Amperometric enzyme-based biosensors: refined bioanalytical tools for in vivo biomonitoring

In de medische zorg wint gepersonaliseerde gezondheidszorg steeds meer terrein. Deze nieuwe benadering is gericht op de individuele patiënt en streeft naar persoonlijke gezondheidsplanning, mogelijk gemaakt door persoonsgerichte biomedische hulpmiddelen. Uiteindelijk zullen nieuwe biomedische hulpmiddelen, mogelijk gemaakt door vooruitgang in wetenschap en technologie, het vermogen om gezondheidsrisico's te voorspellen vergroten door diagnoses te verbeteren en de implementatie van individuele therapeutische regimes te faciliteren. Door middel van bioanalytische hulpmiddelen kunnen (bio)chemische stoffen (biomarker(s)) accuraat worden gemonitord, waardoor de te volgen behandeling inzichtelijker wordt. In het geval van diabetes, een wereldwijde doodsoorzaak waarvan de prevalentie naar verwachting zal toenemen, is de belangrijkste biomarker glucose. Helaas zijn de bestaande medische instrumenten voor glucose (bio)monitoring nog lang niet in staat om diabetes "echt" persoonsgericht te behandelen. Ontwikkeling van amperometische biosensoren op basis van enzymen kunnen hierin mogelijk uitkomst bieden. In mijn proefschrift heb ik het werkingsmechanisme van amperometrische enzymgebaseerde biosensoren diep bestudeerd. Op basis van bestaande kennis ontwikkelde en kenmerkte ik (in vitro en in vivo) geraffineerde amperometrische biosensoren op basis van enzymen voor continue glucosemonitoring. Bovendien koppelde ik ze aan draadloze technologie om therapietrouw te stimuleren. Daarnaast heb ik een multiplex biosensor ontwikkeld, die een simultane monitoring van glucose en andere relevante biomarkers mogelijk maakt. Met dit proefschrift probeer ik bij te dragen aan de bestaande kennis van biosensortechnologie. Ook heb ik geprobeerd de rol van biosensoren als een toekomstig hulpmiddel voor gepersonaliseerde biomonitoring te benadrukken, wat hopelijk helpt om gepersonaliseerde gezondheidszorg een stap dichterbij te laten komen

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

A social and ecological assessment of tropical land uses at multiple scales: the Sustainable Amazon Network

Science has a critical role to play in guiding more sustainable development trajectories. Here, we present the Sustainable Amazon Network (Rede Amazonia Sustentavel, RAS): a multidisciplinary research initiative involving more than 30 partner organizations working to assess both social and ecological dimensions of land-use sustainability in eastern Brazilian Amazonia. The research approach adopted by RAS offers three advantages for addressing land-use sustainability problems: (i) the collection of synchronized and co-located ecological and socioeconomic data across broad gradients of past and present human use; (ii) a nested sampling design to aid comparison of ecological and socioeconomic conditions associated with different land uses across local, landscape and regional scales; and (iii) a strong engagement with a wide variety of actors and non-research institutions. Here, we elaborate on these key features, and identify the ways in which RAS can help in highlighting those problems in most urgent need of attention, and in guiding improvements in land-use sustainability in Amazonia and elsewhere in the tropics. We also discuss some of the practical lessons, limitations and realities faced during the development of the RAS initiative so far.Keywords: Social–ecological systems, Tropical forests, Land use, Interdisciplinary research, Sustainability, Trade-off

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

In vivo continuous and simultaneous monitoring of brain energy substrates with a multiplex amperometric enzyme-based biosensor device

Enzyme-based amperometric biosensors are widely used for monitoring key biomarkers. In experimental neuroscience there is a growing interest in in vivo continuous and simultaneous monitoring of metabolism-related biomarkers, like glucose, lactate and pyruvate. The use of multiplex biosensors will provide better understanding of brain energy metabolism and its role in neuropathologies such as diabetes, ischemia, and epilepsy. We have developed and characterized an implantable multiplex microbiosensor device (MBD) for simultaneous and continuous in vivo monitoring of glucose, lactate, and pyruvate. First, we developed and characterized amperometric microbiosensors for monitoring lactate and pyruvate. In vitro evaluation allowed us to choose the most suitable biosensors for incorporation into the MBD, along with glucose and background biosensors. Fully assembled MBDs were characterized in vitro. The calculated performance parameters (LOD, LR, LRS, IMAX and appKM) showed that the multiplex MBD was highly selective and sensitive (LRS≥100nA/mM) for each analyte and within an adequate range for in vivo application. Finally, MBDs were implanted in the mPFC of anesthetized adult male Wistar rats for in vivo evaluation. Following an equilibration period, baseline brain levels of glucose (1.3±0.2mM), lactate (1.5±0.4mM) and pyruvate (0.3±0.1mM) were established. Subsequently, the MBDs recorded the responses of the animals when submitted to hyperglycemic (40% glucose i.v.) and hypoglycemic (5U/kg insulin i.v.) challenges. Afterwards, MBDs were recalibrated to convert electrochemical readings into accurate substrate concentrations and to assess biofouling. The presented MBD can monitor simultaneously multiple biomarkers in vivo

Perfil epidemiológico de hanseníase no sertão Pernambucano, Brasil / Epidemiological profile of hanseníase in sertão Pernambucano, Brazil

A Hanseníase é uma doença infecciosa crônica causada por Mycobacterium leprae, considerada um grave problema saúde pública mundial. O presente trabalho tem como objetivo traçar um perfil epidemiológico da Hanseníase no sertão pernambucano, tomando por base os dados eletrônicos do SINAN e DATASUS (ambos ligados ao Ministério da Saúde). A partir dessas fontes, realizou-se um estudo de série histórica observacional do tipo transversal dos casos notificados de Hanseníase entre os anos de 2006 a 2017. De acordo com os dados, observa-se que esse agravo apresentou um decréscimo no número de novos casos, na medida em que se constatava 43.642 casos no ano de 2006 contra 26.875 novos casos em 2017. Essa realidade, embora evidencie uma notável redução no número de novos casos de hanseníase, evoca a responsabilidade dos órgãos públicos de saúde no que tange à manutenção do controle desse agravo, assim como a criação de novas medidas que busquem a prevenção e a erradicação desse enfermo no território nacional.

A social and ecological assessment of tropical land uses at multiple scales:the Sustainable Amazon Network

Science has a critical role to play in guiding more sustainable development trajectories. Here, we present the Sustainable Amazon Network (Rede Amazonia Sustentavel, RAS): a multidisciplinary research initiative involving more than 30 partner organizations working to assess both social and ecological dimensions of land-use sustainability in eastern Brazilian Amazonia. The research approach adopted by RAS offers three advantages for addressing land-use sustainability problems: (i) the collection of synchronized and co-located ecological and socioeconomic data across broad gradients of past and present human use; (ii) a nested sampling design to aid comparison of ecological and socioeconomic conditions associated with different land uses across local, landscape and regional scales; and (iii) a strong engagement with a wide variety of actors and non-research institutions. Here, we elaborate on these key features, and identify the ways in which RAS can help in highlighting those problems in most urgent need of attention, and in guiding improvements in land-use sustainability in Amazonia and elsewhere in the tropics. We also discuss some of the practical lessons, limitations and realities faced during the development of the RAS initiative so far