Synthesis, Characterization And Electrolytic Behavior Of Cadmium(II) Complexes Of 5,7,7,12,14,14- Hexamethyl-1,4,8,11-Tetraazacyclotetradeca-4,11- Diene And Isomers Of Its Saturated Analogue

Condensation of ethylendiamine with acetone in the presence of quantitative amount of perchloric acid, yielded the ligand 5,7,7,12,14,14- hexamethyl-1,4,8,11-tetraazacyclotetradeca-4,11-diene dihydroperchlorate (denoted by L.2HClO4). The ligand L.2HClO4 on reduction with NaBH4, yielded an isomeric mixture of saturated macrocycles, the Me6[14]anes, which were resolved into two distinct C-chiral isomers (denoted by ‘tet-a’ and ‘tet-b’). Interaction of ligands L.2HClO4, ‘tet-a’ and ‘tet-b’ with salts CdI2, Cd(NO3)2.4H2O, CdCl2.2H2O and Cd(ClO4)2.6H2O produced different five coordinated square pyramidal and six coordinated octahedral cdmium(II) complexes. Among them the complexes, cis-[Cd(teta)( NO3)](NO3) and cis-[Cd(tet-b)(NO3)](NO3) underwent axial ligand substitution reaction with KCNS; whereas complex [Cd(tet-a)I2] underwent axial ligand substitution reaction and complex [CdLI](ClO4) underwent simultaneous ligand substitution and addition reaction with NaNO2. Characterization of all the complexes were carried out on the basis of elemental analysis; FT-IR, UV-Vis. and 1H-NMR spectroscopy; melting point determination as well as by magnetic moment and conductivity measurements. Molar conductivity measurment of the complexes reavealed that they show different electrolytic behavior in different solvents

High-Fidelity Simulation and Novel Data Analysis of the Bubble Creation and Sound Generation Processes in Breaking Waves

Recent increases in computing power have enabled the numerical simulation of many complex flow problems that are of practical and strategic interest for naval applications. A noticeable area of advancement is the computation of turbulent, two-phase flows resulting from wave breaking and other multiphase flow processes such as cavitation that can generate underwater sound and entrain bubbles in ship wakes, among other effects. Although advanced flow solvers are sophisticated and are capable of simulating high Reynolds number flows on large numbers of grid points, challenges in data analysis remain. Specifically, there is a critical need to transform highly resolved flow fields described on fine grids at discrete time steps into physically resolved features for which the flow dynamics can be understood and utilized in naval applications. This paper presents our recent efforts in this field. In previous works, we developed a novel algorithm to track bubbles in breaking wave simulations and to interpret their dynamical behavior over time (Gao et al., 2021a). We also discovered a new physical mechanism driving bubble production within breaking wave crests (Gao et al., 2021b) and developed a model to relate bubble behaviors to underwater sound generation (Gao et al., 2021c). In this work, we applied our bubble tracking algorithm to the breaking waves simulations and investigated the bubble trajectories, bubble creation mechanisms, and bubble acoustics based on our previous works.Comment: conferenc

Zinc(II) complexes of 3,10-C-meso-2,5,5,7,9,12,12,14- octamethyl-1,8-diaza-4,11-diazoniacyclotetradecane as its bis(acetate) trihydrate, [LBH2][CH3COO]2.3H2O: Synthesis, Characterization and antimicrobial studies

