19 research outputs found

    Modulation Of The Catalytic Activity Of Porphyrins By Lipid- And Surfactant-containing Nanostructures

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    The structural factors modulating porphyrin activity encompass pyrrole and equatorial ligands, as well as the central metal and the number and structure of their axial ligands. Of equal importance is the microenvironment provided by apoproteins, solvents and membranes. Porphyrins are often used to construct supramolecular structures with different applications. The modulation of activity of the porphyrins has been frequently achieved by mimicking nature, i.e., by the provision of different microenvironments for these molecules. The association of porphyrins to surfactant- and lipid-containing nanostructures has changed the activity of these compounds to mimic different enzymes such as SOD, cytochrome P450, peroxidases and others. In determined conditions, the reactive forms of the porphyrins are high-valence states of oxo-metal-π cations and oxo-metal produced by the reaction with peroxides and peracids. The modulation of porphyrin activity by surfactant- and lipid-containing nanostructures has also been achieved for hemeproteins, as the lipid nanostructures affect the conformation of proteins. ©2011 Sociedade Brasileira de Química.22916211633Drain, C.M., Varotto, A., Radivojevic, I., (2009) Chem. Rev., 109, p. 1630Aida, T., Inoue, S., (2000) The Porphyrin Handbook, , Kadish, K., M. Smith, K., M. Guillard R., eds.Academic Press: San Diego ch. 42Ponka, P., (1999) Am. J. Med. Sci., 318, p. 241Da Silva, D.C., De Freitas-Silva, G., Do Nascimento, E., Rebouças, J.S., Barbeira, P.J., De Carvalho, M.E., Idemori, Y.M., (2008) J. Inorg. Biochem., 102, p. 1932Bochot, C., Bartoli, J.F., Frapart, Y., Dansette, P.M., Mansuy, D., Battioni, P., (2007) J. Mol. Catal. A.: Chem., 263, p. 200Alkordi, M.H., Liu, Y.L., Larsen, R.W., Eubank, J.F., Eddaoudi, M., (2008) J. Am. Chem. Soc., 130, p. 12639Suijkerbuijk, B., Schamhart, D.J., Kooijman, H., Spek, A.L., Van Koten, G., Gebbink, R., (2010) Dalton Trans., 39, p. 6198Groves, J.T., Nemo, T.E., (1983) J. Am. Chem. Soc., 10, p. 5786Drain, C.M., Smeureanu, G., Patel, S., Gong, X.C., Garno, J.A., (2006) New. J. Chem., 30, p. 1834Wang, Y.T., Jin, W.J., (2008) Spectrochim. Acta, Part A., 70, p. 871Komatsu, T., Moritake, W., Nakagawa, A., Tsuchida, E., (2002) Chem. - Eur. J., 8, p. 5469Nagami, H., Umakoshi, H., Shimanouchi, T., Kuboi, R., (2004) Biochem. Eng. J., 21, p. 221Szoka, F., Papahadjopoulos, D., (1980) Annu. Rev. Biophys. Bioeng., 9, p. 467Atkin, R., Craig, V.S.J., Wanless, E.J., Biggs, S., (2003) Adv. Colloid Interface Sci., 103, p. 219Grassert, I., Schinkowski, K., Vollhardt, D., Oehme, G., (1998) Chirality, 10, p. 754Hait, S.K., Moulik, S.P., (2001) J. Surfactants Deterg., 4, p. 303Glick, J., Santoyo, G., Casey, P.J., (1996) J. Biol. Chem., 271, p. 2949Maldotti, A., Andreotti, L., Molinari, A., Varani, G., Cerichelli, G., Chiarini, M., (2001) Green Chem., 3, p. 42Batrakova, E.V., Kabanov, A.V., (2008) J. Controlled Release, 130, p. 