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Vaping use has skyrocketed especially among young adults, however there is no consensus on how vaping impacts the lungs. We aimed to determine whether there were changes in lung function acutely after a standard vaping session or if there were differences in lung function metrics between a healthy never‐vaping cohort (N = 6; 27.3 ± 3.0 years) and a young asymptomatic vaping cohort (N = 14; 26.4 ± 8.0 years) indicating chronic changes. Pulmonary function measurements and impulse oscillometry were obtained on all participants. Oxygen‐enhanced and Arterial Spin Labelling MRI were used to measure specific ventilation and perfusion, respectively, before and after vaping, and in the control cohort at baseline. MRI metrics did not show any significant differences in specific ventilation or perfusion after vaping. Heart rate increased post‐vaping (68.1 ± 10.5 to 71.3 ± 8.7, p = 0.020); however, this and other metrics did not show a nicotine dose‐dependent effect. There was a significant negative correlation between BMI and change in mean perfusion post‐vaping (p = 0.003); those with normal/low BMI showing an increase in perfusion and vice versa for high BMI. This may be due to subjects lying supine during vaping inhalation. Pulmonary function metrics indicative of airways resistance showed significant differences between the vaping and control cohorts indicating early airway changes. [ABSTRACT FROM AUTHOR]

Personalised medicine and the development of a virtual human or a digital twin comprises visions of the future of medicine. To realise these innovations, an understanding of the biology and physiology of all people are required if we wish to apply these technologies at a population level. Sex differences in health and biology is one aspect that has frequently been overlooked, with young white males being seen as the "average" human being. This has not been helped by the lack of inclusion of female cells and animals in biomedical research and preclinical studies or the historic exclusion, and still low in proportion, of women in clinical trials. However, there are many known differences in health between the sexes across all scales of biology which can manifest in differences in susceptibility to diseases, symptoms in a given disease, and outcomes to a given treatment. Neglecting these important differences in the development of any health technologies could lead to adverse outcomes for both males and females. Here we highlight just some of the sex differences in the cardio-respiratory systems with the goal of raising awareness that these differences exist. We discuss modelling studies that have considered sex differences and touch on how and when to create sex-specific models. Scientific studies should ensure sex differences are included right from the study planning phase and results reported using sex as a biological variable. Computational models must have sex-specific versions to ensure a movement towards personalised medicine is realised. [ABSTRACT FROM AUTHOR]

The lung is extremely sensitive to interstitial fluid balance, yet the role of pulmonary lymphatics in lung fluid homeostasis and its interaction with cardiovascular pressures is poorly understood. In health, there is a fine balance between fluid extravasated from the pulmonary capillaries into the interstitium and the return of fluid to the circulation via the lymphatic vessels. This balance is maintained by an extremely interdependent system governed by pressures in the fluids (air and blood) and tissue (interstitium), lung motion during breathing, and the permeability of the tissues. Chronic elevation in left atrial pressure (LAP) due to left heart disease increases the capillary blood pressure. The consequent fluid accumulation in the delicate lung tissue increases its weight, decreases its compliance, and impairs gas exchange. This interdependent system is difficult, if not impossible, to study experimentally. Computational modeling provides a unique perspective to analyze fluid movement in the cardiopulmonary vasculature in health and disease. We have developed an initial in silico model of pulmonary lymphatic function using an anatomically structured model to represent ventilation and perfusion and underlying biophysical laws governing fluid transfer at the interstitium. This novel model was tested against increased LAP and noncardiogenic effects (increased permeability). The model returned physiologically reasonable values for all applications, predicting pulmonary edema when LAP reached 25 mmHg and with increased permeability. [ABSTRACT FROM AUTHOR]

Electrical impedance tomography (EIT) is medical imaging technique in which small electrical signals are used to map the electrical impedance distribution within the body. It is safe and non-invasive, which make it attractive for use in continuous monitoring or outpatient applications, but the high cost of commercial devices is an impediment to its adoption. Over the last 10 years, many research groups have developed their own EIT devices, but few designs for open-source EIT hardware are available. In this work, we present a complete open-source EIT system that is designed to be suitable for monitoring the lungs of free breathing subjects. The device is low-cost, wearable, and is designed to comply with the industry accepted safety standard for EIT. The device has been tested in two regimes: Firstly in terms of measurement uncertainty as a voltage measurement system, and secondly against a set of measures that have been proposed specifically for EIT hardware. The voltage measurement uncertainty of the device was measured to be - 0.7 % ± 0.36 mV. The EIT specific performance was measured in a phantom test designed to be as physiologically representative as practicable, and the device performed similarly to other published devices. This work will contribute to increased accessibility of EIT for study and will contribute to consensus on testing methodology for EIT devices., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Author(s).)

