Detection and separation of heterogeneity in molecular complexes by statistical analysis of their two-dimensional projections

Progress in molecular structure determination by cryo electron microscopy and single particle analysis has led to improvements in the resolution achievable. However, in many cases the limiting factor is structural heterogeneity of the sample. To address this problem, we have developed a method based on statistical analysis of the two-dimensional images to detect and sort localised structural variations caused, for example, by variable occupancy of a ligand. Images are sorted by two consecutive stages of multivariate statistical analysis (MSA) to dissect out the two main sources of variation, namely out of plane orientation and local structural changes. Heterogeneity caused by local changes is detected by MSA that reveals significant peaks in the higher order eigenimages. The eigenimages revealing local peaks are used for automated classification. Evaluation of differences between classes allows discrimination of molecular images with and without ligand. This method is very rapid, independent of any initial three-dimensional model, and can detect even minor subpopulations in an image ensemble. A strategy for using this technique was developed on model data sets. Here, we demonstrate the successful application of this method to both model and real EM data on chaperonin-substrate and ribosome-ligand complexes.     

Intérêt de l’imagerie hybride TEMP/TDM pour la scintigraphie des récepteurs de la somatostatine dans le bilan des tumeurs endocrines gastro-entéro-pancréatiques

In this work, we have evaluated the potential of image fusion and attenuation correction (AC) of SPECT-CT imaging for the assessment of gastro-entero-pancreatic endocrine tumors by somatostatin receptor scintigraphy (SRS).MethodAfter optimisation of acquisition and reconstruction parameters, we have evaluated, in a prospective study, SRS performed over a period of one year. We have compared visual interpretations of planar and tomographic images versus SPECT/CT images to determine if anatomical localisation and diagnostic contributions are improved. In a semi-quantitative analysis of pathological foci, we have measured maximal intensity values (T_max), tumour to background ratios (T/B) and tumour contrasts (Ct) with and without AC.ResultsIn 25 SRS, visual analysis has shown anatomical localisation improvements in 60% of cases (CI95%, 39–79) and diagnostic improvements in 64% of cases (CI95%, 43–82). Doubtful foci proportion changed from 44 to 11%. In the semi-quantitative analysis of 41 pathological foci, Wilcoxon matched-pairs tests showed significantly higher T_max, T/B and Ct values after AC.ConclusionSPECT/CT imaging improves diagnostic quality of SRS thanks to a better foci localisation and a better lesional contrast in the image.     

Automatic detection of pulmonary nodules in CT images by incorporating 3D tensor filtering with local image feature analysis

Computer-aided detection (CAD) technology has been developed and demonstrated its potential to assist radiologists in detecting pulmonary nodules especially at an early stage. In this paper, we present a novel scheme for automatic detection of pulmonary nodules in CT images based on a 3D tensor filtering algorithm and local image feature analysis. We first apply a series of preprocessing steps to segment the lung volume and generate the isotropic volumetric CT data. Next, a unique 3D tensor filtering approach and local image feature analysis are used to detect nodule candidates. A 3D level set segmentation method is used to correct and refine the boundaries of nodule candidates subsequently. Then, we extract the features of the detected candidates and select the optimal features by using a CFS (Correlation Feature Selection) subset evaluator attribute selection method. Finally, a random forest classifier is trained to classify the detected candidates. The performance of this CAD scheme is validated using two datasets namely, the LUNA16 (Lung Nodule Analysis 2016) database and the ANODE09 (Automatic Nodule Detection 2009) database. By applying a 10-fold cross-validation method, the CAD scheme yielded a sensitivity of 79.3% at an average of 4 false positive detections per scan (FP/Scan) for the former dataset, and a sensitivity of 84.62% and 2.8 FP/Scan for the latter dataset, respectively. Our detection results show that the use of 3D tensor filtering algorithm combined with local image feature analysis constitutes an effective approach to detect pulmonary nodules.     

