| Literature DB >> 35685683 |
Leilei Gong1, Yangyang Hao2, Xiaojie Yin1, Lan Wang1, Xiaojing Ma1, Jun Cao1, Rixin Liang1, Fulong Liao1, Jianyong Zhang3.
Abstract
Background: It has been recognized that exercise training can attenuate the progression of atherosclerosis (AS). The combined application of components from the fruit of Crataegus pinnatifida Bge. Var. major N.E. Br. (CP) and the root of Salvia miltiorrhiza Bge. (SM) has been effective in the prevention and treatment of atherosclerosis. The present work aims to investigate the joint effects of extracts from the fruit of CP and the root of SM with swimming on atherosclerosis in rats. Method: To establish a rat atherosclerosis model, a combined method of partial ligation of the left common carotid artery leading to low shear stress and a high-fat diet was employed. Blood samples were collected to detect the blood lipid profile, which included total cholesterol (T-CHO), low-density lipoprotein cholesterol (LDL-C), triglycerides (TG) and high-density lipoprotein cholesterol (HDL-C); endothelial cytokines such as 6-keto-prostaglandin F1α (PGF1α), endothelin (ET), thromboxane B2 (TXB2), plasminogen activator inhibitor-1 (PAI-1), and von Willebrand factor (vWF); and inflammatory cytokines such as interleukin-1β (IL-1β), interleukin-6 (IL-6) and interleukin-10 (IL-10). Finally, the common carotid arteries of the rats were removed to observe pathological changes via oil red O staining, and the gene expression of t-PA, PAI-1, and vWF was assayed via real-time (RT) quantitative polymerase chain reaction (qPCR).Entities:
Year: 2018 PMID: 35685683 PMCID: PMC9128347 DOI: 10.1039/c8ra05548c
Source DB: PubMed Journal: RSC Adv ISSN: 2046-2069 Impact factor: 4.036
Selected genes, primers and amplicon characteristics
| Gene | GenBank accession no | Primer sequences (forward/reverse) | Amplicon | Amplicon size (bp) |
|---|---|---|---|---|
| β-Actin | NM_031144 | CCGTAAAGACCTCTATGCCAACA | 57.77 | 230 |
| CGGACTCATCGTACTCCTGCTT | 59.54 | |||
| COX-1 | S67721.1 | GATGGGGGCTCCTTTCT | 55.17 | 198 |
| CCGTCATCTCCAGGGTAAT | 55.88 | |||
| vWF | NM_053889 | ATGAGGATGGGAACGAGAAGA | 55.61 | 240 |
| AGGTGACGATGTGCCGAGT | 57.32 | |||
| PAI-1 | M24067.1 | TACCACGGCGAAACCTC | 57.18 | 155 |
| GAGAACTTAGGCAGGATGAGGAG | 59.55 |
Fig. 1Bar graphs of serum lipoproteins, inflammatory cytokines, and endothelial factors in the model group and sham-operated group. All data are expressed as the mean ± SD. Comparisons between the sham group and model group were analysed using the independent-sample t-test. A value of P < 0.05 was considered statistically significant.
Fig. 2Three-dimensional surface plots of the effects of TCPSM extract and swimming on inflammatory factors. (A) Serum IL-6 (pg ml−1); (B) plasma IL-10 (pg ml−1); (C) serum IL-1β (pg ml−1).
Fig. 3Three-dimensional surface plots of effects of CPSM extract and swimming on endothelial factors. (A) Serum PAI-1 (pg ml−1); (B) plasma TXB2 (pg ml−1); (C) serum vWF (pg ml−1).
Fig. 7Three-dimensional surface plot of effects of CPSM extract and swimming on relative expression levels of genes. (A) Relative expression level of PAI-1 mRNA; (B) relative expression level of COX-1 mRNA; (C) relative expression level of vWF mRNA.
