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This paper investigates delivery of encapsulated drug from poly lactic-co-glycolic micro-/nano-particles. Experimental data collected from about 50 papers are analyzed by machine learning algorithms including linear regression, principal component analysis, Gaussian process regression, and artificial neural networks. The focus is to understand the effect of drug solubility, drug molecular weight, particle size, and pH-value of the release matrix/environment on drug release profiles. The results obtained from machine learning is then used as guidelines for designing new in vitro experiments to examine dependence of drug release profiles on those four factors. It is interesting to see that indeed the results of the new in vitro experiments are in basic agreement with the results obtained from machine learning. [ABSTRACT FROM AUTHOR]

Polyvinyl alcohol (PVA) fibers were prepared using PVA with different degree of polymerization (DP) under the same wet spinning process. The effect of the DP of PVA on the structures and properties of PVA and PVA fibers were studied by using nuclear magnetic resonance hydrogen spectroscopy (1H‐NMR), Fourier transform infrared spectroscopy (FTIR), X‐ray diffraction (XRD), differential scanning calorimeter (DSC), thermo gravimetric analysis (TGA), and environmental scanning electron microscope (ESEM). The results showed that DP had little effect on the crystallinity and tacticity of PVA, but had a positive effect on melting temperature, and initial decomposition temperature of PVAs. The hot drawing ratio determined by the spinning process where the PVA fibers could be continuously collected without breaking. The drawing ratio was decreased with an increase of DP, resulting in an increase of the final fiber diameter. The PVA fibers with medium DP and medium size demonstrated high strength and high modulus, but relatively low breaking elongation. It suggested that high DP of PVA was not a guarantee of high strength and high modulus PVA fibers, but rather a primary structure factor. The fiber performance was determined by a comprehensive effect combining a variety of factors including polymer properties and spinning conditions. It provided a guideline for PVA fiber manufacture that the PVAs with different DP require different spinning processes to obtain optimal fiber performance. [ABSTRACT FROM AUTHOR]

Biomaterials to facilitate the restoration of cardiac tissue is of emerging importance. While there are many aspects to consider in the design of biomaterials, mechanical properties can be of particular importance in this dynamically remodeling tissue. This review focuses on one specific processing method, electrospinning, that is employed to generate materials with a fibrous microstructure that can be combined with material properties to achieve the desired mechanical behavior. Current methods used to fabricate mechanically relevant micro-/nanofibrous scaffolds, in vivo studies using these scaffolds as therapeutics, and common techniques to characterize the mechanical properties of the scaffolds are covered. We also discuss the discrepancies in the reported elastic modulus for physiological and pathological myocardium in the literature, as well as the emerging area of in vitro mechanobiology studies to investigate the mechanical regulation in cardiac tissue engineering. Lastly, future perspectives and recommendations are offered in order to enhance the understanding of cardiac mechanobiology and foster therapeutic development in myocardial regenerative medicine. [ABSTRACT FROM AUTHOR]

Polydiacetylene (PDA) is an attractive conjugated material for use in biosensors due to its unique characteristic of undergoing a blue-to-red color change in response to external stimuli. 10,12-Pentacosadiynoic acid (PCDA) and poly (ethylene oxide) (PEO) were used in this study to develop fiber composites via an electrospinning method at various mass ratios of PEO to PCDA, solution concentrations, and injection speeds. The PEO-PDA fibers in blue phase were obtained via photo-polymerization upon UV-light irritation. High mass ratios of PEO to PCDA, low polymer concentrations of spinning solution, and low injection speeds promoted fine fibers with small diameters and smooth surfaces. The colorimetric transition of the fibers was investigated when the fibers were heated at temperatures ranging from 25 °C to 120 °C. A color switch from blue to red in the fibers was observed when the fibers were heated at temperatures greater than 60 °C. The color transition was more sensitive in the fibers made with a low mass ratio of PEO to PCDA due to high fraction of PDA in the fibers. The large diameter fibers also promoted the color switch due to high reflectance area in the fibers. All of the fibers were analyzed using Fourier transform infrared spectroscopy (FT-IR) and differential scanning calorimetry (DSC) and compared before and after the color change occurred. The colorimetric transitional mechanism is proposed to occur due to conformational changes in the PDA macromolecules.