Nanoporous Polytetrafluoroethylene/Silica Composite Separator as a High‐Performance All‐Vanadium Redox Flow Battery Membrane

A novel low‐cost nanoporous polytetrafluoroethylene (PTFE)/silica composite separator has been prepared and evaluated for its use in an all‐vanadium redox flow battery (VRB). The separator consists of silica particles enmeshed in a PTFE fibril matrix. It possesses unique nanoporous structures with an average pore size of 38 nm and a porosity of 48%. These pores function as the ion transport channels during redox flow battery operation. This separator provides excellent electrochemical performance in the mixed‐acid VRB system. The VRB using this separator delivers impressive energy efficiency, rate capability, and temperature tolerance. In additon, the flow cell using the novel separator also demonstrates an exceptional capacity retention capability over extended cycling, thus offering excellent stability for long‐term operation. The characteristics of low cost, excellent electrochemical performance and proven chemical stability afford the PTFE/silica nanoporous separator great potential as a substitute for the Nafion membrane used in VRB applications.     

A simple method to estimate the exponential material parameters of heart valve tissue based on analogy between uniaxial tension and micropipette aspiration

Micropipette aspiration (MA) has been widely used to measure the biomechanical properties of cells and biomaterials. To estimate material parameters from MA experimental data, analytical half-space models and inverse finite element (FE) analyses are typically used. The half-space model is easy to implement but cannot account for nonlinear material properties and complex geometrical boundary conditions that are inherent to MA. Inverse FE approaches can account for geometrical and material nonlinearities, but their implementation is resource-intensive and not widely available. Here, by making analogy between an analytical uniaxial tension model and a FE model of MA, we proposed an easily implementable and accurate method to estimate the material parameters of tissues tested by MA. We first adopted a strain invariant-based isotropic exponential constitutive model and implemented it in both the analytical uniaxial tension model and the FE model. The two models were fit to experimental data generated by MA of porcine aortic valve tissue (45 spots on four leaflets) to estimate material parameters. We found no significant differences between the effective moduli estimated by the two models ( $p > 0.39$ ), with the effective moduli estimated by the uniaxial tension model correlating significantly with those estimated by the FE model ( $p < 0.001; R^{2}= 0.96$ ) with a linear regression slope that was not different than unity ( $p = 0.38$ ). Thus, the analytical uniaxial tension model, which avoids solving resource-intensive numerical problems, is as accurate as the FE model in estimating the effective modulus of valve tissue tested by MA.     

Unsupervised Clustering of Subcellular Protein Expression Patterns in High-Throughput Microscopy Images Reveals Protein Complexes and Functional Relationships between Proteins

Protein subcellular localization has been systematically characterized in budding yeast using fluorescently tagged proteins. Based on the fluorescence microscopy images, subcellular localization of many proteins can be classified automatically using supervised machine learning approaches that have been trained to recognize predefined image classes based on statistical features. Here, we present an unsupervised analysis of protein expression patterns in a set of high-resolution, high-throughput microscope images. Our analysis is based on 7 biologically interpretable features which are evaluated on automatically identified cells, and whose cell-stage dependency is captured by a continuous model for cell growth. We show that it is possible to identify most previously identified localization patterns in a cluster analysis based on these features and that similarities between the inferred expression patterns contain more information about protein function than can be explained by a previous manual categorization of subcellular localization. Furthermore, the inferred cell-stage associated to each fluorescence measurement allows us to visualize large groups of proteins entering the bud at specific stages of bud growth. These correspond to proteins localized to organelles, revealing that the organelles must be entering the bud in a stereotypical order. We also identify and organize a smaller group of proteins that show subtle differences in the way they move around the bud during growth. Our results suggest that biologically interpretable features based on explicit models of cell morphology will yield unprecedented power for pattern discovery in high-resolution, high-throughput microscopy images.     

Anti-CD70 Immunocytokines for Exploitation of Interferon-γ-Induced RIP1-Dependent Necrosis in Renal Cell Carcinoma

