Statistical analysis of mechanical properties of biological soft tissue under quasi-static mechanical loading

The mechanical properties of biological soft tissues are inextricably linked to the field of health care,and their mechanical properties can be important indicators for diagnosing and detecting diseases;they can also be used to analyze the causes of organ diseases from a pathological point of view and thus guide the deployment of medical solutions.As an effective method to characterize the mechanical properties of materials,mechanical loading experiments have been successfully applied to the mechanical properties of materials,including tension,compression,pure shear,and so on.Under quasi-static loading,when the material is a biological soft tissue material between a solid and an ideal fluid,its viscoelastic properties strongly respond to the force stimulus,and the stress-strain-time in the elastic phase will have obvious disturbance characteristics.Therefore,the existing statistical methods are often difficult to quantitatively describe the mechanical properties of materials.Therefore,this study proposes an Interval Capture Point based on the principle of integration.The experimental data based on this method can characterize its nonlinear mechanical properties well,especially when the loading speed is extremely low and the soft materials show strong disturbance characteristics.The proposed method can still accurately characterize the hyperelastic and viscoelastic properties of the mechanical properties of biological soft tissues under quasi-static loading.

Effect of mechanical stretching and substrate stiffness on the morphology,cytoskeleton and nuclear shape of corneal endothelial cells

Due to the limited capacity of corneal endothelial cells(CECs)division,corneal endothelial diseases have become a great challenge.The cornea is subjected to various mechanical stimuli in vivo,which may have a positive or negative influence.Thus,it is significant to gain an insight into the mechanism of mechanobiology of CECs for seeking more possible treatment.The purpose of this study was to determine the impacts of mechanical stretch and substrate stiffness on the morphology and fundamental cell behavior of CECs.Rabbit corneal endothelial cells(RCECs)were subjected to a 5%mechanical stretch or cultured on substrates of different stiffness.The impacts of mechanical stimulus on cell area,aspect ratio,circularity,cell density,nuclear shape,cytoskeleton,and cell viability were investigated.The expressions of the corneal endothelium-related markers ZO-1 and Na^(+)/K^(+) ATPase were also evaluated by confocal immunofluorescence microscopy in the stiffness group.Our results suggested that mechanical stretch promoted the rearrangement of the cytoskeleton while decreasing the cell circularity,nuclear area,and cell density as well as cell viability.RCECs cultured on 10 kPa substrates,which was close to the physiological stiffness of rabbit Descemet's membrane(DM),showed better cell morphology,more stable actin cytoskeleton assembly,and more robust expression of the functional marker compared with other softer or stiffer substrates.In summary,mechanical stretch and substrate stiffness have profound influences on the morphology and function of CECs,which may have implications for the understanding and possible treatment of corneal endothelial diseases.

Study on the effects of alternating capacitive electric fields with different frequencies on promoting wound healing

Some researches to facilitate wound healing by using electrical stimulation are based on electric current stimulation,which may cause secondary damage and the imbalance of the microenvironment in vivo.In this study,alternating capacitive electric field(ACEF)was applied via a self-designed system so as to avoid direct contact with cells and to maintain stable microenvironment for cell growth.The influences of 58 mV/mm ACEFs with various frequencies of 10,60 and 110 Hz on epidermal cells,fibroblasts and macrophages which involve in wound healing were comprehensively explored.The results suggested that ACEFs of 10,60 and 110 Hz all significantly promoted the proliferation of human dermal fibroblasts(HDFs)and human epidermal keratinocyte cell line(HaCaT)cells,and 60 Hz ACEF furtherly accelerated the migration of these two kinds of cells.Moreover,ACEFs of all different studied frequencies facilitated M2-type polarization of macrophages,and YAP/TAZ expression of macrophages were enhanced under the stimulations of 10 and 60 Hz ACEFs.The enhancements in cell activity,migration rate and M2-type polarizability indicated that 58 mV/mm ACEFs especially at 60 Hz possessing potentially affirmative applications for wound healing without the risks of secondary damage and microenvironment imbalance.

Novel implantable devices delivering electrical cues for tissue regeneration and functional restoration

Millions of people suffer from tissue diseases and organ dysfunction,such as bone or nerve defects,spinal cord injuries and arrhythmia,which often leads to morbidity and disability.Electrical stimulation as a promising nonpharmacological technique has been proven to be effective in promoting tissue regeneration and functional restoration.Nevertheless,existing clinical electrical therapies are often limited to intraoperative window or percutaneous stimulation that suffer from insufficient time frame and potential infection risks.To overcome these challenges,innovative electrical stimulation implants with miniaturized,self-powered,flexible or biodegradable features have been proposed.This review summarizes recent advances of novel materials strategies and device schemes for tissue regeneration and/or functional restoration of bones,nerves,gastrointestinal tracts,cardiac systems,etc.Insights on future directions of electrical stimulation devices are given at the end.

Deep learning in digital pathology image analysis:a survey

deep learning(DL)has achieved state-of-the-art performance in many digital pathology analysis tasks.Traditional methods usually require hand-crafted domain-specific features,and DL methods can learn representations without manually designed features.In terms of feature extraction,DL approaches are less labor intensive compared with conventional machine learning methods.In this paper,we comprehensively summarize recent DL-based image analysis studies in histopathology,including different tasks(e.g.,classification,semantic segmentation,detection,and instance segmentation)and various applications(e.g.,stain normalization,cell/gland/region structure analysis).DL methods can provide consistent and accurate outcomes.DL is a promising tool to assist pathologists in clinical diagnosis.