During the past two decades, efforts have been made to further reduce particulate air pollution across New York State through various Federal and State policy implementations. Air quality has also been affected by economic drivers like the 2007-2009 recession and changing costs for different approaches to electricity generation. Prior work has focused on particulate matter with aerodynamic diameter ≤2.5 μm. However, there is also interest in the effects of ultrafine particles on health and the environment and analyses of changes in particle number concentrations (PNCs) are also of interest to assess the impacts of changing emissions. Particle number size distributions have been measured since 2005. Prior apportionments have been limited to seasonal analyses over a limited number of years because of software limitations. Thus, it has not been possible to perform trend analyses on the source-specific PNCs. Recent development have now permitted the analysis of larger data sets using Positive Matrix Factorization (PMF) including its diagnostics. Thus, this study separated and analyzed the hourly averaged size distributions from 2005 to 2019 into two data sets; October to March and April to September. Six factors were resolved for both data sets with sources identified as nucleation, traffic 1, traffic 2, fresh secondary inorganic aerosol (SIA), aged SIA, and O3-rich aerosol. The resulting source-specific PNCs were combined to provide continuous data sets and analyzed for trends. The trends were then examined with respect to the implementation of regulations and the timing of economic drivers. Nucleation was strongly reduced by the requirement of ultralow (<15 ppm) sulfur on-road diesel fuel in 2006. Secondary inorganic particles and O-rich PNCs show strong summer peaks. Aged SIA was constant and then declined substantially in 2015 but rose in 2019. Traffic 1 and 2 have steadily declined bur rose in 2019.
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http://dx.doi.org/10.1016/j.envpol.2024.123708 | DOI Listing |
Am J Clin Exp Urol
December 2024
Department of Urology, General Hospital of Northern Theater Command Shenyang 110016, Liaoning, China.
Objective: To investigate the expression of metabolism-related genes (MRGs) in kidney renal clear cell carcinoma (KIRC) and their association with patient prognosis, and to identify potential targets for intervention.
Methods: Bioinformatics methods were employed to mine the KIRC transcriptome data in The Cancer Genome Atlas Program (TCGA) database in order to identify MRGs that are aberrantly expressed in cancerous tissues. Subsequently, a prognostic risk score model was constructed and its predictive capacity was evaluated.
Front Res Metr Anal
January 2025
Centre for Postgraduate Studies, Cape Peninsula University of Technology, Cape Town, South Africa.
Big Data communication researchers have highlighted the need for qualitative analysis of online science conversations to better understand their meaning. However, a scholarly gap exists in exploring how qualitative methods can be applied to small data regarding micro-bloggers' communications about science articles. While social media attention assists with article dissemination, qualitative research into the associated microblogging practices remains limited.
View Article and Find Full Text PDFIntroduction: Observational studies have revealed a close relationship between reduced bone mineral density (BMD) and Alzheimer's disease (AD) risk. The receptor activator of nuclear factor kappa-B ligand (RANKL) and osteoprotegerin (OPG) system, pivotal in regulating bone metabolism, has been implicated in brain function, but the causal impact on AD risk remains unclear.
Methods: We employed bi-directional Mendelian randomization (MR) and multivariable MR (MVMR) approaches to elucidate the effect of blood soluble RANKL (sRANKL) and OPG levels on AD, assessing whether this influence was independent of BMD and inflammation.
Quant Imaging Med Surg
January 2025
Department of Radiology, Medical Imaging Institute of Tianjin, Tianjin First Central Hospital, School of Medicine, Nankai University, Tianjin, China.
Background: Although the spatial heterogeneity of glioblastoma (GBM) can be clearly mapped by the habitats generated by magnetic resonance imaging (MRI), the means to accurately predicting the spatial location of local recurrence (SLLR) remains a significant challenge. The aim of this study was to identify the different degrees enhancement of GBM, including the nontumor component and tumor component, and determine their relationship with SLLR.
Methods: A retrospective analysis was performed from three tertiary medical centers, totaling 728 patients with 109 radiation-induced temporal lobe necrosis (TLN) of nasopharyngeal carcinoma (NPC) and 619 with GBM.
J Biomed Sci
January 2025
Department of Viral Glycoproteins, Institute of Biochemistry of the Romanian Academy, Splaiul Independentei 296, Sector 6, 060031, Bucharest, Romania.
Background: Chronic hepatitis B virus (HBV) infection is a major risk for development of hepatocellular carcinoma (HCC), a frequent malignancy with a poor survival rate. HBV infection results in significant endoplasmic reticulum (ER) stress and activation of the unfolded protein response (UPR) signaling, a contributing factor to carcinogenesis. As part of the UPR, the ER-associated degradation (ERAD) pathway is responsible for removing the burden of misfolded secretory proteins, to re-establish cellular homeostasis.
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