Metastatic renal cell carcinoma (RCC) is an incurable disease in clear need of new therapeutic interventions. In early-phase clinical trials, the cytokine IFN-γ showed promise as a biotherapeutic for advanced RCC, but subsequent trials were less promising. These trials, however, focused on the indirect immunomodulatory properties of IFN-γ, and its direct anti-tumor effects, including its ability to kill tumor cells, remains mostly unexploited. We have previously shown that IFN-γ induces RIP1 kinase-dependent necrosis in cells lacking NF-κB survival signaling. RCC cells display basally-elevated NF-κB activity, and inhibiting NF-κB in these cells, for example by using the small-molecule proteasome blocker bortezomib, sensitizes them to RIP1-dependent necrotic death following exposure to IFN-γ. While these observations suggest that IFN-γ-mediated direct tumoricidal activity will have therapeutic benefit in RCC, they cannot be effectively exploited unless IFN-γ is targeted to tumor cells in vivo. Here, we describe the generation and characterization of two novel ‘immunocytokine’ chimeric proteins, in which either human or murine IFN-γ is fused to an antibody targeting the putative metastatic RCC biomarker CD70. These immunocytokines display high levels of species-specific IFN-γ activity and selective binding to CD70 on human RCC cells. Importantly, the IFN-γ immunocytokines function as well as native IFN-γ in inducing RIP1-dependent necrosis in RCC cells, when deployed in the presence of bortezomib. These results provide a foundation for the in vivo exploitation of IFN-γ-driven tumoricidal activity in RCC.     

Neonatal Exendin-4 Reduces Growth,Fat Deposition and Glucose Tolerance during Treatment in the Intrauterine Growth-Restricted Lamb

Background

IUGR increases the risk of type 2 diabetes mellitus (T2DM) in later life, due to reduced insulin sensitivity and impaired adaptation of insulin secretion. In IUGR rats, development of T2DM can be prevented by neonatal administration of the GLP-1 analogue exendin-4. We therefore investigated effects of neonatal exendin-4 administration on insulin action and β-cell mass and function in the IUGR neonate in the sheep, a species with a more developed pancreas at birth.

Methods

Twin IUGR lambs were injected s.c. daily with vehicle (IUGR+Veh, n = 8) or exendin-4 (1 nmol.kg^-1, IUGR+Ex-4, n = 8), and singleton control lambs were injected with vehicle (CON, n = 7), from d 1 to 16 of age. Glucose-stimulated insulin secretion and insulin sensitivity were measured in vivo during treatment (d 12–14). Body composition, β-cell mass and in vitro insulin secretion of isolated pancreatic islets were measured at d 16.

Principal Findings

IUGR+Veh did not alter in vivo insulin secretion or insulin sensitivity or β-cell mass, but increased glucose-stimulated insulin secretion in vitro. Exendin-4 treatment of the IUGR lamb impaired glucose tolerance in vivo, reflecting reduced insulin sensitivity, and normalised glucose-stimulated insulin secretion in vitro. Exendin-4 also reduced neonatal growth and visceral fat accumulation in IUGR lambs, known risk factors for later T2DM.

Conclusions

Neonatal exendin-4 induces changes in IUGR lambs that might improve later insulin action. Whether these effects of exendin-4 lead to improved insulin action in adult life after IUGR in the sheep, as in the PR rat, requires further investigation.     

Divergence and support among slightly suboptimal likelihood gene trees

Contemporary phylogenomic studies frequently incorporate two-step coalescent analyses wherein the first step is to infer individual-gene trees, generally using maximum-likelihood implemented in the popular programs PhyML or RAxML . Four concerns with this approach are that these programs only present a single fully resolved gene tree to the user despite potential for ambiguous support, insufficient phylogenetic signal to fully resolve each gene tree, inexact computer arithmetic affecting the reported likelihood of gene trees, and an exclusive focus on the most likely tree while ignoring trees that are only slightly suboptimal or within the error tolerance. Taken together, these four concerns are sufficient for RAxML and Phy ML users to be suspicious of the resulting (perhaps over-resolved) gene-tree topologies and (perhaps unjustifiably high) bootstrap support for individual clades. In this study, we sought to determine how frequently these concerns apply in practice to contemporary phylogenomic studies that use RAxML for gene-tree inference. We did so by re-analyzing 100 genes from each of ten studies that, taken together, are representative of many empirical phylogenomic studies. Our seven findings are as follows. First, the few search replicates that are frequently applied in phylogenomic studies are generally insufficient to find the optimal gene-tree topology. Second, there is often more topological variation among slightly suboptimal gene trees relative to the best-reported tree than can be safely ignored. Third, the Shimodaira–Hasegawa-like approximate likelihood ratio test is highly effective at identifying dubiously supported clades and outperforms the alternative approaches of relying on bootstrap support or collapsing minimum-length branches. Fourth, the bootstrap can, but rarely does, indicate high support for clades that are not supported amongst slightly suboptimal trees. Fifth, increasing the accuracy by which RA xML optimizes model-parameter values generally has a nominal effect on selection of optimal trees. Sixth, tree searches using the GTRCAT model were generally less effective at finding optimal known trees than those using the GTRGAMMA model. Seventh, choice of gene-tree sampling strategy can affect inferred coalescent branch lengths, species-tree topology and branch support.     

