Improved Narrow Water Extraction Using a Morphological Linear Enhancement Technique

An improved water extraction method using a morphological linear enhancement technique is proposed to improve the delineation of narrow water features for the modified normalized difference water index (MNDWI) derived from remote sensing images. This method introduces a morphological white top-hat (WTH) transforming operation on the MNDWI to extract multi-scale and multidirectional differential morphological profiles and constructs a morphological narrow water index (MNWI). The MNWI can effectively enhance the local contrast of linear objects, allowing narrow water bodies to be easily separated from mountain shadows and other features. Furthermore, to accurately delineate surface water bodies, a dual-threshold segmentation method was also developed by combining an empirical threshold segmentation with the MNDWI for wide water bodies and an automatic threshold segmentation with the MNWI for narrow water bodies. This method was validated using three experimental datasets, which were taken from two different Landsat images. Our results demonstrate that narrow water bodies can be sufficiently identified, with an overall accuracy of over 90%. Most narrow streams or rivers keep a continuous shape in space, and the boundaries of the water bodies are accurately delineated as compared with the MNDWI method. Finally, the proposed method was used to extract the entire inland surface water of Fujian province, China

Proteomic analysis of spinal cord tissue in a rat model of cancer-induced bone pain

BackgroundCancer-induced bone pain (CIBP) is a moderate to severe pain and seriously affects patients’ quality of life. Spinal cord plays critical roles in pain generation and maintenance. Identifying differentially expressed proteins (DEPs) in spinal cord is essential to elucidate the mechanisms of cancer pain.MethodsCIBP rat model was established by the intratibial inoculation of MRMT-1 cells. Positron emission tomography (PET) scan and transmission electron microscopy (TEM) were used to measure the stats of spinal cord in rats. Label free Liquid Chromatography with tandem mass spectrometry (LC-MS-MS) were used to analyze the whole proteins from the lumbar spinal cord. Differentially expressed proteins (DEPs) were performed using Gene Ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis, and verified using Western blot and immunofluorescence assay.ResultsIn the current study, CIBP rats exhibited bone damage, spontaneous pain, mechanical hyperalgesia, and impaired motor ability. In spinal cord, an hypermetabolism and functional abnormality were revealed on CIBP rats. An increase of synaptic vesicles density in active zone and a disruption of mitochondrial structure in spinal cord of CIBP rats were observed. Meanwhile, 422 DEPs, consisting of 167 up-regulated and 255 down-regulated proteins, were identified among total 1539 proteins. GO enrichment analysis indicated that the DEPs were mainly involved in catabolic process, synaptic function, and enzymic activity. KEGG pathway enrichment analysis indicated a series of pathways, including nervous system disease, hormonal signaling pathways and amino acid metabolism, were involved. Expression change of synaptic and mitochondrial related protein, such as complexin 1 (CPLX1), synaptosomal-associated protein 25 (SNAP25), synaptotagmin 1 (SYT1), aldehyde dehydrogenase isoform 1B1 (ALDH1B1), Glycine amidinotransferase (GATM) and NADH:ubiquinone oxidoreductase subunit A11 (NDUFA11), were further validated using immunofluorescence and Western blot analysis.ConclusionThis study provides valuable information for understanding the mechanisms of CIBP, and supplies potential therapeutic targets for cancer pain

Forest Burned Area Detection Using a Novel Spectral Index Based on Multi-Objective Optimization

Forest fires cause environmental and economic damage, destroy large areas of land and displace entire communities. Accurate extraction of fire-affected areas is of vital importance to support post-fire management strategies and account for the environmental impact of fires. In this paper, an analytical burned area index, called ABAI, was proposed to map burned areas from the newly launched Sentinel-2 images. The innovation of this method is to separate the fire scars from other typical land covers by formulating different objective functions, which involved three main components: First, spectral differences between the burned land and other land covers were characterized by analyzing the spectral features of the existing burned area indices. Then, for each type of land cover, we formed an objective function by linear combination of bands with the values of band ratios. Second, all the objective functions and possible constraints were formulated as a multi-objective optimization problem, and then it was solved using a linear programming approach. Finally, the ABAI spectral index was achieved with the optimizing coefficients derived from the multi-objective problem. To validate the effectiveness of the proposed spectral index, three experimental datasets, clipped from Sentinel-2 images at different places, were tested and compared with baseline indices, such as normalized burned area (NBR) and burned area index (BAI) methods. Experimental results demonstrated that the injection of a green band to the spectral index has led to good applicability in burned area detection, where the ABAI can avoid most of the confusion presented by shadows or shallow water. Compared to other burned area indices, the proposed ABAI achieved the best classification accuracy, with the overall accuracy being over 90%. Visually, our approach significantly outperforms other spectral indexed methods, especially in confused areas covered by water bodies and shadows

Optimization of the Natural Gas Purification Process Based on Exergy Analysis

This study is aimed at carrying out investigations on a domestic gas field, located in Yanchang, China, with a view to optimize the natural gas purification process. The main objectives of this work are (i) to reduce the natural gas purification system’s energy consumption and (ii) improve the existing purification levels. Process simulations were carried out using Aspen Plus™ software, and a comprehensive technical and economic analysis was carried out. The single-factor sensitivity analysis method was used to determine the parameters of absorption, such as the reflux ratio and number of stages. The heat transfer process was analyzed using the energy-saving method of the energy system, and a modified process was recommended. The optimization results show that the recommended system has better purification performance, the comprehensive energy consumption is effectively reduced, and the energy efficiency is improved by 9%

