Bioactive cell-derived ECM scaffold forms a unique cellular microenvironment for lung tissue engineering.

Chronic lung diseases are one of the leading causes of death worldwide. Lung transplantation is currently the only causal therapeutic for lung diseases, which is restricted to end-stage disease and limited by low access to donor lungs. Lung tissue engineering (LTE) is a promising approach to regenerating a replacement for at least a part of the damaged lung tissue. Currently, lung regeneration is limited to a simplified local level (e.g., alveolar-capillary barrier) due to the sophisticated and complex structure and physiology of the lung. Here, we introduce an extracellular matrix (ECM)-integrated scaffold using a cellularization-decellularization-recellularization technique. This ECM-integrated scaffold was developed on our artificial co-polymeric BETA (biphasic elastic thin for air-liquid interface cell culture conditions) scaffold, which were initially populated with human lung fibroblasts (IMR90 cell line), as the main generator of ECM proteins. Due to the interconnected porous structure of the thin (<5 µm) BETA scaffold, the cells can grow on and infiltrate into the scaffold and deposit their own ECM. After a mild decellularization procedure, the ECM proteins remained on the scaffold, which now closely mimicked the cellular microenvironment of pulmonary cells more realistically than the plain artificial scaffolds. We assessed several decellularization methods and found that 20 mM NH4OH and 0.1% Triton X100 with subsequent DNase treatment completely removed the fibroblasts (from the first cellularization) and maintains collagen I and IV as the key ECM proteins on the scaffold. We also showed the repopulation of the primary fibroblast from human (without chronic lung disease (non-CLD) donors) and human bronchial epithelial (16HBE14o-) cells on the ECM-integrated BETA scaffold. With this technique, we developed a biomimetic scaffold that can mimic both the physico-mechanical properties and the native microenvironment of the lung ECM. The results indicate the potential of the presented bioactive scaffold for LTE application

Towards a gold standard functional readout to characterize <em>In Vitro</em> lung barriers.

The development of biomimetic in vitro lung models as an alternative to animal studies is urgent to improve the predictability of the pharmacokinetics of potential new drugs. For pharmacokinetics studies, advanced in vitro lung models such as lung-chips should mimic a functional air-blood barrier. Unlike in vivo conditions, stem/primary cells and cell lines do not necessarily form a functional and tight barrier when cultured in vitro. Here, we explore the two gold standard techniques for monitoring barrier integrity: transepithelial electrical resistance (TEER) and permeability. We discuss the advantages and limitations of these methods, provide recommendations for methodological improvements, and we elude on possible future directions

Real-time measurement of cell mechanics as a clinically relevant readout of an in vitro lung fibrosis model established on a bioinspired basement membrane.

Lung fibrosis, as one of the major post-COVID complications, is a progressive and ultimately fatal disease without a cure. Here, we introduce an organ- and disease-specific&nbsp;in vitro&nbsp;mini-lung fibrosis model equipped with non-invasive real-time monitoring of cell mechanics as a functional readout. To establish an intricate multi-culture model under physiologic conditions, we developed a biomimetic ultrathin basement (BETA) membrane (&lt;1&nbsp;μm)&nbsp;with unique properties, including biocompatibility,&nbsp;permeability, and high elasticity (&lt;10&nbsp;kPa) for cell culturing under air-liquid interface (ALI) and cyclic mechanical stretch conditions. The human-based triple co-culture fibrosis model, which includes epithelial and endothelial cell lines combined with primary fibroblasts from&nbsp;idiopathic pulmonary fibrosis (IPF) patients established on the BETA membrane, is integrated into a millifluidic bioreactor system (CIVIC) with dose-controlled aerosolized drug delivery, mimicking inhalation therapy. We show the real-time measurement of cell/tissue stiffness (and compliance) as a clinical biomarker of the progression/attenuation of fibrosis upon drug treatment, which was confirmed for&nbsp;inhaled&nbsp;Nintedanib -an FDA-approved anti-fibrosis drug.&nbsp;The mini-lung fibrosis model allows the combined longitudinal testing of pharmacodynamics and pharmacokinetics of drugs, which is expected to enhance the predictive capacity of&nbsp;preclinical&nbsp;models&nbsp;and hence facilitate the development of approved therapies for lung fibrosis. This article is protected by copyright. All rights reserved

The preparation of decellularized mouse lung matrix scaffolds for analysis of lung regenerative cell potential.

Lung transplantation is the only option for patients with end-stage lung disease, but there is a shortage of available lung donors. Furthermore, efficiency of lung transplantation has been limited due to primary graft dysfunction. Recent mouse models mimicking lung disease in humans have allowed for deepening our understanding of disease pathomechanisms. Moreover, new techniques such as decellularization and recellularization have opened up new possibilities to contribute to our understanding of the regenerative mechanisms involved in the lung. Stripping the lung of its native cells allows for unprecedented analyses of extracellular matrix and sets a physiologic platform to study the regenerative potential of seeded cells. A comprehensive understanding of the molecular pathways involved for lung development and regeneration in mouse models can be translated to regeneration strategies in higher organisms, including humans. Here we describe and discuss several techniques used for murine lung de- and recellularization, methods for evaluation of efficacy including histology, protein/RNA isolation at the whole lung, as well as lung slices level

Development of a dynamic in vitro stretch model of the alveolar interface with aerosol delivery.

