Pesquisadores criam enzima artificial para detecção rápida de hormônio relacionado a doenças no suor
Pesquisadores da Oregon State University College of Engineering desenvolveram um sensor portátil que testa o cortisol na transpiração e fornece resultados em oito minutos, um avanço importante no monitoramento de um hormônio cujos níveis são...
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QKkqF3CQLIBFPmJktD0kRiU0Sl6gaOYa/i2Dyo7D4+hmI3Lo4jG7c7g9zhSHLguSJTdqBk0MS6jDX+xHitUmUC2/aUA3k/cKGK/EuYLnkHaJQmkwaOMH0FfFxvElp6JUegC/QIgB7rKmFDghA2GoWaiGOu0eYlG1nEHzMAreJgkgBhtj0dRfilbu6hrg+nPaeICsS3DoR+BO024mJq1PImR3haQxOiWrCkswoEFGGJfxCKGCn1UufKtQFBEtOy4UcIa/i4rsR2/h1Mw2BHp6spUp/zGwDetyghlGO71Gq0ckErxau8MLHoQUgG8YgRlp5mWLQgDIHLKYpi3bvsxNBoojATfruVLljIJgKPYnLVntMV/IlRMGpCtSG4HchmwMR7EPLLixgQTSXDym93j9BUDodIOhLWuVNGX4dxjYW0DOBUNgbWZxPB/aV5gERgpOJmAHR2leVl5iop+hAzFLg/i3FHwCEL2icnox6M0lkPnCbgUzCSYE5jlh2MxumsQqpjIIlXVWYlu2JEYlHtBWW64yvkJgjsj6wtFTU9SRoAeKhCgId0dDBwgexgGhDoOgi46eop6m+gHAJdmACuu2EOjUUuGGvbCBdZekA4L/wDqVnlyz5hgaDTxF6U6axB0APRtIQ2Q1/FS6d5YCYQlVCsmM1PAR4vz8Rur12uZw1GYBZnR8TwQL2VHB57SzElQIQJ5uFwko4b9eIBUZNpUOwzcG+SzPwSwL9sPMya047olvdDZAYqaF0xCmnaNCB4ZlgZ0uybkzin4rMMOLvQZQZO/GhFQWu/T5h9Aa6Ey7yQAB2J4nMT0hD6TAIVkmArooZ7HPSsRcsfB4lmLRDwzD6c9ykggrYgP/QCYgfHxMWYhKhByQ/ikAYYT3xMHNVAHUWTNbFK2VqcEpiQ0mPM8cIHFaZyeZSgReCHMHYs6Uimes1TWX5sWLT2EDGwsmnC3KVwvxKDK3M4GtTobE/CZzag2rnTlD+kT/mkTVQJ7Ny2TCKO+iqonF6lqFxFh4qfEeWjf9JnUOhx5hDdTh5mkxk/MKaZnZznGM1IgYh9O+EfvEruueUmJgNn7Rk+A/EeYU/KlDwW+pTZBXyhGRlf1CtjWd9xkugdp+xD+LxFFdAQFG8XgiBU2zJJVULNTwSmZ4OcYOQt83mWfCKvMIAgFXLP+Ypz5cDESkeOUCjYQIGsgd+8A3Q1iopSEsLj5SoFrikbxNERHe57z2h5RKqC4RIIymq4iWITeUEJTEN5KBZlE+7bidwknE8gNcE0yRLOZqC3aisTJbF3qFuLrcQEK5GH1LIjxumDOgeemYdQ+vf0KXjcVp5lDfdJaoY8RCtNjuRMQ6dlsJOqA7uDTvI5ju/iIJAGRxxEwBUudgQAan7EP42KCpUaryJ5nVwnAHHATQ/oZJ8jmkaGTUri5SzBD2yicJ4a1Eh7akHptEZgCxMdTfFHaGPaWkvx+KJR84q2fFlTpdDjJGaySHdjFyQI5y5vHv7ARJu4fPtBUtYYJNwRWoEVKJkMTDt7Ezgkf5YNmCtnKO/DMfXLjNSs5ZlsOjqhyqpZ+UBMVSIL7i1McRO6Nm7I6HyH7mBghg+xs6FwUB8xnSmg3s/uYF4f1Mr9U/uAQ4bjVriuIEDYk5e5SkWBlre5mfsQ1/G8ylo1T7jGOqnFRjrDXmYMeifMUKHUCcGbJQO71A2homCagz3ZtvgmQoHncKCo0QGsLnaC+5Mi5mcV0B/0hZmjzGAF+h5QGpjBs9wPorB4VmW+spYz3ia/inFQFHSsCZQGz3yPZLbkJ3qsA1GaEIMI/BTuOWo+ZnSg752gF67RX7S259eSi7uH2Fn0IboHeF2aGU/6u4gV4f1Mx8P7m4lVwhuqwSmSZlM63RhMaQn7H8fE9u5gdjoejGMWMOR6QDiM/MQUbUo7SUF2ppC4sZ7ZwxMqbDH04phYWOWGhnKpYxmuIXczggAklLIUJnsEIa+jIOoTxBKrO4ACvs7/XQ/pDT3F+qI0vKqZjbAH4l+Q95fSvYo3bu0QXbFfSV1ROLIsCvvz0fsfx68uYynF9R1HoARYTEe+kDpG/+CHIbRbRfzta8JjIAuqbymkEA+DoXlwgvmUDDumoO2gGm7+JQvY6fpcn4rUO7XYdo8q2WH1jWeR5OZUYZwnhFw6M5NS6KiH6TNok7VuAhFgC+YdButQBH/1wru32t/roczl7n65HXxSw9z+kQG8xgqgnBAzKNqf7ln3BAs8QhJufsfx+wYhALz3nY/HUxgXCjE1OTRsfU8XvGYBwZblCGTXZKBV3a3A7SlPUwXav3GAhgbM3NKcxHU7e0BVKaeIILCmvpSsI8JPeaRc0jYNsj2GI4DK+QH2agFgSLakFtjzKBjXsivN76DVwxZuUGmq8y93d9nmVt0Ln+8eNmqmz7qOQGaedUgVe6FyxvXj/AJJY8R/cWcOI8IQ3/HCiTQGSA1Uf+dMuDuHV8dHWpyXBgIoEC4AupiEBmjMZQzD/AF9VQlDe5sIykoeLyweFW5Esx3bfpaqq+HEbFZRjeTioikXeyYzww9QqjxF5zNnAKMb1Khwd5SbuPeDJwTuJ0mA8faeR0EaueYbVIqIEukrCHYIt38BiA+F9iWDXREsypdd4I3zk5kVYS1Q0XDX8e9VfeeWYqWGMcHvsnEALAw5nESVKldMhk1LG3JZS86++IYImT0TopD6WPQhx0BuoEADyriXC/qIcICjeCNwCsE8/a3dHUOfU36zRFqPHpI6hBgyNfxwUVZFTbpCWIVUMg+MPRAAxBkxkjUL3fXMU4uCNMtu4/ba7zzUocCAcl4l9pG5cmQk4Bm15QyMwAGDR9vdC+hFrc3ejsTWPFi8kPIlvZ+IayPxNrvZqpbVzDX8dyVBYRO0UsX48RoXkd473DNVv3Pn4iMqp8TNJ0YAsqCJcRLc4mPpp7dC5k3LOpDQRKrcFIOJQ36VG9CoACaVuDo7kLFVrugsADUPtM3dPiZrUtnOaeCXpLdmIa4Ec6wYOmihEozeK1JTdDX8kBSWdo/aOZwwnQY66Nwnr5lN1+Idg9zSW9w0r+4BsepfkPmD4ekH/ALceGFOFLtPz0ZmknqH9VEe2e5rn7n/dRPc1Z/t0ZQ9SOecVXaABWh9xl9Fk8meRPJlzeE5RrvBpnOaS83hQC2P+tS/H8TFX/WItGBtE1/LyVQC17GNDQX2SFcEfoer9bac+nabdGnSkvqsQlpl4lAurhK2x4/zdE0iveZ7D2iirA6K/MrimesRis9WcfRzD6F4wSveC1tNS+pdC38EHbRADEQIf5SyKSy6lw+lLJkU5gu13I/JnzHMJwK4vilO8+Zx9JC5rAX9kN5uM186DIHFfK8Rom+7A7sPt3i5ZL/xXmLGALV7QzVQaCbDrUNfapWibC/E3fxTmR8zsAjF+R0Rv6MOaWwSby7yzJQAMF8Qx2Ie/u8QS5tqI1ZK4Ib+89O8P5B7voOHPdHNgIKXkPaGqmYteMcxAg12bgHtuAbyPr/AriMY7h3lXo7pXFxeqsVNl1j7w30zD7VMkYDy4I23xHI0UrqjW6OYfYOSj7hLzVCHXynmtNhLyFKB1KnV2Cy5bVphofMG9jxUPLdxietIy2IS8u90/evxMINgCM3x3xcbqKwIaj3i9iubVAfWjiPaL5S5hFaJlEKpv/wACSCTapGmKD1Z7oIcGrcB5igCss79ST6Ua4KEEp9fEBYiFOSGIa2OT7BvTBl0M4k9hCFiSrKcXK3Borwmlg27PPeGAZI3hYqzNvrcTwtHBcB1tPo9yi5G+vuYNFrNm/czeoDZDv939K1KVaxBZQC0P00Btljx0adujOAH+0dlwI0jLEAd2VX0E5/VwcIkszrbKh4qVccz4/wAEmMlyvUVCprdzPV03OegUAZZtzUuhywz3xp0psC4KmFtN/ZmPG/8AFHX7AjNARZFLb+3mEB4QVXmGXCrFkxTgXykqzgN9m2YwumMD4l8qk1EVVIrnPzKGiUNwVkFx9Kl2wt2LoAAGMiUGWhaWbYx23uEZshqOtwCqAcspV0zbU4+ICpkj5Zx5lIi/L6g60/OO8E9sSmYWrkwxQAddvGAAB6P5delq09QGLkcEJO9oh36I67dvc5Ho3d3RBz0P+RbXiGufmADdNlY9OiIx8pcXrDCH6zDKijbkwALTZGoaLLQlsS/MsrhvZsNfX/03mVS4KJoRd5ITj7yZzkvDAoHnfhIgVgnp59xkB1/F97l5trPwRYu1skoR4f8AfMth6X+4Es8A4+YSAundKCXvwTlK6PlwGkule4DiIAGppcEPhIDl+IQxnAbjtrKQ/l1y/wDYibLSwEYtfu0vM244IAbVMbRxxhyd4mwgN3LDdDMUJsoz8JRqn5EqAmE8E+HKsuFRkKUgdxNYcp5ZfmKmC39oM7qpnyRIKKo5YGCpSVjtNrfsOGTQFlA1HLQTOEMn039luycajirzxDg8SqJ+UQC7Q+5WdSvEFKQTkrEWQuC1ABj9Qsbm6dG2JBKVmyuIBDwfqvRAoNy8MTshX03xLOlnSyWQlkpdcyz7ghAUjApB8GoESDsSaAmmBC3LCsy/vUVqAhF8Ep7wErpc/uELrTQscbt60hAB6G+0Yzlk12wElPIHmLCMsfslUUFWJp9hAZQnivSZ5IRZOxjeUyh6huJF5U04xDuVr6Gcyj7TEgDKJV4oAl/jn/V8/VLbv4lTesv0ntk+xfHEZa3czIhsIG0twsk37y5GrVeNMfNyi1OSKD2naIDACw5xW+9whXzk1KJQq+590BQRQkl7B9OnT0YR0y2ZPrHmWIL2obfMebMAqmByAB5+yRMB1BVmcyEoZeb/AJ0FGq1meYfEvkEJTkvxQQ7h+3eDxTjtDwdbJNuCN2m0RYfU6jTPHebU1qfsgLkC/wCnLHGGViEWqu3uMK3y0+TAA7LBj5g5p0kFXmK3NXa9y4F8IBoC0CqoXUqG8w5lfYJEH3LwRu1Ons+UU6LgWwm4mgYlAKDiZSiwtYgWFoh2m4p7Me5jcGFVceMQ+NgvP5S6vhPlRYyl/aVvvHB++zDLwMFmE8i/UuaUj/EqjA5jnRMa36g4zF4b8xqaBdwqlolk7AnGs4MeYPNT08O0NSgJR9lka+7TZATuvv8ARCiuKUnM/wClw0uSHyFaO0Qk2o5S+XmF3awZlyNPDKXuN3UGQhMDEuJb7l4g/Qwa6CUPbj59oNCRoIpImx1FEam1n/xA9JT/AKFQeB/bDCAVs7ynJ7gmkaa8z0RLSvezAru4yx3jmJ2TXsTxA839Nw79VYZ5v/tQp1gUWsEzA2gJu4EfiNCAgcNYTiUKbO0FQpgExcoOrnB7nmUXIQyodLgDDZB+pLirYJIKR0a+KVUbNCmCxC16axMBmjkjIwtgwJgHBwqJ0uWEcUSq+cqg/aAH9RGjtADA2wZYw8/7PKHd7hrP20zMdXj/AJCUWSrW/fw6cdGYRDQEJra1XMa5/qHWh7MMp1+E2QZh/UOQv3Frl5qe5hjGemYnd9H7Kcbox7Jqu9oX0xbrG5mk0+yh/g4HMzMzMzczMzEK3Qje9j4Idt//AOv04phMdb631DxicKvEQ6cuJSzXTlDnFdGH3W/EIgHvEFCDmoJbvpUaVAACh6hNhm+mZieIwW6zDbHaXcEqcEA1R0UDKTZimM1eGMN0Kg1uabgfGqCtIvaStY1HxMUKMGkb+Nh+8BatB31GHksMHnOeIuJaGA1piFyrpL6bMLIWQE5XSWWB9eu5vmGScSrsdMbaW1lWHQelzkmNmIGc9P8AtztP90OiUheO8re2MOf4IO4w/wBzWtndRXpWnSAVoUOgLYYEMCayuIB04m/19WSWkCLYLp5pEdB5RFEsu8S/H78TGqlfdfiJLNbc/lEf+zWSJfoJyNkxlYRs8b/tKSywXf3ig/JPpE64W2/OGA6sZvxBqxAcuIgyL4hMp0o+Ei6UrlE6EvPNBo9mrZz78oJ2hqA10464yu6MAoWLlGLdwx91s0YvcpWgRmOyAeoNVBMvZHls3kgAweEEhrvAfHiH6OT2RQAHMHgNOr4g0tL3Sv4Oa3VlIPjoEF9/2HmHQJZKTUvR2PnMDH2wHOqg2Tb6n9H0q8gUNqKGYo8IDzuEPih8z/d8lYleIVR4MCh9jKzmGvvCcKkxiSpwLnPKbPzFkHyyq0UywC6BqLJSGplwQr9tyOYAGvPdWoGGuKjzMVAXunHXmMD86NEVS5XifnYU95XEKfQTOQppcR9epnQF4bBUlDj/AOwKAdgROKjuVV8Ng1dLopAMABqDH8FMxO1X3qVl6POmYlIu0QO+Cjkwsb7lEg5dxRRbxzClXTcj6T49HKUh8PSsQ/kLT/vtGMrsFhDmZ4MXjGIapVPZnPxBAW08IRqqhHV2vqaQSbRklMFCoarYapPOWA/njNH0OuYijIgkW/MvX+MdJmjThgGSzlmGBR/KvcK+BfMSJMC1JuVqeZZf+o3oMNwzWErhDpYK27MVYWPg1MpOlHdC+Y7LtqJbhTbdzvAgLGH00dMVD+fsfJLnzPmfMxL9TExL9T8THifP03moPxNM4l7l9FMy8alyl1Bh9reUV/zHI8s1jzKto7rNe/iXIfyzAsmtPShXNOz7o+ZVZ0m4alxHC7hSO4IeGFNjK4tx6iRwvmHValy5joIYuXLJfS5eZfjptLOlyy6lm4JBOtywaYYaqX0G/quOoBvM8hrvn/vZu7F7TZ/Zn/rZ/wCtn/oYf/Qz81W0/wDUwp/3Y/8A0MWFlNmPpGBoGkc0PXM2CnSTJI6G4lwDcHMJE2VN2tATATc0g0Q23wEEKq8xOrKofbquWcTjM4qG24RB2EK8JAlZmO8IdczhzxAsJcNYTZ4Ar2UN2qCZcyqfMskb4YXPk0pIByy2EcDGhY8LKlNwuDUL5IB+TalAyyhxL7XJMvmVquxYoFug7wdoE0S2gw6OtCwryAstHlSJHBygKRu3x6ixNxfMNlrVsylU7mUBDuTCLdP2Kd3c6nKI3/nHFaoad5ZBGYNf7mmdQcqR87RKMWX2uB8YdBrz9DFAKDSIM5l8ZCnI6Bkpp2O6MEVzCuJk3rRwQkd7hPGaugBM3FPMJyLMIU8S+ggfyL