Paeonia lactiflora 'Hangshao' is widely cultivated in China as a traditional Chinese medicine 'Radix Paeoniae Alba'. Due to the abundant unsaturated fatty acids in its seed, it can also be regarded ...as a new oilseed plant. However, the process of the biosynthesis of unsaturated fatty acids in it has remained unknown. Therefore, transcriptome analysis is helpful to better understand the underlying molecular mechanisms.
Five main fatty acids were detected, including stearic acid, palmitic acid, oleic acid, linoleic acid and α-linolenic acid, and their absolute contents first increased and then decreased during seed development. A total of 150,156 unigenes were obtained by transcriptome sequencing. There were 15,005 unigenes annotated in the seven functional databases, including NR, NT, GO, KOG, KEGG, Swiss-Prot and InterPro. Based on the KEGG database, 1766 unigenes were annotated in the lipid metabolism. There were 4635, 12,304, and 18,291 DEGs in Group I (60 vs 30 DAF), Group II (90 vs 60 DAF) and Group III (90 vs 30 DAF), respectively. A total of 1480 DEGs were detected in the intersection of the three groups. In 14 KEGG pathways of lipid metabolism, 503 DEGs were found, belonging to 111 enzymes. We screened out 123 DEGs involved in fatty acid biosynthesis (39 DEGs), fatty acid elongation (33 DEGs), biosynthesis of unsaturated fatty acid (24 DEGs), TAG assembly (17 DEGs) and lipid storage (10 DEGs). Furthermore, qRT-PCR was used to analyze the expression patterns of 16 genes, including BBCP, BC, MCAT, KASIII, KASII, FATA, FATB, KCR, SAD, FAD2, FAD3, FAD7, GPAT, DGAT, OLE and CLO, most of which showed the highest expression at 45 DAF, except for DGAT, OLE and CLO, which showed the highest expression at 75 DAF.
We predicted that MCAT, KASIII, FATA, SAD, FAD2, FAD3, DGAT and OLE were the key genes in the unsaturated fatty acid biosynthesis and oil accumulation in herbaceous peony seed. This study provides the first comprehensive genomic resources characterizing herbaceous peony seed gene expression at the transcriptional level. These data lay the foundation for elucidating the molecular mechanisms of fatty acid biosynthesis and oil accumulation for herbaceous peony.
Water is the basis for human survival and growth, and it holds great importance for ecological and environmental protection. The Hindu Kush Himalaya (HKH) is known as the “Water Tower of Asia”, where ...water influences changes in the global water cycle and ecosystem. It is thus very important to efficiently measure the status of water in this region and to monitor its changes; with the development of satellite-borne sensors, water surface extraction based on remote sensing images has become an important method through which to do so, and one of the most advanced and accurate methods for water surface extraction involves the use of deep learning networks. We designed a network based on the state-of-the-art Vision Transformer to automatically extract the water surface in the HKH region; however, in this region, terrain shadows are often misclassified as water surfaces during extraction due to their spectral similarity. Therefore, we adjusted the training dataset in different ways to improve the accuracy of water surface extraction and explored whether these methods help to reduce the interference of terrain shadows. Our experimental results show that, based on the designed network, adding terrain shadow samples can significantly enhance the accuracy of water surface extraction in high mountainous areas, such as the HKH region, while adding terrain data does not reduce the interference from terrain shadows. We obtained the water surface extraction results in the HKH region in 2021, with the network and training datasets containing both water surface and terrain shadows. By comparing these results with the data products of Global Surface Water, it was shown that our water surface extraction results are highly accurate and the extracted water surface boundaries are finer, which strongly confirmed the applicability and advantages of the proposed water surface extraction approach in a wide range of complex surface environments.
