Characterization of medicinal Senna genetic resources

2009 ◽  
Vol 7 (03) ◽  
pp. 257-259 ◽  
Author(s):  
J. B. Morris
Keyword(s):  
Pancreatic Cancer ◽  
Principal Component Analysis ◽  
Medicinal Plants ◽  
Genetic Resources ◽  
Morphological Traits ◽  
Principal Component ◽  
Component Analysis ◽  
Pharmaceutical Products ◽  
Seed Reproduction

At 50% maturity, regeneratingSennaspecies were characterized for morphological traits, seed reproduction, and evaluated for regeneration. Quality plants regenerated from all accessions produced 1018 to more than 21,215 total seeds. Principal component analysis revealed which traits contributed the greatest to variability among coffee senna accessions.Sennaspecies have potential to produce pharmaceutical products and can be grown as medicinal plants. The flavonoids quercetin and kaempferol found inSennaspecies have been clinically shown to have anti-pancreatic cancer properties.

Characterization of fretting wear experiments on spline couplings by principal component analysis

2016 ◽  
Vol 231 (7) ◽  
pp. 860-868 ◽  
Author(s):  
Waqar Qureshi ◽  
Francesca Cura ◽  
Andrea Mura
Keyword(s):  
Experimental Data ◽  
Principal Component Analysis ◽  
Principal Component ◽  
Component Analysis ◽  
Fretting Wear ◽  
Aircraft Industry ◽  
Surface Movement ◽  
Noisy Measurements ◽  
Quasi Static Process

Fretting wear is a quasi-static process in which repeated relative surface movement of components results in wear and fatigue. Fretting wear is quite significant in the case of spline couplings which are frequently used in the aircraft industry to transfer torque and power. Fretting wear depends on materials, pressure distribution, torque, rotational speeds, lubrication, surface finish, misalignment between spline shafts, etc. The presence of so many factors makes it difficult to conduct experiments for better models of fretting wear and it is the case whenever a mathematical model is sought from experimental data which is prone to noisy measurements, outliers and redundant variables. This work develops a principal component analysis based method, using a criterion which is insensitive to outliers, to realize a better design and interpret experiments on fretting wear. The proposed method can be extended to other cases too.

Evaluation of the morphological diversity of tea roses (Rosa x odorata) based on phenotypic traits

2020 ◽  
Vol 18 (3) ◽  
pp. 149-158
Author(s):  
Bixuan Cheng ◽  
Chao Yu ◽  
Heling Fu ◽  
Lijun Zhou ◽  
Le Luo ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Correlation Analysis ◽  
Morphological Traits ◽  
Significant Positive Correlation ◽  
Flower Colour ◽  
Principal Component ◽  
Morphological Diversity ◽  
Component Analysis ◽  
Germplasm Resources ◽  
Trait Correlation

AbstractRosa x odorata (sect. Chinenses, Rosaceae) is an important species distributed only in Yunnan Province, China. There is an abundance of wild variation within the species. Using 22 germplasm resources collected from the wild, as well as R. chinensis var. spontanea, R. chinensis ‘Old Blush’ and R. lucidissima, this study involved morphological variation analysis, inter-trait correlation analysis, principal component analysis and clustering analysis based on 16 morphological traits. This study identified a high degree of morphological diversity in R. x odorata germplasm resources and the variation coefficients had a distribution range from 18.00 to 184.04%. The flower colour had the highest degree of variation, while leaflet length/width had the lowest degree of variation. Inter-trait correlation analysis revealed that there was an extremely significant positive correlation between leaflet length and leaflet width. There was also a significant positive correlation between the number of petals and duration of blooming, and the L* and a* values of flower colour were significantly negatively correlated. Principal component analysis screened five principal components with the highest cumulative contribution rate (81.679%) to population variance. Among the 16 morphological traits, style length, sepal width, flower diameter, flower colour, leaflet length and leaflet width were important indices that influenced the morphology of R. x odorata. This study offers guidance for the further development and utilization of R. x odorata germplasm resources.

scholarly journals Derivation and Validation of the Potential Core Genes in Pancreatic Cancer for Tumor-Stroma Crosstalk

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Ran Xue ◽  
Lin Hua ◽  
Wenbin Xu ◽  
Yan Gao ◽  
Yanhua Pang ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Principal Component Analysis ◽  
Cancer Progression ◽  
Principal Component ◽  
Tumor Stroma ◽  
Component Analysis ◽  
Gene Expression Omnibus ◽  
Pancreatic Stellate Cells ◽  
Potential Core ◽  
Core Genes

Background. Pancreatic cancer is a fatal malignancy with a poor prognosis. The interactions between tumor cells and stromal cells contribute to cancer progression. Pancreatic stellate cells (PSCs) play a key role in tumor-stroma crosstalk of pancreatic cancer. The in-depth exploration for tumor-stroma crosstalk is helpful to develop novel therapeutic strategies. Our aim was to identify the potential core genes and pathways in tumor-stroma crosstalk.Methods. 3 microarray datasets were from Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) were screened through bioinformatics analysis. Gene Ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment, and protein-protein interaction (PPI) network were used to obtain the biological roles of DEGs. The top 15 DEGs were explored by principal component analysis. We validated the top 15 DEGs expression in the tumor-stroma crosstalk model in which PSCs were treated with the mixture of Aspc-1 and Panc-1 supernatant.Results. A total of 221 genes were filtered as DEGs for tumor-stroma crosstalk. The results of principal component analysis for the top 15 DEGs can distinguish three groups. According to the KEGG enrichment, there were 8, 7, and 7 DEGs enriched in cancer related pathway, PI3K-Akt signaling pathway, and microRNAs, respectively. In the tumor-stroma crosstalk model, significant differences can be validated in the AKAP12, CLDN1, CP, FKBP1A, LAMB3, LSM4, MTMR3, PRKARIA, YWHAZ, and JUND expressions.Conclusions. These results identified the potential core genes and pathways in pancreatic cancer for tumor-stroma crosstalk, which could provide potential targets for the treatment of pancreatic cancer.

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