Table5_Identification of human placenta-derived circular RNAs and autophagy related circRNA-miRNA-mRNA regulatory network in gestational diabetes mellitus.XLS

Gestational diabetes mellitus (GDM) is a metabolic and reproductive disease with serious risks and adverse health effects. However, the pathophysiological mechanism of GDM, especially the roles of circRNAs in its pathogenesis, is largely unknown. The objective of this study was to identify and investigate the roles of circRNAs in GDM. In the current study, placental circRNA expression profiles of normal controls and GDM patients were analyzed using high-throughput sequencing. Bioinformatics analysis identified a total of 4,955 circRNAs, of which 37 circRNAs were significantly deregulated in GDM placentas compared with NC placentas. GO and KEGG enrichment analyses demonstrated that metabolic process-associated terms and metabolic pathways that may be related to GDM were significantly enriched. The biological characteristics of placenta-derived circRNAs, such as their stability and RNase R resistance, were also validated Bioinformatics prediction. Moreover, we constructed the autophagy related circRNA-miRNA-mRNA regulatory network and further functional analysis revealed that the circCDH2–miR-33b-3p–ULK1 axis may be associated with autophagy in the placentas of GDM patients. Our study indicates that aberrant expression of circRNAs may play roles in autophagy in GDM placentas, providing new insights into GDM.</p

Table6_Identification of human placenta-derived circular RNAs and autophagy related circRNA-miRNA-mRNA regulatory network in gestational diabetes mellitus.XLSX

Gestational diabetes mellitus (GDM) is a metabolic and reproductive disease with serious risks and adverse health effects. However, the pathophysiological mechanism of GDM, especially the roles of circRNAs in its pathogenesis, is largely unknown. The objective of this study was to identify and investigate the roles of circRNAs in GDM. In the current study, placental circRNA expression profiles of normal controls and GDM patients were analyzed using high-throughput sequencing. Bioinformatics analysis identified a total of 4,955 circRNAs, of which 37 circRNAs were significantly deregulated in GDM placentas compared with NC placentas. GO and KEGG enrichment analyses demonstrated that metabolic process-associated terms and metabolic pathways that may be related to GDM were significantly enriched. The biological characteristics of placenta-derived circRNAs, such as their stability and RNase R resistance, were also validated Bioinformatics prediction. Moreover, we constructed the autophagy related circRNA-miRNA-mRNA regulatory network and further functional analysis revealed that the circCDH2–miR-33b-3p–ULK1 axis may be associated with autophagy in the placentas of GDM patients. Our study indicates that aberrant expression of circRNAs may play roles in autophagy in GDM placentas, providing new insights into GDM.</p

Table1_Identification of human placenta-derived circular RNAs and autophagy related circRNA-miRNA-mRNA regulatory network in gestational diabetes mellitus.DOCX

Gestational diabetes mellitus (GDM) is a metabolic and reproductive disease with serious risks and adverse health effects. However, the pathophysiological mechanism of GDM, especially the roles of circRNAs in its pathogenesis, is largely unknown. The objective of this study was to identify and investigate the roles of circRNAs in GDM. In the current study, placental circRNA expression profiles of normal controls and GDM patients were analyzed using high-throughput sequencing. Bioinformatics analysis identified a total of 4,955 circRNAs, of which 37 circRNAs were significantly deregulated in GDM placentas compared with NC placentas. GO and KEGG enrichment analyses demonstrated that metabolic process-associated terms and metabolic pathways that may be related to GDM were significantly enriched. The biological characteristics of placenta-derived circRNAs, such as their stability and RNase R resistance, were also validated Bioinformatics prediction. Moreover, we constructed the autophagy related circRNA-miRNA-mRNA regulatory network and further functional analysis revealed that the circCDH2–miR-33b-3p–ULK1 axis may be associated with autophagy in the placentas of GDM patients. Our study indicates that aberrant expression of circRNAs may play roles in autophagy in GDM placentas, providing new insights into GDM.</p

Table8_Identification of human placenta-derived circular RNAs and autophagy related circRNA-miRNA-mRNA regulatory network in gestational diabetes mellitus.docx

Gestational diabetes mellitus (GDM) is a metabolic and reproductive disease with serious risks and adverse health effects. However, the pathophysiological mechanism of GDM, especially the roles of circRNAs in its pathogenesis, is largely unknown. The objective of this study was to identify and investigate the roles of circRNAs in GDM. In the current study, placental circRNA expression profiles of normal controls and GDM patients were analyzed using high-throughput sequencing. Bioinformatics analysis identified a total of 4,955 circRNAs, of which 37 circRNAs were significantly deregulated in GDM placentas compared with NC placentas. GO and KEGG enrichment analyses demonstrated that metabolic process-associated terms and metabolic pathways that may be related to GDM were significantly enriched. The biological characteristics of placenta-derived circRNAs, such as their stability and RNase R resistance, were also validated Bioinformatics prediction. Moreover, we constructed the autophagy related circRNA-miRNA-mRNA regulatory network and further functional analysis revealed that the circCDH2–miR-33b-3p–ULK1 axis may be associated with autophagy in the placentas of GDM patients. Our study indicates that aberrant expression of circRNAs may play roles in autophagy in GDM placentas, providing new insights into GDM.</p