is a well-known and studied problem, one of its variants, called contiguity-constrained clustering, accepts as a second input a graph used to encode prior information about cluster structure by means of contiguity constraints i.e. clusters must form connected subgraphs of this graph. This paper discusses the interest of such a setting and proposes a new way to formalise it in a Bayesian setting, using results on spanning trees to compute exactly a posteriori probabilities of candidate partitions. An algorithmic solution is then investigated to find a maximum a posteriori partition and extract a Bayesian dendrogram from it. The interest of this last tool, which is reminiscent of the classical output of a simple hierarchical clustering algorithm, is analysed. Finally, the proposed approach is demonstrated with experiments on simulated data and real applications. A reference implementation of this work is available in the R package gtclust that accompanies the paper. [ABSTRACT FROM AUTHOR]

Copyright of Bosque (03048799) is the property of Facultad de Ciencias Forestales, Universidad Austral de Chile and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: Variety characterization is the foremost important step that should be done by breeders to classify a variety into distinct groups. A significant technique for locating and assessing several genotypes for the registration, protection and production of seeds of superior quality is the Distinctness, Uniformity and Stability (DUS) characterization. Consequently, the current investigation aimed to use DUS descriptors to describe and assess the variance present in mungbean genotypes. Methods: One hundred forty-two mungbean genotypes were examined using 21 agro-morphological qualitative DUS descriptors in a randomized block design with two replications across two seasons, kharif 2021 and kharif 2022. Result: In the twenty-one DUS traits that were examined, four characters' plant growth habit, leaf shape, leaf size and seed size exhibited trimorphic variance. Three characters (plant habit, stem pubescence and pod pubescence) were found to be identical among all genotypes while fourteen characters displayed dimorphic variance. All of the mungbean genotypes displayed a significant degree of variance for all DUS characteristics. Based on the UPGMA method of clustering, the dendrogram classified all the one hundred forty-two genotypes into three major clusters. The presence of variation among the genotypes under study was demonstrated by the further classification of these primary clusters into five sub-clusters. The majority of the genotypes were found in cluster II (121 genotypes), which was followed by cluster I (18 genotypes) and cluster III (3 genotypes). [ABSTRACT FROM AUTHOR]

The pH values of soil samples collected from the topsoil to a depth of 50cm range from 5.78 to 6.64, with an average of 6.284, indicating slightly acidic soil. Water samples near auto-mechanic workshops fall below NSDWQ and WHO standards. Soil heavy metal levels mostly meet ACV and Dutch guidelines, except for Iron (Fe), Copper (Cu), Zinc (Zn), Cadmium (Cd), and Chromium (Cr). Soil contamination analysis shows a high to extreme degree of contamination, likely from the auto-mechanic workshop. Positive correlations between metal pairs suggest a common source and transport to the soil. Principal Component Analysis (PCA) of soil samples reveals Cu, Zn, Fe, Ni, and Pb as dominant metals, while Ni-Cr shows negative correlations with others. In water samples, Cu, Cd, and Co dominate, indicating a different contamination source. Soil and water samples generally meet NSDWQ and WHO standards, but Total Dissolved Solids (TDS), Electrical Conductivity (EC), and Salinity exceed these standards. Understanding these findings is crucial for managing and mitigating contamination risks near auto-mechanic workshops. [ABSTRACT FROM AUTHOR]

Copyright of Archaeobios is the property of Arqueobios and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Archaeobios is the property of Arqueobios and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Archaeobios is the property of Arqueobios and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Archaeobios is the property of Arqueobios and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Pomegranate (Punica granatum L.) is an ancient edible fruit crop well recognized for its immense nutraceutical and medicinal properties. Precise morphological characterization of wild, exotic and commercial (cultivar) varieties and understanding the molecular variability in perennial crops like pomegranate is essential for developing varietal DNA fingerprints, identifying true-to-type of genotypes, to avoid duplication and overcome the problem of clonal admixture. It has become a challenge to identify varieties based solely on observable phenotypic traits due to dynamic environmental factors that influence physical traits and increasing number of varieties. Hence, the implementation of stable molecular markers is the best complementary biotechnological tool, which fulfil the above requirements. In our first objective, we identified 24 polymorphic SSR markers out of 40. These SSRs screened on 13 different varieties of pomegranate. The PIC value ranged from 0.13 to 0.37 (mean 0.25) and heterozygosity percent ranged from 0.14% to 0.50% (mean 0.35%). Highest PIC value and heterozygosity observed in PgSSR78 marker. Similarity coefficient matrix showed the genetic distance between the twenty-four varieties, ranged from 0.58 to 0.99. Maximum similarity was observed between Alah and Khandari. Minimum similarity was found between IC318743 and 1185 followed by Maha and 1185. PgSSR16, PgSSR23, PgSSR49, PgSSR60, PgSSR32, PgSSR40, PgSSR78 markers were found with high PIC value and heterozygosity and these primers could be useful for pomegranate cultivar identification. From this study, microsatellite markers have proven to be very useful marker for developing varietal identification marker at early growth stage due to its high polymorphism, abundance, multi-allelic and co-dominant inheritance. [ABSTRACT FROM AUTHOR]

