蒙特卡罗模拟多束光辐照下生物组织中的光吸收分布

用蒙特卡罗方法模拟了均匀分布光和高斯分布光在生物组织内的传播。通过比较单束以及多束均匀分布光和高斯分布光照射下组织内的光子能量分布规律,分析了不同光源和光斑大小对光吸收分布的影响。结果表明:与均匀光束比较,高斯光束辐照时,激光能量较为集中,但侧向传播范围较窄。在总功率相同的情况下,使用单束大功率宽光源与多束功率较小的小光斑光源均能明显地增大光的侧向传播距离,但使用多束功率较小的小光斑光辐照时生物组织中的最大光吸收率增大。多束组合光源光束间距对光吸收分布影响很大。     

生物组织中有限束宽光吸收的蒙特卡罗模拟

用蒙特卡罗法模拟了有限束宽均匀分布和高斯分布光在生物组织中的传播,分析了生物组织的光学参数及光源特性对光吸收分子的影响,结果表明：只要有效光吸收系数增加,最大光吸收率就会增加,光的侧向传输能力主要依赖于光的有效散射,光束宽度增加,辐照范围加宽,高斯光束的吸收分布的梯度更大。     

肾组织脱水对组织光学吸收和散射特性的影响

研究肾组织脱水对组织的吸收和散射特性的影响,实验利用带积分球附件的分光光度计和采用反向倍增法获取组织对532 nm和1064 nm波长的吸收和散射特性。结果表明:在37℃下脱水的肾组织对532 nm和1064 nm的吸收系数和约化散射系数都是随着脱水率的增大而明显地增大的,在37℃下脱水的肾组织对532 nm和1064 nm的吸收系数均明显地较自然的肾组织对相应波长的吸收系数要大,而在37℃下脱水的肾组织对532 nm和1064 nm的约化散射系数也明显地较自然的肾组织对相应波长的约化散射系数要大,在相同脱水率下的肾组织对于532 nm的吸收系数和约化散射系数都明显地较其对1064 nm的吸收系数和约化散射系数要大。研究结果提示,组织脱水、脱水的温度和脱水时间是影响肾组织的吸收和散射特性的重要因素。     

热作用对肾组织光传输特性的影响

研究了热作用下的肾组织对532 nm和1064 nm波长的光学特性的影响。实验利用带积分球附件的分光光度计和采用反向倍增法获取组织的光学特性,结果表明热作用下的肾组织对532 nm和1 064 nm的吸收系数和约化散射系数都是随着加热温度的变化而变化的。在25℃到80℃的温度范围内,肾组织对532 nm的吸收系数和约化散射系数都分别显著地较其对1064 nm的吸收系数和约化散射系数要大。其对532 nm和1 064 nm的吸收系数的最大值都在80℃,其值分别为1.121 mm-1和0.269 mm-1,最小值都在25℃,其值分别为0.131 mm-1和0.019 mm-1。其对532 nm和1 064 nm的约化散射系数的最大值分别在80℃和70℃,其值分别为2.905 mm-1和0.705 mm-1,最小值都在25℃,其值分别为0.391 mm-1和0.184 mm-1。研究结果提示,热作用的温度是影响肾组织的吸收和散射特性的重要因素。     

生物组织X光照片的层析合成法的研究——Ⅱ.优化层片特性的模拟

在圆层析合成法中,我们提出了两种X光扫描采样的方法.一种是以零阶贝塞尔函数为窗函数,采用单个的采样园锥.另一种是以圆长球函数为窗函数,用Fourier-Bessel级数展开的系数为权,采用多重采样圆锥.在适当选择窗函数的参数下,给出了采样几何学的设计及对不同窗函数的衰减特性进行了模拟.     

