scholarly journals Organellar protein multi-functionality and phenotypic plasticity in plants

2019 ◽  
Vol 375 (1790) ◽  
pp. 20190182 ◽  
Author(s):  
Sally A. Mackenzie ◽  
Hardik Kundariya
Keyword(s):  
Phenotypic Plasticity ◽  
Protein Targeting ◽  
Ecological Systems ◽  
Temporal Regulation ◽  
Adaptation Mechanisms ◽  
Retrograde Signalling ◽  
Wide Range ◽  
Mitochondrial Genotype ◽  
Spatio Temporal ◽  
Ample Reason

With the increasing impact of climate instability on agricultural and ecological systems has come a heightened sense of urgency to understand plant adaptation mechanisms in more detail. Plant species have a remarkable ability to disperse their progeny to a wide range of environments, demonstrating extraordinary resiliency mechanisms that incorporate epigenetics and transgenerational stability. Surprisingly, some of the underlying versatility of plants to adapt to abiotic and biotic stress emerges from the neofunctionalization of organelles and organellar proteins. We describe evidence of possible plastid specialization and multi-functional organellar protein features that serve to enhance plant phenotypic plasticity. These features appear to rely on, for example, spatio-temporal regulation of plastid composition, and unusual interorganellar protein targeting and retrograde signalling features that facilitate multi-functionalization. Although we report in detail on three such specializations, involving MSH1, WHIRLY1 and CUE1 proteins in Arabidopsis , there is ample reason to believe that these represent only a fraction of what is yet to be discovered as we begin to elaborate cross-species diversity. Recent observations suggest that plant proteins previously defined in one context may soon be rediscovered in new roles and that much more detailed investigation of proteins that show subcellular multi-targeting may be warranted. This article is part of the theme issue ‘Linking the mitochondrial genotype to phenotype: a complex endeavour’.

scholarly journals Reshaping cAMP nanodomains through targeted disruption of compartmentalised phosphodiesterase signalosomes

2019 ◽  
Vol 47 (5) ◽  
pp. 1405-1414 ◽  
Author(s):  
Connor M. Blair ◽  
George S. Baillie
Keyword(s):  
Protein Complexes ◽  
Short Review ◽  
Effector Protein ◽  
Protein Activity ◽  
Targeted Disruption ◽  
Temporal Regulation ◽  
Wide Range ◽  
Signalling Cascades ◽  
Cell Permeable Peptide ◽  
Spatio Temporal

Abstract Spatio-temporal regulation of localised cAMP nanodomains is highly dependent upon the compartmentalised activity of phosphodiesterase (PDE) cyclic nucleotide degrading enzymes. Strategically positioned PDE–protein complexes are pivotal to the homeostatic control of cAMP-effector protein activity that in turn orchestrate a wide range of cellular signalling cascades in a variety of cells and tissue types. Unsurprisingly, dysregulated PDE activity is central to the pathophysiology of many diseases warranting the need for effective therapies that target PDEs selectively. This short review focuses on the importance of activating compartmentalised cAMP signalling by displacing the PDE component of signalling complexes using cell-permeable peptide disrupters

scholarly journals Kinematic Analysis of Lower Limb Joint Asymmetry during Gait in People with Multiple Sclerosis

Symmetry ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 598
Author(s):  
Massimiliano Pau ◽  
Bruno Leban ◽  
Michela Deidda ◽  
Federica Putzolu ◽  
Micaela Porta ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Lower Limb ◽  
Sagittal Plane ◽  
Cross Sectional Study ◽  
Camera Motion ◽  
Cross Sectional ◽  
Temporal Parameters ◽  
Wide Range ◽  
Edss Score ◽  
Spatio Temporal

