The Role of the Auxin Biosynthesis and Signaling in Soybean Root Nodule Development

Nitrogen(N) is one of the most important plant nutrients for plant growth and yield, however, its abundance in the soil is not sufficient for profitable crop production. The use of chemical fertilizers helps address soil N deficiency in agriculture. However, due to the environmental pollution resulting from excessive use of fertilizers, alternative forms of N for agriculture are a necessity. Leguminous plants such as soybean (Glycine max) form a symbiotic association with N-fixing rhizobia to meet their N demands. Legume-rhizobia symbiosis results in the formation of unique structures called nodules where rhizobia convert atmospheric nitrogen into plant usable forms, thus reducing the need for chemical fertilizer application. The plant hormone auxin plays a crucial role in determining the number of nodules and their rate of maturity in soybean. A better understanding of what roles auxin plays in regulating nodule number and nitrogen fixation would help devise strategies to enhance or optimize N supply from nodules of soybeans and other legumes. Indole-3-acetic acid (IAA) is the most abundant natural form of auxin produced by plants. The conversion of tryptophan to IAA through the two-step IPA pathway is the main source of auxin in Arabidopsis. Auxin action is mediated by a group of F-box proteins belonging to the TIR/AFB family that act as receptors. In this study, we evaluated the role of auxin biosynthesis and signaling in soybean root, nodule development, and nitrogen fixation using yucasin and PEO-IAA, chemicals that inhibit auxin biosynthesis and signaling respectively. The suppression of auxin biosynthesis with the use of yucasin in soybean roots led to a significant increase in root length and to a significant reduction in the expression of the IAA9, an auxin-responsive marker gene. Moreover, the suppression of auxin biosynthesis in soybean roots led to a significant increase in total nodule and mature nodule number at 21 days post rhizobia inoculation (dpi). The expression levels of FWL1, ENOD2, ENOD40, and NSP1 showed an increasing trend but the expression level of these markers was not significantly increased. The application of yucasin did not significantly affect nodule nitrogenase activity per plant and nodule. Pod number, seed number, seed weights, and seed protein concentration were used as a grain yield measurement in soybean and results showed that yucasin treatment did not affect grain yield. The suppression of auxin signaling with the use of PEO-IAA in soybean root led to increase in root length and a reduction in lateral root density. The expression level of auxinresponsive genes showed variable expression levels. Moreover, the application of PEOIAA in soybean root increased the total number of nodules and the mature number of nodules at 10 and 20 μM at 21 dpi. The expression of ENOD2, ENOD40, NIN, FWL1, and NSP1 had a consistent trend of increased marker gene expression at 10μM and 20μM PEOIAA. There was a significant increase in the expression of FWL1, ENOD2, and NIN at 10μM PEO-IAA treatment. Moreover, the application of PEO-IAA did not affect any of the grain yield-related traits evaluated. Overall, our results confirmed that auxin biosynthesis and signaling play an important role in soybean root and nodule development, and that manipulation of auxin biosynthesis and signaling could be used to optimize nodule numbers and potentially nitrogen fixation and grain yield

Exploring Quantitative Trait Loci Mapping for Bud Fruitfulness and Bud Break Traits in Grapevine F2 Population