热作用致良性前列腺增生组织对KTP/Nd:YAG激光的吸收和散射特性变化

研究了热作用下的良性前列腺增生(BPH)组织对532 nm的KTP和1064 nm的Nd:YAG激光的吸收和散射特性的变化及其差异,实验采用双积分球测量系统以及反向倍增法获取BPH组织的吸收和散射特性。结果表明:热作用下的BPH组织对532 nm和1064 nm的吸收系数和约化散射系数都是随着加热温度的变化而变化的,在20℃到80℃的温度范围内,BPH组织对532 nm的吸收系数和约化散射系数都分别显著地较其对1064 nm的吸收系数和约化散射系数要大,其对532 nm和1064 nm的吸收系数的最大值都在20℃,其值分别为1.663 mm-1和0.127 mm-1,最小值分别在50℃和70℃,其值分别为0.864 mm-1和0.034 mm-1,其对532 nm和1064 nm的吸收系数的最大差异在70℃,其值为2647%,其对532 nm和1064 nm的约化散射系数的最大值都在80℃,其值分别为2.036 mm-1和1.421 mm-1,最小值分别在50℃和70℃,其值分别为1.499 mm-1和0.246 mm-1,其对532 nm和1064 nm的约化散射系数的最大差异在70℃,其值为555%,在70℃的热作用下BPH组织达到完全热凝固,其对532 nm和1064 nm的吸收和散射特性的差异达到最大值。     

多层螺旋CT三维重建在鼻骨骨折中的诊断价值

鼻骨位于面部中央,且突出于面部,骨质菲薄,承受力差,很容易受外力撞击而受伤,严重者可引起鼻部塌陷及功能障碍,如不及时做出准确诊断,不仅耽误治疗,而且容易引起医疗及法律上的纠纷。多层螺旋CT重建处理后可以直观准确地显示骨折线、骨折移位及骨折细节,为临床医生及法医提供更明确的诊断和依据。现就多层螺旋CT在鼻骨骨折中的临床应用价值探讨分析如下。     

组织模型偏振散射光谱特性研究

结合偏振门技术和米氏散射理论,建立了组织模型的偏振散射差分光谱理论模型.计算分析了粒子群的平均尺寸、相对折射率变化时后向偏振散射差分光谱的特征.结果表明,利用偏振门技术测量的差分光谱主要是来自表层粒子的光信号,偏振散射差分光谱对粒子平均尺寸及相对折射率的变化比较敏感,随着粒子平均尺寸的增加,光谱振荡频率将增加,而随着相对折射率的减小,光谱的振幅减小,且差分光强值减小.该方法对于早期癌症检测具有潜在应用意义.     

多层生物介质传感器的特性研究

目的 多层生物介质的生物传感器被广泛应用于各大领域,其检测特性对于传感器优劣的评估尤为重要。本文目的在于量化表征多层生物介质的电学特征。方法 基于生物电阻抗谱技术来探究多层生物介质的电化学阻抗谱特性,并结合保角映射的方法来量化表征多层生物介质,阐明其对阻抗的影响规律,继而为生物传感器的研制与开发提供理论基础。有效提取各生物介质层修饰后电阻抗参数(Z^*),从而量化表征多层生物介质层的电阻抗谱特性。结果 对多层模型进行了理论计算并构建了相关试验测试系统,研究结果表明,随着生物介质层的逐步修饰,检测区域电阻抗参数(Z^*)在f=0.1～50 MHz下持续上升,理论计算结果趋势与试验结果趋势较好吻合,论证了此理论计算方法的正确性。结论 本文证实了可根据生物电阻抗谱和保角映射方法量化表征多层生物介质的电阻抗谱特性,对生物传感器的研制与开发有一定的实用价值。     

Kubelka-Munk 模型下的兔血管对He-Cd激光的散射与吸收特性

测量了兔动脉和静脉夺He-Cd激光的反射和透射传输特性。实验采用两积分球系统及波长为441.6nm的He-Cd激光器,并根据测量数据及采用Kubelka-Munk模型分析和计算了兔动脉和静脉组织对该波长激光的吸收系统、散射系数及总的光强I（x）及前向散射通量i(x)和后向散射通量j(x）随厚度的变化情况。结果表明,兔动脉和静脉的温反射率和透射率有明显差别,而且,动脉对激光的吸收系数明显较静脉的要小,耐动脉对激光的散射系数却明显较静脉的要大,在动脉和静脉组织中总的光强I(x)及前向散射通量i(x)和后向散射通量j(x)随厚度的变化情况也有明显的区别。     

