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Research of Quantitative Relation between Insulin and Bone Mechanical Characteristics of Type¢ñdiabet

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Tutor: GuoTongTong
School: Harbin Institute of Technology
Course: Mechanics
Keywords: bone metabolism,bone reconstruction,bone reconstruction thresholdequation,bioche
CLC: Q66
Type: Master's thesis
Year:  2013
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Bone metabolic diseases are bone matrix, bone cell metabolism disorderscaused by abnormal calcium, phosphorus and other minerals in the bone tissue,as well as abnormal osteoblast or osteoclast activity. Scholars at home andabroad believe that biomechanical factors can influence bone metabolic processof the body. Change of bone metabolism related biochemical indicators willcause the change of bone mechanical properties, leading to bone metabolicdisease, such as osteoporosis, rheumatoid arthritis. There is a qualitativerelationship between bone metabolic biochemical indicators and bonemechanical properties, and has been verified in relevant research at home andabroad. However, so far, there is still no study of quantitative relationshipbetween bone metabolic biochemical indicators and bone mechanical properties.The purpose of this article is to establish a "dynamic" quantitative relationshipbetween a variety of biochemical index and bone mechanical properties, so as toearly predict and prevent the happening of disease.Based on the bone reconstruction theory, this paper uses two main methodsthat animal experiments and finite element simulation. The first step putsforward17biochemical indicators clearly affect bone mechanical properti es; thesecond step gets quantitative data of17biochemical indexes affect bonemetabolism respectively, from a large number of relevant literature, at the sametime, records the content of17biological markers content in the target mouse atthe starting and ending point of experiment, which study the influence of17biochemical indicators on bone metabolism; the third step calculates the bonereconstruction threshold corresponds to every biological¡¯ t on bone mineraldensity, using a method of combining every biological marker¡¯ effect on bonemineral density with bone reconstruction equation; based on the multiple linearregression model, the fourth step establishs a quantitative relationship between avariety of biochemical index and bone mechanical properties, gets the bonereconstruction threshold linear regression equation of17biological markers afterintroducing bone reconstruction threshold with respect to every biologicalmarker¡¯ effect on bone mineral density, and change of every biological markercontent in target mouse, into the proposed bone reconstruction threshold equation;the fifth step uses finite element simulation to validate the reasonableness ofobtained bone reconstruction threshold equation.The experimental data of validating justifiability of obtained bone reconstruction threshold equation used by this paper is bone mineral density of11months SD rats after suffering from type I diabetes0,3,6,9weeks, whichwas done at Tsinghua University Shenzhen Graduate School; the finite elementmodel is porous bone trabecular model, established by the right femur of11month-old healthy SD rats in this experiment. The first step uses the obtainedbone reconstruction threshold equation to get a bone reconstruction thresholdcorresponding to type I diabetes SD rats; the second step writes and runs thebone reconstruction procedure; based on bone reconstruction simulation, thethird step gets bone mineral density of normal rats under the bone reconstructionthreshold corresponding to type I diabetes rats, and it is0.4921g/cm3; the fourthstep compares the bone mineral density of finite element simulation to that oftype I diabetes rats, which suffering from type I diabetes9weeks, makesdiscussion and analysis, and draws the conclusion that the proposed bonereconstruction threshold equation in this paper is reasonable.This paper puts forward the quantitative relationship between bonemetabolic biochemical indicators and bone tissue mechanical properities for thefirst time, and proposes the bone reconstruction threshold linear regressionequation about17biochemical indicators, which rationality is validated by finiteelement simulation. These results can provide certain theoretical support to theprediction and prevention of related diseases.
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