The 9-cis-epoxycarotenoid cleavage reaction is the key regulatory step of abscisic acid biosynthesis in water-stressed bean

Abscisic acid (ABA), a cleavage product of carotenoids, is involved in stress responses in plants. A well known response of plants to water stress is accumulation of ABA, which is caused by de novo synthesis. The limiting step of ABA biosynthesis in plants is presumably the cleavage of 9-cis-epoxycarotenoids, the first committed step of ABA biosynthesis. This step generates the C15 intermediate xanthoxin and C25-apocarotenoids. A cDNA, PvNCED1, was cloned from wilted bean (Phaseolus vulgaris L.) leaves. The 2,398-bp full-length PvNCED1 has an ORF of 615 aa and encodes a 68-kDa protein. The PvNCED1 protein is imported into chloroplasts, where it is associated with the thylakoids. The recombinant protein PvNCED1 catalyzes the cleavage of 9-cis-violaxanthin and 9′-cis-neoxanthin, so that the enzyme is referred to as 9-cis-epoxycarotenoid dioxygenase. When detached bean leaves were water stressed, ABA accumulation was preceded by large increases in PvNCED1 mRNA and protein levels. Conversely, rehydration of stressed leaves caused a rapid decrease in PvNCED1 mRNA, protein, and ABA levels. In bean roots, a similar correlation among PvNCED1 mRNA, protein, and ABA levels was observed. However, the ABA content was much less than in leaves, presumably because of the much smaller carotenoid precursor pool in roots than in leaves. At 7°C, PvNCED1 mRNA and ABA were slowly induced by water stress, but, at 2°C, neither accumulated. The results provide evidence that drought-induced ABA biosynthesis is regulated by the 9-cis-epoxycarotenoid cleavage reaction and that this reaction takes place in the thylakoids, where the carotenoid substrate is located.

Coordinate Regulation of G- and C Strand Length during New Telomere Synthesis

We have used the ciliate Euplotes to study the role of DNA polymerase in telomeric C strand synthesis. Euplotes provides a unique opportunity to study C strand synthesis without the complication of simultaneous DNA replication because millions of new telomeres are made at a stage in the life cycle when no general DNA replication takes place. Previously we showed that the C-strands of newly synthesized telomeres have a precisely controlled length while the G-strands are more heterogeneous. This finding suggested that, although synthesis of the G-strand (by telomerase) is the first step in telomere addition, a major regulatory step occurs during subsequent C strand synthesis. We have now examined whether G- and C strand synthesis might be regulated coordinately rather than by two independent mechanisms. We accomplished this by determining what happens to G- and C strand length if C strand synthesis is partially inhibited by aphidicolin. Aphidicolin treatment caused a general lengthening of the G-strands and a large increase in C strand heterogeneity. This concomitant change in both the G- and C strand length indicates that synthesis of the two strands is coordinated. Since aphidicolin is a very specific inhibitor of DNA polα and polδ, our results suggest that this coordinate length regulation is mediated by DNA polymerase.

The estimation of statistical parameters for local alignment score distributions

The distribution of optimal local alignment scores of random sequences plays a vital role in evaluating the statistical significance of sequence alignments. These scores can be well described by an extreme-value distribution. The distribution’s parameters depend upon the scoring system employed and the random letter frequencies; in general they cannot be derived analytically, but must be estimated by curve fitting. For obtaining accurate parameter estimates, a form of the recently described ‘island’ method has several advantages. We describe this method in detail, and use it to investigate the functional dependence of these parameters on finite-length edge effects.

Estimation of divergence times from multiprotein sequences for a few mammalian species and several distantly related organisms

When many protein sequences are available for estimating the time of divergence between two species, it is customary to estimate the time for each protein separately and then use the average for all proteins as the final estimate. However, it can be shown that this estimate generally has an upward bias, and that an unbiased estimate is obtained by using distances based on concatenated sequences. We have shown that two concatenation-based distances, i.e., average gamma distance weighted with sequence length (d2) and multiprotein gamma distance (d3), generally give more satisfactory results than other concatenation-based distances. Using these two distance measures for 104 protein sequences, we estimated the time of divergence between mice and rats to be approximately 33 million years ago. Similarly, the time of divergence between humans and rodents was estimated to be approximately 96 million years ago. We also investigated the dependency of time estimates on statistical methods and various assumptions made by using sequence data from eubacteria, protists, plants, fungi, and animals. Our best estimates of the times of divergence between eubacteria and eukaryotes, between protists and other eukaryotes, and between plants, fungi, and animals were 3, 1.7, and 1.3 billion years ago, respectively. However, estimates of ancient divergence times are subject to a substantial amount of error caused by uncertainty of the molecular clock, horizontal gene transfer, errors in sequence alignments, etc.

