Image Harvest: an open-source platform for high-throughput plant image processing and analysis

High-throughput plant phenotyping is an effective approach to bridge the genotype-to-phenotype gap in crops. Phenomics experiments typically result in large-scale image datasets, which are not amenable for processing on desktop computers, thus creating a bottleneck in the image-analysis pipeline. Here, we present an open-source, flexible image-analysis framework, called Image Harvest (IH), for processing images originating from high-throughput plant phenotyping platforms. Image Harvest is developed to perform parallel processing on computing grids and provides an integrated feature for metadata extraction from large-scale file organization. Moreover, the integration of IH with the Open Science Grid provides academic researchers with the computational resources required for processing large image datasets at no cost. Image Harvest also offers functionalities to extract digital traits from images to interpret plant architecture-related characteristics. To demonstrate the applications of these digital traits, a rice (Oryza sativa) diversity panel was phenotyped and genome-wide association mapping was performed using digital traits that are used to describe different plant ideotypes. Three major quantitative trait loci were identified on rice chromosomes 4 and 6, which co-localize with quantitative trait loci known to regulate agronomically important traits in rice. Image Harvest is an open-source software for high-throughput image processing that requires a minimal learning curve for plant biologists to analyze phenomics datasets. Supplementary files (2) attached below

On the relation between the Feynman paradox and Aharonov-Bohm effects

The magnetic Aharonov-Bohm (A-B) effect occurs when a point charge interacts with a line of magnetic flux, while its dual, the Aharonov-Casher (A-C) effect, occurs when a magnetic moment interacts with a line of charge. For the two interacting parts of these physical systems, the equations of motion are discussed in this paper. The generally accepted claim is that both parts of these systems do not accelerate, while Boyer has claimed that both parts of these systems do accelerate. Using the Euler-Lagrange equations we predict that in the case of unconstrained motion only one part of each system accelerates, while momentum remains conserved. This prediction requires a time dependent electromagnetic momentum. For our analysis of unconstrained motion the A-B effects are then examples of the Feynman paradox. In the case of constrained motion, the Euler-Lagrange equations give no forces in agreement with the generally accepted analysis. The quantum mechanical A-B and A-C phase shifts are independent of the treatment of constraint. Nevertheless, experimental testing of the above ideas and further understanding of A-B effects which is central to both quantum mechanics and electromagnetism may be possible.Comment: 21 pages, 5 figures, recently submitted to New Journal of Physic

Searching the protein structure database for ligand-binding site similarities using CPASS v.2

<p>Abstract</p> <p>Background</p> <p>A recent analysis of protein sequences deposited in the NCBI RefSeq database indicates that ~8.5 million protein sequences are encoded in prokaryotic and eukaryotic genomes, where ~30% are explicitly annotated as "hypothetical" or "uncharacterized" protein. Our Comparison of Protein Active-Site Structures (CPASS v.2) database and software compares the sequence and structural characteristics of experimentally determined ligand binding sites to infer a functional relationship in the absence of global sequence or structure similarity. CPASS is an important component of our Functional Annotation Screening Technology by NMR (FAST-NMR) protocol and has been successfully applied to aid the annotation of a number of proteins of unknown function.</p> <p>Findings</p> <p>We report a major upgrade to our CPASS software and database that significantly improves its broad utility. CPASS v.2 is designed with a layered architecture to increase flexibility and portability that also enables job distribution over the Open Science Grid (OSG) to increase speed. Similarly, the CPASS interface was enhanced to provide more user flexibility in submitting a CPASS query. CPASS v.2 now allows for both automatic and manual definition of ligand-binding sites and permits pair-wise, one versus all, one versus list, or list versus list comparisons. Solvent accessible surface area, ligand root-mean square difference, and Cβ distances have been incorporated into the CPASS similarity function to improve the quality of the results. The CPASS database has also been updated.</p> <p>Conclusions</p> <p>CPASS v.2 is more than an order of magnitude faster than the original implementation, and allows for multiple simultaneous job submissions. Similarly, the CPASS database of ligand-defined binding sites has increased in size by ~ 38%, dramatically increasing the likelihood of a positive search result. The modification to the CPASS similarity function is effective in reducing CPASS similarity scores for false positives by ~30%, while leaving true positives unaffected. Importantly, receiver operating characteristics (ROC) curves demonstrate the high correlation between CPASS similarity scores and an accurate functional assignment. As indicated by distribution curves, scores ≥ 30% infer a functional similarity. Software URL: <url>http://cpass.unl.edu</url>.</p

