Os primeiros microrobôs capazes de navegar dentro de grupos de células e estimular células individuais
Um grupo de pesquisadores da Universidade Técnica de Munique (TUM) desenvolveu o primeiro microrobô ('microbot') do mundo capaz de navegar dentro de grupos de células e estimular células individuais. Berna Özkale Edelmann, professora de Nano e...
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V0o6lD4JvGMWM6N1ekVe1vDjUMXW7fTMY4XK2sUUuFGwdSO1rTkfhAQ6dObEDYBhDQbOYKs8Bh3rQF01iaEpBHff7EVI2LHSOUZJZHozDURKXXWvCVAnK1Bssb6NYli3mtXpApVoCghPuQLpeLNAK0l1QFsdxiA+CoHQ39Z6/3/AOE6R0HCFW90YcOmmkRsR5EgBfj1DRaMp1gt0ClVNFE16ynyFP2rVPMcoDq4cM+kSZKaaBV/G0aA4NNQbrwjWxgDFkZ8/wCD5jiB0LM0Io+IU8Y2lErhSIK5syRjFcDAbC8vHETEVr0MurF1LxelxShcssynJKyYqlEFArOhFQtKkBq7McDVWp4ERCIOa6QDgY9aEuyHB83igWoEYhj3VUhsMY0oZ0g6R6QPuMHsQbOLN57oFihlbAm3zrGZsy3Kp/nrPW/+OfE6ILdDDR3hAO8qrNEADXhKn6CUP4JQc51ahEVhj1QEBSORcamiwJTIwIzfyrhytFjRHMPXYNgbrl9IUVtwkyBnoA8IGgKJ0sP1AxFlpnk1iIcFxRaMy9MBSWgrVsbrBgg3LW5Q4JfFI1t4y/sjAxToasIKoyNUCNXwCcig31vESkeHs9f7/wDNizqGxo1lcz4uydNHgwbLP4fiuJ8vwQqw7aqIKLsuusaLRRQ7ihTQ7De5ccNvRlKANjFmjTtLk8Q8LwuOCHIU4lJeYa945t1webAbBRdauXSs+HEtbW1gaVdneATxZqgd8S5muKDWojtABMIlsGiqy67R42i6FEIujkY1h900RD5wDybXoN3yd4JiUVzQAdAO5hPCBU9R/wCPfI6IaEFZTlS/LaCKQ16aNs7eHnDRCJ6lzbyqvCpUuwohics7RTthBSoFRwqVzS7zOCxLSZwrgFPWETsdeHWhlso9YPO8tqxaS+nSMLpoBS0CdEUTrCgaVECYNBvtTmmXaRBZilAXp4amsI+edEdUg7wRz4aYC2sa2WOVzHFYAQDBahpe3WVmASqsZ6j3/wCHvuV3w7pS8Yc6cPT8k9HyS2ooWOl1mqhEuF87aev9fw/FcT5fhM6GxnO43mK0l4IHQ0PHylGKlmL1t9x69JRxHx1qAXWtR7hvSAKu4Gr3HMqM3C6WoXrhb2jRKlI7cKSrBG6eSCUr0iCYVuPniMfavQAyI7f+TBqxwx0O1j3lnEGqhsUYI98rXOlCHS8HfVxo0V8x1oDV7VxEgz7K2wKMoQzpfSHzcgBBrvnqP/Htp8Um3DuHpn1lUTq0axirL7OjyPRgIGSU07gxSRF1TXjLCh1CxTo1HwYsjSdSMbnRymjGFgWuhCY1X/YGFpMNjaHAWXnBvBfr0haJb1WAsW45DJFoAFr3SulFhiHBi1gLvMqPd3Qyc9L6wG16oaX4ad5iNcWtMVhANI8mSpR4tiL4pEq/DvqwuGhrNcz1XvfzPFXV0NGWVNFmjN0/ZlH8PqPtFpLWIbN9YwoC11L3usHMQbDVcwxl6Aa8J0YjsCKl0faEIUSitDmnA+MTE5+uJULNAuu0Msre4aTXS1O8Ywp1xQEK6gA7Wu0rCnVcdg59gHdgy6NFFQVyW6L2tludgmeKGKpGlmMy7fAtfKep/wCwqqvgeLhy2jFXQ2MtQjuwr60jwJpzznZA1d2L2ZqMzbdtK/8Aj/A6IaHamIZacosLc4pjMJIY0Z4vy8I26UGqNFKFd5E+BVgQOAiBZGWC/DXuI8YZQbrRCnX/ABgFtcKS22ShOjDzXCOgSE0RWTUlEpirec3rFsUPAIyXkwhSEawEEBbJtvDA/wBGabPTvI3XBLJWDryXVVdo7vGytF2typXmnyur+z6j7T5fg7bSpa1pFvlr5wyBQxwYqCWactnHMpBqlH7qKsMXsiHdcleqsGcLMA4qXV7k2+bXxiiCtq5IMo4XEpbIiU1K86VNexJlMms9OJusQdp6WemIqu+IAxaC3dJWdNY/XCYlpakRaM0y1tGXRaW9TSKfNSwTgseVrpPVf+Oeg9iGh2hYiYMDTGo8aQEhRgA2t05aovmW3diDUbbQI2KrU+/gxDSICTsTlNaG3fcBGiM/uyjhM6OKii8ZImAWgN1A3AM7TTo6RBEQSOoWWqc+jDzcw2QBGkKxshrDnCQNh63pimHqV0wFym1OV04YBGzMR4XpZmfN6v7PrftPn+DtzeBoKnZE0Y0gpqiFYGjRqjD4uDpDSY6wais8LWIMVNUlAp0BerBXOKG2RoyHQ75ghDMwy4FXpdsAwRQK8HYKaFOZwYVzu1mxF1FFHRIGSjk8q30ZgHSCcw5K14xuRs59RQUmd6V5Mptuf/HPgdENCLUduzW1d8/olPtAgOXXW8+8pVo7oGSvEOgh0ImMcpPZ3QYB3SpdEg9x3kHQEtABbVkKNhW8tBwKsyNXoDPeditBuKpHpDGPAGPBt36d0AII5EdZiJ1EtKo40HfRBawrWBRctN3rsJZShyjTStDwJRUG6x2xz739n1v2ny/Dsco8v73Q8ZXOfhpZuNUfKi6BilijwRqG6NiVt23laFuXK9WU3hwKuG8ruRl81rQRDAHCDm0t5SEF6dgQv35clDLbKT8xHQWMMXgCX3hv3n/sDtWiNkaQFG0C0U7YunrGyKizHO4dekojewF5Q+NwGIaAKBHHFNHn/jnwOicL979iepIryGPO4AAAYA2lQluA5djzhDW0TgFWmH36wsQcmBvK8Gdq7DhCGWlliaNmOmspw7BjjJx2pcWV7LfJ72JjgyNq00HfUBnQ++G1N1uXm/5BbC0a07tjwnqff/s+o+0suYGoro7p8Vt0z6wcdbCiEiUBawm2zXA2LZC9EZkj4KtB6mTTHPYAC5KOTJfPdHoDtgNbB3QITqe0drGitUq+80fGCgDJterevR4T5P8AydPx3/MEaaybTuNIa77/AMc+B0Q0O3DcudfYeGvl2IOp2AgCOoxg4FsNsnv6vwUyj0TZu+XqkEuhQGx/dbev+0+D4dq7xOjf56efECjEQSkvtIEEArwf+wABoFdtkC3HMaEshsZ5Fyvn+Hqv/HvB2SsbL8oIdDT4tRL1nw/6wJAbzo+sNtZtW1XVcyvlfeV8L7yvhfeV8X7wuJUBtnnK+B95XwPvK+B94pmILcIbGZXyvvK+V95XyvvEaqxZW0DOrHBsHaFVQ8/7NV4sIiuYcuOGe8p8ez/KpuEnaGfB4dpPf8k97yTrIJCq24v3858q7dKFKcKqO73/AIE9SkIGWpFWWtUMAOeS3j/yH6VQbC3OjbnTiH/LYbn8x3zqGgDeCjEmEtqzl6He/wBvBsV8S/3y7zj+gw6WrNnV42eLpCYAKA2P+Tchqg39vVvxrzBEEbH+RlqnNbE6d5ry90Cv7Y92EbjCsECWv7U16j/M7MC1dAljhVZqejxz4un/ACmYCFImEiKFaTfy/bw2z/Gga6F2V2Hl6GeISktDQP7qtEKDVvcaO5N4IYFibn8r1eHuC6eLHdcCijT/AJdds0n7745TbPz+5ueO/wDEbdKNoc9A/wAN5bYl1Aar+pcl4Q9g7zME2I8CNezGCVUddY/JLKSxjcLBZ3tnxGu5P5D3LI7BFoD8z9YZ71/5pm1e/bCf5uQ1baGnTkW3lt/ADC5DIVgDqsYQUccmx0j1bf6hWb7Rkq2zWijgIxFibQ0KmI89fyrK8VDVdEs8Y5WsL1OR6n8eJ5FdyfUHkP8Az0lCzcG50n0cw6CrcMLVHP5FCOoaAN4FcBMazecp5He/1bWbGJ1pfcUUWWJd03vRhp+Wa8M8WuPBk6n8SwgCdCUHql1ewUef/PQafOjqo0BmS2HD1McSwb1YEUIA6a+caOToyG0s6J84eCuC2b9S8CbngNu815cbQD/afdT7afbT7afaT7SfaT7SfaT7afbT7afZT7afdT76fdT7afbRrfely5h8weYhQCmpcCLMeIsrkrnpPuJ91Pup91PuppysLk8j4MBQu3dHU7tzok+4n3U+6n3U6fzmXR59uNZp6j/sW9xz/wA5QLZb0+6aEJF1dJfhR0LX3Dh3Oc7sXfrqM/1y1+7MHolqKo6S+gHM6G0fwqVKlEolExMfmoLVHWMWpUWJ8CNSiijSzzYqMhRct08SNWA8xG1Y6gj4IYxxfhNAFWt3eMJm0AOWUcYr4MNzw2i+mt2h9TBN50NTwowpMdqpsIceh+93nH5JeGZ5PqI9l3qNVsHVcRhUubq27goO7/mgLZSr07HbnbMJZ8PMwMtYsNPf94oFCSFooh4n43Lly/4Hq0q9wuDxYGOcAV3Lg8mAcHZoAAABgOxDPY6HsFFi9i0Xuv8AxL7WrLqFkcRrN1ne8eVQMNWjI+/fxY6yxLESBkQB3GOZIEa/uT1GXLl/hrdY22ofD1QZZL/5Z4aroQG7yfaXLlyoV0Uvy/ZLLlz2aPe9yaI1v4fwYmPxtc1q2VxAEq10N9FP0wKKNPxBoCkY6B6GsPWLGDhedw9wgthUB+QIAiUjvFVzVs83D0cVBZr5juJs9JVjIoNzXyc+fMabBT1lf+05jMYDzi2jM1dNSrbHiy5J2syZfDY6BAnyNmA6quEs/wCT1x36QKt1XV/G72ip4wdTRPWBkhct3lc3v9yd7l0Yr9EESzSXLly5cuXLly5cBTdcFRfWIB4gL8OJcuXLly5fYrazZh8yKvp3iQCN2X1ly5cuXLlwCW55cAasVqNEbeux1ecwb9A1juJsx/a41fc8HHdUA0uoBNLZOtS7kfBjVVOumWQNRvKs/Q+vSZK9iFzdRxWpAwqVyw/5AAejr/70g4/4yx8XRv8A4gAUflWLn6xpLojmLA6ICOjGlYlYXB1YNygRP4wFxqO7i45ylM8HcGP4b/O5cuNIVMqiFi+KcEzL6AVbR/3rKFLS16j3mIKNCz6Yzb5ukdofB0lyRoBZbtmooW7X1N5TFpq0m8HiI3yJqy01DAW6MfcfHM2/1L/4igW6Rlxw5h+d4bzLhcuxl8TwkCMoArwEeFI4rLMe1bQ1QPL8Wciukf8AUQRRQ5gViXdYewNw7UsOAG4a1W3Xu/luXLly+ytKhPG273aaeD4/4g9PO7+7ifV9f0cRr/k2hnyiax7v1dr8LojhsaTSXr9EIXALVmjsU2pyeriUdidfHciBY2f8IzaxLvQaH5XLly4glAe+GUNwlxVt8rPSOBA8LuPxuLEShxNaakUEuDRGkmWQLXhzMgWCA7td5h8e25cvsv8AG5RsnRSzZ5ylaxBEERySgGWEft6SpltN8jLly+UvKfsmRblZ1pWG3kYjvs/C6OxQAtAh87pUrSQZt6v6lCDjtLd79TmGbPE4/wCAGBnYTK2r9n4XLly5cuXL/irVz2Gp2SimnLIr0D1EP4VozBx1Tf6i2qluZoiyy8gY89Jun7yPohi/31imgC0hnz1iKtrq6BPEgHC/FZKZ7qaePENZ4V0FKSagTVCosxfwqOx8OwSvywjNSMAHzxhAbutVUCHheTv/ANhARsZcuXKbsqBwcDU/u3K3V3OxDCuq6vMuXLly5cuXLQEfqHJgAHKGO23dvJFrtL7b7LlCOO27ouwJYUDR1jHd79v3+N/jZdQNr7VUouUwd37qIGL9xYEEvH/kp6vd/hFfQD3mMdWhkd0BtAdAdfbP3Mwg8hu8+srhDpCJFvdcUFCNTFR5RPMkWP8AyKlet/ycvn/8jEpFFbujfEbVGrLXjO+aCHi8+Uu2G90D/fSK1tV6aHQgVrK8wvBiXyJom0y6Gx2f7bFsmN/8Qxg/guaR/wCI6VWzWithYERMiSwgsLv0f9jiX+N9iP0DOp2aiiAUtWuxFu9+n6/O5cvs2+mE1XB7R4ig3Y0hHgvDmapn108oBRnQitTRrI5mMMNGkvwYQ1LalWPeQFyMiljOmXMB1LxlzjyUKSxGE3JTdaiVNbhGV7BE6BB/qYcOyjSDKANIp5yiIeJcaafJSk0bNAN+JA9keg9Q/qIgLYsZ6sGYcFnae7168di4BKY+LvZw74f2ACqiJhpx5m38Ngtpaqs1OxVsNYERRb388P8AAhDnV3duLFglmC6IOmTy6zAOIfyLUIheg7kvMXA/Wg/2bbdwEgv72ejmMxNlLCtmcC+LgljzC7FrHbd7Db7wf5BKZnCdsad5vHBsHKvTaF2HRUUbockfqQT/AAR2oeWa3ngc+Upq2yUidT6nUJ1r+2CN13iSzCDkt/ZMhmNKbeT+4sCri0dxI4+gadaz6wJvKczPeXFwM8eO6ABVj/WsC9xzM2rWg2gtZ4LiFi8iOByjBlMrWpud5+dS5ZrTXlsVs1dilenmh/8Ae1omKu5irvExV3McxsN0m8rGrmAV6Eabxxpwt4ITJTiP3hJt0lrUzFv5X23FojBaPVmnQ5yfKLmt0aPSMa43S2eD7iVBAliKYHVTsx1bgWE2RvWD3uPYmtSU5CVJqaFATaUDwKe7aGgOhdLV+OJxU/PSNGR7v/Usb2mhfshEiVRS0fGAyC6mPKABQVMjHDF8y9K/cB7wjK2uC7qAQAjrcxOXCluO3f8A+TVt0LqzvMCcX7j9VK9/xf7DWC6I9KgQkYDQ+OkuiXzTZliHvOP6hYarQj2pa9Jq9m9YrYVV6jozFW6cj8NrdJaKWzwrbG8F+gZbWbDmEPqJYb02qVKhOKlLNxxtD0ovEyAj3xI3GlIzfTujqDaywUJoBpKoeUFmImMmqdgrpKax0YvRGiZqQD4TWqwADDxuSguauOEVcHArVSzXOJgNByajBtSGu8uAbDGWssHsvezQUlfjcuXEERDqOVVULoLHOnY5O1KKUw2XXjzEVU11JgA94jNDShNocD/5CAaG9Hx4RQEZrLdOSBajcIvLYRq4LVNcN/XpKAAANAlzKWbhQwIahav/AK7GCkSlu+WDF3Rk75jfdmqruZ4kpwvfLVmgvY69YAoTktgAAAGxEA6tzVnfEKy8tPlLAFtrWNKmOY9Tx5a32ZLFCFi4G39Klcm52ItWqvK9lqdiooxXbirxNJvDzKNAMt1VrUBozeF5ifqFSBu5d8OADQCiVjsvvEdqwjSR3WWsIIIeJTkwjq/ifu2XChMwL/HWS0gUeDzijHelYu09wQBGaOie0qKG6BT5JtX7mIGdBuP+wbFYOHw0mSpuGn2ikcRsAolcRRFRqQVmE6L5zHg6tR1UeMUeLEka94SveUXj9PtKCj4iSzBfqQSy7qwg1WMahE3JsfGFqx8Vj/2IOpMUFebG5QbgjRwbig/cLiYb0CS9EbultG2rnUQj7kILonw4n+B/vU0F+Xb5H+wgFWTYuhKu1LrZNHiXJqbOz/Ox8yjfl3QKMR0/B2d19ioosUZUA05aTK2cqpXC7zDjYCg/C961hlmWwb9ewgQIyAxscwnkQRG/ZcuX2XLl9nrU9D9uy5cuX232LiVXE1Jx16QqmGGK7CfQFMzbHGP8hDpktSy6DVgwBNF+930hKzhq39Q1A1FYo2AHlNIXRwf3MlB3VL/8gm1HNv2jK4PQED2Xe/8AYNlm04RX2gelwGy94EtAYs4q3lVfyw7wVq3Nl6E+3Qjoni/yOkM3ynmR5A5MDvzDdrog9JkvN8t4sXGyj7kKgzzdTRk12ZS9LM1u8IBSgEgVAEPwclMTe7Hjvg2fyKkoN2O6LOPPf2oVqquxz6yyLFEqGoZ6SqltXnN1mOv4X2CVJ5YtyJYLqVFOI7ljA3u6UWt1h1EHT+P1KejfxMpS0UPN6NIpZngr1P8AIojHUAcjoy8yuT/pC4U2rQNvGLeVXr4GPZlB6Bq4wUkyBQigtAdWdzE5Dyix1PbR0v6gm6vB+85fl75ogXof9hQZd36oguxWUy81lwyPPQbeNdn6S7vt78en7gGZlwW0JszIhAFRHKK4N02HJySohKAjsxyxcgEdw94PImfJNb0P17wTCgKA2h2X+SPnhx3QblZ/Fel3BqzjTobH4qgNweHiAasrej1nWxcVSjX0g+YwS0NHdLoEYFh/NfZcuX+D81H5T2/G5cvsuX2IYhlJWFUWwBoGk8SNnco58yPrMf8AmW6vc/wRxaeJV80/UR3n1bfnlCiNaFYeVQAKCjsPUYcrRixQh1VvsTSQWOcAarEMVA1a6n+Qq8xvdPCHCJbndmPSChnvGgo+1FfHaX5eFggsFV5KoP69IVYjowr0Hoz55y1sjVDXmwyhOhUoh/FeDvNmELNdzj+DEsu3+xNhfs/JlVlGCiwL1mV08ojQCsUhY2/1E6WERw6QqiXLly5cuX+N/wAT81PTPb+S5fboil1nR/6/2P8A4aGgHcQrIOaM1KS+6XrFYNV0i14Fb8HkgcrF2Ps1LbHzezK7PP62D9yllFa3PN/yGqosta+MpEu0x1NO3WJezXIqU6MHKDsW8mWGA+MQ1B4ysPyKM7+JlZhqkHco8tZphy2qO4IKOy5cvsv8xbCkg5MDb8jFe9zsQ5yrqu/bcuXLjNPWPWV8jUVGVNU04Jpo8IUaEuXLly/yvtvsvtvsuX2etT078rly/wCDTMgQCC2m9cZhNE6Nyo2ESzhidi5CXoHvD5EMYK6rqOnEMBQFAbSkrxKQTvoDw3aek94MA0CcJLdkrhFhaJqILQvCBNoEAJcuXLl/xeiby6mzs89q0Wx7JW7l3QKwH8fznP8AJf53+dz1qPy/tLl/zPZLW3Ks+cQ9C/0lXXzkN8757oRTOAqAQK/D189Gdp6T37SeCw+eSv6bmJvNjuQRLGyN0BxVn1n2L/Z9i/2fYP8AZ9w/2fVT6qfVT6qfVT6qfVTHnypYOilrPop9FPop9VPqJ9RPqJ9B/RiIgAAAAAAAD6ifVRL2JrnEJgWK8J9VPop9VPoPxAAD6KfST6KfVT6qfVT6qfVT6qfRT66fXT66fRT6qfVT6qfVT6qMgN7CJfWG0+qn10fdwfMn1U+qg3Tq2jKBSaz6qfVT6ifWT6qfVT6qfVT6qfVT6KfRT6KfRT6qfVT6KfRT6Kffp96/2Zsj/lHSfD9P7fwnE+M4/uete09E7fSe16x7T07/AIbpPh+n9v5zifMcf3PWvaeidvpvv2+ue09O/wCGlmJrZcrD0r+u44445dc888c8889c84oIIJ9G7Hn16Pr0FVMIugGcQM8UFrZX4unBBPoUfQo+hR9K7Sj306PpcfSo+lR9Kj6VH0qPp3aUU+lR9Kj6FH0KPq0fVo+rRRM2yW/UKSymUEfXo+jQGdILd33Hb657T07/AL/xnKZN8Kf22AIUU4xCYUA1t+WhUIY1amJ4lKW/+zp46hBfVDW7+WzYMGCDAFSISA4YUBQH4oAgYsJsfMJCZLui/wBZwn9jaWiZ5735GnrVrhiBmU99v/n95UHXQAufRZ9Fn1WfXZ9dn12fXZ9Zn1mfWZ9Zn1mfXZ9Un1ifWJ9KnQdwr/D6vBwrYMeg8P8AbwXPX1iq4MV8v7yvk/eV8X7yvifeV877yvlfeDUmdf8AeV8r7yvnfeV8X7yvi/eV8X7yvgfeV8L7yhoB8d4uCdaYeKwEKSxFH1nwf6z4P9ZW/wCb1lfO+8r5/wB5Xy/vDjLQhFCs/Ff1TgEdBU8c+UfqfOP1PlH6nyj9T4x+p8Y/U+cfqfKP1PkH6nyj9T4x+p8Y/U+MfqfGP1PjH6nxj9T5N+ovKBUxcOP4fV4fM9I4HKJbbnTdZoucqA8m9VBUHT5DVbWUzLivUJJYjbdis8y33emRRkx3V+WEEI5ZdiY3D7FFsK2/n+M5/AUZBOAhNGIaLhQ1dTDsDpVNurLpxrFXZ+hJABOHN8RN93A4VUteFdPyGs2kglXVqphX0dabmkc3jSY37c10EyGeEvXpLm/g667S/mvMLRVAx+GaMrffiooOjOBm9y9XbOIsxRiyerRScMPlm3cBY2O8qmBVCWaTvAx0rb+uk2d/so0bC0oXVxtABl6crYrYWmZqcA8YXV7tIPttuL3hhOpCrE5WpShEplvVThuZhjgLRWfP+FqOYCfITQAtFb3eAa2nVfDpOu+HSdd8Ok6z4dJ1nw6Tqvh0nWfDpLRC01Ubl1FqaxYeJQs1HemxGSzyykUaYrQNikxpiPa7jXTYhbbebXaUGuu0qqztfcVmADVoFVa67WXGesNVW8aHnLWAYrpvepVXU0dpUNN+Ylr4Qa2Syfz/AAnM0ypoqq9J9Zn1WDDgqCtWZ74hrNuwCsBdXNp04lDqVOrCjLa2uYCnGpYio2NiW+cyHJYTqgFwY8WfRYeUNAF/AQRgKRtE5INNk26a4ADYZ6EXLm1yw4AK0n02VqHTbaq6DTVFnEuji8U0bKrN23mHUgwGuGQAFdA26x4aVCVCrvZdYeq0hoM6BimYMldA4/rJNnf7NiYwwHcN4HsOikiCqri9ILgEU11B8RiuqbYUXQ7pvNFLMIkrAqq8KlqAlC4PIrLUF0RNBolOcyoouHNW9Q9Khp/AQYI1R3in3tMRq9tDX82epwVCieyNAYWxY5t4CIIUW5YNFw9JQp4wiyjpK3mDEIDbUkXRb6DNPX4p3+IkG4AYmqzLzqoJcZRENnwZo9b0RT1ZZpEeEd4ADl7ujEKOwEvOX8/xnMq04awuqdJ5TpPKdJ5T6yfTR2ygDjKh+4PZzFLLQ90OJ5QCUa9u2LW6ELp5qFaLHCqXhKcE6BOgToHlOgToEpwSnBCED+sKTZ2YgGVjoaPr2ZN62UjhUXNAMHudYBQaKxrjG3SESsGwAACHcEUFVK75zuvOYKBKFUjdnGQcf0verw1D4Hl/QD5y62KLk0EU6Vi5WL+ola7JlCS5VntBDazOsbvCG/aoWNND0ANAVbjcru2UU5PvmEPBhjlymqk1RunhiKq2DXVZrEY61xA88PfvPCOojWxNk4/oUPiOYMiLa0GdJ0fwEgK6TBy3pAO1Ibuh2epFXV9rMLcJ6ez1ntlDr2s1hzBbKYVVLw7bocqeGnv/AHCKTZ2ZW4pHjbJL8nCcNLpesILMyVc1vW79IoEJGVKIDvQlQyoikWpNGsy7S4QPA6nSa9DKYQXatGhfBiRfiYLW5D2l7d0zAWg6iVinJklhvdxEn1tmK5bah4NwddMCKsA9EcdI0MpQWO451/l96vAIBEAGUOs6L8JPWdHtYYqZW5dEHpHFjtJduTiPNjIhpw8ktWq6tOjHEpbnQZppcN1XqvGB6IsfFBYuAixQW1p2fG2xRMMR0YANd9/6FiwdFwQCNu2I4EZUmxsaHv8Aw+Z5j0SWm5mwThXqdnrPbWJIglYtri+HXbSDClZZpnsKk8EXyNesABol/wBtjE29miHZdMEs57yEISAoraUfjJWnI6YqOuJ2hBk+FXUS8VwJgqtAtYM3ODdrAa2T3gT3Vd5SADTXViINNLSy0yqYp84d57lQWBygm0GQ0aMlKXi3G1RXBfWLQWuoxmBbAKcNyvUl4Kmm1Auzn+WzXbOXaFVT/Cu+aaGee61+xyrre+FIKsCHbbesSZLbbDFOf57td41mqnn+0rs0nssUYrGqmt3pBbsAaiKx4i0nQydHX7s8nbs9d7YjEtVFLpemnjDVMcdTA7Nc5Q9ezFclf23MXb2ZeugyI0tvShjsoxxts0B33GP2JwHGWFlkuWSyXLJZLJf/ACjEIIpha3X9wQAgwK9bHZlf52mIcCesyhHg6nomrr/fPWoaT1/trEfkDbAbWV