One isomeric ligand, LB among three isomers (LA, LB and LC) of 2,9- C-meso-2,5,5,7,9,12,12,14-octamethyl-1,4,8,11-tetraazacyclotetradecanes, differing in the orientation of methyl groups on the chiral carbon atoms) on interaction with vinyl acetate produces 2,9-C-meso-2,5,5,7,9,12,12,14- octamethyl-1,8-diaza-4,11-diazoniacyclotetradecane as its bis(acetate) trihydrate, [LBH2][OOCCH3]2.3H2O. This ligand salt trihydrate reacts with Zn(CH3COO)2.2H2O to produce square pyramidal monoacetatozinc(II) acetate complex [ZnLB(CH3COO)](CH3COO), which undergoes anion exchange reaction with NaClO4.6H2O to produce monoacetatozinc(II) perchlorate complex, [ZnLB(CH3COO)](ClO4). The complex, [ZnLB(CH3COO)](ClO4) undergoes axial substitution reactions with KSCN, NaNO2 and KNO3 to form the substitution products, [ZnLB(NCS)](NCS), [ZnLB(NO2)](ClO4) and [ZnLB(NO3)](ClO4) respectively where CH3COOis replaced by NCS- , NO3 - and NO2 - . All these complexes have been characterized on the basis of analytical, spectroscopic, conductometric and magnetochemical data. The antifungal and antibacterial activities of these compounds have been studied against some phytopathogenic fungi and bacteria

Insulin resistance drives hepatic de novo lipogenesis in nonalcoholic fatty liver disease

BACKGROUNDAn increase in intrahepatic triglyceride (IHTG) is the hallmark feature of nonalcoholic fatty liver disease (NAFLD) and is decreased by weight loss. Hepatic de novo lipogenesis (DNL) contributes to steatosis in individuals with NAFLD. The physiological factors that stimulate hepatic DNL and the effect of weight loss on hepatic DNL are not clear.METHODSHepatic DNL, 24-hour integrated plasma insulin and glucose concentrations, and both liver and whole-body insulin sensitivity were determined in individuals who were lean (n = 14), obese with normal IHTG content (n = 26), or obese with NAFLD (n = 27). Hepatic DNL was assessed using the deuterated water method corrected for the potential confounding contribution of adipose tissue DNL. Liver and whole-body insulin sensitivity was assessed using the hyperinsulinemic-euglycemic clamp procedure in conjunction with glucose tracer infusion. Six subjects in the obese-NAFLD group were also evaluated before and after a diet-induced weight loss of 10%.RESULTSThe contribution of hepatic DNL to IHTG-palmitate was 11%, 19%, and 38% in the lean, obese, and obese-NAFLD groups, respectively. Hepatic DNL was inversely correlated with hepatic and whole-body insulin sensitivity, but directly correlated with 24-hour plasma glucose and insulin concentrations. Weight loss decreased IHTG content, in conjunction with a decrease in hepatic DNL and 24-hour plasma glucose and insulin concentrations.CONCLUSIONSThese data suggest hepatic DNL is an important regulator of IHTG content and that increases in circulating glucose and insulin stimulate hepatic DNL in individuals with NAFLD. Weight loss decreased IHTG content, at least in part, by decreasing hepatic DNL.TRIAL REGISTRATIONClinicalTrials.gov NCT02706262.FUNDINGThis study was supported by NIH grants DK56341 (Nutrition Obesity Research Center), DK20579 (Diabetes Research Center), DK52574 (Digestive Disease Research Center), and RR024992 (Clinical and Translational Science Award), and by grants from the Academy of Nutrition and Dietetics Foundation, the College of Natural Resources of UCB, and the Pershing Square Foundation

Addressing the under-reporting of adverse drug reactions in public health programs controlling HIV/AIDS, tuberculosis and malaria: A prospective cohort study

