Elevated gastrocnemius forces compensate for decreased hamstrings forces during the weight-acceptance phase of single-leg jump landing: implications for anterior cruciate ligament injury risk

Approximately 320,000 anterior cruciate ligament (ACL) injuries in the United States each year are non-contact injuries, with many occurring during a single-leg jump landing. To reduce ACL injury risk, one option is to improve muscle strength and/or the activation of muscles crossing the knee under elevated external loading. This study?s purpose was to characterize the relative force production of the muscles supporting the knee during the weight-acceptance (WA) phase of single-leg jump landing and investigate the gastrocnemii forces compared to the hamstrings forces. Amateur male Western Australian Rules Football players completed a single-leg jump landing protocol and six participants were randomly chosen for further modeling and simulation. A three-dimensional, 14-segment, 37 degree-of-freedom, 92 muscle-tendon actuated model was created for each participant in OpenSim. Computed muscle control was used to generate 12 muscle-driven simulations, 2 trials per participant, of the WA phase of single-leg jump landing. A one-way ANOVA and Tukey post-hoc analysis showed both the quadriceps and gastrocnemii muscle force estimates were significantly greater than the hamstrings (p<0.001). Elevated gastrocnemii forces corresponded with increased joint compression and lower ACL forces. The elevated quadriceps and gastrocnemii forces during landing may represent a generalized muscle strategy to increase knee joint stiffness, protecting the knee and ACL from external knee loading and injury risk. These results contribute to our understanding of how muscle?s function during single-leg jump landing and should serve as the foundation for novel muscle-targeted training intervention programs aimed to reduce ACL injuries in sport.     

Computational fluid dynamics endpoints for assessment of adenotonsillectomy outcome in obese children with obstructive sleep apnea syndrome

Background

Improvements in obstructive sleep apnea syndrome (OSAS) severity may be associated with improved pharyngeal fluid mechanics following adenotonsillectomy (AT). The study objective is to use image-based computational fluid dynamics (CFD) to model changes in pharyngeal pressures after AT, in obese children with OSAS and adenotonsillar hypertrophy.

Methods

Three-dimensional models of the upper airway from nares to trachea, before and after AT, were derived from magnetic resonance images obtained during wakefulness, in a cohort of 10 obese children with OSAS. Velocity, pressure, and turbulence fields during peak tidal inspiratory flow were computed using commercial software. CFD endpoints were correlated with polysomnography endpoints before and after AT using Spearman?s rank correlation (r_s).

Results

Apnea hypopnea index (AHI) decreases after AT was strongly correlated with reduction in maximum pressure drop (dP_TAmax) in the region where tonsils and adenoid constrict the pharynx (r_s=0.78, P=0.011), and with decrease of the ratio of dP_TAmax to flow rate (r_s=0.82, P=0.006). Correlations of AHI decrease to anatomy, negative pressure in the overlap region (including nasal flow resistance), or pressure drop through the entire pharynx, were not significant. In a subgroup of subjects with more than 10% improvement in AHI, correlations between flow variables and AHI decrease were stronger than in all subjects.

Conclusions

The correlation between change in dP_TAmax and improved AHI suggests that dP_TAmax may be a useful index for internal airway loading due to anatomical narrowing, and may be better correlated with AHI than direct airway anatomic measurements.     

Ground reaction force estimation using an insole-type pressure mat and joint kinematics during walking

Kinetic analysis of walking requires joint kinematics and ground reaction force (GRF) measurement, which are typically obtained from a force plate. GRF is difficult to measure in certain cases such as slope walking, stair climbing, and track running. Nevertheless, estimating GRF continues to be of great interest for simulating human walking. The purpose of the study was to develop reaction force models placed on the sole of the foot to estimate full GRF when only joint kinematics are provided (Type-I), and to estimate ground contact shear forces when both joint kinematics and foot pressure are provided (Type-II and Type-II-val). The GRF estimation models were attached to a commercial full body skeletal model using the AnyBody Modeling System, which has an inverse dynamics-based optimization solver. The anterior–posterior shear force and medial–lateral shear force could be estimated with approximate accuracies of 6% BW and 2% BW in all three methods, respectively. Vertical force could be estimated in the Type-I model with an accuracy of 13.75% BW. The accuracy of the force estimation was the highest during the mid-single-stance period with an average RMS for errors of 3.10% BW, 1.48% BW, and 7.48% BW for anterior–posterior force, medial–lateral force, and vertical force, respectively. The proposed GRF estimation models could predict full and partial GRF with high accuracy. The design of the contact elements of the proposed model should make it applicable to various activities where installation of a force measurement system is difficult, including track running and treadmill walking.     

Hill-type muscle model with serial damping and eccentric force–velocity relation

Hill-type muscle models are commonly used in biomechanical simulations to predict passive and active muscle forces. Here, a model is presented which consists of four elements: a contractile element with force–length and force–velocity relations for concentric and eccentric contractions, a parallel elastic element, a series elastic element, and a serial damping element. With this, it combines previously published effects relevant for muscular contraction, i.e. serial damping and eccentric force–velocity relation. The model is exemplarily applied to arm movements. The more realistic representation of the eccentric force–velocity relation results in human-like elbow-joint flexion. The model is provided as ready to use Matlab ®$\circledR$ and Simulink ®$\circledR$ code.     