Summary
Genome structural variation (SV) contributes strongly to trait variation in eukaryotic species and may have an even higher functional significance than single‐nucleotide polymorphism (SNP). ...In recent years, there have been a number of studies associating large chromosomal scale SV ranging from hundreds of kilobases all the way up to a few megabases to key agronomic traits in plant genomes. However, there have been little or no efforts towards cataloguing small‐ (30–10 000 bp) to mid‐scale (10 000–30 000 bp) SV and their impact on evolution and adaptation‐related traits in plants. This might be attributed to complex and highly duplicated nature of plant genomes, which makes them difficult to assess using high‐throughput genome screening methods. Here, we describe how long‐read sequencing technologies can overcome this problem, revealing a surprisingly high level of widespread, small‐ to mid‐scale SV in a major allopolyploid crop species, Brassica napus. We found that up to 10% of all genes were affected by small‐ to mid‐scale SV events. Nearly half of these SV events ranged between 100 bp and 1000 bp, which makes them challenging to detect using short‐read Illumina sequencing. Examples demonstrating the contribution of such SV towards eco‐geographical adaptation and disease resistance in oilseed rape suggest that revisiting complex plant genomes using medium‐coverage long‐read sequencing might reveal unexpected levels of functional gene variation, with major implications for trait regulation and crop improvement.
Blood-brain barrier (BBB) dysfunction causing edema and hemorrhagic transformation is one of the pathophysiological characteristics of stroke. Protection of BBB integrity has shown great potential in ...improving stroke outcome. Here, we assessed the efficacy of exosomes extracted from healthy rat serum in protection against ischemic stroke
and
. Exosomes were isolated by gradient centrifugation and ultracentrifugation and exosomes were characterized by transmission electron microscopy (TEM) and nanoparticle tracking video microscope. Exosomes were applied to middle cerebral artery occlusion (MCAO) rats or brain microvascular endothelial cell line (bEnd.3) subjected to oxygen-glucose deprivation (OGD) injury. Serum-derived exosomes were injected intravenously into adult male rats 2 h after transient MCAO. Infarct volume and gross cognitive function were assessed 24 h after reperfusion. Poststroke rats treated with serum-derived exosomes exhibited significantly reduced infarct volumes and enhanced neurological function. Apoptosis was assessed via terminal deoxynucleotidyl transferase (TdT)-mediated dUTP nick-end labeling (TUNEL) staining and the expression of B-cell lymphoma-2 (Bcl-2), Bax, and cleaved caspase-3 24 h after injury. Our data showed that serum exosomes treatment strikingly decreased TUNEL
cells in the striatum, enhanced the ratio of Bcl-2 to Bax, and inhibited cleaved caspase-3 production in MCAO rats and OGD/reoxygenation insulted bEnd.3 cells. Under the consistent treatment, the expression of microtubule-associated protein 1 light chain 3B-II (LC3B-II), LC3B-I, and Sequestosome-1 (SQSTM1)/p62 was detected by Western blotting. Autolysosomes were observed via TEM. We found that serum exosomes reversed the ratio of LC3B-II to LC3B-I, prevented SQSTM1/p62 degradation, autolysosome formation, and autophagic flux. Together, these results indicated that exosomes isolated from healthy serum provided neuroprotection against experimental stroke partially via inhibition of endothelial cell apoptosis and autophagy-mediated BBB breakdown. Intravenous serum-derived exosome treatment may, therefore, provide a novel clinical therapeutic strategy for ischemic stroke.
Herein, we propose a metabolic d‐amino acid‐based labeling and in situ hybridization‐facilitated (MeDabLISH) strategy for the quantitative analysis of the indigenous metabolic status of gut bacteria. ...The fluorescent d‐amino acid (FDAA)‐based labeling intensities of bacteria were found to highly correlate with their temporal and steady‐state metabolic status. Then, after taxonomic identification of bacterial genera in the in vivo FDAA‐labeled mouse gut microbiota, by corresponding fluorescence in situ hybridization (FISH) probes, the metabolic activities of different gut bacterial genera are quantified by flow cytometry, using FISH signals to differentiate genera and FDAA signals to indicate their basal metabolic levels. It was found that Gram‐negative genera in the mouse microbiota have stronger metabolic activities during the daytime, and Gram‐positive genera have higher activities at the night. Our strategy will be instrumental in deepening our understanding of the highly complex microbiota.
