A topologically related singularity suggests a maximum preferred size for protein domains

A variety of protein physicochemical as well as topological properties, demonstrate a scaling behavior relative to chain length. Many of the scalings can be modeled as a power law which is qualitatively similar across the examples. In this article, we suggest a rational explanation to these observations on the basis of both protein connectivity and hydrophobic constraints of residues compactness relative to surface volume. Unexpectedly, in an examination of these relationships, a singularity was shown to exist near 255-270 residues length, and may be associated with an upper limit for domain size. Evaluation of related G-factor data points to a wide range of conformational plasticity near this point. In addition to its theoretical importance, we show by an application of CASP experimental and predicted structures, that the scaling is a practical filter for protein structure prediction.     

Fast spatiotemporal smoothing of calcium measurements in dendritic trees

We discuss methods for fast spatiotemporal smoothing of calcium signals in dendritic trees, given single-trial, spatially localized imaging data obtained via multi-photon microscopy. By analyzing the dynamics of calcium binding to probe molecules and the effects of the imaging procedure, we show that calcium concentration can be estimated up to an affine transformation, i.e., an additive and multiplicative constant. To obtain a full spatiotemporal estimate, we model calcium dynamics within the cell using a functional approach. The evolution of calcium concentration is represented through a smaller set of hidden variables that incorporate fast transients due to backpropagating action potentials (bAPs), or other forms of stimulation. Because of the resulting state space structure, inference can be done in linear time using forward-backward maximum-a-posteriori methods. Non-negativity constraints on the calcium concentration can also be incorporated using a log-barrier method that does not affect the computational scaling. Moreover, by exploiting the neuronal tree structure we show that the cost of the algorithm is also linear in the size of the dendritic tree, making the approach applicable to arbitrarily large trees. We apply this algorithm to data obtained from hippocampal CA1 pyramidal cells with experimentally evoked bAPs, some of which were paired with excitatory postsynaptic potentials (EPSPs). The algorithm recovers the timing of the bAPs and provides an estimate of the induced calcium transient throughout the tree. The proposed methods could be used to further understand the interplay between bAPs and EPSPs in synaptic strength modification. More generally, this approach allows us to infer the concentration on intracellular calcium across the dendritic tree from noisy observations at a discrete set of points in space.     

A Method for Accurate Reconstructions of the Upper Airway Using Magnetic Resonance Images

Objective

The purpose of this study is to provide an optimized method to reconstruct the structure of the upper airway (UA) based on magnetic resonance imaging (MRI) that can faithfully show the anatomical structure with a smooth surface without artificial modifications.

Methods

MRI was performed on the head and neck of a healthy young male participant in the axial, coronal and sagittal planes to acquire images of the UA. The level set method was used to segment the boundary of the UA. The boundaries in the three scanning planes were registered according to the positions of crossing points and anatomical characteristics using a Matlab program. Finally, the three-dimensional (3D) NURBS (Non-Uniform Rational B-Splines) surface of the UA was constructed using the registered boundaries in all three different planes.

Results

A smooth 3D structure of the UA was constructed, which captured the anatomical features from the three anatomical planes, particularly the location of the anterior wall of the nasopharynx. The volume and area of every cross section of the UA can be calculated from the constructed 3D model of UA.

Conclusions

A complete scheme of reconstruction of the UA was proposed, which can be used to measure and evaluate the 3D upper airway accurately.     

3D lidar imaging for detecting and understanding plant responses and canopy structure

Understanding and diagnosing plant responses to stress will benefit greatly from three-dimensional (3D) measurement and analysis of plant properties because plant responses are strongly related to their 3D structures. Light detection and ranging (lidar) has recently emerged as a powerful tool for direct 3D measurement of plant structure. Here the use of 3D lidar imaging to estimate plant properties such as canopy height, canopy structure, carbon stock, and species is demonstrated, and plant growth and shape responses are assessed by reviewing the development of lidar systems and their applications from the leaf level to canopy remote sensing. In addition, the recent creation of accurate 3D lidar images combined with natural colour, chlorophyll fluorescence, photochemical reflectance index, and leaf temperature images is demonstrated, thereby providing information on responses of pigments, photosynthesis, transpiration, stomatal opening, and shape to environmental stresses; these data can be integrated with 3D images of the plants using computer graphics techniques. Future lidar applications that provide more accurate dynamic estimation of various plant properties should improve our understanding of plant responses to stress and of interactions between plants and their environment. Moreover, combining 3D lidar with other passive and active imaging techniques will potentially improve the accuracy of airborne and satellite remote sensing, and make it possible to analyse 3D information on ecophysiological responses and levels of various substances in agricultural and ecological applications and in observations of the global biosphere.     

Convolutional neural networks for reconstruction of undersampled optical projection tomography data applied to in vivo imaging of zebrafish

Optical projection tomography (OPT) is a 3D mesoscopic imaging modality that can utilize absorption or fluorescence contrast. 3D images can be rapidly reconstructed from tomographic data sets sampled with sufficient numbers of projection angles using the Radon transform, as is typically implemented with optically cleared samples of the mm‐to‐cm scale. For in vivo imaging, considerations of phototoxicity and the need to maintain animals under anesthesia typically preclude the acquisition of OPT data at a sufficient number of angles to avoid artifacts in the reconstructed images. For sparse samples, this can be addressed with iterative algorithms to reconstruct 3D images from undersampled OPT data, but the data processing times present a significant challenge for studies imaging multiple animals. We show here that convolutional neural networks (CNN) can be used in place of iterative algorithms to remove artifacts—reducing processing time for an undersampled in vivo zebrafish dataset from 77 to 15 minutes. We also show that using CNN produces reconstructions of equivalent quality to compressed sensing with 40% fewer projections. We further show that diverse training data classes, for example, ex vivo mouse tissue data, can be used for CNN‐based reconstructions of OPT data of other species including live zebrafish.      

Effect of capping upon the mRNA properties of satellite tobacco necrosis virus ribonucleic acid.

The mRNA guanyltransferase-mRNA methyltransferases of vaccinia virions can be used to introduce a 5'-terminal m7g(5')pp(5')Apm... capping group onto the RNA of satellite tobacco necrosis virus (STNV RNA) to yield intact capped STNV RNA. Studies with an in vitro system from wheat germ and limiting quantities of capped and uncapped STNV RNA show that the rates and extents of formation of initiation complexes of protein synthesis by intact capped and uncapped STNV RNA are identical, suggesting that 5'-terminal cap groups cannot function in the translation of STNV RNA. Also, the cap analogue pm7G equally inhibits the initiation and the translation of limiting quantities of both capped and uncapped STNV RNA. These contrasting observations suggest that the wheat germ system contains a pm7G sensitive protein and that STNV RNA has a tertiary structure that restricts the function of an added 5'-terminal capping group. This theory is supported by observations that fragmented capped STNV RNA is better at forming initiation complexes than is equally fragmented uncapped STNV RNA.     

A two-exposure technique for ice-embedded samples successfully reconstructs the chlorocruorin pigment of Sabella spallanzanii at 2. 1 Nm resolution.

A technique for reconstructing ice-embedded macromolecules from electron micrographs taken at two specimen tilts (+/-23 degrees ) has been used to determine the structure of chlorocruorin isolated from the Polychaete annelid Sabella spallanzanii. Images of individual molecules were extracted in couples from two micrographs of the same field of view so each couple consists of two projections of the same molecule. One couple was used as a fixed reference for alignment. Different references yielded reconstructions with different orientations. These were merged to give a model against which the orientation of 1624 first-exposure images was refined to give a final reconstruction at 2.1 nm resolution. The structure of this hematic pigment, essentially the same as that for Lumbricus terrestris, is a bilayer structure with overall symmetry D6, containing six hollow groups per layer. A hollow group is formed by six globular masses and has approximate threefold symmetry. Other structural elements connect the two layers and the hollow groups in a layer. This non-globin material occupies about 15% of the total molecular volume. The results show that the double-exposure strategy, previously described by some of the authors and tested in computer simulations, performs well in real experiments and could be used to obtain preliminary reconstructions in a semiautomatic way.     