The majority of people with Multiple Sclerosis (pwMS), report lower limb motor dysfunctions, which may relevantly affect postural control, gait and a wide range of activities of daily living. While it is quite common to observe a different impact of the disease on the two limbs (i.e., one of them is more affected), less clear are the effects of such asymmetry on gait performance. The present retrospective cross-sectional study aimed to characterize the magnitude of interlimb asymmetry in pwMS, particularly as regards the joint kinematics, using parameters derived from angle-angle diagrams. To this end, we analyzed gait patterns of 101 pwMS (55 women, 46 men, mean age 46.3, average Expanded Disability Status Scale (EDSS) score 3.5, range 1–6.5) and 81 unaffected individuals age- and sex-matched who underwent 3D computerized gait analysis carried out using an eight-camera motion capture system. Spatio-temporal parameters and kinematics in the sagittal plane at hip, knee and ankle joints were considered for the analysis. The angular trends of left and right sides were processed to build synchronized angle–angle diagrams (cyclograms) for each joint, and symmetry was assessed by computing several geometrical features such as area, orientation and Trend Symmetry. Based on cyclogram orientation and Trend Symmetry, the results show that pwMS exhibit significantly greater asymmetry in all three joints with respect to unaffected individuals. In particular, orientation values were as follows: 5.1 of pwMS vs. 1.6 of unaffected individuals at hip joint, 7.0 vs. 1.5 at knee and 6.4 vs. 3.0 at ankle (p < 0.001 in all cases), while for Trend Symmetry we obtained at hip 1.7 of pwMS vs. 0.3 of unaffected individuals, 4.2 vs. 0.5 at knee and 8.5 vs. 1.5 at ankle (p < 0.001 in all cases). Moreover, the same parameters were sensitive enough to discriminate individuals of different disability levels. With few exceptions, all the calculated symmetry parameters were found significantly correlated with the main spatio-temporal parameters of gait and the EDSS score. In particular, large correlations were detected between Trend Symmetry and gait speed (with rho values in the range of –0.58 to –0.63 depending on the considered joint, p < 0.001) and between Trend Symmetry and EDSS score (rho = 0.62 to 0.69, p < 0.001). Such results suggest not only that MS is associated with significantly marked interlimb asymmetry during gait but also that such asymmetry worsens as the disease progresses and that it has a relevant impact on gait performances.

Forest path condition monitoring based on crowd-based trajectory data analysis

2020 ◽  
pp. 1-18
Author(s):  
Francisco Arcas-Tunez ◽  
Fernando Terroso-Saenz
Keyword(s):  
Information Acquisition ◽  
Road Network ◽  
Road Networks ◽  
Trajectory Data ◽  
Country Road ◽  
Wide Range ◽  
Sport Activities ◽  
Path Condition ◽  
Spatio Temporal ◽  
The City

The development of Road Information Acquisition Systems (RIASs) based on the Mobile Crowdsensing (MCS) paradigm has been widely studied for the last years. In that sense, most of the existing MCS-based RIASs focus on urban road networks and assume a car-based scenario. However, there exist a scarcity of approaches that pay attention to rural and country road networks. In that sense, forest paths are used for a wide range of recreational and sport activities by many different people and they can be also affected by different problems or obstacles blocking them. As a result, this work introduces SAMARITAN, a framework for rural-road network monitoring based on MCS. SAMARITAN analyzes the spatio-temporal trajectories from cyclists extracted from the fitness application Strava so as to uncover potential obstacles in a target road network. The framework has been evaluated in a real-world network of forest paths in the city of Cieza (Spain) showing quite promising results.

Predicting Human Mobility with Reinforcement-Learning-Based Long-Term Periodicity Modeling

2021 ◽  
Vol 12 (6) ◽  
pp. 1-23
Author(s):  
Shuo Tao ◽  
Jingang Jiang ◽  
Defu Lian ◽  
Kai Zheng ◽  
Enhong Chen
Keyword(s):  
Reinforcement Learning ◽  
Human Mobility ◽  
Recurrent Network ◽  
Mobility Prediction ◽  
Learning Framework ◽  
Temporal Features ◽  
Wide Range ◽  
Spatio Temporal ◽  
Historical Trajectory

