中日友好医院分型股骨头坏死腓骨植入治疗的三维有限元分析

文题释义：股骨头坏死中日友好医院分型的有限元分析：根据李子荣等提出的中日友好医院分型，建立股骨头坏死三维模型，分为 M型(内侧型)、C型(中央型)和 L型(外侧型)，其中 L型包括L1型(次外侧型)、L2型(极外侧型)和 L3型(全头型)。通过对建立的模型进行有限元分析，为该分型的保髋治疗提供了一定力学依据，显示外侧柱的存留是精准预防塌陷的重要因素，为进一步实现个体化治疗提供力学基础。 腓骨支撑坏死股骨头保髋手术：是对于早中期股骨头坏死需要保留股骨头患者进行的一种手术方式。首先需对股骨头进行髓芯减压，清除一定坏死骨，空腔填塞松质骨(髂骨为主)，打压结实后植入腓骨(异体或自体)支撑，给坏死区的提供力学支撑及生物学修复，预防股骨头进一步坏死及塌陷。 背景：研究报道股骨头坏死的保髋疗效与外侧柱存留密切相关，中日友好医院分型是根据三柱结构确立的，对股骨头塌陷的预测准确性高。 目的：建立股骨头坏死中日友好医院分型各分型仿真的三维有限元模型，通过有限元分析各分型腓骨植入的力学变化，探讨外侧柱存留对保髋疗效的意义，为该分型的塌陷精准预测提供基础。 方法：建立正常股骨头、中日友好医院分型(M型、C型、L1型、L2型、L3型)股骨头坏死及其腓骨植入3组11种三维有限元模型，运用ANSYS软件进行有限元分析计算，观察各组模型的最大应力值、最大位移值及股骨头内部载荷传递模式。 结果与结论：①坏死组位移最大，应变最大，且因坏死分型不同而位移不同，位移变化如下：M型相似文献   

Integrating in vitro testing and physiologically-based pharmacokinetic (PBPK) modelling for chemical liver toxicity assessment—A case study of troglitazone

In vitro to in vivo extrapolation (IVIVE) for next-generation risk assessment (NGRA) of chemicals requires computational modeling and faces unique challenges. Using mitochondria-related toxicity data of troglitazone (TGZ), a prototype drug known for liver toxicity, from HepaRG, HepG2, HC-04, and primary human hepatocytes, we explored inherent uncertainties in IVIVE, including cell models, cellular response endpoints, and dose metrics. A human population physiologically-based pharmacokinetic (PBPK) model for TGZ was developed to predict in vivo doses from in vitro point-of-departure (POD) concentrations. Compared to the 200–800 mg/d dose range of TGZ where liver injury was observed clinically, the predicted POD doses for the mean and top one percentile of the PBPK population were 28–372 and 15–178 mg/d respectively based on C_max dosimetry, and 185–2552 and 83–1010 mg/d respectively based on AUC. In conclusion, although with many uncertainties, integrating in vitro assays and PBPK modeling is promising in informing liver toxicity-inducing TGZ doses.     

Cardiac-type total anomalous pulmonary venous return is not benign

ObjectiveThe objective of this study was to investigate the association between morphological variation and postsurgical pulmonary vein (PV) stenosis (PPVS) in patients with cardiac total anomalous pulmonary venous connection (TAPVC).MethodsThis single-center, retrospective study included 168 pediatric patients who underwent surgical repair of cardiac TAPVC from 2013 to 2019 (connection to the coronary sinus [CS], n = 136; connection directly to the right atrium [RA], n = 32). Three-dimensional computed tomography modeling and geometric analysis were performed to investigate the morphological features; their relevance to the PPVS was examined.ResultsThe connection type had no association with PPVS (CS type: 18% vs right atrial type: 19%; P = .89) but there was a higher incidence of PPVS in patients with a single PV orifice than > 1 orifice (P < .001). Confluence-to-total PV area ratio (hazard ratio, 4.78, 95% CI, 1.86-12.32; P = .001) and length of drainage route (hazard ratio, 1.22; 95% CI, 1.14-1.31; P < .001) had a 4- and 1-fold increase in the risk for PPVS in the CS type after adjustment for age and preoperative pulmonary venous obstruction. In the right atrial type, those with anomalous PV return to the RA roof were more likely to develop PPVS than to the posterior wall of the RA (P < .001).ConclusionsThe number of inter-junction PV orifice correlated with PPVS development in cardiac TAPVC. The confluence-to-total PV ratio, length of drainage route, and anomalous PV return to the RA roof are important predictors for PPVS. Morphological subcategorization in this clinical setting can potentially assist in surgical decision-making.     

