Characterization of plant growth-promoting, antifungal, and enzymatic properties of beneficial bacterial strains associated with pulses rhizosphere from Bundelkhand region of India.

The present study was conducted to characterize the native plant growth-promoting rhizobacteria (PGPRs) from the pulse rhizosphere of the Bundelkhand region of India. Twenty-four bacterial isolates belonging to nineteen species (B. amyloliquefaciens, B. subtilis, B. tequilensis, B. safensis, B. haynesii, E. soli, E. cloacae, A. calcoaceticus, B. valezensis, S. macrescens, P. aeruginosa, P. fluorescens, P. guariconensis, B. megaterium, C. lapagei, P. putida, K. aerogenes, B. cereus, and B. altitudinis) were categorized and evaluated for their plant growth-promoting potential, antifungal properties, and enzymatic activities to identify the most potential strain for commercialization and wider application in pulse crops. Phylogenetic identification was done on the basis of 16 s rRNA analysis. Among the 24 isolates, 12 bacterial strains were gram positive, and 12 were gram negative. Among the tested 24 isolates, IIPRAJCP-6 (Bacillus amyloliquefaciens), IIPRDSCP-1 (Bacillus subtilis), IIPRDSCP-10 (Bacillus tequilensis), IIPRRLUCP-5 (Bacillus safensis), IIPRCDCP-2 (Bacillus subtilis), IIPRAMCP-1 (Bacillus safensis), IIPRMKCP-10 (Bacillus haynesii), IIPRANPP-3 (Bacillus amyloliquefaciens), IIPRKAPP-5 (Enterobacter soli), IIPRAJCP-2 (Enterobacter cloacae), IIPRDSCP-11 (Acinetobacter calcoaceticus), IIPRDSCP-9 (Bacillus valezensis), IIPRMKCP-3 (Seratia macrescens), IIPRMKCP-1 (Pseudomonas aeruginosa), IIPRCKPP-3 (Pseudomonas fluorescens), IIPRMKCP-9 (Pseudomonas guariconensis), IIPRMKCP-8 (Bacillus megatirium), IIPRMWCP-9 (Cedecea lapagei), IIPRKUCP-10 (Pseudomonas putida), IIPRAMCP-4 (Klebsiella aerogenes), IIPRCKPP-7 (Enterobacter cloacae), IIPRAMCP-5 (Bacillus cereus), IIPRSHEP-6 (Bacillus subtilis), IIPRRSBa89 (Bacillus altitudinis) bacterial isolates, IIPRMKCP-9, IIPRAJCP-6, IIPRMKCP-10, IIPRAMCP-5, IIPRSHEP-6, and IIPRMKCP-3 showed the maximum antagonistic activity against Fusarium oxysporum f. sp. ciceris (FOC), Fusarium oxysporum f. sp. lentis (FOL), and Fusarium udum (FU) causing wilt disease of chickpea, lentil, and pigeonpea, respectively, and maximum plant growth-promoting enzyme (phosphatase), plant growth hormone (IAA), and siderophore production show promising results under greenhouse conditions. This study is the first report of bacterial diversity in the pulse-growing region of India.

Phase determination in dual phase steels via HREBSD-based tetragonality mapping.

