Rigid microenvironments promote cardiac differentiation of mouse and human embryonic stem cells

Abstract

While adult heart muscle is the least regenerative of tissues, embryonic cardiomyocytes are proliferative, with embryonic stem (ES) cells providing an endless reservoir. In addition to secreted factors and cell–cell interactions, the extracellular microenvironment has been shown to play an important role in stem cell lineage specification, and understanding how scaffold elasticity influences cardiac differentiation is crucial to cardiac tissue engineering. Though previous studies have analyzed the role of matrix elasticity on the function of differentiated cardiomyocytes, whether it affects the induction of cardiomyocytes from pluripotent stem cells is poorly understood. Here, we examine the role of matrix rigidity on cardiac differentiation using mouse and human ES cells. Culture on polydimethylsiloxane (PDMS) substrates of varied monomer-to-crosslinker ratios revealed that rigid extracellular matrices promote a higher yield of de novo cardiomyocytes from undifferentiated ES cells. Using a genetically modified ES system that allows us to purify differentiated cardiomyocytes by drug selection, we demonstrate that rigid environments induce higher cardiac troponin T expression, beating rate of foci, and expression ratio of adult α- to fetal β- myosin heavy chain in a purified cardiac population. M-mode and mechanical interferometry image analyses demonstrate that these ES-derived cardiomyocytes display functional maturity and synchronization of beating when co-cultured with neonatal cardiomyocytes harvested from a developing embryo. Together, these data identify matrix stiffness as an independent factor that instructs not only the maturation of already differentiated cardiomyocytes but also the induction and proliferation of cardiomyocytes from undifferentiated progenitors. Manipulation of the stiffness will help direct the production of functional cardiomyocytes en masse from stem cells for regenerative medicine purposes.     

Multipath energy balancing for clustered wireless sensor networks

In wireless sensor networks, sensors at different locations in the field use different energy levels to propagate sensing data back to the sink or base station. This causes unbalanced energy usage among sensors and also lowers the network lifetime. Currently there are several techniques to mitigate this problem, such as deploying multiple sinks, adding more sensors on heavy traffic areas, or managing the size of clusters depending on the distance from sensor to sink. In this paper, we propose a distributed algorithm and protocol called Multipath Energy Balancing (MEB) to mitigate unbalanced energy usage in clustered wireless sensor networks using multi-path and multi-hop, with a transmission power control approach. The network field is divided into regions, where the ratio of inter-region transmission traffic from all cluster head sensors in one region to other cluster head sensors in the two regions in front can be pre-computed and pre-programmed into the sensors to ease sensor deployment. To further prolong network lifetime, we also present a simple heuristic algorithm to procrastinate cluster formation and routing. Simulation results show that MEB can balance energy much better than Energy-efficient Clustering (EC) and Balancing Energy Consumption (BEC) solutions. It also has a longer network lifetime than EC and BEC protocols, especially when the required cluster size is small. Procrastinating cluster formation and routing also can further improve the network lifetime.