Bem estar do trabalhador é essencial para o bem estar animal?

Increasingly, animal welfare (AW) is gaining ground worldwide because of pressure from importing countries, as well as the demand from a more conscious society regarding the living conditions of farm animals. Despite the growing concern about AW, there are few studies of stock person’s welfare and how it might influence AW. The treatment of animals connects to stockpersons’ attitudes and behaviour, which in turn are associated with several human factors such as initial experience in the activity, welfare, quality of working conditions and human-animal relationship. Many authors have investigated this relationship and its association with positive attitudes of stock persons towards animals, which consequently influence AW and productivity. However, currently, there is no highlighted concern about the human issue, as the stock person welfare (SW), believed to be a key aspect of a successful implementation of AW programs. The present work suggests a broader view concerning AW, its relation to SW and the importance of improving both aspects in livestock systems.Cada vez mais o bem-estar animal (BEA) está ganhando espaço mundialmente, tanto pela pressão dos países importadores, quanto pela demanda por uma sociedade mais consciente em relação às condições de vida dos animais de produção. Apesar da crescente preocupação com o BEA, há poucos estudos sobre o bem-estar dos trabalhadores e como isso pode influenciar no BEA. O tratamento dos animais está ligado às atitudes e aos comportamentos dos trabalhadores, que por sua vez estão associados a vários fatores humanos, como experiência inicial na atividade, bem-estar e qualidade das condições de trabalho e relação homem-animal. Muitos autores têm investigado essa relação e sua associação às atitudes positivas dos trabalhadores em relação aos animais, o que, consequentemente, influencia o BEA e a produtividade. No entanto, atualmente, não há nenhuma preocupação destacada sobre a questão humana, como o bem-estar dos trabalhadores (BT), que se acredita ser aspecto chave para uma implementação bem sucedida dos programas de BEA. O presente trabalho sugere uma visão mais ampla sobre o BEA, sua relação com o BT e a importância de se melhorar ambos os aspectos em sistemas de produção animal

Escorpionismo no estado de São Paulo: um problema de saúde pública em ascensão

O escorpionismo é reconhecido como um problema de Saúde Pública e são de grande recorrência no Brasil, sendo o estado de São Paulo um dos estados com maior número de casos. A identificação de fatores que possam levar ao aumento da população desses artrópodes é importante para a implementação de planos de prevenção desses acidentes. O presente estudo teve como objetivo retratar os aspectos epidemiológicos descritivos dos acidentes escorpiônicos no estado de São Paulo entre 2012 e 2022, e correlacionar com dados climáticos em cada mês dos anos estudados, por Diretoria Regional de Saúde (DRS). O escorpionismo no Estado de São Paulo teve um salto de 2012 para 2022: passou de 9150 acidentes para 41500. Os óbitos também apresentaram uma oscilação positiva, passando de 3 em 2012 para 22 em 2022. Nas quatro DRS que apresentaram maior taxa de incidência, DRS II (Araçatuba), DRS XV (São José do Rio Preto), DRS V (Barretos) e DRS XI (Presidente Prudente), respectivamente, também se observa o crescimento de escorpionismo. Não foi possível se determinar, pelo Coeficiente de Correlação de Pearson, um ou mais fatores (testados) que justificassem o número elevado de acidentes nessas quatro DRS. Portanto, fica claro que a relação causal é multifatorial, e incide sobre o número de acidentes por escorpião não somente temperatura e precipitação, tão pouco número de habitantes, mas sim diversos fatores, como ambientais, climatológicos, sociodemográficos, entre outros, que precisam ser levados em consideração para se estabelecer a relação causa-efeito no escorpionismo. Os dados apresentados por este trabalho mostram que nos meses mais quentes e chuvosos (outubro a dezembro) são quando os escorpiões deixam seus abrigos em busca de locais secos, para reprodução e alimentação, e colocam a população sob risco. Os dados apresentados contribuem para a regulação da produção e oferta de soro antiescorpiônico pelos órgãos de saúde, bem como para adoção de estratégias para o controle do animal