Variation in Soil Respiration across Soil and Vegetation Types in an Alpine Valley.

BACKGROUND AND AIMS: Soils of mountain regions and their associated plant communities are highly diverse over short spatial scales due to the heterogeneity of geological substrates and highly dynamic geomorphic processes. The consequences of this heterogeneity for biogeochemical transfers, however, remain poorly documented. The objective of this study was to quantify the variability of soil-surface carbon dioxide efflux, known as soil respiration (Rs), across soil and vegetation types in an Alpine valley. To this aim, we measured Rs rates during the peak and late growing season (July-October) in 48 plots located in pastoral areas of a small valley of the Swiss Alps. FINDINGS: Four herbaceous vegetation types were identified, three corresponding to different stages of primary succession (Petasition paradoxi in pioneer conditions, Seslerion in more advanced stages and Poion alpinae replacing the climactic forests), as well as one (Rumicion alpinae) corresponding to eutrophic grasslands in intensively grazed areas. Soils were developed on calcareous alluvial and colluvial fan deposits and were classified into six types including three Fluvisols grades and three Cambisols grades. Plant and soil types had a high level of co-occurrence. The strongest predictor of Rs was soil temperature, yet we detected additional explanatory power of sampling month, showing that temporal variation was not entirely reducible to variations in temperature. Vegetation and soil types were also major determinants of Rs. During the warmest month (August), Rs rates varied by over a factor three between soil and vegetation types, ranging from 2.5 μmol m-2 s-1 in pioneer environments (Petasition on Very Young Fluvisols) to 8.5 μmol m-2 s-1 in differentiated soils supporting nitrophilous species (Rumicion on Calcaric Cambisols). CONCLUSIONS: Overall, this study provides quantitative estimates of spatial and temporal variability in Rs in the mountain environment, and demonstrates that estimations of soil carbon efflux at the watershed scale in complex geomorphic terrain have to account for soil and vegetation heterogeneity

Patient-cooperative control increases active participation of individuals with SCI during robot-aided gait training

ABSTRACT: BACKGROUND: Manual body weight supported treadmill training and robot-aided treadmill training are frequently used techniques for the gait rehabilitation of individuals after stroke and spinal cord injury. Current evidence suggests that robot-aided gait training may be improved by making robotic behavior more patient-cooperative. In this study, we have investigated the immediate effects of patient-cooperative versus non-cooperative robot-aided gait training on individuals with incomplete spinal cord injury (iSCI). METHODS: Eleven patients with iSCI participated in a single training session with the gait rehabilitation robot Lokomat. The patients were exposed to four different training modes in random order: During both non-cooperative position control and compliant impedance control, fixed timing of movements was provided. During two variants of the patient-cooperative path control approach, free timing of movements was enabled and the robot provided only spatial guidance. The two variants of the path control approach differed in the amount of additional support, which was either individually adjusted or exaggerated. Joint angles and torques of the robot as well as muscle activity and heart rate of the patients were recorded. Kinematic variability, interaction torques, heart rate and muscle activity were compared between the different conditions. RESULTS: Patients showed more spatial and temporal kinematic variability, reduced interaction torques, a higher increase of heart rate and more muscle activity in the patient-cooperative path control mode with individually adjusted support than in the non-cooperative position control mode. In the compliant impedance control mode, spatial kinematic variability was increased and interaction torques were reduced, but temporal kinematic variability, heart rate and muscle activity were not significantly higher than in the position control mode. CONCLUSIONS: Patient-cooperative robot-aided gait training with free timing of movements made individuals with iSCI participate more actively and with larger kinematic variability than non-cooperative, position-controlled robot-aided gait training

