Abscessos cerebrais múltiplos causados por infecção por Penicillium spp

We present a case of central nervous system (CNS) infection by a member of the Penicillium genera in a HIV-negative man in Brazil. The patient was admitted complaining of loss of visual fields and speech disturbances. CT scan revealed multiple brain abscesses. Stereothacic biopsies revealed fungal infection and amphotericin B treatment begun with initial improvement. The patient died few days later as a consequence of massive gastrointestinal bleeding due to ruptured esophageal varices. The necropsy and final microbiologic analyses disclosed infection by Penicillium sp. There are thousands of fungal species of the Penicillium genera. Systemic penicilliosis is caused by the P. marneffei and was formerly a rare disease, but now is one of the most common opportunistic infection of AIDS patients in Southeast Asia. The clinical presentation usually involves the respiratory system and the skin, besides general symptoms like fever and weight loss. Penicillium spp infection caused by species other than P. marneffei normally cause only superficial or allergic disease but rare cases of invasive disease do occur. We report the fourth case of Penicillium spp CNS infection.Apresentamos um caso de infecção do sistema nervoso central (SNC) por Penicillium spp em paciente do sexo masculino, HIV-negativo no Brasil. O paciente apresentou-se ao Serviço de Urgência do Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo queixando-se de alteração visual e dificuldade na fala. Exames de neuroimagem mostraram lesões múltiplas, compatíveis com abscessos. A biópsia esterotáxica revelou infecção fúngica, iniciando-se o tratamento com anfotericina B com sucesso inicial. O paciente morreu poucos dias depois, vítima de uma hemorragia digestiva maciça devido a varizes de esôfago. A necropsia e a análise microbiológica final da biópsia cerebral revelaram infecção por Penicillium spp. Exixtem centenas de espécies de fungos do gênero Penicillium. A peniciliose sistêmica é causada pelo P. marneffei e costumava ser uma doença rara, mas atualmente é uma das infecções oportunistas mais comuns em associação com AIDS no Sudeste Asiático. Infecção pelo Penicillium spp de espécie diferente do P. marneffei normalmente causa apenas doenças superficiais ou alérgicas mas doenças invasivas também ocorrem raramente. Nós relatamos o quarto caso de infecção do SNC por Penicillium spp

Use of Propolis Hydroalcoholic Extract to Treat Colitis Experimentally Induced in Rats by 2,4,6-Trinitrobenzenesulfonic Acid

This study focused on the therapeutic effect of a propolis SLNC 106PI extract on experimental colitis. Wistar adult rats received 0.8 mL rectal dose of one of the following solutions: saline (group S), 20 mg TNBS in 50% ethanol (group TNBS), 20 mg TNBS in 50% ethanol and propolis extract in saline (group TNBS-P), propolis extract in saline (group SP), and 20 mg TNBS in 50% ethanol and 50 mg/kg mesalazine (group TNBS-M). The animals were euthanized 7 or 14 days after the colitis induction. Samples of the distal colon were harvested for the analysis of myeloperoxidase (MPO) enzyme activity and for morphometric analysis in paraffin-embedded histological sections with hematoxylin-eosin or histochemical staining. The animals treated with TNBS exhibited the typical clinical signs of colitis. Increased MPO activity confirmed the presence of inflammation. TNBS induced the development of megacolon, ulceration, transmural inflammatory infiltrate, and thickened bowel walls. Treatment with propolis moderately reduced the inflammatory response, decreased the number of cysts and abscesses, inhibited epithelial proliferation, and increased the number of goblet cells. The anti-inflammatory activity of the propolis SLNC 106 extract was confirmed by the reductions in both the inflammatory infiltrate and the number of cysts and abscesses in the colon mucosa

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

Panoramic snapshot of serum soluble mediator interplay in pregnant women with convalescent COVID-19: an exploratory study

IntroductionSARS-CoV-2 infection during pregnancy can induce changes in the maternal immune response, with effects on pregnancy outcome and offspring. This is a cross-sectional observational study designed to characterize the immunological status of pregnant women with convalescent COVID-19 at distinct pregnancy trimesters. The study focused on providing a clear snapshot of the interplay among serum soluble mediators.MethodsA sample of 141 pregnant women from all prenatal periods (1st, 2nd and 3rd trimesters) comprised patients with convalescent SARS-CoV-2 infection at 3-20 weeks after symptoms onset (COVID, n=89) and a control group of pre-pandemic non-infected pregnant women (HC, n=52). Chemokine, pro-inflammatory/regulatory cytokine and growth factor levels were quantified by a high-throughput microbeads array.ResultsIn the HC group, most serum soluble mediators progressively decreased towards the 2nd and 3rd trimesters of pregnancy, while higher chemokine, cytokine and growth factor levels were observed in the COVID patient group. Serum soluble mediator signatures and heatmap analysis pointed out that the major increase observed in the COVID group related to pro-inflammatory cytokines (IL-6, TNF-α, IL-12, IFN-γ and IL-17). A larger set of biomarkers displayed an increased COVID/HC ratio towards the 2nd (3x increase) and the 3rd (3x to 15x increase) trimesters. Integrative network analysis demonstrated that HC pregnancy evolves with decreasing connectivity between pairs of serum soluble mediators towards the 3rd trimester. Although the COVID group exhibited a similar profile, the number of connections was remarkably lower throughout the pregnancy. Meanwhile, IL-1Ra, IL-10 and GM-CSF presented a preserved number of correlations (≥5 strong correlations in HC and COVID), IL-17, FGF-basic and VEGF lost connectivity throughout the pregnancy. IL-6 and CXCL8 were included in a set of acquired attributes, named COVID-selective (≥5 strong correlations in COVID and <5 in HC) observed at the 3rd pregnancy trimester.Discussion and conclusionFrom an overall perspective, a pronounced increase in serum levels of soluble mediators with decreased network interplay between them demonstrated an imbalanced immune response in convalescent COVID-19 infection during pregnancy that may contribute to the management of, or indeed recovery from, late complications in the post-symptomatic phase of the SARS-CoV-2 infection in pregnant women

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

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives