Sensor extended imaging workflow for creating fit for purpose models in basic and applied cell biology.

While various engineering disciplines spent years on developing methods and workflows to increase their R&D efficiency, the field of cell biology has seen limited evolution in the fundamental approaches to interact with living cells. Perturbations are mostly of chemical nature, and physiologically relevant contexts and stimuli are left with limited attention, resulting in a solution space constrained within the boundaries of presently manageable perturbations. To predict in the laboratory how a drug will work in a human patient, cell biology must have a closer look at life and strive to mimic the human being in all his complexity. By implementing an iterative process from perturbation to measurement and vice versa, the authors suggest using a sensor-extended imaging workflow to implement product development practices to cell biology, opening a physiologically relevant solution space for the development of truly translational and predictive fit for purpose in vitro cell models.

Automated Quantification of Human Osteoclasts Using Object Detection.

A balanced skeletal remodeling process is paramount to staying healthy. The remodeling process can be studied by analyzing osteoclasts differentiated in vitro from mononuclear cells isolated from peripheral blood or from buffy coats. Osteoclasts are highly specialized, multinucleated cells that break down bone tissue. Identifying and correctly quantifying osteoclasts in culture are usually done by trained personnel using light microscopy, which is time-consuming and susceptible to operator biases. Using machine learning with 307 different well images from seven human PBMC donors containing a total of 94,974 marked osteoclasts, we present an efficient and reliable method to quantify human osteoclasts from microscopic images. An open-source, deep learning-based object detection framework called Darknet (YOLOv4) was used to train and test several models to analyze the applicability and generalizability of the proposed method. The trained model achieved a mean average precision of 85.26% with a correlation coefficient of 0.99 with human annotators on an independent test set and counted on average 2.1% more osteoclasts per culture than the humans. Additionally, the trained models agreed more than two independent human annotators, supporting a more reliable and less biased approach to quantifying osteoclasts while saving time and resources. We invite interested researchers to test their datasets on our models to further strengthen and validate the results.

Resuscitative endovascular balloon occlusion of the aorta (REBOA) in non-traumatic out-of-hospital cardiac arrest: evaluation of an educational programme.

BACKGROUND: Out-of-hospital cardiac arrest (OHCA) is a critical incident with a high mortality rate. Augmentation of the circulation during cardiopulmonary resuscitation (CPR) might be beneficial. Use of resuscitative endovascular balloon occlusion of the aorta (REBOA) redistribute cardiac output to the organs proximal to the occlusion. Preclinical data support that patients in non-traumatic cardiac arrest might benefit from REBOA in the thoracic level during CPR. This study describes a training programme to implement the REBOA procedure to a prehospital working team, in preparation to a planned clinical study. METHODS: We developed a team-based REBOA training programme involving the physicians and paramedics working on the National Air Ambulance helicopter base in Trondheim, Norway. The programme consists of a four-step approach to educate, train and implement the REBOA procedure in a simulated prehospital setting. An objective structured assessment of prehospital REBOA application scoring chart and a special designed simulation mannequin was made for this study. RESULTS: Seven physicians and 3 paramedics participated. The time needed to perform the REBOA procedure was 8.5 (6.3-12.7) min. The corresponding time from arrival at scene to balloon inflation was 12.0 (8.8-15) min. The total objective assessment scores of the candidates' competency was 41.8 (39-43.5) points out of 48. The advanced cardiovascular life support (ACLS) remained at standard quality, regardless of the simultaneous REBOA procedure. CONCLUSION: This four-step approach to educate, train and implement the REBOA procedure to a prehospital working team ensures adequate competence in a simulated OHCA setting. The use of a structured training programme and objective assessment of skills is recommended before utilising the procedure in a clinical setting. In a simulated setting, the procedure does not add significant time to the prehospital resuscitation time nor does the procedure interfere with the quality of the ACLS. TRIAL REGISTRATION NUMBER: NCT03534011.

Integrated Flow Chamber System for Live Cell Microscopy.

In vitro quantification of the effect of mechanical loads on cells by live microscopy requires precise control of load and culture environment. Corresponding systems are often bulky, their setup and maintenance are time consuming, or the cell yield is low. Here, we show the design and initial testing of a new cell culture system that fits on standard light microscope stages. Based on the parallel plate principle, the system allows for live microscopy of cells exposed to flow-induced shear stress, features short setup time and requires little user interaction. An integrated feedback-controlled heater and a bubble trap enable long observation times. The key design feature is the possibility for quick exchange of the cultured cells. We present first test results that focus on verifying the robustness, biocompatibility, and ease of use of the device.