Compatible solutes are a functional group of small, highly soluble organic molecules that demonstrate compatibility in high amounts with cellular metabolism. The accumulation of compatible solutes is often observed during the acclimation of organisms to adverse environmental conditions, particularly to salt and drought stress. Among cyanobacteria, sucrose, trehalose, glucosylglycerol and glycine betaine are used as major compatible solutes. Interestingly, a close correlation has been discovered between the final salt tolerance limit and the primary compatible solute in these organisms. In addition to the dominant compatible solutes, many strains accumulate mixtures of these compounds, including minor compounds such as glucosylglycerate or proline as secondary or tertiary solutes. In particular, the accumulation of sucrose and trehalose results in an increase in tolerance to general stresses such as desiccation and high temperatures. During recent years, the biochemical and molecular basis of compatible solute accumulation has been characterized using cyanobacterial model strains that comprise different salt tolerance groups. Based on these data, the distribution of genes involved in compatible solute synthesis among sequenced cyanobacterial genomes is reviewed, and thereby, the major compatible solutes and potential salt tolerance of these strains can be predicted. Knowledge regarding cyanobacterial salt tolerance is not only useful to characterize strain-specific adaptations to ecological niches, but it can also be used to generate cells with increased tolerance to adverse environmental conditions for biotechnological purposes.
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Neural Netw
December 2024
Institute of Automation, Chinese Academy of Sciences, MAIS, Beijing, 100190, China; University of Chinese Academy of Sciences, Beijing, 101408, China.
In the rapidly evolving field of deep learning, Convolutional Neural Networks (CNNs) retain their unique strengths and applicability in processing grid-structured data such as images, despite the surge of Transformer architectures. This paper explores alternatives to the standard convolution, with the objective of augmenting its feature extraction prowess while maintaining a similar parameter count. We propose innovative solutions targeting depthwise separable convolution and standard convolution, culminating in our Multi-scale Progressive Inference Convolution (MPIC).
View Article and Find Full Text PDFPhys Med Biol
January 2025
Schlegel Research Institute for Aging, University of Waterloo, 250 Laurelwood Drive, Waterloo, Ontario, N2L 3G1, CANADA.
As ultrasound-compatible flow phantoms are devised for performance testing and calibration, there is a practical need to obtain independent flow measurements for validation using a gold-standard technique such as particle image velocimetry (PIV). In this paper, we present the design of a new dual-modality flow phantom that allows ultrasound and PIV measurements to be simultaneously performed. Our phantom's tissue mimicking material is based on a novel hydrogel formula that uses propylene glycol to lower the freezing temperature of an ultrasound-compatible poly(vinyl) alcohol cryogel and, in turn, maintain the solution's optical transparency after thermocycling.
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UC Davis Alzheimer's Disease Center, Walnut Creek, CA, USA.
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January 2025
College of Food Science and Engineering, Northwest A&F University, Yangling, China.
spp. exhibit remarkable resilience to extreme environmental stresses, including thermal, acidic, desiccation, and osmotic conditions, posing significant challenges to food safety. Their thermotolerance relies on heat shock proteins (HSPs), thermotolerance genomic islands, enhanced DNA repair mechanisms, and metabolic adjustments, ensuring survival under high-temperature conditions.
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January 2025
Division of Entomology, ICAR-Indian Agricultural Research Institute, New Delhi, 110012, India.
The tomato leaf miner (TLM), Phthorimaea absoluta Meyrick, 1917 (Lepidoptera: Gelechiidae) is a destructive invasive insect that has expanded its global distribution. Rapid and accurate identification of invasive pests is essential to support subsequent management and devise control measures. To accurately diagnose P.
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