Tailoring translational strength using Kozak sequence variants improves bispecific antibody assembly and reduces product-related impurities in CHO cells

Optimal production of bispecific antibodies (bsAb) requires efficient and tailored co-expression and assembly of two distinct heavy and two distinct light chains. Here, we describe a novel technology to modulate the translational strength of antibody chains via Kozak sequence variants to produce bsAb in a single cell line. In this study, we designed and screened a large Kozak sequence library to identify 10 independent variants that can modulate protein expression levels from approximately 0.2 to 1.3-fold compared with the wild-type sequence in transient transfection. We used a combination of several of these variants, covering a wide range of translational strength, to develop stable single cell Chinese hamster ovary bispecific cell lines and compared the results with those obtained from the wild-type sequence. A significant increase in bispecific antibody assembly with a concomitant reduction in the level of product-related impurities was observed. Our findings suggest that for production of bsAb it can be advantageous to modify translational strength for selected protein chains to improve overall yield and product quality. By extension, tuning of translational strength can also be applied to improving the production of a wide variety of heterologous proteins.     

Alternative Serotype Adenovirus Vaccine Vectors Elicit Memory T Cells with Enhanced Anamnestic Capacity Compared to Ad5 Vectors

The failure of the adenovirus serotype 5 (Ad5) vector-based human immunodeficiency virus type 1 (HIV-1) vaccine in the STEP study has led to the development of adenovirus vectors derived from alternative serotypes, such as Ad26, Ad35, and Ad48. We have recently demonstrated that vaccines using alternative-serotype Ad vectors confer partial protection against stringent simian immunodeficiency virus (SIV) challenges in rhesus monkeys. However, phenotypic differences between the T cell responses elicited by Ad5 and those of alternative-serotype Ad vectors remain unexplored. Here, we report the magnitude, phenotype, functionality, and recall capacity of memory T cell responses elicited in mice by Ad5, Ad26, Ad35, and Ad48 vectors expressing lymphocytic choriomeningitis virus (LCMV) glycoprotein (GP). Our data demonstrate that memory T cells elicited by Ad5 vectors were high in magnitude but exhibited functional exhaustion and decreased anamnestic potential following secondary antigen challenge compared to Ad26, Ad35, and Ad48 vectors. These data suggest that vaccination with alternative-serotype Ad vectors offers substantial immunological advantages over Ad5 vectors, in addition to circumventing high baseline Ad5-specific neutralizing antibody titers.     

Synthesis and antioxidant evaluation of (S,S)- and (R,R)-secoisolariciresinol diglucosides (SDGs)

Secoisolariciresinol diglucosides (SDGs) (S,S)-SDG-1 (major isomer in flaxseed) and (R,R)-SDG-2 (minor isomer in flaxseed) were synthesized from vanillin via secoisolariciresinol (6) and glucosyl donor 7 through a concise route that involved chromatographic separation of diastereomeric diglucoside derivatives (S,S)-8 and (R,R)-9. Synthetic (S,S)-SDG-1 and (R,R)-SDG-2 exhibited potent antioxidant properties (EC₅₀ = 292.17 ± 27.71 μM and 331.94 ± 21.21 μM, respectively), which compared well with that of natural (S,S)-SDG-1 (EC₅₀ = 275.24 ± 13.15 μM). These values are significantly lower than those of ascorbic acid (EC₅₀ = 1129.32 ± 88.79 μM) and α-tocopherol (EC₅₀ = 944.62 ± 148.00 μM). Compounds (S,S)-SDG-1 and (R,R)-SDG-2 also demonstrated powerful scavenging activities against hydroxyl [natural (S,S)-SDG-1: 3.68 ± 0.27; synthetic (S,S)-SDG-1: 2.09 ± 0.16; synthetic (R,R)-SDG-2: 1.96 ± 0.27], peroxyl [natural (S,S)-SDG-1: 2.55 ± 0.11; synthetic (S,S)-SDG-1: 2.20 ± 0.10; synthetic (R,R)-SDG-2: 3.03 ± 0.04] and DPPH [natural (S,S)-SDG-1: EC₅₀ = 83.94 ± 2.80 μM; synthetic (S,S)-SDG-1: EC₅₀ = 157.54 ± 21.30 μM; synthetic (R,R)-SDG-2: EC₅₀ = 123.63 ± 8.67 μM] radicals. These results confirm previous studies with naturally occurring (S,S)-SDG-1 and establish both (S,S)-SDG-1 and (R,R)-SDG-2 as potent antioxidants and free radical scavengers for potential in vivo use.