DESENVOLVIMENTO SUSTENTÁVEL EM CABO VERDE

Tendo como tripé os fatores econômicos, sociais e ambientais, o Desenvolvimento Sustentável viabiliza suprir as necessidades básicas das gerações presentes sem comprometer a sobrevivência das demais gerações, ou seja, isso será possível se tiver a qualidade ambiental e com a renovação do estoque dos recursos (BECKER; MIRANDA, 1997). Desta forma, abordar o elo que existe entre as políticas públicas adotadas pelos países que almejam o desenvolvimento sustentável nas mais diversas áreas a luz da Agenda 21 de cada país são alguns dos temas que dão sustento a este trabalho podendo entender as vantagens e desvantagens na escolha de um crescimento baseado na sustentabilidade. Portanto, o presente estudo pretende fazer uma breve análise de como estão sendo incorporadas as políticas públicas para o desenvolvimento sustentável em Cabo Verde com o intuito de andar alinhado com todos os objetivos estabelecidos pela Organização das Nações Unidas (ONU) ao longo das suas conferências

CUIDADO INTEGRAL E ATENÇÃO AO PACIENTE EM URGÊNCIAS E EMERGÊNCIAS

  Comprehensive patient care in urgent and crisis situations is essential to guarantee the quality and efficiency of healthcare. This study presents a comprehensive review of the literature exploring approaches and strategies to provide this comprehensive care, considering the complexity of these scenarios. Through the analysis of various studies and professional literature, the most important components that make up a comprehensive approach to critical situations are identified. These approaches include effective screening, interprofessional communication, and implementation of up-to-date medical protocols and consideration of the patient's psychosocial needs. The literature review highlights the importance of properly coordinating healthcare team training and resources to ensure comprehensive and effective patient care in emergencies and crises. Comprehensive patient care in emergency and crisis situations is a difficult challenge, but essential to guarantee the success of healthcare in these situations. This study highlights the need for multidisciplinary approaches, well-defined protocols and effective communication between the healthcare team to ensure that all dimensions of a patient's health are addressed. Additionally, attention to the patient's psychosocial and emotional needs plays a vital role in recovery and overall well-being. Therefore, investments are needed in team training and adequate coordination of resources to provide comprehensive care to patients in emergency and crisis situations.O atendimento integral ao paciente em situações de urgência e crise é essencial para garantir a qualidade e a eficiência dos cuidados de saúde. Este estudo apresenta uma revisão abrangente da literatura explorando abordagens e estratégias para prestar esse cuidado integral, considerando a complexidade desses cenários. Através da análise de diversos estudos e literatura profissional, são identificados os componentes mais importantes que compõem uma abordagem abrangente para situações críticas. Essas abordagens incluem triagem eficaz, comunicação interprofissional e implementação de protocolos médicos atualizados e consideração das necessidades psicossociais do paciente. A revisão da literatura destaca a importância da coordenação adequada do treinamento e dos recursos da equipe de saúde para garantir um tratamento abrangente e eficaz paciente em emergências e crises. O atendimento integral ao paciente em situações de urgência e crise é um desafio difícil, mas essencial para garantir o sucesso da assistência à saúde nessas situações. Este estudo destaca a necessidade de abordagens multidisciplinares, protocolos bem definidos e comunicação eficaz entre a equipe de saúde para garantir que todas as dimensões da saúde do paciente sejam abordadas. Além disso, é dada atenção às necessidades psicossociais e emocionais do paciente desempenha um papel vital na recuperação e no bem-estar geral. Portanto, são necessários investimentos na capacitação da equipe e na coordenação adequada de recursos para prestar atendimento integral aos pacientes em situações de emergência e crise

Behavioral, Neurochemical and Histological Changes in the Use of Low Doses of Naltrexone and Donepezil in the Treatment in Experimental Model of Alzheimer’s Disease by Induction of β-Amyloid1-42 in Rats

Alzheimer's disease (AD) is a progressive neurodegenerative disorder that promotes the involvement of memory-related functions, characterized by the presence of amyloid plaques formed by the β-amyloid peptide (Aβ), and hyperphosphorylated Tau protein neurofibrillary tangles. Evidence suggests that the use of low doses of Naltrexone, an opioid antagonist, possibly promotes a modulation of the immune system and consequent neuroprotective effect. The present study uses the animal model of induction with β-amyloid1-42 (Aβ1-42) to verify the behavioral, neurochemical and histological effects of the use of low doses of Naltrexone. Male wistar rats (250-300g) divided into five groups (N = 8) were used: Control, Sham, Aβ1-42 subdivided into three groups: treated with water, 05 mg Donepezil and 4.5 mg Naltrexone, orally during the 30-day period. Behavioral tests demonstrated the efficacy of induction to the experimental model with reduced memory of Aβ1-42-treated animals as well as reversal of damage in animals treated with Naltrexone. In the structural analysis, observed that the animals induced by Aβ1-42 treated with water alone presented alterations in the pyramidal forms of the hippocampal cells and that the animals treated with Naltrexone presented possibly a reversal of the neuronal damages. In conclusion, treatment with Naltrexone promoted a reversal in the memory impairment of rodents induced to the Alzheimer's model with Aβ1-42 in the behavioral and histological response

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

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

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

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