98Bangham, A.D., Standish, M.M., Watkins, J.C., (1965) J. Mol. Biol., 13, p. 238Johnson, S.M., Bangham, A.D., Hill, M.W., Korn, E.D., (1971) Biochim. Biophys. Acta. Biomembr., 233, p. 820Papahadj, D., Watkins, J.C., (1967) Biochim. Biophys. Acta, Biomembr., 135, p. 639Abramson, M.B., Katzman, R., Gregor, H.P., (1964) J. Biol. Chem., 239, p. 70Hauser, H.O., (1971) Biochem. Biophys. Res. Commun., 45, p. 1049Huang, C.H., (1969) Biochemistry, 8, p. 344Saunders, L., Gammack, D., Perrin, J., (1962) J. Pharm. Pharmacol., 14, p. 567Tien, H.T., (1974) Theory and Practice, , 1th ed.Bilayer Lipid Membranes (BLM): Marcel Dekker: New YorkRazin, S., (1972) Biochim. Biophys. Acta, Biomembr., 265, p. 241Korenbrot, J.I., (1977) Annu. Rev. Physiol., 39, p. 19Batzri, S., Korn, E.D., (1973) Biochim. Biophys. Acta, Biomembr., 298, p. 1015Deamer, D., Bangham, A.D., (1976) Biochim. Biophys. Acta, Biomembr., 443, p. 629Szoka, F., Papahadjopoulos, D., (1978) Proc. Natl. Acad. Sci. U. S. A., 75, p. 4194Mishra, P.P., Bhatnagar, J., Datta, A., (2005) J. Phys. Chem. B., 109, p. 24225Pessoto, F.S., Inada, N.M., Nepomuceno, M.D., Ruggiero, A.C., Nascimento, O.R., Vercesi, A.E., Nantes, I.L., (2009) Chem. Biol. Interact., 181, p. 400Steinbeck, C.A., Hedin, N., Chmelka, B.F., (2004) Langmuir, 20, p. 10399Vanesch, J.H., Feiters, M.C., Peters, A.M., Nolte, R.J.M., (1994) J. Phys. Chem., 98, p. 5541Barber, D.C., Freitagbeeston, R.A., Whitten, D.G., (1991) J. Phys. Chem., 95, p. 4074Maiti, N.C., Mazumdar, S., Periasamy, N.J., (1998) J. Porphyrins Phthalocyanines, 2, p. 369Schmehl, R.H., Whitten, D.G., (1981) J. Phys. Chem., 85, p. 3473Perrin, M.H., (1973) J. Chem. Phys., 59, p. 2090Zhou, X.T., Ji, H.B., (2010) Chem. Eng. J., 156, p. 411Monnereau, C., Ramos, P.H., Deutman, A.B.C., Elemans, J., Nolte, R.J.M., Rowan, A.E., (2010) J. Am. Chem. Soc., 132, p. 1529Merlau, M.L., Grande, W.J., Nguyen, S.T., Hupp, J.T., (2000) J. Mol. Catal. A: Chem., 156, p. 79Anzenbacher, P., Kral, V., Jursikova, K., Gunterova, J., Kasal, A., (1997) J. Mol. Catal. A: Chem., 118, p. 63Zhao, Y.C., Xiang, Y.Z., Pu, L., Yang, M., Yu, X.Q., (2006) Appl. Catal. A, 301, p. 176Zhou, X.T., Tang, Q.H., Ji, H.B., (2009) Tetrahedron Lett., 50, p. 6601Monfared, H.H., Aghapoor, V., Ghorbanloo, M., Mayer, P., (2010) Appl. Catal. A, 372, p. 209Heijnen, J.H.M., De Bruijn, V.G., Van Den Broeke, L.J.P., Keurentjes, J.T.F., (2003) Chem. Eng. Process., 42, p. 223Santos, A.C., Luz, R.A.S., Ferreira, L.G.F., Santos-Júnior, J.R., Silva, W.C., (2010) Quim. Nova, 33, p. 539Zhou, Y.B., Ryu, E.H., Zhao, Y., Woo, L.K., (2007) Organometallics, 26, p. 358Nantes, I.L., Crespilho, F.N., Mugnol, K.C.U., Chaves, J.C.A., Luz, R.A.S., Nascimento, O.R., Pinto, S.M.S., (2010) Circular Dichroism: Theory and Spectroscopy, , Rodgers D. S., ed.Nova Science Publishers: New York ch. 8Travascio, P., Sen, D., Bennet, A.J., (2006) Can. J. Chem., 84, p. 613Omodeo-Sale, F., Monti, D., Olliaro, P., Taramelli, D.P., (2001) Biochem. Pharmacol., 61, p. 999Ishigure, S., Mitsui, T., Ito, S., Kondo, Y., Kawabe, S., Kondo Dewa M, T., Mino, H., Nango, M., (2010) Langmuir, 