Expedição ao Sítio Histórico e Patrimônio Cultural Kalunga: um Relato de Experiência

The Kalunga Historical and Cultural Heritage Site (SHPCK) is located in the northeast of Goiás and is considered one of the best-preserved areas of native Cerrado in all of Brazil. This is due to local geographic characteristics and mainly to the sustainable character of agricultural production by the traditional peoples who inhabit the region. In addition to having a vast preserved territory, the Kalungas have unique traditional knowledge about local plants. Due to biodiversity, they have access to herbal plants that can be used in human and animal food. However, the number of species of toxic plants may also considered high. With this report we aim to describe the unique experience that was the Expedition to the Kalunga Historical and Cultural Site and Heritage, as well as to emphasize the importance of the toxic plants of the Cerrado and the appreciation of traditional knowledge.A Comunidade Quilombola Kalunga fixou-se no Sítio Patrimônio Histórico e Cultural Kalunga (SHPCK), localizado no nordeste do estado de Goiás, e é considerada uma das áreas mais bem preservadas de Cerrado nativo em todo o Brasil. Isso se deve à dificuldade de acesso, às características geográficas locais e também ao caráter sustentável da produção agropecuária do povo quilombola que habita a região. Além de possuírem vasto território preservado, os Kalungas detêm conhecimento tradicional singular sobre as plantas locais e, graças à biodiversidade do Cerrado, eles têm acesso a plantas fitoterápicas e que podem ser utilizadas na alimentação humana e animal. No entanto, o número de espécies de plantas tóxicas também pode ser considerado elevado. Com este relato, objetivamos descrever a experiência única que foi a Expedição ao Sítio e Patrimônio Histórico e Cultural Kalunga, assim como ressaltar a importância das plantas tóxicas do Cerrado e da valorização do conhecimento tradicional.A Comunidade Quilombola Kalunga fixou-se no Sítio Patrimônio Histórico e Cultural Kalunga (SHPCK), localizado no nordeste do estado de Goiás, e é considerada uma das áreas mais bem preservadas de Cerrado nativo em todo o Brasil. Isso se deve à dificuldade de acesso, às características geográficas locais e também ao caráter sustentável da produção agropecuária do povo quilombola que habita a região. Além de possuírem vasto território preservado, os Kalungas detêm conhecimento tradicional singular sobre as plantas locais e, graças à biodiversidade do Cerrado, eles têm acesso a plantas fitoterápicas e que podem ser utilizadas na alimentação humana e animal. No entanto, o número de espécies de plantas tóxicas também pode ser considerado elevado. Com este relato, objetivamos descrever a experiência única que foi a Expedição ao Sítio e Patrimônio Histórico e Cultural Kalunga, assim como ressaltar a importância das plantas tóxicas do Cerrado e da valorização do conhecimento tradicional

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

Detection of an Undescribed <i>Babesia</i> sp. in Capybaras and <i>Amblyomma</i> Ticks in Central-Western Brazil

Capybaras (Hydrochoerus hydrochaeris) are the largest rodents on Earth. While capybaras are hosts for various tick species, there is limited information regarding the tick-borne pathogens they can carry. We investigated the presence of piroplasmids and Ehrlichia spp. in capybaras and their associated ticks in two peri-urban areas in Goiás state, central-western Brazil. Blood samples collected from 23 capybaras were used to investigate the presence of piroplasmids and Ehrlichia spp. in stained-blood smears and by PCR. Ticks collected from the capybaras were identified morphologically and also tested using PCR for the same pathogens. A total of 955 ticks were collected, including 822 (86.1%) Amblyomma sculptum, 132 (13.8%) Amblyomma dubitatum, and one (0.1%) unidentified larva of Amblyomma sp. Neither the capybaras nor ticks were positive for Ehrlichia spp. However, a stained-blood smear examination revealed the presence of ring-stage and pyriform-shaped merozoites in the erythrocytes of one (4.4%) capybara. In the same way, 47.8% (11/23) and 19.9% (36/181) of blood samples and ticks, respectively, were positive for piroplasmids in the PCR. We successfully sequenced a partial 18S rRNA gene fragment of four samples (two capybaras, one A. sculptum, and one A. dubitatum), and the phylogenetic reconstruction disclosed that the organism reported in the present study clusters within the genus Babesia. Further research is required for a formal delineation of this species (designated as Babesia sp. strain Capybara) and to investigate the hypothesis of A. dubitatum and A. sculptum ticks being vectors

Detection of <i>Rickettsia</i> spp. in Animals and Ticks in Midwestern Brazil, Where Human Cases of Rickettsiosis Were Reported

