We report here the synthesis of a new class of hydrogels with an extremely wide range of mechanical properties suitable for cell studies. Mechanobiology has emerged as an important field in bioengineering, in part due to the development of synthetic polymer gels and fibrous protein biomaterials to control and quantify how cells sense and respond to mechanical forces in their microenvironment. To address the problem of limited availability of biomaterials, in terms of both mechanical range and optical clarity, we have prepared hydrogels that combine poly(ethylene glycol) (PEG) and phosphorylcholine (PC) zwitterions. Our goal was to create a hydrogel platform that exceeds the range of Young's moduli reported for similar hydrogels, while being simple to synthesize and manipulate. The Young's modulus of these "PEG-PC" hydrogels can be tuned over 4 orders of magnitude, much greater than commonly used hydrogels such as PEG-diacrylate, PEG-dimethacrylate, and polyacrylamide, with smaller average mesh sizes and optical clarity. We prepared PEG-PC hydrogels to study how substrate mechanical properties influence cell morphology, focal adhesion structure, and proliferation across multiple mammalian cell lines, as a proof of concept. These novel PEG-PC biomaterials represent a new and useful class of mechanically tunable hydrogels for mechanobiology.

Download full-text PDF

Source
http://dx.doi.org/10.1021/bm400418gDOI Listing

Publication Analysis

Top Keywords

mechanical properties
8
optical clarity
8
clarity prepared
8
hydrogels
7
peg-phosphorylcholine hydrogels
4
hydrogels tunable
4
tunable versatile
4
versatile platforms
4
platforms mechanobiology
4
mechanobiology report
4

Similar Publications

This study investigates the quasi-static and dynamic compression performance of a newly designed stacked pyramidal lattice (SPL) structure composed of struts that resemble I-beams. These novel lattice structures are 3D-printed considering three different stacking sequences, and their stiffness, strength, and energy absorption properties are experimentally assessed through low-velocity impact (1.54 m/s) and quasi-static compression tests.

View Article and Find Full Text PDF

In this research, the effect of different plasticizers with different amounts on the properties of monolithic alumina-based refractories has been investigated. All samples were fired at 1100 °C and 1550 °C. In order to evaluate the desired properties, first the rheological properties of the samples were examined, and then for further investigations, loss on ignition (LOI), percentage of permanent linear changes (PLC), apparent porosity (AP), bulk density (BD) and cold crushing strength (CCS) tests were used.

View Article and Find Full Text PDF

The discovery of superconductivity in twisted bilayer and trilayer graphene has generated tremendous interest. The key feature of these systems is an interplay between interlayer coupling and a moiré superlattice that gives rise to low-energy flat bands with strong correlations. Flat bands can also be induced by moiré patterns in lattice-mismatched and/or twisted heterostructures of other two-dimensional materials, such as transition metal dichalcogenides (TMDs).

View Article and Find Full Text PDF

Nanoelectromechanical systems (NEMS) based on atomically-thin tungsten diselenide (WSe), benefiting from the excellent material properties and the mechanical degree of freedom, offer an ideal platform for studying and exploiting dynamic strain engineering and cross-scale vibration coupling in two-dimensional (2D) crystals. However, such opportunity has remained largely unexplored for WSe NEMS, impeding exploration of exquisite physical processes and realization of novel device functions. Here, we demonstrate dynamic coupling between atomic lattice vibration and nanomechanical resonances in few-layer WSe NEMS.

View Article and Find Full Text PDF

Optimizing process and heat-treatment parameters of laser powder bed fusion for producing Ti-6Al-4V alloys with high strength and ductility is crucial to meet performance demands in various applications. Nevertheless, inherent trade-offs between strength and ductility render traditional trial-and-error methods inefficient. Herein, we present Pareto active learning framework with targeted experimental validation to efficiently explore vast parameter space of 296 candidates, pinpointing optimal parameters to augment both strength and ductility.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!