26, p. 7774Umakoshi, H., Morimoto, K., Ohama, Y., Nagami, H., Shimanouchi, T., Kuboi, R., (2008) Langmuir, 24, p. 4451Prieto, T., Marcon, R.O., Prado, F.M., Caires, A.C.F., Di Mascio, P., Brochsztain, S., Nascimento, O.R., Nantes, I.L., (2006) J. Phys.Chem., 8, p. 1963Mugnol, K.C.U., Ando, R.A., Nagayasu, R.Y., Faljoni-Alario, A., Brochsztain, S., Santos, P.S., Nascimento, R.O., Nantes, I.L., (2008) Biophys. J., 94, p. 4066Nagatomo, H., Matsushita, Y., Sugamoto, K., Matsui, T., (2003) Tetrahedron: Asymmetry, 14, p. 2339Cantonetti, V., Monti, D., Venanzi, M., Bombelli, C., Ceccacci, F., Mancini, G., (2004) Tetrahedron: Asymmetry, 15, p. 1969Hiraka, K., Kanehisa, M., Tamai, M., Asayama, S., Nagaoka, S., Oyaizu, K., Yuasa, M., Kawakami, H., (2008) Colloids Surf. B, 67, p. 54Yuasa, M., Oyaizu, K., Horiuchi, A., Ogata, A., Hatsugai, T., Yamaguchi, A., Kawakami, H., (2004) Mol. Pharm., 1, p. 387Aron, J., Baldwin, D.A., Marques, H.M., Pratt, J.M., Adams, P.A., (1986) J. Inorg. Biochem., 27, p. 227Wang, J.S., Vanwart, H.E., (1989) J. Phys. Chem., 93, p. 7925Munro, O.Q., Marques, H.M., (1996) Inorg. Chem., 35, p. 3752Prieto, T., Nascimento, O.R., Tersariol, I.L.S., Faljoni-Alario, A., Nantes, I.L., (2004) J. Phys. Chem. B, 108, p. 11124Prieto, T., Nantes, I.L., Nascimento, O.R., (2004) Prog. Colloid Polym. Sci., 128, p. 1Makarska, M., Radzki, S., Legendziewicz, J., (2002) J. Alloys Compd., 341, p. 233Riposati, A., Prieto, T., Shida, C.S., Nantes, I.L., Nascimento, O.R., (2006) J. Inorg. Biochem., 100, p. 226Claiborne, A., Fridovich, I., (1979) J. Biol. Chem., 254, p. 4245Hiner, A.N.P., Ruiz, J.H., Lopez, J.N.R., Canovas, F.G., Brisset, N.C., Smith, A.T., Arnao, M.B., Acosta, M., (2002) J. Biol. Chem., 277, p. 26879Primus, J.L., Grunenwald, S., Hagedoorn, P.L., Albrecht-Gary, A.M., Mandon, D., Veeger, C.T., (2002) J. Am. Chem. Soc., 124, p. 1214Demontellano, P.R.O., (1992) Annu. Rev. Pharmacol. Toxicol., 32, p. 89Savenkova, M.I., Kuo, J.M., De Montellano, P.R.O., (1998) Biochemistry, 37, p. 10828Smith, A.T., Veitch, N.C., (1998) Curr. Opin. Chem. Biol., 2, p. 269Prieto, T., Mugnol, K.C.U., Araujo, J.C., Sousa, F.L., Soares, V.A., Cilento, G., Nantes, I.L., (2007) Catalysis and Photochemistry in Heterogeneous Media, , Nantes I. L.Brochesztain, S. eds.Research Signpost: Kerala ch. 1Zucchi, M.R., Nascimento, O.R., Faljoni-Alario, A., Prieto, T., Nantes, I.L., (2003) Biochem. J., 370, p. 671Kinnunen, P.K.J., (1992) Chem. Phys. Lipids, 63, p. 251Kawai, C., Prado, F.M., Nunes, G.L.C., Di Mascio, P., Carmona-Ribeiro, A.M., Nantes, I.L., (2005) J. Biol. Chem., 280, p. 34709Araujo, J.C., Prieto, T., Prado, F.M., Trindade, F.J., Nunes, G.L.C., Dos Santos, J.G., Di Masco, P., Nantes, I.L., (2007) J. Nanosci. Nanotechnol., 7, p. 3643Estevam, M.L., Nascimento, O.R., Baptista, M.S., Di Mascio, P., Prado, F.M., Faljoni-Alario, A., Zucchi, M.D., Nantes, I.L., (2004) J. Biol. Chem., 279, p. 39214Kawai, C., Nantes, I.L., Baptista, M.D.S., (2010) FEBS J., 277, p. 224Nantes, I.L., Faljoni-Alario, A., Vercesi, A.E., Santos, K.E., Bechara, E.J.H., (1998) Free Radic. Biol. Med., 25, p. 54