How a small enterprise improved the conditions of night and shift work using local resources

A small oxygen factory in Cantho Province located in the Mekong Delta Area in the southern part of Vietnam was studied to provide practical support measures to improve night and shift work. A direct observation study and a fatigue symptom survey during the work were conducted. The factory applied discontinuous two-shift systems in two teams. Depending on customers' demands, they frequently prolonged oxygen production until midnight. The study results showed work-related risks such as carrying heavy oxygen cylinders, workers' sleepiness during the night work, and increased fatigue feelings among production operators. Based on the study results, better strategies for night and shift work schedules such as regular work hours minimizing overtime and night work were discussed with the managers and workers. A follow-up visit three months later confirmed many improvements undertaken in the factory. Better work arrangements for night and shift workers were made including local lighting, resting corners, filling the height gaps on the work floors, and clear work instructions. Prolonged mid-night shift was stopped. It was concluded that local small enterprises in Vietnam have much potential to improve their conditions of shift and night work once practical support measures based on their local practice is given.     

Crystallization and 7 A resolution electron density map of the large fragment of Escherichia coli DNA polymerase I

Crystals of the large fragment of Escherichia coli DNA polymerase I have been grown that diffract to better than 2.8 A resolution. They are in tetragonal space group P4(3) with a = b = 104.1 A, c = 86 A. A 7 A resolution map shows the protein to consist of two domains and to be mostly alpha-helical. The active site has been located by binding nucleoside monophosphates.     

Crystallization and preliminary X-ray diffraction analysis of arginyl-tRNA synthetase from Escherichia coli.

Arginyl-tRNA Synthetase, a class I aminoacyl tRNA synthetase playing a crucial role in protein biosynthesis, has been crystallized for the first time. Polyethylene glycol (PEG) was used as a precipitant, and the crystallization proceeded at pH 6.5. These single crystals diffracted to 2.8 A with a rotating anode X-ray source and R-axis IIc image plate detector. They have an orthorhombic space group P2(1)2(1)2 with unit cell parameters of a = 251.51 A, b = 53.12 A, and c = 52.35 A. A complete native data set has been collected at 3.1 A resolution for these crystals.     

Purification and crystallization of haemoglobin from donkey (Equus asinus)

Haemoglobin acts as an important protein for oxygen carrier in all living beings. Purification of donkey haemoglobin was done using PEG 4000 as a separating medium. Crystallization was achieved using hanging drop vapor diffusion method using 2.8 M phosphate buffer, pH 6.8. Data collection was done using mar345 image plate detector system. The crystals grown under 2.8 M phosphate buffer are monoclinic with space group C2 and cell dimensions a=107.664 A, b=63.084 A, c=54.042 A, and beta=111.747 degrees.     

Local protein structure prediction using discriminative models

Background  

In recent years protein structure prediction methods using local structure information have shown promising improvements. The quality of new fold predictions has risen significantly and in fold recognition incorporation of local structure predictions led to improvements in the accuracy of results.     

Sensitivity of leaf size and shape to climate: global patterns and paleoclimatic applications

? Paleobotanists have long used models based on leaf size and shape to reconstruct paleoclimate. However, most models incorporate a single variable or use traits that are not physiologically or functionally linked to climate, limiting their predictive power. Further, they often underestimate paleotemperature relative to other proxies. ? Here we quantify leaf-climate correlations from 92 globally distributed, climatically diverse sites, and explore potential confounding factors. Multiple linear regression models for mean annual temperature (MAT) and mean annual precipitation (MAP) are developed and applied to nine well-studied fossil floras. ? We find that leaves in cold climates typically have larger, more numerous teeth, and are more highly dissected. Leaf habit (deciduous vs evergreen), local water availability, and phylogenetic history all affect these relationships. Leaves in wet climates are larger and have fewer, smaller teeth. Our multivariate MAT and MAP models offer moderate improvements in precision over univariate approaches (± 4.0 vs 4.8°C for MAT) and strong improvements in accuracy. For example, our provisional MAT estimates for most North American fossil floras are considerably warmer and in better agreement with independent paleoclimate evidence. ? Our study demonstrates that the inclusion of additional leaf traits that are functionally linked to climate improves paleoclimate reconstructions. This work also illustrates the need for better understanding of the impact of phylogeny and leaf habit on leaf-climate relationships.     