Path control: a method for patient-cooperative robot-aided gait rehabilitation

Gait rehabilitation robots are of increasing importance in neurorehabilitation. Conventional devices are often criticized because they are limited to reproducing predefined movement patterns. Research on patient-cooperative control strategies aims at improving robotic behavior. Robots should support patients only as much as needed and stimulate them to produce maximal voluntary efforts. This paper presents a patient-cooperative strategy that allows patients to influence the timing of their leg movements along a physiologically meaningful path. In this "path control" strategy, compliant virtual walls keep the patient's legs within a "tunnel" around the desired spatial path. Additional supportive torques enable patients to move along the path with reduced effort. Graphical feedback provides visual training instructions. The path control strategy was evaluated with 10 healthy subjects and 15 subjects with incomplete spinal cord injury. The spatio-temporal characteristics of recorded kinematic data showed that subjects walked with larger temporal variability with the new strategy. Electromyographic data indicated that subjects were training more actively. A majority of iSCI subjects was able to actively control their gait timing. Thus, the strategy allows patients to train walking while being helped rather than controlled by the robot

Image Harvest: an open-source platform for high-throughput plant image processing and analysis

High-throughput plant phenotyping is an effective approach to bridge the genotype-to-phenotype gap in crops. Phenomics experiments typically result in large-scale image datasets, which are not amenable for processing on desktop computers, thus creating a bottleneck in the image-analysis pipeline. Here, we present an open-source, flexible image-analysis framework, called Image Harvest (IH), for processing images originating from high-throughput plant phenotyping platforms. Image Harvest is developed to perform parallel processing on computing grids and provides an integrated feature for metadata extraction from large-scale file organization. Moreover, the integration of IH with the Open Science Grid provides academic researchers with the computational resources required for processing large image datasets at no cost. Image Harvest also offers functionalities to extract digital traits from images to interpret plant architecture-related characteristics. To demonstrate the applications of these digital traits, a rice (Oryza sativa) diversity panel was phenotyped and genome-wide association mapping was performed using digital traits that are used to describe different plant ideotypes. Three major quantitative trait loci were identified on rice chromosomes 4 and 6, which co-localize with quantitative trait loci known to regulate agronomically important traits in rice. Image Harvest is an open-source software for high-throughput image processing that requires a minimal learning curve for plant biologists to analyze phenomics datasets. Supplementary files (2) attached below

Forest soil respiration reflects plant productivity across a temperature gradient in the Alps

Soil respiration (R (s)) plays a key role in any consideration of ecosystem carbon (C) balance. Based on the well-known temperature response of respiration in plant tissue and microbes, R (s) is often assumed to increase in a warmer climate. Yet, we assume that substrate availability (labile C input) is the dominant influence on R (s) rather than temperature. We present an analysis of NPP components and concurrent R (s) in temperate deciduous forests across an elevational gradient in Switzerland corresponding to a 6 K difference in mean annual temperature and a considerable difference in the length of the growing season (174 vs. 262 days). The sum of the short-lived NPP fractions ("canopy leaf litter," "understory litter," and "fine root litter") did not differ across this thermal gradient (+6 % from cold to warm sites, n.s.), irrespective of the fact that estimated annual forest wood production was more than twice as high at low compared to high elevations (largely explained by the length of the growing season). Cumulative annual R (s) did not differ significantly between elevations (836 ± 5 g C m(-2) a(-1) and 933 ± 40 g C m(-2) a(-1) at cold and warm sites, +12 %). Annual soil CO(2) release thus largely reflected the input of labile C and not temperature, despite the fact that R (s) showed the well-known short-term temperature response within each site. However, at any given temperature, R (s) was lower at the warm sites (downregulation). These results caution against assuming strong positive effects of climatic warming on R (s), but support a close substrate relatedness of R (s)