Surface Modification of Polycaprolactone Scaffold With Improved Biocompatibility and Controlled Growth Factor Release for Enhanced Stem Cell Differentiation

Polycaprolactone (PCL) has been widely used as a scaffold material for tissue engineering. Reliable applications of the PCL scaffolds require overcoming their native hydrophobicity and obtaining the sustained release of signaling factors to modulate cell growth and differentiation. Here, we report a surface modification strategy for electrospun PCL nanofibers using an azide-terminated amphiphilic graft polymer. With multiple alkylation and pegylation on the side chains of poly-L-lysine, stable coating of the graft polymer on the PCL nanofibers was achieved in one step. Using the azide-alkyne “click chemistry”, we functionalized the azide-pegylated PCL nanofibers with dibenzocyclooctyne-modified nanocapsules containing growth factor, which rendered the nanofiber scaffold with satisfied cell adhesion and growth property. Moreover, by specific immobilization of pH-responsive nanocapsules containing bone morphogenetic protein 2 (BMP-2), controlled release of active BMP-2 from the PCL nanofibers was achieved within 21 days. When bone mesenchyme stem cells were cultured on this nanofiber scaffold, enhanced ossification was observed in correlation with the time-dependent release of BMP-2. The established surface modification can be extended as a generic approach to hydrophobic nanomaterials for longtime sustainable release of multiplex signaling proteins for tissue engineering.

A Variable Sample-Size Stochastic Quasi-Newton Method for Smooth and Nonsmooth Stochastic Convex Optimization

Classical theory for quasi-Newton schemes has focused on smooth, deterministic, unconstrained optimization, whereas recent forays into stochastic convex optimization have largely resided in smooth, unconstrained, and strongly convex regimes. Naturally, there is a compelling need to address nonsmoothness, the lack of strong convexity, and the presence of constraints. Accordingly, this paper presents a quasi-Newton framework that can process merely convex and possibly nonsmooth (but smoothable) stochastic convex problems. We propose a framework that combines iterative smoothing and regularization with a variance-reduced scheme reliant on using an increasing sample size of gradients. We make the following contributions. (i) We develop a regularized and smoothed variable sample-size BFGS update (rsL-BFGS) that generates a sequence of Hessian approximations and can accommodate nonsmooth convex objectives by utilizing iterative regularization and smoothing. (ii) In strongly convex regimes with state-dependent noise, the proposed variable sample-size stochastic quasi-Newton (VS-SQN) scheme admits a nonasymptotic linear rate of convergence, whereas the oracle complexity of computing an [Formula: see text]-solution is [Formula: see text], where [Formula: see text] denotes the condition number and [Formula: see text]. In nonsmooth (but smoothable) regimes, using Moreau smoothing retains the linear convergence rate for the resulting smoothed VS-SQN (or sVS-SQN) scheme. Notably, the nonsmooth regime allows for accommodating convex constraints. To contend with the possible unavailability of Lipschitzian and strong convexity parameters, we also provide sublinear rates for diminishing step-length variants that do not rely on the knowledge of such parameters. (iii) In merely convex but smooth settings, the regularized VS-SQN scheme rVS-SQN displays a rate of [Formula: see text] with an oracle complexity of [Formula: see text]. When the smoothness requirements are weakened, the rate for the regularized and smoothed VS-SQN scheme rsVS-SQN worsens to [Formula: see text]. Such statements allow for a state-dependent noise assumption under a quadratic growth property on the objective. To the best of our knowledge, the rate results are among the first available rates for QN methods in nonsmooth regimes. Preliminary numerical evidence suggests that the schemes compare well with accelerated gradient counterparts on selected problems in stochastic optimization and machine learning with significant benefits in ill-conditioned regimes.

Effect of Tailored Microstructures in CaO-Added AZ31 Extrusion Material on Tensile, High Cycle Fatigue and Fatigue Crack Propagation Properties

The effect of tailored microstructures in 0.5 wt% CaO added AZ31 on tensile, high-cycle fatigue, and fatigue crack growth properties was examined. By adding CaO, the average grain size (AGS) was significantly reduced from 4.25±2.32 μm (conventional AZ31) to 2.42±1.60 μm (CaO-AZ31). The fineprecipitates of CaO-AZ31 were more evenly distributed and their fraction was higher than those of conventional AZ31. The fine-precipitates were identified as Al8Mn4Ca and (Mg, Al)2Ca in CaO-AZ31, meanwhile, were identified as Al8Mn5 and Mg17Al11 in conventional AZ31. The tensile test results showed that the yield strengths of CaO-AZ31 and conventional AZ31 were 238.0 MPa and 206.7 MPa, respectively. The elongation-to-failure also increased when CaO was added. The improved tensile properties of CaO-AZ31 could be explained by grain refinement and precipitation hardening. The high-cycle fatigue limit also increased about 15% with added CaO. The fatigue limits as a function of the tensile strengths of CaO-AZ31 and conventional AZ31 were 0.508 and 0.457, respectively. The origin of the improved fatigue resistance was attributed to inhibition of the formation of DTs, which acted as the fatigue crack source, in CaO-AZ31. In contrast, the fatigue crack growth property did not change when CaO was added. Based on the above findings, the relationships between microstructure, mechanical properties and deformation mechanisms are also discussed.

SARS-CoV-2 bearing a mutation at the S1/S2 cleavage site exhibits attenuated virulence and confers protective immunity

Severe Acute Respiratory Syndrome-Coronavirus-2 (SARS-CoV-2) possesses a discriminative polybasic cleavage motif in its spike protein that is recognized by host furin protease. Proteolytic cleavage activates the spike protein and influences both the cellular entry pathway and cell tropism of SARS-CoV-2. Here, we investigated the impact of the furin cleavage site on viral growth and pathogensis using a hamster animal model infected with SARS-CoV-2 variants bearing mutations at the furin cleavage site (S gene mutants). In the airway tissues of hamsters, the S gene mutants exhibited a low growth property. In contrast to parental pathogenic SARS-CoV-2, hamsters infected with the S gene mutants showed no body weight loss and only a mild inflammatory response, indicating the attenuated variant nature of S gene mutants. We reproduced the attenuated growth of S gene mutants in primary differenciated human airway epithelial cells. This transient infection was enough to induce protective neutralizing antibodies crossreacting with different SARS-CoV-2 lineages. Consequently, hamsters inoculated with S gene mutants showed resistance to subsequent infection with both the parental strain and the currently emerging SARS-CoV-2 variants belonging to lineages B.1.1.7 and P.1. Together, our findings revealed that the loss of the furin cleavage site causes attenuation in the airway tissues of SARS-CoV-2 and highlights the potential benefits of S gene mutants as potential immunogens.

A Statistical Growth Property of Plant Root Architectures

Numerous types of biological branching networks, with varying shapes and sizes, are used to acquire and distribute resources. Here, we show that plant root and shoot architectures share a fundamental design property. We studied the spatial density function of plant architectures, which specifies the probability of finding a branch at each location in the 3-dimensional volume occupied by the plant. We analyzed 1645 root architectures from four species and discovered that the spatial density functions of all architectures are population-similar. This means that despite their apparent visual diversity, all of the roots studied share the same basic shape, aside from stretching and compression along orthogonal directions. Moreover, the spatial density of all architectures can be described as variations on a single underlying function: a Gaussian density truncated at a boundary of roughly three standard deviations. Thus, the root density of any architecture requires only four parameters to specify: the total mass of the architecture and the standard deviations of the Gaussian in the three x,y,z growth directions. Plant shoot architectures also follow this design form, suggesting that two basic plant transport systems may use similar growth strategies.

Retraction Note: Growth property at infinity of harmonic functions

This article has been retracted. Please see the retraction notice for more detail: https://doi.org/10.1186/s13660-015-0919-6.