A robust and fast method for 6DoF motion estimation from generalized 3D data

Nowadays, there is an increasing number of robotic applications that need to act in real three-dimensional (3D) scenarios. In this paper we present a new mobile robotics orientated 3D registration method that improves previous Iterative Closest Points based solutions both in speed and accuracy. As an initial step, we perform a low cost computational method to obtain descriptions for 3D scenes planar surfaces. Then, from these descriptions we apply a force system in order to compute accurately and efficiently a six degrees of freedom egomotion. We describe the basis of our approach and demonstrate its validity with several experiments using different kinds of 3D sensors and different 3D real environments.

Choroidal Thickness And Volume In Healthy Young Whites And Their Relationship With Axial Length, Ammetropy And Sex

Purpose: To evaluate choroidal thickness in young subjects using Enhanced Depth Imaging Spectral Domain Optical Coherence Tomography (EDI SD-OCT) describing volume differences between all the defined areas of the Early Treatment Diabetic Retinopathy Study (ETDRS). Design: Prospective, clinical study. Methods: Seventy-nine eyes of 95 healthy, young (23.8±3.2years), adult volunteers were prospectively enrolled. Manual choroidal segmentation on a 25-raster horizontal scan protocol was performed. The measurements of the nine subfields defined by the ETDRS were evaluated. Results: Mean subfoveal choroidal thickness was 345.67±81.80μm and mean total choroidal volume was 8.99±1.88mm3. Choroidal thickness and volume were higher at the superior and temporal areas compared to inferior and nasal sectors of the same diameter respectively. Strong correlations between subfoveal choroidal thickness and axial length (AL) and myopic refractive error were obtained, r = -0.649, p<0.001 and r = 0.473, p<0.001 respectively. Emmetropic eyes tended to have thicker subfoveal choroidal thickness (381.94±79.88μm versus 307.04±64.91μm) and higher total choroidal volume than myopic eyes (9.80± 1.87mm3 versus 8.14±1.48mm3). The estimation of the variation of the subfoveal choroidal thickness with the AL was-43.84μm/mm. In the myopic group, the variation of the subfoveal choroidal thickness with the myopic refractive error was -10.45μm/D. Conclusions: This study establishes for the first time a normal database for choroidal thickness and volume in young adults. Axial length, and myopic ammetropy are highly associated with choroidal parameters in healthy subjects. EDI SD-OCT exhibited a high degree of intraobserver and interobserver repeatability.

Error induced by the estimation of the corneal power and the effective lens position with a rotationally asymmetric refractive multifocal intraocular lens

AIM: To evaluate the prediction error in intraocular lens (IOL) power calculation for a rotationally asymmetric refractive multifocal IOL and the impact on this error of the optimization of the keratometric estimation of the corneal power and the prediction of the effective lens position (ELP). METHODS: Retrospective study including a total of 25 eyes of 13 patients (age, 50 to 83y) with previous cataract surgery with implantation of the Lentis Mplus LS-312 IOL (Oculentis GmbH, Germany). In all cases, an adjusted IOL power (PIOLadj) was calculated based on Gaussian optics using a variable keratometric index value (nkadj) for the estimation of the corneal power (Pkadj) and on a new value for ELP (ELPadj) obtained by multiple regression analysis. This PIOLadj was compared with the IOL power implanted (PIOLReal) and the value proposed by three conventional formulas (Haigis, Hoffer Q and Holladay). RESULTS: PIOLReal was not significantly different than PIOLadj and Holladay IOL power (P>0.05). In the Bland and Altman analysis, PIOLadj showed lower mean difference (-0.07 D) and limits of agreement (of 1.47 and -1.61 D) when compared to PIOLReal than the IOL power value obtained with the Holladay formula. Furthermore, ELPadj was significantly lower than ELP calculated with other conventional formulas (P<0.01) and was found to be dependent on axial length, anterior chamber depth and Pkadj. CONCLUSION: Refractive outcomes after cataract surgery with implantation of the multifocal IOL Lentis Mplus LS-312 can be optimized by minimizing the keratometric error and by estimating ELP using a mathematical expression dependent on anatomical factors.

