Session A38: Focus Session: Biocompatibility

The quantification of biocompatibility: toward a new definition

Implantable medical devices, and the biomaterials that comprise them, form a {\$}100B business worldwide. Medical devices save lives and/or improve the quality of life for millions. Tissue engineering also makes extensive use of biomaterials -- biomaterials are an enabling technology for tissue engineering. A central word to understanding the effectiveness of such materials and devices is biocompatibility. The word ``biocompatible'' is widely used in reference to biomaterials and medical devices and most everyone has some value understanding of its meaning. Many formal definitions have been proposed for this word, but it is still largely used in an imprecise manner. Four descriptions or definitions of biocompatibility will be reviewed: a widely adopted definition from a consensus conference, a surgeon's perspective on this word, the regulatory agency view and the factors that clearly influence biocompatibility. In this talk, the classical definition of biocompatibility will be contrasted to a newer definition embracing molecular concepts and the understanding of normal wound healing. The biological data on the \textit{in vivo} healing responses of mammals to implants will be described. A strategy to improve the healing of biomaterials will be presented. It is based upon surface molecular engineering. First, non-specific protein adsorption must be inhibited. Strategies to achieve this design parameter will be presented. Then methods to deliver the specific protein signals will be addressed. Matricellular proteins such as osteopontin, thrombospondin 2 and SPARC will be introduced with an emphasis on exploiting the special reactivity of such proteins. A discussion of the influence of surface textures and porosities will also be presented. Finally a new scheme based upon macrophage phenotypic pathways will be proposed that may allow a quantitative measure of extent of biocompatibility.   

Biocompatibility of implantable biomedical devices

Biomedical devices have been broadly used to treat human disease, especially chronic diseases where pharmaceuticals are less effective. Heart valve and artificial joint are examples. Biomedical devices perform by delivering therapies such as electric stimulations, mechanical supports and biological actions. While the uses of biomedical devices are highly successful they can trigger adverse biological reactions as well. The property that medical devices perform with intended functions but not causing unacceptable adverse effects was called biocompatibility in the early time. As our understanding of biomaterial-biological interactions getting broader, biocompatibility has more meanings. In this talk, I will present some adverse biological reactions observed with implantable biomedical devices. Among them are surface fouling of implantable sensors, calcification with vascular devices, restenosis with stents, foreign particle migration and mechanical fractures of devices due to inflammation reactions. While these effects are repeatable, there are very few quantitative data and theories to define them. The purpose of this presentation is to introduce this biocompatibility concept to biophysicists to stimulate research interests at different angles. An open question is how to quantitatively understand the biocompatibility that, like many other biological processes, has not been quantified experimentally.   

A Gaussian theory of the response of heart frequency to ventilator

Extensive studies suggest that there exists a coupling between the human heart and respiration. We constructed a simple Gaussian Markovian propagation model to describe the influence of ventilator on patient's heart frequency. We show that for sedated patients, the theory captures the essential correlations between heart rate and induced ventilation during patient's spontaneous breathing and by so doing successfully predicts the response of heart rate to application of the ventilator. We also discuss the cases in which the theory fails, all of which were none sedated patients. We believe sedation disconnects high brain activities from cardiac and respiratory functions leaving just the primitive response.   

Synchronization of Cardio-Respiratory Dynamics in Critically Ill Patients.

We studied changes in cardio-respiratory synchronization and dynamics of cardiovascular system during transition from mechanical ventilation to spontaneous respiration in critically ill patients. This observational study exploits a standard clinical practice---the spontaneous breathing trial (SBT). The SBT consists of a period of mechanical ventilation, followed by a period of spontaneous breathing, followed by resumption of mechanical ventilation. We collected continuous respiratory, cardiac (EKG), and blood pressure signals of mechanically ventilated patients before, during and after SBT. The data were analyzed by means of spectral analysis, phase dynamics, and entropy measures. Mechanical ventilation appears to affect not only the lungs but also the cardiac and vascular systems. Spontaneous cardiovascular rhythms are entrained by the mechanical ventilator and are drawn into synchrony. Sudden interruption of mechanical ventilation causes gross desynchronization, which is restored by reinstitution of mechanical ventilation. The data suggest (1) therapies intended to support one organ system may propagate unanticipated effects to other organ systems and (2) sustained therapies may adversely affect recovery of normal organ system interactions.   

