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Systemic acquired resistance (SAR), initiated by a plant upon recognition of microbial effectors, involves the generation of mobile signals at the primary infection site, which translocate to and activate defense responses in distal tissues. Among the signals contributing to SAR include salicylic acid (SA), nitric oxide (NO), reactive oxygen species (ROS), glycerol-3-phosphate (G3P), and pipecolic acid (Pip). Our previous studies show there are two branches of SAR signaling pathways in Arabidopsis: one regulated by NO/ROS-G3P and the other by SA. Both NO/ROS-G3P and SA-mediated signaling branches function in parallel during SAR. To better understand the role of Pip in SAR and the molecular mechanisms underlying Pip-mediated signaling, I investigated relationship between Pip and other SAR signals. My results suggest that Pip-mediated SAR is dependent on the NO/ROS-G3P branch of the SAR pathway. This is supported by the results that exogenous Pip increases NO, ROS, and G3P, but not SA. Detailed characterization of Pip metabolism showed that Pip acts upstream of several known and unknown derivatives. I also investigated involvement of ascorbic acid biosynthetic enzymes and several ROS scavenging enzymes in SAR. Together, my results suggest that Pip- and ROS-metabolic pathways regulate key steps of SAR signaling in plants., © 2020 Ruiying Liu

Purpose: To propose a deep learning-based reconstruction framework for ultrafast and robust diffusion tensor imaging and fiber tractography. Methods: We propose SuperDTI to learn the nonlinear relationship between diffusion-weighted images (DWIs) and the corresponding tensor-derived quantitative maps as well as the fiber tractography. Super DTI bypasses the tensor fitting procedure, which is well known to be highly susceptible to noise and motion in DWIs. The network is trained and tested using datasets from Human Connectome Project and patients with ischemic stroke. SuperDTI is compared against the state-of-the-art methods for diffusion map reconstruction and fiber tracking. Results: Using training and testing data both from the same protocol and scanner, SuperDTI is shown to generate fractional anisotropy and mean diffusivity maps, as well as fiber tractography, from as few as six raw DWIs. The method achieves a quantification error of less than 5% in all regions of interest in white matter and gray matter structures. We also demonstrate that the trained neural network is robust to noise and motion in the testing data, and the network trained using healthy volunteer data can be directly applied to stroke patient data without compromising the lesion detectability. Conclusion: This paper demonstrates the feasibility of superfast diffusion tensor imaging and fiber tractography using deep learning with as few as six DWIs directly, bypassing tensor fitting. Such a significant reduction in scan time may allow the inclusion of DTI into the clinical routine for many potential applications., Comment: 27 pages, 7 figures, 3 tables, 3 supporting figures

This is a preliminary outline for my research project 'Strategies for sustainability in shrinking cities' as part of the MSCA-funded ITN RE-CITY.

Geomagnetic field (GMF) intensity can be used by some animals to determine their position during migration. However, its role, if any, in mediating other migration-related phenotypes remains largely unknown. Here, we simulated variation in GMF intensity between two locations along the migration route of a nocturnal insect migrant, the brown planthopper Nilaparvata lugens , that varied by approximately 5 µT in field intensity. After one generation of exposure, we tested for changes in key morphological, behavioural and physiological traits related to migratory performance, including wing dimorphism, flight capacity and positive phototaxis. Our results showed that all three morphological and behavioural phenotypes responded to a small difference in magnetic field intensity. Consistent magnetic responses in the expression of the phototaxis-related Drosophila-like cryptochrome 1 ( Cry1 ) gene and levels of two primary energy substrates used during flight, triglyceride and trehalose, were also found. Our findings indicate changes in GMF intensity can alter the expression of phenotypes critical for insect migration and highlight the unique role of magnetoreception as a trait that may help migratory insects express potentially beneficial phenotypes in geographically variable environments.

This is a preliminary outline for my research project 'Strategies for sustainability in shrinking cities' as part of the MSCA-funded ITN RE-CITY.

This is a preliminary outline for my research project 'Strategies for sustainability in shrinking cities' as part of the MSCA-funded ITN RE-CITY.