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Poor wound healing after diabetes mellitus remains a challenging problem, and its pathophysiological mechanisms have not yet been fully elucidated. Persistent bleeding, disturbed regulation of inflammation, blocked cell proliferation, susceptible infection and impaired tissue remodeling are the main features of diabetic wound healing. Conventional wound dressings, including gauze, films and bandages, have a limited function. They generally act as physical barriers and absorbers of exudates, which fail to meet the requirements of the whol diabetic wound healing process. Wounds in diabetic patients typically heal slowly and are susceptible to infection due to hyperglycemia within the wound bed. Once bacterial cells develop into biofilms, diabetic wounds will exhibit robust drug resistance. Recently, the application of stimuli-responsive hydrogels, also known as "smart hydrogels", for diabetic wound healing has attracted particular attention. The basic feature of this system is its capacities to change mechanical properties, swelling ability, hydrophilicity, permeability of biologically active molecules, etc., in response to various stimuli, including temperature, potential of hydrogen (pH), protease and other biological factors. Smart hydrogels can improve therapeutic efficacy and limit total toxicity according to the characteristics of diabetic wounds. In this review, we summarized the mechanism and application of stimuli-responsive hydrogels for diabetic wound healing. It is hoped that this work will provide some inspiration and suggestions for research in this field.

GLP-1 receptor (GLP-1R) and glucagon receptor (GCGR) are critical for the maintenance of glucose and energy homeostasis, but their roles in chronic kidney disease (CKD) are still unknown. Herein we found that the expression of GLP-1R and GCGR was lower in kidney from patients with CKD than in control individuals and was correlated with disease severity. RNA-seq analysis showed that adeno-associated viral vector serotype 9-GLP-1R or GCGR small hairpin RNA (AAV9-GLP-1R or GCGR shRNA) treatment in db/db mice exhibited more advanced diabetic nephropathy than wild-type mice. We also found that GLP-1R mainly expressed in glomeruli and GCGR expressed in both glomeruli and tubuli renales. Based on the importance of GLP-1R and GCGR in CKD, we design and report a new monomeric peptide, 1907-B, with agonism at the GLP-1R and GCGR that have more prolonged half-time than long-acting semaglutide in cynomolgus rats or monkeys (~2-3 fold) and exhibit better therapeutic contribution to CKD than best-in-class monoagonists, semaglutide or glucagon in db/db mice and unilateral ureter obstruction (UUO) mice. Various loss-of-function models, including selective pharmacological blockade and genetic knockdown, confirmed that the effects of 1907-B on improving glucose control and ameliorating the diabetic nephropathy in db/db mice were mediated through GLP-1 and glucagon signaling, whereas its action on inhibiting renal fibrosis in UUO mice was predominantly mediated through glucagon signaling. Mechanistically, 1907-B activated downstream cAMP-PKA pathway to promote mitochondrial biogenesis and bioenergetics, as well as to attenuate renal oxidative stress under chronic hyperglycemia via stimulating GLP-1R and GCGR simultaneously. Furthermore, 1907-B had crucial protection roles against inflammation via NFκB pathway and renal fibrosis via TGF-β-SMAD pathway. Thus 1907-B, via direct kidney (GCGR) and part-glomerulus (GLP-1R) effects, exerts multifactorial improvement in renal injuries and is a more effective and promising therapeutic option for the treatment of CKD.

Soil microorganisms play important roles in crop production and sustainable agricultural management. However, soil conditions and crop selection are key determining factors for soil microbial communities. This study investigated the effect of plant types and soil salinity on the microbial community of interspecific interaction zone (II) based on the sorghum/peanut intercropping system. Microbial community diversity and composition were determined through PacBio single molecule, real-time sequencing of 16S rDNA and internal transcribed spacer (ITS) genes. Results showed Proteobacteria, Bacteroidota, and Acidobacteriota to be the dominant bacterial phyla in IP, II, and IS, whereas Ascomycota, Basidiomycota, and Mucoromycota were the dominant fungal phyla. Under salt-treated soil conditions, the plants-specific response altered the composition of the microbial community (diversity and abundance). Additionally, the interspecific interactions were also helpful for maintaining the stability and ecological functions of microbial communities by restructuring the otherwise stable core microbiome. The phylogenetic structure of the bacterial community was greatly similar between IP and II while that of the fungal community was greatly similar between IP and IS; however, the phylogenetic distance between IP and IS increased remarkably upon salinity stress. Overall, salinity was a dominant factor shaping the microbial community structure, although plants could also shape the rhizosphere microenvironment by host specificity when subjected to environmental stresses. In particular, peanut still exerted a greater influence on the microbial community of the interaction zone than sorghum.