Challenges with Forecasting Budget Impact: A Case Study of Six ICER Reports

Background

Payers frequently rely on budget impact model (BIM) results to help determine drug coverage policy and its effect on their bottom line. It is unclear whether BIMs typically overestimate or underestimate real-world budget impact.

Temperature-controlled power modulation compensates for heterogeneous nanoparticle distributions: a computational optimization analysis for magnetic hyperthermia

Purpose: To study, with computational models, the utility of power modulation to reduce tissue temperature heterogeneity for variable nanoparticle distributions in magnetic nanoparticle hyperthermia.

Methods: Tumour and surrounding tissue were modeled by elliptical two- and three-dimensional computational phantoms having six different nanoparticle distributions. Nanoparticles were modeled as point heat sources having amplitude-dependent loss power. The total number of nanoparticles was fixed, and their spatial distribution and heat output were varied. Heat transfer was computed by solving the Pennes’ bioheat equation using finite element methods (FEM) with temperature-dependent blood perfusion. Local temperature was regulated using a proportional-integral-derivative (PID) controller. Tissue temperature, thermal dose and tissue damage were calculated. The required minimum thermal dose delivered to the tumor was kept constant, and heating power was adjusted for comparison of both the heating methods.

Results: Modulated power heating produced lower and more homogeneous temperature distributions than did constant power heating for all studied nanoparticle distributions. For a concentrated nanoparticle distribution, located off-center within the tumor, the maximum temperatures inside the tumor were 16% lower for modulated power heating when compared to constant power heating. This resulted in less damage to surrounding normal tissue. Modulated power heating reached target thermal doses up to nine-fold more rapidly when compared to constant power heating.

Conclusions: Controlling the temperature at the tumor-healthy tissue boundary by modulating the heating power of magnetic nanoparticles demonstrably compensates for a variable nanoparticle distribution to deliver effective treatment.     

Derivation of internal dose-based thresholds of toxicological concern for occupational inhalation exposure to systemically acting organic chemicals

This study aimed at deriving occupational thresholds of toxicological concern for inhalation exposure to systemically-acting organic chemicals using predicted internal doses. The latter were also used to evaluate the quantitative relationship between occupational exposure limit and internal dose. Three internal dose measures were identified for investigation: (i) the daily area under the venous blood concentration vs. time curve, (ii) the daily rate of the amount of parent chemical metabolized, and (iii) the maximum venous blood concentration at the end of an 8-hr work shift. A dataset of 276 organic chemicals with 8-hr threshold limit values-time-weighted average was compiled along with their molecular structure and Cramer classes (Class I: low toxicity, Class II: intermediate toxicity, Class III: suggestive of significant toxicity). Using a human physiologically-based pharmacokinetic model, the three identified dose metrics were predicted for an 8-hr occupational inhalation exposure to the threshold limit value for each chemical. Distributional analyses of the predicted dose metrics were performed to identify the percentile values corresponding to the occupational thresholds of toxicological concern. Also, simple linear regression analyses were performed to evaluate the relationship between the 8-hr threshold limit value and each of the predicted dose metrics, respectively. No threshold of toxicological concern could be derived for class II due to few chemicals. Based on the daily rate of the amount of parent chemical metabolized, the proposed internal dose-based occupational thresholds of toxicological concern were 5.61?×?10^?2 and 9?×?10^?4 mmol/d at the 10th percentile level for classes I and III, respectively, while they were 4.55?×?10^?1 and 8.5?×?10^?3 mmol/d at the 25th percentile level. Even though high and significant correlations were observed between the 8-hr threshold limit values and the predicted dose metrics, the one with the rate of the amount of chemical metabolized was remarkable regardless of the Cramer class (r² = 0.81; n = 276). The proposed internal dose-based occupational thresholds of toxicological concern are potentially useful for screening-level assessments as well as prioritization within an integrated occupational risk assessment framework.     