Crystal Structure Properties of Human Teeth as a Function of Age

We report on crystal structure studies of human teeth as a function of age in the range of 5-87 years. The crystallinity of the hydroxyapatite, which is the main dental mineral phase in teeth, decreases with age in a systematic way starting at $\sim $ 40 years old teeth. The average crystallite size decreases from $\sim $40 nm to $\sim $12 nm in the age range 30 to 60 years old and then it remains practically constant. The a-lattice constant decreases in a similar systematic way and it is associated with the carbonate content of the tooth. Development of the secondary phases with the tooth-age questions the crystallographic structure of the dental apatite. FTIR spectroscopy reveals both types of carbonate substitution, but B-type substitution is greater by a factor of 4 than the A-type. An increase of the carbonate content with the tooth age is also deduced from the ratio of the v$_{2}$ CO$_{3}$ to the v$_{1}$ PO$_{4}$ IR modes from 17 to 70 years of age. TGA measurements confirm the results of both experimental methods.   

Procedure to Measure Effect of Excess Body Mass on Musculoskeleture: II. Implementation

There are a number of ways in which the musculoskeletal system can be affected by excess body mass. One representative quantity for these is the torque exerted on the spinal column about a horizontal lateral axis; hence, its use as an illustrative mechanical indicator in the research reported here. Values of the torque are determined for all subjects in an exceptionally broad adult population that was developed during a companion study. Increases in body mass index caused nearly uniform increases in torque for all height percentiles in both sexes. Overweight individuals had torques that were 35 and 30 percent greater (females and males, respectively) than those for healthy individuals of the same height. Corresponding increases for obese individuals occurred at the much higher levels of 75 and 66 percent. Any resulting musculosketal damage from this is in addition to other problems arising from obesity, such as heart disease, diabetes, and high blood pressure. However, whereas the latter can be treated or managed with medication, some facets of the former might be irreversible and/or irremediable.   

Extremely high paw accelerations during paw shake in the cat: A mechanism revealed by computer simulations

Paw shake response is a reflex aimed at removing an irritating stimulus from the paw by imparting to it high periodic accelerations (\underline {$>$}10 g). These values seem too high to be produced by distal muscles exclusively. According to Prilutsky et al. (2005), resultant hip moments during paw shake are much greater than distal joint moments, whereas distal joint velocities and accelerations exceed those of the proximal joints. The goal of this study was to examine how proximal hip muscles could contribute to high paw accelerations. Using software AnimatLab, we developed a 2D model of the cat hindlimb consisting of 5 rigid segments with 4 hinge joints and 11 muscles spanning all joints. The muscles were assumed passive except for those crossing the hip. When in simulations the hip muscles were reciprocally activated to periodically flex and extend the hip joint with a typical paw shake frequency of 10 Hz, the hindlimb segments demonstrated motion resembling experimental observations: linear and angular velocities and accelerations of the distal segments exceeded several fold the values of the proximal segments. Simulated paw shake revealed features of a whip-like motion.   

Is movement organization in cat paw shake response optimal?

Animal musculoskeletal systems are highly redundant: they have more kinematic degrees of freedom and muscles than strictly necessary to execute a given motor task. Such redundancy gives the animal many choices in selecting kinematic and muscle activity patterns to achieve movement goal. Given a stereotypic execution of cat paw shake response (very fast periodic oscillations of the paw) among deferent cats despite the motor redundancy, we hypothesized that the movement strategy in this reflex is optimal. The goal of this study was to test several physiologically plausible cost functions, optimizations of which could explain the functional significance of chosen movement strategy in paw shake. A 2D, 5 degrees-of-freedom forward dynamics cat hindlimb model was developed. The model has 5 body segments, 4 frictionless hinge joints, 11 muscles with realistic muscle and activation dynamics. Muscle activations were computed using a simulated annealing optimization algorithm and several cost functions. The best match between simulated and experimentally recorded muscle activity patterns was obtained when peak paw acceleration was maximized.