Image enhancement technology is often used to improve the quality of medical images and helps doctors or expert systems identify and diagnose diseases. This paper aimed at the characteristics of magnetic resonance imaging (MRI) with complex and difficult-to-enhance details and to propose a nonsubsampled contourlet transform- (NSCT-) based enhancement algorithm called MIE-NSCT. NSCT was used for MRI sub-band decomposition. For high-pass sub-bands, four fuzzy rules were proposed to enhance multiscale and multidirectional edge contour details from adjacent eight directions, whilst for low-pass sub-bands, a new adaptive histogram enhancement algorithm was proposed. The problem of noise amplification and loss of details during the enhancement process was solved. The algorithm was verified on the public dataset BraTS2017 and compared with other advanced methods. Experimental results showed that MIE-NSCT had obvious advantages in improving the quality of medical images, and high-quality medical images showed enhanced performance in grading tumour. MIE-NSCT is suitable for integration into an interactive expert system to provide support for the visualization of disease diagnosis.

The use of medical image synthesis with generative adversarial networks (GAN) is effective for expanding medical samples. The structural consistency between the synthesized and actual image is a key indicator of the quality of the synthesized image, and the region of interest (ROI) of the synthesized image is related to its usability, and these parameters are the two key issues in image synthesis. In this paper, the fusion-ROI patch GAN (Fproi-GAN) model was constructed by incorporating a priori regional feature based on the two-stage cycle consistency mechanism of cycleGAN. This model has improved the tissue contrast of ROI and achieved the pairwise synthesis of high-quality medical images and their corresponding ROIs. The quantitative evaluation results in two publicly available datasets, INbreast and BRATS 2017, show that the synthesized ROI images have a DICE coefficient of 0.981 ± 0.11 and a Hausdorff distance of 4.21 ± 2.84 relative to the original images. The classification experimental results show that the synthesized images can effectively assist in the training of machine learning models, improve the generalization performance of prediction models, and improve the classification accuracy by 4% and sensitivity by 5.3% compared with the cycleGAN method. Hence, the paired medical images synthesized using Fproi-GAN have high quality and structural consistency with real medical images.

Cold stress restricts peanut (Arachis hypogaea L.) growth, development, and yield. However, the specific mechanism of cold tolerance in peanut remains unknown. Here, the comparative physiological, transcriptomic, and lipidomic analyses of cold tolerant variety NH5 and cold sensitive variety FH18 at different time points of cold stress were conducted to fill this gap. Transcriptomic analysis revealed lipid metabolism including membrane lipid and fatty acid metabolism may be a significant contributor in peanut cold tolerance, and 59 cold-tolerant genes involved in lipid metabolism were identified. Lipidomic data corroborated the importance of membrane lipid remodeling and fatty acid unsaturation. It indicated that photosynthetic damage, resulted from the alteration in fluidity and integrity of photosynthetic membranes under cold stress, were mainly caused by markedly decreased monogalactosyldiacylglycerol (MGDG) levels and could be relieved by increased digalactosyldiacylglycerol (DGDG) and sulfoquinovosyldiacylglycerol (SQDG) levels. The upregulation of phosphatidate phosphatase (PAP1) and phosphatidate cytidylyltransferase (CDS1) inhibited the excessive accumulation of PA, thus may prevent the peroxidation of membrane lipids. In addition, fatty acid elongation and fatty acid β-oxidation were also worth further studied in peanut cold tolerance. Finally, we constructed a metabolic model for the regulatory mechanism of peanut cold tolerance, in which the advanced lipid metabolism system plays a central role. This study lays the foundation for deeply analyzing the molecular mechanism and realizing the genetic improvement of peanut cold tolerance.

