Chromatin differentiation between Theobroma cacao L. and T. grandiflorum Schum

A comparative analysis of mitotic chromosomes of Theobroma cacao (cacao) and T. grandiflorum (cupuaçu) was performed aiming to identify cytological differences between the two most important species of this genus. Both species have symmetric karyotypes, with 2n = 20 metacentric chromosomes ranging in size from 2.00 to 1.19 μm (cacao) and from 2.21 to 1.15 μm (cupuaçu). The interphase nuclei of both species were of the arreticulate type, displaying up to 20 chromocentres, which were more regularly shaped in cacao than in cupuaçu. Prophase chromosomes of both species were more condensed in the proximal region, sometimes including the whole short arm. Both species exhibited only one pair of terminal heterochromatic bands, positively stained with chromomycin A 3 , which co-localized with the single 45S rDNA site. Each karyotype displayed a single 5S rDNA site in the proximal region of another chromosome pair. Heterochromatic bands were also observed on the centromeric/pericentromeric regions of all 20 chromosomes of cacao after C-banding followed by Giemsa or DAPI staining, whereas in cupuaçu they were never detected. These data suggest that the chromosomes of both species have been largely conserved and their pericentromeric chromatin is the only citologically differentiated region

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

A cross-sectional study on canine Leishmania (L.) infantum chagasi infection in Amazonian Brazil ratifies a higher prevalence of specific IgG-antibody response than delayed-type hypersensitivity in symptomatic and asymptomatic dogs

This was a cross-sectional study which analyzed the prevalence and the clinical and immunological spectrum of canine Leishmania (L.) infantum chagasi infection in a cohort of 320 mongrel dogs living in an endemic area of American visceral leishmaniasis in the Amazonian Brazil by using, mainly, the indirect fluorescence antibody test (IFAT-IgG) and the delayed-type hypersensitivity (DTH), and the parasite research by the popliteal lymph node aspiration. The IFAT and DTH reactivity recognized three different immune response profiles: (1) IFAT((+))/DTH(-) (107 dogs), (2) IFAT((-))/DTH(+) (18 dogs), and (3) IFAT((+))/DTH(+) (13 dogs), providing an overall prevalence of infection of 43 % (138/320). Thus, the specific prevalence of IFAT ((+)) /DTH ((-)) 33.4 % (107/320) was higher than those of IFAT ((-)) /DTH ((+)) 5.6 % (18/320) and IFAT ((+)) /DTH ((+)) 4.0 % (13/320). Moreover, the frequency of these profiles among 138 infected dogs showed that the IFAT ((+)) /DTH ((-)) rate of 77.5 % (107/138) was also higher than those of 13.0 % (18/138) of IFAT ((-)) /DTH ((+)) and 9.5 % (13/138) of IFAT ((+)) /DTH ((+)) rates. The frequency of asymptomatic dogs (76 %-105) was higher than those of symptomatic (16.6 %-23) and oligosymptomatic ones (7.4 %-10). A total of 16 (11.6 %) L. (L.) i. chagasi isolates were obtained from infected dogs, all from the IFAT ((+)) /DTH ((-)) profile: 41 % (9/22) from symptomatic, 33.3 % (3/9) from oligosymptomatic, and 5.2 % (4/76) from asymptomatic dogs. These findings strongly suggested that despite the higher frequency of asymptomatic dogs (76 %-105), the majority (72.4 %-76) was characterized by the IFAT ((+)) /DTH ((-)) profile with a doubtful immunogenetic resistance against infection

The Omicron Lineages BA.1 and BA.2 (<i>Betacoronavirus</i> SARS-CoV-2) Have Repeatedly Entered Brazil through a Single Dispersal Hub

Brazil currently ranks second in absolute deaths by COVID-19, even though most of its population has completed the vaccination protocol. With the introduction of Omicron in late 2021, the number of COVID-19 cases soared once again in the country. We investigated in this work how lineages BA.1 and BA.2 entered and spread in the country by sequencing 2173 new SARS-CoV-2 genomes collected between October 2021 and April 2022 and analyzing them in addition to more than 18,000 publicly available sequences with phylodynamic methods. We registered that Omicron was present in Brazil as early as 16 November 2021 and by January 2022 was already more than 99% of samples. More importantly, we detected that Omicron has been mostly imported through the state of São Paulo, which in turn dispersed the lineages to other states and regions of Brazil. This knowledge can be used to implement more efficient non-pharmaceutical interventions against the introduction of new SARS-CoV variants focused on surveillance of airports and ground transportation