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Efficient diagnosis of diabetes mellitus using an improved ensemble method
Simultaneous evaluation of restless leg syndrome, neuropathic pain, disease activity, and quality of life in patients with Takayasu arteritis: a cross-sectional study
Association between intraoperative fluid management and postoperative outcomes in living kidney donors: a retrospective cohort study
Influences of age and sex on the diagnostic accuracy of human epididymis secretory protein 4 for malignant pleural effusion
A process inspired by fractals for embedding digital codes into additively manufactured components for supply chain security
Multi-objective optimization of the heating oil circuit inside the calendering roller for the lithium battery pole piece
Expression of interleukin-17 in oral tongue squamous cell carcinoma and its effect on biological behavior
Interaction of population density and slope will exacerbate spatiotemporal changes in land use and landscape patterns in mountain city
Smart oxygen monitoring in hospitals: a pilot study during COVID-19
Estimating self-performance when making complex decisions
Effect of artificial fish nest placement on spawning site preference and reproductive efficiency in reservoir fish with adhesive and demersal eggs
Adjusting on-scene CPR duration based on transport time interval in out-of-hospital cardiac arrest: a nationwide multicenter study
Spatial variations in urban woodland cooling between background climates
Abstract Urban woodland composition and configuration have strong associations with land surface temperatures (LST), but the evidence is contradictory due to different spatial scales, regional climate zones, woodland types and urban contexts. In this study, we analyse associations between urban woodland and LST within and between five cities in different Köppen climate zones. Our consistent methodology is framed around local climate zones and conducted at a fine spatial scale. We find that urban woodland fragmentation, connectedness, and shape complexity all influence LST, though much less than overall cover. The importance of cover holds for all climates except for hot-desert (Cairo). Otherwise, every 1% increase in woodland cover corresponds to a reduction of LST of around 0.07 °C to 0.02 °C (London-Cfb > Toronto-Dfa > Nanjing-Cfa > Shenyang-Dwa). Within cities, increasing urban woodland cover generally reduces LST more in built-up compared to vegetated zones. Nevertheless, associations between local LST and urban woodland composition and configuration are highly heterogeneous across cities, especially in cooler climates. Thus, to unravel the complexities of urban woodland cooling, systematic analysis of contemporaneous local and regional factors is required.
Identification of gas outburst precursors based on outburst percolation theory
Randomized controlled trial on the efficacy of forest walking compared to urban walking in enhancing mucosal immunity
Genetic association of lipid-lowering drug target genes with pancreatic cancer: a Mendelian randomization study
Characterizing the omics landscape based on 10,000+ datasets
Abstract The characteristics of data produced by omics technologies are pivotal, as they critically influence the feasibility and effectiveness of computational methods applied in downstream analyses, such as data harmonization and differential abundance analyses. Furthermore, variability in these data characteristics across datasets plays a crucial role, leading to diverging outcomes in benchmarking studies, which are essential for guiding the selection of appropriate analysis methods in all omics fields. Additionally, downstream analysis tools are often developed and applied within specific omics communities due to the presumed differences in data characteristics attributed to each omics technology. In this study, we investigate over ten thousand datasets to understand how proteomics, metabolomics, lipidomics, transcriptomics, and microbiome data vary in specific data characteristics. We were able to show patterns of data characteristics specific to the investigated omics types and provide a tool that enables researchers to assess how representative a given omics dataset is for its respective discipline. Moreover, we illustrate how data characteristics can impact analyses at the example of normalization in the presence of sample-dependent proportions of missing values. Given the variability of omics data characteristics, we encourage the systematic inspection of these characteristics in benchmark studies and for downstream analyses to prevent suboptimal method selection and unintended bias.
The role of Box A of HMGB1 in producing γH2AX associated DNA breaks in lung cancer
Residual nitrite and nitrate in processed meats and meat analogues in the United States
Abstract Residual nitrite (NO 2 − ) and nitrate (NO 3 − ) have been widely studied in the past few decades for their function to improve processed meat quality and their impact on human health 1–4 . In this study we examined how the residual nitrite and nitrate (NO x − ) content of major classes of processed meats products ( n = 1132) produced locally from three regions (East Coast, Midwest and West Coast) and plant protein-based meat analogues ( n = 53) available at retail in the United States was influenced by their composition, processing, and geographical attributes. We also conducted time-dependent depletion studies and observed different patterns of NO x − depletion and conversion during processing and storage and correlated them with product quality. Together, our results reveal a comprehensive prospective of NO x − content in processed meats and meat analogues. The NO 2 − in processed meats and meat analogues averaged (± standard error; minimum and maximum value in parentheses) 13.7 ± 0.62 (0.0-214.5) and 1.7 ± 0.34 (0.0–11.0), respectively, and the NO 3 − in processed meats and meat analogues averaged 32.6 ± 0.90 (2.0–205.9) and 7.2 ± 0.56 (4.0-25.3) ppm, respectively.