Integrated morphology analysis, metabolomic analysis and gene expression to assess the quality of four adventitious roots lines of Glycyrrhiza uralensis Fisch

2018 ◽  
Vol 135 (1) ◽  
pp. 169-177 ◽  
Author(s):  
Jun Lu ◽  
Wenxia Liang ◽  
Jianli Li ◽  
Shihui Wang ◽  
Lu Yao ◽  
...  
Keyword(s):  
Gene Expression ◽  
Adventitious Roots ◽  
Glycyrrhiza Uralensis ◽  
Metabolomic Analysis ◽  
Glycyrrhiza Uralensis Fisch ◽  
Morphology Analysis

Protein elicitor isolated from Escherichia coli induced bioactive compound biosynthesis as well as gene expression in Glycyrrhiza uralensis Fisch adventitious roots

RSC Advances ◽  
2016 ◽  
Vol 6 (112) ◽  
pp. 111622-111631 ◽  
Author(s):  
Jianli Li ◽  
Juan Wang ◽  
Jing Li ◽  
Jinxin Li ◽  
Shujie Liu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Escherichia Coli ◽  
Bacillus Subtilis ◽  
Adventitious Roots ◽  
Bioactive Compound ◽  
Glycyrrhiza Uralensis ◽  
Glycyrrhiza Uralensis Fisch ◽  
Protein Elicitor

This study explored the ability of three rhizobacterial strains (Bacillus subtilis, Penicillium fellutanum and Escherichia coli) to trigger metabolism.

Non-targeted metabolomic analysis of the variations in the metabolites of two genotypes of Glycyrrhiza uralensis Fisch. under drought stress

2022 ◽  
Vol 176 ◽  
pp. 114402
Author(s):  
Qianqian Zhang ◽  
Bingzhen Li ◽  
Qing Chen ◽  
Youla Su ◽  
Ruijuan Wang ◽  
...  
Keyword(s):  
Drought Stress ◽  
Glycyrrhiza Uralensis ◽  
Metabolomic Analysis ◽  
Glycyrrhiza Uralensis Fisch

scholarly journals The complete mitochondrial genome of Glycyrrhiza uralensis Fisch. (Fabales, Leguminosae)

2021 ◽  
Vol 6 (2) ◽  
pp. 475-477
Author(s):  
Yan-Yun Yang ◽  
Sheng-Nan Li ◽  
Liang Xu ◽  
Yan-Ping Xing ◽  
Rong Zhao ◽  
...  
Keyword(s):  
Mitochondrial Genome ◽  
Complete Mitochondrial Genome ◽  
Glycyrrhiza Uralensis ◽  
Glycyrrhiza Uralensis Fisch

244An automated beat exclusion algorithm to improve beat-to-beat P-wave morphology analysis

EP Europace ◽  
2020 ◽  
Vol 22 (Supplement_1) ◽  
Author(s):  
D Tachmatzidis ◽  
D Filos ◽  
I Chouvarda ◽  
A Tsarouchas ◽  
D Mouselimis ◽  
...  
Keyword(s):  
P Wave ◽  
Strongly Correlated ◽  
Wave Analysis ◽  
Morphology Analysis ◽  
Wave Morphology ◽  
History Of ◽  
Ectopic Beats ◽  
Rater Variability ◽  
Operator Workload