    O cuidado em saúde mental pelos agentes comunitários de saúde: o que aprendem em seu cotidiano de trabalho?

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    Este trabalho visa descrever o conhecimento em saúde mental construído pelo agente comunitário de saúde, concomitante à produção de cuidado em saúde mental. Trata-se de pesquisa qualitativa, cujo referencial teórico é o Construcionismo Social. Os dados foram produzidos em grupos focais, analisados e elencados nas seguintes categorias temáticas: “A gente precisa orientar as famílias”, que agrupa os entidos relacionados à construção do cuidado às famílias que convivem com o sofrimento mental; “Só de você parar e ouvir...”, onde se descrevem os repertórios relacionados ao uso de tecnologias relacionais de cuidado; “Nós sabemos disso, porque nós andamos ali”, que delineia as estratégias para construção de saberes e, finalmente, a categoria que descreve os sentidos do medo do louco: “A gente tem medo daquilo que a gente vê”. Conclui-se que os conhecimentos construídos no cotidiano de trabalho dos agentes comunitários de saúde, quando refletidos e sistematizados, são potentes para a produção de práticas de cuidado condizentes com o paradigma psicossocial de atenção a pessoas e famílias em sofrimento mental

    Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

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    Background: Disorders affecting the nervous system are diverse and include neurodevelopmental disorders, late-life neurodegeneration, and newly emergent conditions, such as cognitive impairment following COVID-19. Previous publications from the Global Burden of Disease, Injuries, and Risk Factor Study estimated the burden of 15 neurological conditions in 2015 and 2016, but these analyses did not include neurodevelopmental disorders, as defined by the International Classification of Diseases (ICD)-11, or a subset of cases of congenital, neonatal, and infectious conditions that cause neurological damage. Here, we estimate nervous system health loss caused by 37 unique conditions and their associated risk factors globally, regionally, and nationally from 1990 to 2021. Methods: We estimated mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs), with corresponding 95% uncertainty intervals (UIs), by age and sex in 204 countries and territories, from 1990 to 2021. We included morbidity and deaths due to neurological conditions, for which health loss is directly due to damage to the CNS or peripheral nervous system. We also isolated neurological health loss from conditions for which nervous system morbidity is a consequence, but not the primary feature, including a subset of congenital conditions (ie, chromosomal anomalies and congenital birth defects), neonatal conditions (ie, jaundice, preterm birth, and sepsis), infectious diseases (ie, COVID-19, cystic echinococcosis, malaria, syphilis, and Zika virus disease), and diabetic neuropathy. By conducting a sequela-level analysis of the health outcomes for these conditions, only cases where nervous system damage occurred were included, and YLDs were recalculated to isolate the non-fatal burden directly attributable to nervous system health loss. A comorbidity correction was used to calculate total prevalence of all conditions that affect the nervous system combined. Findings: Globally, the 37 conditions affecting the nervous system were collectively ranked as the leading group cause of DALYs in 2021 (443 million, 95% UI 378–521), affecting 3·40 billion (3·20–3·62) individuals (43·1%, 40·5–45·9 of the global population); global DALY counts attributed to these conditions increased by 18·2% (8·7–26·7) between 1990 and 2021. Age-standardised rates of deaths per 100 000 people attributed to these conditions decreased from 1990 to 2021 by 33·6% (27·6–38·8), and age-standardised rates of DALYs attributed to these conditions decreased by 27·0% (21·5–32·4). Age-standardised prevalence was almost stable, with a change of 1·5% (0·7–2·4). The ten conditions with the highest age-standardised DALYs in 2021 were stroke, neonatal encephalopathy, migraine, Alzheimer's disease and other dementias, diabetic neuropathy, meningitis, epilepsy, neurological complications due to preterm birth, autism spectrum disorder, and nervous system cancer. Interpretation: As the leading cause of overall disease burden in the world, with increasing global DALY counts, effective prevention, treatment, and rehabilitation strategies for disorders affecting the nervous system are needed. Funding: Bill & Melinda Gates Foundation