Grapevine (Vitis vinifera L. subsp. vinifera) is one of the most important and valuable fruit crops around the world and grape industries in the USA have been growing increasingly regarding the demand for highly productive and quality grapes that can be grown in the cold region around the USA. The development of new cultivars with these features is performed through grape breeding with the help of quantitative trait loci (QTL) mapping, marker-assisted selection (MAS), and and other technologies. In this study, we evaluated grapevine bud fruitfulness by position and bud break in controlled conditions. These traits are multi-genetic and understanding the genetics mechanism behind the complex traits will help to discover the underlying genes. The objectives of this thesis were to identify phenotypic variation in these traits and reveal QTL. A subset of 179 genotypes from a F2 mapping population developed from the self of a single F1 (16_9_2) derived from a cross between V. riparia and ‘Seyval’ were used. The F2s were grown in the greenhouse for bud fruitfulness and bud break study. Bud fruitfulness was determined, and an integrated genotype by sequencing (GBS) and rhAmpSeq linkage map (2519 markers) and standard interval mapping (SIM) were used to identify QTL. Two main QTL related to bud fruitfulness were identified, explaining 25.5 % of phenotypic variation on chromosome 4 and 5. Bud break phenology was studied to identify the rate of bud break QTL in the F2 genotypes. Bud break occurs after the chilling requirement is fulfilled and optimal growth conditions promote bud break. Six one-node cuttings of each genotype were forced under greenhouse conditions for thirty days and the growth stage of cuttings measured based on Modified Eichhorn-Lorenz (Modified E-L) phenology scale was monitored daily. Data were processed using the area under the curve concept (area under bud break progression curve, AUBPC) to capture the rate of bud break values for each genotype. SIM was conducted with the average AUBPC, bud break score at the third week, and bud break rate using R/qtl, 1000 permutations and the integrated GBS and rhAmpSeq linkage map. A major QTL was identified on chromosome 10 and explained 11.04% of the genotypic variation. Bud break and bud fruitfulness studies identified several QTL and these QTL can provide candidate genes that may be used further to dissect the mechanisms underlying bud break and fruitfulness for sustainable production of grapevine

The Problems of School Administrators Scale

In the research conducted with the survey design, data were collected from 709 school administrators to develop the problems of school administrators scale. In this study, a theoretical framework was created according to the findings of the relevant studies and the scale of determining the problems of school administrators was developed. Exploratory and confirmatory factor analyses were done. According to the results, the problems of school administrators scale is a valid and reliable data collection tool that consists of 44 items and 8 dimensions. The scale can determine the problems of school administrators related to workload, personal rights, school administration, school climate, respect, education system, organizational commitment, and violence. With the Problems of School Administrators Scale, the level of problems can be determined and necessary measures can be taken. If the scale can be applied in different regions at the same time, comparisons between regions can be made and attempts can be made to ensure equal opportunity

DIGITAL DEVICES AND STUDENT ACHIEVEMENT: THE RELATIONSHIP IN PISA 2018 DATA

This research aims to find how the infrastructure of digital devices within the school and teachers’ capacity using digital devices affect student achievement defined as PISA 2018 reading, math, and science scores. The data were obtained from the school questionnaire administered to school principals who participated in PISA 2018. This research has shown that the infrastructure of digital devices within the school affects PISA 2018 reading, math and science scores more than teachers’ capacity using digital devices. This research has also shown that there is a strong interplay between the infrastructure of digital devices within the school and teachers’ capacity using digital devices. Research has shown that developing the infrastructure of digital technologies can have practical benefits for students