We describe the engineering design, computational modeling, and empirical performance of a moving air-liquid interface (MALI) bioreactor for the study of aerosol deposition on cells cultured on an elastic, porous membrane which mimics both air-liquid interface exposure conditions and mechanoelastic motion of lung tissue during breathing. The device consists of two chambers separated by a cell layer cultured on a porous, flexible membrane. The lower (basolateral) chamber is perfused with cell culture medium simulating blood circulation. The upper (apical) chamber representing the air compartment of the lung is interfaced to an aerosol generator and a pressure actuation system. By cycling the pressure in the apical chamber between 0 and 7 kPa, the membrane can mimic the periodic mechanical strain of the alveolar wall. Focusing on the engineering aspects of the system, we show that membrane strain can be monitored by measuring changes in pressure resulting from the movement of media in the basolateral chamber. Moreover, liquid aerosol deposition at a high dose delivery rate (&gt;1 mu l cm(-2) min(-1)) is highly efficient (ca. 51.5%) and can be accurately modeled using finite element methods. Finally, we show that lung epithelial cells can be mechanically stimulated under air-liquid interface and stretch-conditions without loss of viability. The MALI bioreactor could be used to study the effects of aerosol on alveolar cells cultured at the air-liquid interface in a biodynamic environment or for toxicological or therapeutic applications

Development of a dynamic in vitro stretch model of the alveolar interface with aerosol delivery

We describe the engineering design, computational modeling, and empirical performance of a moving air–liquid interface (MALI) bioreactor for the study of aerosol deposition on cells cultured on an elastic, porous membrane which mimics both air–liquid interface exposure conditions and mechanoelastic motion of lung tissue during breathing. The device consists of two chambers separated by a cell layer cultured on a porous, flexible membrane. The lower (basolateral) chamber is perfused with cell culture medium simulating blood circulation. The upper (apical) chamber representing the air compartment of the lung is interfaced to an aerosol generator and a pressure actuation system. By cycling the pressure in the apical chamber between 0 and 7 kPa, the membrane can mimic the periodic mechanical strain of the alveolar wall. Focusing on the engineering aspects of the system, we show that membrane strain can be monitored by measuring changes in pressure resulting from the movement of media in the basolateral chamber. Moreover, liquid aerosol deposition at a high dose delivery rate (&gt;1 µl cm−2 min−1) is highly efficient (ca. 51.5%) and can be accurately modeled using finite element methods. Finally, we show that lung epithelial cells can be mechanically stimulated under air–liquid interface and stretch-conditions without loss of viability. The MALI bioreactor could be used to study the effects of aerosol on alveolar cells cultured at the air–liquid interface in a biodynamic environment or for toxicological or therapeutic applications

IOS crowd–sensing won’t hurt a bit!:AWARE framework and sustainable study guideline for iOS platform

Abstract The latest smartphones have advanced sensors that allow us to recognize human and environmental contexts. They operate primarily on Android and iOS, and can be used as sensing platforms for research in various fields owing to their ubiquity in society. Mobile sensing frameworks help to manage these sensors easily. However, Android and iOS are constructed following different policies, requiring developers and researchers to consider framework differences during research planning, application development, and data collection phases to ensure sustainable data collection. In particular, iOS imposes strict regulations on background data collection and application distribution. In this study, we design, implement, and evaluate a mobile sensing framework for iOS, namely AWARE-iOS, which is an iOS version of the AWARE Framework. Our performance evaluations and case studies measured over a duration of 288 h on four types of devices, show the risks of continuous data collection in the background and explore optimal practical sensor settings for improved data collection. Based on these results, we develop guidelines for sustainable data collection on iOS

Estimation of symptom severity during chemotherapy from passively sensed data:exploratory study

Abstract Background: Physical and psychological symptoms are common during chemotherapy in cancer patients, and real-time monitoring of these symptoms can improve patient outcomes. Sensors embedded in mobile phones and wearable activity trackers could be potentially useful in monitoring symptoms passively, with minimal patient burden. Objective: The aim of this study was to explore whether passively sensed mobile phone and Fitbit data could be used to estimate daily symptom burden during chemotherapy. Methods: A total of 14 patients undergoing chemotherapy for gastrointestinal cancer participated in the 4-week study. Participants carried an Android phone and wore a Fitbit device for the duration of the study and also completed daily severity ratings of 12 common symptoms. Symptom severity ratings were summed to create a total symptom burden score for each day, and ratings were centered on individual patient means and categorized into low, average, and high symptom burden days. Day-level features were extracted from raw mobile phone sensor and Fitbit data and included features reflecting mobility and activity, sleep, phone usage (eg, duration of interaction with phone and apps), and communication (eg, number of incoming and outgoing calls and messages). We used a rotation random forests classifier with cross-validation and resampling with replacement to evaluate population and individual model performance and correlation-based feature subset selection to select nonredundant features with the best predictive ability. Results: Across 295 days of data with both symptom and sensor data, a number of mobile phone and Fitbit features were correlated with patient-reported symptom burden scores. We achieved an accuracy of 88.1% for our population model. The subset of features with the best accuracy included sedentary behavior as the most frequent activity, fewer minutes in light physical activity, less variable and average acceleration of the phone, and longer screen-on time and interactions with apps on the phone. Mobile phone features had better predictive ability than Fitbit features. Accuracy of individual models ranged from 78.1% to 100% (mean 88.4%), and subsets of relevant features varied across participants. Conclusions: Passive sensor data, including mobile phone accelerometer and usage and Fitbit-assessed activity and sleep, were related to daily symptom burden during chemotherapy. These findings highlight opportunities for long-term monitoring of cancer patients during chemotherapy with minimal patient burden as well as real-time adaptive interventions aimed at early management of worsening or severe symptoms