23ECQKYlLRuokHxOHFM2UerwgqBVau+5bDZGDDQgL8VEBPtvllwsVmUJkwY89yUajm2eyKBktqbISueDXeKGWTuRrhrtK7XMbOy1RIaRbdK9y3EXgr1CpOq0HQwC5kt7gWJYZy7vMBo8Izv3DapQF+GcQaZG+0qsCaDI6BO6BRfYbvU0buKmVoWFxX6sBJqdcoG418GeUmik08zGyz/o6V6YVSUkPzFj6gFIZ1Q0orDEtA26GFesshtfeHS3HvJBuLFqXLgmHUDK2o2IJm4t1KjANq+ZcRVs3X8laHTBXtCoBWEUKDQjBPu6XLYko75iU+BLgQsLKFP0piJhOapjsQksxYayrbDEgsqykrZ2Bd1Dy/b9IfGNCDymVHNZn4I7L8za8CsXvLoYnRBmoACziopwLXFErMYhDrFQ+YttxLEZlslSkWcqFB8pYLUW2FwxZ4I6Hab9JU2sDX2EsqYFw1yxIs08twzJ3gSDxgOKMBXe0hPSImI07owA4NoeSYCb0Ze4AorD2uH+JNvWX62Oif1Q3P95v9dIw6HPTy9QhhHc5ThHc2YTlDZOY/a5huHUcTnB/rP2YbPXT/2Q==)
Resumo gráfico. Crédito: ACS Applied Materials & Interfaces (2023). DOI: 10.1021/acsami.2c21980
Pesquisadores da Oregon State University College of Engineering desenvolveram um sensor portátil que testa o cortisol na transpiração e fornece resultados em oito minutos, um avanço importante no monitoramento de um hormônio cujos níveis são um marcador para muitas doenças, incluindo vários tipos de câncer.
Os resultados foram publicados na revista ACS Applied Materials & Interfaces . O material e o mecanismo de detecção do novo dispositivo podem ser facilmente projetados para detectar outros hormônios específicos, dizem os pesquisadores - por exemplo, a progesterona, um marcador importante para a saúde reprodutiva das mulheres e os resultados da gravidez.
"Inspiramo-nos nas enzimas naturais usadas em medidores de glicose no sangue vendidos em farmácias", disse Larry Cheng, professor associado de engenharia elétrica e ciência da computação. "Nos medidores de glicose, enzimas específicas são aplicadas a um eletrodo, onde podem capturar e reagir com moléculas de glicose para gerar um sinal elétrico para detecção. No entanto, encontrar enzimas naturais para detecção de cortisol não é simples, e enzimas naturais são propensas a instabilidade e têm uma vida útil curta."
