Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time, and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space. While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes, vast areas of the tropics remain understudied. In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity, but it remains among the least known forests in America and is often underrepresented in biodiversity databases. To worsen this situation, human-induced modifications may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge, it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Understanding The Interaction Of Multi-walled Carbon Nanotubes With Mutagenic Organic Pollutants Using Computational Modeling And Biological Experiments

Carbon nanotubes (CNTs) are very promising materials to remove pollutants from the environment. To develop safe, efficient technologies, it is necessary to understand the mechanisms of interaction between CNTs and pollutants. This requires innovative, interdisciplinary approaches. Detailed chemical analysis of the CNTs along with computational modeling can provide important information about the mechanisms of interaction. If biological experiments are included in these studies, useful complementary information is obtained. To exemplify the use of this approach, we present a case study in which detailed calculations and the Salmonella mutagenicity assay were applied to elucidate how multi-walled CNTs interact with 1-nitropyrene, an important mutagenic pollutant. © 2011 Elsevier Ltd.303437446Baughman, R.H., Zakhidov, A.A., de Heer, W.A., (2002) Science (Washington, DC), 297, p. 787Dresselhaus, M.S., (2010) ACS Nano, 4, p. 4344Kostarelos, K., Bianco, A., Prato, M., (2009) Nat. Nanotechnol., 4, p. 627Khodakovskaya, M., Dervishi, E., Mahmood, M., Xu, Y., Watanabe, Z.L.F., Biris, A.S., (2009) ACS Nano, 3, p. 3221Wang, J., Lin, Y.H., (2008) Trends Anal. Chem., 27, p. 619Upadhyayula, V.K.K., Deng, S.G., Mitchell, M.C., Smith, G.B., (2009) Sci. Total Environ., 408, p. 1Ren, X., Chen, C., Nagatsu, M., Wang, X., (2010) Chem. Eng., , Journal, (in press). doi:10.1016/j.cej.2010.08.045Mauter, M.S., Elimelech, M., (2008) Environ. Sci. Tech., 42, p. 5843Kundu, S., Wang, Y., Xia, M., Muhler, M., (2008) J. Phys. Chem. C., 112, p. 16869Datsyuk, V., Kalyva, M., Papagelis, K., Parthenios, J., Tasis, D., Siokou, A., (2008) Carbon, 46, p. 833Peng, X., Jia, J., Luan, Z., (2009) J. Chem. Technol. Biotechnol., 84, p. 275Sheng, G.D., Shao, D.D., Ren, X.M., Wang, X.Q., Li, J.X., Chen, Y.X., Wang, X.K., (2010) J. Hazard. Mater., 178, p. 505Smajda, R., Mionic, M., Duchamp, M., Andresen, J.C., Forró, L., Magrez, A., (2010) Phys. Status Solidi C, 7, p. 1236Köhler, A.R., Som, C., Helland, A., Gottschalk, F., (2008) J. Cleaner Prod., 16, p. 927Cornelissen, G., Gustafsson, O., Bucheli, T.D., Koelmans, M.O., Van Noort, P.M., (2005) Environ. Sci. Technol., 39, p. 6881Ferguson, P.L., Chandler, G.T., Templeton, R.C., DeMarco, A., Scrivens, W.A., Englehart, B.A., (2008) Environ. Sci. Technol., 42, p. 3879Pérez, S., Farré, M., Barceló, D., (2009) Trends Anal. Chem., 28, p. 