Electron Backscatter Diffraction (EBSD) is a widely used approach for characterising the microstructure of various materials. However, it is difficult to accurately distinguish similar (body centred cubic and body centred tetragonal, with small tetragonality) phases in steels using standard EBSD software. One method to tackle the problem of phase distinction is to measure the tetragonality of the phases, which can be done using simulated patterns and cross-correlation techniques to detect distortion away from a perfectly cubic crystal lattice. However, small errors in the determination of microscope geometry (the so-called pattern or projection centre) can cause significant errors in tetragonality measurement and lead to erroneous results. This paper utilises a new approach for accurate pattern centre determination via a strain minimisation routine across a large number of grains in dual phase steels. Tetragonality maps are then produced and used to identify phase and estimate local carbon content. The technique is implemented using both kinetically simulated and dynamically simulated patterns to determine their relative accuracy. Tetragonality maps, and subsequent phase maps, based on dynamically simulated patterns in a point-by-point and grain average comparison are found to consistently produce more precise and accurate results, with close to 90% accuracy for grain phase identification, when compared with an image-quality identification method. The error in tetragonality measurements appears to be of the order of 1%, thus producing a commensurate ∼0.2% error in carbon content estimation. Such an error makes the technique unsuitable for estimation of total carbon content of most commercial steels, which often have carbon levels below 0.1%. However, even in the DP steel for this study (0.1 wt.% carbon) it can be used to map carbon in regions with higher accumulation (such as in martensite with nonhomogeneous carbon content). LAY DESCRIPTION: Electron Backscatter Diffraction (EBSD) is a widely used approach for characterising the microstructure of various materials. However, it is difficult to accurately distinguish similar (BCC and BCT) phases in steels using standard EBSD software due to the small difference in crystal structure. One method to tackle the problem of phase distinction is to measure the tetragonality, or apparent 'strain' in the crystal lattice, of the phases. This can be done by comparing experimental EBSD patterns with simulated patterns via cross-correlation techniques, to detect distortion away from a perfectly cubic crystal lattice. However, small errors in the determination of microscope geometry (the so-called pattern or projection centre) can cause significant errors in tetragonality measurement and lead to erroneous results. This paper utilises a new approach for accurate pattern centre determination via a strain minimisation routine across a large number of grains in dual phase steels. Tetragonality maps are then produced and used to identify phase and estimate local carbon content. The technique is implemented using both simple kinetically simulated and more complex dynamically simulated patterns to determine their relative accuracy. Tetragonality maps, and subsequent phase maps, based on dynamically simulated patterns in a point-by-point and grain average comparison are found to consistently produce more precise and accurate results, with close to 90% accuracy for grain phase identification, when compared with an image-quality identification method. The error in tetragonality measurements appears to be of the order of 1%, thus producing a commensurate error in carbon content estimation. Such an error makes an estimate of total carbon content particularly unsuitable for low carbon steels; although maps of local carbon content may still be revealing. Application of the method developed in this paper will lead to better understanding of the complex microstructures of steels, and the potential to design microstructures that deliver higher strength and ductility for common applications, such as vehicle components.

Digital Image Correlation of Forescatter Detector Images for Simultaneous Strain and Orientation Mapping.

Improved plasticity models require simultaneous experimental local strain and microstructural evolution data. Microscopy tools, such as electron backscatter diffraction (EBSD), that can monitor transformation at the relevant length-scale, are often incompatible with digital image correlation (DIC) techniques required to determine local deformation. In this paper, the viability of forescatter detector (FSD) images as the basis for the DIC study is investigated. Standard FSD and an integrated EBSD/FSD approach (Pattern Region of Interest Analysis System: PRIAS™) are analyzed. Simultaneous strain and microstructure maps are obtained for tensile deformation of Q&P 1180 steel up to ~14% strain. Tests on an undeformed sample that is simply shifted indicate a standard deviation of error in strain of around 0.4% without additional complications from a deformed surface. The method resolves strain bands at ~2 µm spacing but does not provide significant sub-grain strain resolution. Similar resolution was obtained for mechanically polished and electropolished samples, despite electropolished surfaces presenting a smoother, simpler topography. While the resolution of the PRIAS approach depends upon the EBSD step size, the 80 nm step size used provides seemingly similar resolution as 8,000× (22.7 nm) FSD images. Surface feature evolution prevents DIC analysis across large strain steps (>6% strain), but restarting DIC, using an FSD reference image from an interim strain step, allows reasonable DIC across the stress­strain curve. Furthermore, the data are obtained easily and provide complementary information for EBSD analysis.

Chronic hyperinsulinemia reduces insulin sensitivity and metabolic functions of brown adipocyte.

The growing pandemics of diabetes have become a real threat to world economy. Hyperinsulinemia and insulin resistance are closely associated with the pathophysiology of type 2 diabetes. In pretext of brown adipocytes being considered as the therapeutic strategy for the treatment of obesity and insulin resistance, we have tried to understand the effect of hyperinsulinemia on brown adipocyte function. We here with for the first time report that hyperinsulinemia-induced insulin resistance in brown adipocyte is also accompanied with reduced insulin sensitivity and brown adipocyte characteristics. CI treatment decreased expression of brown adipocyte-specific markers (such as PRDM16, PGC1α, and UCP1) and mitochondrial content as well as activity. CI-treated brown adipocytes showed drastic decrease in oxygen consumption rate (OCR) and spare respiratory capacity. Morphological study indicates increased accumulation of lipid droplets in CI-treated brown adipocytes. We have further validated these findings in vivo in C57BL/6 mice implanted with mini-osmotic insulin pump for 8weeks. CI treatment in mice leads to increased body weight gain, fat mass and impaired glucose intolerance with reduced energy expenditure and insulin sensitivity. CI-treated mice showed decreased BAT characteristics and function. We also observed increased inflammation and ER stress markers in BAT of CI-treated animals. The above results conclude that hyperinsulinemia has deleterious effect on brown adipocyte function, making it susceptible to insulin resistance. Thus, the above findings have greater implication in designing approaches for the treatment of insulin resistance and diabetes via recruitment of brown adipocytes.