A statistical simulation model for field testing of non‐target organisms in environmental risk assessment of genetically modified plants

Genetic modification of plants may result in unintended effects causing potentially adverse effects on the environment. A comparative safety assessment is therefore required by authorities, such as the European Food Safety Authority, in which the genetically modified plant is compared with its conventional counterpart. Part of the environmental risk assessment is a comparative field experiment in which the effect on non‐target organisms is compared. Statistical analysis of such trials come in two flavors: difference testing and equivalence testing. It is important to know the statistical properties of these, for example, the power to detect environmental change of a given magnitude, before the start of an experiment. Such prospective power analysis can best be studied by means of a statistical simulation model. This paper describes a general framework for simulating data typically encountered in environmental risk assessment of genetically modified plants. The simulation model, available as Supplementary Material, can be used to generate count data having different statistical distributions possibly with excess‐zeros. In addition the model employs completely randomized or randomized block experiments, can be used to simulate single or multiple trials across environments, enables genotype by environment interaction by adding random variety effects, and finally includes repeated measures in time following a constant, linear or quadratic pattern in time possibly with some form of autocorrelation. The model also allows to add a set of reference varieties to the GM plants and its comparator to assess the natural variation which can then be used to set limits of concern for equivalence testing. The different count distributions are described in some detail and some examples of how to use the simulation model to study various aspects, including a prospective power analysis, are provided.     

Coarse-grained Modeling and Simulation of Actin Filament Behavior Based on Brownian Dynamics Method

The actin filament, which is the most abundant component of the cytoskeleton, plays important roles in fundamental cellular activities such as shape determination, cell motility, and mechanosensing. In each activity, the actin filament dynamically changes its structure by polymerization, depolymerization, and severing. These phenomena occur on the scales ranging from the dynamics of actin molecules to filament structural changes with its deformation due to the various forces, for example, by the membrane and solvent. To better understand the actin filament dynamics, it is important to focus on these scales and develop its mathematical model. Thus, the objectives of this study were to model and simulate actin filament polymerization, depolymerization, and severing based on the Brownian dynamics method. In the model, the actin monomers and the solvent were considered as globular particles and a continuum, respectively. The motion of the actin molecules was assumed to follow the Langevin equation. The polymerization, which increases the filament length, was determined by the distance between the center of the actin particle at the barbed end and actin particles in the solvent. The depolymerization, which decreases the filament length, was modeled such that the number of dissociation particles from the filament end per unit time was constant. In addition, the filament severing, in which one filament divides into two, was modeled to occur at an equal rate along the filament. Then, we simulated the actin filament dynamics using the developed model, and analyzed the filament elongation rate, its turnover, and the effects of filament severing on the polymerization and depolymerization. Results indicated that the model reproduced the linear dependence of the filament elongation on time, filament turnover process by polymerization and depolymerization, and acceleration of the polymerization and depolymerization by severing, which qualitatively agreed with those observed in experiments.     

基于地统计学和GIS的苜蓿斑蚜种群空间结构分析和分布模拟

运用地理信息系统(GIS)和地统计学方法对宁夏南部固原市原州区不同时期苜蓿斑蚜(Therioaphis trifolii)种群的空间结构进行了分析,并采用普通克立格插值法模拟了苜蓿斑蚜种群空间分布.结果表明:不同时期苜蓿斑蚜种群存在空间相关性,其半变异函数曲线均为指数型,空间格局呈聚集分布,空间变异成分的变化范围为34.13%~48.77%,空间相关范围为8.751~12.049km,聚集程度和方向有从西南向东北方向聚集的趋势.空间分布模拟图能较好地从时间、空间两个角度直观地分析不同时期苜蓿斑蚜种群的动态变化,易于确定同一时期苜蓿斑蚜的发生位置和发生程度.     

混合暴露条件下近江牡蛎对重金属的积累与释放特征

选择近江牡蛎作为试验生物,研究了混合暴露条件下8种重金属在近江牡蛎体内的积累和释放特征.结果表明: 近江牡蛎对重金属Pb、Cu、Ni、Cd、Cr和Hg有很强的累积能力,可较好地指示溶液中的重金属浓度水平,但对重金属Zn和As的积累能力很小,不能真实反映溶液中重金属Zn和As含量的变化水平.在随后35 d的释放阶段,8种重金属在近江牡蛎体内的含量没有明显变化,表明近江牡蛎对重金属的释放能力较差.双箱动力学模型可较好地反映混合暴露条件下近江牡蛎对重金属的积累特征,但不适合对其释放特征进行描述.     

珠江三角洲地区森林生物量及其动态

利用生物量转换因子连续函数法,通过69组不同龄级的森林样地实测数据,拟合了珠江三角洲主要森林类型的生物量和蓄积量之间的回归方程,并结合3个时段森林清查资料,估算了区域森林生物量及其动态.结果表明：珠江三角洲的中幼林面积占森林总面积的80％以上,其林下植被生物量约占森林总生物量的33％,充分考虑林下植被生物量能提高区域森林生物量估算的精度.在1989—1993年、1994—1998年、1999—2003年3个研究时段,珠江三角洲森林生物量共增加了14.67×10⁶ t.其中,马尾松林、常绿阔叶林和针阔混交林的生物量约占区域总生物量的80％,是区域森林生物量的主体;而中、幼林的生物量所占比例达90％,但呈逐年下降趋势.珠江三角洲快速城市化和经济发展对区域森林生物量的积累并没有产生明显影响,区域森林面积基本保持不变,而区域森林生物量呈逐年增长趋势,年增长率为1.2％.随着珠江三角洲区域中、幼林不断发育成熟,区域森林的生物量将不断增加,其环境效应也将不断增强.