820Farré, M., Pérez, S., Kantiani, L., Barceló, D., (2008) Trends Anal. Chem., 27, p. 991Petersen, E.J., Pinto, R.A., Mai, D.J., Landrum, P.F., Weber, W.J., (2010) Environ. Sci. Technol., , in press, doi:10.1021/es10302Scheringer, M., (2008) Nat. Nanotechnol., 3, p. 322Kahru, A., Dubourguier, H.C., (2010) Toxicology, 269, p. 105Schatz, G.C., (2007) Proc. Natl. Acad. Sci. USA, 104, p. 6885Ohno, K., Esfarjani, K., Kawazoe, Y., (2000) Computational Materials Science. From Ab Initio to Monte Carlo Methods, (Springer Series in Solid-State Sciences) Springer, , New York, USAMartin, R.M., (2004) Electronic Structure: Basic Theory and Practical Methods, , Cambridge University Press, Cambridge, UKRapaport, D.C., (2004) The Art of Molecular Dynamics Simulation, , Cambridge University Press, Cambridge, UKKarplus, M., McCammon, J.A., (2002) Nat. Struct. Biol., 9, p. 646Barnard, A.S., (2010) Rep. Progr. Phys., 73, p. 086502Guo, G., Wang, F., Sun, H., Zhang, D., (2008) Int. J. Quantum Chem., 108, p. 203Yim, W.L., Gong, X.G., Liu, Z.F., (2003) J. Phys. Chem. B, 107, p. 9363Fagan, S.B., Santos, E.J.G., Souza Filho, A.G., Mendes Filho, J., Fazzio, A., (2007) Chem. Phys. Lett., 437, p. 79Fagan, S.B., Souza Filho, A.G., Lima, J.O.G., Mendes Filho, J., Ferreira, O.P., Mazali, I.O., Alves, O.L., Dresselhaus, M.S., (2004) Nano Lett., 4, p. 1285Tournus, F., Latil, S., Heggie, M.I., Charlier, J.C., (2005) Phys. Rev. B: Condens. Matter, 72, p. 075431Tournus, F., Charlier, J.C., (2005) Phys. Rev. B: Condens. Matter, 71, p. 165421Irving, D.L., Sinnott, S.B., Lindner, A.S., (2004) Chem. Phys. Lett., 389, p. 96Long, R.Q., Yang, R.T., (2001) J. Am. Chem. Soc., 123, p. 2058Li, Y.H., Wang, S.G., Zhang, X.F., Wei, J.Q., Xu, C.L., Luan, Z.K., Wu, D.H., (2003) Mater. Res. Bull., 38, p. 469Lu, C.S., Chung, Y.L., Chang, K.F., (2005) Water Res., 39, p. 1183Chen, Z.G., Zhang, L.S., Tang, Y.W., Jia, Z.J., (2006) Appl. Surf. Sci., 252, p. 2933Ji, L., Chen, W., Duan, L., Zhu, D., (2009) Environ. Sci. Tech., 43, p. 2322Ji, L., Chen, W., Zheng, S., Xu, Z., Zhu, D., (2009) Langmuir, 25, p. 11608Yang, K., Wang, X.L., Zhu, L.Z., Xing, B.S., (2006) Environ. Sci. Tech., 40, p. 5804Pan, B., Xing, B.S., (2008) Environ. Sci. Tech., 42, p. 9005Lam, C., James, J.T., McCluskey, R., Arepalli, S., Hunter, R.L., (2006) Crit. Rev. Toxicol., 36, p. 189Smart, S.K., Cassady, A.I., Lu, G.Q., Martin, D.J., (2006) Carbon, 44, p. 1034Oberdorster, G., (2010) J. Internal Med., 267, p. 89Koyama, S., Endo, M., Kim, Y.A., Hayashi, T., Yanagisawa, T., Osaka, K., Koyama, H., Kuroiwa, N., (2006) Carbon, 44, p. 1079Pauluhn, J., (2010) Toxicol. Sci., 113, p. 226Kolosnjaj-Tabi, J., Hartman, K.B., Boudjemaa, S., Ananta, J.S., Morgant, G., Szwarc, H., Wilson, L.J., Moussa, F., (2010) ACS Nano, 4, p. 1481Elder, A., (2009) Nat. Nanotechnol., 4, p. 409Bai, Y.H., Zhang, Y., Zhang, J.P., Mu, Q.X., Zhang, W.D., Butch, E.R., Snyder, S.E., Yan, B., (2010) Nat. Nanotechnol., 5, p. 683Migliore, L., Saracino, D., Bonelli, A., Colognato, R., D'Errico, M.R., Magrini, A., Bergamaschi, A., Bergamaschi, E., (2010) Environ. Mol. Mutagen., 51, p. 