scholarly journals Trace elements in road-deposited and waterbed sediments in Kogarah Bay, Sydney: enrichment, sources and fractionation

Soil Research ◽  
2015 ◽  
Vol 53 (4) ◽  
pp. 401 ◽  
Author(s):  
Thuy C. Nguyen ◽  
Paripurnanda Loganathan ◽  
Tien V. Nguyen ◽  
Thi T. N. Pham ◽  
Jaya Kandasamy ◽  
...  
Keyword(s):  
Trace Elements ◽  
Acetic Acid ◽  
Principal Component ◽  
Water Bodies ◽  
Road Asphalt ◽  
Principal Component Analyses ◽  
Mobile Fraction ◽  
Potential Mobility ◽  
Total Concentrations ◽  
Sydney Australia

Trace elements (TEs) in road-deposited sediments (RDS) can be transported by stormwater to neighbouring water bodies to cause aquatic pollution. A study was conducted in Kogarah Bay, Sydney, Australia, to assess the possible sources and potential mobility of TEs in RDS and the contribution to the TE load to the adjacent waterbed sediments in canals and the bay. Of the 11 TEs analysed, pseudo-total concentrations of zinc (Zn), copper (Cu), vanadium (V), chromium (Cr), and antimony (Sb) were greatly enriched in RDS over baseline soils (top 10 cm depth) collected in bushlands. All TE concentrations in waterbed sediments (top 10 cm depth) were similar to those in baseline soils but lower than in RDS. Correlation and principal component analyses revealed that Zn, Cu, Cr and Sb were related to each other in RDS, and probably originated from tyres and brake linings. Vanadium occurred in another component, likely to have originated mainly from road asphalt. Pseudo-total and mobile-fraction (0.1 m acetic acid, pH 2.85 extraction) TE concentrations in RDS were: iron > manganese, Zn > Cu, lead > Cr, nickel, V, Sb, cadmium. The potential ecological TE risk was low to medium in RDS but low in baseline soils and waterbed sediments.

scholarly journals Fast diffusion kurtosis mapping of human brain at 7 Tesla with hybrid principal component analyses

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Fangrong Zong ◽  
Jiaxin Du ◽  
Xiaofeng Deng ◽  
Xubin Chai ◽  
Yan Zhuo ◽  
...  
Keyword(s):  
Human Brain ◽  
Principal Component ◽  
7 Tesla ◽  
Fast Diffusion ◽  
Principal Component Analyses ◽  
Diffusion Kurtosis

scholarly journals Dimension reduction of Malaria Box data allows efficient compound prioritization

F1000Research ◽  
2016 ◽  
Vol 5 ◽  
pp. 2701
Author(s):  
Gajinder Pal Singh
Keyword(s):  
Specific Activity ◽  
Rank Correlation ◽  
Artemisinin Resistance ◽  
Principal Component ◽  
Principal Component Analyses ◽  
Systematic Strategy ◽  
Positive Correlations ◽  
Further Development ◽  
Malaria Box

Background: New anti-malarial drugs are needed to meet the challenge of artemisinin resistance and to achieve malaria elimination and eradication. The new anti-malarial compounds are expected to have many desirable properties, such as activity against multiple stages of Plasmodium, low host cytotoxicity, and low propensity for resistance development, but whether and how these properties might be linked to each other is not clear. A better understanding of the relationship between activities of compounds against different stages of Plasmodium could help in the development of strategies to prioritize compounds with maximum potential for further development. Methods: We utilized the large amount of data that has recently been generated on 400 anti-malarial Malaria Box compounds and performed statistical analyses, such as rank correlation, hierarchical clustering, and principal-component analyses, to test associations between activities against different stages of Plasmodium, other pathogens, and human cells. Results: We found significant positive correlations between the activities of compounds against different stages of Plasmodium. Our results also show toxicity associated with assays conducted at higher compound concentrations. Principal-component analyses (PCA) of the data allowed differentiation of Plasmodium-specific activity from general toxicity and predicted success in in vitro evolution of resistance. We found that a single principal-component can capture most of the desirable properties of Malaria Box compounds and can be used to rank compounds from most desirable to least desirable activity-profile. Conclusions: Here, we provide a systematic strategy to prioritize Malaria Box compounds for further development. This approach may be applied for prioritization of anti-malarial compounds in general.

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