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Lu Y, Zhou G, Huang M, Huang Y. Color Night Light Remote Sensing Images Generation Using Dual-Transformation. Sensors (Basel) 2024; 24:294. [PMID: 38203156 PMCID: PMC10781353 DOI: 10.3390/s24010294] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Revised: 12/22/2023] [Accepted: 12/30/2023] [Indexed: 01/12/2024]
Abstract
Traditional night light images are black and white with a low resolution, which has largely limited their applications in areas such as high-accuracy urban electricity consumption estimation. For this reason, this study proposes a fusion algorithm based on a dual-transformation (wavelet transform and IHS (Intensity Hue Saturation) color space transform), is proposed to generate color night light remote sensing images (color-NLRSIs). In the dual-transformation, the red and green bands of Landsat multi-spectral images and "NPP-VIIRS-like" night light remote sensing images are merged. The three bands of the multi-band image are converted into independent components by the IHS modulated wavelet transformed algorithm, which represents the main effective information of the original image. With the color space transformation of the original image to the IHS color space, the components I, H, and S of Landsat multi-spectral images are obtained, and the histogram is optimally matched, and then it is combined with a two-dimensional discrete wavelet transform. Finally, it is inverted into RGB (red, green, and blue) color images. The experimental results demonstrate the following: (1) Compared with the traditional single-fusion algorithm, the dual-transformation has the best comprehensive performance effect on the spatial resolution, detail contrast, and color information before and after fusion, so the fusion image quality is the best; (2) The fused color-NLRSIs can visualize the information of the features covered by lights at night, and the resolution of the image has been improved from 500 m to 40 m, which can more accurately analyze the light of small-scale area and the ground features covered; (3) The fused color-NLRSIs are improved in terms of their MEAN (mean value), STD (standard deviation), EN (entropy), and AG (average gradient) so that the images have better advantages in terms of detail texture, spectral characteristics, and clarity of the images. In summary, the dual-transformation algorithm has the best overall performance and the highest quality of fused color-NLRSIs.
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Affiliation(s)
- Yanling Lu
- Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin University of Technology, Guilin 541004, China;
- College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China; (M.H.); (Y.H.)
- College of Earth Sciences, Guilin University of Technology, Guilin 541004, China
| | - Guoqing Zhou
- Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin University of Technology, Guilin 541004, China;
- College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China; (M.H.); (Y.H.)
| | - Meiqi Huang
- College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China; (M.H.); (Y.H.)
| | - Yaqi Huang
- College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China; (M.H.); (Y.H.)
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Qin L, Liu Q, Zhang T, Tang X, Mo X, Liang Y, Wang X, Cao J, Huang C, Lu Y, Zhang Z, Qin J, Cai J. Association Between Combined Polymetallic Exposure and Osteoporosis. Biol Trace Elem Res 2023:10.1007/s12011-023-04002-6. [PMID: 38109003 DOI: 10.1007/s12011-023-04002-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Accepted: 12/05/2023] [Indexed: 12/19/2023]
Abstract
Combined polymetallic exposure may be an influential factor in osteoporosis. This study aimed to explore the association between polymetallic combined exposure and osteoporosis. A total of 2115 participants were included. Plasma concentrations of 22 metals were determined by inductively coupled plasma mass spectrometry. Osteoporosis was defined as a T ≤ - 2.5. The least absolute shrinkage and selection operator (LASSO) regression, binary logistics regression, and Bayesian kernel machine regression (BKMR) model were used to explore the association between plasma metals and osteoporosis. LASSO regression showed that 10 metals were associated with osteoporosis in the total population (magnesium, calcium, manganese, nickel, cobalt, arsenic, selenium, rubidium, cadmium, aluminum) and women (magnesium, calcium, molybdenum, nickel, cobalt, arsenic, selenium, rubidium, cadmium, aluminum), and four metals associated with men (magnesium, cobalt, aluminum, iron). Logistics regression showed that in total population, magnesium (ORQ3 = 0.653, 95% CI = 0.446-0.954) was negatively correlated with osteoporosis, while aluminum (ORQ2 = 1.569, 95% CI = 1.095-2.248, ORQ4 = 1.616, 95% CI = 1.109-2.354) and cadmium (ORQ4 = 1.989, 95% CI = 1.379-2.870) were positively correlated; in women, magnesium (ORQ3 = 0.579, 95% CI = 0.379-0.883) was negatively correlated with osteoporosis, while aluminum (ORQ2 = 1.563, 95% CI = 1.051-2.326, ORQ4 = 1.543, 95% CI = 1.024-2.326) and cadmium (ORQ3 = 1.482, 95% CI = 1.003-2.191, ORQ4 = 1.740, 95% CI = 1.167-2.596) were positively correlated. BKMR model showed that combined polymetallic exposure had an overall positive effect on osteoporosis, magnesium was negatively associated with osteoporosis, and cadmium, selenium, and aluminum were positively associated with osteoporosis. Metal mixtures in plasma were associated with osteoporosis risk. Magnesium may reduce the risk of osteoporosis, while cadmium, selenium, and aluminum may increase the risk of osteoporosis. Future studies needed to explore correlations and mechanisms.
