Effects of Radix Astragali and Its Split Components on Gene Expression Profiles Related to Water Metabolism in Rats with the Dampness Stagnancy due to Spleen Deficiency Syndrome

Radix Astragali (RA) with slight sweet and warm property is a significant “qi tonifying” herb; it is indicated for the syndrome of dampness stagnancy due to spleen deficiency (DSSD). The purpose of this research was to explore effects of RA and its split components on gene expression profiles related to water metabolism in rats with the DSSD syndrome for identifying components representing property and flavor of RA. The results indicated that RA and its split components, especially polysaccharides component, significantly increased the body weight and the urine volume and decreased the water load index of model rats. Our data also indicated differentially expressed genes (DEGs) related to water metabolism involved secretion, ion transport, water homeostasis, regulation of body fluid levels, and water channel activity; the expression of AQP1, AQP3, AQP4, AQP5, AQP6, and AQP8 was improved; calcium, cAMP, MAPK, PPAR, AMPK, and PI3K-Akt signaling pathway may be related to water metabolism. In general, results indicate that RA and its split components could promote water metabolism in rats with the DSSD syndrome via regulating the expression of AQPs, which reflected sweet-warm properties of RA. Effects of the polysaccharides component are better than others.

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Aortic heterogeneity across segments and under high fat/salt/glucose conditions at the single-cell level

National Science Review ◽

10.1093/nsr/nwaa038 ◽

2020 ◽

Vol 7 (5) ◽

pp. 881-896 ◽

Cited By ~ 1

Author(s):

Dongxu He ◽

Aiqin Mao ◽

Chang-Bo Zheng ◽

Hao Kan ◽

Ka Zhang ◽

...

Keyword(s):

Gene Expression ◽

Single Cell ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Cell Types ◽

The Body ◽

Dietary Salt ◽

High Fat ◽

High Blood Glucose ◽

Thoracic And Abdominal

Abstract The aorta, with ascending, arch, thoracic and abdominal segments, responds to the heartbeat, senses metabolites and distributes blood to all parts of the body. However, the heterogeneity across aortic segments and how metabolic pathologies change it are not known. Here, a total of 216 612 individual cells from the ascending aorta, aortic arch, and thoracic and abdominal segments of mouse aortas under normal conditions or with high blood glucose levels, high dietary salt, or high fat intake were profiled using single-cell RNA sequencing. We generated a compendium of 10 distinct cell types, mainly endothelial (EC), smooth muscle (SMC), stromal and immune cells. The distributions of the different cells and their intercommunication were influenced by the hemodynamic microenvironment across anatomical segments, and the spatial heterogeneity of ECs and SMCs may contribute to differential vascular dilation and constriction that were measured by wire myography. Importantly, the composition of aortic cells, their gene expression profiles and their regulatory intercellular networks broadly changed in response to high fat/salt/glucose conditions. Notably, the abdominal aorta showed the most dramatic changes in cellular composition, particularly involving ECs, fibroblasts and myeloid cells with cardiovascular risk factor-related regulons and gene expression networks. Our study elucidates the nature and range of aortic cell diversity, with implications for the treatment of metabolic pathologies.

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Whole blood genome-wide gene expression profile in males after prolonged wakefulness and sleep recovery

Physiological Genomics ◽

10.1152/physiolgenomics.00058.2012 ◽

2012 ◽

Vol 44 (21) ◽

pp. 1003-1012 ◽

Cited By ~ 24

Author(s):

R. Pellegrino ◽

D. Y. Sunaga ◽

C. Guindalini ◽

R. C. S. Martins ◽

D. R. Mazzotti ◽

...

Keyword(s):

Gene Expression ◽

Whole Blood ◽

Inflammatory Responses ◽

Expression Profiles ◽

Killer Cell ◽

Gene Expression Profiles ◽

Sleep Loss ◽

The Body ◽

Dna Damage And Repair ◽

Peripheral Tissues

Although the specific functions of sleep have not been completely elucidated, the literature has suggested that sleep is essential for proper homeostasis. Sleep loss is associated with changes in behavioral, neurochemical, cellular, and metabolic function as well as impaired immune response. Using high-resolution microarrays we evaluated the gene expression profiles of healthy male volunteers who underwent 60 h of prolonged wakefulness (PW) followed by 12 h of sleep recovery (SR). Peripheral whole blood was collected at 8 am in the morning before the initiation of PW (Baseline), after the second night of PW, and one night after SR. We identified over 500 genes that were differentially expressed. Notably, these genes were related to DNA damage and repair and stress response, as well as diverse immune system responses, such as natural killer pathways including killer cell lectin-like receptors family, as well as granzymes and T-cell receptors, which play important roles in host defense. These results support the idea that sleep loss can lead to alterations in molecular processes that result in perturbation of cellular immunity, induction of inflammatory responses, and homeostatic imbalance. Moreover, expression of multiple genes was downregulated following PW and upregulated after SR compared with PW, suggesting an attempt of the body to re-establish internal homeostasis. In silico validation of alterations in the expression of CETN3, DNAJC, and CEACAM genes confirmed previous findings related to the molecular effects of sleep deprivation. Thus, the present findings confirm that the effects of sleep loss are not restricted to the brain and can occur intensely in peripheral tissues.