IMPACT OF L-ARGININE TRANSPORTATION ON MYELOID-DERIVED SUPPRESSOR CELL FUNCTION

Inflammatory chronic prostatitis/chronic pelvic pain syndrome has been linked to autoimmune inflammation. Likewise, prostatitis has been linked to prostate cancer development and progression. A better understanding of the mechanisms by which inflammation is regulated may provide the foundation for novel approaches to controlling inflammation. Myeloid-derived suppressor cells (MDSC) are a heterogeneous population of immature cells that expand during benign and cancer-associated inflammation. MDSC are characterized by their ability to potently inhibit T cell responses. Therefore, by dampening inflammation, MDSC benefit autoimmune diseases. Instead, they aggravate cancer by blocking antitumor immune responses. Identification of mechanisms underlying MDSC activities can enable the development of strategies to modify MDSC function in disease. Thus, in this study we investigated the mechanisms that regulate MDSC functions. Using murine models of prostatitis and cancer, we identified two novel pathways, p38 and p53 signaling, that are involved in MDSC functional activity and differentiation capacity, respectively. We showed that p38-MAPK pathway is involved in the regulation of MDSC-mediated immunoregulatory processes such that inhibition of p38 diminished MDSC expansion at the inflamed prostate, leading to greater numbers of T cells. Furthermore, inhibition of p38 reduced Nos2 expression and abolished MDSC suppressor activity. Our studies also demonstrated that the in vitro differentiation capacity of MDSC is restricted to cells at the peripheral sites. Tumor site monocytic-MDSC lacked the ability to differentiate into other cells types such as osteoclasts and granulocytic-MDSC, whereas the bone marrow and spleen counterparts could form both cell types. Notably, we identified p53 as a critical regulator of MDSC differentiation. Induction of p53 signaling elevated the differentiation of the bone marrow MDSC into granulocytic cell types. A well-established mechanism for MDSC suppressive activity is the metabolism of L-Arginine (L-Arg) by Arginase 1 (ARG1) and nitric oxide synthase 2 (NOS2). Therefore, we hypothesized that restricting MDSC uptake of L-Arg is a critical control point to modulate their suppressor activity. To this end, we have identified the mechanisms by which extracellular L-Arg is transported into MDSC. We have shown that cationic amino acid transporter 2 (Cat2) expression is induced in MDSC at the inflammatory sites in parallel to Arg1 and Nos2 expression. CAT2 acts as an important regulator of MDSC suppressive function. MDSC that lack CAT2 have reduced capacity to suppress T cell responses both ex vivo and in vivo, as evidenced by increased T cell expansion in prostatitis and decreased tumor growth in cancer models. The abrogation of suppressive function is due to low intracellular L-Arginine levels, which leads to the impaired ability of NOS2 to catalyze L-Arginine metabolic processes. In summary, here we identify 3 components that regulate MDSC: L-Arg transportation through CAT2, p38-MAPK signaling and p53 signaling. CAT2 and p38 are critical regulators of MDSC suppressive function and p53 acts as an inducer of MDSC differentiation. Targeting of these molecules can be utilized as a strategy to modulate MDSC function in disease

Accelerating the HyperLogLog Cardinality Estimation Algorithm

[Abstract] In recent years, vast amounts of data of different kinds, from pictures and videos from our cameras to software logs from sensor networks and Internet routers operating day and night, are being generated. This has led to new big data problems, which require new algorithms to handle these large volumes of data and as a result are very computationally demanding because of the volumes to process. In this paper, we parallelize one of these new algorithms, namely, the HyperLogLog algorithm, which estimates the number of different items in a large data set with minimal memory usage, as it lowers the typical memory usage of this type of calculation from () to (1). We have implemented parallelizations based on OpenMP and OpenCL and evaluated them in a standard multicore system, an Intel Xeon Phi, and two GPUs from different vendors. The results obtained in our experiments, in which we reach a speedup of 88.6 with respect to an optimized sequential implementation, are very positive, particularly taking into account the need to run this kind of algorithm on large amounts of data.This research was supported by the Ministry of Economy and Competitiveness of Spain and FEDER funds (80%) of the EU (Projects TIN2013-42148-P and TIN2016-75845-P) as well as by the Xunta de Galicia (Centro Singular de Investigación de Galicia accreditation 2016–2019) and the European Union (European Regional Development Fund, ERDF) under Grant Ref. ED431G/01Xunta de Galicia; ED431G/0

The effect of psychological factors on Syrian refugees’ participation in lifelong education

The purpose of this research was to determine the effect of psychological factors on Syrian refugees’ participation in lifelong education. The ex post facto co-relational causal design was employed in this research. A questionnaire form consisted of four scales was used to collect data from 297 refugees participated in lifelong education. The structural equation modeling analysis revealed that psychological factors affect participation in lifelong education and learning approaches played the biggest role in this effect. It was claimed that learning approach is a strong predictor of participation in lifelong education. The effect of locus of control on participation in lifelong education was medium while the effects of self-efficacy and self-worth were weak. Recommendations to education providers, decision-makers and researchers to align both formal and lifelong education curricula with the results were given

