WAV E3 ubiquitin ligases mediate degradation of IAA32/34 in the TMK1-mediated auxin signaling pathway during apical hook development.

Auxin regulates plant growth and development through downstream signaling pathways, including the best-known SCFTIR1/AFB-Aux/IAA-ARF pathway and several other less characterized "noncanonical" pathways. Recently, one SCFTIR1/AFB-independent noncanonical pathway, mediated by Transmembrane Kinase 1 (TMK1), was discovered through the analyses of its functions in Arabidopsis apical hook development. Asymmetric accumulation of auxin on the concave side of the apical hook triggers DAR1-catalyzed release of the C-terminal of TMK1, which migrates into the nucleus, where it phosphorylates and stabilizes IAA32/34 to inhibit cell elongation, which is essential for full apical hook formation. However, the molecular factors mediating IAA32/34 degradation have not been identified. Here, we show that proteins in the CYTOKININ INDUCED ROOT WAVING 1 (CKRW1)/WAVY GROWTH 3 (WAV3) subfamily act as E3 ubiquitin ligases to target IAA32/34 for ubiquitination and degradation, which is inhibited by TMK1c-mediated phosphorylation. This antagonistic interaction between TMK1c and CKRW1/WAV3 subfamily E3 ubiquitin ligases regulates IAA32/34 levels to control differential cell elongation along opposite sides of the apical hook.

Exploring second language students' language assessment literacy: impact on test anxiety and motivation.

Introduction: This research aims to investigate the impact of students' language assessment literacy (LAL) on their cognition. The study specifically examines how different levels of LAL influence two critical factors: test anxiety and motivation to learn a second language. Methods: To achieve the research objectives, a questionnaire was administered to a sample of 415 university students in China. The questionnaire utilized a five-point Likert scale to assess students' levels of LAL, test anxiety, and motivation to learn a second language. Descriptive data were examined to reveal students' proficiency in LAL, along with their levels of test anxiety and motivation. Multilevel regression analyses were performed using Mplus to investigate whether students' LAL proficiency can predict their levels of test anxiety and motivation. Results: The findings indicated that the participating students had a proficiency level of approximately 60% in the content of the LAL questionnaire. The analysis further revealed the relationships between specific dimensions of LAL and both test anxiety and second language motivation. The multilevel regression analysis suggested that theoretical knowledge about language and language learning, the understanding of the impact and social value of language assessments, and the uses of assessments to enhance learning, positively predicted students' extrinsic motivation. Furthermore, students' understanding of the uses of assessments to learn and their theoretical knowledge about language learning were identified as positive predictors of intrinsic motivation. Additionally, it was observed that students' LAL did not significantly predict test anxiety. Discussion: These findings emphasize the significance of enhancing students' LAL due to the identified relationships between LAL dimensions and motivation to learn a second language. The study suggests pedagogical implications for improving LAL, with a focus on specific dimensions that positively impact students' motivation. The absence of a significant relationship between LAL dimensions and test anxiety prompts further exploration and consideration of additional factors influencing students' anxiety in language assessments.

Dynamic Changes of Net Primary Productivity and Associated Urban Growth Driving Forces in Guangzhou City, China.

Urban growth has caused environmental problems around the world and profoundly altered the terrestrial carbon cycle, especially net primary productivity (NPP). Sustainable urban development requires a better understanding of the impacts of urban growth on ecosystems. We selected Guangzhou City to analyze the impacts of urban development processes and urban geographic changes on NPP, as well as the correlation between urbanization intensity and NPP, using a deep-learning urbanization characteristic index (UCI). The results showed that the NPP in the study area had clear spatial heterogeneity and declined overall from 2001 to 2013. Guangzhou's urbanization became more and more intense, the mean UCI increased significantly from 0.1293 in 2001 to 0.2879 in 2013, and urban geographic type was dominated by urban exurbs in 2001 and 2013 while urban fringe areas increased most significantly and about 2,320.24 km2 of urban exurbs were converted to urban fringes. There was a significant negative correlation between UCI and NPP in 2001 and 2013, implying that NPP had been negatively influenced by the increasing urban development intensity. The transition of urban exurbs to urban fringes was associated with the highest NPP losses, which was caused by cropland loss and built-up land expansion.

An examination of the OMIM database for associating mutation to a consensus reference sequence.

Gene mutation (e.g. substitution, insertion and deletion) and related phenotype information are important biomedical knowledge. Many biomedical databases (e.g. OMIM) incorporate such data. However, few studies have examined the quality of this data. In the current study, we examined the quality of protein single-point mutations in the OMIM and identified whether the corresponding reference sequences align with the mutation positions. Our results show that close to 20% of mutation data cannot be mapped to a single reference sequence. The failed mappings are caused by position conflict, site shifting (peptide, N-terminal methionine) and other types of data error. We propose a preliminary model to resolve such inconsistency in the OMIM database.

DRUMS: a human disease related unique gene mutation search engine.

With the completion of the human genome project and the development of new methods for gene variant detection, the integration of mutation data and its phenotypic consequences has become more important than ever. Among all available resources, locus-specific databases (LSDBs) curate one or more specific genes' mutation data along with high-quality phenotypes. Although some genotype-phenotype data from LSDB have been integrated into central databases little effort has been made to integrate all these data by a search engine approach. In this work, we have developed disease related unique gene mutation search engine (DRUMS), a search engine for human disease related unique gene mutation as a convenient tool for biologists or physicians to retrieve gene variant and related phenotype information. Gene variant and phenotype information were stored in a gene-centred relational database. Moreover, the relationships between mutations and diseases were indexed by the uniform resource identifier from LSDB, or another central database. By querying DRUMS, users can access the most popular mutation databases under one interface. DRUMS could be treated as a domain specific search engine. By using web crawling, indexing, and searching technologies, it provides a competitively efficient interface for searching and retrieving mutation data and their relationships to diseases. The present system is freely accessible at http://www.scbit.org/glif/new/drums/index.html.