Mobility prediction plays an important role in a wide range of location-based applications and services. However, there are three problems in the existing literature: (1) explicit high-order interactions of spatio-temporal features are not systemically modeled; (2) most existing algorithms place attention mechanisms on top of recurrent network, so they can not allow for full parallelism and are inferior to self-attention for capturing long-range dependence; (3) most literature does not make good use of long-term historical information and do not effectively model the long-term periodicity of users. To this end, we propose MoveNet and RLMoveNet. MoveNet is a self-attention-based sequential model, predicting each user’s next destination based on her most recent visits and historical trajectory. MoveNet first introduces a cross-based learning framework for modeling feature interactions. With self-attention on both the most recent visits and historical trajectory, MoveNet can use an attention mechanism to capture the user’s long-term regularity in a more efficient way. Based on MoveNet, to model long-term periodicity more effectively, we add the reinforcement learning layer and named RLMoveNet. RLMoveNet regards the human mobility prediction as a reinforcement learning problem, using the reinforcement learning layer as the regularization part to drive the model to pay attention to the behavior with periodic actions, which can help us make the algorithm more effective. We evaluate both of them with three real-world mobility datasets. MoveNet outperforms the state-of-the-art mobility predictor by around 10% in terms of accuracy, and simultaneously achieves faster convergence and over 4x training speedup. Moreover, RLMoveNet achieves higher prediction accuracy than MoveNet, which proves that modeling periodicity explicitly from the perspective of reinforcement learning is more effective.

scholarly journals Rainfall spatio-temporal correlation and intermittency structure from micro-γ to meso-β scale in the Netherlands

2021 ◽  
Author(s):  
Thomas C. van Leth ◽  
Hidde Leijnse ◽  
Aart Overeem ◽  
Remko Uijlenhoet
Keyword(s):  
The Netherlands ◽  
Spatial Scales ◽  
Rainfall Variability ◽  
Temporal Structure ◽  
Temporal Correlation ◽  
Exponential Model ◽  
Rain Gauges ◽  
Wide Range ◽  
Spatio Temporal ◽  
Two Parameter

AbstractWe investigate the spatio-temporal structure of rainfall at spatial scales from 7m to over 200 km in the Netherlands. We used data from two networks of laser disdrometers with complementary interstation distances in two Dutch cities (comprising five and six disdrometers, respectively) and a Dutch nationwide network of 31 automatic rain gauges. The smallest aggregation interval for which raindrop size distributions were collected by the disdrometers was 30 s, while the automatic rain gauges provided 10-min rainfall sums. This study aims to supplement other micro-γ investigations (usually performed in the context of spatial rainfall variability within a weather radar pixel) with new data, while characterizing the correlation structure across an extended range of scales. To quantify the spatio-temporal variability, we employ a two-parameter exponential model fitted to the spatial correlograms and characterize the parameters of the model as a function of the temporal aggregation interval. This widely used method allows for a meaningful comparison with seven other studies across contrasting climatic settings all around the world. We also separately analyzed the intermittency of the rainfall observations. We show that a single parameterization, consisting of a two-parameter exponential spatial model as a function of interstation distance combined with a power-law model for decorrelation distance as a function of aggregation interval, can coherently describe rainfall variability (both spatial correlation and intermittency) across a wide range of scales. Limiting the range of scales to those typically found in micro-γ variability studies (including four of the seven studies to which we compare our results) skews the parameterization and reduces its applicability to larger scales.

scholarly journals A Survey on Spatio-temporal Data Analytics Systems

2022 ◽  
Author(s):  
Md Mahbub Alam ◽  
Luis Torgo ◽  
Albert Bifet
Keyword(s):  
Programming Languages ◽  
Spatial Data ◽  
Data Analytics ◽  
Spatial Databases ◽  
Location Based Services ◽  
Temporal Data ◽  
Wide Range ◽  
Data Volume ◽  
Spatio Temporal ◽  
Gis Software

Due to the surge of spatio-temporal data volume, the popularity of location-based services and applications, and the importance of extracted knowledge from spatio-temporal data to solve a wide range of real-world problems, a plethora of research and development work has been done in the area of spatial and spatio-temporal data analytics in the past decade. The main goal of existing works was to develop algorithms and technologies to capture, store, manage, analyze, and visualize spatial or spatio-temporal data. The researchers have contributed either by adding spatio-temporal support with existing systems, by developing a new system from scratch, or by implementing algorithms for processing spatio-temporal data. The existing ecosystem of spatial and spatio-temporal data analytics systems can be categorized into three groups, (1) spatial databases (SQL and NoSQL), (2) big spatial data processing infrastructures, and (3) programming languages and GIS software. Since existing surveys mostly investigated infrastructures for processing big spatial data, this survey has explored the whole ecosystem of spatial and spatio-temporal analytics. This survey also portrays the importance and future of spatial and spatio-temporal data analytics.

scholarly journals Stem photosynthesis: new evidence highlights the contribution of phenotypic plasticity to the invasion success of Mikania micrantha

2020 ◽  
Author(s):  
Jin Zheng ◽  
Tai-Jie Zhang ◽  
Bo-Hui Li ◽  
Wei-Jie Liang ◽  
Qi-Lei Zhang ◽  
...  
Keyword(s):  
Phenotypic Plasticity ◽  
Plant Species ◽  
Invasive Plant ◽  
Stem Elongation ◽  
Invasion Success ◽  
Invasive Plant Species ◽  
Alien Plant ◽  
Mikania Micrantha ◽  
Stem Photosynthesis ◽  
Wide Range

Phenotypic plasticity affords invasive plant species the ability to colonize a wide range of habitats, but physiological plasticity of their stems is seldom recognized. Investigation of the stem plasticity of invasive plant species could lead to a better understanding of their invasiveness. We performed a pot experiment involving defoliation treatments and an isolated culture experiment to determine whether the invasive species Mikania micrantha exhibits greater plasticity in the stems than do three native species that co-occur in southern China and then explored the mechanism underlying the modification of its stem photosynthesis. Our results showed that the stems of M. micrantha exhibited higher plasticity in terms of either net or gross photosynthesis in response to the defoliation treatment. These effects were positively related to an increased stem elongation rate. The enhancement of stem photosynthesis in M. micrantha resulted from the comprehensive action involving increases in the Chl a/b ratio, D1 protein and stomatal aperture, changes in chloroplast morphology and a decrease in anthocyanins. Increased plasticity of stem photosynthesis may improve the survival of M. micrantha under harsh conditions and allow it to rapidly recover from defoliation injuries. Our results highlight that phenotypic plasticity promotes the invasion success of alien plant invaders.

scholarly journals P-bodies and the miRNA pathway regulate translational repression of bicoid mRNA during Drosophila melanogaster oogenesis

2018 ◽  
Author(s):  
John M. McLaughlin ◽  
Daniel F.Q. Smith ◽  
Irina E. Catrina ◽  
Diana P. Bratu
Keyword(s):  
Drosophila Melanogaster ◽  
Small Rna ◽  
Translational Regulation ◽  
Translational Repression ◽  
Temporal Regulation ◽  
P Bodies ◽  
Maternal Transcripts ◽  
Spatio Temporal ◽  
Mirna Pathway ◽  
Rna Pathways

ABSTRACTEmbryonic axis patterning in Drosophila melanogaster is partly achieved by mRNAs that are maternally localized to the oocyte; the spatio-temporal regulation of these transcripts’ stability and translation is a characteristic feature of oogenesis. While protein regulatory factors are necessary for the translational regulation of some maternal transcripts (e.g. oskar and gurken), small RNA pathways are also known to regulate mRNA stability and translation in eukaryotes. MicroRNAs (miRNAs) are small RNA regulators of gene expression, widely conserved throughout eukaryotic genomes and essential for animal development. The main D. melanogaster anterior determinant, bicoid, is maternally transcribed, but it is not translated until early embryogenesis. We investigated the possibility that its translational repression during oogenesis is mediated by miRNA activity. We found that the bicoid 3’UTR contains a highly conserved, predicted binding site for miR-305. Our studies reveal that miR-305 regulates the translation of a reporter gene containing the bicoid 3’UTR in cell culture, and that miR-305 only partially contributes to bicoid mRNA translational repression during oogenesis. We also found that Processing bodies (P-bodies) in the egg chamber may play a role in stabilizing bicoid and other maternal transcripts. Here, we offer insights into the possible role of P-bodies and the miRNA pathway in the translational repression of bicoid mRNA during oogenesis.

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