PIF4–Mediated Activation of YUCCA8 Expression Integrates Temperature into the Auxin Pathway in Regulating Arabidopsis Hypocotyl Growth

Higher plants adapt their growth to high temperature by a dramatic change in plant architecture. It has been shown that the transcriptional regulator phytochrome-interacting factor 4 (PIF4) and the phytohormone auxin are involved in the regulation of high temperature–induced hypocotyl elongation in Arabidopsis. Here we report that PIF4 regulates high temperature–induced hypocotyl elongation through direct activation of the auxin biosynthetic gene YUCCA8 (YUC8). We show that high temperature co-upregulates the transcript abundance of PIF4 and YUC8. PIF4–dependency of high temperature–mediated induction of YUC8 expression as well as auxin biosynthesis, together with the finding that overexpression of PIF4 leads to increased expression of YUC8 and elevated free IAA levels in planta, suggests a possibility that PIF4 directly activates YUC8 expression. Indeed, gel shift and chromatin immunoprecipitation experiments demonstrate that PIF4 associates with the G-box–containing promoter region of YUC8. Transient expression assay in Nicotiana benthamiana leaves support that PIF4 directly activates YUC8 expression in vivo. Significantly, we show that the yuc8 mutation can largely suppress the long-hypocotyl phenotype of PIF4–overexpression plants and also can reduce high temperature–induced hypocotyl elongation. Genetic analyses reveal that the shy2-2 mutation, which harbors a stabilized mutant form of the IAA3 protein and therefore is defective in high temperature–induced hypocotyl elongation, largely suppresses the long-hypocotyl phenotype of PIF4–overexpression plants. Taken together, our results illuminate a molecular framework by which the PIF4 transcriptional regulator integrates its action into the auxin pathway through activating the expression of specific auxin biosynthetic gene. These studies advance our understanding on the molecular mechanism underlying high temperature–induced adaptation in plant architecture

Auxin Response Factor2 (ARF2) and Its Regulated Homeodomain Gene HB33 Mediate Abscisic Acid Response in Arabidopsis

The phytohormone abscisic acid (ABA) is an important regulator of plant development and response to environmental stresses. In this study, we identified two ABA overly sensitive mutant alleles in a gene encoding Auxin Response Factor2 (ARF2). The expression of ARF2 was induced by ABA treatment. The arf2 mutants showed enhanced ABA sensitivity in seed germination and primary root growth. In contrast, the primary root growth and seed germination of transgenic plants over-expressing ARF2 are less inhibited by ABA than that of the wild type. ARF2 negatively regulates the expression of a homeodomain gene HB33, the expression of which is reduced by ABA. Transgenic plants over-expressing HB33 are more sensitive, while transgenic plants reducing HB33 by RNAi are more resistant to ABA in the seed germination and primary root growth than the wild type. ABA treatment altered auxin distribution in the primary root tips and made the relative, but not absolute, auxin accumulation or auxin signal around quiescent centre cells and their surrounding columella stem cells to other cells stronger in arf2-101 than in the wild type. These results indicate that ARF2 and HB33 are novel regulators in the ABA signal pathway, which has crosstalk with auxin signal pathway in regulating plant growth

Why organizational and community diversity matter:Representativeness and the Emergence of Incivility and Organizational Performance

Integrating sociological and psychological perspectives, this research considers the value of organizational ethnic diversity as a function of community diversity. Employee and patient surveys, census data, and performance indexes relevant to 142 hospitals in the United Kingdom suggest that intraorganizational ethnic diversity is associated with reduced civility toward patients. However, the degree to which organizational demography was representative of community demography was positively related to civility experienced by patients and ultimately enhanced organizational performance. These findings underscore the understudied effects of community context and imply that intergroup biases manifested in incivility toward out-group members hinder organizational performance

Follow my friends this Friday! An analysis of human-generated friendship recommendations

Online social networks support users in a wide range of activities, such as sharing information and making recommendations. In Twitter, the hashtag #ff, or #followfriday, arose as a popular convention for users to create contact recommendations for others. Hitherto, there has not been any quantitative study of the effect of such human-generated recommendations. This paper is the first study of a large-scale corpus of human friendship recommendations based on such hashtags, using a large corpus of recommendations gathered over a 24 week period and involving a set of nearly 6 million users. We show that these explicit recommendations have a measurable effect on the process of link creation, increasing the chance of link creation between two and three times on average, compared with a recommendation-free scenario. Also, ties created after such recommendations have up to 6% more longevity than other Twitter ties. Finally, we build a supervised system to rank user-generated recommendations, surfacing the most valuable ones with high precision (0.52 MAP), and we find that features describing users and the relationships between them, are discriminative for this task

Follow my friends this Friday! An analysis of human-generated friendship recommendations

Online social networks support users in a wide range of activities, such as sharing information and making recommendations. In Twitter, the hashtag #ff, or #followfriday, arose as a popular convention for users to create contact recommendations for others. Hitherto, there has not been any quantitative study of the effect of such human-generated recommendations. This paper is the first study of a large-scale corpus of human friendship recommendations based on such hashtags, using a large corpus of recommendations gathered over a 24 week period and involving a set of nearly 6 million users. We show that these explicit recommendations have a measurable effect on the process of link creation, increasing the chance of link creation between two and three times on average, compared with a recommendation-free scenario. Also, ties created after such recommendations have up to 6% more longevity than other Twitter ties. Finally, we build a supervised system to rank user-generated recommendations, surfacing the most valuable ones with high precision (0.52 MAP), and we find that features describing users and the relationships between them, are discriminative for this task

The asymptotic structure of weakly strained stoichiometric methane-air flames

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