Electronic cigarettes (ECs) generate aerosols by heating up a liquid ('e-liquid') that typically consists of propylene glycol (PG), vegetable glycerol (VG), nicotine and flavouring agents. These aerosols transport through the airway tree, and lung and deposit non-uniformly in the bronchi and alveoli. Studying the transport of aerosols through lung airways is necessary because it provides information about the concentration and deposition of particles in the upper and lower airways. Here, particle transport and deposition were simulated within an anatomically-realistic airway model, which was constructed from computed tomography imaging. Particle transport was simulated using the advection-diffusion equations. Particle deposition was estimated using three different mechanisms; including sedimentation, impaction and Brownian diffusion. Results show that by increasing the particle size (PS) from 50 nm to 500 nm, the total deposition efficiency decreased from 50% to 10%, and then by increasing the PS to 3 μm, it increased to 60%. In addition, Brownian deposition was the dominant mechanism for nanoparticles (PS≪0.5μm), while the sedimentation deposition mechanism was the dominant one for microparticles (PS≫0.5μm).Clinical relevance-There is an urgent need to understand the risk that ECs pose to human health and to determine the safest methods for using these devices to support smoking cessation whilst also minimising harm. The results of this study will be used to simulate the conditions such as aerosol concentration and flow rate in airways and alveoli to use in in vitro studies.

Our study methodology is motivated from three disparate needs: one, imaging studies have existed in silo and study organs but not across organ systems; two, there are gaps in our understanding of paediatric structure and function; three, lack of representative data in New Zealand. Our research aims to address these issues in part, through the combination of magnetic resonance imaging, advanced image processing algorithms and computational modelling. Our study demonstrated the need to take an organ-system approach and scan multiple organs on the same child. We have pilot tested an imaging protocol to be minimally disruptive to the children and demonstrated state-of-the-art image processing and personalized computational models using the imaging data. Our imaging protocol spans brain, lungs, heart, muscle, bones, abdominal and vascular systems. Our initial set of results demonstrated child-specific measurements on one dataset. This work is novel and interesting as we have run multiple computational physiology workflows to generate personalized computational models. Our proposed work is the first step towards achieving the integration of imaging and modelling improving our understanding of the human body in paediatric health and disease., Competing Interests: Authors HK and JM were employed by the company GE Healthcare (Australia & New Zealand). The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Kumar, Green, Cornfeld, Condron, Emsden, Elsayed, Zhao, Gilbert, Nash, Clark, Tawhai, Burrowes, Murphy, Tayebi, McGeown, Kwon, Shim, Wang, Choisne, Carman, Besier, Handsfield, Babarenda Gamage, Shen, Maso Talou, Safaei, Maller, Taylor, Potter, Holdsworth and Wilson.)

Chronic obstructive pulmonary disease (COPD) is a heterogeneous group of chronic lung conditions. Genome-wide association studies have identified single-nucleotide polymorphisms (SNPs) associated with COPD and the co-occurring conditions, suggesting common biological mechanisms underlying COPD and these co-occurring conditions. To identify them, we have integrated information across different biological levels (i.e., genetic variants, lung-specific 3D genome structure, gene expression and protein-protein interactions) to build lung-specific gene regulatory and protein-protein interaction networks. We have queried these networks using disease-associated SNPs for COPD, unipolar depression and coronary artery disease. COPD-associated SNPs can control genes involved in the regulation of lung or pulmonary function, asthma, brain region volumes, cortical surface area, depressed affect, neuroticism, Parkinson's disease, white matter microstructure and smoking behaviour. We describe the regulatory connections, genes and biochemical pathways that underlay these co-occurring trait-SNP-gene associations. Collectively, our findings provide new avenues for the investigation of the underlying biology and diverse clinical presentations of COPD. In so doing, we identify a collection of genetic variants and genes that may aid COPD patient stratification and treatment., (© 2022 Golovina et al.)