Pathways in the association between sugar sweetened beverages and child asthma traits in the 2nd year of life: Findings from the BRISA cohort

Studies on the exposure of children to sugar-sweetened beverages (SSBs) at an early age may contribute to better understand the common causes and the temporal order of the relationships between obesity and asthma in early childhood. The objective of this study was to estimate the association between SSB and child asthma traits in the 2nd year of life, modeling direct and indirect pathways mediated by the highest BMI-z of the child and allergic inflammation. Data from the BRISA cohort, São Luís-MA, Brazil (n = 1140), were obtained from the baseline and from the follow-up performed at the 2nd year of life. The main explanatory variable was the calories from added sugars in SSBs as a percentage of the total daily energy intake. The outcome child asthma traits was a latent variable deduced from four indicators: medical diagnosis of asthma, wheezing, emergency visit due to intense wheezing, and medical diagnosis of rhinitis. A high percentage of daily calories from sugars added to SSBs was directly associated with higher values of child asthma traits (standardized coefficient (SC = 0.073; P = .030)). High levels of eosinophils were also directly associated with child asthma traits (SC = 0.118; P = .049). No mediation pathways were observed via greater BMI-z or eosinophil counts. Therefore, early exposure of children to SSB may contribute to increased risk of childhood asthma, preceding the link between sugar consumption and overweight/obesity, not yet evident in children in the first 2 years of life.     

Learning to Discretize: Solving 1D Scalar Conservation Laws via Deep Reinforcement Learning

Conservation laws are considered to be fundamental laws of nature. It has broad applications in many fields, including physics, chemistry, biology, geology, and engineering. Solving the differential equations associated with conservation laws is a major branch in computational mathematics. The recent success of machine learning, especially deep learning in areas such as computer vision and natural language processing, has attracted a lot of attention from the community of computational mathematics and inspired many intriguing works in combining machine learning with traditional methods. In this paper, we are the first to view numerical PDE solvers as an MDP and to use (deep) RL to learn new solvers. As proof of concept, we focus on 1-dimensional scalar conservation laws. We deploy the machinery of deep reinforcement learning to train a policy network that can decide on how the numerical solutions should be approximated in a sequential and spatial-temporal adaptive manner. We will show that the problem of solving conservation laws can be naturally viewed as a sequential decision-making process, and the numerical schemes learned in such a way can easily enforce long-term accuracy. Furthermore, the learned policy network is carefully designed to determine a good local discrete approximation based on the current state of the solution, which essentially makes the proposed method a meta-learning approach. In other words, the proposed method is capable of learning how to discretize for a given situation mimicking human experts. Finally, we will provide details on how the policy network is trained, how well it performs compared with some state-of-the-art numerical solvers such as WENO schemes, and supervised learning based approach L3D and PINN, and how well it generalizes.     

Kinetic modeling of PET-FDG in the brain without blood sampling

The aim in this work is to report a new method to calculate parametric images from a single scan acquisition with positron emission tomography (PET) and fluorodeoxyglucose (FDG) in the human brain without blood sampling. It is usually practical for research or clinical purposes to inject the patient in an isolated room and to start the PET acquisition only for some 10–20 min, about 30 min after FDG injection. In order to calculate the cerebral metabolic rates for glucose (CMRG), usually several blood samples are required. The proposed method considers the relation between the uptake of the tracer in the cerebellum as a reference tissue and the population based input curve. Similar results were obtained for CMRG values with the present method in comparison to the usual autoradiographic and the non-linear least squares fitting of regions of interest.     

膝关节运动过程的应力数值模拟

目的观察膝关节关节面在整个运动过程中的应力、应变分布范围、大小及变化规律。方法利用有限元数值模拟方法对行走过程中膝关节关节面应力、应变情况进行分析。结果与结论行走过程中关节面产生应力、应变随时间推移而增加，并且变化规律近似的服从抛物线变化。通过对不同体重的人在行走时膝关节面上产生的应力分析得出，体重对关节面上的应力的大小并不产生重大影响，体重带来的应力差异仅占总应力的10％。