Using lab-on-chip technology, bulky lab equipment is shrunk into a simple, portable, and quantitative microfluidic chip for DNA diagnostics.

In natural settings, microbes tend to grow in dense populations [1–4] where they need to push against their surroundings to accommodate space for new cells. The associated contact forces play a critical role in a variety of population-level processes, including biofilm formation [5–7], the colonization of porous media [8, 9], and the invasion of biological tissues [10–12]. Although mechanical forces have been characterized at the single cell level [13–16], it remains elusive how collective pushing forces result from the combination of single cell forces. Here, we reveal a collective mechanism of confinement, which we call self-driven jamming, that promotes the build-up of large mechanical pressures in microbial populations. Microfluidic experiments on budding yeast populations in space-limited environments show that self-driven jamming arises from the gradual formation and sudden collapse of force chains driven by microbial proliferation, extending the framework of driven granular matter [17–20]. The resulting contact pressures can become large enough to slow down cell growth, to delay the cell cycle in the G1 phase, and to strain or even destroy the microenvironment through crack propagation. Our results suggest that self-driven jamming and build-up of large mechanical pressures is a natural tendency of microbes growing in confined spaces, contributing to microbial pathogenesis and biofouling [21–26].

In this work, we describe a benchtop model that recreates the motion and function of the diaphragm using a combination of advanced robotic and organic tissue. First, we build a high-fidelity anthropomorphic model of the diaphragm using thermoplastic and elastomeric material based on clinical imaging data. We then attach pneumatic artificial muscles to this elastomeric diaphragm, pre-programmed to move in a clinically relevant manner when pressurized. By inserting this diaphragm as the divider between two chambers in a benchtop model—one representing the thorax and the other the abdomen—and subsequently activating the diaphragm, we can recreate the pressure changes that cause lungs to inflate and deflate during regular breathing. Insertion of organic lungs in the thoracic cavity demonstrates this inflation and deflation in response to the pressures generated by our robotic diaphragm. By tailoring the input pressures and timing, we can represent different breathing motions and disease states. We instrument the model with multiple sensors to measure pressures, volumes, and flows and display these data in real-time, allowing the user to vary inputs such as the breathing rate and compliance of various components, and so they can observe and measure the downstream effect of changing these parameters. In this way, the model elucidates fundamental physiological concepts and can demonstrate pathology and the interplay of components of the respiratory system. This model will serve as an innovative and effective pedagogical tool for educating students on respiratory physiology and pathology in a user-controlled, interactive manner. It will also serve as an anatomically and physiologically accurate testbed for devices or pleural sealants that reside in the thoracic cavity, representing a vast improvement over existing models and ultimately reducing the requirement for testing these technologies in animal models. Finally, it will act as an impactful visualization tool for educating and engaging the broader community.

In natural settings, microbes tend to grow in dense populations [1][2][3][4] where they need to push against their surroundings to accommodate space for new cells. The associated contact forces play a critical role in a variety of population-level processes, including biofilm formation [5][6][7], the colonization of porous media [8,9], and the invasion of biological tissues [10][11][12]. Although mechanical forces have been characterized at the single cell level [13][14][15][16], it remains elusive how collective pushing forces result from the combination of single cell forces. Here, we reveal a collective mechanism of confinement, which we call self-driven jamming, that promotes the buildup of large mechanical pressures in microbial populations. Microfluidic experiments on budding yeast populations in space-limited environments show that self-driven jamming arises from the gradual formation and sudden collapse of force chains driven by microbial proliferation, extending the framework of driven granular matter [17][18][19][20]. The resulting contact pressures can become large enough to slow down cell growth, to delay the cell cycle in the G1 phase, and to strain or even destroy the microenvironment through crack propagation. Our results suggest that self-driven jamming and build-up of large mechanical pressures is a natural tendency of microbes growing in confined spaces, contributing to microbial pathogenesis and biofouling [21][22][23][24][25][26].

Introduction: Heart failure remains a substantive contributor to patient morbidity and mortality rates worldwide and represents a significant burden on the healthcare ecosystem. Faced with persistent physical symptoms and debilitating social consequences, patients follow complex treatment regimens and often have difficulty adhering to them. Purpose: In this manuscript, we review factors which contribute to low adherence rates and advance potential single-and multi-factor-based interventions. It is hoped that these observations can lead to improvements in managed care of this vulnerable population of patients. Methods: A narrative review of the primary literature was performed on contributing factors with primary focus on the period 2015-2020 using available databases and search engines. Adherence pain points identified were mapped against a series of potential solutions which are presented. Results: Enhancement of treatment adherence relies on two approaches viz. single-factor and multi-factor solutions. Single factors identified include electronic reminders, enhanced health education, financial incentives, gamification strategies, community drivers, personabased modeling, and burden relief of poly pharmacy. Multi-factor solutions combine two or more of the seven approaches offering the potential for flexible interventions tailored to the individual. Discussion and Conclusion: Heart failure patients with poor adherence have increased mortality, hospitalization needs, and healthcare costs. This review highlights current singlefactor and multi-factor adherence methods. Against a backdrop of diversity of approaches, multi-factor solutions cast the widest net for positively influencing adherent behaviors. A key enabler lies in the development and leveraging of patient personas in the synthesis of successful intervention methods. Deployable solutions can also be envisioned in clinical trials where adherence tracking represents an essential component.