The use of electronic cigarettes (ECs) has become widespread despite many unknowns around their long-term health impact. ECs work by vapourising a liquid, known as an e-liquid, typically consisting of propylene glycol, glycerol, flavourings and nicotine. The chemical constituents and resultant impact on cells and tissue are dependent on several factors, including the flavourings used, the vaping topography/use pattern, and the device used. ECAM (Electronic Cigarette Aerosol Machine) is an open source, portable device for creating EC aerosol - for condensate collection and in vitro studies - using a controlled methodology. ECAM was developed as a low cost, automated, and customisable alternative to commercial devices. ECAM consists of a micro diaphragm gas pump to draw air/EC aerosol through the system. The device is automated using an Arduino and solenoid pinch valves are used to alternate between air and EC vapour. Condensate is collected in a vial within a cold-water bath. Each ECAM unit uses a temperature/humidity sensor to measure ambient air conditions and a differential pressure sensor to determine the pressure within the system. ECAM is programmed to adhere to International Standards Organisation 20768:2018. The design files, source code, and build instructions for this device can be found at https://dx.doi.org/10.17605/OSF.IO/3NGU4., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2021 The Author(s).)

Many patients with respiratory disease lack an understanding of basic respiratory physiology and the changes occurring in their lungs due to disease. Describing how the lungs work using realistic 3D visualisation of lung structure and function will improve communication of complicated concepts, resulting in improved health literacy. We developed a web-based platform, using anatomically realistic 3D lung models, to create an interactive visualisation tool to improve health literacy for patients with respiratory disease. A small amount of non-identifying personal information including gender, age, weight, height and smoking history can be used to customise the visualisation to an individual user. 3D computer modelling was used to create a web-based application that helps people understand how their lungs work in health and disease. The web-based application includes pages describing and visualising how the lungs work and the changes that occur during asthma and damage that smoking may be doing to their lungs. The application is freely available and located at https://sites.bioeng.auckland.ac.nz/silo6/lung_new/. This application bridges the gap between computational modelling and patient education, giving a visually compelling view into the patient's body that cannot be provided with any existing tools, hence providing a novel platform for enhancing patient-clinician interaction., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2021. No commercial re-use. See rights and permissions. Published by BMJ.)

Rationale: Asthma is characterized by disease within the small airways. Several studies have suggested that forced oscillation technique-derived resistance at 5 Hz (R5) - resistance at 20 Hz (R20) is a measure of small airway disease; however, there has been limited validation of this measurement to date. Objectives: To validate the use of forced oscillation R5 - R20 as a measure of small airway narrowing in asthma, and to investigate the role that small airway narrowing plays in asthma. Methods: Patient-based complete conducting airway models were generated from computed tomography scans to simulate the impact of different degrees of airway narrowing at different levels of the airway tree on forced oscillation R5 - R20 ( n  = 31). The computational models were coupled with regression models in an asthmatic cohort ( n  = 177) to simulate the impact of small airway narrowing on asthma control and quality of life. The computational models were used to predict the impact on small airway narrowing of type-2 targeting biologics using pooled data from two similarly design randomized, placebo-controlled biologic trials ( n  = 137). Measurements and Main Results: Simulations demonstrated that narrowing of the small airways had a greater impact on R5 - R20 than narrowing of the larger airways and was associated (above a threshold of approximately 40% narrowing) with marked deterioration in both asthma control and asthma quality of life, above the minimal clinical important difference. The observed treatment effect on R5 - R20 in the pooled trials equated to a predicted small airway narrowing reversal of approximately 40%. Conclusions: We have demonstrated, using computational modeling, that forced oscillation R5 - R20 is a direct measure of anatomical narrowing in the small airways and that small airway narrowing has a marked impact on both asthma control and quality of life and may be modified by biologics.