This is aimed at assessing the effect of the analysed physico-chemical, microbial parameters and heavy metals on run-off in selected routes at Nsukka Urban. The major roads selected included campus gate (CG), Ikenga road (IR), Enugu road (ER) and Ikpa/Orba road (IKPR); with university market road serving as control location (C). Four run-off samples were collected from each of the selected roads; in October 2020. The heavy metals were analysed using the Atomic Absorption Spectrophotometer (AAS); other parameters were analysed using standard methods. The results revealed that the analysed metals concentrations ranges from (in ppm): Cd (0.00–0.09), As (0.23–1.58 mg/L), Fe (6.48–79.72), Hg (.00–3.00), Pb (0.25–0.75), Ni (0.21–0.92), Mn (0.10–0.21), and Cr (0.67– 01.33) indicating increase in the concentration of samples as against control showing anthropogenic influences. The results also unravelled that metal concentrations are above the permissible standards for potable water. Coliform ranged (0.00–1736.00 cfu/mL), Turbidity (22.50–52.80 NTU) and Organic matter (55–130 mg/l). All other parameters like pH, EC, K+, Mg2+, and Na+ are all within the permissible limit of WHO. Multivariate and Sorensen analyses were also employed to separate chemical variables into components which gave a clue to the different sources of contaminants within an area, based on the indicator parameter associations. This analysis unravels anthropogenic contamination from domestic solid and sewage wastes on the quality of surface run-off and should be mitigated. [ABSTRACT FROM AUTHOR]

Context: Preservation of genetic diversity of species is a pressing issue; in particular, the preservation of the gene pool of many rare and endangered plants is a priority. Species of the genus Crambe (family Brassicaceae) have potential in agriculture and bioremediation. Aims: This study aims to assess the genetic diversity and DNA fingerprint of five rare species of the genus Crambe , and to develop the concept of a genetic passport for rare plants. Methods: DNA fingerprinting was conducted via the inter simple sequence repeat (ISSR) method, using six ISSR primers. Hierarchical cluster analysis of the species was performed. Key results: In total, 145 polymorphic loci were detected. The studied species formed two different clusters on genetic dendrogram analysis. The first cluster comprised two species, Crambe steveniana and C. tataria from a single subsection (Tatariae), forming a common clade. They were the most genetically close species with genetic similarity of 0.8431. The remaining three species (C. cordifolia , C. maritima , C. pinnatifida), from another subsection of Crambe , formed nodes from the general clade. Conclusions: The findings allow plants to be genetically certified using our methods and informative ISSR primers for rare plants. We were able to propose a genetic formula identifying a species and present an example of a genetic passport for rare plants. The genetic structure of C. pinnatifida was investigated for the first time. Implications: The present findings contribute to the systematics and critical investigation of rare plant species with genetic resource potential. A genetic passport could be used in the protection of copyright of agricultural varieties. We assessed the genetic diversity and DNA fingerprint of five rare species of the Brassicaceae genus Crambe , using six inter simple sequence repeat primers. The species could be clustered into two groups according to subsection of Crambe. The results demonstrate that the methods allow rare plants to be genetically certified. [ABSTRACT FROM AUTHOR]

This article considers clustering stationary scalar time series using their marginal properties and a hierarchical method. Two major issues involved are to detect the existence of clusters and to determine their number. We propose a new test statistic for detecting whether a data set consists of multiple clusters and a new procedure to determine the number of clusters. The proposed method is based on the jumps, that is, the increments, in the heights of the dendrogram when a hierarchical clustering is applied to the data. We use autoregressive sieve bootstrap to obtain a reference distribution of the test statistics and propose an iterative procedure to find the number of clusters. The clusters found are internally homogeneous according to the test statistics used in the analysis. The performance of the proposed procedure in finite samples is investigated by Monte Carlo simulations and illustrated by some empirical examples. Comparisons with some existing methods for selecting the number of clusters are also investigated. [ABSTRACT FROM AUTHOR]

The Ann Arbor system is disadvantaged in utilizing information from additional prognostic factors. In this study, we applied the Ensemble Algorithm for Clustering Cancer Data (EACCD) to create a prognostic system for lymphoma that integrates additional prognostic factors. Hodgkin and non-Hodgkin lymphoma survival data were extracted from the Surveillance, Epidemiology, and End Results Program of the National Cancer Institute and divided into the training set (131,725 cases) and the validation set (15,683 cases). Five prognostic factors were studied: Ann Arbor stage, type, site, age, and sex. EACCD was applied to the training set to produce a prognostic system, called an EACCD system, for convenience. The EACCD system stratified patients into eight prognostic groups with well-separated survival curves. These eight prognostic groups had significantly higher accuracies in survival prediction than the 24 Ann Arbor substages. A higher-risk group in the EACCD system roughly corresponds to a higher Ann Arbor substage. The proposed system shows a good performance in risk stratification and survival prediction on both the training and the validation sets. The EACCD system expands the traditional Ann Arbor staging system by leveraging additional prognostic information and is expected to advance treatment management for lymphoma patients. [ABSTRACT FROM AUTHOR]

