Monitoria na disciplina de Patologia Clínica Veterinária no período 2022.4

O estudo da patologia clínica veterinária é de extrema importância, desempenhando um papel fundamental em diversas áreas da medicina veterinária. Consequentemente, este trabalho objetivou mostrar a contribuição da monitoria patologia clínica veterinária no processo de ensino-aprendizagem e com a formação profissional do discente monitor. A disciplina de patologia clínica foi ministrada durante o período de 28/11/2022 até 10/04/2023. Para um total de 22 alunos durante o Período Letivo 2022.4. Os planos de trabalho dos monitores incluíram: auxiliar a professora a conduzir as aulas pratica no laboratório, produzir portfólios contendo as metodologias das aulas práticas da disciplina, além da produção de resumos dos assuntos abordados na aula, e coordenação de um grupo de WhatsApp com os alunos para sanar as dúvidas relacionadas aos assuntos ministrados durante as aulas e, a realização de plantão tira-dúvidas antes das provas teóricas e práticas. Estavam matriculados na disciplina 22 alunos, 2 não cursaram a disciplina, desses 95% (19/20) foram aprovados e, 5% (1/20) reprovado. Diante do desempenho dos alunos na disciplina, pode-se concluir que o plano de monitoria foi cumprido de acordo com o planejado. Evidenciando assim, a extrema importância e o suporte da monitoria para disciplina

Ectosparasitas em cachorros do mato (Cerdocyon thous) vítimas de atropelamento na Floresta Nacional dos Carajás (PA) / Ectoparasites in road kill dogs (Cerdocyon thous) in Carajás National Forest (PA)

Pesquisas envolvendo a biodiversidade de esctoparasitas de animais silvestres são de valia para a compreensão do status sanitário de indivíduos no seu habitat, ainda que estes sejam invariavelmente alterados por ações humanas. Por se tratarem de reconhecida causa de doenças em animais silvestres e domésticos, as parasitoses devem ser investigadas sempre que possível e levantamentos da diversidade parasitária devem ser incentivados. O presente trabalho teve por objeto identificar a fauna de ectoparasitos que ocorre em cachorro-do-mato (Cerdocyon thous), vítimas de atropelamento na Floresta Nacional (FLONA) Carajás. No ano 2019, foi realizado o recolhimento de 5 cadáveres de canídeos na área do estudo, dos quais foram coletados sete ectoparasitas, prontamente acondicionados em solução de álcool 70% GL. Os espécimes foram encaminhados para a identificação no Centro de Estudos e Diagnóstico Parasitológico (CEDIPA) da Universidade Federal do Sul e Sudeste do Pará (UNIFESSPA). As características morfológicas permitiram a identificação de carrapatos do gênero Amblyomma sp. e Ctenocephalides sp. A relevância de estudos sobre os ectoparasitos em animais silvestres reside no conhecimento da realidade epidemiológica de enfermidades parasitárias em ambiente silvestre.  Além disso, há que se considerar o risco para a fauna silvestre representada pelo contato com ambientes antropizados e patógenos dos animais domésticos. Em suma, o contato entre a fauna silvestre e animais domésticos pode representar risco para ambas

Dynamics and determinants of SARS-CoV-2 RT-PCR testing on symptomatic individuals attending healthcare centers during 2020 in Bahia, Brazil

RT-PCR testing data provides opportunities to explore regional and individual determinants of test positivity and surveillance infrastructure. Using Generalized Additive Models, we explored 222,515 tests of a random sample of individuals with COVID-19 compatible symptoms in the Brazilian state of Bahia during 2020. We found that age and male gender were the most significant determinants of test positivity. There was evidence of an unequal impact among socio-demographic strata, with higher positivity among those living in areas with low education levels during the first epidemic wave, followed by those living in areas with higher education levels in the second wave. Our estimated probability of testing positive after symptom onset corroborates previous reports that the probability decreases with time, more than halving by about two weeks and converging to zero by three weeks. Test positivity rates generally followed state-level reported cases, and while a single laboratory performed ~90% of tests covering ~99% of the state's area, test turn-around time generally remained below four days. This testing effort is a testimony to the Bahian surveillance capacity during public health emergencies, as previously witnessed during the recent Zika and Yellow Fever outbreaks

UTILIZAÇÃO DA LASERTERAPIA NA REDUÇÃO DO EDEMA PÓS PREENCHIMENTO FACIAL COM ÁCIDO HIALURÔNICO

A cultura digital influenciou os padrões de beleza, destacando a harmonização facial como técnica não cirúrgica de remodelação facial. Procedimentos populares incluem marcação da mandíbula, correção de rugas e mudança do formato do nariz, com uso predominante de ácido hialurônico (AH). O AH, um polímero natural no corpo, melhora a sustentação, hidratação, elasticidade e volume da pele, sendo ideal para preenchimentos dérmicos. O envelhecimento cutâneo provoca perda de contornos e surgimento de rugas, tornando os tratamentos com AH, que são minimamente invasivos e reversíveis, uma escolha popular. Apesar de riscos como reações alérgicas, essas complicações são raras. Laserterapia de baixa intensidade é uma alternativa complementar que reduz edemas, promove a regeneração tecidual e tem efeitos anti-inflamatórios e analgésicos, acelerando a recuperação após o uso de AH

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

Genomics and epidemiology of the P.1 SARS-CoV-2 lineage in Manaus, Brazil

Cases of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in Manaus, Brazil, resurged in late 2020 despite previously high levels of infection. Genome sequencing of viruses sampled in Manaus between November 2020 and January 2021 revealed the emergence and circulation of a novel SARS-CoV-2 variant of concern. Lineage P.1 acquired 17 mutations, including a trio in the spike protein (K417T, E484K, and N501Y) associated with increased binding to the human ACE2 (angiotensin-converting enzyme 2) receptor. Molecular clock analysis shows that P.1 emergence occurred around mid-November 2020 and was preceded by a period of faster molecular evolution. Using a two-category dynamical model that integrates genomic and mortality data, we estimate that P.1 may be 1.7- to 2.4-fold more transmissible and that previous (non-P.1) infection provides 54 to 79% of the protection against infection with P.1 that it provides against non-P.1 lineages. Enhanced global genomic surveillance of variants of concern, which may exhibit increased transmissibility and/or immune evasion, is critical to accelerate pandemic responsiveness

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