294Patlolla, A., Patlolla, B., Tchounwou, P., (2010) Mol. Cell. Biochem., 338, p. 225Singh, N., Manshian, B., Jenkins, G.J.S., Griffiths, S.M., Williams, P.M., Maffeis, T.G.G., Wright, C.J., Doak, S.H., (2009) Biomaterials, 30, p. 3891Di Sotto, A., Chiaretti, M., Carru, G.A., Belluci, S., Mazzanti, G., (2009) Toxicol. Lett., 184, p. 192Wirnitzer, U., Herbold, B., Voetz, M., Ragot, J., (2009) Toxicol. Lett., 186, p. 160Szendi, K., Varga, C., (2008) Anticancer Res., 28, p. 348Kim, J.S., Lee, K., Lee, Y.H., Cho, H.S., Kim, K.H., Choi, K.H., Lee, S.H., Yu, I.J., (2010) Arch. Toxicol., , in press, doi:10.1007/s00204-010-0574-0Landsiedel, R., Kapp, M.D., Schulz, M., Wiench, K., Oesch, F., (2009) Mutat. Res., 681, p. 241Maron, D.M., Ames, B.N., (1983) Mutat. Res., 113, p. 173Claxton, L.D., Umbuzeiro, G.A., DeMarini, D.M., (2010) Environ. Health Perspect., 118, p. 1515Hagiwara, Y., Watanabe, M., Oda, Y., Sofuni, T., Nohmi, T., (1993) Mutat. Res., 291, p. 171Matsui, K., Yamada, M., Imai, M., Yamamoto, K., Nohmi, T., (2006) DNA Repair, 5, p. 465Umbuzeiro, G.A., Roubicek, D.A., Rech, C.M., Sato, M.I., Claxton, L.D., (2004) Chemosphere, 54, p. 1589Mermelstein, R., Kiriazides, D.K., Butler, M., McCoy, E., Rosenkranz, H.S., (1981) Mutat. Res., 89, p. 187Blasco, C., Picó, Y., (2009) Trends Anal. Chem., 28, p. 745Barnard, A.S., (2009) Nanoscale, 1, p. 89Umbuzeiro, G.A., Franco, A., Magalhães, D., de Castro, F.J.V., Kummrow, F., Rech, C.M., de Carvalho, L.R.F., Vasconcellos, P.C., (2008) Environ. Mol. Mutagen., 49, p. 249Monge, M.E., D'Anna, B., Mazri, L., Giroir-Fendler, A., Ammann, M., Donaldsonc, D.J., George, C., (2010) Proc. Natl. Acad. Sci. USA, 107, p. 6605Bamford, H.A., Bezabeh, D.Z., Schantz, S., Wise, S.A., Baker, J.E., (2003) Chemosphere, 50, p. 575Andersson, H., Piras, E., Demma, J., Hellman, B., Brittebo, E., (2009) Toxicology, 262, p. 57Koyama, S., Kim, Y.A., Hayashi, T., Takeuchi, K., Fujii, C., Kuroiwa, N., Koyama, H., Endo, M., (2009) Carbon, 47, p. 1365Freiman, S., Hooker, S., Migler, K., Arepalli, S., (2008) Measurement Issues in Single Wall Carbon Nanotubes, NIST Recommended Practice Guide, Special Publication 960-19, , NIST, Gaithersburg, MD, USAOrganization for Economic Co-Operation and Development (OECD), Guideline for Testing of Chemicals 471 (1997) Bacterial Reverse Mutation Test, OECD, Paris, FranceYang, K., Xing, B., (2010) Chem. Rev., 110, p. 5989Chen, W., Duan, L., Zhu, D., (2007) Environ. Sci. Technol., 41, p. 8295Cançado, L.G., Takai, K., Enoki, T., Endo, M., Kim, Y.A., Mizusaki, H., Jorio, A., Pimenta, M.A., (2006) Appl. Phys. Lett., 88, p. 163106Hashimoto, A., Suenaga, K., Gloter, A., Urita, K., Iijima, S., (2004) Nature (London), 430, p. 870Dubinin, M.M., (1966) Chemistry and Physics of Carbon, , Marcel Dekker, New York, USA, P.L. Walker (Ed.)Peng, X., Li, Y., Luan, Z., Di, Z., Wang, H., Tian, B., Jia, Z., (2003) Chem. Phys. Lett., 376, p. 154Artacho, E., Anglada, E., Diéguez, O., Gale, J.D., García, A., Junquera, J., Martin, R.M., Soler, J.M., (2008) J. Phys. B: Condens. Matter, 20, p. 064208Boys, S.F., Bernardi, F., (1970) Mol. Phys., 19, p. 55

