DESENVOLVIMENTO DE UM APLICATIVO MÓVEL PARA REALIZAR A CONTAGEM DE CARBOIDRATOS EM REFEIÇÕES A PARTIR DE UM SISTEMA DE VISÃO COMPUTACIONAL

Diabetes Mellitus (DM) is a condition characterized by hyperglycemia. Carbohydrates present in foods are the nutrients that have the greatest impact on blood glucose levels, as they are fully converted to glucose after ingestion and absorption. Thus, solutions aimed at carbohydrate counting (CHO) in meals enable greater flexibility and enhance the quality of life for individuals with this condition, serving as an adjunct to treatment. Therefore, the present study aimed to develop a mobile application that automates CHO counting through user-taken photographs of food.A Diabetes Mellitus (DM) é uma patologia cuja principal característica é a hiperglicemia. Os carboidratos presentes nos alimentos são os nutrientes que têm o maior efeito sobre a glicemia, uma vez que, após a ingestão e absorção, são totalmente transformados em glicose. Desse modo, soluções que visem a contagem de carboidratos (CHC) presentes na refeição permitem maior flexibilidade e melhoram a qualidade de vida dos portadores dessa patologia, além de serem um auxiliar no tratamento. Assim, o presente trabalho teve como objetivo desenvolver um aplicativo para dispositivos móveis que automatiza a contagem de CHC por meio de fotografias tiradas do alimento pelo usuário

Correlação de diferentes períodos de jejum com níveis séricos de cortisol, glicemia plasmática, estado clínico e equilíbrio ácido-base em cães submetidos à anestesia geral inalatória

Este estudo correlacionou os tempos de jejum sólido pré-anestésico com alterações nos níveis de glicemia plasmática, cortisol sérico, estado clínico e equilíbrio ácido-base em cães submetidos a anestesia geral inalatória. Utilizaram-se oito animais, adultos, sem raça definida, distribuídos de acordo com o período de jejum sólido: Grupo 1 (12 horas), Grupo 2 (18 horas) e Grupo 3 (24 horas). Foi acompanhado o esvaziamento do conteúdo gástrico e em seguida, todos animais foram submetidos ao mesmo procedimento anestésico. Freqüência cardíaca e respiratória, temperatura retal, tempo de reperfusão capilar, grau de hidratação e pressão arterial não-invasiva foram mensurados previamente à administração de acepromazina, 10 minutos decorridos da mesma e a cada 10 minutos durante a manutenção anestésica, incluindo-se ETCO2; valores hemogasométricos (pH, PaCO2, PaO2, HCO3, CO2 total, SatO2, déficit de base), glicêmicos e de cortisol sérico foram avaliados previamente à MPA e a cada trinta minutos durante a manutenção anestésica. No período de recuperação anestésica, novas dosagens glicêmicas e de cortisol foram realizadas. Constataram-se poucas alterações cardiocirculatórias e respiratórias durante a anestesia, não havendo interferência dos diferentes tempos de jejum. Os animais com 12 horas de jejum pré-anestésico apresentaram glicemia mais elevada do que os demais grupos, no período de recuperação anestésica. As concentrações de cortisol não foram afetadas pelo jejum. O jejum pré-anestésico sólido, independente do tempo de duração, caracterizou um quadro de discreta alcalose respiratória. Todos os animais apresentaram-se em bom estado clínico nos três grupos. Recomenda-se jejum pré-anestésico sólido de 18 horas para garantir ausência completa de conteúdo alimentar sólido no estômago.This study correlated the solid preoperative fasting periods with plasma glycemia, serum cortisol, condition clinic and acid-base balance in dogs submitted to inhalation of general anaesthesia. Eight adults, animals were distributed into three groups in accordance with solid preoperative fasting: group 1 (12 hours), group 2 (18 hours) and group 3 (24 hours). Gastric emptying was observed and following this animals were submitted to the same anesthetic procedure. Heart and respiratory rate, rectal temperature, capillary refill time, percent hydration and noninvasive arterial pressure determined before and after Acepromazine and every 10 minutes during anaesthesia, included ETCO2; values blood gas (pH, PaCO2, PaO2, HCO3, TCO2, SaO2, BE), glycemic and serum cortisol were analyzed before MPA and each 30 minutes during anaesthesia. In recovery anaesthetic, glycemia and serum cortisol were repeated. During anaesthesia there were little cardiovascular and respiratory alteration not having interference of the preoperative fasting periods. Animals with 12 hours of the preoperative fasting showed a higher rise in glycemia levels than others groups in recovery anaesthetic. Serum cortisol wasn't influenced by fasting. Solid preoperative fasting independent of the duration describe a discreet respiratory alkalosis. All animals showed good clinical condition in all three groups. Solid preoperative fasting of the 18 hours is recommended to ensure a complete absence of the solid food contents in stomach

The pace of life for forest trees.

