Soil Moisture Determines Horizontal and Vertical Root Extension in the Perennial Grass Lolium perenne L. Growing in Karst Soil

Karst regions are characterized by heterogeneous soil habitats, with shallow wide soil (SW) on hilly slopes and deep narrow soil (DN) in rocky trenches. To make full use of limited water and nutrients, plants have therefore developed a number of root extension strategies. This study investigated the effect of soil moisture on horizontal root extension in SW and vertical root extension in DN by assessing root growth responses, biomass allocation, and root distribution. A full two-way factorial blocked design of soil dimensions by water availability was followed. The perennial grass Lolium perenne L. was grown in SW and DN under high (W100%), moderate (W50%), and low (W30%) water availability, respectively. The main results were as follows: (1) The total biomass of L. perenne was not influenced either by soil habitat or by water application. Root length, root surface area, root biomass and root to shoot ratio all decreased with decreasing water application in SW, but not in DN soil. (2) With decreasing water application, the cumulative percentage of root length, root surface area and root biomass in 4 rings from the center out to 12 cm of SW soil showed a trend of W50% > W30% > W100% in SW, however, the cumulative percentage of root biomass in 4 layers from the surface to a depth of 36 cm was not significantly different between different water treatments in DN. (3) Under all three water treatments, specific root length showed an increase but root length density showed a decreasing trend from the center outward in SW soil or from the surface to bottom in DN soil. Overall, these results suggest that in SW habitat, soil moisture determines horizontal expansion of the roots in L. perenne, although the overall expansion ability was limited in severe drought. However, due to the relatively strong water retention ability, soil moisture changes were less obvious in DN, resulting in no significant vertical extension of the root system. The root response of L. perenne helps our understanding of how herbaceous plants can adjust their belowground morphology to support their growth in harsh karst soil environments

Impact of CRAMP-34 on Pseudomonas aeruginosa biofilms and extracellular metabolites

Biofilm is a structured community of bacteria encased within a self-produced extracellular matrix. When bacteria form biofilms, they undergo a phenotypic shift that enhances their resistance to antimicrobial agents. Consequently, inducing the transition of biofilm bacteria to the planktonic state may offer a viable approach for addressing infections associated with biofilms. Our previous study has shown that the mouse antimicrobial peptide CRAMP-34 can disperse Pseudomonas aeruginosa (P. aeruginosa) biofilm, and the potential mechanism of CRAMP-34 eradicate P. aeruginosa biofilms was also investigated by combined omics. However, changes in bacterial extracellular metabolism have not been identified. To further explore the mechanism by which CRAMP-34 disperses biofilm, this study analyzed its effects on the extracellular metabolites of biofilm cells via metabolomics. The results demonstrated that a total of 258 significantly different metabolites were detected in the untargeted metabolomics, of which 73 were downregulated and 185 were upregulated. Pathway enrichment analysis of differential metabolites revealed that metabolic pathways are mainly related to the biosynthesis and metabolism of amino acids, and it also suggested that CRAMP-34 may alter the sensitivity of biofilm bacteria to antibiotics. Subsequently, it was confirmed that the combination of CRAMP-34 with vancomycin and colistin had a synergistic effect on dispersed cells. These results, along with our previous findings, suggest that CRAMP-34 may promote the transition of PAO1 bacteria from the biofilm state to the planktonic state by upregulating the extracellular glutamate and succinate metabolism and eventually leading to the dispersal of biofilm. In addition, increased extracellular metabolites of myoinositol, palmitic acid and oleic acid may enhance the susceptibility of the dispersed bacteria to the antibiotics colistin and vancomycin. CRAMP-34 also delayed the development of bacterial resistance to colistin and ciprofloxacin. These results suggest the promising development of CRAMP-34 in combination with antibiotics as a potential candidate to provide a novel therapeutic approach for the prevention and treatment of biofilm-associated infections

Deep learning for detection and segmentation of artefact and disease instances in gastrointestinal endoscopy

The Endoscopy Computer Vision Challenge (EndoCV) is a crowd-sourcing initiative to address eminent problems in developing reliable computer aided detection and diagnosis endoscopy systems and suggest a pathway for clinical translation of technologies. Whilst endoscopy is a widely used diagnostic and treatment tool for hollow-organs, there are several core challenges often faced by endoscopists, mainly: 1) presence of multi-class artefacts that hinder their visual interpretation, and 2) difficulty in identifying subtle precancerous precursors and cancer abnormalities. Artefacts often affect the robustness of deep learning methods applied to the gastrointestinal tract organs as they can be confused with tissue of interest. EndoCV2020 challenges are designed to address research questions in these remits. In this paper, we present a summary of methods developed by the top 17 teams and provide an objective comparison of state-of-the-art methods and methods designed by the participants for two sub-challenges: i) artefact detection and segmentation (EAD2020), and ii) disease detection and segmentation (EDD2020). Multi-center, multi-organ, multi-class, and multi-modal clinical endoscopy datasets were compiled for both EAD2020 and EDD2020 sub-challenges. The out-of-sample generalization ability of detection algorithms was also evaluated. Whilst most teams focused on accuracy improvements, only a few methods hold credibility for clinical usability. The best performing teams provided solutions to tackle class imbalance, and variabilities in size, origin, modality and occurrences by exploring data augmentation, data fusion, and optimal class thresholding techniques. [Abstract copyright: Copyright © 2021 The Authors. Published by Elsevier B.V. All rights reserved.

SIMULATION OF THERMALLY ACTIVATED METAL FORMING PROCESS WITH MESO-SCALE CRYSTAL PLASTICITY

ABSTRACT Under thermally activated deformation conditions many engineering metals (steels, aluminum and magnesium alloys) exhibit much enhanced formability; thus, thermal forming has received increasing interests by automotive industries. The thermally activated material constitutive behaviors are not only strain dependent, but also strain rate and temperature dependent, and it is sensitive to in-situ microstructure evolution. In addition, non-steady-state deformation at a high strain rate (in the order of 10 -2 s -1 or above) introduces additional challenges in forming simulation. In this case, von Mises based macroscopic plasticity are often not sufficient to describe material behaviors with complex thermomechanical history. In this paper, the rate-dependent crystal plasticity model [1] was applied to the high temperature and high strain rate deformation that is dominated by dislocation creep. A user material subroutine was developed and used for FEA metal forming simulation using commercial ABAQUS/Dynamic code. In the simulation, material behavior was computed based on crystal plasticity at each strain increment without using von-Mises equation or a look-up table of material testing data. By inputting different slip systems or their combinations, and by matching the predicted crystallographic textures with experimentally obtained ones, the active slip systems responsible for the deformation was identified. Then, the material parameters were best fitted to the tensile curves obtained at various strain rates and temperatures. The model was applied for more complex multi-axial metal forming processes. The material behavior, along with its crystallographic texture development, was obtained and validated. As a demonstration, this paper also provides an analysis of a newly developed thermal forming process [2] with this meso-scale crystal plasticity approach. This forming process involves diameter expansion of a tubular workpiece under combined internal pressure and axial loading and at elevated temperatures. ACKNOWLEDGMENT