Guard cells regulate stomatal pore size through integration of both endogenous and environmental signals; they are widely recognized as providing a key switching mechanism that maximizes both the ...efficient use of water and rates of CO2 exchange for photosynthesis; this is essential for the adaptation of plants to water stress. Reactive oxygen species (ROS) are widely considered to be an important player in guard cell signalling. In this review, we focus on recent progress concerning the role of ROS as signal molecules in controlling stomatal movement, the interaction between ROS and intrinsic and environmental response pathways, the specificity of ROS signalling, and how ROS signals are sensed and relayed. However, the picture of ROS-mediated signalling is still fragmented and the issues of ROS sensing and the specificity of ROS signalling remain unclear. Here, we review some recent advances in our understanding of ROS signalling in guard cells, with an emphasis on the main players known to interact with abscisic acid signalling.
Stomata, the pores formed by a pair of guard cells, are the main gateways for water transpiration and photosynthetic CO2 exchange, as well as pathogen invasion in land plants. Guard cell movement is ...regulated by a combination of environmental factors, including water status, light, CO2 levels and pathogen attack, as well as endogenous signals, such as abscisic acid and apoplastic reactive oxygen species (ROS). Under abiotic and biotic stress conditions, extracellular ROS are mainly produced by plasma membrane‐localized NADPH oxidases, whereas intracellular ROS are produced in multiple organelles. These ROS form a sophisticated cellular signaling network, with the accumulation of apoplastic ROS an early hallmark of stomatal movement. Here, we review recent progress in understanding the molecular mechanisms of the ROS signaling network, primarily during drought stress and pathogen attack. We summarize the roles of apoplastic ROS in regulating stomatal movement, ABA and CO2 signaling, and immunity responses. Finally, we discuss ROS accumulation and communication between organelles and cells. This information provides a conceptual framework for understanding how ROS signaling is integrated with various signaling pathways during plant responses to abiotic and biotic stress stimuli.
Stomata are the main gateways for water transpiration and photosynthetic CO2 exchange, as well as pathogen invasion in land plants. Stomatal movement is regulated by a combination of environmental factors including water status, light, CO2 levels and pathogen attack, as well as abscisic acid and apoplastic reactive oxygen species (ROS).
Abscisic acid (ABA) is an important phytohormone regulating plant growth, development, and stress responses. It has an essential role in multiple physiological processes of plants, such as stomatal ...closure, cuticular wax accumulation, leaf senescence, bud dormancy, seed germination, osmotic regulation, and growth inhibition among many others. Abscisic acid controls downstream responses to abiotic and biotic environmental changes through both transcriptional and posttranscriptional mechanisms. During the past 20 years, ABA biosynthesis and many of its signaling pathways have been well characterized. Here we review the dynamics of ABA metabolic pools and signaling that affects many of its physiological functions.
Abscisic acid (ABA) is the major stress hormone that coordinates plant growth, development and abiotic stress responses. In this review, we summarized the recent progresses on its metabolism, transport and signaling, and discussed the open questions about ABA dynamics and functions.
This paper presents an attribute and-or grammar (A-AOG) model for jointly inferring human body pose and human attributes in a parse graph with attributes augmented to nodes in the hierarchical ...representation. In contrast to other popular methods in the current literature that train separate classifiers for poses and individual attributes, our method explicitly represents the decomposition and articulation of body parts, and account for the correlations between poses and attributes. The A-AOG model is an amalgamation of three traditional grammar formulations: (i) Phrase structure grammar representing the hierarchical decomposition of the human body from whole to parts; (ii) Dependency grammar modeling the geometric articulation by a kinematic graph of the body pose; and (iii) Attribute grammar accounting for the compatibility relations between different parts in the hierarchy so that their appearances follow a consistent style. The parse graph outputs human detection, pose estimation, and attribute prediction simultaneously, which are intuitive and interpretable. We conduct experiments on two tasks on two datasets, and experimental results demonstrate the advantage of joint modeling in comparison with computing poses and attributes independently. Furthermore, our model obtains better performance over existing methods for both pose estimation and attribute prediction tasks.
Over 17 and 160 types of chemical modifications have been identified in DNA and RNA, respectively. The interest in understanding the various biological functions of DNA and RNA modifications has lead ...to the cutting-edged fields of epigenomics and epitranscriptomics. Developing chemical and biological tools to detect specific modifications in the genome or transcriptome has greatly facilitated their study. Here, we review the recent technological advances in this rapidly evolving field. We focus on high-throughput detection methods and biological findings for these modifications, and discuss questions to be addressed as well. We also summarize third-generation sequencing methods, which enable long-read and single-molecule sequencing of DNA and RNA modification.
• As abscisic acid (ABA) receptors, PYR1/PYL/RCAR (PYLs) play important roles in ABA-mediated seed germination, but the regulation of PYLs in this process, especially at the transcriptional level, ...remains unclear.
• In this study, we found that expression of 11 of 14 PYLs changes significantly during seed germination and is affected by exogenous ABA. Two PYLs, PYL11 and PYL12, both of which are expressed specifically in mature seeds, positively modulate ABA-mediated seed germination.
