The present work is the ensuing part of the study on spatial and temporal variations in chemical characteristics of PM (particulate matter with aerodynamic diameter ≤ 10 μm) over Indo Gangetic Plain (IGP) of India. It focuses on the apportionment of PM sources with the application of different receptor models, i.e., principal component analysis with absolute principal component scores (PCA-APCS), UNMIX, and positive matrix factorization (PMF) on the same chemical species of PM. The main objective of this study is to perform the comparative analysis of the models, obtained mutually validated outputs and more robust results. The average PM concentration during January 2011 to December 2011 at Delhi, Varanasi, and Kolkata were 202.3 ± 74.3, 206.2 ± 77.4, and 171.5 ± 38.5 μg m, respectively. The results provided by the three models revealed quite similar source profile for all the sampling regions, with some disaccords in number of sources as well as their percent contributions. The PMF analysis resolved seven individual sources in Delhi [soil dust (SD), vehicular emissions (VE), secondary aerosols (SA), biomass burning (BB), sodium and magnesium salt (SMS), fossil fuel combustion, and industrial emissions (IE)], Varanasi [SD, VE, SA, BB, SMS, coal combustion, and IE], and Kolkata [secondary sulfate (Ssulf), secondary nitrate, SD, VE, BB, SMS, IE]. However, PCA-APCS and UNMIX models identified less number of sources (besides mixed type sources) than PMF for all the sampling sites. All models identified that VE, SA, BB, and SD were the dominant contributors of PM mass concentration over the IGP region of India.
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Elife
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Department of Neurology, University of Iowa, Iowa City, United States.
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January 2025
European Brain Research Institute (EBRI), Fondazione Rita Levi-Montalcini, Viale Regina Elena 295, 00161 Rome, Italy.
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April 2025
Research Center for Computer-aided Drug Discovery, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China.
The aberrant activation of the canonical Wnt/β-catenin signaling has been identified as a significant contributor to the pathogenesis of osteoarthritis (OA), exacerbating OA symptoms and driving OA progression. Despite its potential as a therapeutic target, clinical translation is impeded by the lack of a targeting delivery system and effective drug candidate that can modulate steady-state protein levels of β-catenin at post-translational level. Our study addresses these challenges by offering a new approach for OA treatment.
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