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Affiliation(s)
- Lidong Qin
- Department of Environmental and Occupational Health, School of Public Health, Guangxi Medical University, Shuangyong Road 22, Nanning, 530021, Guangxi, China
| | - Qiumei Liu
- Department of Environmental and Occupational Health, School of Public Health, Guangxi Medical University, Shuangyong Road 22, Nanning, 530021, Guangxi, China
| | - Tiantian Zhang
- Department of Environmental and Occupational Health, School of Public Health, Guangxi Medical University, Shuangyong Road 22, Nanning, 530021, Guangxi, China
| | - Xu Tang
- Department of Environmental and Occupational Health, School of Public Health, Guangxi Medical University, Shuangyong Road 22, Nanning, 530021, Guangxi, China
| | - Xiaoting Mo
- Department of Environmental and Occupational Health, School of Public Health, Guangxi Medical University, Shuangyong Road 22, Nanning, 530021, Guangxi, China
| | - Yujian Liang
- Department of Environmental and Occupational Health, School of Public Health, Guangxi Medical University, Shuangyong Road 22, Nanning, 530021, Guangxi, China
| | - Xuexiu Wang
- Department of Environmental and Occupational Health, School of Public Health, Guangxi Medical University, Shuangyong Road 22, Nanning, 530021, Guangxi, China
| | - Jiejing Cao
- Department of Environmental and Occupational Health, School of Public Health, Guangxi Medical University, Shuangyong Road 22, Nanning, 530021, Guangxi, China
| | - Chuwu Huang
- Department of Environmental and Occupational Health, School of Public Health, Guangxi Medical University, Shuangyong Road 22, Nanning, 530021, Guangxi, China
| | - Yufu Lu
- Department of Environmental and Occupational Health, School of Public Health, Guangxi Medical University, Shuangyong Road 22, Nanning, 530021, Guangxi, China
| | - Zhiyong Zhang
- Department of Environmental and Occupational Health, School of Public Health, Guangxi Medical University, Shuangyong Road 22, Nanning, 530021, Guangxi, China
- Department of Environmental Health and Occupational Medicine, School of Public Health, Guilin Medical University, Guilin, China
- Guangxi Health Commission Key Laboratory of Entire Lifecycle Health and Care, Guilin Medical University, Guilin, China
| | - Jian Qin
- Department of Environmental and Occupational Health, School of Public Health, Guangxi Medical University, Shuangyong Road 22, Nanning, 530021, Guangxi, China.
- Guangxi Colleges and Universities Key Laboratory of Prevention and Control of Highly Prevalent Diseases, Guangxi Medical University, Nanning, China.
- Guangxi Key Laboratory of Environment and Health Research, Guangxi Medical University, Nanning, China.
- Key Laboratory of Longevity and Aging-Related Diseases of Chinese Ministry of Education, Guangxi Medical University, Nanning, China.
| | - Jiansheng Cai
- Department of Environmental and Occupational Health, School of Public Health, Guangxi Medical University, Shuangyong Road 22, Nanning, 530021, Guangxi, China.