A Fast Image Alignment Approach for 2D Classification of Cryo-EM Images Using Spectral Clustering

Three-dimensional (3D) reconstruction in single-particle cryo-electron microscopy (cryo-EM) is a significant technique for recovering the 3D structure of proteins or other biological macromolecules from their two-dimensional (2D) noisy projection images taken from unknown random directions. Class averaging in single-particle cryo-EM is an important procedure for producing high-quality initial 3D structures, where image alignment is a fundamental step. In this paper, an efficient image alignment algorithm using 2D interpolation in the frequency domain of images is proposed to improve the estimation accuracy of alignment parameters of rotation angles and translational shifts between the two projection images, which can obtain subpixel and subangle accuracy. The proposed algorithm firstly uses the Fourier transform of two projection images to calculate a discrete cross-correlation matrix and then performs the 2D interpolation around the maximum value in the cross-correlation matrix. The alignment parameters are directly determined according to the position of the maximum value in the cross-correlation matrix after interpolation. Furthermore, the proposed image alignment algorithm and a spectral clustering algorithm are used to compute class averages for single-particle 3D reconstruction. The proposed image alignment algorithm is firstly tested on a Lena image and two cryo-EM datasets. Results show that the proposed image alignment algorithm can estimate the alignment parameters accurately and efficiently. The proposed method is also used to reconstruct preliminary 3D structures from a simulated cryo-EM dataset and a real cryo-EM dataset and to compare them with RELION. Experimental results show that the proposed method can obtain more high-quality class averages than RELION and can obtain higher reconstruction resolution than RELION even without iteration.     

Predicting mountain plant richness and rarity from space using satellite-derived vegetation indices

Can species richness and rarity be predicted from space? If satellite‐derived vegetation indices can provide us with accurate predictions of richness and rarity in an area, they can serve as an excellent tool in diversity and conservation research, especially in inaccessible areas. The increasing availability of high‐resolution satellite images is enabling us to study this question more carefully. We sampled plant richness and rarity in 34 quadrats (1000 m²) along an elevation gradient between 300 and 2200 m focusing on Mount Hermon as a case study. We then used 10 Landsat, Aster, and QuickBird satellite images ranging over several seasons, going up to very high resolutions, to examine the relationship between plant richness, rarity, and vegetation indices calculated from the images. We used the normalized difference vegetation index (NDVI), one of the most commonly used vegetation indexes, which is strongly correlated to primary production both globally and locally (in more seasonal and in drier and/or colder environments that have wide ranges of NDVI values). All images showed a positive significant correlation between NDVI and both plant species richness and percentage tree cover (with R² as high as 0.87 between NDVI and total plant richness and 0.89 for annual plant richness). The high resolution images enabled us to examine spatial heterogeneity in NDVI within our quadrats. Plant richness was significantly correlated with the standard deviation of NDVI values (but not with their coefficient of variation) within quadrats and between images. Contrary to richness, relative range size rarity was negatively correlated with NDVI in all images, this result being significant in most cases. Thus, given that they are validated by fieldwork, satellite‐derived indices can shed light on richness and even rarity patterns in mountains, many of which are important biodiversity centres.     

玉龙雪山地区地表三维温度场时空变化分析

玉龙雪山属于海洋型冰川,对全球气候变化敏感,具有重要的生态研究价值。为了获取玉龙雪山地区的地表温度变化情况,提出了一种基于地表三维温度场的定量分析方法。首先,采用高分辨率立体测绘卫星影像构建数字表面模型,作为三维底图参考,并利用多时序热红外卫星影像数据反演地表温度场模型,提供地表温度变化依据;然后,在统一参考坐标系下将数字表面模型和多时序地表温度场模型套合,准确地分析地表温度时空变化情况。试验利用1987年至2018年间同一季节的Landsat卫星遥感影像反演地表温度,结合资源三号卫星立体影像构建的数字表面模型,并采用四阶温度区间分析多时序范围内玉龙雪山地区的地表温度变化情况。试验结果表明玉龙雪山低温区和次低温区面积逐渐减小,减小速度分别为2.096 km²/a和2.662 km²/a,中温区和暖温区面积逐渐增大,增大速度分别为2.902 km²/a和1.703km²/a,玉龙雪山地区的地表温度呈现整体上升的趋势,为全球生态环境变化提供参考。     