Respiratory disease is a significant problem worldwide, and it is a problem with increasing prevalence. Pathology in the upper airways and lung is very difficult to diagnose and treat, as response to disease is often heterogeneous across patients. Computational models have long been used to help understand respiratory function, and these models have evolved alongside increases in the resolution of medical imaging and increased capability of functional imaging, advances in biological knowledge, mathematical techniques and computational power. The benefits of increasingly complex and realistic geometric and biophysical models of the respiratory system are that they are able to capture heterogeneity in patient response to disease and predict emergent function across spatial scales from the delicate alveolar structures to the whole organ level. However, with increasing complexity, models become harder to solve and in some cases harder to validate, which can reduce their impact clinically. Here, we review the evolution of complexity in computational models of the respiratory system, including successes in translation of models into the clinical arena. We also highlight major challenges in modelling the respiratory system, while making use of the evolving functional data that are available for model parameterisation and testing.

We develop a lung ventilation model based on a continuum poroelastic representation of lung parenchyma that is strongly coupled to a pipe network representation of the airway tree. The continuous system of equations is discretized using a low-order stabilised finite element method. The framework is applied to a realistic lung anatomical model derived from computed tomography data and an artificially generated airway tree to model the conducting airway region. Numerical simulations produce physiologically realistic solutions and demonstrate the effect of airway constriction and reduced tissue elasticity on ventilation, tissue stress and alveolar pressure distribution. The key advantage of the model is the ability to provide insight into the mutual dependence between ventilation and deformation. This is essential when studying lung diseases, such as chronic obstructive pulmonary disease and pulmonary fibrosis. Thus the model can be used to form a better understanding of integrated lung mechanics in both the healthy and diseased states. Copyright © 2015 John Wiley & Sons, Ltd., (Copyright © 2015 John Wiley & Sons, Ltd.)

Background and Hypothesis: Chronic Obstructive Pulmonary Disease (COPD) patients are characterized by heterogeneous clinical manifestations and patterns of disease progression. Two major factors that can be used to identify COPD subtypes are muscle dysfunction/wasting and co-morbidity patterns. We hypothesized that COPD heterogeneity is in part the result of complex interactions between several genes and pathways. We explored the possibility of using a Systems Medicine approach to identify such pathways, as well as to generate predictive computational models that may be used in clinic practice., Objective and Method: Our overarching goal is to generate clinically applicable predictive models that characterize COPD heterogeneity through a Systems Medicine approach. To this end we have developed a general framework, consisting of three steps/objectives: (1) feature identification, (2) model generation and statistical validation, and (3) application and validation of the predictive models in the clinical scenario. We used muscle dysfunction and co-morbidity as test cases for this framework., Results: In the study of muscle wasting we identified relevant features (genes) by a network analysis and generated predictive models that integrate mechanistic and probabilistic models. This allowed us to characterize muscle wasting as a general de-regulation of pathway interactions. In the co-morbidity analysis we identified relevant features (genes/pathways) by the integration of gene-disease and disease-disease associations. We further present a detailed characterization of co-morbidities in COPD patients that was implemented into a predictive model. In both use cases we were able to achieve predictive modeling but we also identified several key challenges, the most pressing being the validation and implementation into actual clinical practice., Conclusions: The results confirm the potential of the Systems Medicine approach to study complex diseases and generate clinically relevant predictive models. Our study also highlights important obstacles and bottlenecks for such approaches (e.g. data availability and normalization of frameworks among others) and suggests specific proposals to overcome them.

Clot load scores have previously been developed with the goal of improving prognosis in acute pulmonary embolism (PE). These scores provide a simple estimate of pulmonary vascular bed obstruction, however they have not been adopted clinically as they have poor correlation with mortality and right ventricular (RV) dysfunction. This study performed a quantitative analysis of blood flow and gas exchange in 12 patient-specific models of PE, to understand the limitations of current clot load scores and how their prognostic value could be improved. Prediction of hypoxemia in the models when using estimated baseline (non-occluded) minute ventilation and cardiac output correlated closely with clinical metrics for RV dysfunction, whereas the clot load score had only a weak correlation. The model predicts that large central clots have a greater impact on function than smaller distributed clots with the same total clot load, and that the partial occlusion of a vessel only has a significant impact on pulmonary function when the vessel is close to completely occluded. The effect of clot distribution on the redistribution of blood from its normal pattern - and hence the magnitude of the potential effect on gas exchange - is represented in the model but is not included in current clot load scores. Improved scoring systems need to account for the expected normal distribution of blood in the lung, and the impact of clot on redistributing the blood flow., (Copyright © 2013 Elsevier B.V. All rights reserved.)

