Poly(lactic acid) polymer stars built from early generation dendritic polyols

A family of polymer stars has been prepared from early generation dendritic cores with four, six, and eight arms. Four dendritic cores were prepared from the sequential reaction of a multifunctional alcohol with a protected anhydride, followed by deprotection to afford two or three new alcohol functionalities per reactive site. These cores were used as initiators for the tin-catalyzed ring-opening polymerization of l-lactide and rac-lactide to afford isotactic and atactic degradable stars, respectively. Two series of stars were prepared for each monomer, either maintaining total molecular weight or number of monomer units per arm. The polymers were characterized by NMR spectroscopy, light-scattering gel-permeation chromatography, differential scanning calorimetry, and thermogravimetric analysis. Our results support previous work that suggests that the length of the arms dictates thermal properties rather than the total molecular weight of the star. Little effect was noted between aromatic and aliphatic cores, presumably due to the flexibility of the rest of the core molecule. We have shown that early generation dendrimers can serve as excellent core structures for building core-first polymer stars via the ring-opening of cyclic esters

Novel approaches for immune reconstitution and adaptive immune modeling with human pluripotent stem cells

Pluripotent stem cells have the capacity to generate all cell lineages, and substantial progress has been made in realizing this potential. One fascinating but as yet unrealized possibility is the differentiation of pluripotent stem cells into thymic epithelial cells. The thymus is a primary lymphoid organ essential for naïve T-cell generation. T cells play an important role in adaptive immunity, and their loss or dysfunction underlies in a wide range of autoimmune and infectious diseases. T cells are generated and selected through interaction with thymic epithelial cells, the functionally essential element of thymus. The ability to generate functional thymic epithelial cells from pluripotent stem cells would have applications in modeling human immune responses in mice, in tissue transplantation, and in modulating autoimmune and infectious disease

BMP-2/6 Heterodimer Is More Effective than BMP-2 or BMP-6 Homodimers as Inductor of Differentiation of Human Embryonic Stem Cells

Bone Morphogenetic Protein (BMP) signaling pathways are involved in differentiation of stem cells into diverse cell types, and thus BMPs can be used as main guidance molecules for in vitro differentiation of human stem cells.We have analyzed the ability for inducing differentiation of the heterodimer BMP-2/BMP-6 (BMP-2/6) compared to the homodimers BMP-2 or BMP-6, using human embryonic stem (hES) cells H9 as model system. When incubated in a medium with high concentration of basic fibroblastic growth factor (FGF2), 100 ng/ml of human recombinant BMPs induced morphological changes and differentiation of hES cells in 24 to 48 hours. After 5 days, expression of differentiation markers was induced and quantified by quantitative PCR (qPCR) and flow cytometry. BMP-2/6 exhibited stronger activity for the induction of the expression of trophectodermal (CDX2) and endodermal (SOX17, GATA4, AFP) markers than BMP-2 or BMP-6 homodimers. BMP-2/6 also induced the expression of BMPR2 gene more effectively than BMP-2 or BMP-6 when used at the same concentration and time. Moreover, the percentage of cells expressing the surface endodermal marker CXCR4 was also increased for the heterodimer when compared to both homodimers. BMP-2/6 was a more potent activator of Smad-dependent (SMAD1/5) and Smad-independent signaling (mitogen-activated protein kinases ERK and p38) than BMP-2 and BMP-6, and the activation of these pathways might play a role in its increased potency for inducing hES cell differentiation.Therefore, we conclude that BMP-2/6 is more potent than BMP-2 or BMP-6 for inducing differentiation of hES cells, and it can be used as a more powerful substitute of these BMPs in in vitro differentiation guidance

NCBI's Virus Discovery Hackathon:Engaging Research Communities to Identify Cloud Infrastructure Requirements

A wealth of viral data sits untapped in publicly available metagenomic data sets when it might be extracted to create a usable index for the virological research community. We hypothesized that work of this complexity and scale could be done in a hackathon setting. Ten teams comprised of over 40 participants from six countries, assembled to create a crowd-sourced set of analysis and processing pipelines for a complex biological data set in a three-day event on the San Diego State University campus starting 9 January 2019. Prior to the hackathon, 141,676 metagenomic data sets from the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA) were pre-assembled into contiguous assemblies (contigs) by NCBI staff. During the hackathon, a subset consisting of 2953 SRA data sets (approximately 55 million contigs) was selected, which were further filtered for a minimal length of 1 kb. This resulted in 4.2 million (Mio) contigs, which were aligned using BLAST against all known virus genomes, phylogenetically clustered and assigned metadata. Out of the 4.2 Mio contigs, 360,000 contigs were labeled with domains and an additional subset containing 4400 contigs was screened for virus or virus-like genes. The work yielded valuable insights into both SRA data and the cloud infrastructure required to support such efforts, revealing analysis bottlenecks and possible workarounds thereof. Mainly: (i) Conservative assemblies of SRA data improves initial analysis steps; (ii) existing bioinformatic software with weak multithreading/multicore support can be elevated by wrapper scripts to use all cores within a computing node; (iii) redesigning existing bioinformatic algorithms for a cloud infrastructure to facilitate its use for a wider audience; and (iv) a cloud infrastructure allows a diverse group of researchers to collaborate effectively. The scientific findings will be extended during a follow-up event. Here, we present the applied workflows, initial results, and lessons learned from the hackathon

Bias-robust Integration of Observational and Experimental Estimators

We describe a simple approach for combining an unbiased and a (possibly) biased estimator, and demonstrate its robustness to bias: estimate the error and cross-correlation of each estimator, and use these to construct a weighted combination that minimizes mean-squared error (MSE). Theoretically, we demonstrate that for any amount of (unknown) bias, the MSE of the resulting estimator is bounded by a small multiple of the MSE of the unbiased estimator. In simulation, we demonstrate that when the bias is sufficiently small, this estimator still yields notable improvements in MSE, and that as the bias increases without bound, the MSE of this estimator approaches that of the unbiased estimator. This approach applies to a range of problems in causal inference where combinations of unbiased and biased estimators arise. When small-scale experimental data is available, estimates of causal effects are unbiased under minimal assumptions, but may have high variance. Other data sources (such as observational data) may provide additional information about the causal effect, but potentially introduce biases. Estimators incorporating these data can be arbitrarily biased when the needed assumptions are violated. As a result, naive combinations of estimators can have arbitrarily poor performance. We show how to apply the proposed approach in these settings, and benchmark its performance in simulation against recent proposals for combining observational and experimental estimators. Here, we demonstrate that this approach shows improvement over the experimental estimator for a larger range of biases than alternative approaches

Association of abnormal liver function parameters with HIV serostatus and CD4 count in antiretroviral-naive Rwandan women

We determined the associations of HIV infection/CD4 count with markers of hepatocellular damage [elevated aspartate aminotransferase (AST) and alanine aminotransferase (ALT)] and liver synthetic function (decreased albumin) in HIV-infected (HIV+) antiretroviral therapy (ART)-naive and uninfected (HIV-) Rwandan women. In 2005, 710 HIV+ ART-naive and 226 HIV- women enrolled in the Rwanda Women's Interassociation Study and Assessment. Liver enzymes were measured with abnormality defined as either AST or ALT >= 1.25 times the upper limit of normal. Low serum albumin level was defined a