    Global incidence, prevalence, years lived with disability (YLDs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

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    Background: Detailed, comprehensive, and timely reporting on population health by underlying causes of disability and premature death is crucial to understanding and responding to complex patterns of disease and injury burden over time and across age groups, sexes, and locations. The availability of disease burden estimates can promote evidence-based interventions that enable public health researchers, policy makers, and other professionals to implement strategies that can mitigate diseases. It can also facilitate more rigorous monitoring of progress towards national and international health targets, such as the Sustainable Development Goals. For three decades, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) has filled that need. A global network of collaborators contributed to the production of GBD 2021 by providing, reviewing, and analysing all available data. GBD estimates are updated routinely with additional data and refined analytical methods. GBD 2021 presents, for the first time, estimates of health loss due to the COVID-19 pandemic. Methods: The GBD 2021 disease and injury burden analysis estimated years lived with disability (YLDs), years of life lost (YLLs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries using 100 983 data sources. Data were extracted from vital registration systems, verbal autopsies, censuses, household surveys, disease-specific registries, health service contact data, and other sources. YLDs were calculated by multiplying cause-age-sex-location-year-specific prevalence of sequelae by their respective disability weights, for each disease and injury. YLLs were calculated by multiplying cause-age-sex-location-year-specific deaths by the standard life expectancy at the age that death occurred. DALYs were calculated by summing YLDs and YLLs. HALE estimates were produced using YLDs per capita and age-specific mortality rates by location, age, sex, year, and cause. 95% uncertainty intervals (UIs) were generated for all final estimates as the 2·5th and 97·5th percentiles values of 500 draws. Uncertainty was propagated at each step of the estimation process. Counts and age-standardised rates were calculated globally, for seven super-regions, 21 regions, 204 countries and territories (including 21 countries with subnational locations), and 811 subnational locations, from 1990 to 2021. Here we report data for 2010 to 2021 to highlight trends in disease burden over the past decade and through the first 2 years of the COVID-19 pandemic. Findings: Global DALYs increased from 2·63 billion (95% UI 2·44–2·85) in 2010 to 2·88 billion (2·64–3·15) in 2021 for all causes combined. Much of this increase in the number of DALYs was due to population growth and ageing, as indicated by a decrease in global age-standardised all-cause DALY rates of 14·2% (95% UI 10·7–17·3) between 2010 and 2019. Notably, however, this decrease in rates reversed during the first 2 years of the COVID-19 pandemic, with increases in global age-standardised all-cause DALY rates since 2019 of 4·1% (1·8–6·3) in 2020 and 7·2% (4·7–10·0) in 2021. In 2021, COVID-19 was the leading cause of DALYs globally (212·0 million [198·0–234·5] DALYs), followed by ischaemic heart disease (188·3 million [176·7–198·3]), neonatal disorders (186·3 million [162·3–214·9]), and stroke (160·4 million [148·0–171·7]). However, notable health gains were seen among other leading communicable, maternal, neonatal, and nutritional (CMNN) diseases. Globally between 2010 and 2021, the age-standardised DALY rates for HIV/AIDS decreased by 47·8% (43·3–51·7) and for diarrhoeal diseases decreased by 47·0% (39·9–52·9). Non-communicable diseases contributed 1·73 billion (95% UI 1·54–1·94) DALYs in 2021, with a decrease in age-standardised DALY rates since 2010 of 6·4% (95% UI 3·5–9·5). Between 2010 and 2021, among the 25 leading Level 3 causes, age-standardised DALY rates increased most substantially for anxiety disorders (16·7% [14·0–19·8]), depressive disorders (16·4% [11·9–21·3]), and diabetes (14·0% [10·0–17·4]). Age-standardised DALY rates due to injuries decreased globally by 24·0% (20·7–27·2) between 2010 and 2021, although improvements were not uniform across locations, ages, and sexes. Globally, HALE at birth improved slightly, from 61·3 years (58·6–63·6) in 2010 to 62·2 years (59·4–64·7) in 2021. However, despite this overall increase, HALE decreased by 2·2% (1·6–2·9) between 2019 and 2021. Interpretation: Putting the COVID-19 pandemic in the context of a mutually exclusive and collectively exhaustive list of causes of health loss is crucial to understanding its impact and ensuring that health funding and policy address needs at both local and global levels through cost-effective and evidence-based interventions. A global epidemiological transition remains underway. Our findings suggest that prioritising non-communicable disease prevention and treatment policies, as well as strengthening health systems, continues to be crucially important. The progress on reducing the burden of CMNN diseases must not stall; although global trends are improving, the burden of CMNN diseases remains unacceptably high. Evidence-based interventions will help save the lives of young children and mothers and improve the overall health and economic conditions of societies across the world. Governments and multilateral organisations should prioritise pandemic preparedness planning alongside efforts to reduce the burden of diseases and injuries that will strain resources in the coming decades. Funding: Bill & Melinda Gates Foundation

    Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

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    Background: Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. Methods: The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model—a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates—with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality—which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. Findings: The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2–100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1–290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1–211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4–48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3–37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7–9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. Interpretation: Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. Funding: Bill & Melinda Gates Foundation

    Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

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    Background: Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period. Methods: 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution. Findings: Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations. Interpretation: Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic. Funding: Bill & Melinda Gates Foundation

    Morfologia de frutos, sementes e plântulas de castanheira (Terminalia catappa L. - COMBRETACEAE) Morphology of the fruit, the seed and the seedlings of chestnut tree (Terminalia catappa L. - COMBRETACEAE)

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    O trabalho foi realizado com o objetivo de descrever morfologicamente os frutos, sementes e plântulas de castanheira. Foi feita a biometria dos frutos e das sementes e sua caracterização quanto à forma, por meio de mensurações com paquímetro e observações realizadas em estereomicroscópio com câmara clara. Os frutos de castanheira são carnosos, indeiscentes, do tipo nucóide, glabros, de coloração verde a vinácea, projeção das nervuras carpelares externamente evidentes, com epicarpo delgado, mesocarpo carnoso e esponjoso de coloração vinácea, com feixes vasculares conspícuos em corte transversal. Geralmente, cada fruto contém apenas uma semente. As sementes são exalbuminosas, de formas alongadas e cilíndricas, recobertas por endocarpo rígido de coloração marrom; possuem cerca de 2,5cm, 0,7cm e 0,7cm, de comprimento, largura e espessura, respectivamente. A germinação das sementes de castanheira é epígea, e a plantula é fanerocotiledonar.<br>The work was carried out with the objective of describing morphologically the fruits, seeds and seedlings of chestnut tree. It was made the biometry of the fruits and seeds with a digital pachymeter and its characterization in relation to the shape, in stereomicroscope with clear chamber. It can be evidenced that the chestnut tree fruits are fleshly, indehiscent, nucoid, glabrous, from green to purple coloration, with evident projection of the carpel ribbings, with a fleshly and spongy epicarp and mesocarp, of purple color, with conspicuous vascular bundle in transversal cut. Generally, it has a seed per fruit. The seeds are unalbuminous, of prolongated and cylindrical shape and recovered with a rigid endocarp of brown coloration. The seeds possess about 2,5; 0,7 and 0,7 cm, of length, width and thickness, respectively. The germination of the seeds of chestnut tree is epigeal and the seedling is fanerocotyledonary

    The Study Of Cardiovascular Risk In Adolescents - Erica: Rationale, Design And Sample Characteristics Of A National Survey Examining Cardiovascular Risk Factor Profile In Brazilian Adolescents