| Swimming (min) | CPSM (mg kg−1) | T-CHO (pg ml−1) | TG (pg ml−1) | LDL-C (pg ml−1) | HDL-C (pg ml−1) |
|---|---|---|---|---|---|
| 0 | 0 | 2.39 ± 0.19 | 1.08 ± 0.13 | 1.11 ± 0.08 | 0.79 ± 0.05 |
| 0 | 118.5 | 1.86 ± 0.22 | 0.79 ± 0.04 | 0.72 ± 0.21 | 0.78 ± 0.02 |
| 0 | 237 | 1.93 ± 0.04 | 0.68 ± 0.06 | 0.82 ± 0.12 | 0.79 ± 0.12 |
| 0 | 474 | 1.84 ± 0.14 | 0.84 ± 0.12 | 0.71 ± 0.12 | 0.74 ± 0.07 |
| 10 | 0 | 2.03 ± 0.06 | 0.63 ± 0.10 | 0.91 ± 0.23 | 0.83 ± 0.14 |
| 10 | 118.5 | 1.88 ± 0.10 | 0.59 ± 0.05 | 0.74 ± 0.23 | 0.82 ± 0.17 |
| 10 | 237 | 1.71 ± 0.05 | 0.50 ± 0.08 | 0.57 ± 0.09 | 0.91 ± 0.08 |
| 10 | 474 | 1.74 ± 0.19 | 0.70 ± 0.14 | 0.63 ± 0.06 | 0.79 ± 0.15 |
| 20 | 0 | 1.93 ± 0.16 | 0.73 ± 0.06 | 0.73 ± 0.09 | 0.87 ± 0.10 |
| 20 | 118.5 | 1.79 ± 0.34 | 0.75 ± 0.13 | 0.60 ± 0.23 | 0.86 ± 0.10 |
| 20 | 237 | 1.75 ± 0.07 | 0.55 ± 0.05 | 0.55 ± 0.09 | 0.95 ± 0.04 |
| 20 | 474 | 1.54 ± 0.23 | 0.42 ± 0.11 | 0.42 ± 0.10 | 0.93 ± 0.10 |
| 40 | 0 | 1.75 ± 0.24 | 0.60 ± 0.08 | 0.55 ± 0.28 | 0.93 ± 0.13 |
| 40 | 118.5 | 1.64 ± 0.05 | 0.47 ± 0.05 | 0.44 ± 0.06 | 0.98 ± 0.07 |
| 40 | 237 | 1.68 ± 0.19 | 0.50 ± 0.13 | 0.42 ± 0.11 | 1.03 ± 0.15 |
| 40 | 474 | 2.04 ± 0.25 | 0.50 ± 0.06 | 0.79 ± 0.15 | 1.02 ± 0.07 |
All data are expressed as the mean ± SD. The GLM procedure was applied for a two-way ANOVA to test for synergy. Comparisons between each pair of factor levels were analysed using a Bonferroni post hoc test. A value of P < 0.05 was considered statistically significant.
| Two-way ANOVA |
|
|
|
|
|
|
|
|
|---|---|---|---|---|---|---|---|---|
| Swimming | 4.852 | 0.007 | 27.892 | <0.001 | 9.040 | <0.001 | 8.647 | <0.001 |
| CPSM | 5.580 | 0.003 | 9.849 | <0.001 | 5.587 | 0.003 | 0.892 | 0.456 |
| CPSM × swimming | 2.801 | 0.015 | 3.982 | 0.002 | 2.412 | 0.032 | 0.381 | 0.936 |
| Swimming (min) | CPSM (mg kg−1) | IL-1β (pg ml−1) | IL-6 (pg ml−1) | IL-10 (pg ml−1) | Area proportion (%) |
|---|---|---|---|---|---|
| 0 | 0 | 0.351 ± 0.020 | 95.68 ± 3.24 | 57.61 ± 8.16 | 32.29 ± 0.41 |
| 0 | 118.5 | 0.278 ± 0.014 | 119.78 ± 30.39 | 121.50 ± 33.34 | 1.24 ± 0.29 |
| 0 | 237 | 0.277 ± 0.055 | 134.28 ± 13.90 | 132.40 ± 12.58 | 8.52 ± 1.20 |
| 0 | 474 | 0.265 ± 0.038 | 88.28 ± 13.74 | 130.39 ± 12.91 | 3.13 ± 0.43 |
| 10 | 0 | 0.267 ± 0.060 | 81.77 ± 8.17 | 52.50 ± 22.97 | 10.20 ± 1.14 |
| 10 | 118.5 | 0.244 ± 0.030 | 83.80 ± 3.46 | 77.13 ± 10.63 | 0.37 ± 0.15 |
| 10 | 237 | 0.276 ± 0.007 | 63.53 ± 13.90 | 111.87 ± 8.19 | 0.05 ± 0.01 |
| 10 | 474 | 0.284 ± 0.012 | 112.83 ± 15.74 | 133.16 ± 16.74 | 1.45 ± 0.06 |
| 20 | 0 | 0.244 ± 0.058 | 72.70 ± 24.33 | 118.94 ± 17.98 | 11.49 ± 2.35 |
| 20 | 118.5 | 0.285 ± 0.037 | 139.18 ± 3.09 | 126.39 ± 9.35 | 1.69 ± 0.71 |
| 20 | 237 | 0.249 ± 0.023 | 99.65 ± 9.01 | 120.06 ± 19.20 | 0.04 ± 0.01 |
| 20 | 474 | 0.274 ± 0.050 | 65.24 ± 26.35 | 129.53 ± 6.22 | 0.03 ± 0.01 |
| 40 | 0 | 0.252 ± 0.026 | 131.18 ± 11.01 | 69.39 ± 14.06 | 0.15 ± 0.01 |
| 40 | 118.5 | 0.262 ± 0.026 | 101.94 ± 3.45 | 117.22 ± 10.37 | 0.45 ± 0.10 |
| 40 | 237 | 0.239 ± 0.024 | 91.06 ± 17.84 | 105.29 ± 5.92 | 0.03 ± 0.01 |
| 40 | 474 | 0.277 ± 0.014 | 77.24 ± 11.37 | 113.88 ± 4.87 | 0.06 ± 0.02 |
All data are expressed as the mean ± SD. The GLM procedure was applied for a two-way ANOVA to test for synergy. Comparisons between each pair of factor levels were analysed using a Bonferroni post hoc test. A value of P < 0.05 was considered statistically significant.
