Scarabaeoidea (Insecta : Coleoptera) in the Brazilian Cerrado : current state of knowledge

Besouros pertencentes à superfamília Scarabaeoidea ocupam habitats variados, possuem hábitos alimentares diversifi cados, desempenham importante papel ecológico e diversas espécies apresentam importância agrícola. No entanto, estudos com esse grupo na região do Cerrado são escassos. Nesta revisão realizou-se um levantamento dos artigos publicados nos últimos 30 anos a respeito dos Scarabaeoidea no Cerrado. Foram recuperados 64 artigos, realizados em nove unidades da federação, que focavam quatro temas principais espécies praga, aspectos bioecológicos, biodiversidade e importância ecológica, e técnicas e metodologias de coleta de Scarabaeoidea. Os resultados desta revisão indicam que poucos estudos foram realizados com os Scarabaeoidea no Cerrado brasileiro nas últimas décadas frente à importância e diversidade desse grupo de insetos.Beetles belonging to the superfamily Scarabaeoidea occupy different habitats, present feeding habits diversifi ed, play an important ecological role and several species have agricultural importance. However, studies with this group in the Brazilian Cerrado are scarce. In this review we carried out a survey of scientifi c articles published in the past 30 years concerning Scarabaeoidea in the Cerrado. Were found 64 studies in nine Brazilian states. The studies focused on four main topics: pest species, bioecology, biodiversity and ecological importance, techniques and methodologies for collecting Scarabaeoidea. The results of this review indicate that few studies have been conducted with Scarabaeoidea in the Cerrado in recent decades compared to the importance and diversity of this group of insects

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

COVID-19 symptoms at hospital admission vary with age and sex: results from the ISARIC prospective multinational observational study

Background: The ISARIC prospective multinational observational study is the largest cohort of hospitalized patients with COVID-19. We present relationships of age, sex, and nationality to presenting symptoms. Methods: International, prospective observational study of 60 109 hospitalized symptomatic patients with laboratory-confirmed COVID-19 recruited from 43 countries between 30 January and 3 August 2020. Logistic regression was performed to evaluate relationships of age and sex to published COVID-19 case definitions and the most commonly reported symptoms. Results: ‘Typical’ symptoms of fever (69%), cough (68%) and shortness of breath (66%) were the most commonly reported. 92% of patients experienced at least one of these. Prevalence of typical symptoms was greatest in 30- to 60-year-olds (respectively 80, 79, 69%; at least one 95%). They were reported less frequently in children (≤ 18 years: 69, 48, 23; 85%), older adults (≥ 70 years: 61, 62, 65; 90%), and women (66, 66, 64; 90%; vs. men 71, 70, 67; 93%, each P < 0.001). The most common atypical presentations under 60 years of age were nausea and vomiting and abdominal pain, and over 60 years was confusion. Regression models showed significant differences in symptoms with sex, age and country. Interpretation: This international collaboration has allowed us to report reliable symptom data from the largest cohort of patients admitted to hospital with COVID-19. Adults over 60 and children admitted to hospital with COVID-19 are less likely to present with typical symptoms. Nausea and vomiting are common atypical presentations under 30 years. Confusion is a frequent atypical presentation of COVID-19 in adults over 60 years. Women are less likely to experience typical symptoms than men

Prognostication of prostate cancer based on TOP2A protein and gene assessment: TOP2A in prostate cancer

Abstract Background TOP2A encodes for topoisomerase IIα, a nuclear enzyme that controls DNA topological structure and cell cycle progression. This enzyme is a marker of cell proliferation in normal and neoplastic tissues; however, little information is available about its expression in prostate cancer (PCa). Methods Immunohistochemistry (IHC) was automated using mouse monoclonal antibody against TOP2A (clone SWT3D1; DAKO, Carpenteria, CA, USA) at dilution 1:800 and Flex Plus detection system in autostainer 48Ultra (DAKO). FISH was performed using TOP2A (17q21)/ CEP17 probe kit (Kreateck Biotechnology, San Diego, CA, USA). Biochemical and pathological data from 193 patients with PCa were retrieved for the analysis, whose significance was considered when p < 0.05. Also, fractal analysis was performed in a subset of 20 randomly selected cases. Results TOP2A protein expression correlated with higher Gleason scores and higher levels of preoperative PSA (p = 0.018 and p = 0.011). Patients with higher levels of TOP2A presented shorter biochemical recurrence-free survival (BRFS) (p = 0.001). In multivariate analysis, we found that TOP2A remained an independent prognostic factor of BRFS, with a relative risk of 1.98 (p = 0.001; 95% CI, 1.338–2.93); thus, cases that expressed high levels of this enzyme had a shorter BRFS compared with TOP2A-negative or TOP2A-low cases. No alterations in TOP2A gene status nor correlation between FISH and IHC results were observed. Concerning fractal analysis, patients who expressed higher levels of TOP2A have angiolymphatic invasion and presented higher Gleason scores (p = 0.033 and p = 0.025, respectively). Also, patients with higher expression of TOP2A presented shorter BRFS (p = 0.001). Conclusions This is the first study to perform TOP2A protein and gene digital assessment and fractal analysis in association with BRFS in a large series of PCa. Also, we show that TOP2A gene copy number alterations are not observed in this type of tumor. So, higher protein expression of TOP2A is not related to gene amplification in PCa. Furthermore, TOP2A protein assessment has prognostic importance and, due to its relation with poor outcome, TOP2A IHC evaluation in the biopsy can represent an important tool for selecting the most suitable surgical and clinical approach for patients with PCa

Genome-wide association studies, meta-analyses and derived gene network for meat quality and carcass traits in pigs

A large number of quantitative trait loci (QTL) for meat quality and carcass traits has been reported in pigs over the past 20 years. However, few QTL have been validated and the biological meaning of the genes associated to these QTL has been underexploited. In this context, a meta-analysis was performed to compare the significant markers with meta-QTL previously reported in literature. Genome association studies were performed for 12 traits, from which 144 SNPs were found out to be significant (P < 0.05). They were validated in the meta-analysis and used to build the Association Weight Matrix, a matrix framework employed to investigate co-association of pairwise SNP across phenotypes enabling to derive a gene network. A total of 45 genes were selected from the Association Weight Matrix analysis, from which 25 significant transcription factors were identified and used to construct the networks associated to meat quality and carcass traits. These networks allowed the identification of key transcription factors, such as SOX5 and NKX2-5, gene-gene interactions (e.g. ATP5A1, JPH1, DPT and NEDD4) and pathways related to the regulation of adipose tissue metabolism and skeletal muscle development. Validated SNPs and knowledge of key genes driving these important industry traits might assist future strategies in pig breeding