Androstane-3β,5α,6β,17β-tetrol tri­hydrate

The title hydrated tetrol, C19H32O4·3H2O, was synthesized by stereoselective reduction of the compound 3β,5α,6β-trihy­droxy­androstan-17-one. All rings are fused trans. The organic mol­ecules are connected head-to-tail along the c axis via O—H⋯O hydrogen bonds. Layers of water mol­ecules in the ab plane inter­connect these chains. A quantum chemical ab initio Roothan Hartree–Fock calculation of the isolated mol­ecule gives values for the mol­ecular geometry close to experimentally determined ones, apart from the C—O bond lengths, whose calculated values are significantly smaller than the measured ones, probably a consequence of the involvement of the C—OH groups in the hydrogen-bonding network

<i>Gaia</i> Data Release 1. Summary of the astrometric, photometric, and survey properties

Context. At about 1000 days after the launch of Gaia we present the first Gaia data release, Gaia DR1, consisting of astrometry and photometry for over 1 billion sources brighter than magnitude 20.7. Aims. A summary of Gaia DR1 is presented along with illustrations of the scientific quality of the data, followed by a discussion of the limitations due to the preliminary nature of this release. Methods. The raw data collected by Gaia during the first 14 months of the mission have been processed by the Gaia Data Processing and Analysis Consortium (DPAC) and turned into an astrometric and photometric catalogue. Results. Gaia DR1 consists of three components: a primary astrometric data set which contains the positions, parallaxes, and mean proper motions for about 2 million of the brightest stars in common with the HIPPARCOS and Tycho-2 catalogues – a realisation of the Tycho-Gaia Astrometric Solution (TGAS) – and a secondary astrometric data set containing the positions for an additional 1.1 billion sources. The second component is the photometric data set, consisting of mean G-band magnitudes for all sources. The G-band light curves and the characteristics of ∼3000 Cepheid and RR-Lyrae stars, observed at high cadence around the south ecliptic pole, form the third component. For the primary astrometric data set the typical uncertainty is about 0.3 mas for the positions and parallaxes, and about 1 mas yr−1 for the proper motions. A systematic component of ∼0.3 mas should be added to the parallax uncertainties. For the subset of ∼94 000 HIPPARCOS stars in the primary data set, the proper motions are much more precise at about 0.06 mas yr−1. For the secondary astrometric data set, the typical uncertainty of the positions is ∼10 mas. The median uncertainties on the mean G-band magnitudes range from the mmag level to ∼0.03 mag over the magnitude range 5 to 20.7. Conclusions. Gaia DR1 is an important milestone ahead of the next Gaia data release, which will feature five-parameter astrometry for all sources. Extensive validation shows that Gaia DR1 represents a major advance in the mapping of the heavens and the availability of basic stellar data that underpin observational astrophysics. Nevertheless, the very preliminary nature of this first Gaia data release does lead to a number of important limitations to the data quality which should be carefully considered before drawing conclusions from the data

EXTL3 mutations cause skeletal dysplasia, immune deficiency, and developmental delay.

We studied three patients with severe skeletal dysplasia, T cell immunodeficiency, and developmental delay. Whole-exome sequencing revealed homozygous missense mutations affecting exostosin-like 3 (EXTL3), a glycosyltransferase involved in heparan sulfate (HS) biosynthesis. Patient-derived fibroblasts showed abnormal HS composition and altered fibroblast growth factor 2 signaling, which was rescued by overexpression of wild-type EXTL3 cDNA. Interleukin-2-mediated STAT5 phosphorylation in patients' lymphocytes was markedly reduced. Interbreeding of the extl3-mutant zebrafish (box) with Tg(rag2:green fluorescent protein) transgenic zebrafish revealed defective thymopoiesis, which was rescued by injection of wild-type human EXTL3 RNA. Targeted differentiation of patient-derived induced pluripotent stem cells showed a reduced expansion of lymphohematopoietic progenitor cells and defects of thymic epithelial progenitor cell differentiation. These data identify EXTL3 mutations as a novel cause of severe immune deficiency with skeletal dysplasia and developmental delay and underline a crucial role of HS in thymopoiesis and skeletal and brain development

Unsupervised High-Dimensional Analysis Aligns Dendritic Cells across Tissues and Species.

Dendritic cells (DCs) are professional antigen-presenting cells that hold great therapeutic potential. Multiple DC subsets have been described, and it remains challenging to align them across tissues and species to analyze their function in the absence of macrophage contamination. Here, we provide and validate a universal toolbox for the automated identification of DCs through unsupervised analysis of conventional flow cytometry and mass cytometry data obtained from multiple mouse, macaque, and human tissues. The use of a minimal set of lineage-imprinted markers was sufficient to subdivide DCs into conventional type 1 (cDC1s), conventional type 2 (cDC2s), and plasmacytoid DCs (pDCs) across tissues and species. This way, a large number of additional markers can still be used to further characterize the heterogeneity of DCs across tissues and during inflammation. This framework represents the way forward to a universal, high-throughput, and standardized analysis of DC populations from mutant mice and human patients

Systems biology-guided identification of synthetic lethal gene pairs and its potential use to discover antibiotic combinations

Mathematical models of metabolism from bacterial systems biology have proven their utility across multiple fields, for example metabolic engineering, growth phenotype simulation, and biological discovery. The usefulness of the models stems from their ability to compute a link between genotype and phenotype, but their ability to accurately simulate gene-gene interactions has not been investigated extensively. Here we assess how accurately a metabolic model for Escherichia coli computes one particular type of gene-gene interaction, synthetic lethality, and find that the accuracy rate is between 25% and 43%. The most common failure modes were incorrect computation of single gene essentiality and biological information that was missing from the model. Moreover, we performed virtual and biological screening against several synthetic lethal pairs to explore whether two-compound formulations could be found that inhibit the growth of Gram-negative bacteria. One set of molecules was identified that, depending on the concentrations, inhibits E. coli and S. enterica serovar Typhimurium in an additive or antagonistic manner. These findings pinpoint specific ways in which to improve the predictive ability of metabolic models, and highlight one potential application of systems biology to drug discovery and translational medicine

Rigorous and thorough bioinformatic analyses of olfactory receptor promoters confirm enrichment of O/E and homeodomain binding sites but reveal no new common motifs

<p>Abstract</p> <p>Background</p> <p>Mammalian olfactory receptors (ORs) are subject to a remarkable but poorly understood regime of transcriptional regulation, whereby individual olfactory neurons each express only one allele of a single member of the large OR gene family.</p> <p>Results</p> <p>We performed a rigorous search for enriched sequence motifs in the largest dataset of OR promoter regions analyzed to date. We combined measures of cross-species conservation with databases of known transcription factor binding sites and <it>ab initio </it>motif-finding algorithms. We found strong enrichment of binding sites for the O/E family of transcription factors and for homeodomain factors, both already known to be involved in the transcriptional control of ORs, but did not identify any novel enriched sequences. We also found that TATA-boxes are present in at least a subset of OR promoters.</p> <p>Conclusions</p> <p>Our rigorous approach provides a template for the analysis of the regulation of large gene families and demonstrates some of the difficulties and pitfalls of such analyses. Although currently available bioinformatics methods cannot detect all transcriptional regulatory elements, our thorough analysis of OR promoters shows that in the case of this gene family, experimental approaches have probably already identified all the binding factors common to large fractions of OR promoters.</p