Background Adverse Drug Reactions (ADRs) are a major clinical and public health problem world-wide. The prompt reporting of suspected ADRs to regulatory authorities to activate drug safety surveillance and regulation appears to be the most pragmatic measure for addressing the problem. This paper evaluated a pharmacovigilance (PV) training model that was designed to improve the reporting of ADRs in public health programs treating the Human Immunodeficiency Virus (HIV), Tuberculosis (TB) and Malaria. Methods A Structured Pharmacovigilance and Training Initiative (SPHAR-TI) model based on the World Health Organization accredited Structured Operational Research and Training Initiative (SOR-IT) model was designed and implemented over a period of 12 months. A prospective cohort design was deployed to evaluate the outcomes of the model. The primary outcomes were knowledge gained and Individual Case Safety Reports (ICSR) (completed adverse drug reactions monitoring forms) submitted, while the secondary outcomes were facility based Pharmacovigilance Committees activated and health facility healthcare workers trained by the participants. Results Fifty-five (98%) participants were trained and followed up for 12 months. More than three quarter of the participants have never received training on pharmacovigilance prior to the course. Yet, a significant gain in knowledge was observed after the participants completed a comprehensive training for six days. In only seven months, 3000 ICSRs (with 100% completeness) were submitted, 2,937 facility based healthcare workers trained and 46 Pharmacovigilance Committees activated by the participants. Overall, a 273% increase in ICSRs submission to the National Agency for Food and Drug Administration and Control (NAFDAC) was observed. Conclusion Participants gained knowledge, which tended to increase the reporting of ADRs. The SPHAR-TI model could be an option for strengthening the continuous reporting of ADRs in public health programs in resource limited settings

Identification of a tyrosine residue responsible for N-acetylimidazole-induced increase of activity of ecto-nucleoside triphosphate diphosphohydrolase 3

Chemical modification in combination with site-directed mutagenesis was used to identify a tyrosine residue responsible for the increase in ecto-nucleoside triphosphate diphosphohydrolase 3 (NTPDase3) nucleotidase activity after acetylation with a tyrosine-selective reagent, N-acetylimidazole. The NTPDase3 ATPase activity is increased more than the ADPase activity by this reagent. Several fairly well conserved tyrosine residues (252, 255, and 262) that are located in or very near apyrase conserved region 4a (ACR4a) were mutated. These mutants were all active, but mutation of tyrosine 252 to either alanine or phenylalanine eliminated the activity increase observed after N-acetylimidazole treatment of the wild-type enzyme. This suggests that the acetylation of tyrosine 252 is responsible for the increased activity. Stabilization of quaternary structure has resulted in increased enzyme activities for the NTPDases. However, mutation of these three tyrosine residues did not result in global changes of tertiary or quaternary structure, as measured by Cibacron blue binding, chemical cross linking, and native gel electrophoretic analysis. Nevertheless, disruption of the oligomeric structure with the detergent Triton X-100 abolished the increase in activity induced by this reagent. In addition, mutations that abolished the N-acetylimidazole effect also attenuated the increases of enzyme activity observed after lectin and chemical cross-linking treatments, which were previously attributed to stabilization of the quaternary structure. Thus, we speculate that the acetylation of tyrosine 252 might induce a subtle conformational change in NTPDase3, resulting in the observed increase in activity

Electrical conductivity during incipient melting in the oceanic low-velocity zone

International audienceThe low-viscosity layer in the upper mantle, the asthenosphere, is a requirement for plate tectonics1. The seismic low velocities and the high electrical conductivities of the asthenosphere are attributed either to subsolidus, water-related defects in olivine minerals2, 3, 4 or to a few volume per cent of partial melt5, 6, 7, 8, but these two interpretations have two shortcomings. First, the amount of water stored in olivine is not expected to be higher than 50 parts per million owing to partitioning with other mantle phases9 (including pargasite amphibole at moderate temperatures10) and partial melting at high temperatures9. Second, elevated melt volume fractions are impeded by the temperatures prevailing in the asthenosphere, which are too low, and by the melt mobility, which is high and can lead to gravitational segregation11, 12. Here we determine the electrical conductivity of carbon-dioxide-rich and water-rich melts, typically produced at the onset of mantle melting. Electrical conductivity increases modestly with moderate amounts of water and carbon dioxide, but it increases drastically once the carbon dioxide content exceeds six weight per cent in the melt. Incipient melts, long-expected to prevail in the asthenosphere10, 13, 14, 15, can therefore produce high electrical conductivities there. Taking into account variable degrees of depletion of the mantle in water and carbon dioxide, and their effect on the petrology of incipient melting, we calculated conductivity profiles across the asthenosphere for various tectonic plate ages. Several electrical discontinuities are predicted and match geophysical observations in a consistent petrological and geochemical framework. In moderately aged plates (more than five million years old), incipient melts probably trigger both the seismic low velocities and the high electrical conductivities in the upper part of the asthenosphere, whereas in young plates4, where seamount volcanism occurs6, a higher degree of melting is expected

Report on the sixth blind test of organic crystal structure prediction methods.

The sixth blind test of organic crystal structure prediction (CSP) methods has been held, with five target systems: a small nearly rigid molecule, a polymorphic former drug candidate, a chloride salt hydrate, a co-crystal and a bulky flexible molecule. This blind test has seen substantial growth in the number of participants, with the broad range of prediction methods giving a unique insight into the state of the art in the field. Significant progress has been seen in treating flexible molecules, usage of hierarchical approaches to ranking structures, the application of density-functional approximations, and the establishment of new workflows and `best practices' for performing CSP calculations. All of the targets, apart from a single potentially disordered Z' = 2 polymorph of the drug candidate, were predicted by at least one submission. Despite many remaining challenges, it is clear that CSP methods are becoming more applicable to a wider range of real systems, including salts, hydrates and larger flexible molecules. The results also highlight the potential for CSP calculations to complement and augment experimental studies of organic solid forms.The organisers and participants are very grateful to the crystallographers who supplied the candidate structures: Dr. Peter Horton (XXII), Dr. Brian Samas (XXIII), Prof. Bruce Foxman (XXIV), and Prof. Kraig Wheeler (XXV and XXVI). We are also grateful to Dr. Emma Sharp and colleagues at Johnson Matthey (Pharmorphix) for the polymorph screening of XXVI, as well as numerous colleagues at the CCDC for assistance in organising the blind test. Submission 2: We acknowledge Dr. Oliver Korb for numerous useful discussions. Submission 3: The Day group acknowledge the use of the IRIDIS High Performance Computing Facility, and associated support services at the University of Southampton, in the completion of this work. We acknowledge funding from the EPSRC (grants EP/J01110X/1 and EP/K018132/1) and the European Research Council under the European Union’s Seventh Framework Programme (FP/2007-2013)/ERC through grant agreements n. 307358 (ERC-stG- 2012-ANGLE) and n. 321156 (ERC-AG-PE5-ROBOT). Submission 4: I am grateful to Mikhail Kuzminskii for calculations of molecular structures on Gaussian 98 program in the Institute of Organic Chemistry RAS. The Russian Foundation for Basic Research is acknowledged for financial support (14-03-01091). Submission 5: Toine Schreurs provided computer facilities and assistance. I am grateful to Matthew Habgood at AWE company for providing a travel grant. Submission 6: We would like to acknowledge support of this work by GlaxoSmithKline, Merck, and Vertex. Submission 7: The research was financially supported by the VIDI Research Program 700.10.427, which is financed by The Netherlands Organisation for Scientific Research (NWO), and the European Research Council (ERC-2010-StG, grant agreement n. 259510-KISMOL). We acknowledge the support of the Foundation for Fundamental Research on Matter (FOM). Supercomputer facilities were provided by the National Computing Facilities Foundation (NCF). Submission 8: Computer resources were provided by the Center for High Performance Computing at the University of Utah and the Extreme Science and Engineering Discovery Environment (XSEDE), supported by NSF grant number ACI-1053575. MBF and GIP acknowledge the support from the University of Buenos Aires and the Argentinian Research Council. Submission 9: We thank Dr. Bouke van Eijck for his valuable advice on our predicted structure of XXV. We thank the promotion office for TUT programs on advanced simulation engineering (ADSIM), the leading program for training brain information architects (BRAIN), and the information and media center (IMC) at Toyohashi University of Technology for the use of the TUT supercomputer systems and application software. We also thank the ACCMS at Kyoto University for the use of their supercomputer. In addition, we wish to thank financial supports from Conflex Corp. and Ministry of Education, Culture, Sports, Science and Technology. Submission 12: We thank Leslie Leiserowitz from the Weizmann Institute of Science and Geoffrey Hutchinson from the University of Pittsburgh for helpful discussions. We thank Adam Scovel at the Argonne Leadership Computing Facility (ALCF) for technical support. Work at Tulane University was funded by the Louisiana Board of Regents Award # LEQSF(2014-17)-RD-A-10 “Toward Crystal Engineering from First Principles”, by the NSF award # EPS-1003897 “The Louisiana Alliance for Simulation-Guided Materials Applications (LA-SiGMA)”, and by the Tulane Committee on Research Summer Fellowship. Work at the Technical University of Munich was supported by the Solar Technologies Go Hybrid initiative of the State of Bavaria, Germany. Computer time was provided by the Argonne Leadership Computing Facility (ALCF), which is supported by the Office of Science of the U.S. Department of Energy under contract DE-AC02-06CH11357. Submission 