Background: Healthcare-associated infections appear in a patient receiving medical attention at a hospital or other healthcare facility and develops infections that weren't present when they were admitted. One of the most important organisms causing infections acquired in hospitals is Staphylococcus aureus (S. aureus). For many bacterial species, Random Amplified Polymorphic DNA (RAPD) is a low-cost but effective typing technique. Objectives: To determine the genotypic polymorphism, the level of genetic relatedness, and the antimicrobial sensitivity and resistance among various S. aureus isolates. Methods: The following tests were performed on 50 samples that were obtained using strict aseptic precautions: sample culture, isolate identification using colony morphology, Gram stained film, biochemical responses, and antibiotic susceptibility testing. After RAPD-PCR, Syngene gene tool software was used to analyse the fingerprint pattern. Results: The most prevalent isolated organism was S. aureus. as it represented (70%) of isolated pathogens. Vancomycin and linezolid were effective against S. aureus isolates. The isolates of S. aureus were more common in nasal swab (42.9%) followed by wound (28.5%) then urine &endotracheal aspirate (14.3%). Patterns of RAPD-PCR of S.aureus isolates generated with primer GEN1-50-01 (5'GTGCAATGAG-3') resulting in several polymorphic bands and a dendrogram was created. Conclusions: S. aureus is an important cause of HCAI, Health care workers represent an important source of HCAI, RAPD -PCR technique was an easy and rapid one to perform with a good discriminatory power in typing (fingerprinting) of Staphylococcus aureus. [ABSTRACT FROM AUTHOR]

Knowledge about the genetic diversity of the available common bean germplasm can help breeders properly direct the choice of genetic material in the breeding process. The aim of the present work was to estimate the usefulness of 10 RAPD and 10 SCoT markers in genetic diversity detection among 33 common bean genotypes. Both molecular marker systems were able to generate high levels of polymorphism in the genetic material, which was supported by the relatively high polymorphic information content (PIC) values observed for the used markers. The Diversity Detection Index (DDI) and Marker Index (MI) were used to compare the effectiveness of RAPD and SCoT markers. For both techniques, high values of MI and DDI were calculated, representing their effectivity. The SCoT markers showed higher values of the parameters used (MI = 7.474, DI = 2.265) than the RAPD markers (MI = 5.323, DDI = 1.612), indicating their higher efficiency in the detection of molecular variability. Three constructed dendrograms and PCoA plots were created using RAPD and SCoT, and both methods combined confirmed sufficient separation of the bean genotypes from each other. At the same time, a higher efficiency of SCoT markers compared to RAPD markers in the detection of the genetic diversity of beans was also proven. The results may be of future interest in the choice of genetically distant material for breeding purposes. [ABSTRACT FROM AUTHOR]

In this era, news is not only generated continuously with high speed but also growing in its amount by different web sources like talent hunt, news agencies, and so on. To predict the exact class of news depending on its topic, GepH (Grouped entity predictor for Hindi) is proposed using entity extraction and grouping. Entity extraction is popular for English corpus. Hindi is a national language due to its resource scarceness not being explored so much by researchers. More than 1,270 news are processed to apply entity extraction, clustering, and classification using the vector space model for Hindi (VSMH), Synset vector space model for Hindi (SVSMH), and grouped entity document matrix for Hindi (GEDMH). Synset-based dimension reduction techniques are used to get improved accuracy. Evaluation of HAC using three matrices shows the best performance of GEDMH for varied datasets. Thus labelled corpus obtained after applying HAC (Hierarchical agglomerative clustering) to GEDMH is used as a training dataset and predictions are done using random forest and Naïve Bayes. The Naïve Bayes classifier implemented using the proposed GEDMH performs the best. GepH shows 0.8 purity, 0.4 entropy, and 0.3 as error rate for 1,273 Hindi news. [ABSTRACT FROM AUTHOR]

In the present investigation 28 genotypes of soybean were analysed using 37 start codon targeted (SCoT) markers and 37 primers produced 260 DNA fragments with an average of 7.03 bands per primer. From these 37 primers, primers SCoT 33 and SCoT 65 wos the most polymorphic, where 10 polymorphic amplification products were detected. The lowest number of amplified polymorphic fragments (2) was detected by primers SCoT 8, SCoT 14, SCoT 19, SCoT 31 and SCoT 59. Of the 260 amplified bands, 200 (77.27 %) were polymorphic, with an average of 5.41 polymorphic bands per primer. To determine the level of polymorphism in the analysed group of soybean genotypes, polymorphic information content (PIC) was calculated. The polymorphic information content (PIC) value ranged from 0.512 (ScoT 66) to 0.968 (SCoT 12) with an average of 0.777. The dendrogram of genetic relationships among 28 soybean genotypes based on 37 SCoT markers was constructed. The hierarchical cluster analysis showed that the soybean geno-types were divided into 4 main clusters. The markers used in this study created a number of polymorphic bands among the different cultivars that can be utilized as molecular markers for their differentiation. The obtained data indicated that SCoT technique could be used efficiently for identification and differentiation of the soybean genotypes. [ABSTRACT FROM AUTHOR]