The isoforms of phospholipase C-gamma are differentially used by distinct human NK activating receptors

The two isoforms of phospholipase C (PLC)-gamma couple immune recognition receptors to important calcium- and protein kinase C-dependent cellular functions. It has been assumed that PLC-gamma1 and PLC-gamma2 have redundant functions and that the receptors can use whichever PLC-gamma isoform is preferentially expressed in a cell of a given hemopoietic lineage. In this study, we demonstrate that ITAM-containing immune recognition receptors can use either PLC-gamma1 or PLC-gamma2, whereas the novel NK cell-activating receptor NKG2D preferentially couples to PLC-gamma2. Experimental models evaluating signals from either endogenous receptors (FcR vs NKG2D-DAP10) or ectopically expressed chimeric receptors (with ITAM-containing cytoplasmic tails vs DAP10-containing cytoplasmic tails) demonstrate that PLC-gamma1 and PLC-gamma2 both regulate the functions of ITAM-containing receptors, whereas only PLC-gamma2 regulates the function of DAP10-coupled receptors. These data suggest that specific immune recognition receptors can differentially couple to the two isoforms of PLC-gamma. More broadly, these observations reveal a basis for selectively targeting the functions initiated by distinct immune recognition receptors.     

Human artificial chromosomes with alpha satellite-based de novo centromeres show increased frequency of nondisjunction and anaphase lag

Human artificial chromosomes have been used to model requirements for human chromosome segregation and to explore the nature of sequences competent for centromere function. Normal human centromeres require specialized chromatin that consists of alpha satellite DNA complexed with epigenetically modified histones and centromere-specific proteins. While several types of alpha satellite DNA have been used to assemble de novo centromeres in artificial chromosome assays, the extent to which they fully recapitulate normal centromere function has not been explored. Here, we have used two kinds of alpha satellite DNA, DXZ1 (from the X chromosome) and D17Z1 (from chromosome 17), to generate human artificial chromosomes. Although artificial chromosomes are mitotically stable over many months in culture, when we examined their segregation in individual cell divisions using an anaphase assay, artificial chromosomes exhibited more segregation errors than natural human chromosomes (P < 0.001). Naturally occurring, but abnormal small ring chromosomes derived from chromosome 17 and the X chromosome also missegregate more than normal chromosomes, implicating overall chromosome size and/or structure in the fidelity of chromosome segregation. As different artificial chromosomes missegregate over a fivefold range, the data suggest that variable centromeric DNA content and/or epigenetic assembly can influence the mitotic behavior of artificial chromosomes.     

A general method for calculating likelihoods under the coalescent process

Analysis of genomic data requires an efficient way to calculate likelihoods across very large numbers of loci. We describe a general method for finding the distribution of genealogies: we allow migration between demes, splitting of demes [as in the isolation-with-migration (IM) model], and recombination between linked loci. These processes are described by a set of linear recursions for the generating function of branch lengths. Under the infinite-sites model, the probability of any configuration of mutations can be found by differentiating this generating function. Such calculations are feasible for small numbers of sampled genomes: as an example, we show how the generating function can be derived explicitly for three genes under the two-deme IM model. This derivation is done automatically, using Mathematica. Given data from a large number of unlinked and nonrecombining blocks of sequence, these results can be used to find maximum-likelihood estimates of model parameters by tabulating the probabilities of all relevant mutational configurations and then multiplying across loci. The feasibility of the method is demonstrated by applying it to simulated data and to a data set previously analyzed by Wang and Hey (2010) consisting of 26,141 loci sampled from Drosophila simulans and D. melanogaster. Our results suggest that such likelihood calculations are scalable to genomic data as long as the numbers of sampled individuals and mutations per sequence block are small.     

On the structural complexity of a protein

The determination of the configuration of a protein in three-dimensional (3D) space constitutes one of the major challenges in molecular biology research today. A method consists in choosing a protein structure from a database that minimizes an energy function. First, we model the problem in terms of dynamic programming and show that the determination of the order in which the variables must be considered to minimize the time complexity is an NP-hard problem. Second, we propose a new decomposition algorithm of the threading problem that is based on the connectivity of the graph induced by the 3D structure of a protein. Our decomposition could be used to solve the threading problem. The goal in this paper is to evaluate the intrinsic complexity of 3D structure, which can be viewed as information that may be incorporated into a solution method. It provides two indexes of complexity (time and space) and determines in polynomial time complex components of the 3D structure of a protein.     

