Carbon-Chain Molecules in Molecular Outflows and Lupus I Region--New Producing Region and New Forming Mechanism

Using the new equipment of the Shanghai Tian Ma Radio Telescope, we have searched for carbon-chain molecules (CCMs) towards five outflow sources and six Lupus I starless dust cores, including one region known to be characterized by warm carbon-chain chemistry (WCCC), Lupus I-1 (IRAS 15398-3359), and one TMC-1 like cloud, Lupus I-6 (Lupus-1A). Lines of HC3N J=2-1, HC5N J=6-5, HC7N J=14-13, 15-14, 16-15 and C3S J=3-2 were detected in all the targets except in the outflow source L1660 and the starless dust core Lupus I-3/4. The column densities of nitrogen-bearing species range from 10$^{12}$ to 10$^{14}$ cm$^{-2}$ and those of C$_3$S are about 10$^{12}$ cm$^{-2}$. Two outflow sources, I20582+7724 and L1221, could be identified as new carbon-chain--producing regions. Four of the Lupus I dust cores are newly identified as early quiescent and dark carbon-chain--producing regions similar to Lup I-6, which together with the WCCC source, Lup I-1, indicate that carbon-chain-producing regions are popular in Lupus I which can be regard as a Taurus like molecular cloud complex in our Galaxy. The column densities of C3S are larger than those of HC7N in the three outflow sources I20582, L1221 and L1251A. Shocked carbon-chain chemistry (SCCC) is proposed to explain the abnormal high abundances of C3S compared with those of nitrogen-bearing CCMs. Gas-grain chemical models support the idea that shocks can fuel the environment of those sources with enough $S^+$ thus driving the generation of S-bearing CCMs.Comment: 7 figures, 8 tables, accepted by MNRA

Augmenting hematoma-scavenging capacity of innate immune cells by CDNF reduces brain injury and promotes functional recovery after intracerebral hemorrhage

During intracerebral hemorrhage (ICH), hematoma formation at the site of blood vessel damage results in local mechanical injury. Subsequently, erythrocytes lyse to release hemoglobin and heme, which act as neurotoxins and induce inflammation and secondary brain injury, resulting in severe neurological deficits. Accelerating hematoma resorption and mitigating hematoma-induced brain edema by modulating immune cells has potential as a novel therapeutic strategy for functional recovery after ICH. Here, we show that intracerebroventricular administration of recombinant human cerebral dopamine neurotrophic factor (rhCDNF) accelerates hemorrhagic lesion resolution, reduces peri-focal edema, and improves neurological outcomes in an animal model of collagenase-induced ICH. We demonstrate that CDNF acts on microglia/macrophages in the hemorrhagic striatum by promoting scavenger receptor expression, enhancing erythrophagocytosis and increasing anti-inflammatory mediators while suppressing the production of pro-inflammatory cytokines. Administration of rhCDNF results in upregulation of the Nrf2-HO-1 pathway, but alleviation of oxidative stress and unfolded protein responses in the perihematomal area. Finally, we demonstrate that intravenous delivery of rhCDNF has beneficial effects in an animal model of ICH and that systemic application promotes scavenging by the brain's myeloid cells for the treatment of ICH.Peer reviewe

Glycolytic flux control by drugging phosphoglycolate phosphatase

Targeting the intrinsic metabolism of immune or tumor cells is a therapeutic strategy in autoimmunity, chronic inflammation or cancer. Metabolite repair enzymes may represent an alternative target class for selective metabolic inhibition, but pharmacological tools to test this concept are needed. Here, we demonstrate that phosphoglycolate phosphatase (PGP), a prototypical metabolite repair enzyme in glycolysis, is a pharmacologically actionable target. Using a combination of small molecule screening, protein crystallography, molecular dynamics simulations and NMR metabolomics, we discover and analyze a compound (CP1) that inhibits PGP with high selectivity and submicromolar potency. CP1 locks the phosphatase in a catalytically inactive conformation, dampens glycolytic flux, and phenocopies effects of cellular PGP-deficiency. This study provides key insights into effective and precise PGP targeting, at the same time validating an allosteric approach to control glycolysis that could advance discoveries of innovative therapeutic candidates

Disentangling the Evolution of Electrons and Holes in photoexcited ZnO nanoparticles

