Influence of foot excitation and shin posture on the vibration behavior of the entire spine inside a seated human body

Due to ethical issues and simplification of traditional biomechanical models, experimental methods and traditional computer methods were difficult to quantify the effects of foot excitation and shin posture on vibration behavior of the entire spine inside a seated human body under vertical whole-body vibration. This study developed and verified different three-dimensional (3D) finite element (FE) models of seated human body with detailed anatomical structure under the biomechanical characteristics to predict vibration behavior of the entire spine inside a seated human body with different foot excitation (with and without vibration) and shin posture (vertical and tilt posture). Random response analysis was performed to study the transmissibility of the entire spine to seat under vertical white noise excitation between 0 and 20 Hz at 0.5 m/s2 r.m.s. The results showed that although the foot excitation could reduce the fore-aft transmissibility in the cervical spine (23% reduction), it could significantly increase that in the lumbar spine (52% increase), which resulted in complex alternating stresses at lumbar spine and made the lumbar spine more vulnerable to injury in long-term vibration environment. Moreover, the shin tilt posture made the maximum fore-aft transmissibility in the lumbar spine move to the upper lumbar spine. The study provided new insights into the influence of foot excitation and shin posture on the vibration behavior of the entire spine inside a seated human body. Foot excitation exposed the lumbar spine to complex alternating stresses and made it more vulnerable to injury in long-term whole body vibration.

Exploring the Bacterial Impact on Cholesterol Cycle: A Numerical Study

High blood cholesterol levels are often associated with cardiovascular diseases. Therapeutic strategies, targeting different functions involved in cholesterol transport or synthesis, were developed to control cholesterolemia in human. However, the gut microbiota is also involved in cholesterol regulation by direct biotransformation of luminal cholesterol or conversion of bile salts, opening the way to the design of new strategies to manage cholesterol level. In this report, we developed for the first time a whole-body human model of cholesterol metabolism including the gut microbiota in order to investigate the relative impact of host and microbial pathways. We first used an animal model to investigate the ingested cholesterol distribution in vivo. Then, using in vitro bacterial growth experiments and metabolite measurements, we modeled the population dynamics of bacterial strains in the presence of cholesterol or bile salts, together with their bioconversion function. Next, after correct rescaling to mimic the activity of a complex microbiota, we developed a whole body model of cholesterol metabolism integrating host and microbiota mechanisms. This global model was validated with the animal experiments. Finally, the model was numerically explored to give a further insight into the different flux involved in cholesterol turn-over. According to this model, bacterial pathways appear as an important driver of cholesterol regulation, reinforcing the need for development of novel "bacteria-based" strategies for cholesterol management.

Uncertainty Analysis of the Core Body Temperature Under Thermal and Physical Stress Using a Three-Dimensional Whole Body Model

Heat stress experienced by firefighters is a common consequence of extreme firefighting activity. In order to avoid the adverse health conditions due to uncompensable heat stress, the prediction and monitoring of the thermal response of firefighters is critical. Tissue properties, among other parameters, are known to vary between individuals and influence the prediction of thermal response. Further, measurement of tissue properties of each firefighter is not practical. Therefore, in this study, we developed a whole body computational model to evaluate the effect of variability (uncertainty) in tissue parameters on the thermal response of a firefighter during firefighting. Modifications were made to an existing human whole body computational model, developed in our lab, for conducting transient thermal analysis for a firefighting scenario. In conjunction with nominal (baseline) tissue parameters obtained from literature, and physiologic conditions from a firefighting drill, the Pennes bioheat and energy balance equations were solved to obtain the core body temperature of a firefighter. Subsequently, the uncertainty in core body temperature due to variability in the tissue parameters (input parameters), metabolic rate, specific heat, density, and thermal conductivity was computed using the sensitivity coefficient method. On comparing the individual effect of tissue parameters on the uncertainty in core body temperature, the metabolic rate had the highest contribution (within ±0.20°C) followed by specific heat (within ±0.10°C), density (within ±0.07°C), and finally thermal conductivity (within ±0.01 °C). A maximum overall uncertainty of ±0.23 °C in the core body temperature was observed due to the combined uncertainty in the tissue parameters. Thus, the model results can be used to effectively predict a realistic range of thermal response of the firefighters during firefighting or similar activities.

BioDMET: a physiologically based pharmacokinetic simulation tool for assessing proposed solutions to complex biological problems

We developed a detailed, whole-body physiologically based pharmacokinetic (PBPK) modeling tool for calculating the distribution of pharmaceutical agents in the various tissues and organs of a human or animal as a function of time. Ordinary differential equations (ODEs) represent the circulation of body fluids through organs and tissues at the macroscopic level, and the biological transport mechanisms and biotransformations within cells and their organelles at the molecular scale. Each major organ in the body is modeled as composed of one or more tissues. Tissues are made up of cells and fluid spaces. The model accounts for the circulation of arterial and venous blood as well as lymph. Since its development was fueled by the need to accurately predict the pharmacokinetic properties of imaging agents, BioDMET is more complex than most PBPK models. The anatomical details of the model are important for the imaging simulation endpoints. Model complexity has also been crucial for quickly adapting the tool to different problems without the need to generate a new model for every problem. When simpler models are preferred, the non-critical compartments can be dynamically collapsed to reduce unnecessary complexity. BioDMET has been used for imaging feasibility calculations in oncology, neurology, cardiology, and diabetes. For this purpose, the time concentration data generated by the model is inputted into a physics-based image simulator to establish imageability criteria. These are then used to define agent and physiology property ranges required for successful imaging. BioDMET has lately been adapted to aid the development of antimicrobial therapeutics. Given a range of built-in features and its inherent flexibility to customization, the model can be used to study a variety of pharmacokinetic and pharmacodynamic problems such as the effects of inter-individual differences and disease-states on drug pharmacokinetics and pharmacodynamics, dosing optimization, and inter-species scaling. While developing a tool to aid imaging agent and drug development, we aimed at accelerating the acceptance and broad use of PBPK modeling by providing a free mechanistic PBPK software that is user friendly, easy to adapt to a wide range of problems even by non-programmers, provided with ready-to-use parameterized models and benchmarking data collected from the peer-reviewed literature.