Gut sensing: The indigenous metabolic status of mouse gut microbiota is quantified by flow cytometry using the signal from fluorescent d‐amino acid‐based in vivo labeling as the indicator of bacterial metabolic activities, and signals from fluorescence in situ hybridization to indicate their taxonomic identification.
Mutations within the
gene, which encodes a key postsynaptic density (PSD) protein at glutamatergic synapses, contribute to the genetic etiology of defined autism spectrum disorders (ASDs), including ...Phelan-McDermid syndrome (PMS) and intellectual disabilities (ID). Although there are a series of genetic mouse models to study
gene in ASDs, there are few rat models with species-specific advantages. In this study, we established and characterized a novel rat model with a deletion spanning exons 11-21 of
, leading to a complete loss of the major SHANK3 isoforms. Synaptic function and plasticity of
-deficient rats were impaired detected by biochemical and electrophysiological analyses.
-depleted rats showed impaired social memory but not impaired social interaction behaviors. In addition, impaired learning and memory, increased anxiety-like behavior, increased mechanical pain threshold and decreased thermal sensation were observed in
-deficient rats. It is worth to note that
-deficient rats had nearly normal levels of the endogenous social neurohormones oxytocin (OXT) and arginine-vasopressin (AVP). This new rat model will help to further investigate the etiology and assess potential therapeutic target and strategy for
-related neurodevelopmental disorders.
The integrity and permeability of the intestinal epithelial barrier are important indicators of intestinal health. Impaired intestinal epithelial barrier function and increased intestinal ...permeability are closely linked to the onset and progression of various intestinal diseases. Sinapic acid (SA) is a phenolic acid that has anti-inflammatory, antihyperglycemic, and antioxidant activities; meanwhile, it is also effective in the protection of inflammatory bowel disease (IBD), but the specific mechanisms remain unclear. Here, we evaluated the anti-inflammatory of SA and investigated its potential therapeutic activity in LPS-induced intestinal epithelial barrier and tight junction (TJ) protein dysfunction. SA improved cell viability; attenuated epithelial permeability; restored the protein and mRNA expression of claudin-1, ZO-1, and occludin; and reversed the redistribution of the ZO-1 and claudin-1 proteins in LPS-treated Caco-2 cells. Moreover, SA reduced the inflammatory response by downregulating the activation of the TLR4/NF-κB pathway and attenuated LPS-induced intestinal barrier dysfunction by decreasing the activation of the MLCK/MLC pathway. This study demonstrated that SA has strong anti-inflammatory activity and can alleviate the occurrence of high intercellular permeability in Caco-2 cells exposed to LPS.
Scope
Recently, casein glycomacropeptide (GMP)‐derived peptide was found to possess potent antioxidant and anti‐inflammatory activities. In this study, the improvement effects and underlying ...molecular mechanisms of GMP‐derived peptide on hepatic insulin resistance were investigated.
Methods and results
The peptide IPPKKNQDKTE was identified from GMP papain hydrolysates by LC‐ESI‐MS/MS. Effects of IPPKKNQDKTE on glucose metabolism and expression levels of the hepatic insulin signaling proteins in high glucose‐induced insulin‐resistant HepG2 cells were evaluated. Results showed that IPPKKNQDKTE dose‐dependently increased glucose uptake and intracellular glycogen in insulin‐resistant HepG2 cells without affecting cell viability. IPPKKNQDKTE increased the phosphorylation of Akt and GSK3β and decreased the expression levels of p‐GS, G6Pase and PEPCK. These IPPKKNQDKTE‐mediated protection effects were reversed by PI3K/Akt inhibitor LY294002, showing the mediatory role of PI3K/Akt. Moreover, treatment with IPPKKNQDKTE reduced IRS‐1 Ser307 phosphorylation and increased phosphorylation of AMPK. Knockdown AMPK using siRNA in HepG2 cells increased Ser307 phosphorylation of IRS‐1 and reduced Akt phosphorylation in IPPKKNQDKTE‐treated insulin‐resistant cells.