6yt8pTOny7Hh5excGYt6d8RLSvegpBHc/smfrp73ZCu6VyIRarO9v+yvgTFi1tpBWzeOZe0NjKTVZw2lf3dgbbKqywCvKgumxa6laS1RxZF1J2NSmE4oMddjq7eEtrQBS1g5w840y1JyoNi95mrtYipnveL6wUUxUbXRxFMVWI1K61+Dl+Y4dyKBrgDW7AHd/xPPnjhg0aJHjx48ePHj79+fPHj7s2zZkyZs2bPuTLlgGpNjV7FYtoBTy4NSEdh+dp8jyjseD2MKXuEB5n6hsvhTHXwsQ0nq/bNNHvy2rcrPTME61XLDOny7LsnBcNXYupmBedW7d/R0hRQvtv3OnSBeQb7j/DGKXwBlnP9ez9dPf9vYfKDQ1oTPmxDYZL1ArHEv4bRaqLvnQlGTd01tL0M1aKVHU8IoYd94uNEENzFDkGmDCNrDkU5IKECiYXUEzneCREMskRpctDEu6hzwFcHSBTjrG2uy9a/j6r/i3zPMoAsGy5kesN2np/jCGzWhare0qVZ1pVFt7kHKYdQ0UTAAaWqzu0huBAFXSbHWIgsSkZU+GWfe4yswUyvK7TsVCmmpTVy1O9xb/zf5DN7mBlkScionly3KihXM2qyKmByFQyreIJ7S9y07/+y8sXSJ6v9b6+p9v/AGFfcCsQhsQC+05PIi+vl9nslvZzeOTBi9YGhgCI28d+ZmHT6dnqzxEV2+N89JoUqQ07boripppjTYMLIHg9Jnv4XfMkmRr9H3V6zN8fzlCh3bvXu4Y84OAZdDVihNWXy2+O1esz/K84Im9Rmu+PjMAgKOJFF1Xg/rXbVEISUu+Z9M/2fIP3Om+HWdF8Os6P4dZ0Py6zofl1nQ/LrOh+XWdD8us6H5dZ0Hy6zofl1nQ/LrOh+XWfGv3PjH7mkX0BpV/xRmA4CWWKPgnz39T5/wDqfKf1Phf6hKhOH/OZ9Vr34nV1nw39T4T+p8J/U+E/qfCf1PhP6nz39T57+p89/U+e/qfJf1HRR0Wa39kJAOAgWteJufJf1Phv6nx39dmouxkoqluH2/m//9k=)
Representação esquemática de microrrobôs TACSI. Microrobôs individuais são acionados por luz laser em um espaço de trabalho 3D, o que permite o controle espaço-temporal da locomoção e da geração de calor. Um nanosensor termorresponsivo integrado fornece feedback de temperatura em tempo real, enquanto o aquecimento localizado ativo leva à atuação térmica de células individuais. O sistema permite a medição de alterações celulares dinâmicas, como o conteúdo de cálcio intracelular, em paralelo. Crédito: Materiais Avançados de Saúde (2023). DOI: 10.1002/adhm.202300904
Um grupo de pesquisadores da Universidade Técnica de Munique (TUM) desenvolveu o primeiro microrobô ("microbot") do mundo capaz de navegar dentro de grupos de células e estimular células individuais. Berna Özkale Edelmann, professora de Nano e Microrobótica, vê potencial para novos tratamentos de doenças humanas. A pesquisa foi publicada na revista Advanced Healthcare Materials .