13: This work would not have been possible without funding from Khalifa University’s College of Engineering. I would like to acknowledge Prof. Robert Bennell and Prof. Bayan Sharif for supporting me in acquiring the resources needed to carry out this research. Dr. Louise Price is thanked for her guidance on the use of DMACRYS and NEIGHCRYS during the course of this research. She is also thanked for useful discussions and numerous e-mail exchanges concerning the blind test. Prof. Sarah Price is acknowledged for her support and guidance over many years and for providing access to DMACRYS and NEIGHCRYS. Submission 15: The work was supported by the United Kingdom’s Engineering and Physical Sciences Research Council (EPSRC) (EP/J003840/1, EP/J014958/1) and was made possible through access to computational resources and support from the High Performance Computing Cluster at Imperial College London. We are grateful to Professor Sarah L. Price for supplying the DMACRYS code for use within CrystalOptimizer, and to her and her research group for support with DMACRYS and feedback on CrystalPredictor and CrystalOptimizer. Submission 16: R. J. N. acknowledges financial support from the Engineering and Physical Sciences Research Council (EPSRC) of the U.K. [EP/J017639/1]. R. J. N. and C. J. P. acknowledge use of the Archer facilities of the U.K.’s national high-performance computing service (for which access was obtained via the UKCP consortium [EP/K014560/1]). C. J. P. also acknowledges a Leadership Fellowship Grant [EP/K013688/1]. B. M. acknowledges Robinson College, Cambridge, and the Cambridge Philosophical Society for a Henslow Research Fellowship. Submission 17: The work at the University of Delaware was supported by the Army Research Office under Grant W911NF-13-1- 0387 and by the National Science Foundation Grant CHE-1152899. The work at the University of Silesia was supported by the Polish National Science Centre Grant No. DEC-2012/05/B/ST4/00086. Submission 18: We would like to thank Constantinos Pantelides, Claire Adjiman and Isaac Sugden of Imperial College for their support of our use of CrystalPredictor and CrystalOptimizer in this and Submission 19. The CSP work of the group is supported by EPSRC, though grant ESPRC EP/K039229/1, and Eli Lilly. The PhD students support: RKH by a joint UCL Max-Planck Society Magdeburg Impact studentship, REW by a UCL Impact studentship; LI by the Cambridge Crystallographic Data Centre and the M3S Centre for Doctoral Training (EPSRC EP/G036675/1). Submission 19: The potential generation work at the University of Delaware was supported by the Army Research Office under Grant W911NF-13-1-0387 and by the National Science Foundation Grant CHE-1152899. Submission 20: The work at New York University was supported, in part, by the U.S. Army Research Laboratory and the U.S. Army Research Office under contract/grant number W911NF-13-1-0387 (MET and LV) and, in part, by the Materials Research Science and Engineering Center (MRSEC) program of the National Science Foundation under Award Number DMR-1420073 (MET and ES). The work at the University of Delaware was supported by the U.S. Army Research Laboratory and the U.S. Army Research Office under contract/grant number W911NF-13-1- 0387 and by the National Science Foundation Grant CHE-1152899. Submission 21: We thank the National Science Foundation (DMR-1231586), the Government of Russian Federation (Grant No. 14.A12.31.0003), the Foreign Talents Introduction and Academic Exchange Program (No. B08040) and the Russian Science Foundation, project no. 14-43-00052, base organization Photochemistry Center of the Russian Academy of Sciences. Calculations were performed on the Rurik supercomputer at Moscow Institute of Physics and Technology. Submission 22: The computational results presented have been achieved in part using the Vienna Scientific Cluster (VSC). Submission 24: The potential generation work at the University of Delaware was supported by the Army Research Office under Grant W911NF-13-1-0387 and by the National Science Foundation Grant CHE-1152899. Submission 25: J.H. and A.T. acknowledge the support from the Deutsche Forschungsgemeinschaft under the program DFG-SPP 1807. H-Y.K., R.A.D., and R.C. acknowledge support from the Department of Energy (DOE) under Grant Nos. DE-SC0008626. This research used resources of the Argonne Leadership Computing Facility at Argonne National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-06CH11357. This research used resources of the National Energy Research Scientific Computing Center, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DEAC02-05CH11231. Additional computational resources were provided by the Terascale Infrastructure for Groundbreaking Research in Science and Engineering (TIGRESS) High Performance Computing Center and Visualization Laboratory at Princeton University.This is the final version of the article. It first appeared from Wiley via http://dx.doi.org/10.1107/S2052520616007447

