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Journal of Chinese Integrative Medicine ›› 2011, Vol. 9 ›› Issue (9): 941-947.doi: 10.3736/jcim20110904

• Methodology • Previous Articles     Next Articles

Ridit analysis of experimental data from animal models of yang deficiency induced by different doses of hydrocortisone

Qian Zhao1, Rui Jin1, Bing Zhang1(), Sen-mao Liu2, Min Li1, Xin Liu1, Lian-zhen Li1, Qian Zhang1   

  1. 1. School of Chinese Material Medica, Beijing University of Chinese Medicine, Beijing 100102, China
    2. School of Mathematical Sciences, Peking University, Beijing 100871, China
  • Received:2011-05-10 Accepted:2011-05-31 Online:2011-09-20 Published:2011-09-15
  • Contact: Zhang Bing E-mail:zhangbing6@263.net

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Objective: Hydrocortisone-induced yang-deficiency animal model has now become the generally accepted model of yang deficiency. However, assessing the most appropriate dose of hydrocortisone is a long-term challenge. For analyzing the modeling dose, the authors have built several kinds of yang-deficiency models induced by hydrocortisone at different doses, and analyzed the experimental data with various mathematical statistical methods. In order to discuss the effects of the modeling dose on the basis of previous research, the authors introduced Ridit analysis.

Methods: After categorizing 27 batches of experiments with four different doses (including 2.5, 3.75, 10 and 20 mg/kg), the data were standardized and the data type was changed to meet the needs of subsequent calculations. Then, by using Ridit analysis, the authors compared the variation of 19 biochemistry indexes involving nervous-endocrine system, immune system, metabolic system and the function of the liver and kidney, so as to analyze the similarities and differences of those yang-deficiency models mentioned above. The effects of modeling dose were then discussed.

Results: With regard to the overall state of the animal model, the difference between the models induced by different doses of hydrocortisone (2.5, 3.75, 10 and 20 mg/kg) showed no statistical significance, indicating that differences in hydrocortisone dose barely lead to significant changes in yang-deficiency models. For the trends of changing in different indexes, indexes had different performances when the doses differs: gonad indexes (estradiol and testosterone) showed better performance in 2.5 mg/kg group, immunological indexes (immunoglobulin M and immunoglobulin G) showed better performance in 3.75 mg/kg group and metabolic indexes (triglyceride and total cholesterol) showed better performance in 10 mg/kg group, etc. This indicates that the dose of hydrocortisone should be determined according to the research purposes.

Conclusion: Ridit analysis can be used as an integration analysis method for animal models of yang deficiency induced by hydrocortisone at different doses.

Key words: Ridit analysis, yang deficiency, hydrocortisone, disease models, animal, data interpretation, statistical, rats

Table 1

Amount of every experiment"

Dose (mg/kg) Batch (n) Animal number of each batch (n)
2.5 6 20, 10, 12, 12, 12, 12
3.75 6 12, 12, 10, 10, 10, 12
10 4 10, 10, 10, 10
20 11 10 ,10, 10, 9, 12 ,12, 10, 9, 10, 12, 12

Table 2

Level frequency of albumin"

Interval Frequency of various doses Sum
2.5
(mg/kg)		 3.75
(mg/kg)		 10
(mg/kg)		 20
(mg/kg)
[0.5, 1) 3 4 4 9 20
[0.1, 0.5) 29 24 8 37 98
(–0.1, 0.1) 17 16 8 25 66
[–0.1, –0.5) 23 19 20 33 95
[–0.5, –1) 6 3 0 2 11
Sum 78 66 40 96 290

Table 3

Ridit value calculation of standard group"

Interval a b c d e
[0.5, 1) 20 10.0 10.0 0.035
[0.1, 0.5) 98 49.0 20 69.0 0.238
(–0.1, 0.1) 66 33.0 118 151.0 0.521
[–0.1, –0.5) 95 47.5 184 231.5 0.798
[–0.5, –1) 11 5.5 279 284.5 0.981
Sum 290

Table 4

R value and 95% confidence interval of albumin in different groups"

Group R value 95% confidence interval
2.5 mg/kg 0.514 0.450 1–0.578 2
3.75 mg/kg 0.489 0.419 6–0.558 9
10 mg/kg 0.554 0.464 8–0.643 8
20 mg/kg 0.476 0.420 9–0.530 8

Table 5

$\overline{R_{k}}$ value"

Index $\overline{R_{k}}$ of various doses P value
2.5 (mg/kg) 3.75 (mg/kg) 10 (mg/kg) 20 (mg/kg)
Triiodothyronine 0.423 0.505 0.645 0.499 0.001
Estradiol 0.553 0.520 0.347 0.508 0.003
Alanine aminotransferase 0.494 0.414 0.567 0.541 0.021
Blood urea nitrogen 0.469 0.601 0.504 0.474 0.062
Immunoglobulin G 0.463 0.622 0.502 0.483 0.072
Lactic dehydrogenase 0.446 0.563 0.540 0.492 0.101
Thyroxne 0.559 0.483 0.499 0.469 0.190
Testosterone 0.523 0.434 0.500 0.518 0.278
Glucose 0.543 0.459 0.518 0.489 0.341
Total protein 0.545 0.484 0.451 0.496 0.355
Complement 3 0.445 0.503 0.543 0.510 0.394
Albumin 0.514 0.489 0.554 0.476 0.487
Uric acid 0.506 0.528 0.444 0.499 0.542
Immunoglobulin M 0.472 0.560 0.514 0.489 0.560
Total cholesterol 0.520 0.485 0.465 0.507 0.751
Triacylglycerol 0.503 0.517 0.526 0.481 0.792
Aspartate aminotransferase 0.479 0.520 0.521 0.492 0.800
Corticosteroid 0.508 0.505 0.517 0.486 0.924
Creatinine 0.495 0.487 0.523 0.503 0.940

Table 6

Index distribution"

Index Distribution
[0.5, 1) [0.1, 0.5) (–0.1, 0.1) [–0.1, –0.5) [–0.5, –1)
Albumin 20 98 66 95 11
Blood urea nitrogen 23 73 65 86 11
Complement 3 15 83 50 75 19
Corticosteroid 34 76 69 110 11
Creatinine 25 97 50 67 7
Estradiol 20 88 67 105 10
Glucose 13 84 72 109 22
Aspartate aminotransferase 19 78 65 71 12
Alanine aminotransferase 23 73 58 88 16
Immunoglobulin G 12 71 64 80 15
Immunoglobulin M 25 68 53 78 8
Lactic dehydrogenase 25 108 53 89 15
Testosterone 28 58 71 117 4
Triiodothyronine 13 82 78 106 21
Thyroxne 24 65 71 117 13
Total cholesterol 26 86 77 104 7
Triacylglycerol 31 58 80 119 2
Total protein 23 109 76 80 12
Uric acid 26 61 81 105 7
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