Plants tolerate cold stress by regulating gene networks controlling cellular and physiological traits to modify growth and development. Transcription factor (TF)-directed regulation of transcription within these gene networks is key to eliciting appropriate responses. Identifying TFs related to cold tolerance contributes to cold-tolerant crop breeding. In this study, a comparative transcriptome analysis was carried out to investigate global gene expression of entire TFs in two peanut varieties with different cold-tolerant abilities. A total of 87 TF families including 2328 TF genes were identified. Among them, 445 TF genes were significantly differentially expressed in two peanut varieties under cold stress. The TF families represented by the largest numbers of differentially expressed members were bHLH (basic helix―loop―helix protein), C2H2 (Cys2/His2 zinc finger protein), ERF (ethylene-responsive factor), MYB (v-myb avian myeloblastosis viral oncogene homolog), NAC (NAM, ATAF1/2, CUC2) and WRKY TFs. Phylogenetic evolutionary analysis, temporal expression profiling, protein&ndash, protein interaction (PPI) network, and functional enrichment of differentially expressed TFs revealed the importance of plant hormone signal transduction and plant-pathogen interaction pathways and their possible mechanism in peanut cold tolerance. This study contributes to a better understanding of the complex mechanism of TFs in response to cold stress in peanut and provides valuable resources for the investigation of evolutionary history and biological functions of peanut TFs genes involved in cold tolerance.

The unclear molecular mechanism by which peanuts adapt to chilling stress limits progress in molecular breeding for peanut chilling tolerance. Here, the physiological and transcriptional differences between two genotypes with contrasting tolerance under chilling stress were compared. The inhibition of photosynthesis mainly caused by stomatal factors was a common response of peanut seedlings to chilling stress. Chilling-tolerant genotypes could inhibit the accumulation of ROS to adapt to chilling stress, and enhanced activities of CAT and APX were major causes of lower H

Early sowing has been extensively used in high-latitude areas to avoid drought stress during sowing; however, cold damage has become the key limiting factor of early sowing. To relieve cold stress, plants develop a series of physiological and biochemical changes and sophisticated molecular regulatory mechanisms. The biomembrane is the barrier that protects cells from injury as well as the primary place for sensing cold signals. Chilling tolerance is closely related to the composition, structure, and metabolic process of membrane lipids. This review focuses on membrane lipid metabolism and its molecular mechanism, as well as lipid signal transduction in peanut (Arachis hypogaea L.) under cold stress to build a foundation for explicating lipid metabolism regulation patterns and physiological and molecular response mechanisms during cold stress and to promote the genetic improvement of peanut cold tolerance.

In this work, we report a solution processed hole extraction layer (HEL) for highly efficient organic solar cells (OSCs), which is formed by CuSCN and perylene. It shows that the introduction of perylene helps to polish the interface between HEL and active layers, leading to efficient charge transport and collection, diminished recombination loss, and thereby improving the photovoltaic performance. In poly[4,8-bis(5-(2-ethylhexyl)thiophen-2-yl)benzo[1,2-b; 4,5-b′]dithiophene-2,6-diyl-alt-(4-(2-ethylhexyl)-3-fluorothieno[3,4-b]thiophene-)-2-carboxylate-2-6-diyl)]:[6,6]-phenyl C71-butyric acid methyl ester (PTB7-Th:PC71BM) based OSCs, over 9% enhancement of power conversion efficiency (PCE) is obtained in the cells using bilayer CuSCN/perylene as HEL compared with that of the reference cell using pure CuSCN as HEL. The advantage of bilayer CuSCN/perylene HEL is also confirmed in nonfullerene system. An improved PCE is also obtained after application of perylene in nonfullerene system based cell. Furthermore, superior air stability has been observed in CuSCN and CuSCN/perylene HEL based cells. The use of a bilayer CuSCN/perylene HEL proves a potential approach to obtain efficient and stable OSCs.

Artificial tongue systems are multisensory devices which are highly desirable for the analysis and recognition of complicated composition samples. Herein, a low-cost and simple colorimetric sensor array for identification and quantification of proteins were reported. Using prophyrin, porphyrin derivatives (mainly metalloporphyrins) and chemically responsive dyes as the sensing elements, the developed sensor array of artificial tongue showed a unique pattern of colorific change upon its exposure to proteins. The composite pattern for each sample was subjected to principal component analysis (PCA), thus providing a clustering map for more practical visualization. All the pure and mixed proteins, as well as denatured proteins, gave distinct patterns, thus resulting in their unambiguous identification. The PCA analysis also suggested that the unique pattern of colorific change may be due to the change of protein conformation and local environmental pH. These results demonstrate that the developed colorimetric artificial tongue system is an excellent sensing platform for identification and quantitative analysis of protein samples.