Enzimas são substâncias produzidas por organismos vivos que atuam como catalisadores de reações bioquímicas. Para superar os desafios impostos pelas enzimas naturais , Cheng e Sanjida Yeasmin, uma estudante de doutorado que liderou o estudo, criaram uma enzima artificial robusta e estável, capaz de detectar cortisol de forma sensível e seletiva.
O cortisol é um hormônio produzido nas glândulas supra-renais. Os hormônios são os mensageiros químicos do corpo, e o cortisol é um dos hormônios esteroides , juntamente com andrógenos, estrogênios e progestágenos. Os hormônios esteróides desempenham um papel em vários processos fisiológicos, incluindo o desenvolvimento sexual.
Entre suas funções, o cortisol auxilia no combate a infecções, na manutenção da pressão arterial e na regulação do açúcar no sangue e no metabolismo, sendo apelidado de "hormônio do estresse" porque é liberado quando as pessoas se encontram sob pressão.
O cortisol é benéfico para lidar com o estresse a curto prazo, mas períodos prolongados de altos níveis de cortisol podem ter efeitos prejudiciais no corpo, como aumento do risco de ansiedade, depressão e doenças cardíacas.
“Em um indivíduo saudável, os níveis de cortisol sobem e descem dependendo do horário ao longo do dia”, disse Yeasmin. "Eles geralmente são mais altos pela manhã e mais baixos à noite - isso significa que, se você deseja monitorar o cortisol com eficácia, é necessária uma medição rápida e frequente".
Os níveis de cortisol são mais comumente detectados por meio de exames de sangue ou urina em uma clínica, "que requer equipamento de laboratório e pessoal treinado e leva mais de 30 minutos para completar a medição", disse ela. "Além disso, os pacientes geralmente precisam esperar mais de dois dias para receber os resultados".
Para resolver esses problemas, Yeasmin e Cheng criaram um "sensor de imitação de enzima" que evita os elementos mais caros e demorados do teste de cortisol convencional.
"Este sensor é livre de enzimas naturais, sem etiquetas e sem sondas de sinalização redox", disse Yeasmin. "É um sensor robusto e integrado que pode ser aplicado para aplicações no local de atendimento - como ao lado da cama de alguém, fora de um ambiente de laboratório - e até mesmo para aplicações vestíveis. Nosso novo sensor é mais sensível e seletivo do que a maioria dos sensores relatados e, portanto, mais confiável para o monitoramento do hormônio do estresse."
A enzima artificial é um polímero especial com pequenos espaços moldados para caber apenas moléculas de cortisol. Esses espaços são cercados por catalisadores que fazem o cortisol reagir, produzindo sinais elétricos . Medindo os sinais, pode-se determinar a quantidade de cortisol presente, uma importante ferramenta diagnóstica.
Níveis de cortisol muito altos ou baixos podem indicar um distúrbio adrenal, como a doença de Addison, caracterizada por dor abdominal, períodos menstruais anormais, desidratação, náusea e irritabilidade, ou síndrome de Cushing, que pode causar ganho de peso, alterações de humor, fraqueza muscular e diabetes .
"O sensor pode detectar os níveis de cortisol no suor em minutos, mesmo quando eles são tipicamente 10.000 vezes menos concentrados do que os níveis de glicose no sangue", disse Cheng. “A enzima artificial usada nesta tecnologia abre novos caminhos para o desenvolvimento de futuros sensores vestíveis para monitoramento da saúde”.
Mais informações: Sanjida Yeasmin et al, Enzyme-Mimics for Sensitive and Selective Steroid Metabolite Detection, ACS Applied Materials & Interfaces (2023). DOI: 10.1021/acsami.2c21980
Informações do jornal: ACS Applied Materials and Interfaces