The evolution of charge carriers in photoexcited room temperature ZnO nanoparticles in solution is investigated using ultrafast ultraviolet photoluminescence spectroscopy, ultrafast Zn K-edge absorption spectroscopy and ab-initio molecular dynamics (MD) simulations. The photoluminescence is excited at 4.66 eV, well above the band edge, and shows that electron cooling in the conduction band and exciton formation occur in <500 fs, in excellent agreement with theoretical predictions. The X-ray absorption measurements, obtained upon excitation close to the band edge at 3.49 eV, are sensitive to the migration and trapping of holes. They reveal that the 2 ps transient largely reproduces the previously reported transient obtained at 100 ps time delay in synchrotron studies. In addition, the X-ray absorption signal is found to rise in ~1.4 ps, which we attribute to the diffusion of holes through the lattice prior to their trapping at singly-charged oxygen vacancies. Indeed, the MD simulations show that impulsive trapping of holes induces an ultrafast expansion of the cage of Zn atoms in <200 fs, followed by an oscillatory response at a frequency of ~100 cm-1, which corresponds to a phonon mode of the system involving the Zn sub-lattice

A parallel cellular automata Lattice Boltzmann Method for convection-driven solidification

This article presents a novel coupling of numerical techniques that enable three-dimensional convection-driven microstructure simulations to be con- ducted on practical time scales appropriate for small-size components or experiments. On the microstructure side, the cellular automata method is efficient for relatively large-scale simulations, while the lattice Boltzmann method provides one of the fastest transient computational fluid dynamics solvers. Both of these methods have been parallelized and coupled in a single code, allowing resolution of large-scale convection-driven solidification problems. The numerical model is validated against benchmark cases, extended to capture solute plumes in directional solidification and finally used to model alloy solidification of an entire differentially heated cavity capturing both microstructural and meso-/macroscale phenomena

Identification of six new susceptibility loci for invasive epithelial ovarian cancer.

Genome-wide association studies (GWAS) have identified 12 epithelial ovarian cancer (EOC) susceptibility alleles. The pattern of association at these loci is consistent in BRCA1 and BRCA2 mutation carriers who are at high risk of EOC. After imputation to 1000 Genomes Project data, we assessed associations of 11 million genetic variants with EOC risk from 15,437 cases unselected for family history and 30,845 controls and from 15,252 BRCA1 mutation carriers and 8,211 BRCA2 mutation carriers (3,096 with ovarian cancer), and we combined the results in a meta-analysis. This new study design yielded increased statistical power, leading to the discovery of six new EOC susceptibility loci. Variants at 1p36 (nearest gene, WNT4), 4q26 (SYNPO2), 9q34.2 (ABO) and 17q11.2 (ATAD5) were associated with EOC risk, and at 1p34.3 (RSPO1) and 6p22.1 (GPX6) variants were specifically associated with the serous EOC subtype, all with P < 5 × 10(-8). Incorporating these variants into risk assessment tools will improve clinical risk predictions for BRCA1 and BRCA2 mutation carriers.COGS project is funded through a European Commission's Seventh Framework Programme grant (agreement number 223175 ] HEALTH ]F2 ]2009 ]223175). The CIMBA data management and data analysis were supported by Cancer Research.UK grants 12292/A11174 and C1287/A10118. The Ovarian Cancer Association Consortium is supported by a grant from the Ovarian Cancer Research Fund thanks to donations by the family and friends of Kathryn Sladek Smith (PPD/RPCI.07). The scientific development and funding for this project were in part supported by the US National Cancer Institute GAME ]ON Post ]GWAS Initiative (U19 ]CA148112). This study made use of data generated by the Wellcome Trust Case Control consortium. Funding for the project was provided by the Wellcome Trust under award 076113. The results published here are in part based upon data generated by The Cancer Genome Atlas Pilot Project established by the National Cancer Institute and National Human Genome Research Institute (dbGap accession number phs000178.v8.p7). The cBio portal is developed and maintained by the Computational Biology Center at Memorial Sloan ] Kettering Cancer Center. SH is supported by an NHMRC Program Grant to GCT. Details of the funding of individual investigators and studies are provided in the Supplementary Note. This study made use of data generated by the Wellcome Trust Case Control consortium, funding for which was provided by the Wellcome Trust under award 076113. The results published here are, in part, based upon data generated by The Cancer Genome Atlas Pilot Project established by the National Cancerhttp://dx.doi.org/10.1038/ng.3185This is the Author Accepted Manuscript of 'Identification of six new susceptibility loci for invasive epithelial ovarian cancer' which was published in Nature Genetics 47, 164–171 (2015) © Nature Publishing Group - content may only be used for academic research

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals &lt;1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe