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,5–7 vast areas of the tropics remain understudied.8–11 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 underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s 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 region’s vulnerability to environmental change. 15%–18% 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

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%–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

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%–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

Sinusopatia fúngica - relato de caso

Introdução: O relato visa à discussão das sinusopatias exclusivamente esfenoidais, sobretudo fúngicas, entidades raras com sintomatologia inespecífica, que constituem um  desafio diagnóstico na prática clínica. Relato do Caso: Paciente masculino, 80 anos, cefaléia em peso à esquerda e obstrução nasal há 3 meses. Diabetes não-insulino dependente controlada. Laboratoriais sem evidência de eosinofilia.Tomografia: esclerose e espessamento das paredes do seio esfenoidal e calcificações no seu interior à direita. Obliteração do recesso esfenoetmoidal direito. Realizada cirurgia endoscópica com acesso esfenoidal via transetmoidal. Retirada grande quantidade de material esverdeado compatível com fungo. Anatomopatológico: edema e infiltrado linfomononuclear de lamina própria. Pesquisa de fungos negativa. Paciente evolui com resolução da cefaléia no trigéssimo pós-operatório.Discussão: A rinossinusite   esfenoidal isolada é em sua maioria resultado de processo inflamatório crônico, sendo a bola fúngica a terceira etiologia mais frequente. A cefaléia é percebida em até 85% dos casos seguida por obstrução e gotejamento pós-nasal. Os achados tomográficos são inespecíficos, sendo   esclerose,  calcificação e opacificação completa dos seios achados sugestivos de bola fúngica. Conclusão: A perspicácia do otorrinolaringologista em suspeitar de rinossinusite esfenoidal isolada associada a sinais radiológicos e/ou endoscópicos são essenciais para o diagnostico precoce e, consequentemento, para o sucesso terapêutico da doença

Comparação entre métodos subjetivos e objetivo para avaliação de pacientes submetidos a cirurgias funcionais nasais

A prevalência da obstrução nasal é estimada em aproximadamente 30% em centros urbanos. A obstrução nasal gera sensação de desconforto pela insuficiente passagem de ar pelo nariz, podendo ocorrer por: obstáculo anatômico, processos alérgicos, processos infecciosos, indução medicamentosa, alterações endócrinas e metabólicas e rinites idiopáticas. São encontradas deficiências na filtração, no aquecimento e umidificação do ar inspirado. Há, também, alteração do padrão respiratório, levando à respiração oral, relacionada diretamente às alterações de sono, face, fala, distúrbios alimentares, alterações posturais, dificuldades escolares e sociais. A septoplastia e a turbinectomia são cirurgias funcionais nasais que visam aliviar a obstrução nasal na ineficácia do tratamento medicamentoso. Objetivo: Comparar os métodos subjetivos e objetivo de avaliação da obstrução nasal em pacientes submetidos a cirurgias funcionais nasais e analisar a eficácia destas cirurgias no pós-operatório precoce (35 a 45 dias) e em longo prazo (seis meses). Materiais e Métodos: A avaliação objetiva foi realizada através do Peak Flow, avaliando a função nasal como um todo. As análises subjetivas foram baseadas na autoavaliação do paciente através da escala visual analógica (EVA), e do nasal index score (NIS). Resultados: Não há diferença significativa entre pré e pós-operatório precoce, pré e pós operatório tardio e pós operatório precoce e tardio, comparando NIS ou EVA com Peak Flow (p ≥ 0,05).Há diferença significativa entre as respostas de evolução do NIS e EVA (p ≤0,05). A evolução do NIS é significativamente maior do que do EVA. A comparação das evoluções do NIS, EVA e Peak Flow, individualmente, mostrou que houve diferença significativa (p ≤ 0,05). Conclusão: Há grande relação entre os métodos subjetivos (NIS e EVA) e objetivo (Peak Flow) para a avaliação da obstrução nasal. Os resultados mostraram eficácia significativa das cirurgias funcionais nasais em pacientes com obstrução nasal no pós-operatório precoce e em longo prazo