Conclusion
IPPKKNQDKTE prevents high glucose‐induced insulin resistance in HepG2 cells by modulating the IRS‐1/PI3K/Akt signaling pathway through AMPK activation, indicating that IPPKKNQDKTE plays a potential role in the prevention and treatment of hepatic insulin resistance and type 2 diabetes.
The casein glycomacropeptide‐derived peptide IPPKKNQDKTE improved high glucose‐induced insulin resistance in HepG2 cells via activation of the AMPK/PI3K/Akt signaling pathway. Red solid line arrows represent changes in response to high glucose; Blue dotted line arrows represent changes in high glucose‐stimulated cells receiving peptide intervention.
The brown adipose tissue (BAT) is a target for treating obesity. BAT losses thermogenic capacity and gains a "white adipose tissue-like" phenotype ("BAT whitening") under thermoneutral environments, ...which is a potential factor causing a low curative effect in BAT-related obesity treatments. Circular RNAs (circRNAs) and long non-coding RNAs (lncRNAs) can act as competing endogenous RNAs (ceRNA) to mRNAs and function in various processes by sponging shared microRNAs (miRNAs). However, the roles of circRNA- and lncRNA-related ceRNA networks in regulating BAT whitening remain litter known.
In this study, BATs were collected from rabbits at day0 (D0), D15, D85, and 2 years (Y2). MiRNA-seq was performed to investigate miRNA changes during BAT whitening. Then, a combined analysis of circRNA-seq and whole-transcriptome sequencing was used for circRNA assembly and quantification during BAT whitening. Our data showed that 1187 miRNAs and 6204 circRNAs were expressed in the samples, and many of which were identified as significantly changed during BAT whitening. Target prediction showed that D0-selective miRNAs were significantly enriched in the Ras, MAPK, and PI3K-Akt signaling pathways, and Y2-selective miRNAs were predicted to be involved in cell proliferation. The cyclization of several circRNAs could form novel response elements of key thermogenesis miRNAs at the back-splicing junction (BSJ) sites, and in combination with a dual-luciferase reporter assay confirmed the binding between the BSJ site of novel_circ_0013792 and ocu-miR-378-5p. CircRNAs and lncRNAs have high cooperativity in sponging miRNAs during BAT whitening. Both circRNA-miRNA-mRNA and lncRNA-miRNA-mRNA triple networks were significantly involved in immune response-associated biological processes. The D15-selective circRNA might promote BAT whitening by increasing the expression of IDH2. The Y2-selective circRNA-related ceRNA network and lncRNA-related ceRNA network might regulate the formation of the WAT-like phenotype of BAT via MAPK and Ras signaling pathways, respectively.
Our work systematically revealed ceRNA networks during BAT whitening in rabbits and might provide new insight into BAT-based obesity treatments.
With the development of earth observation technologies, the acquired remote sensing images are increasing dramatically, and a new era of big data in remote sensing is coming. How to effectively mine ...these massive volumes of remote sensing data are new challenges. Deep learning provides a new approach for analyzing these remote sensing data. As one of the deep learning models, convolutional neural networks (CNNs) can directly extract features from massive amounts of imagery data and is good at exploiting semantic features of imagery data. CNNs have achieved remarkable success in computer vision. In recent years, quite a few researchers have studied remote sensing image classification using CNNs, and CNNs can be applied to realize rapid, economical and accurate analysis and feature extraction from remote sensing data. This paper aims to provide a survey of the current state-of-the-art application of CNN-based deep learning in remote sensing image classification. We first briefly introduce the principles and characteristics of CNNs. We then survey developments and structural improvements on CNN models that make CNNs more suitable for remote sensing image classification, available datasets for remote sensing image classification, and data augmentation techniques. Then, three typical CNN application cases in remote sensing image classification: scene classification, object detection and object segmentation are presented. We also discuss the problems and challenges of CNN-based remote sensing image classification, and propose corresponding measures and suggestions. We hope that the survey can facilitate the advancement of remote sensing image classification research and help remote-sensing scientists to tackle classification tasks with the state-of-art deep learning algorithms and techniques.
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