Stocks of Amur common carps of three different geographical locations viz. Tamil Nadu (Krishnagiri hatchery), Karnataka (Hesaraghatta) and Kolkata (Das fish hatchery) representing different environmental conditions were collected at selected breeding centres. All three stocks were acclimatized and reared in laboratory conditions with similar environmental and management conditions. The screening was performed with 140 decamer primers, of which, eight primers (OPA-04, OPA-06, OPA-10, OPA-20, OPB-17, OPF-09, OPF-10, and OPG-9) indicated consistent and significant polymorphism were selected for RAPD-PCR analysis. RAPD - PCR analysis result indicated Tamil Nadu stock with higher polymorphism (82.38%) compared to the other two stocks. Highest Shannon's diversity (0.3079) and higher Nei's heterozygosity (0.2395) were observed for Tamil Nadu stock. In terms of genetic identity and genetic distance, Kolkata and Karnataka stocks showed a maximum genetic distance of 0.5075 and a minimum genetic identity of 0.6020, while the Kolkata and Tamil Nadu stocks exhibited a maximum genetic identity of 0.7234 and a minimum genetic distance of 0.3238. Further, the study indicated that Tamil Nadu stock is related closely to Kolkata stock and distantly to Karnataka stock. Growth trials indicated better performance of Tamil Nadu stock in comparison with the other two stocks. The r2 value of 0.5710 between the percentage of polymorphism and mean body weight attained for different stocks of Amur common carp showed that the percentage of polymorphism and mean body weight attained are moderately positively correlated. [ABSTRACT FROM AUTHOR]

Background: Lentil is an important legume crop that plays a vital role in sustainable agriculture and human health. However, the restricted genetic foundation or parentage of contemporary cultivars has arisen as a serious challenge for lentil development. Therefore, determining the genetic diversity and yield-related characteristics is crucial for the breeder to broaden the genetic base and aid in selecting the desirable parents for hybrid development programmes. Methods: In the current study, microsatellite markers were used for diversity analysis among 37 lentil genotypes. Morphological and molecular systems both were able to differentiate lentil genotypes. Among applied SSR primers 10 were able to produce successful amplifications with template DNA of all the studied genotypes of lentil. Result: A sum of 357 scoreable bands were produced, 148 of which accounted for 41.45% polymorphism. The UPGMA dendrogram grouped 37 lentil genotypes into 2 groups. PIC values ranged from 0.37 to 0.77. For this experiment, SSR 80, SSR 130, SSR 34-2 and SSR 33 were highly informative polymorphic markers, demonstrating the efficacy and higher resolution in exposing molecular genetic diversity among lentil genotypes. The highest numbers of alleles (5) were produced by SSR 80 primer which was selected as extremely polymorphic. This study reveals the variation across lentil genotypes, which might be employed further in breeding efforts for lentils that result in strong heterosis in the segregating generation. The SSR markers found as polymorphic may also be utilized for further polymorphism analysis among different set of lentil genotypes. [ABSTRACT FROM AUTHOR]

Background: Lignocellulosic biomass from rice straw possesses enormous potential in generating bioenergy thereby reducing the dependence of human on non-renewable fuel sources. Developing rice varieties of such calibre necessitates biochemical characterization as well as assessing the presence of genetic diversity among the rice genotypes with respect to cellulose content. Methods and results: Forty-three elite rice genotypes were selected for biochemical characterization and SSR marker-based genetic fingerprinting. For genotyping, 13 cellulose synthase specific polymorphic markers were used. The diversity analysis was performed using TASSEL 5.0 and GenAlE × 6.51b2, software program. Of the 43 rice varieties, CR-Dhan-601, CR-Dhan-1014, Mahanadi, Jagabandhu, Gouri, Samanta and Chandrama were found to possess desirable lignocellulosic composition with respect to harnessing green fuels. The marker OsCESA-1.3 expressed the highest PIC (0.640), while the marker OsCESA-6.3 of lowest PIC (0.128). A moderate average estimate (0.367) of PIC was observed under current set of genotypes and marker system. The dendrogram analysis grouped the rice genotypes into two principal clusters i.e., cluster I and II. Cluster-II is monogenetic, while cluster-I is having 42 genotypes. Conclusions: The moderate level of both PIC and H average estimates indicate the narrow genetic bases of the germplasms. The varieties falling under different clusters possessing desirable lignocellulosic composition can be used in a hybridization programme to develop bioenergy efficient varieties. The promising varietal combinations that can be used as parents for developing bioenergy efficient genotypes are Kanchan / Gobinda, Mahanadi / Ramachandi, Mahanadi / Rambha, Mahanadi / Manika, Rambha / Manika, Rambha / Indravati and CR-Dhan-601 / Manika as they offer an advantage of higher cellulose accumulation. This study helped in identification of suitable dual purpose rice varieties for biofuel production without compromising food security. [ABSTRACT FROM AUTHOR]

Salvia is the largest genus in the Lamiaceae family in the world and Iran contains 58 species. This genus contains over 900 species of annual and perennial herbaceous plants and differs from other lamias in the unusual structure of their plumage. Information on important medicinal plants' genetic diversity and population structure is well documented in the literature. Increased genetic diversity can reduce the negative effects of inbreeding on populations. We investigated genetic variation among eight Salvia species using ISSR molecular markers. ISSR is a molecular marker amplified by PCR using microsatellite primers. Samples were gathered from various locations in Iran. Most samples were assigned to Ardabil city. Twenty randomized ISSR primers were used, generating different polymorphic bands. The 20 ISSR primers generated 225 valuable bands and 221 bands were polymorphic (98/2%). Pairwise genetic distances ranged from 0.083 to 0.577. Dendrograms were generated using the UPGMA method using NTSYSpc 2.02i software to identify seven major groups from eight Salvia species. The polymorphism levels observed in the present study represent a high degree of genetic diversity among Salvia species. Following the first study on the genetic relationships of eight species of Salvia in Iran using RAPD and ISSR molecular markers, this study was performed using the ISSR molecular marker to investigate the genetic relationships of eight other species of Salvia. The results of this research represented that the molecular markers of the ISSR are suitable for assessing genetic variation and evolutionary relationships among Salvia species, showing a wide range of dispersal. [ABSTRACT FROM AUTHOR]