| Two-way ANOVA |
|
|
|
|
|
|
|
|
|---|---|---|---|---|---|---|---|---|
| Swimming | 2.348 | 0.091 | 5.189 | 0.005 | 8.715 | <0.001 | 238.003 | 0.000 |
| CPSM | 0.933 | 0.436 | 5.507 | 0.004 | 27.173 | <0.001 | 450.841 | 0.000 |
| CPSM × swimming | 1.620 | 0.152 | 8.757 | <0.001 | 4.267 | <0.001 | 92.550 | 0.000 |
| Swimming (min) | CPSM (mg kg−1) | 6-keto-PGF1α (pg ml−1) | TX-B2 (pg ml−1) | PAI-1 (pg ml−1) | vWF (pg ml−1) |
|---|---|---|---|---|---|
| 0 | 0 | 86.10 ± 3.60 | 1013.05 ± 24.45 | 415.39 ± 31.07 | 3370.98 ± 520.31 |
| 0 | 118.5 | 89.49 ± 11.54 | 1097.32 ± 48.76 | 408.65 ± 3.53 | 3139.61 ± 218.08 |
| 0 | 237 | 98.27 ± 8.07 | 856.30 ± 150.06 | 247.72 ± 82.19 | 3048.56 ± 167.48 |
| 0 | 474 | 111.39 ± 11.62 | 771.93 ± 191.52 | 540.74 ± 35.28 | 3119.72 ± 383.80 |
| 10 | 0 | 105.22 ± 10.51 | 1008.67 ± 291.55 | 483.90 ± 61.29 | 2630.53 ± 290.08 |
| 10 | 118.5 | 103.13 ± 34.49 | 909.13 ± 223.35 | 550.44 ± 97.73 | 2741.71 ± 177.03 |
| 10 | 237 | 109.73 ± 21.53 | 1103.77 ± 202.15 | 428.82 ± 58.86 | 1191.90 ± 64.79 |
| 10 | 474 | 126.33 ± 30.69 | 1213.07 ± 215.12 | 347.31 ± 87.64 | 2919.60 ± 357.39 |
| 20 | 0 | 154.30 ± 34.61 | 956.90 ± 158.26 | 453.94 ± 58.53 | 2950.73 ± 301.59 |
| 20 | 118.5 | 154.77 ± 48.88 | 983.67 ± 349.84 | 460.99 ± 11.30 | 2079.09 ± 385.65 |
| 20 | 237 | 141.68 ± 11.95 | 555.89 ± 216.95 | 498.75 ± 90.95 | 1989.76 ± 571.72 |
| 20 | 474 | 167.71 ± 18.51 | 308.77 ± 94.87 | 343.34 ± 41.55 | 2612.74 ± 270.84 |
| 40 | 0 | 145.44 ± 24.72 | 582.07 ± 93.35 | 643.85 ± 52.96 | 2385.94 ± 270.99 |
| 40 | 118.5 | 164.52 ± 27.10 | 423.43 ± 111.73 | 261.38 ± 44.42 | 2001.27 ± 152.75 |
| 40 | 237 | 130.63 ± 17.46 | 358.27 ± 123.64 | 452.18 ± 37.68 | 2661.67 ± 288.10 |
| 40 | 474 | 159.34 ± 21.34 | 597.30 ± 118.40 | 502.63 ± 16.52 | 1563.23 ± 26.68 |
All data are expressed as the mean ± SD. The GLM procedure was applied for a two-way ANOVA to test for synergy. Comparisons between each pair of factor levels were analysed using a Bonferroni post hoc test. A value of P < 0.05 was considered statistically significant.
| Two-way ANOVA |
|
|
|
|
|
|
|
|
|---|---|---|---|---|---|---|---|---|
| Swimming | 17.473 | <0.001 | 22.670 | <0.001 | 2.586 | 0.072 | 24.183 | <0.001 |
| CPSM | 1.861 | 0.156 | 2.797 | 0.056 | 6.033 | 0.002 | 7.731 | 0.001 |
| CPSM × swimming | 0.405 | 0.923 | 3.804 | 0.002 | 13.348 | <0.001 | 8.524 | <0.001 |