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    Background: The Study of Cardiovascular Risk in Adolescents (Portuguese acronym, "ERICA") is a multicenter, school-based country-wide cross-sectional study funded by the Brazilian Ministry of Health, which aims at estimating the prevalence of cardiovascular risk factors, including those included in the definition of the metabolic syndrome, in a random sample of adolescents aged 12 to 17 years in Brazilian cities with more than 100,000 inhabitants. Approximately 85,000 students were assessed in public and private schools. Brazil is a continental country with a heterogeneous population of 190 million living in its five main geographic regions (North, Northeast, Midwest, South and Southeast). ERICA is a pioneering study that will assess the prevalence rates of cardiovascular risk factors in Brazilian adolescents using a sample with national and regional representativeness. This paper describes the rationale, design and procedures of ERICA. Methods/Design: Participants answered a self-administered questionnaire using an electronic device, in order to obtain information on demographic and lifestyle characteristics, including physical activity, smoking, alcohol intake, sleeping hours, common mental disorders and reproductive and oral health. Dietary intake was assessed using a 24-hour dietary recall. Anthropometric measures (weight, height and waist circumference) and blood pressure were also be measured. Blood was collected from a subsample of approximately 44,000 adolescents for measurements of fasting glucose, total cholesterol, HDL-cholesterol, LDL-cholesterol, triglycerides, glycated hemoglobin and fasting insulin. Discussion: The study findings will be instrumental to the development of public policies aiming at the prevention of obesity, atherosclerotic diseases and diabetes in an adolescent population.151Schmidt, M.I., Duncan, B.B., Silva, G.A., Menezes, A.M., Monteiro, C.A., Barreto, S.M., Chronic non-communicable diseases in brazil: Burden and current challenges (2011) Lancet, 377 (9781), pp. 1949-1961Juonala, M., Viikari, J.S., Kahonen, M., Taittonen, L., Laitinen, T., Hutri-Kahonen, N., Life-time risk factors and progression of carotid atherosclerosis in young adults: The cardiovascular risk in young finns study (2010) Eur Heart J., 31 (14), pp. 1745-1751WHO, Obesity - Preventing and managing the global epidemic (2004) Geneva: Report of a WHO Consultation on Obesity, , World Health OrganizationJuonala, M., Magnussen, C.G., Berenson, G.S., Venn, A., Burns, T.L., Sabin, M.A., Childhood adiposity, adult adiposity, and cardiovascular risk factors (2011) N Engl J Med., 365 (20), pp. 1876-1885Williams, D.E., Cadwell, B.L., Cheng, Y.J., Cowie, C.C., Gregg, E.W., Geiss, L.S., Prevalence of impaired fasting glucose and its relationship with cardiovascular disease risk factors in us adolescents, 1999-2000 (2005) Pediatrics, 116 (5), pp. 1122-1126IBGE, (2010) Antropometria E Estado Nutricional de Crianças, Adolescentes E Adultos No Brasil2008-2009, p. 130. , Pesquisa de Orçamentos Familiares (POF). Rio de Janeiro: Instituto Brasileiro de Geografia e EstatísticaFreedman, D.S., Khan, L.K., Dietz, W.H., Srinivasan, S.R., Berenson, G.S., Relationship of childhood obesity to coronary heart disease risk factors in adulthood: The bogalusa heart study (2001) Pediatrics, 108 (3), pp. 712-718Franks, P.W., Hanson, R.L., Knowler, W.C., Sievers, M.L., Bennett, P.H., Looker, H.C., Childhood obesity, other cardiovascular risk factors, and premature death (2010) N Engl J Med., 362 (6), pp. 485-493Juonala, M., Viikari, J.S., Raitakari, O.T., Main findings from the prospective cardiovascular risk in young finns study (2013) Curr Opin Lipidol, 24 (1), pp. 57-64Vasconcellos, M.T.L., Silva, P.L.N., Szklo, M., Bloch, K.V., Kuschnir, M.C.C., Klein, C.H., Desenho da amostra do estudo de