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In this paper, we report on the electrical impedance measurement of human endothelial cellular networks and show the existence of emergent power law behavior in its admittance. In particular, we find that the admittance scales with the frequency ω as ωα, with the exponent that varies with the degree of the disruption caused by the inflammation in the endothelial cellular network. We demonstrate that the power law of the measured electrical admittance can be understood by a simple percolation model of a large R–C (resistor–capacitor) network, which allows us to relate quantitatively and the intensity of inflammation. Our results suggest that the electrical properties of heterogeneous biomaterials, like living tissues, behave as a complex microstructural network. 

For people who have experienced a spinal cord injury or an amputation, the recovery of sensation and motor control could be incomplete despite noteworthy advances with invasive neural interfaces. Our objective is to explore the feasibility of a novel biohybrid robotic hand model to investigate aspects of tactile sensation and sensorimotor integration with a pre-clinical research platform. Our new biohybrid model couples an artificial hand with biological neural networks (BNN) cultured in a multichannel microelectrode array (MEA). We decoded neural activity to control a finger of the artificial hand that was outfitted with a tactile sensor. The fingertip sensations were encoded into rapidly adapting (RA) or slowly adapting (SA) mechanoreceptor firing patterns that were used to electrically stimulate the BNN. We classified the coherence between afferent and efferent electrodes in the MEA with a convolutional neural network (CNN) using a transfer learning approach. The BNN exhibited the capacity for functional specialization with the RA and SA patterns, represented by significantly different robotic behavior of the biohybrid hand with respect to the tactile encoding method. Furthermore, the CNN was able to distinguish between RA and SA encoding methods with 97.84% ± 0.65% accuracy when the BNN was provided tactile feedback, averaged across three days in vitro (DIV). This novel biohybrid research platform demonstrates that BNNs are sensitive to tactile encoding methods and can integrate robotic tactile sensations with the motor control of an artificial hand. This opens the possibility of using biohybrid research platforms in the future to study aspects of neural interfaces with minimal human risk. 

Abstract The human placenta is a critical organ, mediating the exchange of nutrients, oxygen, and waste products between fetus and mother. Placental malaria (PM) resulted from Plasmodium falciparum infections causes up to 200 thousand newborn deaths annually, mainly due to low birth weight, as well as 10 thousand mother deaths. In this work, a placenta-on-a-chip model is developed to mimic the nutrient exchange between the fetus and mother under the influence of PM. In this model, trophoblasts cells (facing infected or uninfected blood simulating maternal blood and termed “trophoblast side”) and human umbilical vein endothelial cells (facing uninfected blood simulating fetal blood and termed “endothelial” side) are cultured on the opposite sides of an extracellular matrix gel in a compartmental microfluidic system, forming a physiological barrier between the co-flow tubular structure to mimic a simplified maternal–fetal interface in placental villi. The influences of infected erythrocytes (IEs) sequestration through cytoadhesion to chondroitin sulfate A (CSA) expressed on the surface of trophoblast cells, a critical feature of PM, on glucose transfer efficiency across the placental barrier was studied. To create glucose gradients across the barrier, uninfected erythrocyte or IE suspension with a higher glucose concentration was introduced into the “trophoblast side” and a culture medium with lower glucose concentration was introduced into the “endothelial side”. The glucose levels in the endothelial channel in response to CSA-adherent erythrocytes infected with CS2 line of parasites in trophoblast channel under flow conditions was monitored. Uninfected erythrocytes served as a negative control. The results demonstrated that CSA-binding IEs added resistance to the simulated placental barrier for glucose perfusion and decreased the glucose transfer across this barrier. The results of this study can be used for better understanding of PM pathology and development of models useful in studying potential treatment of PM. 

Abstract Heart failure is a chronic disease, the symptoms of which occur due to a lack of cardiac output. It can be better managed with continuous and real time monitoring. Some efforts have been made in the past for the management of heart failure. Most of these efforts were based on a single parameter for example thoracic impedance or heart rate alone. Herein, we report a wearable device that can provide monitoring of multiple physiological parameters related to heart failure. It is based on the sensing of multiple parameters simultaneously including thoracic impedance, heart rate, electrocardiogram and motion activity. These parameters are measured using different sensors which are embedded in a wearable belt for their continuous and real time monitoring. The healthcare wearable device has been tested in different conditions including sitting, standing, laying, and walking. Results demonstrate that the reported wearable device keeps track of the aforementioned parameters in all conditions.