Effects of weather and climate on the dynamics of animal population time series

Weather is one of the most basic factors impacting animal populations, but the typical strength of such impacts on population dynamics is unknown. We incorporate weather and climate index data into analysis of 492 time series of mammals, birds and insects from the global population dynamics database. A conundrum is that a multitude of weather data may a priori be considered potentially important and hence present a risk of statistical over-fitting. We find that model selection or averaging alone could spuriously indicate that weather provides strong improvements to short-term population prediction accuracy. However, a block randomization test reveals that most improvements result from over-fitting. Weather and climate variables do, in general, improve predictions, but improvements were barely detectable despite the large number of datasets considered. Climate indices such as North Atlantic Oscillation are not better predictors of population change than local weather variables. Insect time series are typically less predictable than bird or mammal time series, although all taxonomic classes display low predictability. Our results are in line with the view that population dynamics is often too complex to allow resolving mechanisms from time series, but we argue that time series analysis can still be useful for estimating net environmental effects.     

Crystallization and preliminary crystallographic data of the Fab fragment of an anti-phenylalanine hydroxylase monoclonal antibody

Two crystal habits, one rod shaped and the other square prismatic, of the Fab fragment of a monoclonal anti-phenylalanine hydroxylase antibody have been grown using the method of vapour phase diffusion against polyethylene glycol 6000. The square prisms diffract to better than 2.8 A, belong to the space group P1 and have unit cell parameters a = 41.8 A, b = 50.3 A, c = 114.7 A, alpha = 97.6 degrees, beta = 91.7 degrees, gamma = 91.0 degrees, while the rod-shaped crystals belong to the space group P212121, have unit cell parameters a = 105.6 A, b = 119.8 A, c = 82.2 A and diffract to 3.5 A resolution.     

A comprehensive comparison of multiple sequence alignment programs.

In recent years improvements to existing programs and the introduction of new iterative algorithms have changed the state-of-the-art in protein sequence alignment. This paper presents the first systematic study of the most commonly used alignment programs using BAliBASE benchmark alignments as test cases. Even below the 'twilight zone' at 10-20% residue identity, the best programs were capable of correctly aligning on average 47% of the residues. We show that iterative algorithms often offer improved alignment accuracy though at the expense of computation time. A notable exception was the effect of introducing a single divergent sequence into a set of closely related sequences, causing the iteration to diverge away from the best alignment. Global alignment programs generally performed better than local methods, except in the presence of large N/C-terminal extensions and internal insertions. In these cases, a local algorithm was more successful in identifying the most conserved motifs. This study enables us to propose appropriate alignment strategies, depending on the nature of a particular set of sequences. The employment of more than one program based on different alignment techniques should significantly improve the quality of automatic protein sequence alignment methods. The results also indicate guidelines for improvement of alignment algorithms.     

Crystallographic refinement of ricin to 2.5 A

The plant cytotoxin ricin consists of two disulfide-linked chains, each of about 30,000 daltons. An initial model based on a 2.8 A MIR electron density map has been refined against 2.5 A data using rounds of hand rebuilding coupled with either a restrained least squares algorithm or molecular dynamics (XPLOR). The last model (9) has an R factor of 21.6% and RMS deviations from standard bond lengths and angles of 0.021 A and 4.67 degrees, respectively. Refinement required several peptide segments in the original model to be adjusted translationally along the electron density. A wide range of lesser changes were also made. The RMS deviation of backbone atoms between the original and model 9 was 1.89 A. Molecular dynamics proved to be a very powerful refinement tool. However, tests showed that it could not replace human intervention in making adjustments such as local translations of the peptide chain. The R factor is not a completely satisfactory indicator of refinement progress; difference Fouriers, when observed carefully, may be a better monitor.     

Massively parallel acceleration methods for image handling operations

In the image handling and image processing areas, most operations can be executed in a pixel-by-pixel or cluster-by-cluster manner. These parallel and simultaneous executions have many benefits, and many researchers showed remarkable improvements. In this paper, we started from a specific and practical image handling and feature extraction sequences. We focused on the detailed design and robust implementation on the modern massively parallel architecture of CUDA. We present the enhanced features of our implementation and their design details. Our final result shows 13 times faster execution speed, in comparison with its previous CPU-based implementation. These methods can be applied to the variety of image manipulation processes.     