riscos cardiovasculares em adolescentes (ERICA) (2015) Cadernos de Saúde Pública, , In pressCenso Escolar - Inep, , http://portal.inep.gov.br/basica-censoCastro, I.R., Cardoso, L.O., Engstrom, E.M., Levy, R.B., Monteiro, C.A., Surveillance of risk factors for non-communicable diseases among adolescents: The experience in rio de janeiro, Brazil (2008) Cad Saude Publica, 24 (10), pp. 2279-2288Farias, J.C., Jr., Lopes, A.S., Mota, J., Santos, M.P., Ribeiro, J.C., Hallal, P.C., Validade e reprodutibilidade de um questionário para medida de atividade física em adolescentes: Uma adaptação do self-administered physical activity checklist (2012) Rev Bras Epidemiol., 15 (1), pp. 198-210Biddle, S., Sallis, J.F., Cavill, N.A., Young and active? Young people and health enhancing physical activity (1998) Evidence and Implication, , London: Health Education AuthorityMari, J.J., Williams, P., A comparison of the validity of two psychiatric screening questionnaires (GHQ-12) (1985) Psychol Med., 15 (3), pp. 651-659Conway, J.M., Ingwersen, L.A., Vinyard, B.T., Moshfegh, A.J., Effectiveness of the us department of agriculture 5-step multiple-pass method in assessing food intake in obese and nonobese women (2003) Am J Clin Nutr., 77 (5), pp. 1171-1178(2011) 2008-2009. Tabela de Medidas Referidas Para Os Alimentos Consumidos No Brasil, , Pesquisa de Orçamentos Familiares (POF), Rio de Janeiro: Instituto Brasileiro de Geografia e Estatística(2011) 2008-2009 Tabela de Composição Nutricional Dos Alimentos Consumidos No Brasil, , Pesquisa de Orçamentos Familiares (POF), Rio de Janeiro: Instituto Brasileiro de Geografia e EstatísticaMultiple Source Method (MSM), , https://msm.dife.de/Lohman, T.G., Roche, A.F., Martorell, R., (1988) Anthropometric Standardization Reference Manual: Human Kinetics BooksDe Onis, M., Onyango, A.W., Borghi, E., Siyam, A., Nishida, C., Siekmann, J., Development of a who growth reference for school-aged children and adolescents (2007) Bull World Health Organ, 85 (9), pp. 660-667Obesity: Preventing and managing the global epidemic (2000) Report of a WHO Consultation, 894, pp. i-xi. , World Health Organ Tech Rep Ser., 1-253The fourth report on the diagnosis, evaluation, and treatment of high blood pressure in children and adolescents (2004) Pediatrics, 114 (2), pp. 555-576. , National High Blood Pressure Education Program Working Group on High Blood Pressure in ChildrenStergiou, G.S., Yiannes, N.G., Rarra, V.C., Validation of the omron 705 IT oscillometric device for home blood pressure measurement in children and adolescents: The arsakion school study (2006) Blood Press Monit., 11 (4), pp. 229-234Pickering, T.G., Hall, J.E., Appel, L.J., Falkner, B.E., Graves, J., Hill, M.N., Recommendations for blood pressure measurement in humans and experimental animals: Part 1: Blood pressure measurement in humans: A statement for professionals from the subcommittee of professional and public education of the American heart association council on high blood pressure research (2005) Circulation, 111 (5), pp. 697-716Xavier, H.T., Izar, M.C., Faria Neto, J.R., Assad, M.H., Rocha, V.Z., Sposito, A.C., V brazilian guidelines on dyslipidemias and prevention of atherosclerosis (2013) Arq Bras Cardiol., 101 (4), pp. 1-20Diagnosis and classification of diabetes mellitus (2010) Diabetes Care, 33, pp. S62-S69Back Giuliano Ide, C., Caramelli, B., Pellanda, L., Duncan, B., Mattos, S., Fonseca, F.H., I guidelines of prevention of atherosclerosis in childhood and adolescence (2005) Arq Bras Cardiol, 85, pp. 4-36Medicina Laboratorial, , http://www.sbpc.org.br/?C=133Programa Nacional de Controle de Qualidade, , http://www.pncq.org.br/, American Diabetes AssociationHabicht, J.P., Standardization of quantitative epidemiological methods in the field (1974) Bol Oficina Sanit Panam, 76 (5), pp. 375-38
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