59 research outputs found
CĂąncer de mama e enfrentamento da COVID-19 simultĂąneos: relato de caso sobre espiritualidade
In this case study, a woman in her sixties had had recent diagnosis of locally advanced breast cancer just in the nick of time COVID-19 pandemic emerged with the first severe cases popping up in Rio de Janeiro State, Brazil. Her close brother had just died of COVID-19 infection and soon after respiratory distress symptoms came up to her. Due to other serious comorbidities, including emphysema, previous stroke, obesity and tabagism, and mechanical ventilation assistance for two weeks, it was also likely she would succumb to COVID-19 and breast cancer, If hadnât it been for inherent spiritual strength, resilience and faith in God. After Ethical Committee approval, analysis on her speech demonstrated her faith in spiritual treatment, in that she would never stop praying Hail Mary and compared the fact to medical cancer treatment. Altogether with catholic colleagues, she prayed three times a day as a kind of ritual, which ameliorated her grief and depression and influenced positively upon breast cancer and COVID-19 healing.Neste estudo de caso, uma mulher na casa dos sessenta anos teve um diagnĂłstico recente de cĂąncer de mama localmente avançado bem na hora em que a pandemia de COVID-19 surgiu com os primeiros casos graves no Estado do Rio de Janeiro, Brasil. Seu irmĂŁo prĂłximo havia acabado de morrer de infecção por COVID-19 e, logo depois, os sintomas de desconforto respiratĂłrio surgiram para ela. Devido a outras comorbidades graves, incluindo enfisema, acidente vascular cerebral anterior, obesidade e tabagismo e assistĂȘncia de ventilação mecĂąnica por duas semanas, tambĂ©m era provĂĄvel que ela sucumbisse Ă COVID-19 e cĂąncer de mama, se nĂŁo fosse pela força espiritual inerente, resiliĂȘncia e fĂ© em Deus. ApĂłs a aprovação do ComitĂȘ de Ătica, a anĂĄlise de sua fala demonstrou sua fĂ© no tratamento espiritual, pois ela nunca deixaria de rezar a Ave Maria e comparou o fato ao tratamento mĂ©dico do cĂąncer. Junto com colegas catĂłlicos, ela rezava trĂȘs vezes ao dia como uma espĂ©cie de ritual, o que amenizava sua dor e depressĂŁo e influenciava positivamente na cura do cĂąncer de mama e da COVID-19
CĂąncer de mama e enfrentamento da COVID-19 simultĂąneos: relato de caso sobre espiritualidade
In this case study, a woman in her sixties had had recent diagnosis of locally advanced breast cancer just in the nick of time COVID-19 pandemic emerged with the first severe cases popping up in Rio de Janeiro State, Brazil. Her close brother had just died of COVID-19 infection and soon after respiratory distress symptoms came up to her. Due to other serious comorbidities, including emphysema, previous stroke, obesity and tabagism, and mechanical ventilation assistance for two weeks, it was also likely she would succumb to COVID-19 and breast cancer, If hadnât it been for inherent spiritual strength, resilience and faith in God. After Ethical Committee approval, analysis on her speech demonstrated her faith in spiritual treatment, in that she would never stop praying Hail Mary and compared the fact to medical cancer treatment. Altogether with catholic colleagues, she prayed three times a day as a kind of ritual, which ameliorated her grief and depression and influenced positively upon breast cancer and COVID-19 healing.Neste estudo de caso, uma mulher na casa dos sessenta anos teve um diagnĂłstico recente de cĂąncer de mama localmente avançado bem na hora em que a pandemia de COVID-19 surgiu com os primeiros casos graves no Estado do Rio de Janeiro, Brasil. Seu irmĂŁo prĂłximo havia acabado de morrer de infecção por COVID-19 e, logo depois, os sintomas de desconforto respiratĂłrio surgiram para ela. Devido a outras comorbidades graves, incluindo enfisema, acidente vascular cerebral anterior, obesidade e tabagismo e assistĂȘncia de ventilação mecĂąnica por duas semanas, tambĂ©m era provĂĄvel que ela sucumbisse Ă COVID-19 e cĂąncer de mama, se nĂŁo fosse pela força espiritual inerente, resiliĂȘncia e fĂ© em Deus. ApĂłs a aprovação do ComitĂȘ de Ătica, a anĂĄlise de sua fala demonstrou sua fĂ© no tratamento espiritual, pois ela nunca deixaria de rezar a Ave Maria e comparou o fato ao tratamento mĂ©dico do cĂąncer. Junto com colegas catĂłlicos, ela rezava trĂȘs vezes ao dia como uma espĂ©cie de ritual, o que amenizava sua dor e depressĂŁo e influenciava positivamente na cura do cĂąncer de mama e da COVID-19
Genomics and epidemiology of the P.1 SARS-CoV-2 lineage in Manaus, Brazil
