Arabidopsis CULLIN3 Genes Regulate Primary Root Growth and Patterning by Ethylene-Dependent and -Independent Mechanisms

CULLIN3 (CUL3) together with BTB-domain proteins form a class of Cullin-RING ubiquitin ligases (called CRL3s) that control the rapid and selective degradation of important regulatory proteins in all eukaryotes. Here, we report that in the model plant Arabidopsis thaliana, CUL3 regulates plant growth and development, not only during embryogenesis but also at post-embryonic stages. First, we show that CUL3 modulates the emission of ethylene, a gaseous plant hormone that is an important growth regulator. A CUL3 hypomorphic mutant accumulates ACS5, the rate-limiting enzyme in ethylene biosynthesis and as a consequence exhibits a constitutive ethylene response. Second, we provide evidence that CUL3 regulates primary root growth by a novel ethylene-dependant pathway. In particular, we show that CUL3 knockdown inhibits primary root growth by reducing root meristem size and cell number. This phenotype is suppressed by ethylene-insensitive or resistant mutations. Finally, we identify a function of CUL3 in distal root patterning, by a mechanism that is independent of ethylene. Thus, our work highlights that CUL3 is essential for the normal division and organisation of the root stem cell niche and columella root cap cells

Effects of long-term continuous positive airway pressure on body composition and IGF1

OBJECTIVE: To investigate the long-term effects of nasal continuous positive airway pressure (CPAP) ventilation in patients with obstructive sleep apnea syndrome (OSAS) on body composition (BC) and IGF1. DESIGN: Observational study. SUBJECTS: Seventy-eight (11 females and 67 males) OSAS patients who were compliant with CPAP (age 51+/-1.1 years) participated in the study. We assessed body mass index (BMI), total body mass (TBM), total body fat (TBF; kg) and lean body mass (LBM; kg), abdominal subcutaneous (SC) and visceral (V) fat (cm(2)), and waist circumference (WC; cm) by magnetic resonance imaging, and IGF1 (ng/ml) before and after 7.8+/-1.3 months of CPAP use of an average of 5.9+/-1.2 h. RESULTS: Women had a higher BMI, WC; TBM, TBF, and more SC fat. Men had a higher LBM and more V fat. CPAP increased WC (+2.8+/-9.6 cm, P=0.02) and LBM (2.2+/-0.5 kg, P=0.006), but not IGF1. In men, CPAP increased BMI (0.5+/-0.2 kg/m(2), P=0.02), WC (1.7+/-6.9 cm, P=0.002), TBM (1.7+/-0.4 kg, P=0.0001), LBM (1.5+/-0.4 kg, P=0.0003), SC fat (12.9+/-5.1 cm(2), P=0.02), and IGF1 (13.6+/-4.2 ng/ml, P=0.002). Compliance with CPAP increased LBM in men aged 60 years, and IGF1 increased in men aged 40-60 years only. CONCLUSIONS: Long-term CPAP increased LBM in both sexes and IGF1 in men, while fat mass remained unchanged, suggesting a sexually dimorphic response of IGF1 to CPAP. The role of the GH axis activity and age to this response is unclear. The metabolic consequences of changes in LBM are still to be determined. Future studies on the effects of CPAP on BC should include LBM as an outcome

Modelling the population distribution in multi-objective optimization by generative topographic mapping

Abstract. Under mild conditions, the Pareto set of a continuous multi-objective optimization problem exhibits certain regularity. We have recently advocated taking into consideration such regularity in designing multi-objective evolutionary algorithms. Following our previous work on using Local Principal Component Analysis for capturing the regularity, this paper presents a new approach for acquiring and using the regularity of the Pareto set in evolutionary algorithms. The approach is based on the Generative Topographic Mapping and can be regarded as an Estimation of Distribution Algorithm. It builds models of the distribution of promising solutions based on regularity patterns extracted from the previous search, and samples new solutions from the models thus built. The proposed algorithm has been compared with two other state-of-the-art algorithms, NSGA-II and SPEA2 on a set of test problems.

Energy efficient design for portable storages on battery powered computers

Abstract. In engineering and other ‘real-world ’ applications, multiobjective optimization problems must frequently be tackled on a tight evaluation budget — tens or hundreds of function evaluations, rather than thousands. In this paper, we investigate two algorithms that use advanced initialization and search strategies to operate better under these conditions. The first algorithm, Bin MSOPS, uses a binary search tree to divide up the decision space, and tries to sample from the largest empty regions near ‘fit ’ solutions. The second algorithm, ParEGO, begins with solutions in a latin hypercube and updates a Gaussian processes surrogate model of the search landscape after every function evaluation, which it uses to estimate the solution of largest expected improvement. The two algorithms are tested using a benchmark suite of nine functions of two and three objectives — on a budget of only 250 function evaluations each, in total. Results indicate that the two algorithms search the space in very different ways and this can be used to understand performance differences. Both algorithms perform well but ParEGO comes out on top in seven of the nine test cases after 100 function evaluations, and on six after the first 250 evaluations. Keywords: multiobjective optimization, expensive black-box functions, ParEGO, DACE, Bin MSOPS, landscape approximation, response surfaces, test suites