Brazilian spotted fever (BSF) is the most important tick-borne diseases affecting humans in Brazil. Cases of BSF have recently been reported in the Goiás state, midwestern Brazil. All cases have been confirmed by reference laboratories by seroconversion to Rickettsia rickettsii antigens. Because serological cross-reactions among different rickettsial species that belong to the spotted fever group (SFG) are common, the agent responsible for BSF cases in Goiás remains unknown. From March 2020 to April 2022, ticks and plasma were collected from dogs, horses and capybaras (Hydrochoerus hydrochaeris), and from the vegetation in an area where BSF cases have been reported and two areas under epidemiological surveillance in Goiás. Horses were infested by Amblyomma sculptum, Dermacentor nitens and Rhipicephalus microplus; dogs by Rhipicephalus sanguineus sensu lato (s.l.), Amblyomma ovale and A. sculptum, and capybaras by A. sculptum and Amblyomma dubitatum. Adults of A. sculptum, A. dubitatum, Amblyomma rotundatum and immature stages of A. sculptum and A. dubitatum, and Amblyomma spp. were collected from the vegetation. DNA of Rickettsia that did not belong to the SFG was detected in A. dubitatum, which was identified by DNA sequencing as Rickettsia bellii. Seroreactivity to SFG and Rickettsia bellii antigens was detected in 25.4% (42/165) of dogs, 22.7% (10/44) of horses and 41.2% (7/17) of capybaras, with higher titers for R. bellii in dogs and capybaras. The seropositivity of animals to SFG Rickettsia spp. antigens demonstrates the circulation of SFG rickettsiae in the region. Further research is needed to fully determine the agent responsible for rickettsiosis cases in this area

A global metagenomic map of urban microbiomes and antimicrobial resistance

We present a global atlas of 4,728 metagenomic samples from mass-transit systems in 60 cities over 3 years, representing the first systematic, worldwide catalog of the urban microbial ecosystem. This atlas provides an annotated, geospatial profile of microbial strains, functional characteristics, antimicrobial resistance (AMR) markers, and genetic elements, including 10,928 viruses, 1,302 bacteria, 2 archaea, and 838,532 CRISPR arrays not found in reference databases. We identified 4,246 known species of urban microorganisms and a consistent set of 31 species found in 97% of samples that were distinct from human commensal organisms. Profiles of AMR genes varied widely in type and density across cities. Cities showed distinct microbial taxonomic signatures that were driven by climate and geographic differences. These results constitute a high-resolution global metagenomic atlas that enables discovery of organisms and genes, highlights potential public health and forensic applications, and provides a culture-independent view of AMR burden in cities.Funding: the Tri-I Program in Computational Biology and Medicine (CBM) funded by NIH grant 1T32GM083937; GitHub; Philip Blood and the Extreme Science and Engineering Discovery Environment (XSEDE), supported by NSF grant number ACI-1548562 and NSF award number ACI-1445606; NASA (NNX14AH50G, NNX17AB26G), the NIH (R01AI151059, R25EB020393, R21AI129851, R35GM138152, U01DA053941); STARR Foundation (I13- 0052); LLS (MCL7001-18, LLS 9238-16, LLS-MCL7001-18); the NSF (1840275); the Bill and Melinda Gates Foundation (OPP1151054); the Alfred P. Sloan Foundation (G-2015-13964); Swiss National Science Foundation grant number 407540_167331; NIH award number UL1TR000457; the US Department of Energy Joint Genome Institute under contract number DE-AC02-05CH11231; the National Energy Research Scientific Computing Center, supported by the Office of Science of the US Department of Energy; Stockholm Health Authority grant SLL 20160933; the Institut Pasteur Korea; an NRF Korea grant (NRF-2014K1A4A7A01074645, 2017M3A9G6068246); the CONICYT Fondecyt Iniciación grants 11140666 and 11160905; Keio University Funds for Individual Research; funds from the Yamagata prefectural government and the city of Tsuruoka; JSPS KAKENHI grant number 20K10436; the bilateral AT-UA collaboration fund (WTZ:UA 02/2019; Ministry of Education and Science of Ukraine, UA:M/84-2019, M/126-2020); Kyiv Academic Univeristy; Ministry of Education and Science of Ukraine project numbers 0118U100290 and 0120U101734; Centro de Excelencia Severo Ochoa 2013–2017; the CERCA Programme / Generalitat de Catalunya; the CRG-Novartis-Africa mobility program 2016; research funds from National Cheng Kung University and the Ministry of Science and Technology; Taiwan (MOST grant number 106-2321-B-006-016); we thank all the volunteers who made sampling NYC possible, Minciencias (project no. 639677758300), CNPq (EDN - 309973/2015-5), the Open Research Fund of Key Laboratory of Advanced Theory and Application in Statistics and Data Science – MOE, ECNU, the Research Grants Council of Hong Kong through project 11215017, National Key RD Project of China (2018YFE0201603), and Shanghai Municipal Science and Technology Major Project (2017SHZDZX01) (L.S.