Three-dimensional planar model estimation using multi-constraint knowledge based on k-means and RANSAC

Plane model extraction from three-dimensional point clouds is a necessary step in many different applications such as planar object reconstruction, indoor mapping and indoor localization. Different RANdom SAmple Consensus (RANSAC)-based methods have been proposed for this purpose in recent years. In this study, we propose a novel method-based on RANSAC called Multiplane Model Estimation, which can estimate multiple plane models simultaneously from a noisy point cloud using the knowledge extracted from a scene (or an object) in order to reconstruct it accurately. This method comprises two steps: first, it clusters the data into planar faces that preserve some constraints defined by knowledge related to the object (e.g., the angles between faces); and second, the models of the planes are estimated based on these data using a novel multi-constraint RANSAC. We performed experiments in the clustering and RANSAC stages, which showed that the proposed method performed better than state-of-the-art methods.

Spatially explicit estimates of length and biomass of Micromesistius poutassou (Blue Whiting) from acoustic and trawl surveys in the North-East Atlantic in May 2012

Acoustic estimates of herring and blue whiting abundance were obtained during the surveys using the Simrad ER60 scientific echosounder. The allocation of NASC-values to herring, blue whiting and other acoustic targets were based on the composition of the trawl catches and the appearance of echo recordings. To estimate the abundance, the allocated NASC -values were averaged for ICES-squares (0.5° latitude by 1° longitude). For each statistical square, the unit area density of fish (rA) in number per square nautical mile (N*nm-2) was calculated using standard equations (Foote et al., 1987; Toresen et al., 1998). To estimate the total abundance of fish, the unit area abundance for each statistical square was multiplied by the number of square nautical miles in each statistical square and then summed for all the statistical squares within defined subareas and over the total area. Biomass estimation was calculated by multiplying abundance in numbers by the average weight of the fish in each statistical square then summing all squares within defined subareas and over the total area. The Norwegian BEAM soft-ware (Totland and Godø 2001) was used to make estimates of total biomass.

Finite mixture regression model with random effects: application to neonatal hospital length of stay

A two-component mixture regression model that allows simultaneously for heterogeneity and dependency among observations is proposed. By specifying random effects explicitly in the linear predictor of the mixture probability and the mixture components, parameter estimation is achieved by maximising the corresponding best linear unbiased prediction type log-likelihood. Approximate residual maximum likelihood estimates are obtained via an EM algorithm in the manner of generalised linear mixed model (GLMM). The method can be extended to a g-component mixture regression model with the component density from the exponential family, leading to the development of the class of finite mixture GLMM. For illustration, the method is applied to analyse neonatal length of stay (LOS). It is shown that identification of pertinent factors that influence hospital LOS can provide important information for health care planning and resource allocation. (C) 2002 Elsevier Science B.V. All rights reserved.

Modelling inpatient length of stay by a hierarchical mixture regression via the EM algorithm

The modelling of inpatient length of stay (LOS) has important implications in health care studies. Finite mixture distributions are usually used to model the heterogeneous LOS distribution, due to a certain proportion of patients sustaining-a longer stay. However, the morbidity data are collected from hospitals, observations clustered within the same hospital are often correlated. The generalized linear mixed model approach is adopted to accommodate the inherent correlation via unobservable random effects. An EM algorithm is developed to obtain residual maximum quasi-likelihood estimation. The proposed hierarchical mixture regression approach enables the identification and assessment of factors influencing the long-stay proportion and the LOS for the long-stay patient subgroup. A neonatal LOS data set is used for illustration, (C) 2003 Elsevier Science Ltd. All rights reserved.

Targeting a complex transcriptome: The construction of the mouse full-length cDNA encyclopedia

We report the construction of the mouse full-length cDNA encyclopedia, the most extensive view of a complex transcriptome, on the basis of preparing and sequencing 246 libraries. Before cloning, cDNAs were enriched in full-length by Cap-Trapper, and in most cases, aggressively subtracted/normalized. We have produced 1,442,236 successful 3'-end sequences clustered into 171,144 groups, from which 60,770 clones were fully sequenced cDNAs annotated in the FANTOM-2 annotation. We have also produced 547,149 5' end reads, which clustered into 124,258 groups. Altogether, these cDNAs were further grouped in 70,000 transcriptional units (TU), which represent the best coverage of a transcriptome so far. By monitoring the extent of normalization/subtraction, we define the tentative equivalent coverage (TEC), which was estimated to be equivalent to >12,000,000 ESTs derived from standard libraries. High coverage explains discrepancies between the very large. numbers of clusters (and TUs) of this project, which also include non-protein-coding RNAs, and the lower gene number estimation of genome annotations. Altogether, S'-end clusters identify regions that are potential promoters for 8637 known genes and S'-end clusters suggest the presence of almost 63,000 transcriptional starting points. An estimate of the frequency of polyadenylation signals suggests that at least half of the singletons in the EST set represent real mRNAs. Clones accounting for about half of the predicted TUs await further sequencing. The continued high-discovery rate suggests that the task of transcriptome discovery is not yet complete.

Accessing chain length dependent termination rate coefficients of methyl methacrylate (MMA) via the reversible addition fragmentation chain transfer (RAFT) process

The RAFT-CLD-T methodology is demonstrated to be not only applicable to 1-substituted monomers such as styrene and acrylates, but also to 1,1-disubstituted monomers such as MMA. The chain length of the terminating macromolecules is controlled by CPDB in MMA bulk free radical polymerization at 80 degrees C. The evolution of the chain length dependent termination rate coefficient, k(t)(i,i), was constructed in a step-wise fashion, since the MMA/CPDB system displays hybrid behavior (between conventional and living free radical polymerization) resulting in initial high molecular weight polymers formed at low RAFT agent concentrations. The obtained CLD of k(t) in MMA polymerizations is compatible with the composite model for chain length dependent termination. For the initial chain-length regime, up to a degree of polymerization of 100, k(t) decreases with alpha (in the expression k(t)(i,i) = k(t)(0) . i(-alpha)) being close to 0.65 at 80 degrees C. At chain lengths exceeding 100, the decrease is less pronounced (affording an alpha of 0.15 at 80 degrees C). However, the data are best represented by a continuously decreasing nonlinear functionality implying a chain length dependent alpha.

Optimal sampling strategy for estimation of spatial genetic structure in tree populations

Fine-scale spatial genetic structure (SGS) in natural tree populations is largely a result of restricted pollen and seed dispersal. Understanding the link between limitations to dispersal in gene vectors and SGS is of key interest to biologists and the availability of highly variable molecular markers has facilitated fine-scale analysis of populations. However, estimation of SGS may depend strongly on the type of genetic marker and sampling strategy (of both loci and individuals). To explore sampling limits, we created a model population with simulated distributions of dominant and codominant alleles, resulting from natural regeneration with restricted gene flow. SGS estimates from subsamples (simulating collection and analysis with amplified fragment length polymorphism (AFLP) and microsatellite markers) were correlated with the 'real' estimate (from the full model population). For both marker types, sampling ranges were evident, with lower limits below which estimation was poorly correlated and upper limits above which sampling became inefficient. Lower limits (correlation of 0.9) were 100 individuals, 10 loci for microsatellites and 150 individuals, 100 loci for AFLPs. Upper limits were 200 individuals, five loci for microsatellites and 200 individuals, 100 loci for AFLPs. The limits indicated by simulation were compared with data sets from real species. Instances where sampling effort had been either insufficient or inefficient were identified. The model results should form practical boundaries for studies aiming to detect SGS. However, greater sample sizes will be required in cases where SGS is weaker than for our simulated population, for example, in species with effective pollen/seed dispersal mechanisms.

Adsorption of Lennard-Jones fluids in carbon slit pores of a finite length. A computer simulation study

The adsorption of simple Lennard-Jones fluids in a carbon slit pore of finite length was studied with Canonical Ensemble (NVT) and Gibbs Ensemble Monte Carlo Simulations (GEMC). The Canonical Ensemble was a collection of cubic simulation boxes in which a finite pore resides, while the Gibbs Ensemble was that of the pore space of the finite pore. Argon was used as a model for Lennard-Jones fluids, while the adsorbent was modelled as a finite carbon slit pore whose two walls were composed of three graphene layers with carbon atoms arranged in a hexagonal pattern. The Lennard-Jones (LJ) 12-6 potential model was used to compute the interaction energy between two fluid particles, and also between a fluid particle and a carbon atom. Argon adsorption isotherms were obtained at 87.3 K for pore widths of 1.0, 1.5 and 2.0 nm using both Canonical and Gibbs Ensembles. These results were compared with isotherms obtained with corresponding infinite pores using Grand Canonical Ensembles. The effects of the number of cycles necessary to reach equilibrium, the initial allocation of particles, the displacement step and the simulation box size were particularly investigated in the Monte Carlo simulation with Canonical Ensembles. Of these parameters, the displacement step had the most significant effect on the performance of the Monte Carlo simulation. The simulation box size was also important, especially at low pressures at which the size must be sufficiently large to have a statistically acceptable number of particles in the bulk phase. Finally, it was found that the Canonical Ensemble and the Gibbs Ensemble both yielded the same isotherm (within statistical error); however, the computation time for GEMC was shorter than that for canonical ensemble simulation. However, the latter method described the proper interface between the reservoir and the adsorbed phase (and hence the meniscus).