All-Atom Monte Carlo Approach to Protein-Peptide Binding

We develop a procedure for exploring the free energy landscape of protein-peptide binding at atomic detail and apply it to PDZ domain-peptide interactions. The procedure involves soft constraints on receptor proteins providing limited chain flexibility, including backbone motions. Peptide chains are left fully flexible and kept in spatial proximity of the protein through periodic boundary conditions. By extensive Monte Carlo simulations, full representative conformational ensembles at temperatures where bound and unbound states coexist are obtained. To make this approach computationally feasible, we develop an effective all-atom energy function centering on hydrophobicity, hydrogen bonding, and electrostatic interactions. Our initial focus is a set of 11 PDZ domain-peptide pairs with experimentally determined complex structures. Minimum-energy conformations are found to be highly similar to the respective native structures in eight of the cases (all-atom peptide RMSDs < 6 Å). Having achieved that, we turn to a more complete characterization of the bound peptide state through a clustering scheme applied on the full ensembles of peptide structures. We find a significant diversity among bound peptide conformations for several PDZ domains, in particular involving the N terminal side of the peptide chains. Our computational model is then tested further on a set of nine PDZ domain-peptide pairs where the peptides are not originally present in the experimentally determined structures. We find a similar success rate in terms of the nativeness of minimum-energy conformations. Finally, we investigate the ability of our approach to capture variations in binding affinities for different peptide sequences. This is done in particular for a set of related sequences binding to the third PDZ domain of PSD-95 with encouraging results.     

A Monte Carlo Study of the Relative Stability of Protein Helical Forms

We present simulation results on a simple model to describe the hydrogen bonding in proteins with helical structures. The approximation distinguishes between ! helices, where each amino acid interacts with another one located four residues apart, 3 10 structures, where the number of amino acids in between is three, and the ? arrangement, in which that number is five. We found that the main features of the system are determined by the most stable structure (the ! helix) and that the other type of hydrogen bonds appears just below the denaturation temperature of the peptide. The probability of finding a 3 10 -type bond is greater at the beginning or at the end of the peptide chain, irrespectively of its length, while in short peptides the existence of those bonds increases appreciably the denaturation temperature, promoting stability. On the other hand, the temperature of denaturation decreases with the length of the peptide to reach a value independent of the number of amino acid residues.     

Monte Carlo Comparison of Multiple Comparison Procedures

Seven procedures of multiple comparisons: Tukey, Scheffé, Bonferroni, Studentized Maximum Modulus, Duncan, Newman-Keuls and F are compared with respect to the probability of the correct decision. Monte Carlo simulation shows that there is no the best procedure. AMS 1985 Subject Classification: 62 J 15.     

Bayesian phylogeny analysis via stochastic approximation Monte Carlo

Monte Carlo methods have received much attention in the recent literature of phylogeny analysis. However, the conventional Markov chain Monte Carlo algorithms, such as the Metropolis–Hastings algorithm, tend to get trapped in a local mode in simulating from the posterior distribution of phylogenetic trees, rendering the inference ineffective. In this paper, we apply an advanced Monte Carlo algorithm, the stochastic approximation Monte Carlo algorithm, to Bayesian phylogeny analysis. Our method is compared with two popular Bayesian phylogeny software, BAMBE and MrBayes, on simulated and real datasets. The numerical results indicate that our method outperforms BAMBE and MrBayes. Among the three methods, SAMC produces the consensus trees which have the highest similarity to the true trees, and the model parameter estimates which have the smallest mean square errors, but costs the least CPU time.     

Monte Carlo Simulation of Nonionic Surfactants at the Oil-Water Interface

Abstract

A Monte Carlo simulation method has been developed for modelling amphiphiles at an oil-water interface. Properties are calculated for the mixture water, benzene and tetraoxyethylene glycol dodecyl ether.     

Folding small proteins via annealing stochastic approximation Monte Carlo

Recently, the stochastic approximation Monte Carlo algorithm has been proposed by Liang et al. (2007) as a general-purpose stochastic optimization and simulation algorithm. An annealing version of this algorithm was developed for real small protein folding problems. The numerical results indicate that it outperforms simulated annealing and conventional Monte Carlo algorithms as a stochastic optimization algorithm. We also propose one method for the use of secondary structures in protein folding. The predicted protein structures are rather close to the true structures.