Violent Deaths of Iraqi Civilians, 2003–2008: Analysis by Perpetrator, Weapon, Time, and Location

Madelyn Hsiao-Rei Hicks and colleagues provide a detailed analysis of Iraqi civilian violent deaths during 2003-2008 of the Iraq war and show that of 92,614 deaths, unknown perpetrators caused 74% of deaths, Coalition forces 12%, and Anti-Coalition forces 11%

Crystal Structures of DNA Intercalating Agents Dipyrido[3,2-f:2′,3′-h]quinoxaline (dpq), (Benzo[<i>i</i>]dipyrido[3,2-a:2′,3′c]phenazine (dppn), and [Ir(ppy)₂(dppn)][PF₆] (Where Hppy = 2-Phenylpyridine)

Pyrazino-phenanthroline ligands are commonly used with transition metals as DNA intercalation agents. Herein, we report the characterization of two commonly utilized pyrazino-phenanthroline ligands, dipyrido[3,2-f:2′,3′-h]quinoxaline (dpq) and (benzo[i]dipyrido[3,2-a:2′,3′c]phenazine (dppn), by single-crystal X-ray diffraction. Additionally, the characterization of [Ir(ppy)2(dppn)][PF6], where Hppy = 2-phenylpyridine, by single-crystal X-ray diffraction is described. Both the dpq and dppn ligands crystallize as chloroform solvates where the chloroform molecule occupies the equivalent binding pocket of a metal in metal complexes of these ligands. These pyrazino-phenanthrolines are largely planar, with the dppn ligand displaying a slight twist. When the dppn ligand is coordinated to iridium(III), the dppn ligand on the resulting complex displays a significant degree of bending along the longitudinal direction of the ligand. This iridium (III) complex crystallizes as a CH2Cl2 and Et2O solvate and due to the volatility of these solvents these crystals are only stable for a few seconds outside of the mother liquor. The structures of the free ligands and the [Ir(ppy)2(dppn)][PF6] complex all display extensive π stacking interactions

Genome-wide miRNA response to anacardic acid in breast cancer cells.

MicroRNAs are biomarkers and potential therapeutic targets for breast cancer. Anacardic acid (AnAc) is a dietary phenolic lipid that inhibits both MCF-7 estrogen receptor α (ERα) positive and MDA-MB-231 triple negative breast cancer (TNBC) cell proliferation with IC50s of 13.5 and 35 μM, respectively. To identify potential mediators of AnAc action in breast cancer, we profiled the genome-wide microRNA transcriptome (microRNAome) in these two cell lines altered by the AnAc 24:1n5 congener. Whole genome expression profiling (RNA-seq) and subsequent network analysis in MetaCore Gene Ontology (GO) algorithm was used to characterize the biological pathways altered by AnAc. In MCF-7 cells, 69 AnAc-responsive miRNAs were identified, e.g., increased let-7a and reduced miR-584. Fewer, i.e., 37 AnAc-responsive miRNAs were identified in MDA-MB-231 cells, e.g., decreased miR-23b and increased miR-1257. Only two miRNAs were increased by AnAc in both cell lines: miR-612 and miR-20b; however, opposite miRNA arm preference was noted: miR-20b-3p and miR-20b-5p were upregulated in MCF-7 and MDA-MB-231, respectively. miR-20b-5p target EFNB2 transcript levels were reduced by AnAc in MDA-MB-231 cells. AnAc reduced miR-378g that targets VIM (vimentin) and VIM mRNA transcript expression was increased in AnAc-treated MCF-7 cells, suggesting a reciprocal relationship. The top three enriched GO terms for AnAc-treated MCF-7 cells were B cell receptor signaling pathway and ribosomal large subunit biogenesis and S-adenosylmethionine metabolic process for AnAc-treated MDA-MB-231 cells. The pathways modulated by these AnAc-regulated miRNAs suggest that key nodal molecules, e.g., Cyclin D1, MYC, c-FOS, PPARγ, and SIN3, are targets of AnAc activity

Resistance exercise protects mice from protein-induced fat accretion

Low-protein (LP) diets extend the lifespan of diverse species and are associated with improved metabolic health in both rodents and humans. Paradoxically, many athletes and bodybuilders consume high-protein (HP) diets and protein supplements, yet are both fit and metabolically healthy. Here, we examine this paradox using weight pulling, a validated progressive resistance exercise training regimen, in mice fed either an LP diet or an isocaloric HP diet. We find that despite having lower food consumption than the LP group, HP-fed mice gain significantly more fat mass than LP-fed mice when not exercising, while weight pulling protected HP-fed mice from this excess fat accretion. The HP diet augmented exercise-induced hypertrophy of the forearm flexor complex, and weight pulling ability increased more rapidly in the exercised HP-fed mice. Surprisingly, exercise did not protect from HP-induced changes in glycemic control. Our results confirm that HP diets can augment muscle hypertrophy and accelerate strength gain induced by resistance exercise without negative effects on fat mass, and also demonstrate that LP diets may be advantageous in the sedentary. Our results highlight the need to consider both dietary composition and activity, not simply calories, when taking a precision nutrition approach to health

miRNAs upregulated by AnAc MCF-7 cells.