Enhancement of okra fruit production requires identification of genotypes with promising seed yield attributes, thus multivariate techniques were employed to reveal genetic and morphological attributes of sixteen diverse okra lines during wet and dry seasons in 2019 at Teaching and Research Farm, College of Agriculture, Osun State University, Ejigbo Campus. Seeds were sown in single-row plots of 5 m long, spaced 0.70 m apart and 0.50 m within on sandy loam soil in a randomized complete block design. The dry season crop was supported by the application of 12 mm water weekly. Data collected on growth and seed traits were subjected to the General Linear Model (GLM), principal component analysis (PCA), and cluster analysis using the Statistical Analysis System (SAS, 2018). The petiole color was scored according to IPGRI (1991) square root transformed prior to the analysis. Results showed highly significant lines, season, and their interactions for almost all traits. Four PCAs accounted for 85.77% and the first two PCA captured 51% of the total variations. Both PCA and cluster analysis grouped the lines into four and revealed the potentials of SAHARI F1, NGB01197, and LD-88 for high seed yield. It is concluded that these lines can be incorporated into okra yield improvement program. [ABSTRACT FROM AUTHOR]

A farmer can use machine learning to make decisions about what crops to sow, how to care for those crops throughout the growing season, and how to predict crop yields. According to the World Health Organization, agriculture is essential to the nation's quick economic development. Food security, access, and adoption are the three cornerstones of the organization. Without a doubt, the main priority is to ensure that there is enough food for everyone. Increasing agricultural yield can help ensure a sufficient supply. The country-wide variation in crop yields is substantial. As a result, this will be the foundation for research into whether cluster analysis can be used to identify crop yield patterns in a field. Previous study investigations were only marginally successful in accomplishing their primary intended objectives because of unstable conditions and imprecise methodology. The vast majority of farmers base their predictions of crop yield on prior observations of crop growth in their farms, which can be deceptive. Standard preprocessing methods and random cluster value selection are not always reliable, according to the literature. The proposed study overcomes the shortcomings of conventional methodology by highlighting the significance of machine learning-based classification/partitioning and hierarchical approaches in offering a trained analysis of yield prediction in the state of Karnataka. The dataset used for the study was collected from the ICAR-Taralabalu Krishi Vigyan Kendra, Davangere, Karnataka. In the two dataset analysis techniques employed in the study to find anomalies, crop area, and crop production are significant variables. Crop area and crop yield are important variables in the two dataset analysis methods used in the study to detect anomalies. The study emphasizes the importance of a mathematical model and algorithm for identifying yield trends, which can assist farmers in selecting crops that have a large seasonal impact on yield productivity. [ABSTRACT FROM AUTHOR]

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Comparing parasite genotypes to inform parasitic disease outbreak investigations involves computation of genetic distances that are typically analyzed by hierarchical clustering to identify related isolates, indicating a common source. A limitation of hierarchical clustering is that hierarchical clusters are not discrete; they are nested. Consequently, small groups of similar isolates exist within larger groups that get progressively larger as relationships become increasingly distant. Investigators must dissect hierarchical trees at a partition number ensuring grouped isolates belong to the same strain; a process typically performed subjectively, introducing bias into resultant groupings. We describe an unbiased, probabilistic framework for partition number selection that ensures partitions comprise isolates that are statistically likely to belong to the same strain. We computed distances and established a normalized distribution of background distances that we used to demarcate a threshold below which the closeness of relationships is unlikely to be random. Distances are hierarchically clustered and the dendrogram dissected at a partition number where most within-partition distances fall below the threshold. We evaluated this framework by partitioning 1,137 clustered Cyclospora cayetanensis genotypes, including 552 isolates epidemiologically linked to various outbreaks. The framework was 91% sensitive and 100% specific in assigning epidemiologically linked isolates to the same partition. [ABSTRACT FROM AUTHOR]

In the current paper, we present the results of Kazakh propolis investigations. Due to limited data about propolis from this country, research was focused mainly on phytochemical analysis and evaluation of propolis antimicrobial activity. uHPLC-DAD (ultra-high-pressure-liquid chromatography coupled with diode array detection, UV/VIS) and uHPLC-MS/MS (ultra-high-pressure-liquid chromatography coupled with tandem mass spectrometry) were used to phytochemical characteristics while antimicrobial activity was evaluated in the serial dilution method (MIC, minimal inhibitory concentration, and MBC/MFC, minimal bactericidal/fungicidal concentration measurements). In the study, Kazakh propolis exhibited a strong presence of markers characteristic of poplar-type propolis—flavonoid aglycones (pinocembrin, galangin, pinobanksin and pinobanskin-3-O-acetate) and hydroxycinnamic acid monoesters (mainly caffeic acid phenethyl ester and different isomers of caffeic acid prenyl ester). The second plant precursor of Kazakh propolis was aspen–poplar with 2-acetyl-1,3-di-p-coumaroyl glycerol as the main marker. Regarding antimicrobial activity, Kazakh propolis revealed stronger activity against reference Gram-positive strains (MIC from 31.3 to above 4000 mg/L) and yeasts (MIC from 62.5 to 1000 mg/L) than against reference Gram-negative strains (MIC ≥ 4000 mg/L). Moreover, Kazakh propolis showed good anti-Helicobacter pylori activity (MIC and MBC were from 31.3 to 62.5 mg/L). All propolis samples were also tested for H. pylori urease inhibitory activity (IC50, half-maximal inhibitory concentration, ranged from 440.73 to 11,177.24 µg/mL). In summary Kazakh propolis are potent antimicrobial agents and may be considered as a medicament in the future. [ABSTRACT FROM AUTHOR]

Laportea aestuans L. (Chew), Commelina virginica (L.) and Sida rhombifolia (L.) are common wild plants used in treating several ailments including diarrhea, dysentery, hernia, oedema, ulcers and many more in traditional African medicine especially, Nigeria. The potentials of Random Amplified polymorphic DNA (RAPD) primers in delimiting intra-specific variation in L. aestuans, C. virginica and S. rhombifolia was assessed using three RAPD primers. Plant and soil samples were collected from 19 local government areas in Lagos State and assessed for genetic and biochemical relationships. A total of 56 bands were produced of which 44 were polymorphic. Maximum number of bands (21) was produced by OPY20 while OPC04 produced minimum number of bands (14). The maximum and minimum percentage polymorphisms were 100% (OPC04) and 50% (OPA12), The dendrogram of genetic diversity had a genetic distance range of 0.57 to 1.00, 0.58 to 1.00 and 0.52 to 1.00 and clustered at 0.57, 0.58, 0.52 implying 57%, 58%, 52% similarity and 43%, 42% and 48% variability for L. aestuans, C. virginica and S. rhombifolia respectively. Results of phytochemical analysis show that S. rhombifolia is particularly high in steroids (I134.19±0.23), flavonoids (118.65±0.18), phenolics (125.25±1.43), alkaloids (63.56±0.11) and triterpenes (72.44±0.12) but low in saponins (23.29±0.05), glycosides (6.79±0.01) and tannins (7.10±0.02). [ABSTRACT FROM AUTHOR]

Hierarchical and k‐medoids clustering are deterministic clustering algorithms defined on pairwise distances. We use these same pairwise distances in a novel stochastic clustering procedure based on a probability distribution. We call our proposed method CaviarPD, a portmanteau from cluster analysis via random partition distributions. CaviarPD first samples clusterings from a distribution on partitions and then finds the best cluster estimate based on these samples using algorithms to minimize an expected loss. Using eight case studies, we show that our approach produces results as close to the truth as hierarchical and k‐medoids methods, and has the additional advantage of allowing for a probabilistic framework to assess clustering uncertainty. The method provides an intuitive graphical representation of clustering uncertainty through pairwise probabilities from partition samples. A software implementation of the method is available in the CaviarPD package for R. [ABSTRACT FROM AUTHOR]

The results of long-term geochemical studies of the content of metals: aluminum, mercury, chromium, manganese, iron, zinc, cobalt, nickel and vanadium are presented, as well as the total concentration of these metals and sulfur in oils from 36 deposits of the main oil and gas-bearing region of Ukraine - the Dnipro-Donetsk Basin. The purpose of the research was to develop a classification of oil deposits on the example of the Dnipro-Donetsk basin based on geochemical studies of metal content and their cluster analysis, which can be used as the strictest criterion for dividing them into two fundamentally different groups - deposits formed mainly by oils of biogenic origin and deposits that contain oil of essentially abiogenic generation. According to the results of the cluster analysis, natural classifications of these deposits were developed for the first time according to the listed indicators and the V/Ni ratio, which are presented in the work in the form of dendrograms. It is shown that according to the results of the cluster analysis, the sample mean values of the analyzed indicators, which differ significantly between individual deposits or groups of deposits in the established series, can be interpreted in the terminology of qualitative assessment as: abnormally low; low; below average; average; above average; high; abnormally high. The analysis of the research results and their interpretation in the genetic sense with comparison with three different geochemical criteria of the relationship of the origin of oil to abiogenic or biogenic sources of petrogenesis according to the existing ideas made it possible to establish, firstly, the deposits that, according to each of these ideas, belong to those formed mainly by abiogenic matter, second, to establish and analyze coincidences and differences in the list of these deposits. It is substantiated that the comparative analysis of the results of the clustering of the considered deposits by the content of such abiogenic elements as Al and Hg in the oils according to the results of their clustering by the concentrations of V, Cr and Co shows that the totality of the deposits belonging to the clusters with high and abnormally high content of V, Cr and Co differs from the list of deposits with high and abnormally high concentrations of Al and Hg only in the absence of the Yuryivskyi deposit, and they completely coincide with each other. Thus, high and abnormally high contents of V, Cr and Co in the oils of the studied fields, based on the logic of previous studies, can be used as a stricter criterion for dividing them into two fundamentally different groups - fields formed mainly by oils of biogenic origin and fields containing oil significantly abiogenic generation. In this regard, according to the previously established laws, it makes sense to consider as a criterion the selection of deposits with oil of essentially abiogenic origin besidesto the concentrations of V, Cr and Co, also ratios of Co/Ni and Cr/Ni. [ABSTRACT FROM AUTHOR]