Usefulness of aqueous and vitreous humor analysis in infectious uveitis

OBJECTIVE: To evaluate the role of intraocular fluid analysis as a diagnostic aid for uveitis. METHODS: Twenty-eight samples (27 patients including 3 HIV-infected patients) with active (n=24) or non-active (n=4) uveitis were submitted to aqueous (AH; n=12) or vitreous humor (VH) analysis (n=16). All samples were analyzed by quantitative PCR for herpes simplex virus (HSV), varicella zoster virus (VZV), cytomegalovirus (CMV), Epstein-Barr virus (EBV) and Toxoplasma gondii. RESULTS: The positivity of the PCR in AH was 41.7% (5/12), with 50% (2/4) in immunocompetent and 67% (2/3) in HIV+ patients. The positivity of the PCR in VH was 31.2% (5/16), with 13% (1/8) in immunocompetent and 50% (4/8) in immunosuppressed HIV negative patients. The analysis was a determinant in the diagnostic definition in 58% of HA and 50% of VH. CONCLUSION: Even in posterior uveitis, initial AH analysis may be helpful. A careful formulation of possible clinical diagnosis seems to increase the chance of intraocular sample analysis being meaningful

Gene Duplication in the Sugarcane Genome: A Case Study of Allele Interactions and Evolutionary Patterns in Two Genic Regions

Sugarcane (Saccharum spp.) is highly polyploid and aneuploid. Modern cultivars are derived from hybridization between S. officinarum and S. spontaneum. This combination results in a genome exhibiting variable ploidy among different loci, a huge genome size (~10 Gb) and a high content of repetitive regions. An approach using genomic, transcriptomic, and genetic mapping can improve our knowledge of the behavior of genetics in sugarcane. The hypothetical HP600 and Centromere Protein C (CENP-C) genes from sugarcane were used to elucidate the allelic expression and genomic and genetic behaviors of this complex polyploid. The physically linked side-by-side genes HP600 and CENP-C were found in two different homeologous chromosome groups with ploidies of eight and ten. The first region (Region01) was a Sorghum bicolor ortholog region with all haplotypes of HP600 and CENP-C expressed, but HP600 exhibited an unbalanced haplotype expression. The second region (Region02) was a scrambled sugarcane sequence formed from different noncollinear genes containing partial duplications of HP600 and CENP-C (paralogs). This duplication resulted in a non-expressed HP600 pseudogene and a recombined fusion version of CENP-C and the orthologous gene Sobic.003G299500 with at least two chimeric gene haplotypes expressed. It was also determined that it occurred before Saccharum genus formation and after the separation of sorghum and sugarcane. A linkage map was constructed using markers from nonduplicated Region01 and for the duplication (Region01 and Region02). We compare the physical and linkage maps, demonstrating the possibility of mapping markers located in duplicated regions with markers in nonduplicated region. Our results contribute directly to the improvement of linkage mapping in complex polyploids and improve the integration of physical and genetic data for sugarcane breeding programs. Thus, we describe the complexity involved in sugarcane genetics and genomics and allelic dynamics, which can be useful for understanding complex polyploid genomes

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

Geography and ecology shape the phylogenetic composition of Amazonian tree communities

