scholarly journals Correlation Network Analysis Visually Identifies Interactions of Antioxidant Compounds with Plant Growth, Leaf Photosynthetic Performance, and Agronomic Quality in Strawberry

2021 ◽  
Vol 59 (3) ◽  
pp. 147-155
Author(s):  
Kazufumi ZUSHI ◽  
Kan TSUTSUKI ◽  
Hiromi TAKAHASHI ◽  
Masaaki KIRIMURA
Keyword(s):  
Network Analysis ◽  
Plant Growth ◽  
Photosynthetic Performance ◽  
Correlation Network ◽  
Antioxidant Compounds ◽  
Agronomic Quality

scholarly journals Lipidomic Network of Mild Cognitive Impairment from the Mayo Clinic Study of Aging

2021 ◽  
pp. 1-11
Author(s):  
Xuewei Wang ◽  
Hai Bui ◽  
Prashanthi Vemuri ◽  
Jonathan Graff-Radford ◽  
Clifford R. Jack Jr ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Network Analysis ◽  
Mayo Clinic ◽  
Plasma Lipids ◽  
Amyloid Β ◽  
Cognitive Status ◽  
Correlation Network ◽  
Lipid Species ◽  
Clinic Study

Background: Lipid alterations contribute to Alzheimer’s disease (AD) pathogenesis. Lipidomics studies could help systematically characterize such alterations and identify potential biomarkers. Objective: To identify lipids associated with mild cognitive impairment and amyloid-β deposition, and to examine lipid correlation patterns within phenotype groups Methods: Eighty plasma lipids were measured using mass spectrometry for 1,255 non-demented participants enrolled in the Mayo Clinic Study of Aging. Individual lipids associated with mild cognitive impairment (MCI) were first identified. Correlation network analysis was then performed to identify lipid species with stable correlations across conditions. Finally, differential correlation network analysis was used to determine lipids with altered correlations between phenotype groups, specifically cognitively unimpaired versus MCI, and with elevated brain amyloid versus without. Results: Seven lipids were associated with MCI after adjustment for age, sex, and APOE4. Lipid correlation network analysis revealed that lipids from a few species correlated well with each other, demonstrated by subnetworks of these lipids. 177 lipid pairs differently correlated between cognitively unimpaired and MCI patients, whereas 337 pairs of lipids exhibited altered correlation between patients with and without elevated brain amyloid. In particular, 51 lipid pairs showed correlation alterations by both cognitive status and brain amyloid. Interestingly, the lipids central to the network of these 51 lipid pairs were not significantly associated with either MCI or amyloid, suggesting network-based approaches could provide biological insights complementary to traditional association analyses. Conclusion: Our attempt to characterize the alterations of lipids at network-level provides additional insights beyond individual lipids, as shown by differential correlations in our study.

scholarly journals Integrative Identification of Hub Genes Associated With Immune Cells in Atrial Fibrillation Using Weighted Gene Correlation Network Analysis

2021 ◽  
Vol 7 ◽  
Author(s):  
Tao Yan ◽  
Shijie Zhu ◽  
Miao Zhu ◽  
Chunsheng Wang ◽  
Changfa Guo
Keyword(s):  
Atrial Fibrillation ◽  
Network Analysis ◽  
Molecular Mechanism ◽  
Immune Cells ◽  
Bioinformatics Analysis ◽  
Functional Enrichment ◽  
Correlation Network ◽  
Hub Genes ◽  
Qrt Pcr ◽  
Gene Correlation