- Key Laboratory of Tumor Immunology and Microenvironmental Regulation, Guilin Medical University, Huan Cheng North 2Nd Road 109, Guilin, 541004, Guangxi, China.
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Chen P, Cheng H, Zheng F, Li S, Bornhorst J, Yang B, Lee KH, Ke T, Li Y, Schwerdtle T, Yang X, Bowman AB, Aschner M. BTBD9 attenuates manganese-induced oxidative stress and neurotoxicity by regulating insulin growth factor signaling pathway. Hum Mol Genet 2022; 31:2207-2222. [PMID: 35134179 PMCID: PMC9262395 DOI: 10.1093/hmg/ddac025] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Revised: 12/29/2021] [Accepted: 01/21/2022] [Indexed: 02/05/2023] Open
Abstract
Manganese (Mn) is an essential mineral, but excess exposure can cause dopaminergic neurotoxicity. Restless legs syndrome (RLS) is a common neurological disorder, but the etiology and pathology remain largely unknown. The purpose of this study was to identify the role of Mn in the regulation of an RLS genetic risk factor BTBD9, characterize the function of BTBD9 in Mn-induced oxidative stress and dopaminergic neuronal dysfunction. We found that human subjects with high blood Mn levels were associated with decreased BTBD9 mRNA levels, when compared with subjects with low blood Mn levels. In A549 cells, Mn exposure decreased BTBD9 protein levels. In Caenorhabditis elegans, loss of hpo-9 (BTBD9 homolog) resulted in more susceptibility to Mn-induced oxidative stress and mitochondrial dysfunction, as well as decreased dopamine levels and alternations of dopaminergic neuronal morphology and behavior. Overexpression of hpo-9 in mutant animals restored these defects and the protection was eliminated by mutation of the forkhead box O (FOXO). In addition, expression of hpo-9 upregulated FOXO protein levels and decreased protein kinase B levels. These results suggest that elevated Mn exposure might be an environmental risk factor for RLS. Furthermore, BTBD9 functions to alleviate Mn-induced oxidative stress and neurotoxicity via regulation of insulin/insulin-like growth factor signaling pathway.
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Affiliation(s)
- Pan Chen
- Department of Molecular Pharmacology, Albert Einstein College of Medicine, Bronx, NY 10461, USA
| | - Hong Cheng
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning 53021, China
| | - Fuli Zheng
- Department of Molecular Pharmacology, Albert Einstein College of Medicine, Bronx, NY 10461, USA
| | - Shaojun Li
- Department of Molecular Pharmacology, Albert Einstein College of Medicine, Bronx, NY 10461, USA
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning 53021, China
| | - Julia Bornhorst
- Food Chemistry, Faculty of Mathematics and Natural Sciences, University of Wuppertal, Wuppertal 42119, Germany
| | - Bobo Yang
- Department of Molecular Pharmacology, Albert Einstein College of Medicine, Bronx, NY 10461, USA
| | - Kun He Lee
- Department of Molecular Pharmacology, Albert Einstein College of Medicine, Bronx, NY 10461, USA
| | - Tao Ke
- Department of Molecular Pharmacology, Albert Einstein College of Medicine, Bronx, NY 10461, USA
| | - Yunhui Li
- Department of Molecular Pharmacology, Albert Einstein College of Medicine, Bronx, NY 10461, USA
- Key Laboratory of Environmental Medicine Engineering Ministry of Education, School of Public Health, Southeast University, Nanjing, Jiangsu 210000, China
| | - Tanja Schwerdtle
- Department of Food Chemistry, Institute of Nutritional Science, University of Potsdam, Nuthetal 14558, Germany
- TraceAge—DFG Research Group on Interactions of Essential Trace Elements in Healthy and Diseased Elderly (FOR 2558), Berlin-Potsdam-Jena 14558, Germany
| | - Xiaobo Yang
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning 53021, China
- Department of Public Health, School of Medicine, Guangxi University of Science and Technology, Liuzhou 545026, China
| | - Aaron B Bowman
- School of Health Sciences, Purdue University, West Lafayette, IN 47907, USA
| | - Michael Aschner
- Department of Molecular Pharmacology, Albert Einstein College of Medicine, Bronx, NY 10461, USA
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