First-line antiretroviral therapy with a protease inhibitor versus non-nucleoside reverse transcriptase inhibitor and switch at higher versus low viral load in HIV-infected children: An open-label, randomised phase 2/3 trial

Background: Children with HIV will be on antiretroviral therapy (ART) longer than adults, and therefore the durability of first-line ART and timing of switch to second-line are key questions. We assess the long-term outcome of protease inhibitor and non-nucleoside reverse transcriptase inhibitor (NNRTI) first-line ART and viral load switch criteria in children. Methods: In a randomised open-label factorial trial, we compared effectiveness of two nucleoside reverse transcriptase inhibitors (NRTIs) plus a protease inhibitor versus two NRTIs plus an NNRTI and of switch to second-line ART at a viral load of 1000 copies per mL versus 30 000 copies per mL in previously untreated children infected with HIV from Europe and North and South America. Random assignment was by computer-generated sequentially numbered lists stratified by age, region, and by exposure to perinatal ART. Primary outcome was change in viral load between baseline and 4 years. Analysis was by intention to treat, which we defined as all patients that started treatment. This study is registered with ISRCTN, number ISRCTN73318385. Findings: Between Sept 25, 2002, and Sept 7, 2005, 266 children (median age 6\ub75 years; IQR 2\ub78-12\ub79) were randomly assigned treatment regimens: 66 to receive protease inhibitor and switch to second-line at 1000 copies per mL (PI-low), 65 protease inhibitor and switch at 30 000 copies per mL (PI-higher), 68 NNRTI and switch at 1000 copies per mL (NNRTI-low), and 67 NNRTI and switch at 30 000 copies per mL (NNRTI-higher). Median follow-up was 5\ub70 years (IQR 4\ub72-6\ub70) and 188 (71%) children were on first-line ART at trial end. At 4 years, mean reductions in viral load were -3\ub716 log10copies per mL for protease inhibitors versus -3\ub731 log10copies per mL for NNRTIs (difference -0\ub715 log10copies per mL, 95% CI -0\ub741 to 0\ub711; p=0\ub726), and -3\ub726 log10copies per mL for switching at the low versus -3\ub720 log10copies per mL for switching at the higher threshold (difference 0\ub706 log10copies per mL, 95% CI -0\ub720 to 0\ub732; p=0\ub756). Protease inhibitor resistance was uncommon and there was no increase in NRTI resistance in the PI-higher compared with the PI-low group. NNRTI resistance was selected early, and about 10% more children accumulated NRTI mutations in the NNRTI-higher than the NNRTI-low group. Nine children had new CDC stage-C events and 60 had grade 3/4 adverse events; both were balanced across randomised groups. Interpretation: Good long-term outcomes were achieved with all treatments strategies. Delayed switching of protease-inhibitor-based ART might be reasonable where future drug options are limited, because the risk of selecting for NRTI and protease-inhibitor resistance is low. Funding: Paediatric European Network for Treatment of AIDS (PENTA) and Pediatric AIDS Clinical Trials Group (PACTG/IMPAACT). \ua9 2011 Elsevier Ltd