Photoreceptor glucose metabolism determines normal retinal vascular growth

Abstract The neural cells and factors determining normal vascular growth are not well defined even though vision‐threatening neovessel growth, a major cause of blindness in retinopathy of prematurity (ROP) (and diabetic retinopathy), is driven by delayed normal vascular growth. We here examined whether hyperglycemia and low adiponectin (APN) levels delayed normal retinal vascularization, driven primarily by dysregulated photoreceptor metabolism. In premature infants, low APN levels correlated with hyperglycemia and delayed retinal vascular formation. Experimentally in a neonatal mouse model of postnatal hyperglycemia modeling early ROP, hyperglycemia caused photoreceptor dysfunction and delayed neurovascular maturation associated with changes in the APN pathway; recombinant mouse APN or APN receptor agonist AdipoRon treatment normalized vascular growth. APN deficiency decreased retinal mitochondrial metabolic enzyme levels particularly in photoreceptors, suppressed retinal vascular development, and decreased photoreceptor platelet‐derived growth factor (Pdgfb). APN pathway activation reversed these effects. Blockade of mitochondrial respiration abolished AdipoRon‐induced Pdgfb increase in photoreceptors. Photoreceptor knockdown of Pdgfb delayed retinal vascular formation. Stimulation of the APN pathway might prevent hyperglycemia‐associated retinal abnormalities and suppress phase I ROP in premature infants

Software for the frontiers of quantum chemistry:An overview of developments in the Q-Chem 5 package

This article summarizes technical advances contained in the fifth major release of the Q-Chem quantum chemistry program package, covering developments since 2015. A comprehensive library of exchange–correlation functionals, along with a suite of correlated many-body methods, continues to be a hallmark of the Q-Chem software. The many-body methods include novel variants of both coupled-cluster and configuration-interaction approaches along with methods based on the algebraic diagrammatic construction and variational reduced density-matrix methods. Methods highlighted in Q-Chem 5 include a suite of tools for modeling core-level spectroscopy, methods for describing metastable resonances, methods for computing vibronic spectra, the nuclear–electronic orbital method, and several different energy decomposition analysis techniques. High-performance capabilities including multithreaded parallelism and support for calculations on graphics processing units are described. Q-Chem boasts a community of well over 100 active academic developers, and the continuing evolution of the software is supported by an “open teamware” model and an increasingly modular design