Os microrobôs são redondos, têm metade da espessura de um fio de cabelo humano , contêm nanobastões de ouro e corante fluorescente , e são cercados por um biomaterial obtido de algas. Eles podem ser acionados por luz laser para se moverem entre as células. Esses minúsculos robôs foram inventados pela Prof. Berna Özkale Edelmann. Para ser mais exato, a bioengenheira e diretora do Laboratório de Bioengenharia Microrobótica tem trabalhado com a sua equipa de investigadores para desenvolver uma plataforma tecnológica para a produção em larga escala destes veículos. Atualmente estão sendo usados in vitro, fora do corpo humano.
Minirobôs: uma corrida de táxi até a cela
Os microbots TACSI diferem dos robôs humanoides clássicos ou braços robóticos vistos nas fábricas. Todo o sistema requer um microscópio para ampliar os mundos em pequena escala, um computador e um laser para acionar os microrobôs de 30 micrômetros (µm) controlados por humanos. Os robôs podem ser aquecidos e também indicam continuamente a sua temperatura. Isto é importante porque, juntamente com a capacidade de encontrar o caminho para células individuais , eles também são projetados para aquecer a localização de células individuais ou grupos de células.
TACSI significa Imagem de Sinal Celular Ativada Termicamente. Em termos simples, é um sistema baseado em imagens capaz de aquecer células para ativá-las. TACSI é um “táxi” em todos os sentidos da palavra – no futuro, o minúsculo robô irá “dirigir” diretamente para o local onde os pesquisadores desejam estudar os processos celulares. “Pela primeira vez a nível mundial, desenvolvemos um sistema que não só permite aos microbots navegar através de grupos de células, como também pode estimular células individuais através de mudanças de temperatura”, afirma o Professor.
Como são feitos os microbots?
A produção de microbots é baseada em “chips microfluídicos” que modelam o processo de fabricação. O biomaterial é injetado através de um canal localizado no lado esquerdo do chip. Um óleo com componentes específicos é então adicionado de cima e de baixo através de canais de 15–60 µm. Os robôs finalizados surgem à direita. No caso do microbot TACSI, são adicionados os seguintes componentes:
Um corante fluorescente: neste caso é utilizado o corante laranja rodamina B que perde intensidade de cor com o aumento da temperatura. Isto torna o microbot um termômetro eficaz para o observador.
Nanobastões de ouro: as hastes de metal precioso de 25 a 90 nanômetros (nm) têm a propriedade de aquecer rapidamente (e resfriar novamente) quando bombardeadas com luz laser . Leva apenas alguns microssegundos para aumentar a temperatura do robô em 5°C. Os nanobastões podem ser aquecidos a 60°C. Através do processo automático de equilíbrio de temperatura dos nanobastões (conhecido como convecção), os robôs são acionados a uma velocidade máxima de 65 µm por segundo.
“Isso torna possível fabricar até 10.000 microbots em uma única produção”, explica Philipp Harder, membro da equipe de pesquisa.
As células respondem às mudanças de temperatura
Às vezes, pequenas mudanças de temperatura são suficientes para influenciar os processos celulares. “Quando a pele é ferida, por exemplo, através de um corte, a temperatura corporal aumenta ligeiramente, fazendo com que o sistema imunológico seja ativado”, explica o Prof. Özkale Edelmann.
Ela quer saber mais sobre se esta “estimulação térmica” pode ser usada para curar feridas. Também faltam pesquisas sobre se as células cancerígenas se tornam mais agressivas quando estimuladas. Estudos atuais mostram que as células cancerígenas morrem a altas temperaturas (60°C). Este efeito também pode ser usado para tratar arritmia cardíaca e depressão.
Importação de cálcio: canais iônicos nas células abertos
Pesquisadores da equipe do Prof. Özkale Edelmann usaram células renais para demonstrar que os canais iônicos celulares podem ser influenciados. Para fazer isso, eles direcionaram os microbots TACSI até as células. “Usamos o laser infravermelho para aumentar a temperatura. Para medir o aumento, medimos a intensidade da cor do corante rodamina B”, explica Philipp Harder. A equipe observou que os canais iônicos das células se abriam em determinadas temperaturas, por exemplo, para permitir a entrada de cálcio na célula.
“Usando este exemplo concreto, mostramos que o calor causa mudanças na célula, mesmo com ligeiros aumentos de temperatura”, diz o Prof. Özkale Edelmann. Ela espera que novas pesquisas apontem o caminho para novos tratamentos – por exemplo, tornando possível canalizar medicamentos para células individuais.
Mais informações: Philipp Harder et al, A Laser?Driven Microrobot for Thermal Stimulation of Single Cells, Advanced Healthcare Materials (2023). DOI: 10.1002/adhm.202300904
Informações do periódico: Materiais Avançados de Saúde