Retinal imaging with optical coherence tomography and low‐loss adaptive optics using a 2.8‐mm beam size

As data acquisition for retinal imaging with optical coherence tomography (OCT) becomes faster, efficient collection of photons becomes more important to maintain image quality. One approach is to use a larger aperture at the eye's pupil to collect more photons that have been reflected from the retina. A 2.8‐mm beam diameter system with only seven reflecting surfaces was developed for low‐loss retinal imaging. The larger beam size requires defocus and astigmatism correction, which was done in a closed loop adaptive optics method using a Shack‐Hartmann wavefront sensor and a deformable mirror (DM) with 140 actuators and a ±2.75 μm stroke. This DM facilitates defocus correction ranging from approximately ?3 D to +3 D. Comparing the new system with a standard 1.2‐mm system on a model eye, a signal‐to‐noise gain of 4.5 dB and a 2.3 times smaller speckle size were measured. Measurements on the retinas of five subjects showed even better results, with increases in dynamic range up to 13 dB. Note that the new sample arm only occupies 30 cm × 60 cm, which makes it highly suitable for imaging in a clinical environment. Figure: B‐scan images obtained over a width of 8 deg from the right eye of a 31‐year‐old Caucasian male. While the left side was imaged with a standard 1.2‐mm OCT system, the right side was imaged with the 2.8‐mm system. Both images were collected with the same integration time and incident power, after correction of aberrations. Using the dynamic range within the images, which is determined by comparing the highest pixel value to the noise floor, a difference in dynamic range of 10.8 dB was measured between the two systems.      

Prospective analysis of psychosocial outcomes in breast reconstruction: one-year postoperative results from the Michigan Breast Reconstruction Outcome Study

In the past decade, changing attitudes toward breast reconstruction among both patients and providers have led a growing number of women to seek breast reconstruction after mastectomy. Although investigators have documented the psychological, social, emotional, and functional benefits of breast reconstruction, little research has evaluated the effects of procedure choice on these outcomes. The current study prospectively evaluated and compared psychosocial outcomes for three common options for mastectomy reconstruction: tissue expander/implant, pedicle TRAM, and free TRAM techniques. In a prospective cohort design, patients undergoing postmastectomy reconstruction for the first time with expander/implant, pedicle TRAM, or free TRAM procedures were recruited from 12 centers and 23 plastic surgeons in the United States and Canada. Before reconstruction and at 1 year after reconstruction, patients were evaluated by a battery of questionnaires consisting of both generic and condition-specific surveys. Outcomes assessed included emotional well-being, vitality, general mental health, social functioning, functional well-being, social well-being, and body image. Baseline (preoperative) scores and the change in scores (the difference between postoperative and preoperative scores) were compared across procedure types using t tests and analysis of covariance. Preoperative and 1-year postoperative surveys were obtained from 273 patients. Procedure type was reported in 250 patients, of whom 56 received implant reconstructions, 128 pedicle TRAM flaps, and 66 free TRAM flaps. A total of 161 immediate and 89 delayed reconstructions were performed. Among women receiving immediate reconstruction, significant improvements were observed in all psychosocial variables except body image. However, no significant effects of procedure type on these changes over time existed. Similarly, delayed reconstruction patients had significant increases in emotional well-being, vitality, general mental health, functional well-being, and body image. Although the choice of reconstructive technique did not significantly impact most of these outcomes, significant differences existed among procedure types for three psychosocial subscales. Patients undergoing delayed expander/implant reconstructions reported greater improvements in vitality and social well-being relative to women receiving delayed TRAM procedures. By contrast, delayed TRAM patients noted significantly greater gains in body image compared with women choosing delayed expander-implant reconstruction. The authors conclude that both immediate and delayed breast reconstructions provide substantial psychosocial benefits for mastectomy patients. Although the choice of reconstructive procedure does not seem to significantly affect improvements in psychosocial status with immediate reconstruction, our data suggest that procedure type does have a significant effect on gains in vitality and body image for women undergoing delayed reconstruction.     