Background: Atrial fibrillation (AF) is the most common tachyarrhythmia in the clinic, leading to high morbidity and mortality. Although many studies on AF have been conducted, the molecular mechanism of AF has not been fully elucidated. This study was designed to explore the molecular mechanism of AF using integrative bioinformatics analysis and provide new insights into the pathophysiology of AF.Methods: The GSE115574 dataset was downloaded, and Cibersort was applied to estimate the relative expression of 22 kinds of immune cells. Differentially expressed genes (DEGs) were identified through the limma package in R language. Weighted gene correlation network analysis (WGCNA) was performed to cluster DEGs into different modules and explore relationships between modules and immune cell types. Functional enrichment analysis was performed on DEGs in the significant module, and hub genes were identified based on the protein-protein interaction (PPI) network. Hub genes were then verified using quantitative real-time polymerase chain reaction (qRT-PCR).Results: A total of 2,350 DEGs were identified and clustered into eleven modules using WGCNA. The magenta module with 246 genes was identified as the key module associated with M1 macrophages with the highest correlation coefficient. Three hub genes (CTSS, CSF2RB, and NCF2) were identified. The results verified using three other datasets and qRT-PCR demonstrated that the expression levels of these three genes in patients with AF were significantly higher than those in patients with SR, which were consistent with the bioinformatic analysis.Conclusion: Three novel genes identified using comprehensive bioinformatics analysis may play crucial roles in the pathophysiological mechanism in AF, which provide potential therapeutic targets and new insights into the treatment and early detection of AF.

scholarly journals The Use of RNA Sequencing and Correlation Network Analysis to Study Potential Regulators of Crabapple Leaf Color Transformation

2018 ◽  
Vol 59 (5) ◽  
pp. 1027-1042 ◽  
Author(s):  
Tuo Yang ◽  
Keting Li ◽  
Suxiao Hao ◽  
Jie Zhang ◽  
Tingting Song ◽  
...  
Keyword(s):  
Network Analysis ◽  
Rna Sequencing ◽  
Correlation Network ◽  
Leaf Color ◽  
Color Transformation

Correlation Network Analysis and Knowledge Integration

2011 ◽  
pp. 251-280 ◽  
Author(s):  
Thomas N. Plasterer ◽  
Robert Stanley ◽  
Erich Gombocz
Keyword(s):  
Network Analysis ◽  
Knowledge Integration ◽  
Correlation Network

scholarly journals Effects of Climate Temperature and Water Stress on Plant Growth and Accumulation of Antioxidant Compounds in Sweet Basil (Ocimum basilicum L.) Leafy Vegetable

Scientifica ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-12 ◽  
Author(s):  
Asma Al-Huqail ◽  
Rehab M. El-Dakak ◽  
Marwa Nme Sanad ◽  
Reem H. Badr ◽  
Mohamed M. Ibrahim ◽  
...  
Keyword(s):  
Water Stress ◽  
Plant Growth ◽  
Growth Parameters ◽  
Stress Conditions ◽  
Total Phenolic ◽  
Antioxidant Compounds ◽  
Chlorophyll Contents ◽  
Sweet Basil ◽  
Stress Markers ◽  
Response To Water

The effects of climate temperature and water stress on growth and several stress markers were investigated in sweet basil plants. Some growth parameters (shoot length and number of leaves) and photosynthetic chlorophyll contents were determined every two days during plant growth, and foliage leaf material was collected after 15 and 21 days of treatment. Both climate temperature and water stress inhibited sweet basil plant growth; especially, total chlorophyll levels were decreased significantly in response to high-temperature treatments. Under strong stresses, basil plants induced the synthesis and accumulation of glycine betaine (GB) as a secondary osmolyte, although at less content when compared with the proline content under the same stress conditions. Proline concentrations particularly increased in leaves of both basil stressed plants, accomplishing levels high enough to play a crucial role in cellular osmoregulation adjustment. Stress-induced accumulation of these antioxidant compounds was detected in sweet basil. Therefore, it appears that sweet basil-treated plants are able to synthesize antioxidant compounds under strong stress conditions. On the other hand, total sugar concentrations decreased in stress-treated basil plants. Both temperature and water stress treatments caused oxidative stress in the treated plants, as indicated by a significant increment in malondialdehyde (MDA) concentrations. An increase in total phenolic and flavonoid concentrations in response to water stress and a highly significant decrease in carotenoid concentrations in basil leaves were observed; flavonoids also increased under high climate temperature conditions.

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