Tree growth and longevity trade-offs fundamentally shape the terrestrial carbon balance. Yet, we lack a unified understanding of how such trade-offs vary across the world's forests. By mapping life history traits for a wide range of species across the Americas, we reveal considerable variation in life expectancies from 10 centimeters in diameter (ranging from 1.3 to 3195 years) and show that the pace of life for trees can be accurately classified into four demographic functional types. We found emergent patterns in the strength of trade-offs between growth and longevity across a temperature gradient. Furthermore, we show that the diversity of life history traits varies predictably across forest biomes, giving rise to a positive relationship between trait diversity and productivity. Our pan-latitudinal assessment provides new insights into the demographic mechanisms that govern the carbon turnover rate across forest biomes

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

Sensitivity of South American tropical forests to an extreme climate anomaly

The tropical forest carbon sink is known to be drought sensitive, but it is unclear which forests are the most vulnerable to extreme events. Forests with hotter and drier baseline conditions may be protected by prior adaptation, or more vulnerable because they operate closer to physiological limits. Here we report that forests in drier South American climates experienced the greatest impacts of the 2015–2016 El Niño, indicating greater vulnerability to extreme temperatures and drought. The long-term, ground-measured tree-by-tree responses of 123 forest plots across tropical South America show that the biomass carbon sink ceased during the event with carbon balance becoming indistinguishable from zero (−0.02 ± 0.37 Mg C ha −1 per year). However, intact tropical South American forests overall were no more sensitive to the extreme 2015–2016 El Niño than to previous less intense events, remaining a key defence against climate change as long as they are protected

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

Correlação de diferentes períodos de jejum com níveis séricos de cortisol, glicemia plasmática, estado clínico e equilíbrio ácido-base em cães submetidos à anestesia geral inalatória

Este estudo correlacionou os tempos de jejum sólido pré-anestésico com alterações nos níveis de glicemia plasmática, cortisol sérico, estado clínico e equilíbrio ácido-base em cães submetidos a anestesia geral inalatória. Utilizaram-se oito animais, adultos, sem raça definida, distribuídos de acordo com o período de jejum sólido: Grupo 1 (12 horas), Grupo 2 (18 horas) e Grupo 3 (24 horas). Foi acompanhado o esvaziamento do conteúdo gástrico e em seguida, todos animais foram submetidos ao mesmo procedimento anestésico. Freqüência cardíaca e respiratória, temperatura retal, tempo de reperfusão capilar, grau de hidratação e pressão arterial não-invasiva foram mensurados previamente à administração de acepromazina, 10 minutos decorridos da mesma e a cada 10 minutos durante a manutenção anestésica, incluindo-se ETCO2; valores hemogasométricos (pH, PaCO2, PaO2, HCO3, CO2 total, SatO2, déficit de base), glicêmicos e de cortisol sérico foram avaliados previamente à MPA e a cada trinta minutos durante a manutenção anestésica. No período de recuperação anestésica, novas dosagens glicêmicas e de cortisol foram realizadas. Constataram-se poucas alterações cardiocirculatórias e respiratórias durante a anestesia, não havendo interferência dos diferentes tempos de jejum. Os animais com 12 horas de jejum pré-anestésico apresentaram glicemia mais elevada do que os demais grupos, no período de recuperação anestésica. As concentrações de cortisol não foram afetadas pelo jejum. O jejum pré-anestésico sólido, independente do tempo de duração, caracterizou um quadro de discreta alcalose respiratória. Todos os animais apresentaram-se em bom estado clínico nos três grupos. Recomenda-se jejum pré-anestésico sólido de 18 horas para garantir ausência completa de conteúdo alimentar sólido no estômago

Correlação de diferentes períodos de jejum com níveis séricos de cortisol, glicemia plasmática, estado clínico e equilíbrio ácido-base em case submetidos à anestesia geral inalatória

This study correlated the solid preoperative fasting periods with plasma glycemia, serum cortisol, condition clinic and acid-base balance in dogs submitted to inhalation of general anaesthesia. Eight adults, animals were distributed into three groups in accordance with solid preoperative fasting: group 1 (12 hours), group 2 (18 hours) and group 3 (24 hours). Gastric emptying was observed and following this animals were submitted to the same anesthetic procedure. Heart and respiratory rate, rectal temperature, capillary refill time, percent hydration and noninvasive arterial pressure determined before and after Acepromazine and every 10 minutes during anaesthesia, included ETCO 2; values blood gas (pH, PaCO 2, PaO 2, HCO 3, TCO 2, SaO 2, BE), glycemic and serum cortisol were analyzed before MPA and each 30 minutes during anaesthesia. In recovery anaesthetic, glycemia and serum cortisol were repeated. During anaesthesia there were little cardiovascular and respiratory alteration not having interference of the preoperative fasting periods. Animals with 12 hours of the preoperative fasting showed a higher rise in glycemia levels than others groups in recovery anaesthetic. Serum cortisol wasn't influenced by fasting. Solid preoperative fasting independent of the duration describe a discreet respiratory alkalosis. All animals showed good clinical condition in all three groups. Solid preoperative fasting of the 18 hours is recommended to ensure a complete absence of the solid food contents in stomach