Nanoparticle delivery in infant lungs.

The lung surface is an ideal pathway to the bloodstream for nanoparticle-based drug delivery. Thus far, research has focused on the lungs of adults, and little is known about nanoparticle behavior in the immature lungs of infants. Here, using nonlinear dynamical systems analysis and in vivo experimentation in developing animals, we show that nanoparticle deposition in postnatally developing lungs peaks at the end of bulk alveolation. This finding suggests a unique paradigm, consistent with the emerging theory that as alveoli form through secondary septation, alveolar flow becomes chaotic and chaotic mixing kicks in, significantly enhancing particle deposition. This finding has significant implications for the application of nanoparticle-based inhalation therapeutics in young children with immature lungs from birth to 2 y of age.

Alveolar Microdynamics during Tidal Ventilation in Live Animals Imaged by SPring-8 Synchrotron.

It is self-evident that our chests expand and contract during breathing but, surprisingly, exactly how individual alveoli change shape over the respiratory cycle is still a matter of debate. Some argue that all the alveoli expand and contract rhythmically. Others claim that the lung volume change is due to groups of alveoli collapsing and reopening during ventilation. Although this question might seem to be an insignificant detail for healthy individuals, it might be a matter of life and death for patients with compromised lungs. Past analyses were based on static post-mortem preparations primarily due to technological limitations, and therefore, by definition, incapable of providing dynamic information. In contrast, this study provides the first comprehensive dynamic data on how the shape of the alveoli changes, and, further, provides valuable insights into the optimal lung volume for efficient gas exchange. It is concluded that alveolar micro-dynamics is nonlinear; and at medium lung volume, alveoli expand more than the ducts.

Application of Machine Learning for Segmentation of the Pulmonary Acinus Imaged by Synchrotron X-Ray Tomography.

Background: To assess the effectiveness of inhalation therapy, it is important to evaluate the lungs' structure; thus, visualization of the entire lungs at the level of the alveoli is necessary. To achieve this goal, the applied visualization technique must satisfy the following two conditions simultaneously: (1) it has to obtain images of the entire lungs, since one part of the lungs is influenced by the other parts, and (2) the images have to capture the detailed structure of the alveolus/acinus in which gas exchange occurs. However, current visualization techniques do not fulfill these two conditions simultaneously. Segmentation is a process in which each pixel of the obtained high-resolution images is simplified (i.e., the representation of an image is changed by categorizing and modifying each pixel) so that we can perform three-dimensional volume rendering. One of the bottlenecks of current approaches is that the accuracy of the segmentation of each image has to be evaluated on the outcome of the process (mainly by an expert). It is a formidable task to evaluate the astronomically large numbers of images that would be required to resolve the entire lungs in high resolution. Methods: To overcome this challenge, we propose a new approach based on machine learning (ML) techniques for the validation step. Results: We demonstrate the accuracy of the segmentation process itself by comparison with previously validated images. In this ML approach, to achieve a reasonable accuracy, millions/billions of parameters used for segmentation have to be optimized. This computationally demanding new approach is achievable only due to recent dramatic increases in computation power. Conclusion: The objective of this article is to explain the advantages of ML over the classical approach for acinar imaging.

Comment on "Microflow in a rhythmically expanding alveolar chip with dynamic similarity" by H. Lv, J. Dong, Y. Qiu, Y. Yang and Y. Zhu, Lab Chip, 2020, 20, 2394.

This comment on an article that appeared in this journal (H. Lv, J. Dong, Y. Qiu, Y. Yang and Y. Zhu, Lab Chip, 2020, 20, 2394-2402) highlights some important inconsistencies between the authors' experimental measurements and their numerical simulations.

Gas and aerosol mixing in the acinus.

This review is concerned with mixing and transport in the human pulmonary acinus. We first examine the current understanding of the anatomy of the acinus and introduce elements of fluid mechanics used to characterize the transport of momentum, gas and aerosol particles. We then review gas transport in more detail and highlight some areas of current research. Next we turn our attention to aerosol transport and in particular to mixing within the alveoli. We examine the factors influencing the level of mixing, review the concept of chaotic convective mixing, and make some brief comments on how mixing affects particle deposition. We end with a few comments on some issues unique to the neonatal and developing lung.

Onset of alveolar recirculation in the developing lungs and its consequence on nanoparticle deposition in the pulmonary acinus.

The structure of the gas exchange region of the human lung (the pulmonary acinus) undergoes profound change in the first few years of life. In this paper, we investigate numerically how the change in alveolar shape with time affects the rate of nanoparticle deposition deep in the lung during postnatal development. As human infant data is unavailable, we use a rat model of lung development. The process of postnatal lung development in the rat is remarkably similar to that of the human, and the structure of the rat acinus is indistinguishable from that of the human acinus. The current numerical predictions support our group's recent in vivo findings, which were also obtained by using growing rat lung models, that nanoparticle deposition in infants is strongly affected by the change in the structure of the pulmonary acinus. In humans, this major structural change occurs over the first 2 yr of life. Our current predictions would suggest that human infants at the age of ∼ 2 yr might be most at risk to the harmful effects of air pollution. Our results also suggest that dose estimates for inhalation therapies using nanoparticles, based on fully developed adult lungs with simple body weight scaling, are likely to overestimate deposition by up to 55% for newborns and underestimate deposition by up to 17% for 2-yr-old infants.

Particle transport and deposition: basic physics of particle kinetics.

The human body interacts with the environment in many different ways. The lungs interact with the external environment through breathing. The enormously large surface area of the lung with its extremely thin air-blood barrier is exposed to particles suspended in the inhaled air. The particle-lung interaction may cause deleterious effects on health if the inhaled pollutant aerosols are toxic. Conversely, this interaction can be beneficial for disease treatment if the inhaled particles are therapeutic aerosolized drugs. In either case, an accurate estimation of dose and sites of deposition in the respiratory tract is fundamental to understanding subsequent biological response, and the basic physics of particle motion and engineering knowledge needed to understand these subjects is the topic of this article. A large portion of this article deals with three fundamental areas necessary to the understanding of particle transport and deposition in the respiratory tract. These are: (i) the physical characteristics of particles, (ii) particle behavior in gas flow, and (iii) gas-flow patterns in the respiratory tract. Other areas, such as particle transport in the developing lung and in the diseased lung are also considered. The article concludes with a summary and a brief discussion of areas of future research.

Low reynolds number viscous flow in an alveolated duct.

Flow visualization studies and supplementary numerical simulations are carried out on slow flow through a model alveolated duct. The results reveal that the type of flow that develops in the alveoli, or cavities, is controlled by the ratio of the depth to the width of the cavity and by the ratio of cavity volume to duct volume. While weak, the slowly rotating flow in the cavity is thought to be important to the convective transport of heat and mass transfer to, or from, the walls of the cavity. The relevance of these finding to particle transport and deposition deep in the lung is discussed.