Aim: Amazonia hosts more tree species from numerous evolutionary lineages, both young and ancient, than any other biogeographic region. Previous studies have shown that tree lineages colonized multiple edaphic environments and dispersed widely across Amazonia, leading to a hypothesis, which we test, that lineages should not be strongly associated with either geographic regions or edaphic forest types. Location: Amazonia. Taxon: Angiosperms (Magnoliids; Monocots; Eudicots). Methods: Data for the abundance of 5082 tree species in 1989 plots were combined with a mega-phylogeny. We applied evolutionary ordination to assess how phylogenetic composition varies across Amazonia. We used variation partitioning and Moran\u27s eigenvector maps (MEM) to test and quantify the separate and joint contributions of spatial and environmental variables to explain the phylogenetic composition of plots. We tested the indicator value of lineages for geographic regions and edaphic forest types and mapped associations onto the phylogeny. Results: In the terra firme and várzea forest types, the phylogenetic composition varies by geographic region, but the igapó and white-sand forest types retain a unique evolutionary signature regardless of region. Overall, we find that soil chemistry, climate and topography explain 24% of the variation in phylogenetic composition, with 79% of that variation being spatially structured (R$^{2}$ = 19% overall for combined spatial/environmental effects). The phylogenetic composition also shows substantial spatial patterns not related to the environmental variables we quantified (R$^{2}$ = 28%). A greater number of lineages were significant indicators of geographic regions than forest types. Main Conclusion: Numerous tree lineages, including some ancient ones (>66 Ma), show strong associations with geographic regions and edaphic forest types of Amazonia. This shows that specialization in specific edaphic environments has played a long-standing role in the evolutionary assembly of Amazonian forests. Furthermore, many lineages, even those that have dispersed across Amazonia, dominate within a specific region, likely because of phylogenetically conserved niches for environmental conditions that are prevalent within regions

Geography and ecology shape the phylogenetic composition of Amazonian tree communities

AimAmazonia hosts more tree species from numerous evolutionary lineages, both young and ancient, than any other biogeographic region. Previous studies have shown that tree lineages colonized multiple edaphic environments and dispersed widely across Amazonia, leading to a hypothesis, which we test, that lineages should not be strongly associated with either geographic regions or edaphic forest types.LocationAmazonia.TaxonAngiosperms (Magnoliids; Monocots; Eudicots).MethodsData for the abundance of 5082 tree species in 1989 plots were combined with a mega-phylogeny. We applied evolutionary ordination to assess how phylogenetic composition varies across Amazonia. We used variation partitioning and Moran's eigenvector maps (MEM) to test and quantify the separate and joint contributions of spatial and environmental variables to explain the phylogenetic composition of plots. We tested the indicator value of lineages for geographic regions and edaphic forest types and mapped associations onto the phylogeny.ResultsIn the terra firme and várzea forest types, the phylogenetic composition varies by geographic region, but the igapó and white-sand forest types retain a unique evolutionary signature regardless of region. Overall, we find that soil chemistry, climate and topography explain 24% of the variation in phylogenetic composition, with 79% of that variation being spatially structured (R2 = 19% overall for combined spatial/environmental effects). The phylogenetic composition also shows substantial spatial patterns not related to the environmental variables we quantified (R2 = 28%). A greater number of lineages were significant indicators of geographic regions than forest types.Main ConclusionNumerous tree lineages, including some ancient ones (>66 Ma), show strong associations with geographic regions and edaphic forest types of Amazonia. This shows that specialization in specific edaphic environments has played a long-standing role in the evolutionary assembly of Amazonian forests. Furthermore, many lineages, even those that have dispersed across Amazonia, dominate within a specific region, likely because of phylogenetically conserved niches for environmental conditions that are prevalent within regions

Mapping density, diversity and species-richness of the Amazon tree flora

Using 2.046 botanically-inventoried tree plots across the largest tropical forest on Earth, we mapped tree species-diversity and tree species-richness at 0.1-degree resolution, and investigated drivers for diversity and richness. Using only location, stratified by forest type, as predictor, our spatial model, to the best of our knowledge, provides the most accurate map of tree diversity in Amazonia to date, explaining approximately 70% of the tree diversity and species-richness. Large soil-forest combinations determine a significant percentage of the variation in tree species-richness and tree alpha-diversity in Amazonian forest-plots. We suggest that the size and fragmentation of these systems drive their large-scale diversity patterns and hence local diversity. A model not using location but cumulative water deficit, tree density, and temperature seasonality explains 47% of the tree species-richness in the terra-firme forest in Amazonia. Over large areas across Amazonia, residuals of this relationship are small and poorly spatially structured, suggesting that much of the residual variation may be local. The Guyana Shield area has consistently negative residuals, showing that this area has lower tree species-richness than expected by our models. We provide extensive plot meta-data, including tree density, tree alpha-diversity and tree species-richness results and gridded maps at 0.1-degree resolution

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