Construction of enzyme digested holes on hydrogel surface inspired by cell migration processes.

The construction of in vitro capillary network models for drug testing and toxicity evaluation has become a major challenge in the field of tissue engineering. Previously, we discovered a novel phenomenon of hole formation by endothelial cell migration on the surface of fibrin gels. Interestingly, the hole characteristics, such as depth and number, were strongly influenced by the gel stiffness, but the details of hole formation are not to be clarified. In this study, we tried to understand the effect of hydrogel stiffness on the hole formation by dropping collagenase solution onto the surface of the hydrogels because the endothelial cell migration was made possible by the metalloproteinases' digestion. We found that smaller hole structures were formed on stiffer fibrin gels, but larger ones were formed on softer fibrin gels after the hydrogel digestion of the collagenase. This is consistent with our previous results in experiments on hole structures formed by endothelial cells. Furthermore, deep and small hole structures were successfully obtained by optimizing the volume of collagenase solution and incubation time. This unique approach inspired by endothelial cell hole formation may provide new methods of fabricating hydrogels with opening hole structures.

Application of Foot Hallux Contact Force Signal for Assistive Hand Fine Control.

Accurate recognition of disabled persons' behavioral intentions is the key to reconstructing hand function. Their intentions can be understood to some extent by electromyography (EMG), electroencephalogram (EEG), and arm movements, but they are not reliable enough to be generally accepted. In this paper, characteristics of foot contact force signals are investigated, and a method of expressing grasping intentions based on hallux (big toe) touch sense is proposed. First, force signals acquisition methods and devices are investigated and designed. By analyzing characteristics of signals in different areas of the foot, the hallux is selected. The peak number and other characteristic parameters are used to characterize signals, which can significantly express grasping intentions. Second, considering complex and fine tasks of the assistive hand, a posture control method is proposed. Based on this, many human-in-the-loop experiments are conducted using human-computer interaction methods. The results showed that people with hand disabilities could accurately express their grasping intentions through their toes, and could accurately grasp objects of different sizes, shapes, and hardness using their feet. The accuracy of the action completion for single-handed and double-handed disabled individuals was 99% and 98%, respectively. This proves that the method of using toe tactile sensation for assisting disabled individuals in hand control can help them complete daily fine motor activities. The method is easily acceptable in terms of reliability, unobtrusiveness, and aesthetics.

Technology for the formation of engineered microvascular network models and their biomedical applications.

Tissue engineering and regenerative medicine have made great progress in recent decades, as the fields of bioengineering, materials science, and stem cell biology have converged, allowing tissue engineers to replicate the structure and function of various levels of the vascular tree. Nonetheless, the lack of a fully functional vascular system to efficiently supply oxygen and nutrients has hindered the clinical application of bioengineered tissues for transplantation. To investigate vascular biology, drug transport, disease progression, and vascularization of engineered tissues for regenerative medicine, we have analyzed different approaches for designing microvascular networks to create models. This review discusses recent advances in the field of microvascular tissue engineering, explores potential future challenges, and offers methodological recommendations.

Research on Intelligent Wheelchair Attitude-Based Adjustment Method Based on Action Intention Recognition.

At present, research on intelligent wheelchairs mostly focuses on motion control, while research on attitude-based adjustment is relatively insufficient. The existing methods for adjusting wheelchair posture generally lack collaborative control and good human-machine collaboration. This article proposes an intelligent wheelchair posture-adjustment method based on action intention recognition by studying the relationship between the force changes on the contact surface between the human body and the wheelchair and the action intention. This method is applied to a multi-part adjustable electric wheelchair, which is equipped with multiple force sensors to collect pressure information from various parts of the passenger's body. The upper level of the system converts the pressure data into the form of a pressure distribution map, extracts the shape features using the VIT deep learning model, identifies and classifies them, and ultimately identifies the action intentions of the passengers. Based on different action intentions, the electric actuator is controlled to adjust the wheelchair posture. After testing, this method can effectively collect the body pressure data of passengers, with an accuracy of over 95% for the three common intentions of lying down, sitting up, and standing up. The wheelchair can adjust its posture based on the recognition results. By adjusting the wheelchair posture through this method, users do not need to wear additional equipment and are less affected by the external environment. The target function can be achieved with simple learning, which has good human-machine collaboration and can solve the problem of some people having difficulty adjusting the wheelchair posture independently during wheelchair use.

Control of blood capillary networks and holes in blood-brain barrier models by regulating elastic modulus of scaffolds.

The blood-brain barrier (BBB) is a type of capillary network characterized by a highly selective barrier, which restricts the transport of substances between the blood and nervous system. Numerous in vitro models of the BBB have been developed for drug testing, but a BBB model with controllable capillary structures remains a major challenge. In this study, we report for the first time a unique method of controlling the blood capillary networks and characteristic holes formation in a BBB model by varying the elastic modulus of a three-dimensional scaffold. The characteristic hole structures are formed by the migration of endothelial cells from the model surface to the interior, which have functions of connecting the model interior to the external environment. The hole depth increased, as the elastic modulus of the fibrin gel scaffold increased, and the internal capillary network length increased with decreasing elastic modulus. Besides, internal astrocytes and pericytes were also found to be important for inducing hole formation from the model surface. Furthermore, RNA sequencing indicated up-regulated genes related to matrix metalloproteinases and angiogenesis, suggesting a relationship between enzymatic degradation of the scaffolds and hole formation. The findings of this study introduce a new method of fabricating complex BBB models for drug assessment.