Measuring cell deformation by microfluidics.

Microfluidics is an increasingly popular method for studying cell deformation, with various applications in fields such as cell biology, biophysics, and medical research. Characterizing cell deformation offers insights into fundamental cell processes, such as migration, division, and signaling. This review summarizes recent advances in microfluidic techniques for measuring cellular deformation, including the different types of microfluidic devices and methods used to induce cell deformation. Recent applications of microfluidics-based approaches for studying cell deformation are highlighted. Compared to traditional methods, microfluidic chips can control the direction and velocity of cell flow by establishing microfluidic channels and microcolumn arrays, enabling the measurement of cell shape changes. Overall, microfluidics-based approaches provide a powerful platform for studying cell deformation. It is expected that future developments will lead to more intelligent and diverse microfluidic chips, further promoting the application of microfluidics-based methods in biomedical research, providing more effective tools for disease diagnosis, drug screening, and treatment.

Modeling of Red Blood Cells in Capillary Flow Using Fluid-Structure Interaction and Gas Diffusion.

Red blood cell (RBC) distribution, RBC shape, and flow rate have all been shown to have an effect on the pulmonary diffusing capacity. Through this study, a gas diffusion model and the immersed finite element method were used to simulate the gas diffusion into deformable RBCs running in capillaries. It has been discovered that when RBCs are deformed, the CO flux across the membrane becomes nonuniform, resulting in a reduced capacity for diffusion. Additionally, when compared to RBCs that were dispersed evenly, our simulation showed that clustered RBCs had a significantly lower diffusion capability.

Mechanically Robust Shape Memory Polyurethane Nanocomposites for Minimally Invasive Bone Repair.

Shape memory polymers (SMPs) have great potential utility in the area of minimally invasive surgery; however, insufficient mechanical properties hinder their applications for bone defect repair, particularly in high load-bearing locations. In this study, hydroxyapatite (HA)/reduced graphene oxide (rGO) nanofillers were incorporated into a shape memory polyurethane (SMPU) to enhance its mechanical properties. Then the nanocomposite was further modified using arginyl-glycyl-aspartic acid (RGD peptide) to improve its cellular adhesion toward promoting neotissue formation and integration with surrounding bone tissue. The physical and biological properties in terms of their chemical structure, surface wettability, mechanical behaviors, shape memory performance, and cell adhesion were systematically investigated. The results demonstrated that the multimodified SMPU/HA/rGO/RGD nanocomposite significantly enhanced mechanical properties (e.g., ∼200% increase in Young's modulus and >300% enhancement in tensile strength compared with the unmodified SMPU), which might be attributed to the intercalated structure and metal affinity inside the nanocomposite. Adhesion of rabbit bone mesenchymal stem cells was clearly demonstrated on an RGD-immobilized SMPU nanocomposite surface. With an excellent shape memory behavior (e.g., 97.3% of shape fixity ratio and 98.2% of shape recovery ratio), we envision that our SMPU/HA/rGO/RGD nanocomposite can be implanted into a bone defect with a minimally invasive surgery.

Stress-memory polymeric filaments for advanced compression therapy.

Shape memory polymers are stimulus responsive smart materials that can be applied in several forms such as films, fibers, and foams for a wide range of applications. Novel stress-memory behavior at a fiber level is yet to be uncovered, which would be favorable to control stress in the broad horizon of smart materials for numerous functions. In this work, a semi-crystalline segmented polyurethane was synthesized to prepare filaments/fibres and films. A rational experimental design was established and the stress-memory behavior of both the films and filaments was systematically studied for comparison. Tensile stress-memory programming was performed at three strain levels (20%, 40%, and 60%) to record the memory stress response as a function of temperature with time. The characterization of the thermal and mechanical properties of the stress-memory programmed specimens has objectively proven the reason behind the higher stress response in the filaments than in the films. Melt spinning has induced perfect crystallization with ordered polymer packing and enabled maximum memory stress to be retrieved in the filaments. The evolution of memory stress follows a linear trend with an increase in strain and temperature (r2 = 0.91-1). In addition, pressure related studies were also carried out for smart filament integrative fabrics to realize stress-memory behavior. This unprecedented and novel approach of unveiling the memory behavior specifically at the filament level will enable material scientists to comprehend the fundamental aspects for precise optimization and control of memory stress in smart structures for applications such as compression stockings that require stimuli responsive force.

Revealing the morphological architecture of a shape memory polyurethane by simulation.

The lack of specific knowledge of the network structure in shape memory polymers (SMPs) has prevented us from gaining an in-depth understanding of their mechanisms and limited the potential for materials innovation. This paper firstly reveals the unit-cell nanoscale morphological architecture of SMPs by simulation. The phase separated architecture of a segmented shape memory polyurethane (SMPU) with a 30 wt% hard segment content (HSC, 4,4'-diphenylmethane diisocyanate (MDI) and 1,4-butanediol (BDO)) showing good shape memory properties was investigated by dissipative particle dynamics (DPD) simulations. A linked-spherical netpoint-frame phase of MDI, a matrix-switch phase of polycaprolactone (PCL) and a connected-spider-like interphase for BDO were obtained for this SMPU. The BDO interphase can reinforce the MDI network. Based on these simulation results, a three-dimensional (3D) overall morphological architectural model of the SMPU can be established. This theoretical study has verified, enriched and integrated two existing schematic models: one being the morphological model deduced from experiments and the other the frame model for SMPs reported before. It can serve as a theoretical guide for smart polymeric materials design. This method for the simulation of polymer structure at the nanoscale can be extended to many areas such as photonic crystals where nanoscale self-assembly plays a vital role.

A combined experimental and computational study on the material properties of shape memory polyurethane.

A type of shape memory polyurethane with 60 wt% hard segments (SMPU60) was prepared. Its material properties were tested by dynamic mechanical analysis (DMA) and Instron, and simulated using fully atomistic molecular dynamics (MD). The glass transition temperature (T (g)) of SMPU60 determined by DMA is 316 K, which is slightly lower than that estimated through MD simulations (T (g) = 328 K) , showing the calculated T ( g ) is in good agreement with experimental data. A complex hydrogen bonding network was revealed with the calculation of radial distribution functions (RDFs). The C═O⋯H bond is the predominant hydrogen-bonding interaction. With increasing temperature, both the hydrogen bonding and the moduli decreased, and the dissociation of intermolecular hydrogen bonding induced the decrease of the moduli.

Theoretical study of hydrogen bonding interactions on MDI-based polyurethane.

Hydrogen bonding among hard-hard segments and hard-soft segments in 4,4'-diphenylmethane diisocyanate (MDI)-based polyurethane was investigated theoretically by density functional theory (DFT). Both B3LYP/6-31G* and B3PW91/6-31G* methods gave good structures, reasonable Mulliken charges, binding energies, dipole moments, and good infrared (IR) spectra trends in predicting hydrogen bonding. Bond distances R(N-H...O), which were in the range of 3.005-3.028 A for the carbonyl bonded hydrogen-bond, and 3.074-3.075 A for the ester bonded hydrogen-bond, are in reasonable agreement with experimental values. Most of the carbonyl oxygen in polyurethane exists in a hydrogen-bonded form. Complex (c), with two carbonyl hydrogen bonds, features the largest dipole moment, while complex (d) with two ester hydrogen bonds, possesses the smallest dipole moment, i.e., lower than that of the isolated monomer, which may be due to the symmetry of the two monomers. These results confirm that the DFT method is a good tool with which to study weak interactions, and indicate that hydrogen bonds are indeed formed between carbonyl and N-H, or ester and N-H, with the former being stronger.