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Eight-year longitudinal study of whole blood gene expression profiles in individuals undergoing long-term medical follow-up

Scientific Reports ◽

10.1038/s41598-021-96078-0 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Yoshio Sakai ◽

Alessandro Nasti ◽

Yumie Takeshita ◽

Miki Okumura ◽

Shinji Kitajima ◽

...

Keyword(s):

Gene Expression ◽

Whole Blood ◽

Peripheral Blood ◽

Blood Cells ◽

Expression Profiles ◽

Gene Expression Profiles ◽

The Body ◽

Peripheral Blood Cells ◽

Peripheral Tissues ◽

Altered Gene

AbstractBlood circulates throughout the body via the peripheral tissues, contributes to host homeostasis and maintains normal physiological functions, in addition to responding to lesions. Previously, we revealed that gene expression analysis of peripheral blood cells is a useful approach for assessing diseases such as diabetes mellitus and cancer because the altered gene expression profiles of peripheral blood cells can reflect the presence and state of diseases. However, no chronological assessment of whole gene expression profiles has been conducted. In the present study, we collected whole blood RNA from 61 individuals (average age at registration, 50 years) every 4 years for 8 years and analyzed gene expression profiles using a complementary DNA microarray to examine whether these profiles were stable or changed over time. We found that the genes with very stable expression were related mostly to immune system pathways, including antigen cell presentation and interferon-related signaling. Genes whose expression was altered over the 8-year study period were principally involved in cellular machinery pathways, including development, signal transduction, cell cycle, apoptosis, and survival. Thus, this chronological examination study showed that the gene expression profiles of whole blood can reveal unmanifested physiological changes.

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The Effects of Radix Astragali Water Abstract on Energy Metabolism in Rat Yang-Deficiency Cold Syndrome Model through PPAR Signaling Pathway

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2018/9194362 ◽

2018 ◽

Vol 2018 ◽

pp. 1-19 ◽

Cited By ~ 3

Author(s):

Wanchen Yu ◽

Haijun Zhao ◽

Xin Zong ◽

Xuming Ji ◽

Xiaochun Han ◽

...

Keyword(s):

Gene Expression ◽

Amino Acids ◽

Energy Metabolism ◽

Signaling Pathway ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Metabolic Process ◽

Metabolic Function ◽

Radix Astragali ◽

Ppar Signaling

Radix Astragali (RA) herb with warm property and significant “tonifying qi” effects is indicated for the syndrome of internal cold due to Yang deficiency. The purpose of this research was to explore effects of Radix Astragali (RA) through PPAR signaling pathway on gene expression profiles related to energy metabolism in rats with the Yang-deficiency cold (YDC) syndrome, for identifying the pathological mechanism of Yang-deficiency cold (YDC) syndrome and the effects mechanism of RA. The results indicated that RA could significantly increase body weight (BM), cold and heat tendency (CT), overall temperature (OT), rectum temperature (RT), toe temperature (TT), energy intake (EI), and V(O2)/V(CO2) ratio (which indicates basal metabolism, BM) (P<0.05), enhancing the depressed metabolic function in YDC syndrome model rat. Our data also indicated differentially expressed genes (DEGs) related to energy metabolism involving lipids, carbohydrates, and amino acids metabolic process; the expression of CPT-1 and FABP4 (ap2) was improved; PPAR, Glycolysis, Wnt, cAMP, MAPK, AMPK, and fatty acid degradation signaling pathway may be related to energy metabolism. However, the Chinese herbal medicine RA plays a certain role in promoting the metabolism of substances and energy in rats by its warming and beneficial effect. Our results suggest that the mechanism underlying the function of RA may take effect through the regulation of PPAR signaling pathway and related gene expression. Lipids, carbohydrates, and amino acids metabolic process may be affected to adjust the reduced metabolic function in the model animals. In general, results indicate that RA could promote energy metabolism in rats with the YDC syndrome via PPAR signaling pathway regulating the expression of CPT-1 and FABP4 (ap2), which reflected the warm and qi tonifying properties of RA.

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piRNAs as Modulators of Disease Pathogenesis

International Journal of Molecular Sciences ◽

10.3390/ijms22052373 ◽

2021 ◽

Vol 22 (5) ◽

pp. 2373

Author(s):

Kayla J. Rayford ◽

Ayorinde Cooley ◽

Jelonia T. Rumph ◽

Ashutosh Arun ◽

Girish Rachakonda ◽

...

Keyword(s):

Gene Expression ◽

Expression Profiles ◽

Regulation Of Gene Expression ◽

Gene Expression Profiles ◽

Regulatory Elements ◽

The Body ◽

Small Interfering Rnas ◽

Disease Pathogenesis ◽

The Past ◽

Organ Systems

Advances in understanding disease pathogenesis correlates to modifications in gene expression within different tissues and organ systems. In depth knowledge about the dysregulation of gene expression profiles is fundamental to fully uncover mechanisms in disease development and changes in host homeostasis. The body of knowledge surrounding mammalian regulatory elements, specifically regulators of chromatin structure, transcriptional and translational activation, has considerably surged within the past decade. A set of key regulators whose function still needs to be fully elucidated are small non-coding RNAs (sncRNAs). Due to their broad range of unfolding functions in the regulation of gene expression during transcription and translation, sncRNAs are becoming vital to many cellular processes. Within the past decade, a novel class of sncRNAs called PIWI-interacting RNAs (piRNAs) have been implicated in various diseases, and understanding their complete function is of vital importance. Historically, piRNAs have been shown to be indispensable in germline integrity and stem cell development. Accumulating research evidence continue to reveal the many arms of piRNA function. Although piRNA function and biogenesis has been extensively studied in Drosophila, it is thought that they play similar roles in vertebrate species, including humans. Compounding evidence suggests that piRNAs encompass a wider functional range than small interfering RNAs (siRNAs) and microRNAs (miRNAs), which have been studied more in terms of cellular homeostasis and disease. This review aims to summarize contemporary knowledge regarding biogenesis, and homeostatic function of piRNAs and their emerging roles in the development of pathologies related to cardiomyopathies, cancer, and infectious diseases.

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Biochemical characteristics and gene expression profiles of two paralogous luciferases from the Japanese firefly Pyrocoelia atripennis (Coleoptera, Lampyridae, Lampyrinae): insight into the evolution of firefly luciferase genes

Photochemical & Photobiological Sciences ◽

10.1039/c7pp00110j ◽

2017 ◽

Vol 16 (8) ◽

pp. 1301-1310 ◽

Cited By ~ 7

Author(s):

Manabu Bessho-Uehara ◽

Kaori Konishi ◽

Yuichi Oba

Keyword(s):

Gene Expression ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Firefly Luciferase ◽

The Body ◽

Green Luminescence ◽

Biochemical Characteristics ◽

Insight Into

The same green luminescence is generated by two luciferase isoforms: PatLuc1 is used in lanterns of various stages, and PatLuc2 is used in the body of immobile/less-mobile stages.

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Universal cancer tasks, evolutionary tradeoffs, and the functions of driver mutations

10.1101/382291 ◽

2018 ◽

Cited By ~ 1

Author(s):

Jean Hausser ◽

Pablo Szekely ◽

Noam Bar ◽

Anat Zimmer ◽

Hila Sheftel ◽

...

Keyword(s):

Gene Expression ◽

Molecular Diversity ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Molecular Data ◽

The Body ◽

Driver Mutations ◽

Passenger Mutations ◽

Tumor Gene Expression ◽

Tumor Gene

AbstractRecent advances have led to an appreciation of the vast molecular diversity of cancer. Detailed data has enabled powerful methods to sort tumors into groups with benefits for prognosis and treatment. We are still missing, however, a general theoretical framework to understand the diversity of tumor gene-expression and mutations. To address this, we present a framework based on multi-task evolution theory, using the fact that tumors evolve in the body, and that tumors are faced with multiple tasks that contribute to their fitness. In accordance with the theory, we find that tradeoff between tasks constrains tumor gene-expression to a continuum bounded by a polyhedron. The vertices of the polyhedron are gene-expression profiles each specializing in one task, allowing the tasks to be identified. We find five universal cancer tasks across tissue-types: cell-division, biomass & energy, lipogenesis, immune-interaction and invasion & tissue remodeling. Tumors whose gene-expression lies close to a vertex are task specialists. We find evidence that such specialists are more sensitive to drugs that interfere with this task. We find that driver mutations, but not passenger mutations, tune gene-expression towards specialization in specific tasks. This approach can integrate additional types of molecular data into a theoretically-based framework for understanding tumor diversity.

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Classification of Gene Expression Data with Optimized Feature Selection

International Journal of Recent Technology and Engineering - 2 ◽

10.35940/ijrte.b1845.078219 ◽

2019 ◽

Vol 8 (2) ◽

pp. 4763-4769

Keyword(s):

Gene Expression ◽

Feature Selection ◽

Gene Expression Data ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Vital Role ◽

The Body ◽

Disease Classification ◽

Learning Approaches ◽

Expression Data

There are different types of fatal diseases that could possibly outspread to various parts of the body. It thus becomes obligatory to predict the existence of such anomalies, in order to prune the extent of their spread. Examining the characteristics of genes provides a deep intuition about the disease classification, as they play a vital role in influencing how an organism appears, behaves and survives in an environment. The detection of the abnormal genes could be efficiently modelled using statistical methods and machine learning approaches. Gene expression data derived from a microarray could act as an aid for this statistical computation. Microarray being a recent leap in molecular biology, provides a scope for hybridization of DNA samples that can be interpreted as values based on the gene expression level that the genome possesses. We propose an idea to select a subset of features from the huge number of samples retrieved from the gene expression profiles using Boruta feature selection algorithm. A comparative study with various supervised classification algorithms is made to categorize this subset to a normal and deviant gene. This serves to discover the most appropriate algorithm to classify the gene expression data. Hence assorting the abnormal genes in future could be accelerated with ease

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