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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Sanhuang Xiexin Tang Ameliorates Type 2 Diabetic Rats via Modulation of the Metabolic Profiles and NF-κB/PI-3K/Akt Signaling Pathways
|
|---|---|
| Published in |
Frontiers in Pharmacology, August 2018
|
| DOI | 10.3389/fphar.2018.00955 |
| Pubmed ID | |
| Authors |
Xiaoyan Wei, Jinhua Tao, Yumeng Shen, Suwei Xiao, Shu Jiang, Erxin Shang, Zhenhua Zhu, Dawei Qian, Jinao Duan |
| Abstract |
Sanhuang Xiexin Tang (SXT), a classic prescription, has been clinically used to cure diabetes for thousands of years, but its mechanism remains unclear. Here, a systematic in-depth research was performed to unravel how it worked by the signaling pathway and metabonomics analysis. Our studies were conducted using high-fat diets (HFD) and streptozocin (STZ)-induced type 2 diabetes mellitus (T2DM) rats. The blood glucose was measured by a glucose-meter. Protein contents were determined by western blotting or ELISA and mRNA expression was identified by RT-PCR analysis. The pathological status of pancreas was assessed by histopathological analysis. Furthermore, Ultra Performance Liquid Chromatography-Quadrupole-Time of Flight/Mass Spectrometry (UPLC-Q-TOF/MS) coupled with multivariate statistical analysis was performed to discover potential biomarkers and the associated pathways. Hyperglycaemia, insulin resistance, dyslipidemia and inflammation in T2DM rats were significantly ameliorated after 7-week oral administration of SXT. The expressions of phosphatidylinositol-3-kinase (PI-3K), protein kinase B (Akt), glucose transporters-4 (GLUT4) Mrna, and p-PI-3K, p-Akt, GLUT4 protein involved in the PI-3K/Akt signaling pathway of T2DM were markedly up-regulated. Further investigation indicated that the perturbance of metabolic profiling in T2DM rats was obviously reversed by SXT and 38 potential biomarkers were screened and identified. Our study might help clarify the mechanism of SXT and provide some evidences for its clinical application in the future. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 12 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 3 | 25% |
| Student > Ph. D. Student | 2 | 17% |
| Student > Master | 2 | 17% |
| Lecturer > Senior Lecturer | 1 | 8% |
| Unspecified | 1 | 8% |
| Other | 1 | 8% |
| Unknown | 2 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 3 | 25% |
| Unspecified | 2 | 17% |
| Nursing and Health Professions | 1 | 8% |
| Agricultural and Biological Sciences | 1 | 8% |
| Neuroscience | 1 | 8% |
| Other | 2 | 17% |
| Unknown | 2 | 17% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 15 September 2018.
All research outputs
#17,989,170
of 23,102,082 outputs
Outputs from Frontiers in Pharmacology
#7,271
of 16,459 outputs
Outputs of similar age
#240,302
of 334,872 outputs
Outputs of similar age from Frontiers in Pharmacology
#184
of 390 outputs
Altmetric has tracked 23,102,082 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 16,459 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.0. This one is in the 48th percentile – i.e., 48% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 334,872 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 390 others from the same source and published within six weeks on either side of this one. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.