Background: Fenugreek (Trigonella foenum-graecum L.) is an important seed spice crop widely grown all over the world. In India, the state of Rajasthan is known for fenugreek production and productivity in the world. A concerted assessment of genetic variability among the germplasm accession is essential for breeding new superior varieties. Molecular markers such as AFLP, RAPD, ISSR, SSR, SCAR, SCoT, SRAP have become for the characterization of the germplasm rapidly and accurately. The present study aimed to characterize 20 elite fenugreek genotypes using simple sequence repeat (SSR) markers to assess the existing genetic diversity of this medicinal crop. Methods: The present study was carried out at the Rajasthan College of Agriculture, Maharana Pratap University of Agriculture and Technology, Udaipur, Rajasthan, India. Total genomic DNA was isolated from old leaves using the CTAB method (Doyle and Doyle, 1990). Further, PCR based genetic diversity was analyzed with using 50 SSR primer pairs. Dendrogram was constructed using NTSYSpc version 2.2 and clustering of the genotypes was done. Result: Twenty genotypes of fenugreek were assessed for genetic diversity analysis using SSR markers. Out of 50 markers 43 primer pairs produced 130 alleles with an average of 84.60% polymorphism. Jaccard's similarity coefficient lied between and 0.39 to 0.82. Based on UPGMA clustering, a dendrogram consisting of five main clusters was generated with wide variability among the studied genotypes. These diverse genotypes so identified could be gainfully utilized in the fenugreek breeding programme. [ABSTRACT FROM AUTHOR]

Introduction: Russian olive (Senjed) is planted in a large area in Iran, and at the same time, there are limited natural habitats for its species. This elder tree can be found in different types of soils and moisture conditions, but preferably it grows better in flood plains and humid coastal areas. Russian olive has a special place as one of the important products of Kerman Province. The area under cultivation and the amount of its production in Kerman are 309 hectares and 1100 metric tons, respectively. In this province, native trees are mainly cultivated along streams and on the edge of fields due to the deliciousness of their fruits. In spite of the wide variety and potential of it, there is less information available on the number of species and the genetic diversity of local genotypes. This study, as a preliminary investigation, showed the existence of high morphological diversity in the native Russian olive genotypes of the province, which reveals the importance of using them in future multibreeding programs. Material and methods: In this research, six qualitative traits include fruit shape, fruit aroma and flavor, fruit skin color, fruit ripening date, flowering date, and leaf shape, and fourteen quantitative traits including panicle length, panicle width, petiole length, petiole width, thorn length, thorn width, fruit length, fruit width, seed length, seed width, fruit tail length, fruit tail width, fruit weight, and seed weight were studied between 22 Russian olive native genotypes from Sirjan, Bardsir and Kerman regions. Results and discussion: The results showed the existence of many traits among genotypes. The average fruit length was 1.87 cm, fruit diameter 1.12 cm, fruit weight 1.49 grams, seed weight 0.52 grams, leaf length 4.27 cm and leaf width 2.48 cm. The highest fruit weight and fruit quality and flavor were reported in genotype number (4) of Mahmoudabad, Sirjan. The highest positive correlation coefficient at the probable level (p<0.01) was observed in petiole length and spine length (r=0.669), petiole length and fruit tail length (r=0.601), and fruit length and fruit diameter (r=0.584). Analyzing into main components in qualitative traits showed that the first two components explained 62% of the total changes. In quantitative traits, the first five components included 74.77% of the total changes. Based on the dendrogram of the scatterplot of quantitative and qualitative traits, all genotypes were divided into three separate groups. In the present research, the classification of masses based on quantitative traits did not follow their geographical distribution. Conclusion: The highest fruit weight belonged to the genotype of Mahmoud Abad Sirjan, which is a tropical region of Sirjan, and it had a sweet taste and a good aroma. The highest correlation values of traits were observed in PC1 between the traits of flowering date, leaf shape, leaf, fruit and seed dimensions, as well as seed weight. The presence of superior leaf traits and the subsequent improvement programs on them can expand the scope of use of elderberry from the fruit-only state. Environmental conditions and being at different heights above sea level do not play a significant role in the classification of genotypes. [ABSTRACT FROM AUTHOR]

The purpose of this study was to see how interstocks affected the anatomy, physiology, and genetic characteristics of grafted 'Borneo Prima' (BP) trees. 'Tangelo' (C. reticulata x C. paradisi) (TGL), 'Waturejo' (C. sinensis L.) (SW-W), 'Cina Licin' (C. reticulata Blanco) (M-CL), and 'Konde Purworejo' (C. reticulata Blanco) (M-KP) with Japanese Citroen/JC (C. limonin Osbeck) as their rootstocks have been planted at Tlekung Experimental Garden, Batu, Indonesia (950 asl) since 2002. In 2007, the top grafting technique was used to replace these with 'BP' mandarin. BP/TGL/JC, BP/SW-W/JC, BP/M-CL/JC, and BP/M-KP/JC were the new tree combinations, plus control (BP/JC). The TGL, SW-W, M-CL, and M-KP served as interstocks. The observation variables were monitored from January 2021 to May 2022. Interstocks significantly influenced the thickness of leaf, and palisade; oil gland diameter; stomatal density; peel thickness, and titratable acidity (TA) of grafted BP. 'M-CL' as an interstock had a significant impact on several grafted BP variables. Based on DNA analysis using six ISSR markers, the plant was grouped in two main clusters on the 0.63 coefficient, i.e., control and interstock treatments, respectively. In the second one, it was divided into three subclusters i.e., tangelo, mandarin group, and sweet orange interstocks. The genetic alteration was shown between the control (BP/JC), and BP grafted onto interstocks (BP/interstocks). [ABSTRACT FROM AUTHOR]