<p>The genomic location of each miRNA was identified in miRAD <a href="http://bmi.ana.med.uni-muenchen.de/miriad/" target="_blank">http://bmi.ana.med.uni-muenchen.de/miriad/</a> [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0184471#pone.0184471.ref034" target="_blank">34</a>]. Verified targets are those experimentally validated targets of the indicated miRNA as demonstrated by 3’-UTR luciferase reporter assay in the cited reference. Since many publications do not include whether the 5p or 3p arm of the miRNA was studied, if the sequence of the miRNA was provided, it was searched in miRBase.org to identify which arm was used in the target gene 3’-UTR luciferase reporter assay.</p

miRNAs upregulated by AnAc in MDA-MB-231 cells.

<p>The genomic location of each miRNA was identified in miRAD <a href="http://bmi.ana.med.uni-muenchen.de/miriad/" target="_blank">http://bmi.ana.med.uni-muenchen.de/miriad/</a> [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0184471#pone.0184471.ref034" target="_blank">34</a>]. Verified targets are those experimentally validated targets of the indicated miRNA as demonstrated by 3’-UTR luciferase reporter assay. Since many publications do not include whether the 5p or 3p arm of the miRNA was studied, if the sequence of the miRNA was provided, it was searched in miRBase.org to identify which arm was used in the target gene 3’-UTR luciferase reporter assay.</p

miRNAs downregulated by AnAc in MCF-7 cells.

<p>The genomic location of each miRNA was identified in miRAD <a href="http://bmi.ana.med.uni-muenchen.de/miriad/" target="_blank">http://bmi.ana.med.uni-muenchen.de/miriad/</a> [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0184471#pone.0184471.ref034" target="_blank">34</a>]. Verified targets are those experimentally validated targets of the indicated miRNA as demonstrated by 3’-UTR luciferase reporter assay. Since many publications do not include whether the 5p or 3p arm of the miRNA was studied, if the sequence of the miRNA was provided, it was searched in miRBase.org to identify which arm was used in the target gene 3’-UTR luciferase reporter assay.</p

A global metagenomic map of urban microbiomes and antimicrobial resistance

We present a global atlas of 4,728 metagenomic samples from mass-transit systems in 60 cities over 3 years, representing the first systematic, worldwide catalog of the urban microbial ecosystem. This atlas provides an annotated, geospatial profile of microbial strains, functional characteristics, antimicrobial resistance (AMR) markers, and genetic elements, including 10,928 viruses, 1,302 bacteria, 2 archaea, and 838,532 CRISPR arrays not found in reference databases. We identified 4,246 known species of urban microorganisms and a consistent set of 31 species found in 97% of samples that were distinct from human commensal organisms. Profiles of AMR genes varied widely in type and density across cities. Cities showed distinct microbial taxonomic signatures that were driven by climate and geographic differences. These results constitute a high-resolution global metagenomic atlas that enables discovery of organisms and genes, highlights potential public health and forensic applications, and provides a culture-independent view of AMR burden in cities.Funding: the Tri-I Program in Computational Biology and Medicine (CBM) funded by NIH grant 1T32GM083937; GitHub; Philip Blood and the Extreme Science and Engineering Discovery Environment (XSEDE), supported by NSF grant number ACI-1548562 and NSF award number ACI-1445606; NASA (NNX14AH50G, NNX17AB26G), the NIH (R01AI151059, R25EB020393, R21AI129851, R35GM138152, U01DA053941); STARR Foundation (I13- 0052); LLS (MCL7001-18, LLS 9238-16, LLS-MCL7001-18); the NSF (1840275); the Bill and Melinda Gates Foundation (OPP1151054); the Alfred P. Sloan Foundation (G-2015-13964); Swiss National Science Foundation grant number 407540_167331; NIH award number UL1TR000457; the US Department of Energy Joint Genome Institute under contract number DE-AC02-05CH11231; the National Energy Research Scientific Computing Center, supported by the Office of Science of the US Department of Energy; Stockholm Health Authority grant SLL 20160933; the Institut Pasteur Korea; an NRF Korea grant (NRF-2014K1A4A7A01074645, 2017M3A9G6068246); the CONICYT Fondecyt Iniciación grants 11140666 and 11160905; Keio University Funds for Individual Research; funds from the Yamagata prefectural government and the city of Tsuruoka; JSPS KAKENHI grant number 20K10436; the bilateral AT-UA collaboration fund (WTZ:UA 02/2019; Ministry of Education and Science of Ukraine, UA:M/84-2019, M/126-2020); Kyiv Academic Univeristy; Ministry of Education and Science of Ukraine project numbers 0118U100290 and 0120U101734; Centro de Excelencia Severo Ochoa 2013–2017; the CERCA Programme / Generalitat de Catalunya; the CRG-Novartis-Africa mobility program 2016; research funds from National Cheng Kung University and the Ministry of Science and Technology; Taiwan (MOST grant number 106-2321-B-006-016); we thank all the volunteers who made sampling NYC possible, Minciencias (project no. 639677758300), CNPq (EDN - 309973/2015-5), the Open Research Fund of Key Laboratory of Advanced Theory and Application in Statistics and Data Science – MOE, ECNU, the Research Grants Council of Hong Kong through project 11215017, National Key RD Project of China (2018YFE0201603), and Shanghai Municipal Science and Technology Major Project (2017SHZDZX01) (L.S.