• However, ABI5 was found to modulate the PYL11- and PYL12-mediated ABA response. In the abi5-7 mutant, ABA hypersensitivity caused by PYL11 and PYL12 overexpression was totally or partially blocked. By contrast, ABI5 regulates the expression of PYL11 and PYL12 by directly binding to their promoters. Moreover, the expression of eight other PYLs is also affected during the germination of abi5 mutants. Promoter analysis revealed that an ABI5-binding region is present next to the TATA box or initiator box.
• Together, our data demonstrate the role of PYL11 and PYL12 in seed germination. In addition, the identification of PYLs as targets of ABI5 reveals a role of ABI5 in the feedback regulation of ABA-mediated seed germination.
This paper presents a method for localizing functional objects and predicting human intents and trajectories in surveillance videos of public spaces, under no supervision in training. People in ...public spaces are expected to intentionally take shortest paths (subject to obstacles) toward certain objects (e.g., vending machine, picnic table, dumpster etc.) where they can satisfy certain needs (e.g., quench thirst). Since these objects are typically very small or heavily occluded, they cannot be inferred by their visual appearance but indirectly by their influence on people's trajectories. Therefore, we call them "dark matter", by analogy to cosmology, since their presence can only be observed as attractive or repulsive "fields" in the public space. A person in the scene is modeled as an intelligent agent engaged in one of the "fields" selected depending his/her intent. An agent's trajectory is derived from an Agent-based Lagrangian Mechanics. The agents can change their intents in the middle of motion and thus alter the trajectory. For evaluation, we compiled and annotated a new dataset. The results demonstrate our effectiveness in predicting human intent behaviors and trajectories, and localizing and discovering distinct types of "dark matter" in wide public spaces.
We present DenseRaC, a novel end-to-end framework for jointly estimating 3D human pose and body shape from a monocular RGB image. Our two-step framework takes the body pixel-to-surface correspondence ...map (i.e., IUV map) as proxy representation and then performs estimation of parameterized human pose and shape. Specifically, given an estimated IUV map, we develop a deep neural network optimizing 3D body reconstruction losses and further integrating a render-and-compare scheme to minimize differences between the input and the rendered output, i.e., dense body landmarks, body part masks, and adversarial priors. To boost learning, we further construct a large-scale synthetic dataset (MOCA) utilizing web-crawled Mocap sequences, 3D scans and animations. The generated data covers diversified camera views, human actions and body shapes, and is paired with full ground truth. Our model jointly learns to represent the 3D human body from hybrid datasets, mitigating the problem of unpaired training data. Our experiments show that DenseRaC obtains superior performance against state of the art on public benchmarks of various human-related tasks.
This paper addresses the task of detecting and recognizing human-object interactions (HOI) in images. Considering the intrinsic complexity and structural nature of the task, we introduce a cascaded ...parsing network (CP-HOI) for a multi-stage, structured HOI understanding. At each cascade stage, an instance detection module progressively refines HOI proposals and feeds them into a structured interaction reasoning module. Each of the two modules is also connected to its predecessor in the previous stage, enabling efficient cross-stage information propagation. The structured interaction reasoning module is built upon a graph parsing neural network (GPNN), which efficiently models potential HOI structures as graphs and mines rich context for comprehensive relation understanding. In particular, GPNN infers a parse graph that i) interprets meaningful HOI structures by a learnable adjacency matrix, and ii) predicts action (edge) labels. Within an end-to-end, message-passing framework, GPNN blends learning and inference, iteratively parsing HOI structures and reasoning HOI representations ( i.e ., instance and relation features). Further beyond relation detection at a bounding-box level, we make our framework flexible to perform fine-grained pixel-wise relation segmentation; this provides a new glimpse into better relation modeling. A preliminary version of our CP-HOI model reached 1 st place in the ICCV2019 Person in Context Challenge, on both relation detection and segmentation. In addition, our CP-HOI shows promising results on two popular HOI recognition benchmarks, i.e ., V-COCO and HICO-DET.
Bisulfite sequencing has been the gold standard for mapping DNA modifications including 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC) for decades
. However, this harsh chemical treatment ...degrades the majority of the DNA and generates sequencing libraries with low complexity
. Here, we present a bisulfite-free and base-level-resolution sequencing method, TET-assisted pyridine borane sequencing (TAPS), for detection of 5mC and 5hmC. TAPS combines ten-eleven translocation (TET) oxidation of 5mC and 5hmC to 5-carboxylcytosine (5caC) with pyridine borane reduction of 5caC to dihydrouracil (DHU). Subsequent PCR converts DHU to thymine, enabling a C-to-T transition of 5mC and 5hmC. TAPS detects modifications directly with high sensitivity and specificity, without affecting unmodified cytosines. This method is nondestructive, preserving DNA fragments over 10 kilobases long. We applied TAPS to the whole-genome mapping of 5mC and 5hmC in mouse embryonic stem cells and show that, compared with bisulfite sequencing, TAPS results in higher mapping rates, more even coverage and lower sequencing costs, thus enabling higher quality, more comprehensive and cheaper methylome analyses.
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