High-throughput, detailed, cell-specific neuroanatomy of dendritic spines using microinjection and confocal microscopy

Morphological features such as size, shape and density of dendritic spines have been shown to reflect important synaptic functional attributes and potential for plasticity. Here we describe in detail a protocol for obtaining detailed morphometric analysis of spines using microinjection of fluorescent dyes, high-resolution confocal microscopy, deconvolution and image analysis with NeuronStudio. Recent technical advancements include better preservation of tissue, resulting in prolonged ability to microinject, and algorithmic improvements that compensate for the residual z-smear inherent in all optical imaging. Confocal imaging parameters were probed systematically to identify both optimal resolution and the highest efficiency. When combined, our methods yield size and density measurements comparable to serial section transmission electron microscopy in a fraction of the time. An experiment containing three experimental groups with eight subjects each can take as little as 1 month if optimized for speed, or approximately 4-5 months if the highest resolution and morphometric detail is sought.     

Image Registration Algorithm Using Mexican Hat Function-Based Operator and Grouped Feature Matching Strategy

Feature detection and matching are crucial for robust and reliable image registration. Although many methods have been developed, they commonly focus on only one class of image features. The methods that combine two or more classes of features are still novel and significant. In this work, methods for feature detection and matching are proposed. A Mexican hat function-based operator is used for image feature detection, including the local area detection and the feature point detection. For the local area detection, we use the Mexican hat operator for image filtering, and then the zero-crossing points are extracted and merged into the area borders. For the feature point detection, the Mexican hat operator is performed in scale space to get the key points. After the feature detection, an image registration is achieved by using the two classes of image features. The feature points are grouped according to a standardized region that contains correspondence to the local area, precise registration is achieved eventually by the grouped points. An image transformation matrix is estimated by the feature points in a region and then the best one is chosen through competition of a set of the transformation matrices. This strategy has been named the Grouped Sample Consensus (GCS). The GCS has also ability for removing the outliers effectively. The experimental results show that the proposed algorithm has high registration accuracy and small computational volume.     

Structure and variability of recently inserted Alu family members.

The HS subfamily of Alu sequences is comprised of a group of nearly identical members. Individual subfamily members share 97.7% nucleotide identity with each other and 98.9% nucleotide identity with the HS consensus sequence. Individual subfamily members are on the average 2.8 million years old, and were probably derived from a single source 'master' gene sometime after the human/great ape divergence. The recent Alu family member insertions provide a better image of the structure of Alu retroposons before they have had the opportunity to change significantly. All of the HS subfamily members are flanked by perfect direct repeats as a result of insertion at staggered nicks. The 'master' gene from which the HS subfamily members were derived had an oligo-dA rich tail at least 40 bases long. The 'master' gene is very rich in CpG dinucleotides, but nucleotide substitutions within subfamily members accumulated in a random manner typical for Alu sequence with CpG substitutions occurring 9.2 fold faster than non-CpG substitutions.     

Improving the physical realism and structural accuracy of protein models by a two-step atomic-level energy minimization

Most protein structural prediction algorithms assemble structures as reduced models that represent amino acids by a reduced number of atoms to speed up the conformational search. Building accurate full-atom models from these reduced models is a necessary step toward a detailed function analysis. However, it is difficult to ensure that the atomic models retain the desired global topology while maintaining a sound local atomic geometry because the reduced models often have unphysical local distortions. To address this issue, we developed a new program, called ModRefiner, to construct and refine protein structures from Cα traces based on a two-step, atomic-level energy minimization. The main-chain structures are first constructed from initial Cα traces and the side-chain rotamers are then refined together with the backbone atoms with the use of a composite physics- and knowledge-based force field. We tested the method by performing an atomic structure refinement of 261 proteins with the initial models constructed from both ab initio and template-based structure assemblies. Compared with other state-of-art programs, ModRefiner shows improvements in both global and local structures, which have more accurate side-chain positions, better hydrogen-bonding networks, and fewer atomic overlaps. ModRefiner is freely available at http://zhanglab.ccmb.med.umich.edu/ModRefiner.