Automated Hazard Assessment Techniques Using Satellite Images Following the 2008 Sichuan China Earthquake

Rapid seismic hazard assessment is crucial for accurate damage estimation right after earthquakes. New technologies provide faster damage detection compared to the traditional, manual assessments. One of the new technologies includes using satellite images. Pre- and post-earthquake satellite images can be used to identify damage patterns. One of the recent disastrous earthquakes occurred in Sichuan (M_w = 7.9) on May 12, 2008. Records show that 5 million buildings have collapsed, and more than 21 million buildings were damaged. This article presents an approach for earthquake hazard assessment using a change detection method applied to pre- and post-earthquake satellite imagery of Sichuan. The damage inspection for the identified areas was carried out performing image analysis of the pre- and post-event satellite images. In this study, a novel automated image analysis technique was developed to assess the impact of the earthquake on the flooding of the area's rivers as well as the tectonic movement of mountains. The technique was used to quantify the flooding and movement of mountains in Sichuan right after the earthquake. The proposed methodology utilizes satellite images and may potentially be used as a rapid procedure to quantify damage soon after an earthquake.     

Chromatin structure of Drosophila nasutoides satellites as probed by cross-linking DNA in situ

Chromatin structure can be probed by cross-linking DNA in situ using trioxsalen and irradiation with UV light. Presumably DNA within a nucleosome is protected from cross-linking so that this region appears as a single-strand loop in the electron microscope under a condition in which single-strands and double-strands are distinguished. Unprotected regions appear as duplex due to cross-linking.We have used this approach to investigate the structure of chromatins containing satellite DNAs of Drosophila nasutoides. We have previously shown that D. nasutoides has an unusually large autosome pair which is almost entirely heterochromatic. Its nuclear DNA reveals four major satellite components amounting up to 60% of the total genome. All of them are localized in this large heterochromatic chromosome. We wish to ask whether chromatins containing different satellite sequences have different arrangements of nucleosomes. Our results from cross-linking experiments show that all DNA components including main band DNA have different patterns of protected and unprotected regions: (a) The length distributions of protected regions show multiple peaks with the smallest unit lengths being 200 nucleotides for main band DNA, 180 for satellites I, II and III, and 160 for satellite IV. (b) The amounts of unprotected regions, presumably internucleosome DNA, vary from 16% for main band DNA to 60% for satellite IV, suggesting that satellite chromatins have fewer nucleosomes per given length of chromatin than main band DNA chromatin. The spacings between nucleosomes appear to be random in satellite chromatins.     

Genetic structure of a foundation species: scaling community phenotypes from the individual to the region

Understanding the local and regional patterns of species distributions has been a major goal of ecological and evolutionary research. The notion that these patterns can be understood through simple quantitative rules is attractive, but while numerous scaling laws exist (e.g., metabolic, fractals), we are aware of no studies that have placed individual traits and community structure together within a genetics based scaling framework. We document the potential for a genetic basis to the scaling of ecological communities, largely based upon our long-term studies of poplars (Populus spp.). The genetic structure and diversity of these foundation species affects riparian ecosystems and determines a much larger community of dependent organisms. Three examples illustrate these ideas. First, there is a strong genetic basis to phytochemistry and tree architecture (both above- and belowground), which can affect diverse organisms and ecosystem processes. Second, empirical studies in the wild show that the local patterns of genetics based community structure scale up to western North America. At multiple spatial scales the arthropod community phenotype is related to the genetic distance among plants that these arthropods depend upon for survival. Third, we suggest that the familiar species-area curve, in which species richness is a function of area, is also a function of genetic diversity. We find that arthropod species richness is closely correlated with the genetic marker diversity and trait variance suggesting a genetic component to these curves. Finally, we discuss how genetic variation can interact with environmental variation to affect community attributes across geographic scales along with conservation implications.