Precision luminosity measurement in proton-proton collisions at root S=13 TeV in 2015 and 2016 at CMS

The measurement of the luminosity recorded by the CMS detector installed at LHC interaction point 5, using proton-proton collisions at root S = 13 TeV in 2015 and 2016, is reported. The absolute luminosity scale is measured for individual bunch crossings using beam-separation scans (the van der Meer method), with a relative precision of 1.3 and 1.0% in 2015 and 2016, respectively. The dominant sources of uncertainty are related to residual differences between the measured beam positions and the ones provided by the operational settings of the LHC magnets, the factorizability of the proton bunch spatial density functions in the coordinates transverse to the beam direction, and the modeling of the effect of electromagnetic interactions among protons in the colliding bunches. When applying the van der Meer calibration to the entire run periods, the integrated luminosities when CMS was fully operational are 2.27 and 36.3 fb(-1) in 2015 and 2016, with a relative precision of 1.6 and 1.2%, respectively. These are among the most precise luminosity measurements at bunched-beam hadron colliders.Peer reviewe

TRY plant trait database - enhanced coverage and open access

10.1111/gcb.14904GLOBAL CHANGE BIOLOGY261119-18

Search for new heavy resonances decaying to WW, WZ, ZZ, WH, or ZH boson pairs in the all-jets final state in proton-proton collisions at s\sqrt{s} = 13 TeV

International audienceA search for new heavy resonances decaying to WW, WZ, ZZ, WH, or ZH boson pairs in the all-jets final state is presented. The analysis is based on proton-proton collision data recorded by the CMS detector in 2016-2018 at a centre-of-mass energy of 13 TeV at the CERN LHC, corresponding to an integrated luminosity of 138 fb$^{-1}$. The search is sensitive to resonances with masses between 1.3 and 6 TeV, decaying to bosons that are highly Lorentz-boosted such that each of the bosons forms a single large-radius jet. Machine learning techniques are employed to identify such jets. No significant excess over the estimated standard model background is observed. A maximum local significance of 3.6 standard deviations, corresponding to a global significance of 2.3 standard deviations, is observed at masses of 2.1 and 2.9 TeV. In a heavy vector triplet model, spin-1 Z' and W' resonances with masses below 4.8 TeV are excluded at the 95% confidence level (CL). These limits are the most stringent to date. In a bulk graviton model, spin-2 gravitons and spin-0 radions with masses below 1.4 and 2.7 TeV, respectively, are excluded at 95% CL. Production of heavy resonances through vector boson fusion is constrained with upper cross section limits at 95% CL as low as 0.1 fb

Search for long-lived particles decaying to a pair of muons in proton-proton collisions at s \sqrt{s} = 13 TeV

An inclusive search for long-lived exotic particles decaying to a pair of muons is presented. The search uses data collected by the CMS experiment at the CERN LHC in proton-proton collisions at $\sqrt{s}$ = 13 TeV in 2016 and 2018 and corresponding to an integrated luminosity of 97.6 fb$^{−1}$. The experimental signature is a pair of oppositely charged muons originating from a common secondary vertex spatially separated from the pp interaction point by distances ranging from several hundred μm to several meters. The results are interpreted in the frameworks of the hidden Abelian Higgs model, in which the Higgs boson decays to a pair of long-lived dark photons Z$_{D}$, and of a simplified model, in which long-lived particles are produced in decays of an exotic heavy neutral scalar boson. For the hidden Abelian Higgs model with m(Z$_{D}$) greater than 20 GeV and less than half the mass of the Higgs boson, they provide the best limits to date on the branching fraction of the Higgs boson to dark photons for cτ(Z$_{D}$) (varying with m(Z$_{D}$)) between 0.03 and ≈0.5 mm, and above ≈0.5 m. Our results also yield the best constraints on long-lived particles with masses larger than 10 GeV produced in decays of an exotic scalar boson heavier than the Higgs boson and decaying to a pair of muons.[graphic not available: see fulltext