Abstract Background A manually beat-to-beat P-wave analysis has previously revealed the existence of multiple P-wave morphologies in patients with paroxysmal Atrial Fibrillation (AF) while on sinus rhythm, distinguishing them from healthy, AF free patients. Purpose The aim of this study was to investigate the effectiveness of an Automated Beat Exclusion algorithm (ABE) that excludes noisy or ectopic beats, replacing manual beat evaluation during beat-to-beat P-wave analysis, by assessing its effect on inter-rater variability and reproducibility. Methods Beat-to-beat P-wave morphology analysis was performed on 34 ten-minute ECG recordings of patients with a history of AF. Each recording was analyzed independently by two clinical experts for a total of four analysis runs; once with ABE and once again with the manual exclusion of ineligible beats. The inter-rater variability and reproducibility of the analysis with and without ABE were assessed by comparing the agreement of analysis runs with respect to secondary morphology detection, primary morphology ECG template and the percentage of both, as these aspects have been previously used to discriminate PAF patients from controls. Results Comparing ABE to manual exclusion in detecting secondary P-wave morphologies displayed substantial (Cohen"s k = 0.69) to almost perfect (k = 0.82) agreement. Area difference among auto and manually calculated main morphology templates was in every case <5% (p < 0.01) and the correlation coefficient was >0.99 (p < 0.01). Finally, the percentages of beats classified to the primary or secondary morphology per recording by each analysis were strongly correlated, for both main and secondary P-wave morphologies, ranging from ρ=0.756 to ρ=0.940 (picture) Conclusion The use of the ABE algorithm does not diminish inter-rater variability and reproducibility of the analysis. The primary and secondary P-wave morphologies produced by all analyses were similar, both in terms of their template and their frequency. Based on the results of this study, the ABE algorithm incorporated in the beat-to-beat P-wave morphology analysis drastically reduces operator workload without influencing the quality of the analysis. Abstract Figure.

scholarly journals The impact of RNA extraction method on accurate RNA sequencing from formalin-fixed paraffin-embedded tissues

BMC Cancer ◽  
2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Michal Marczyk ◽  
Chunxiao Fu ◽  
Rosanna Lau ◽  
Lili Du ◽  
Alexander J. Trevarton ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Rna Sequencing ◽  
Rna Extraction ◽  
Formalin Fixed Paraffin ◽  
Ffpe Samples ◽  
Formalin Fixed Paraffin Embedded ◽  
The Impact ◽  
Formalin Fixed

Abstract Background Utilization of RNA sequencing methods to measure gene expression from archival formalin-fixed paraffin-embedded (FFPE) tumor samples in translational research and clinical trials requires reliable interpretation of the impact of pre-analytical variables on the data obtained, particularly the methods used to preserve samples and to purify RNA. Methods Matched tissue samples from 12 breast cancers were fresh frozen (FF) and preserved in RNAlater or fixed in formalin and processed as FFPE tissue. Total RNA was extracted and purified from FF samples using the Qiagen RNeasy kit, and in duplicate from FFPE tissue sections using three different kits (Norgen, Qiagen and Roche). All RNA samples underwent whole transcriptome RNA sequencing (wtRNAseq) and targeted RNA sequencing for 31 transcripts included in a signature of sensitivity to endocrine therapy. We assessed the effect of RNA extraction kit on the reliability of gene expression levels using linear mixed-effects model analysis, concordance correlation coefficient (CCC) and differential analysis. All protein-coding genes in the wtRNAseq and three gene expression signatures for breast cancer were assessed for concordance. Results Despite variable quality of the RNA extracted from FFPE samples by different kits, all had similar concordance of overall gene expression from wtRNAseq between matched FF and FFPE samples (median CCC 0.63–0.66) and between technical replicates (median expression difference 0.13–0.22). More than half of genes were differentially expressed between FF and FFPE, but with low fold change (median |LFC| 0.31–0.34). Two out of three breast cancer signatures studied were highly robust in all samples using any kit, whereas the third signature was similarly discordant irrespective of the kit used. The targeted RNAseq assay was concordant between FFPE and FF samples using any of the kits (CCC 0.91–0.96). Conclusions The selection of kit to purify RNA from FFPE did not influence the overall quality of results from wtRNAseq, thus variable reproducibility of gene signatures probably relates to the reliability of individual gene selected and possibly to the algorithm. Targeted RNAseq showed promising performance for clinical deployment of quantitative assays in breast cancer from FFPE samples, although numerical scores were not identical to those from wtRNAseq and would require calibration.

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