Modeling intracranial aneurysm stability and growth: An integrative mechanobiological framework for clinical cases

We present a novel patient-specific fluid-solid-growth framework to model the mechanobiological state of clinically detected intracranial aneurysms (IAs) and their evolution. The artery and IA sac are modeled as thick-walled, non-linear elastic fiber-reinforced composites. We represent the undulation distribution of collagen fibers: the adventitia of the healthy artery is modeled as a protective sheath whereas the aneurysm sac is modeled to bear load within physiological range of pressures. Initially, we assume the detected IA is stable and then consider two flow-related mechanisms to drive enlargement: (1) low wall shear stress; (2) dysfunctional endothelium which is associated with regions of high oscillatory flow. Localized collagen degradation and remodelling gives rise to formation of secondary blebs on the aneurysm dome. Restabilization of blebs is achieved by remodelling of the homeostatic collagen fiber stretch distribution. This integrative mechanobiological modelling workflow provides a step towards a personalized risk-assessment and treatment of clinically detected IAs

Accurate estimation of commercial volume in tropical forests.

Accurate estimates of commercial volume in tropical forests are key for the implementation of sustainable forest management plans. Because of the lack of local or generic volumetric equations, most forest managers and forestry services are still using traditional expansion factors (i.e., multiplication of the diameter by a given value) to estimate the volume of commercial tree species in the Amazon. Volumetric models were developed through a unique data set of 1,264 fallen trees fully measured in 150 sample plots located across a broad range of forests in Amapá, Brazil. Forest-specific volumetric models were developed and compared with a generic (i.e., across all forests) model and with published equations developed elsewhere in the Amazon. The generic equation performed well in all forest types and allowed precise predictions. The most efficient sampling design to develop volumetric models consists of measuring approximately 50 trees across four different size classes representing the whole population. The form factors (FF) developed locally generated substantial bias but performed better than the traditional FF (0.7). Overall, our results suggest that it is possible to develop accurate generic models to estimate commercial timber volume, and this study can serve as a guideline for forest managers or scientists interested in calibrating volumetric models in a cost-efficient way. Study Implications: This work provides useful information on volumetric modeling methods for Brazilian Amazon tropical forests. Most of the studies in the literature only investigate the classical modeling using regression models considering only boom metrics with or without bark, and, in this way, they provide incomplete and biased total knowledge and estimates for a given population. Therefore, detailed and accurate analyzes are crucial tools for decisionmaking. If the harvesting interventions are carried out without considering the most appropriate method to estimate the total wood stock, there may be damages or even extinction of some species, as has happened with other forest domains in Brazil and in other rainforest regions in the world. In this work, the results clearly show the importance of testing different methodologies and selecting the one best suited for a particular site, as well as carrying out techniques for the sustainable and correct management of the forest. Because the analysis procedures provide only information on how methodologies behave statistically, our results may contribute to a more refined analysis to be applied in the future in similar environments. Currently, the Brazilian forestry sector is looking for alternatives to obtain forest resources within the concept of sustainability. For the Brazilian Amazon tropical forest domain, it is extremely important to achieve a sustainable management of resources through forest management. Most studies in the literature investigate the management of tropical rainforest, whereas there is a lack of scientific information on the transition range for the cerrado

A theoretical model of inflammation- and mechanotransduction- driven asthmatic airway remodelling

Inflammation, airway hyper-responsiveness and airway remodelling are well-established hallmarks of asthma, but their inter-relationships remain elusive. In order to obtain a better understanding of their inter-dependence, we develop a mechanochemical morphoelastic model of the airway wall accounting for local volume changes in airway smooth muscle (ASM) and extracellular matrix in response to transient inflammatory or contractile agonist challenges. We use constrained mixture theory, together with a multiplicative decomposition of growth from the elastic deformation, to model the airway wall as a nonlinear fibre-reinforced elastic cylinder. Local contractile agonist drives ASM cell contraction, generating mechanical stresses in the tissue that drive further release of mitogenic mediators and contractile agonists via underlying mechanotransductive signalling pathways. Our model predictions are consistent with previously described inflammation-induced remodelling within an axisymmetric airway geometry. Additionally, our simulations reveal novel mechanotransductive feedback by which hyper-responsive airways exhibit increased remodelling, for example, via stress-induced release of pro-mitogenic and procontractile cytokines. Simulation results also reveal emergence of a persistent contractile tone observed in asthmatics, via either a pathological mechanotransductive feedback loop, a failure to clear agonists from the tissue, or a combination of both. Furthermore, we identify various parameter combinations that may contribute to the existence of different asthma phenotypes, and we illustrate a combination of factors which may predispose severe asthmatics to fatal bronchospasms

Usability of Computerized Lung Auscultation–Sound Software (CLASS) for learning pulmonary auscultation

The mastering of pulmonary auscultation requires complex acoustic skills. Computer-assisted learning tools (CALTs) have potential to enhance the learning of these skills; however, few have been developed for this purpose and do not integrate all the required features. Thus, this study aimed to assess the usability of a new CALT for learning pulmonary auscultation. Computerized Lung Auscultation-Sound Software (CLASS) usability was assessed by eight physiotherapy students using computer screen recordings, think-aloud reports, and facial expressions. Time spent in each task, frequency of messages and facial expressions, number of clicks and problems reported were counted. The timelines of the three methods used were matched/synchronized and analyzed. The tasks exercises and annotation of respiratory sounds were the ones requiring more clicks (median 132, interquartile range [23-157]; 93 [53-155]; 91 [65-104], respectively) and where most errors (19; 37; 15%, respectively) and problems (n = 7; 6; 3, respectively) were reported. Each participant reported a median of 6 problems, with a total of 14 different problems found, mainly related with CLASS functionalities (50%). Smile was the only facial expression presented in all tasks (n = 54). CLASS is the only CALT available that meets all the required features for learning pulmonary auscultation. The combination of the three usability methods identified advantages/disadvantages of CLASS and offered guidance for future developments, namely in annotations and exercises. This will allow the improvement of CLASS and enhance students' activities for learning pulmonary auscultation skills