Pulmonary embolism (PE) is the most common cause of acute pulmonary hypertension, yet it is commonly undiagnosed, with risk of death if not recognized promptly and managed accordingly. Patients typically present with hypoxemia and hypomania, although the presentation varies greatly, being confounded by co-morbidities such as pre-existing cardio-respiratory disease. Previous studies have demonstrated variable patient outcomes in spite of similar extent and distribution of pulmonary vascular occlusion, but the path physiological determinants of outcome remain unclear. Computational models enable exact control over many of the compounding factors leading to functional outcomes and therefore provide a useful tool to understand and assess these mechanisms. We review the current state of pulmonary blood flow models. We present a pilot study within 10 patients presenting with acute PE, where patient-derived vascular occlusions are imposed onto an existing model of the pulmonary circulation enabling predictions of resultant haemodynamic after embolus occlusion. Results show that mechanical obstruction alone is not sufficient to cause pulmonary arterial hypertension, even when up to 65 per cent of lung tissue is occluded. Blood flow is found to preferentially redistribute to the gravitationally non-dependent regions. The presence of an additional downstream occlusion is found to significantly increase pressures.

Embolus occlusion of pulmonary arteries can result in elevated pulmonary blood pressures, often resulting in pulmonary hypertension (PH). Experimental observations have shown that small emboli (diameter <170 μm) can have a disproportionate effect on pulmonary vascular resistance (PVR) compared with larger emboli for the same tissue occlusion. We present an anatomically based theoretical model of perfusion in the acinar blood vessels designed to investigate changes in PVR following occlusion of arteries <500 μm in diameter. The model predicts that emboli lodged near proximal capillary beds have a greater effect on PVR--regardless of their size--than emboli occluding 200 μm diameter arterioles, with PH occurring for 10% less tissue occlusion. Capillary blood pressures are predicted to exceed 24 mmHg (levels initiating capillary wall damage) in regions of the capillary bed at approximately the onset of PH. This study focuses on the effect of mechanical obstruction alone; however, we present simple models of vasoconstriction illustrating an increased impact on PVR., (Copyright © 2011 Elsevier B.V. All rights reserved.)

Both the development of accurate models of lung function and their quantitative validation can be significantly enhanced by the use of functional imaging techniques. The advent of hyperpolarized noble gas magnetic resonance imaging (MRI) technology has increased the amount of local, functional information we can obtain from the lung. In particular, application of (3)He to measure apparent diffusion coefficients has enabled some measure of lung microstructure and airspace size within the lung. Models mimicking image acquisition in hyperpolarized gas MRI can improve understanding of the relationship between image findings and lung structure, and can be used to improve the definition of imaging protocols. In this paper, we review the state of the art in hyperpolarized gas MRI modelling. We also present our own results, obtained using a Monte Carlo approach and a realistic alveolar sac geometry, which has previously been applied in functional lung studies. In this way, we demonstrate the potential for models combining lung function and image acquisition, which could provide valuable tools in both basic studies and clinical practice.

We have developed an image-based computational model of blood flow within the human pulmonary circulation in order to investigate the distribution of flow under various conditions of posture and gravity. Geometric models of the lobar surfaces and largest arterial and venous vessels were derived from multi-detector row X-ray computed tomography. The remaining blood vessels were generated using a volume-filling branching algorithm. Equations representing conservation of mass and momentum are solved within the vascular geometry to calculate pressure, radius, and velocity distributions. Flow solutions are obtained within the model in the upright, inverted, prone, and supine postures and in the upright posture with and without gravity. Additional equations representing large deformation mechanics are used to calculate the change in lung geometry and pressure distributions within the lung in the various postures - creating a coupled, co-dependent model of mechanics and flow. The embedded vascular meshes deform in accordance with the lung geometry. Results illustrate a persistent flow gradient from the top to the bottom of the lung even in the absence of gravity and in all postures, indicating that vascular branching structure is largely responsible for the distribution of flow.

Violent behavior is reviewed in regard to its relationship with genetic, hormonal, neurochemical, electrical, substance abuse, and psychiatric factors. The most significant relationships were found between violent behavior and the neurotransmitter serotonin. Suggestive associations were found between violent acts and testosterone serum levels, epilepsy, and episodic dyscontrol.