Dendrogram (DE), heat map (HM) and principal component analysis (PCA) methods were used in order to identify possible emission sources of As, Cd, Co, Cr, Hg, Mn, Ni, Pb, Sb and Se in ambient PM10 collected in the surroundings of working power plants. Each statistical tool resulted in slightly different clusters. The best approximation of possible emission sources was received by the use of statistical analysis of trace-element concentrations combined with characterization of the sampling sites. In the study, PCA was indicated as the most useful statistical tool for source apportionment of trace elements in PM10. Major sources identified by PCA included: (1) coal combustion, (2) soil and road-dust resuspension, (3) the use of pesticides and (4) waste incineration. [ABSTRACT FROM AUTHOR]

Helicobacter pylori (H. pylori) is considered the most common bacterial pathogen colonizing stomach mucosa of almost half the world's population and is associated with various gastrointestinal diseases (from digestive problems and ulcers to gastric cancer). A lack of new drugs and a growing number of H. pylori antibiotic-resistant strains is a serious therapeutic problem.As a mixture of natural compounds, propolis has antimicrobial activity based on high concentrations of bioactive polyphenols (mainly flavonoids and phenolic acid derivates). The chemical composition of tested Georgian propolis is characterized by the presence of flavonoids aglycones, and phenolic acid monoesters, e.g., pinobanksin-5-methyl ether, pinobanksin, chrysin, pinocembrin, galangin, pinobanksin-3-O-acetate, pinostrobin and pinobanksin-3-O-butanoate, or isobutanoate and methoxycinnamic acid cinnamyl ester. The anti-H. pylori activity of 70% ethanol water extracts of 10 Georgian propolis samples was evaluated in vitro by MIC (minimal inhibitory concentration) against the reference strain (H. pylori ATCC 43504) and 10 clinical strains with different antibiotic-resistance patterns. The strongest anti-Helicobacter activity (MIC and MBC = 31.3 µg/mL) was observed for propolis from Orgora, Ota, and Vardzia and two from Khaheti. Lower levels of activity (MIC = 62.5 µg/mL) were found in propolis obtained from Qvakhreli and Pasanauri, while the lowest effect was observed for Norio and Mestia (MIC = 125.0 µg/mL). However, despite differences in MIC, all evaluated samples exhibited bactericidal activity. We selected the most active propolis samples for assessment of urease inhibition property. Enzyme activity was inhibited by propolis extracts, with IC50 ranging from 4.01 to 1484.8 µg/mL. Principal component analysis (PCA) and hierarchical fuzzy clustering (dendrograms) coupled with matrix correlation analysis exhibited that the strongest anti-Helicobacter activity was connected with black poplar origin and high flavonoid content of propolis. Samples with lower activity contained higher presence of aspen markers and/or dominance of non-flavonoid polyphenols over flavonoids. In summary, Georgian propolis can be regarded as a source bioactive compounds that can be used as adjuvant in therapy of H. pylori infection. [ABSTRACT FROM AUTHOR]

The present study was undertaken at ICAR-CTCRI, Sreekaryam to identify and group N and K efficient genotypes from a pool of released varieties, pre-breeding lines and elite landraces of cassava during 2021-2022. Thirty genotypes of cassava were evaluated for their diversity based on N and K efficiency along with some of its contributing plant characters using statistical tools like principal component analysis, and dendrogram clustering. The variation existing among the selected genotypes was observed through PCA, where the first six principal components accounted for nearly 81% of the total variability. Characters like tuber yield, plant height, stem girth, tuber length and tuber girth contributed to the greater variability among the genotypes. The dendrogram analysis classified the genotypes into six clusters based on the 18 parameters contributing to nutrient use efficiency. The proportion of the variance accounted by these clusters came up to the extent of 50% displaying the association of the genotypes with similar characters in these clusters. These analyses helped to realize the wide range of variability existing among the selected genotypes for the 18 characters studied. A simple correlation was also worked out between N and K use efficiency with root traits, which revealed that characters such as weight of storage roots, number of storage roots, and number of basal roots showed a positive correlation with both N and K use efficiency in cassava. [ABSTRACT FROM AUTHOR]

Pyrrosia belonging to Polypodiaceae, commonly known as felt ferns is characterized by its simple leaves and the presence of stellate hairs in the frond. Despite the great range of variability within the species, accessions of P. heterophylla (L.) Price from Kerala have not been extensively examined. The present study aims at the morpho-anatomical comparison of accessions. The samples were collected and variable characters such as habitats, shape, colour, thickness, width, length of sterile fronds, length, width and spore arrangement of fertile fronds, scales and the internal structure of the rhizome, stipe, and lamina of 20 accessions were examined and photographed using Carl Zeiss photomicroscope. Observations of the epidermis, including stomata and stellate hairs, were also made. Coded binary states of characters were used for developing a data matrix, which was further analysed. Cluster analysis using the UPGMA method were done from which a dendrogram was constructed which represents the taxonomic relationships among the species. In terms of the morphology and anatomy of the plant parts, three of the 20 accessions differed from P. heterophylla (L.) Price. [ABSTRACT FROM AUTHOR]