Organoids are self‐organizing 3D structures grown from stem cells that recapitulate essential aspects of organ structure and function. Here, we describe a method to establish long‐term‐expanding human airway organoids from broncho‐alveolar resections or lavage material. The pseudostratified airway organoids consist of basal cells, functional multi‐ciliated cells, mucus‐producing secretory cells, and CC10‐secreting club cells. Airway organoids derived from cystic fibrosis (CF) patients allow assessment of CFTR function in an organoid swelling assay. Organoids established from lung cancer resections and metastasis biopsies retain tumor histopathology as well as cancer gene mutations and are amenable to drug screening. Respiratory syncytial virus (RSV) infection recapitulates central disease features, dramatically increases organoid cell motility via the non‐structural viral NS2 protein, and preferentially recruits neutrophils upon co‐culturing. We conclude that human airway organoids represent versatile models for the in vitro study of hereditary, malignant, and infectious pulmonary disease.

Time-lapse microscopy is routinely used to follow cells within organoids, allowing direct study of division and differentiation patterns. There is an increasing interest in cell tracking in organoids, which makes it possible to study their growth and homeostasis at the single-cell level. As tracking these cells by hand is prohibitively time consuming, automation using a computer program is required. Unfortunately, organoids have a high cell density and fast cell movement, which makes automated cell tracking difficult. In this work, a semi-automated cell tracker has been developed. To detect the nuclei, we use a machine learning approach based on a convolutional neural network. To form cell trajectories, we link detections at different time points together using a min-cost flow solver. The tracker raises warnings for situations with likely errors. Rapid changes in nucleus volume and position are reported for manual review, as well as cases where nuclei divide, appear and disappear. When the warning system is adjusted such that virtually error-free lineage trees can be obtained, still less than 2% of all detected nuclei positions are marked for manual analysis. This provides an enormous speed boost over manual cell tracking, while still providing tracking data of the same quality as manual tracking.

2Organoids are self-organizing 3D structures grown from stem cells that recapitulate essential 1 3

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Inward remodeling of small arteries occurs after prolonged vasoconstriction, low blood flow, and in several models of hypertension. The cross-linking enzyme, transglutaminases 2 (TG2), is able to induce inward remodeling and stiffening of arteries. The activity of TG2 is dependent on its conformation, which can be open or closed, and on its redox state. Several factors have been shown to be involved in modulating TG2 activity, including Ca²⁺ and GTP/GDP concentrations, as well as the redox state of the environment. This review introduces the hypothesis that mechanical force could be involved in regulating the activity of TG2 during inward remodeling by promoting its open and reduced active state. Several aspects of TG2, such as its structure and localization, are assessed in order to provide arguments that support the hypothesis. We conclude that a direct activation of TG2 by mechanical force exerted by smooth muscle cells may explain the link between smooth muscle activation and inward remodeling, as observed in several physiological and pathological conditions.