Cases of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in Manaus, Brazil, resurged in late 2020 despite previously high levels of infection. Genome sequencing of viruses sampled in Manaus between November 2020 and January 2021 revealed the emergence and circulation of a novel SARS-CoV-2 variant of concern. Lineage P.1 acquired 17 mutations, including a trio in the spike protein (K417T, E484K, and N501Y) associated with increased binding to the human ACE2 (angiotensin-converting enzyme 2) receptor. Molecular clock analysis shows that P.1 emergence occurred around mid-November 2020 and was preceded by a period of faster molecular evolution. Using a two-category dynamical model that integrates genomic and mortality data, we estimate that P.1 may be 1.7- to 2.4-fold more transmissible and that previous (non-P.1) infection provides 54 to 79% of the protection against infection with P.1 that it provides against non-P.1 lineages. Enhanced global genomic surveillance of variants of concern, which may exhibit increased transmissibility and/or immune evasion, is critical to accelerate pandemic responsiveness
Off-target effects of bacillus CalmetteâGuĂ©rin vaccination on immune responses to SARS-CoV-2: implications for protection against severe COVID-19
Background and objectives: Because of its beneficial off-target effects against non-mycobacterial infectious diseases, bacillus CalmetteâGuĂ©rin (BCG) vaccination might be an accessible early intervention to boost protection against novel pathogens. Multiple epidemiological studies and randomised controlled trials (RCTs) are investigating the protective effect of BCG against coronavirus disease 2019 (COVID-19). Using samples from participants in a placebo-controlled RCT aiming to determine whether BCG vaccination reduces the incidence and severity of COVID-19, we investigated the immunomodulatory effects of BCG on in vitro immune responses to SARS-CoV-2. Methods: This study used peripheral blood taken from participants in the multicentre RCT and BCG vaccination to reduce the impact of COVID-19 on healthcare workers (BRACE trial). The whole blood taken from BRACE trial participants was stimulated with Îł-irradiated SARS-CoV-2-infected or mock-infected Vero cell supernatant. Cytokine responses were measured by multiplex cytokine analysis, and single-cell immunophenotyping was made by flow cytometry. Results: BCG vaccination, but not placebo vaccination, reduced SARS-CoV-2-induced secretion of cytokines known to be associated with severe COVID-19, including IL-6, TNF-α and IL-10. In addition, BCG vaccination promoted an effector memory phenotype in both CD4+ and CD8+ T cells, and an activation of eosinophils in response to SARS-CoV-2. Conclusions: The immunomodulatory signature of BCGâs off-target effects on SARS-CoV-2 is consistent with a protective immune response against severe COVID-19
Pervasive gaps in Amazonian ecological research
Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4
While the increasing availability of global databases on ecological communities has advanced our knowledge
of biodiversity sensitivity to environmental changes,5â7 vast areas of the tropics remain understudied.8â11 In
the American tropics, Amazonia stands out as the worldâs most diverse rainforest and the primary source of
Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13â15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazonâs biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 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 or ganism groups in a machine learning model framework to map the research probability across the Brazilian
Amazonia, while identifying the regionâs vulnerability to environmental change. 15%â18% of the most ne glected 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 lostinfo:eu-repo/semantics/publishedVersio
Search for dark matter produced in association with bottom or top quarks in âs = 13 TeV pp collisions with the ATLAS detector
A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fbâ1 of protonâproton collision data recorded by the ATLAS experiment at âs = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements
Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950â2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021
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 2020â21 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 60·5â65·1] decline), and increased during the COVID-19 pandemic period (2020â21; 5·1% [0·9â9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98â5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50â6·01) in 2019. An estimated 131 million (126â137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7â17·2) 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 (20·8â24·8), from 49·0 years (46·7â51·3) to 71·7 years (70·9â72·5). Global life expectancy at birth declined by 1·6 years (1·0â2·2) 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 (7·67â8·13) 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% [28·4â52·7]) and south Asia (26·3% [9·0â44·7]). 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
Pervasive gaps in Amazonian ecological research
Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 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,18,19 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%â18% 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
Pervasive gaps in Amazonian ecological research
Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 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,18,19 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%â18% 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
- âŠ