Cluster Detection by Lifting with Application to Phylogenetics

In this thesis, we propose a new algorithm which automatically detects the number of clusters in a tree structure data set by denoising some generalized node values in the tree using lifting “one coefficient at a time” (LOCAAT) algorithm introduced by Jansen et al. (2001). Our algorithm can be applied to any multidimensional data set using compactness value as a node value or to phylogenetic data sets, DNA sequences, using either compactness value or dissimilarity score as a node value. Compactness value is defined as the average distance from the centroid of each possible cluster in the tree, and the dissimilarity score is the average number of loci, where at least one of them does not share the same nucleotide between sequences under the node of interest. For multidimensional data sets, we consider each node in the tree as a possible location of a cluster after denoising the tree by LOCAAT. Thus, for each possible cluster, we check how much departure we can allow from the centroid of the cluster to assign the objects under the node of interest as a cluster. Then if a node and all its child nodes are denoised less than or equal to the allowed amount of departure from the centroid of their clusters, a cluster is located at this node. We also propose another version of our algorithm based on non-decimated lifting (Knight & Nason, 2009) in which we generate a probability of being clustered for each node. If a node and all its child nodes have a probability of being clustered less than or equal to the probability of acceptance, θ∈[0; 1], a cluster is located at this node. We provide a comparison study between our algorithms and some available internal cluster validity indices (CVIs) in the literature using some artificial data sets and a real data set. In addition, we compare the performance of each method using some available external cluster validity scores. For phylogenetic data sets, we check the performance of our algorithms and other CVIs using both compactness value and dissimilarity score as a node value. To be able to compute compactness value for a phylogenetic tree, we need to find the position of each specie in Rp using multidimensional scaling (MDS), and then we can find which species share the similar features using our algorithm. If we use the dissimilarity score as a node value, we will cluster similar species together by finding how much difference we can allow between species. We check the performance of our algorithms using some artificial and a real data sets. In the final part of our thesis, we propose a visualization tool for cophylogenetic data sets. We only consider the associated two phylogenetic trees case, and we apply our algorithm to both host and parasite trees separately to provide a summary of these data sets. We check the performance of our algorithm using two well-known cophylogenetic data sets

Organizational Culture Change and Technology: Navigating the Digital Transformation

The chapter investigates the critical relationship between technology and organizational culture change. It presents a framework that elucidates the interplay between technological adoption and the ensuing cultural shifts within organizations. The author delves into the various stages of the digital transformation process, examining the challenges and opportunities that organizations encounter as they integrate new technologies. By drawing on real-world examples and case studies, the chapter underscores the pivotal role that organizational leaders play in guiding their teams through these transitions, fostering a culture of adaptability, and promoting a growth mindset. The chapter also explores the importance of addressing the human element in digital transformation efforts, emphasizing the need to effectively manage change, overcome resistance, and bridge skill gaps to ensure a successful transition. Furthermore, the author discusses the ethical implications of adopting new technologies, advocating for a responsible and people-centric approach to innovation. In conclusion, the chapter offers a forward-looking perspective on the future of organizational culture in the digital era, anticipating emerging trends and novel technologies that will continue to shape the way organizations function. This informative chapter provides a valuable resource for understanding and navigating the complex interplay between organizational culture change and technology

Exploiting Heterogeneous Parallelism With the Heterogeneous Programming Library

[Abstract] While recognition of the advantages of heterogeneous computing is steadily growing, the issues of programmability and portability hinder its exploitation. The introduction of the OpenCL standard was a major step forward in that it provides code portability, but its interface is even more complex than that of other approaches. In this paper, we present the Heterogeneous Programming Library (HPL), which permits the development of heterogeneous applications addressing both portability and programmability while not sacrificing high performance. This is achieved by means of an embedded language and data types provided by the library with which generic computations to be run in heterogeneous devices can be expressed. A comparison in terms of programmability and performance with OpenCL shows that both approaches offer very similar performance, while outlining the programmability advantages of HPL.This work was funded by the Xunta de Galicia under the project “Consolidación e Estructuración de Unidades de Investigación Competitivas” 2010/06 and the MICINN, cofunded by FEDER funds, under grant TIN2010-16735. Zeki Bozkus is funded by the Scientific and Technological Research Council of Turkey (TUBITAK; 112E191)Scientific and Technological Research Council of Turkey (TUBITAK); 112E19