Em camundongos, o declínio cognitivo é influenciado pela obesidade devido à potencial associação de um eixo adiposo-cérebro. Para examinar esta proposta, Núria Olivera-Canellas e uma equipa de investigadores dos departamentos de medicina...
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ZGdmqbZwvitTv7D+zIrTYpmxYfj1CZMypiVIkbO3TNabCAZq1sy6FavPponPJqPLU5mnvFNZ1xIpvNtVF+bOx/t3L+kb61adjb0b/JqL9wssFdaLt2+RnlPKf6HpXyg84jrsTczvTYo0R9NlC2EDA7P7uyzv1PLvTOyXWrUrnLCf6b6E+YPnWfV5Q2Gxdomib0NaqvayolNr2DY5gDGNybu5iBbuXO4Tcs3DO4TcI9gEY7qdNvE1Vz1gaqzisuLaVs52nLVsJp8pc+XsVLM7ThEZjo6zVF9V+4TcM7lm4RiN/cv6ddSHNVG6um0eIjrvnyT0+Bnp5bRP9DE0ttVJdk1Fek2jv8A7uyztPkH1L2LomyhIWJelja451GCBnE+QrTJxmfE8sBoWDGjelz0Iz5Bg3rGJm+2ZJ7z+1iksgwnYyhpuVAjZN/nGQ8WIoxN/rGdm4l2UmKvpGOLSbY5O4hUiPk9X+3cueTJmTPOalrAiBrNOqcJFT8nHXv4iz7PVweZpebPMoop4/8AGK0NfExqWkvNNSdtdJqYNumTL6rHsG7GTPPK55uyztXUlrjRWRRRxTV1M40QPiNR5am597xoBk/M893wc4PxMzR2ZmZu87X2KtrOG1GFJLVdu71n9ux22hXzLX21rgucq3NU0a1I6kWA7amsJORH9aDcy7Tj6xCAy7N+Q6IqiMdqo7bo/wBu5f07HVssI35nymF3FaySPU4YJxOAm9lyJ+J2+aEcigKLs7kOzu/u7LJiYmJica7sRwdtf2t46ywRyKjCPQi8bacepQobYEC1oZX9NuHSk8nGKzp2LIXALIGnEkNSEOgWvtx6toW7sZdwavEALqibTYK4+7Z6VIySuEbPkpZJaoFdTJtMZd4rQbydtmTxqzSuzdAoXo/27l/Tuu83K7yuWJ5AzEcbbcsNwIsZyPR/rPmPVDlivwyEsBgdn93ZZ7Fiks2UgzvztYZNh3SrcXi1kMNrz/nzZQG2P6Ymcup3m/DHU4nKYbdy9x/buZgrtuEdzvcYXC7wVgLvNoxjAs3NTlVBUiDYZXiolg0R1npsVa8Gcgy/27l/Tt5lhIy+SRs3DKwbiQuZZ501+mncXHGmS52+nNLelSVZ2O5DuXs/u7LO+4kSp2IjfclhWWIi+haEcxHOFyoyFRd1g2naqpPiVfdlBJWraFqEUJHrVU7j+3c1IZuRTLtqqXO5ywb6WEFT5R9u0hwtJOwKFP2jfK45EH+OrGOnF5v9u5f07D5h6TDRZHHE6sM7Ww5Y2k7T9U+kB4yFRou7FeAybd3GpJUN3f3dlnsNYqG36NuZwVi/GK2AGSGyu7z4yWXazGvcc7jUp2KFUR1jVMWqr45b+fcf27XLbpYBXGLRyVOVDAmAlHjZBZCRkFPSgC7D5ZCpBtdVXb2P9u5f07XzsViJYfQbQAOPeuSConzCfQLdtu1t+jVeMIohBWxTle7+7ss9h6/X9KrWJf07QAYhyw+mxRMZqxlQA48pU1biWL6uOzfxbl4riHrJO0ivuP7d9i7lcGEerFRYMxcehWBz8z7Uoyikr6gxsmcJxExSydr/AG7l/TuFYBsrTaxsDn4slielMClnczyVM7xSrFju3kA+x/d2WeyQCGpYMV47VYGLnkfyVOTLLW1gBY1VDBpyErO/ut/PuP7ewKwDZSIlAYuHU1kNN7LMglPOvceL18bElEG+6bVz2P8AbtBBi/p7DUeb1bX9cNrb/N5Yp3KnoSnHt/3dcjL+3qaTjyC7jy52R/iivc7U+moEH2Lfz7cjJ/b2zQJZpkBdWI5fIEPU7GpPMymgF1q2nuf7dqIQKxh/ZKgxq1Y2aWt41FqRNJbmupUX2/7urKS7g7vbetXFmibJ0+od69CoUAAe1b+faFO/BF3vWaQNDpb6oumtsdKUr9l/t3BlFnIk5EnIk5EnIk5EnIk5EnIk5EnIk5EjWJt5EnIk5EnIk5EnIk5EnIk5EnIk5EnIk5EikG7ssOJyJORJyJORJyJORJyJORJyJORJyJORJyJBYk5EnIk5EnIk5EnIk5EnIk5EnIk5EnIksdSncxAt5EnIk5EnIk5EnIk5EnIk5EnIk5EnIk5EnIk5EjWJt5EnIk5EnIk5EnIk5EnIk5EnIkZlL92BMCYEwJgR9oOUBwJgTAmBMCYEfaZld2BMCYEwJgTAjbVg2IMCYEwJgTHdgTAmBMCYE9Js31zAmBMCYEwIxRZ6FZdrTAmBMCYEwIdpgKAYEwJgTAmB7GBMCYEwJgTAhwINkBQzAmBMCYEwJgQ7Xm+uYEwJgTAmBMCHaAdmQVJwPcauFWLdzJlwh39zqWhRvfKgwIQ3EcDyHY67oyboile7Yd3EYowv8FkDTa+BX59wQ54mgGB2uMjY2xa8N/AV1W7msxTbkHdgu2+g7rrHZq2sdSLbShusB5Har+LqDiW3ea2ty3HdA7LNx4LnKsjOpF1hnI4Zb7TKvt/GdlTVNc+6m712DfHsZqwxa5nPKrvXUlljtzvsrsd7aCTT/GxGUMOICBQvcKlDlQR/GxOFcrWB0x1xHrDwAAKoX+RicIChAO5qlZiMgDA//pjWFzqlNun1f8hmCjnqwXVYL6iVtrY/y6bdy1fl/PFtZhYLGdVCWJZCwBW6tj11aWnUJXdbqf5LDOkOSV/9NR8v5dCailK9xr/nakE1ZquI3OtNiMml/wDNd+wD7O0WEze03tN7Te03tN7Te03tN7Te03tN7Te03tN7Te03tN7Te03tN7Te03tN7TeZvM3tN5m9pvab2m9pvab2m9pvab2m9pvab2m9pvab2m9pvab2m9pvab2m9pvab2m9or7j0Zts5Fm9RFYOP5JOJuM3TMzMxxui+kZm4zd2U/j7Wf511myU2b/cH79HXdDRmeHiLtHQallYaoGNq/SdWoB1MqvFk8YuPFLjxOZ4zzOrUM2rCg6obvFElNZ6Vv3V+LG6vVgzxi48WhY3f5BqlMOq2uLA/bfqeNqbBYnVuyn8vavTkXF8xcARdG5TLeTB5DMXTbcZ/k4lFwhF2ALcqbSQtwiC4ygOG7Xs2tyqF5UnKk5a5zVzkWNYqlmrtWrjScteOWvAsUzlrnNXOVJy147B+/Rjhf8A6V/KDlanLjp4enK01rPD1Y8PVDTWYK1WcFWPD1GGmsrwV58PVlqKmnDXOCqeHqnGuzhr3cFWfDUicFQLVIzpp0CcFWNoXtu0wtatBWnVuyn8veBB/hPWS3DmxtOdnASPDTg8hRgvVuIonhvMUefh/IU7KRRPD5nhvJtPun+uo/frj/8AHeI/0AB0ufjqGo2nxVQh1NSnxVcGprzXelg8VVt8TVjxVc8XXk6qsE6qoQ6msMdUu5NZWQt6Mniq8pqkI8XVPEV7jcofxNePEqG3q/YbQCO1ulpwqM26n8YtlgPM+K3csb3Dczbhe6jlsE5n39o+382z6WYRRZUZyVSvjsXYs2LNixlAg/fpqgzabHnpVZdNxPujqHTwyQ6QbvB1ZOnQzw1croWtfC148Kk8OuPDV58JXufS1vPDpkaZBBpKwRUopOnQuNLWCNHWANLWrGkGxNKAh0tZmxV7DT5jtbsp/LrkZFag+yfn+bZ+bKGHFXOKuKoUdXg/fpbYtVf/ANFeWqxba96/wL7hQo1Nc5q54mqc9WRerPz1ZN9QI1NcOpqBd/JbPP2G7Kfx6/8AfbnEV1bsbzA8x2EgQHMJAgIP8Wz82GVFbinbepxqCuL5XzckeD9+mura3S7Tu0NTVaXh8/fsrFk8DXg6UFjpgYdKuKtMtbNphu8GDU2kViNMoLVhEVST7DdlP5df++3VKzVaZG5Oxe3UKxbTghNQpM06kdxOAL23TUDNYLKFe0wtazqbgtLsxRrEqPJxh75ut3hrGUG0yz82ztXl4i983XMwtvY8tuOe3a31H79cDPs2OK0W+tpvWciTmr3ciTkrwbEEN9alLq3G9TORIlqOOSvG9cllB3pjmTcfMwuAe9uyn8uv/fdcxRaLGY9f++zVWOr6Z2dO02oG6ClA3R3XeLqxOZNwvTCPXsNyEG9AOdILkJAwJZ+fe8H7+7cnJUdF6vCHHhcDweIdISz6TdPC+oaQiDRmLRjTnSf5F0ZDeCaDSEO1J5q9M2xtITEr4xGQ7lGF7mlv61OOLcCafx6/99xAYKgXo9r71OVb4sduRfr0ZVeAADtal9w8gfit35OltW+cK44FzwJtWoKvAkbTox4Ky3AvWz87d2AdRD4gn/8AYArNu/o8H7/wXLglrBEc7vEGc88QdviI9pE5zv8AERryIbzu5zHt2lSSnZntaW1sxQ76+P1Ufj1/7ttKGtt6dbG2JVaXPQopPTIWsXjdzJOVZyplrFVuVMcqTkTJsWG6ucixWVumB1NqBu0+QUdln5xWBhZQQyk9Xg/f+CbPVzVmctYjsgCtUo5K93LVORdm9dqENGevCWIzclcNqZ+x7GRt3Y0e3a2mwwlP49f+3rV5uSqA5HRgGCVqncy7gaFwNMZ4byWjaz0biaWSLQeNdPtUacwaYieH9KJtPY1DF+35bss/OKoy9e5lQhurwfv7bMFBIHTOJnyhrUkUoIKqyONdprTPFXOOsvsQrsXATaTSpipWG4hOFJgL7TTU4NlIArlP5dT95bSWZF2r7J+YTgyy9lsF4htHGLLN3NYEW+eJTbyja14Cpcrv7DQDA7LPzcZVR6rN/Im7l6vB+/t3VtZOOwxanmx4arCURxY6HIRzOOzPFZh0c1mo7uN88T5FZnq8M1dhHC2eOzJWxZgjtYNv7GjpRvAwJT+PU/b3G8wPMEZAOQ6JjiQgiutK1ryEUR669wprIKLtFSkhUrZrUWG+pZypu3rhHVx1Xus/NzhfMFrNrpaHfq8H79LbeOWXbCuoy1d+9/byPeb59lpZw8isGEp/Hqft7q9PhosuUsrLYorrcgVW8gqsC0ec2OiPVuCJahWtgqq6laWWUqw6nzPdZ+bEBVwGYIWG3d1eD9+lz1g89THYs2gH26lYMxsLOLZ/mwvLuflh5ssLCx5Sf82RvFI5YvKZiyerp/vvaf5gzZWsOd9H49T9ujHC+IXbykLzjcLwQ1gQ8yZ5a5zV4F6Gc1cDqXjDyHmG6McBj6EsIgvct4mJc+FuLPyuHNm/Tm1wTnB8mNlm0N/mAwO6z82KkfJcBnQBX3LNyzcsZhB+/TUrl1T1fy2+fZaWusVt4xKfx6n7dGGVOnUng3TwwnEAtlW9npWCjyGn2zw/nwQVbD0HkYPIz4gVYlSpNqzaJxLyECIF2Ym0AFQZgRVXc7hAtisNywuoG4Tcs3LA6sMrFdWm5YHUjIz1H79LBkhfOywrY97AjzH8C5C9gVlevfys9m9i2S9kBsgawkFj7TdlP5dT8+wfhPr1MX6xvmN89F7k+vV/rLP2v+cDa31TzazyVPNVH+Gjzb/ZlQ/yafsH79D1x/Kb59lp/8QALREAAQMDAwIEBQUAAAAAAAAAAQACERIhMQMQMEBBICIyUAQTUWBhQlJxgJH/2gAIAQMBAT8B+/569oacn24ZuiBEg7ujtsSh1rTSZHsZjtvfrWgd1Rp/u2ce2w66Dz+V2LLTElal2BPymlT266TzBjnXCBZgrT02m61m+VOymnlbYynemY2Cah1Qjuu1lS1oBITmtJqGFqzQnZTRKweO7oCYYlrii6NJOvZVJuEBuBHARGxdIhNEmOSDEoOjzFAQaXrTABWr6CjlByDvpx1GITGF1wpLmyE7CiU36KPohx2j8prmgXCYW4pT7EoVcU9tg1hFRKpaey1PQjlBNFrJp4QwkSNmaTpCFwn52EC6BkcYElPM/wA7EFplqcIsVEItnhY6kynARUE1oFlmycZad+3E17m4UVnyhST/AKqU/wBSBUoLvwAxdEyZRFodaFXEQU0CakAWr4iQbpqAM3QbB8bA3LkFFJsqrYUJ12ne6GLKO/A0SYQdAhabqsjCCf6thZNPHEiUWl91pSApEr4mJshITSZTeD9KDx2XzWlHUATtRkESqSqSmym4R8YaThFzaYCawFhKYSGiNtT1HcZ9tD3DBVZ2hQo/vb5aepdRQIz7i2nv7gMp4E24ymw3y+G1apvPgbPfrGgHPDPbcQbognGwEeEidgI64iPGfxzET1pEewyOcCfYyL/Y3//EACURAAIBAwQCAgMBAAAAAAAAAAABERAwMQIhQVAgQBJhA1FwgP/aAAgBAgEBPwH+PP8Ai0uj6/dDFkYutk3GzS9xivc1Xuy6acjFcwP9kbjJF7n0faGacjJJuNmGOiIuwM4FNzfBLFmqFZmj1UdVcXjFloQ3RXYMVeb8DMnFER5usUWfDiyyB7eKuTA6cUQrHJB8WQJMggQrO8k7j7KER/vHefZUz2OqeOw1YPxttb9lrbWBdmm32S1T0MO/q1/Ho09vQbjtv//EAEAQAAEDAgIJBAEDAgUCBQUBAAEAAhEhMRJBAxAgIjJRYXGRMHKBoTMTQLFCUiNDYsHhgvAEFFDC0WBzgKKy8f/aAAgBAQAGPwJFw4jQJ+j035GH0paJKc9rmbvRNDntqJnCmgQHGsnkv06Y5vksLi0EEVyTpihoRmgXAzhkwjiB4oCJ0bSaSsJugSHCk/CisTEqS1wm05rE309KD/4oaMNdQFTpK1oefqFzCKc1o8WE4r0Wlw4QGWomS5u9/pQcf2Gkbo9J+mzR07ojTwYNDz9RzuQRO4aKWRESsTCPkLeMlXA3yLSpPOh5+oxglrG1xdU14c7SB1HH0okjsnAknFcoO5CEMLnCLdFc4pnFmpkkzM6sNatwqZMzKcK1CJk9kKkUhf8AVKq5xi3RR6emLv8Awh0gc6ieXtwhzpDeXqFvNCchCIrVuFNhxbh5KB+w0jm6I6RmkrTJOdp6SaN5eoQbFSXOdFpTmgneRa55ct1gI7oOzmUYsTP/ANavxNBXA3wuBvhcDfC4G+FwN8Lgb4XA3wuBvhcDfC4G+FwN8Lgb4R3W+FwN8Lgb4XA3wuBvhcDfC4G+FwN8Lgb4XA3wuBvhcDfC4G+FwN8IwAKbLZ/uXA3wuBvhcDfC4G+FwN8Lgb4XA3wuBvhcDfC4G+FwN8Lgb4XA3wuBvhcDfC4G+FwN8Lgb4XA3wuBvhcDfC4G+FwN8Lgb4XA3wuBvhSGjxttkTQrgb4XA3wuBvhcDfC4G+FwN8Lgb4XA3wuBvhcDfC4G+FwN8Lgb4XA3wuBvhHcb4XA3wuBvhcDfC4G+FwN8Lgb4XA3wuBvhcDfC4G+EyGgV23+qfWPt2ByTRhPFf1jqcf6Wpzc6QnS4kAx6J229j+wPps77b/AECRfJB1JJjDyRn4+LqOTa99R9Y+3Zb7v2BdCNII9I7bex/YH02d9t/pTFlDXN7ajOzUqrgoxCVRwKFRXZPt2W+71jqg2W6PSO23sf2B9Nnfbf6Th0UkjUdkI8O8K9E74hAmkckw4uEbJ9uy33ftMSnD4RAExmg3Caidg7UJvY+jU7Z9NnfbfrlxhSDTaLJqjQwLlOAE4VMYZ1X14fRPt2W+79g6AeKVhOItb9puFrqZKTyTZ5qtgt0nvKaAcqbB2sUobxND6Iw5INO0fTZ32364mEGtM1kqHbOOc7I1NbhHDIpBUZRqMCao48zbYuqOBVxsn27Lfd6x1YYPfVGrsi0ZpzHBtZWLIbB229j+wPps77b9ZcVhCsY5qYNpTcEy5UP/AH/2E44oCbWkTqPdHYnxrbisHYk0homSVflTmgTa577B9uy33epgrsYtW8pCJU8k0EOw9E8b2KKIhjXVzKg0gQnkk3ojtt7H9gfTZ323qphcQr1UYxQzdTo9IrlOhxGLWaL51Hujrjzrxegfbst93qY69lxCinGFxBcQ5LDNVNlAy1VVVhaJzRAyU6jtt7H9gfTZ323oObBI5o4zfIIGZp9oaPMBQo5a3S4Kjs81xt8ooqSgNE8IE31YWurrLuSholBxETsH27Lfd6oGLut2/MlGtzVYcUBtkXFBAKFHNQpKt4UDUdtvY7UyFEidgdTCwjnFlZWBMxREERyR9NnfadiFVpC6iv8ASiap1eG6EGs01Trq6hKqWq4WAuqjCcquga8ROvBzCjpCjYPt2W+71N2YAkwqv3hEDmpmmfRHC8/6eqFUdRR1Ep292UfqQIvzTq8oTOX9RTjixCm23sdkgKgDeixO67FQqil1hDcs+SoFQXR9Nnfb0rRmg6RI6KjorK4j1TYyqp86nH+1WEqSKhNQwi6xGKrFaQnQoCBjisiHAU5ekfbst93qwCsWKhKK+Nc6uqAC4ZJXDUdVhDftSWwjtt7FTyViE01qJQkGpjVTXVVcEd4UuiC4dUXNdOVdZ9NnfbeuIKCaqrgpkSB9KWmQo8KVGEQVugxlyTVhLAQFhYyyI0nhN7rD/wBhYLhQRFUMOaDip2z7dhtN1NoIxeqG4hApRBs/1Siigu6AQC7LEt4mSt0z1lA4hyug2R0RrtZoSBYot5o5TyUglRNjOvvqbymVQgzzRGKhRBN+qrXemTrPps77GE6bD2U4sQyMatIhahsjaCZUCLlYw4EkfCr86qrAGzCl9CroBvFmV15qXXWEziRhCwKBddVEqBYegfbq4sKhumx6m+70xgp1TMvi6BN0E8tunYqhGMgodUfwiVvfPRe5Qv1BE2AQoBEbvNSXAGqgRknT02AP1MEoxpMYGpvY7EjbI1N3sIzKbxQDUwnnEYBojHps77BEtO9ijCSgZB7an7FLaiTbJVZ3qsRaChh3YQLJ6qdT2k0agBeFijEFMUQAJ7KphbtvQPt1NcCBBzWDdp0g6m+70pcYW64FACC5ZYuWo4j8KWoq+rDIlYlGZUBHckzRyl9akysQgkZJ4dzFdihG83DESv6achGpvYqKVNEYIAHPNGmcLDS32pNtcaxrFL6jsEi8IYeEoOcb7LO+w/A5lXZhQb6n7OHDAKjSEQVw/wDKLcMgIhoquJyGNu8Rq0n8LEDUhQSrlDStd4WJ8zNJRGfoH26mYSJxZoaRxaRGWpvu9CW2/jVAMKHm3JF2IQUK21P73Q0eKqfWJQdIjogFW0zK6BTrLUSTdHYxNc0Q2spxeRLuWpvYrgb4U4RIVWhcEjkt0UXTV22JZMZQqr51HYqrbTO+wMDny44oohUnvq0pF1Gjc55KmvB9qHGmXVNxuNp7oGIcQgQUNEHbwRxs+EYFQsVx0WFzuHMorSAXhOxfGoQrrnK3BFakLfRJyURGyfbqxYiMNaIMcXWkVGpvu9CXGAg7RwZUkImKE3RwuBzUh4LioaiNIN7+FLszdBrsLRzRIcDVFyJBkqPOouOQlDC29kQW1hHdJiE5oFs/nYmXV3YCcHkkjnqb2OzI1QVnf4hRrjlqKbgmOi3uKNidtnfYro2PHVQGtbPLVpCUDBqpVjHNAgOqrOm4osWWfVf4c3og594rCwtnugGuobLpyGoyf6U8EmBRQFDTfkhzR/ViOSws/jVBUjZPt1Uj5QnQsb2qpCb7tjdTYLaiUCBnHNUH0iOHC6iwuqoCJVTCbqkf1LRv6QogUT+a/T5hFxrFkZAKIgUWF5JlYpIrkgK3RAPCarG3PYjC1w5FfjaztXU3sUcLncVFNcPhQHEkptciTmjJxdVI1QbqeSlylqluay/+VDRFFR30nF/lOcLgLDpazmsANfQZ32BM15CUXtP/AOsang2kI/XRV5yquJyWJwxcgnPDj4TWssB5X6rzRqwxQ2WNnhG/yt4FqC57qfhtKNVIX5DK3ib3Q5TT0D7dUnJNFR3Zqb7tjeEq2UKrVEAKmouGSIe0OCjRREZKQAsRVEf1JLOqOFoA7JzmvFOSNZrRT4VhVbjfhAzCAxChkUU4q9kRiNlh5RsS5XgjIs1N7HVRwVwoXJQVIUjVgxVaoClWCqAURAx9k7FUZIgLET4WKaclUgbbO+wwNOF1aysQuaX1aQnJEuYRy6rdaTSV8whiaeKFhY2k3lSNRDRiOahpI6riOFYXGg1NyunTz1dEX/2okgkASpa0AnNAOO9tn26nSJEIDSHFSRDtTfd6EHXiDRKugeSHKdXEsINSiyap5NSoICwtAU81Am9YQ3X4eScK4+qbQ0Mmqea/PfY+aIl1XNN5UUhCJsckYUUAyVWtM36LG4ioquY1cwpasQTXmqxDVOYRDqhb3NU5KnynBuaOKY6qWwsN4oFXZZ32MLtE53wqiK21aXHZbzi6K7yo50CiF7QjWzsuaDq9FuqWouHCVikNA5oz9aqlNmyJOZULooBobqI4lRoX+nFtn26uEnshg0ZY2K0jU33bWJb9Dq3lDJHVNmsIYhdADNaNtzqkiiiKIGwCIbEI4RRf0mF0TsDrD7WEfMI7yE3JF08EyOnfYgsLh2TtwsbkIhTAlN7HXRyjEjW11IPyFveVLUP0/kJv6x+0BIA1EZ5KriEJqYRK3lxgd1hAxLHYKWwVKkKNHM3onxNeHosVa9VvU3o+thnR069K3mpnP6UZ5zmpcZKMAGTyWASQMkNG928pW6d4fa/TymVMrNBNpWVM31XoslijetKAaLoaXDvHbPt1hp1N920W81vGEGZcuWq1/pfqSQ7+VGSaX2lMIzz1Q4mIQBN7VUTZYHhtlviQt97ZGSmKFWiFiKiKrPvCdHPYc0ZjW3sdbm0rbohFABCLQ6pMo4s9W5MZQr7yAFxRNh1BzQ3qDPJE5BN/vaM89TjG7CgcQWGk9VV7YiSsIkDIJ28JPJQ4eEDzuumtnfaO7hWkm/RBle6AimKqcXtdvWAQaTVTmsY55J36sx1W797Ig6py1VAITTRrTZVAI2KbB9uy33ejDB8qYEk1TWuEcipXdaENdIhQuSmyjJFAvbRf9UqHLA2gmyjFnKxY65r8kclEzXbb2Koow5TPRHcqBJGwTyRZEUUuiFiYLotmqxSFXJTblqwdE9UCpYGso4LHqiXKok7LO+2/XhieeqWojSGqLiDCCqqWKnU2OaqFCh1UGprRksE0lVtkoMoYO6h3PYPt2Bu/KbURi9A4Lpznt7SihidOHUapntV9WLkqFMwtaHf3LEWS6arFMCJUYTJdboiRTwufZE0OKJTpbeK8kMRpeOqYBG5Cc4tjZb2K3grZQjS91QwryqhVUtCOG6OKY66oE4eiaTFclKxJzTYhPhVToEklbrRKJzCwuiuyzvtv1GFOkFP51/2iYWCSG5ckWghznZp2KhVkFEKLIFSdRIut0O6QsThUXKcFMkIAZbJ9uy33bYw4o6IYr6pcjAudVEz2qVvBSWyO+rBA6CEZcnNvVQ50HsiQJKNBRQMQ6qXtdWw5IucKHbbPIqJV1dRKurqLlOLKORxGB1Qwx3XWbqt/51WlVQ/UT3HiVMlIFFACdigF2SyAJV1Eq6umDrtv2NxE6VYtELXQZj3gIqq7ErNVuoshCo5HEflEaN4ThiE7Z9uy33bRAEIyVUwsIR6BW1WUKF1VlVfwr91HwVJf3WGPpOgQK4YQ/Tc45rFWDRPqS2m23sVMSgDtQKlQQgEQIqU1pPwntEOaEQG5UpRfqGsfSaXtiTdS2K1hPLHwmN/Uock6APhOMZ3RfhEqCI2Gd9t9FZWVlu07KH5qG3OZUriRGaAzUYqlfUqC4UTXY5lYq9EHNMuOSLslDVjNZELESqR5VlIH/CqFZWRkZbLfds4cNJhEARKJmSVLckJRmtViAwjXkuyrnqOq4WB4k5FcJVihFyVQCl5VuaM/xtYU3sdozSFMoNBkck4jI81Dj5UZDMJ4Fe6mDU06qwg0Uut0Qc41abLcGE5lBwbiDbrg3isDDMhW+F0UgyieSgxqZ3237JgHFzViG5ygTYGECABWiGJsnNEEEGfCEGQTcota+1kCbtUQEwCXK6YXCZOSIBc2FAX8dVv0J2j7dlvu2cUV1GLrOOqpSbwt6eibFuyLIrKjSskmyfEfK3gKoPfBHJOcd0cipbCIlAKtf9kZyKivdCclZQRRU2pQgZHZgqleaDTQEyOikmSt7NBoiU0CWnNDC4kQt5pjIFHRChTg6Km6h4tYppcJ/wB0RVjDkiauwm8ploPJHEYIzTR891PCDVCREqg1M77b9uYnCU54OEhNMwT0Tn4m0pa6gNOPOi/wqn/dYnuGMZIw5opdMb/SDdFzatCxB3wpIk5QjuldVIN1Gyfbst93oTEhAisKrcQdyVQaWCpmck5z3jojpHMnmsQpP9KIiYCZ/iKuVkHUxOyRdyROE4ullDSPhEN7uTh/aEN3KqacPEopWt9tvY7bsMDCpiDN1EhVJa05rdqIqU5rJJbaMlBuUY3cKxT2WMtKLnMut/eMUWHDBzQw3mida9zRWnFkqtUzOqK90zvtv2s+iJw2MrG0Aud0USRAzX6jWzXndO/plYtFuwEG0xJrsFM1h0QzW6bVKJbo6FANJMqP7v6lOGALqAp2T7dlvu2xWAjXEv8AVdMawuTpArmnZO5Ig1cbyntbpIRBHRVccRQe3RjrKwcrdEHZcpWYEZqZxdOaoRXkpeFJiAmkR0W7/SjA229jtyoiicKQmjCYNpTRJ7hf4Zmbo1qBSFLjU3lYbvnJODu6LInFmUBJkXMqA3FyKmg7L/DrSsprnfEKNd6ckzvtv2YQh1rI14r1XFWKdVJ3pUThDclI3o6UW6ZK3GmCiN7oMlBNUQ6qgkQ1DnyQv0lSqido+3Zb7vQtTNbsb2apGIKH4gVpCWYkMU0usUFOYRbNY3X5QoeYByCoSXC63Ru3UtNBzQOk4bqRnqBZh3Sg/GJCIxSD6Dex2jUzlqGdaBW4aGUAd6BZCvcJwDKGqzcYTXNGdZRo2SZRdpTQ2RIIHRB7jM5IQCJuhhdQlY3HosNo2Wd9t+0YUhsSEaT/AKlw8WSrmnt0cAJmKhdcpzcVAg1s4nXlTxG0I4qTXCnUrNdXFYZoHbPt2W+70MQUUKw2j+3koYMTlDjFOag8PJPezKyP6rr2WM15BHe3rQgNH8yhxWogKSNTThxAZIOoIoByQbgjmVWJv3TyM4TpAEnbb2PodqozNU1z6N5BOJyXwg5tX2IVRWZRIAqFhMyEG4aZlbujoVvAkxRQAL3WK8jwiaGL7LO+2/blOKaS0fC/VnC7ksWjxVuUOK1QsEjmFPRSMjfNYpr1WM2/lZzKqPQPt2W+70YKOABbrhOawl0RZQ5u/wDSeSyqAwCWri6rE4HqjiHaVGLssTts7bex9HMoHDK3m7vUIu0UmBRR+oQBVDS3yWLC53OMlhJwhEBu72WKeyDsTeyZSG/zqmBOyzvtUMp/ondJ5dFaQBZOaGwOSuDkmiAj+m2KZI1km4TcQFPTPt2Imqb7vTJjEFDBasqADidmU5ulBLk3SDSVzhTo6H+oo4SevVGkD0TtRNU3sfUMOIlAhshYHOgNsCpZ4RDW/Kw87iEJkzdoyTnYS1vZCtBts77XKkUT5M+lUKSKrkRYhEiHNhFzn3M4UMzz9Q+3Y6UTTi/qt6lUDon25o7rR1JQGkcXKnpnanJCXTQ+vR5CJaQ4LHpsI6Bbo9FnfbfJAXG3yuNvlcbfK42+Vxt8rjb5XG3yuNvlcbfK42+Vxt8rjb5R3m+Vxt8rjb5XG3yuNvlcbfK42+Vxt8rjb5XG3yuNvlcbfK42+Vxt8owZpstn+5cbfK42+Vxt8rjb5XG3yuNvlcbfK42+Vxt8rjb5XG3yuNvlcbfKO83yuNvlcbfK42+Vxt8rjb5XG3yuNvlcbfK42+Vxt8rjb5XG3yqOHnbbJihXG3yuNvlcbfK42+Vxt8rjb5XG3yuNvlcbfK42+Vxt8rjb5XG3yuNvlcbfKO83yuNvlcbfK42+Vxt8rjb5XG3yuNvlcbfK42+Vxt8pkOBr6FlZWVk2VFJVlZWVlZWWDMrDSVZWVlZWVlVAGFZWVlbbsrKysrLsv+FZWVlZWVYRmKqisrKysrItpKjl0VlZWVlb0LKysrKyssk53XkqfwrKysrKysnNCy8KwVlZWVlZVQfkqerunohaBtzKmeu3RASIHr1V1ltUOUK9Cq7Uz1WRhAfsijUSULbcyriRRRtwCFNPj9jpQXCZp4Q35kb1OBOxPnegdVo3ipwl3yhDv1ADQ/BU48W4E7frXdiyLMed/hYsVmg2VHS6TuQtJLgYEg9f22jJoMaODSUjdj+opuJ8bxlvJPg/5ZiFhDrEANi4QaXRRsDmgMeARdF2Kh0lo6Kjrx/KLXaSACd6E2oy+VpBkHft2lxAGA3RwukzRnRHFpZGEHsUa/5gHwoxTIq3+1Ml1cR3eSIL8NoEXTd6hZysg3H/AFET8KS/CaQIusLogzLU2f3EFDCYEz3VNrFWVB/cFwuhNxntVn4KAGSp+5IYYJzvtydUD/8AJnQ6NmkLA6bJmifpDpGaS05fuZcYCn9RtEJIE2UB4lQ14J/eE6X/AMY9hmybvYqX5/8AoBh7adVUwpJAC3HAqCVAe0nY0Wk0TMWDqm6XTNDAywn904R/mf8AuTAf8pwatJ7QtAMQdB4QKj95h/8AKtdWZJCGJuE8v39K1EjosLRNL8k7F/lNLflNaHAmFo+yZ7XLQfqH/DpYW2pGjdC/G76X43fS/G76X43fS/G76X43fS/G76X43fS/G76X43fS/G76X43fS/G76X43fS/G76X43fS/G76X43fS/G76X43fS/G76X43fS/G76X43fS/E76X4nfS/E76X4nfS/G76X43fS/G76X43fS/G76X43fS/G76X43fS/G76X43fS/G76X43fS/G76X43fS/G76X43fS/G76X43fS/G76X43fS/G76X43fS/G76X43fS/G76RGEgjnr7q8d1VwUt/d8JXCVwlcJXCV/mDsVZ57rhK4SuE7De3/pNLqDf1He0axBghVca3Rl11Gs/q2rkhuOqpbozJgieRRJY6Kx1hcJEGo+JTt0iBKkscLR1lThdYfzCgaN1yB1RhhLaR8pwLTQSqsdeFA0bjWEMDZBI+03EwyeSfpMJAbPyg3A4EpgcDJvCO4aJoANYWAMJi63WkmnlHE3IQFozacjs4QJWLY+dhvb0w3qje+WdEXVLpsoBdP1ZSMQTcMzyCeATu8lMOkgSql2SzvXnCEYgP8AlZ0MdwpdiymLojexCO1ld2V0MRdE1RL5kgbWENLjeixEriHNCCIOa4wuNqqQoJryWLFELjBJU4wpxhGtBmuMIb0yYXEFOMbLvaNZKxSMP9sIFVEHWdwVQhtkRgujuXVWowL0UYeiG5ZRhpdThROC6q1cK4UNyyLI3Sg7DUIbllRn2gcFrLGW7yLXb0nEVGBMAFBs4pgrCNj52G9vXp+yxMfhMRZVmMMd0Rin4zhVfXsjv1JUYsiPKo+96Imbwhv8NqLj7oEut0Qh+QCc0GZEKXOqhL7dFGL6XFHxsu9o2OI3+NVBGpz4nCJUaVsGJEVlZ+LIgk0rZGJmtwoP8Ilpsprlkpnkv6rxZG8CKxeUQZECbLO8RCw709kIEgkWTSZEpzxOFt6ICteibioXI3p0QbNSsFZ6BUk2yRm0CExzTQ7ERtfOq8K89E3tqc4ggPEiVWAeUfSGKxlZdotVUtz+Vzry6rKvS1UBQjtfaI/fFThlCl1/wparKyshHNO9o16QMvCjNaMPvC+edtRYbFVLiec1XEcMVrdE1qjepJWd5+oRDZqorYDwhV3lCC4RNQUIkWp2TjXeRmamVNbz9QhE0j6Q4qI6L+kyg6shAiaIgFyaRNFjkg97oh3EXYpGSriyrKYBlsX2h32G9tiFIFfSB/fFQQuELhCgDYHdO9o1l7rBYv8Ay7e+aD22KuP2Ac4SJhGTEGFxIb90RjsmtbWZR3rXUFydJjCYUY0xzayq+j87De2wdqq3SD6VTCoqqn7UogGE5s1KhpoqyrrfO7qHdO9o1ua26wwZ5JrXXuqGK/sGzkZUAm6O8Y5fC4iBAB6riOf2gQ40lPeKlwsmNc6rblE4jeVc3n6haNorhp6Q77De2x8bW7zspggbJGyDEhVQIRnalVtqsb5CUIbhHbsnEOdS27eqIh2Ht1U1pFITgSTui4U70NAmQmV3iaozPWlkLx1F0wy42NkBLsp3bIo4bpxN8lY+FSg7Lhj/AKV+NcFUO4TvaNiY9IvdYLipEyuIeVxt8otxiRdcbadVONvlVe3yoLorCBDxWyMOFL1XG3ymkHisFONtOqAxCtqqC4SpxDyiMVhMpvf0vnYb22PjboiHbHfZDWmBC3stqJ1zrwOFFDQfgKKz2VU46MWQJqFJnwjeiAGapqPoDune0es5lpCcWvoYgKA8WE06yhhLZBJqOajECN245J5xjeBFkYcBXkpJBrNukJu8KRlyCbvCnTqn6ORLpqg4ERSnZNOO0Iy8E0yTSXzEfSxyIMTIUmhxSJ5KcQmmS0bZt6Q7qML30mjohYpdH+pQm9tj424KoNRikIFTyRqUJ17wBUARtGLKFRCp1mLkQs8kL0WHJFtarNSZRqZTb01lUnrCiFEQOawic6qHCmsd072j9k+HGgVT/wDKdWVVmUoyBTqrCYR3EwgAhwWHDXuuH7UwKdVYR0XCLTdQAtGXX9L5VmO+lg5ilFM+EztsfCgKdiVBGuSNeIjhWFzS09UN4VMIQZkwmgOBxINmpU4xC4wgMQqh1XELwuIWlbpB2YJ25z2DrAJqUQDUbA7p3tH7K1Ji6v8ASNUCbFf/ACoj6X/CDiKSsQGaNBIoiDa1lAFBmv8AhD+YTHNNPSHdYQxzqTRFwnwNTe2wFVYVI1wVTaez+4KGbqq9Vcg6ayjvUJn6UtqVGKtP4UYuX0hv2pZTjWHFTt0RPONkxEHa6DZOq8oGUSTM7A7p3tHqSTCrrnVOqRYoNyCqOag3d1R5rCiOakE9VWVS6byCzTAOfpfK3iGUvz6IHDhJvqb22BqkFAekDqHXUWiKZRdHEDn8pzoO7kiyWYolMLiwYuibjBBKlNIk4rKgM9VhHo0vtFGEIbCbEwnTOHrsDune0eoBMBCb0rK3udarB0XSDmpNk4nzKDiL9bJvTqoy7poF4XSsVVp+VP8AuiXUEUrZOJ4jVHCO1bI055q9EXeK5pgn0h3W9cqBqb22B+xdizvqOKxvOalhmlKym/6bLE7mpE95QHJE5EQFyJsquCEvFVhxCUDN1LTOxO0VKFZlBsJzR/TsDune0a7T8qIVqf8A+qMP7pvf0vlAuccQ5ZKWmdTe2wPWI1d9UclQTXnCBdbMfKxV6V6qTbv1Uzvd+ifTIZqlDSBOa0bcm5rHhDjXNMtR0lYcIIxTiTDUkZE0Ti4RJ5642yqqrftDFE5IxE57A7p3tGsDSd1H+y4Qpgeoz/DiOIwn4C6h/wBkWjF/xCitv9l5uvjJQJjJWM1RnFH/ACjdOwzMoXr9KpdlKneWjkekO6P4wJpREiMS/wBkztsDWTyQdBqE4uYRH2tGI4/pThPFhW9RROUriCnEEa2XEFQ7E6rSiZyXEXWzlBsNrCbQVhDMxNeyaIEEx1TgIO9AHwnvbTkVhJgiJP8AutIG6VxDWzMoNdpXNGGZm60mGoi9kYfi5j0HLiCElo+UHB7UTiFVxBcQXEEKi6d7RrHZDv8AvG9/S+UA6Ww6bKx+dTe2w3WRzUybQv8AEeXKASBl0UDnKBmyq41R3rhSH1U4uydvcSLp1xqjVIVAFRWCsseaJz5oBttUACFUA6sWEKv0pt3VwjWyuFcK4Ug2VwqK4UzRRInYd7RsgURjD+yFAaZreqwFYnNo9HCDnkruI7I3oYspMzSkICTHOFo5HpDvsN7bA9IbI1N1Dvrd32hsHVovlP8A/to0yf8Ayv8Ard/Kr/3vBCOZ/wD6T5/tP8p3uP8AKdNb/wAof95laL4/hNH+n/YLRnPF/wC3Yd7R/wCgN7+l8r//xAAqEAEAAgIBAgQHAQEBAQAAAAABABEhMUFRYRAgcfEwgZGhsdHwwUDhgP/aAAgBAQABPyGOl/IsXC8rufC2NBxdd6iFNvyz8uIkRsVj07wc5Cgao1dd4VkNw9Chv7ktCVNXBHj5R2uwCogDvkhgLlomRBjNcy8rDasF6grLwXG+m42gGyvm3DUGzDi6uIuMMFZQbocfDH7UAMxJmDKar1+ICClWl3LBBmilGP3FrYF2tZn9Q0mSt3enFxqNb0/4MyyyC1Qvy4Ph8QWS81RpBMgLw9O8pZVKXu4/2V4a2Wcwk1dQKi1G2V4BcWVpgBQOvxKzKuIMY9o18IrSBsdhhY/3NxTMtP59IGEb3ODx6TBoRsbQaLI62tV4Bu1PoP5i2SSGBq9zYaEPymIAKum2YxQLqskvKbq321FiKVu1pDEq934dsJCxqbpEO6/ENTQqHlsv1wltCXpn9zNvChp/syOc2ry/8AyVd1RiB8pPiCHYUkpKIoLUCKBXfSXtaRtr/JXeumv+QCLLa3ylTYeg6f8ADQ5ncJ3CdwncJ3CdwncJ3CdwncJ3CdwncJ3CdwncJ3CdwncJ3CdwncJ3CdwncJ3CCOvLdbncJ3CdwncJ3CdwncJ3CdwncJ3CdwncJ3CdwncJ3CdwncJ3CdwncJ3CdwncJ3CU6nnUNs7hO4TuE7hO4TuE7hO4TuE7hO4TuE7hO4TuE7hO4TuE7hO4TuE7hO4TuE7hO4SnU86lkDZfE9uT25Pbk9uT25Pbk9uT25Pbk9uT25PbkzAsbrPbk9uT25Pbk9uT25Pbk9uT25Pbk9uT25PbkGzK6K5fKVAERhntye3J7cntye3J7cntye3J7cntye3J7cntyWnqdE9qT2JPYk9qT25Pbk9uT25Pbk9uT25PbkcBomTu85+Q5j0ntye3J7cntye3J7cntye3J7cntye3J7cntye3J7cmdBjdZ7cntye3J7cntye3J7cntye3J7cjq10lcPn+9Px8Xorxr4x9h+XyGIXTHXrNJHYr423q8La2zePkfclGQXTHXD95YaSCjp8H7w/Pn/hdv+Dprx8P+fs+f70/HwBLvUd5iwvVyNVRtbVst/j7zOQgKOrwvgaa+MfYfl8u3pfG5evgpLdusPIYK+D94fnz/wALt/wWwNNfD/n7Pn+9Px8BB2TsHWVYGw1MQFeCeFOkry1tBbRc0D43Kk6my5X5jGGX+iGd+U+w/L5dvS+Nt6vBCdriHpVe/hfeH58/8Lt/wVzar4f8/Z8/3p+PhZzq0SoDOzDU6S8a8rUXQW/PiGGTU/muvrN4Mgt0OsTMqaHz6xQ2Ka717+U+w/L5dvS+Ny9fMdjqG6mZzva71+5oMt2xmYyH0B5PvD8+amzO6n8Lt8E2yPVg3rzdBeNfD/n7Pn+9Px410CVDvVLvyiTp6gku03EorkPrEF1FlvglsQQWNnh9ZuBRR8A+w/L5dvS+Ny9fDWt27aDERMBFjkMsArWLJv7SiKc8Vn/YL5cYeso3b1MHMM6VbHZKMrxF8eT7w/PmWMolahc7G6sZPg3+r0LFdtPNxmsb+H/P2fP96fjxqRYNkvocDrAW69dPK5dqifNG6kVg4ZZBYm5e8CeDwKIbLvcPcMhbU9Y4lTO3fhiula3PsMMSaSXvKdTp5D7D8vl29L423q8LdwNPg6d1d+DkHRcd1SaidoA3eWBCxiovtWvJ94fnz/wu3/BXPqvh/wA/Z8/3p+PEkVDpuZlLu+OP3N7j3rjE0q7O39U5rJXWt8wnMq8he+fqhwppRgUrvzqUKiysU3Z4a+pL4C2teT03wMNiZgvms/eF5AQXWXUyrto9Dn7rKrN83PyH2H5fLt6XxLkbXV1g8OXr4XuN3aXh8HWSuAISfDMu4wBelUzcMlq/LUQhp3Ma6w7OAV+e4EW17K76nWFZBpbpU+8Pz5/4Xb/gtgLa18P+fs+f70/EOsh1WJVZ8OqIC2wpxFs4MYpjzVAhrAzNlDJiAAcSjpFurTND0eG0uurG/HS68Qts1oPgH2H5fLt6XxLOcm2M6cy89JTcG+sQabqvcTFaB5c9IOga8XMwVC5JxjGIV6RNz1MwL2uYLNwtbUCAcLb5WqmqhlMPh94fnz/wu3/B11Y38P8An7Pn+9PxEm3OFjMpqih0uv5Y+lg8LqAcEfnCdaZzN4eOjAW5lZWJphLKrJH3/wDkpm1UBkANrBxFV4zLhaRb4NQHlTqBRR4YIulxzc1m61uYQNYXfkPsPy+Xb0viq5izZ1bmvvLSvbOYP9xLuAZBtMfqFagPr9Yqxm/nb4bPurmVdbMqgkHNmQF1TTVxhcFpvDU4078PvD8+f+F28wtCBzcFobovyNQLQEWGNClsvOZnKomqSs0ZmYOHJq5QufcSuTVfD/n7Ple0rumVguNRAAol5vialZrCjcsn6DiZRwadYlwXSxTc/wBiYnyvivA5nMqGFoYZznwzpiBLYFtQIi+NesxJoyspWG5m7axBZqDFc+LUhdkoAa6/EABox5D7D8vl29L4hQFJsV/cynCXADAxmWW1lbov2xA3jOXsiLnYGY+hDBUMt0xMk6YmS8GJn8gSnOs0o4z0zLwBn0zaP46A4VS9ZsHKqOuj8Taq0fn5/wCF28u8p+8o4al12d4KpRa2c9PIeF1NkQoAymMGqAIAAaG/nEFMdpbAW18P+fs+d7ymhfyiva9pVP7iG0nTe/rqBEthrLmlfyynVG9zNLqNO0egtH1mcPTPBGJBOOan3n+SvguWYtAOaT2ZJ3DUyo4cpKMLWDxM+Jy8vGp1eJUzt35j7D8vl29L4tfqyncqCCy3hQan4RqOqTiPK9ZtvqzP9MxIPb/kFgcOTDUoVGlZrHWC4nKfJ1jCQus3AFBWT8+f+F2hO9C4rep05glHKrWghcBqGL8CrFT1ipXfPgGys1NTM1uJ54N5alaxTC/dRa8eurG/h/z9nz/en4mgTNbgUouIKoAac8wFOSJcUYJNrqMH7/SAMc4VuGxF9NCcHSyNlu0mWKggdNG2Gi80thHiPk6zLLq+S4tZBdJliXLWCEYr5MUXTzM1/l5z7D8vkurVHhiyepXn4jkqKkQ0pmvaBwZv58Pt+hNf5zj9EzY5vUyxwnqi2tcekdMZDNJHSdDOSAaABDyjPBihe4JgUSzpnzCxCtZvUvDmqm+SE5oUzFLOVdVVBQNbpOM3CYNbfr4/R/LwSi6FlNMtFqwqcZmGhgvvWvtKRqVqPrbiHUMO4148/VfD/n7PkcsHwD7rMgX2UfC+DePxEgxBza5/qg+pTr6TGFaYxuCaqFJ2V+J3Wznees/yJgNjDKutFscdxVGYK2HNnFyjlGjYRbW6PzTL9zq+YF6wJxECQjyxUwNNQlqRmHUQ7yhVdb9fAPsPy+GfTdq6v6S4LwtEEr5a8NvS+Hc6jukeuRdwJ2kZIm45agMWCyAi5LrmJEFuElrKC3EbFxglBVjdKjdOcvlMA6MsZI8ugKefWWDxIy0IpgIRVbeuO0FHVVa3QViNXPqu29+QW/SGYlrVTZz6nh/C7eTAeeTrECzwF4bMkoHr4nJO78FApb/TLhCh6y3F/LMahaAdaluor4f8/Z8gBgUeExzUdW1zr4fen48nIMtkwnaUQsfwnQnZwlNWfuS3XoEJF0Qr2esMnrOn2HpM8NM64zDWYtI8wvoeqYDpynFTEi3LAy76vgH2H5fCyyX4LeE4iBTyVf1M+G3pfAQNKZ8K4BMH6GwK1HTxM4QNhnH1fxNgDVDc4dKzb+UWjK2k4n1P9lkrZ3nMVCvl6TJDI9BMq7JHAcQRDYYJqjcVGbK5YK30lVLbU51fkuaV+SvtFbgqpqfJ8P7XaGeyClcXu+cRRtIMMG7KqziruIIw3fRf0lpWp2FX38cng5PHBuuPGhZdXhzmsb8j0aSS3AW01wG/rFbNF6ry/wA/Z8l4QV5rujEMuNla1lvw+9Px5FRcDtCzqCqHVj0aWZ3iBGsuspZnG3UUTvZzmDx6VYplli9aIle0VPKR0lOg7kCaUe0ug8dZLS094wO8W/APsPy+BVIOFLHDLiMhV/uPDb0vgbHI6wUAtoRTsBsgCzzYpRO7kjVcFucfV/EpLUqmb5p6xFjsZmboNWmfzjBhWzJmo0/OsF57ft45pq+YiEvRPvD8+RdMBXVxflDXw/pdp+SjC6Ea1AqQXeTmGqgOiBQDoIaOWu3hpZvKDZZ4G3WzMPWUGbBLU5czQeg8OcXjyd1MQIKGCjEACjXl/n7Pk4EICAQrkl+UZFpf28FJbBYfKcITujHVnE2pVapa/ePCi6LqDn7xFKCrGLXg+kovrTcY7AxnidJhusX0imuzSMMIHNzeZe53FGMSBdFTDvMdG1TG4CYDvJSN2ptgqy7rEIRsCtwGAF1ANZY+kl1td4vdQtSFxncjOfKfYfl8Ascvreu8NADVUK+R4bel8CvDqM2ENXxKHhusR02sZcSwR15a7Qp+u8iNsr9ZVL4YuLiFWHVFrbFwO8PCPZr/ACAH9D8Qs8wz3PgGjNCFX97dblmoA756fiVDIDHVh2SvqUPIeDo1c295mLebD+PD+F28qL4OSY6wxK+k9Y52vOGC/OeO7qV4G/QjJZzgAHzEPH0Y15/5+z5DaC1aklhoAC1jvz4A4oKX6TBnotYxUEdmhD61+4fdNbGYSWMVFqsgbmooFnKAHZyLFjemVOsEC6utDZy8wlA1TmIgKt2IZW2qhL2yoq4ahxFaGTcBaO7Bq4xUcXD243yjQ1dDDwNSsSmNrbeV8p9h+XwaF97NGGJjm7LHyiAyDkm3peQKi2/XHpKzVvNMDzzwuXPylRUtFlst/aY/LuLxMJrtuMQCAA4Jja8VDRSDYRyiZRnH1fxKHjZuUX3je0WD1AI6Y2qmFNbHtGeGKBywDQLxxLMu5TI2zQaJZbjlO9MSMZXDN2YhRxoUvMsbaql92/J32PHL20t1dur4f0u067LA9A/ZKmRtvq9OhLCoSuhn0w1GiVQB+05q3pYi+DkiGB9GN2Ewr+iWixxXMvFieg0vSBhYq5SDgrBVIDgaI+0ghp3YJpEaA1OR5q4FFHn/AJ+z5BQt0F/CO7LemyvAWTsBziYg23yztcVbFuZrLLNRXZZ0h9yzSZq8xliVzgp29Ir9YrUKQgrTnUQGD5wiqV3vuhQDAq8JlqDVlTFWMvNQaSgrl+E1KKYyhKPGYQ2nQwCXXJwhrfwAfYfl8BXULZf2/V2fqQUCbel5B6CkUKrX2JrSA3OuK5gaK58GCWi6jnlRxHGhu4RQ/wAMM0Ba/SCtGgwMprBrAvMxeanSoY5TnTEVO6lnU+U/lyq66zG5gQt4cyimlcZPRg8huOrO894cZw2994mIZxzznP3g0tUffyZJVdYLmAroE/fw/hdvAfKc1vmI7K2tzkCziYgXuIIfu9YFfVIgS54ZQ/JLNNmKZeZc2rB8iLBWrWNSpXDVkHtRw8CUdQ5cxSwe8tQVqmMCl0bKSpzmrZZ1838/Z8llicMVHSYCdi7aX/3wDo1F+kTpoL+iGHWlnVxAUlPLtz9ptQ0BsZQsui2zEXSPaI6zZSdYXx2y1XaK7g4XJF6WB6wjy6qzMImi4fhFurzvszU/VnNbppuWMlLXMwJlJbbMpxOnk635z7D8vgw+YWHM65I2UCY/H08NvS84CmIP03r4oChzDC6pcDDyijrC5qVElJ2o8wtqwGe0LH9S5UyHYsyBBaHQmJ5VlcTSgLbmRexbc3moV2qcjFaDzEgNFZVo5h94qLf6ldhVq6Vno8lfXS11T1hqrnMg2Qv2XKuIcHNyOSFSoqczPKDeVpjE3InZ6sxChxDXSZD8jkg9QTP8KlVzXs6zI/llgaW1W2CNLEspiSBYOO8RDBetRuWFolaJYmFYTLObS6ERRVCZ9ITA1z3Q+yKrPEpHa+SqBCK2svl/n7PkxDT1kw7slIqi8eDHJocdodEOFtdag0ilVdNYi7N8FOS+ZjpQsTsQ4dLQ6LnPy2dZvrcksKV+j0lZ4FbwxzIq82uFnAneWMUVqbdsJjrUQZixZQJbBgNY9Ut8AwYJV87ZLGve8St6KHW/OfYfl8M/t1RuMWtDTZxX++G3pea7BbqH18pkiHanGvR6xgU9/NLDtGSGaYxLVmVW8S5FgueuCYNtZx6TmQRNi7BcwS3csuuKb6xlEW49VuWcst1x1dZYqAUUbYICtsxguwzv1JYlgGjGw5mSmq1+dVAw7Do8gG3DNWJbHgbvmQJklzU/hdvHTDmpjbHBidJ/F4WLdjolf4ItBc4pxbn1E6Wpt3BHTGhJbIm13vjMCMcrvKPpWHmGl98BLSvoEyoOaYQbZ14gV3cI4bdYoj+3GEZSZAs8CKF6dPQy8Vy4HqcemIeRhUXfkKgrc8UYNYH2mE1acfRDAorqJGR5AGXv+4vMSmVYqX2QoM2lNena5UVaTmal9WNM4ZINLk6xHiNwa0tsvmOC9xajjIt4YGqB6oZ07ZmI7rQ2QuVsoBPyec+w/L4vTLOnht6XmQ+rHMSrV6GYsA4YQRQly8p6EZi1EZ1m+DpCOKBYDzhrsqXeaR56EaYla9xpL2Gad6lo8WpqVC2Ks47zSAasbkCjvNS2VUahroTTh4RMyytIGuC4nFMLErp5Ho1sF+P8Lt4WVTTBXIBQLr0Tu5iuLmT7ZcweRaujjwP/AJxGqCHdMEFSWeI6lop6JQRrVlpEbz1OkRA5OF/LnU2wqxdOdLNgdXaN0C6tQruvDMajHqdRAXdVggpxjlLd5Npis0H3+P8AP2fMYy10OomaI6O03mtZXm8/4ykiOAuKfxj7yhrIFGs67RF8153BWmOqKlW7IIncijaoqKYMClhorEXDHeGJeu026qsLM5Q3iMxOmbhyNhgWooY0A5unmHhAwh/mRACgoPBAtaIAtWeQ+w/L5Lm/pfAoFaLljBzhRDZ0UG5znFo4lhaqlI1z0SgRin0MyoUtKlspXBuCDg5g89nXA4iVEoI16znd4DrKviPEFA9I0RK6ulnPMtTPeOtfqVDYXXkv8wWpVM9W5TrBFBLN+X+F2gBI9V4IcobwnHVEM5e1plqXvxNHQuXFeqkYtfBWOY5sHdqcTItefWZXM0hxDC6f6iV1Zwls6v5wyuIpHpKnyt4hQ0Nd49mi6krh0OiVwFlUMVLh6NQSdtHB5P5+z5/vT8eOStNpTFBjd79c1DewKEQLwZXXyltZQd1EswiCU7XmVxnMvRLt5qG3CjMAib3zCOHSMi8y7mAlPQ1Mldp5Q7cXOOJegfyiXY2rp5D7D8vkfL0Znd9CrPwEVv6YKRf4ZdY4cY4hrgMEeQ+2YNi2ly2B+W4Xgz51MKtd5rETg44T1BlpyC0XcwIGyWh+UOPaKzXznCCZFOHeN8IPotQuIKDJhFtrRMVTdTBDUCTCFuUWsMJ/9Y4YFgdW8w1iuCunl/hdpQ5KjYs5+hM7rf1oVRY6wA09Uq2/LM1F8nEbRi83GH4MesNG6ZppgmYDLs4RQkNwckaPV0nIqtgBqawIM88w4LFtwy6+vExGDdwLhy1Hsul6+X+fs+f70/HgFBU1iXh03b4HJmaiCYAgztUZ6Tjhl4irppx3mXMYOCRtQyjaIH7hASs0xnZRiAAeKQZGdw704u461sG7ITaNY5h60KPKfYfl8u3pec9Fcd89Bc+HUjgOswkBPlL5cHSXV8nmJFEqmOuZoziZLszDcQGNJyrA9YfwzR98cwBOJYQK+ifKENPnOBtZzMED98DVBd3w4tz86j1tWwdr/VQWoFRnWSv989zq/wDKJBEWb8MTFdKndEvFpiYxpmIhBOIXSNh5l+ymuuDDC7ESLrVjH1Kf+pbkYeY0S2FwWhS6h0RprHNalqGzHJOfug9+HmACWbzENYVeDOlva2TGNKZwi5iulE14ZjiOf1fP96fjyVq93kOSJYQHF7CAwS6nDMODYcPrCqA5Zc4KGopVjT0mQeZbh9I1dopyXHLIppL3m4CuDuwQ4+F1FKEznEwRE3R42HPkPsPy+Xb0vKrHpKAndjmohVacDsh1kO8vq3xZuJhWAEp3liIrZnmbXC9wG6aNyw13p6y+nEPCw8VMsTG3bZwnTBrTNzE2raK0TnM0nK0T0R9QYj5Z/MHhY2vmjUuEOrK0uR/EbviF9b8/8LtKYrqq6RswQ8tZdiaSK6gcXm4rCEziCmPLdpcyU3moWaktLA1LBsiuOkRSgoeg5gZ29jAJTCujpNsLKrq3rMg8OTbFYBXOEwVtNYSsmph0TBByQyxc9Ve78n8/Z86wrFnPabcfrMOt+su5w9YGqi8uTKtr1aY2PRthbitrnW40RWrq8jdQKBo5s0TEN3a1FmBxZxLhRt7Epa259YIrKDAWSQ++I4dy/wAlTUC8cxJBwZuXKFqpjEqOQPSo4UI7Rh1v1mc4rGYqICh13MOt+svsOtxLAY893y7el5b5F/UhGUcpAXyIhJii2MD2TKvDscz0tgTquWZWN60QxtoELwUOMHQs7JtaqG07zG12ajtzSnoWTcKaCaDf2iIFgDFxpV9Bz/5LRHd8HRcWa7ORz38wVVbC7n8Lt5cnVq0E1y22YTYtAk3cpanLbcrUvVPkiQJmwmoGIXM9ArmmB2mFEwmK2lMusges7DaPWVDclpzcckBaeZmo1CrxHCaA5+35jCc+zr1gpe2EZyGc3cxrdLiDessrw/n7Pn+9Px5ctVsGLZ3AJWwcQm0mema3iBsOcZloj6ITUdYK+cvpXPu1HAhhe+YLI3b19IOI4ETAwscHDfRmdH3O3HMSMRWDj0YB1BUb2SqRApUUcGa9fMfYfl8v4U9TNts9TPUwNkX5nqZkVwxAiyWZz384DhbKYZdN2GbSNVZy3GD2FsQkoDhcSk4UP+JwqMBG866IqTFjBjrNwAqkZjIbwXz2h6ttfUgCjO6rMZkZDcWLE3wJt12MzMPHUE4jBGJerOe/mr3aqFJi7q9TyhAqCWrdts4AKdzfWHF1UYtWxxctFoxefSKRfJbJascb9aJjUjALqWaq2w6F3ELzDy4iZK0t2S1BFGISXWBwPaAPR6ickZUi2gaa2QBZLhLDJnO4IooG0EhUOdMvqi+nh/P2fP8Aen48+fWbd51Wp0YqVATttlNfkmbBwmXVEbCzNDmYWGghcwOk4Bg5EJoWC6a+kq0BWnN/OJScw7D9ZbMcgbf4iWVTBXE0iiDMeCOVkqRwV5T7D8vl29L4BDTVXSdQhG9F95xJimwPSNQoanfuTtDdw/epaYHjCmAUdj9TFo5dtUm43C8OLgI/4xCrNAdqjPNxpTYu8yBeF9+33nA2xbqlAMsvDERRaoWj+xBFBtd8nH3lZ5WGnC1iFDYPd6KuNcDQBtVnn/hdvOy9UxAgkvyyLYZAHvABKitLzmNUD3BX7iO4ggPBQpx2zEXqt/pyyqu179G4L8JWLrnpAsimCyEAR9HFSvzexBeLaFvH6lcpOb/DMZaDYf7hpXRHiUadNX4D4qXRTE/n7Pn+9Px5Vot4iHGXRuWlzT9491pXCGnoJ6567FmA1qbeUC2S1kyK3cSULZTjvAJXO3L3lpQG3y94Ur+CrXzmATOfKCXRl6fqJnu9OrEwNwctw4rMXaSlRV+U+w/L5dvS8+1OVJeGAU69pVmOpvHWUUKuF1iYdDxNbdt3OtfSU5IbNf8AkJRB23ECtA3/ADDdMFN8MoCAVoILotyS0f6id2h/Fx9jayumeJvxDFvs7ROOItoVPQhscPrAAOonNM8tuf8A2J4NkxwxOqcG9F+f+F287ROHZUs3VmrrDEMWngz3qGuB1wjLMvHQHtK3IpZNPeNz84oVACDDCssPVn6S82rwNRqPsCyYyrVjUXKkpUd/zNBOryJY3vCi6ByDruKwCJu8+IA50bI/n7Pn+9Px5QItMUJbdwzk9BU6eqKEYpNZ2z0ljyS23z3NMLq+DvGe1OF1FwAxqn2i0pwyDh0l0ge8fOF3Fw1uybHUiBlxPvRUwcw4wTZ0jYx61eJqqnWABQUeU+w/L5dvS+AuMBsYlOJbhA63SxGACrtBl9rONTaVNJtrrKkUNUnOM/KNQG1PrFUpaDo6xRqu7KLlAMtUdkqVDiFOekLaQ/qigAsxjyGV9ZZ1gXmLKcE7BirA/wAxnqBzuIXTeT8+f+F28xsTwnMNZljttCgwK9AuKSH1EzFNq9D1mw3RZJWqVzzKDPXTICrABohuu0Tr0Diu8+kyOkoaaWl/zLM0FHUll1rKbvvUycrQLuGoHockO9WrtfJ/P2fP96fjzblTUyqPJ/esuDTmlTg/Du106SgNkwr/AMm3BauUUhQkxo5daVuEqfy2JZyBThG6qBAD5B9ZWEXwdpaULZWW5WhhcYRnClPOfYfl8u3pfAd5dZLjZIRarjMCHLLCqhsWfN+cyZFSDVdlRi+IQZAty4lLdyp/kEdCvNxmLRt7pMpK5ehC5gDjx6wHiDpKiIMl8/WLCDxHCopUnBdljowPzuPx94NV4KvYOZb6xoCsY8/8Lt8AsjWhmRRsIFZqMUfpP1ltkAV2j2jKaouPJXzGYazI/REwefMIgWpbcRCWXcD9M3CBrOFmMxtjUFdCBw03zEQcg7RZymGHl/n7Pn+9Px5mGgrWh4lqFYX+JiPxq13ALd1qqelTM7Qc12ZlZsg2GGSClQzE4ibMUv5PrL4ymRdY6QqIATDAuxxnippBrr8A+w/L5dvS+DUiyJFxduqnPPyMX6wBstXWYJlNpeXP4m2N9n2iFHyPWpkOfQ5uYMhgcxS33gcCJatXR+YTGEKA8/3h+fP/AAu3wEspl6ujV8S6CION1OP62tGdSozotxEcAbVv9Rs/VbhJiyKayYpKLq8xtIAz/icRJVG9cQKX3QO+IYEhd4x2eC1/eV5f5+z5tPU6M+9Px8BBKdSioL1QGPkR+5DGwLesJglKUree0W9sWqOh+IRCrRth+Udsaqg1NHp5+GfYfl8iYQFoub+l8Oh+kKtM3HDi80jnpp469JTl6HcZe1AWcQQJs0/aUlk5EKQq9PX4P3h+fNeyKcXP4Xb4iGl8CKIApNxy7JBSku1KUrHL0qXlQTLH8ylGxZcj/wAgPhsycoWEMF0ZWKcZXn/n7PmbCioPRzEsisy+nwkxBrqSiNHPMPMO4NRXlwXmYw+Qv7wAoDoz8Q+w/L5LQVbJ6VMhK6B8SsWO5AnFdnP6xFu1WX+JVx200SlEDofD+8Pz5j3Vkt85hYzqg6nxkHcFocbqpzT2ta5l0nqjJUz2Tqt/B/n7PnFs4be09kT2RPZE9kT2RPZE9kT2RPZE9kT2RPZE3YxqPZE9kT2RPZE9kT2RPZE9keCPZE9kT2RPZEp2w6e75StQFNz2RPZE9kT2RPZE9kT2RPZE9kT2RPZE9kT2RLPVR7InsieyJ7InsieyPFCPZE9kT2RPZEai1TB3ed3Lqn0nsieyJ7InsieyJ7InsjwR7InsieyJ7InsieyJ7Im7WNR7InsieyJ7InsieyJ7InsjwR7Igqx0vZ86mwnafSdp9J2n0nafSHESm9RBeTtO0+k7T6TtPpO0+k7T6TtPpCSqB6T9ITtPpO0+k7T6TtPpO0+k7T6RFZD5TkE7TtPpO0+k7T6TtPpAGivKg7nafSdp9J2n0nafSdp9JRqqy2VMF43Udl9J2n0nafSdp9J2n0lBUX2hSKzvWoisj8p2n0nafSdp9J2n0nafSWx0dJpp0gUun0nafSdp9J2n0nafTzoOy52n0nafSdp9J2n0nafSdp9ICVKHaVGCn5EUADcdp9J2n0nafSdp9J2n0nafSVqV1WpguAv6J2n0nafSdp9J2n0nafSZoFek4Bghjf8AVKsB+Uo0Hw0splvAIq87iEvReazrEwANWekyAVeHeq89YoEsz3iKuhdfj8y+tS9UouvmzEFdAFnH8w0l3RvyXFzClL0Y9sCi/lLhYr08u5ViVdDvOs6gJLIbo3/xGbClblVZPd1qUPjXTfiobZcvwJiJmvmyikqKY4lX0FeZahpESPVVmcWHZ/wm6I0XeEMBsMfI/wDd9JUBzK0aE7BOq+EdtiA26MfL6xVV+TGm9QHc9HpHEfixUqHVvUV4sdTLbf4hnIC8VDUEVTkdfJDR/wApNoAtfRiXAC9A9iUzIBwwBrM6djPq5lTUwCyVb+Y4wzAdeZkMU4m+kAywH+TL4toxoaujqNQFLDOqPvErZDFxnvFR/Ij6D/z7waFXJLBodG6biIEbFAsdSzfbruH7iVWLi6ppPaulNQ9MCMrOXu6KYcg/2YoNADij/sVGI4jfctjgOgRgyaq+v/PTpF54emJiaCwc29ZcU2rKJRKJRKJ3JKtwSvGLv/mS9ynSU3I7pWwXtCbru6LuUSkq5Up0lFgrsQUABRAE5N/86DsiEpN4l8FQtw6RmwzQPylEolEolEyy4xeH5QUHkqEQUBR/9M5JkmDFg2GUf9NHnUYOhRs3qbpmrO4ETXFzs+Qf+t0wbxIpnE6z1v8A3lAtwEGSDboldVbVwa8aWWmB6MCAFyQYsaL35Nt2soQf5tdlX/qtTaINH6o3v6V9YOL+WO3MGh8z/rdMfvNQTROvJbr/AL2NECBzbMTcmxBpMUt+qVy/T8wuQNkFehn9DoQ1K5NKuL7eYUUWnH7nvf7T3v8Aae9/tPe/2nvf7T3v9p73+097/ae9/tPe/wBp73+097/ae9/tPe/2nvf7T3v9p73+097/AGnvf7T3v9p73+097/ae9/tPe/2nuv7T3X9p7j+091/ae9/tPe/2nvf7T3v9p73+097/AGnvf7T3v9p73+097/ae9/tPe/2nvf7T3v8Aae9/tPe/2nvf7T3v9p73+097/ae9/tPe/wBp73+097/ae9/tLlCDp4nWxXADmC1ZSXWDF1BXhZfay6/6sfC30n8ZLe3L+3L+3L+3Erw9Ihavm4y/tz+Mm5YW18ekG2pY/LzX4iOvCy6vJ/xJQBbrFSJTOPifwOr45SwYYdxx9RlGyqKuvT9Tbryvi81CIDaujplJLk3rFVn7xjUCIylXMCRsx3IY5tglMAMmVHolwyQIg1/GIO9BK9YF1uuYNNws1Ix1axeltgjqYZks1jF7+cFxgImWr/EzNK04oFwXDO3oLqF1TatOn0gqKh0xeoAqItoXM6LY0jv2giutkrFyp42sVi9QUtlKxtx9pVkrult/qHjtvk0yyXLJZMX1tuCxjqRZZLJx9Px+wMpW64lTcyzewpmRyCuCV+4K0NR6P9XGaBYx1x+5nziz1Inqyocrtv7TNUAMrwL/AOQAfJ8Ytv7SgRzNXUlN2CY5tv5VLrNPvDP4gtAluzf/AJLLf+wfOUCI9TGsykhQ6eG/8hmbk/PzaR+xTBFWhWx3q4OHS5cTNZIlHBi5gvlrcRabvWF9CVQLlSPrQPS/sljGp5nSHW4NRSd5czReiquXAmVozzG4gwlTFYhdLesXOkOt+X+B1fHsQXO6D5E7+lx01DrxATUR+e53BKze9wEoql5eJ0bFHPWIKKrb9K/ExTKC9CKYNUbcGo5QYAZfWW7iXblmHTZVfLUVQLveXncsM9tuWUNhw386r8QIAJVVl41AWgysywEm5Z67iiBQB8oEoLNGYAqj5oAQHigwCNMBTbNZnEKoN9NTSZKD5PlyQ1PeHtZHx4+n/j42+qvAA0eeq+DyWBtZLIqjI8tXGE6lYXgmaorVnZU73IusmDv2iV8lquq4jNX+i4GOUGujcUObb6+Y2D9Aq83Nn2taYB/ccBCtDdX+49nKXHFS5L1KaK4qKsuaGKYpP9gc3bfoT/ZcUufoxUCgXdeT+B1fFqs6m5m4dcKcNTGl6PChshTrEU1SzsxEArqrnpu4ZhX1CNAwuSZC6jgyOBbUNXv0iasbbOIMr46KzeqglDqlrq1+ZbdWywea3U4vWC0Eka5a1BC0qsm8R8rBrD3VwQKUEPJcsZeKazU2GGz0bgtgOlo3qHuCGjIXqIlk2CtszfmGsddTd3lY1NpWYBlnUTZQJhlu8V8oBuEs+j5MpPWKy/B8ePp8M9fLFczaJ02Pt4UtbiJkLkXxj0m/gr6zcH1OjKqmpUL5XsoD8RRtNjBwUzANO97prC4X+yv6QrGQZw382PzH/d9nMI9KMBo4axfS/nB9D62/uYqXZrU7CdhOwlgFNJ/A6vjtaupbQ9ksKqbjQTJdF6h4Xu001MDptPBWqiThtOSzbcU67vPWP27g6lTBWRXbp/hG2QKy8RbpQN64fmK9AA9VNlxpkEjIzuBJSNDjoiqc7XnrMgbjPav8gYGi2/jEy4VIb6KiAPzOLuoMr2s5zv8AMw1AGHdalLmgb3UyUFc9PeVB6hvddZVOEsKFNXGYrJNW7Tck1ks494VZ0C70yiVKllzBgAqURJRKJ+L8Dsi2SN8x8LH5T/u+xmSI8KwBiNTBkeTT0fzP4HV8UHo7Z05gg9niIINy0Z5/4HoIMOJoYqOb7xK7OFPoWwXAdGGDAF2vHTc7/K1VTE19LUrZu61LYTkzcsgX6PrAugKx+UZoTM6eJ4Pjx9PwKD6B5kBVQTgU6PkFpFQ9fKbZDvAFqyC2wO8FtCdvhX8P7GJcBN9Jlf0U6hmgV+f6l6MPFJ95fzPp/VANqnbw09H8z+B1fHKnuHWfJLhmYE80dLjjQonBr/gyB+dKKNk6HDx9osVpXTF0leWhZxNRFA+s7ripFlo5r9QSiwXwN9YJTQ0crtubyVGBqymDExYoWkaD2qEcYlSpUqVElSp+L8Djb0ealBasjkhbyDNlX5cOw+UgKiscRdVLbBlVFDdQphB0PmueguVWFnXhgFSl/wCDmJ7ZS+m9B1ziBoC+j8HSMHI50odoQwWGMO8JnWaKW4IslhX6kxVwFw1OI+zrcY6esK846w0vN4lGdbOOfpqPkd5Wls2GJ9jPRHEQua5wLYEwiJ6rz/5C3sRbfo7esA1TfKjdb4Ol/wBs+8swxgpT/dYrVKuH8Dq+TiF9fhWGU21EMDDdgpmG+EYTFcWHDEy4acnrLb4FuGJ0iWrpuLIJN2JUVYBeZQS45bgJLODSW1SLoBmCRKWjSzMwlS0xOUOQ5QeStCxKwyruMqBUk4p1mMSNj/jwqiwRLPA8Hx4+n4/Bl3WohV0XfkcDs8qCGtZzGFrtQ9fNYOfjSI40XjxtL9BtMZampgiMDk44RwyMZaxq/wAQA0raVXEDy3OryVr6zADmnonVZK1ti9K9kAAUHHh9j56Lmno/mfwOr8ahnSuagIqMFe8pAghk40ZlkWpZRgsOQtjD8qAOFx0rpJ0YD/JnvT3JXK5bz2EE2Yw21l1lO0N69b/cCkAWo/RKFGlsPHTMKLM6hq+/eEMptZXyZiGVwFrjpENKapuhoZwaGJQxfT1mRnHGtMqXVF3K4WVAlRlSp+LLWXsFJloceX/sGTdm8fEorDZC9V+BiVFVTuQXPzEDgqcAxKm1Z8TKM7krSBweZVQU7uGnoJcbtWIjLK5PGg1W11NApwR1Wpeiu15dt3c602vfaoNlBpuaqoGi8Gv1GSZ3eY2BHneszOr5zPj9jLDqvZmoOqQrblic9DD1i0lcvq19pTcv46ej+Z/A6v8Axa0QhRyytxGXNWMRgpIWVKq+QPUuGZsKsba/cxgTm71ctpp371MqQN+n7mYQ2o+aukNcCwqAnCVNbYWFpgbtd5NR61VlccfuMoHBt6xpLWX6eWg0pfg+PH0zJCcKqPpCS4cKgHabajelPlDhBkxavMpK15LStxya6vHjTivgllRQvUb64lAmVinPtMpEwKeZagdgOsXL7AKKYthdVXqd3VXc/K7nMPIL3Ab3cqu8FVJeh5g+EHRfENsQ6PhU2BfjsV8yEWbWZb8n2MWi2K1SYsvmC0NBDaOw8mno/mfwOr/xAUryGk7pXcy8Kd8bgE4Kus1UwXFNtM/2IIeQ5p0/ctssz9Uvo1hk1V/qNu+4VVNzIzyKbn7NiIBUWfR+4UdD5LlsTFYXo/cs2D1XZnznznznziGhd8wO8fWfOfOfix725MMR5gOxDvx5qfsMUu9nJExp2IAJY+Kk7GKLu8vmzJXsSnAytQ3LC2LXD0Tr3lWnBWOlJ/sai0s4c4rrFuUuCs3huVXS8HFd2BGDI46UnO3XXVcBkMQei/3GrWccPFnXvL/N+q8Jly6D6eWwFi76QKA6eX+jny/YxBKdMLYaCt6lC1qsVuskK/wYqvJp6P5n8Dq/EoiHebBVteCArolNmN3LlgXltLwzQj9Ygt7LF63RzHnc/luNjegmcnX6JhG/A9K/8m+3Su89/wAxZ5hW+s51HZ3PWyzOmIjcVV+n/kb8m285ixTasFuv6p0iP8PnfHj6YSAhixgICER383fYv+eFDxe7nJtfCx7ivCsU8PA/VYCy/mmEEiDHBqAzy9rdxDNMC8R3O27UYg0aT4xBduWjUaa4AMscPYR84kfJfzr4KorZqAAeX7GILZJkkrvH2iHS2jG838o+lWKc+TT0fzP4HV+IiIG1auOF2HsK7THE1Tubli2vNc85D+7RljIO7GINuPVxWpoobOIrp6yyhRdYWv8AUDoKw/adWy1s4j5NELfaKWMfsD/YvZspB4tGftHTW5z0XctNbUDvXCIdUDdIWPyEPU1ND7/DliK74crS/mBvqtTMzMzMYsPaF8xuZmZ+LAUPNVubhFoNeavs34otIqHrMRPWOZa9M4SLHms9W5YfrFcVzb7HQmFGlQo3DTnniANjJZceywzEckxxS0dIFbsoF53iBWTNfOcQCzvMPO8XNQ1oyhMdvFaILb869PN9jGcbg37CpubgjVt6tqdC9m/Jp6P5n8Dq+OkXVfCAyzqzPE31NN6fZDIoE3fa/iWNCWceN4vyKG3xG/J/N2fKeD48fTH0WOT9kCgHU81fl/Gw7D4fR/KIJSWTC3v8IEzi1ZPkz0Sw/dUR4Mmbxn/kRQ2F+Q/iGkgJnLG33l8aBLNs5uU6Ka5l6P5+02o7LZ1v6wSsCTDbsgi5KRou/wBxLfcp73rrDQbC7OkR3CrLx9HN+f7GMKWdOsorC8DlUoh325jMXFN+TT0fzP4HV8Qwt0xKxC3jMYaw9KhSCdXXw26a3APIaT7r5gzdQ7B0d7mVHsHj9lyrhjqJx/q4De1tu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eZ4Lv1/8KqIHxc/dZ+6z91n7rP3Wfus/dZ+6z91n7rP3Wfus/dZ+6z91n7rP3Wfus/dZ+6z91n7rP3Wfus/dZ+6ypQzs/KjZAeOfus/dZ+6z91n7rP3Wfus/dZ+6z91n7rP3Wfus/dZ+6z91n7rP3Wfus/dZ+6z91n7rP3Wfus/dZ2W9fniQL3c/dZ+6z91n7rP3Wfus/dZ+6z91n7rP3Wfus/dZ+6z91n7rP3Wfus/dZ+6z91n7rP3Wfus/dZ+6wVgj4PzpIwROCO+e1vxntb8Z7W/Ge1vxntb8Z7W/Ge1vxntb8Z7W/Ge1vxntb8Z7W/GGktUUPtntb8Z7W/Ge1vxntb8Z7W/Ge1vxntb8Z7W/Ge1vxntb8Z7W/Ge1vxntb8Y5JOhB8j5S7rAUdPTPa34z2t+M9rfjPa34z2t+M9rfjPa34z2t+M9rfjPa34z2t+M9rfjPa34zkP4tWjwz2N+M9zfjPc34z2N+M9rfjPa34z2t+M9rfjPa34z2t+M9rfjPa34xGfIATTr85o4oElvfntb8Z7W/Ge1vxntb8Z7W/Ge1vxntb8Z7W/Ge1vxntb8Z7W/Ge1vxntb8Z7W/Ge1vxgFAqih9sI+2+me1vxntb8Z7W/Ge1vxntb8Z7W/Ge1vxntb8Z7W/GPjSFNTwvn9h7P5VHRC26/+LoERwjvXs6axjAA2aafG/b+bsJ/bRjxjgET5S83mfXE7MlR1X/p6mbmZqHBeC6VPT+H3ns+f3/v/AOC48Q9PXWHH8X3j572Hs/gQVoAVUgf3myyuh0gXrEb56xdd0UxcHn9jDy46g/8AA+58O5QjZP8Ax9PZOz/NVtvR4aMeMADMI6l/7hhUBQ2I8b8xwBwB/D7z2fP7/wB//B73CNkcOP4vvHz3sPZ/BAgxpTrm67r0de/ngZ1AIE74T1Wm8j4dXbrOZ8vDpqJV4DxxEEFRSbGP3xEWVUCHjnImRBrLPpgoCUxGxaHfh/i6eydn+adF7vofAMZYrItauyr6v8XvPZ8/v/f/AMHrfbZzMOP4vvHz3sPZ/EgCRidNYRBYKinlrNAeGNGC62LflIn3zqRF6LfTLBqSuypCbNtay5FlKitngWmOWqRGgCxvQ9OuPfsUDwGmddn+Lp7J2f5uWs/to+Fy5cHEgjoiAqhy8c4scooIhFHqL9ji+AjAFrl6BOcB5GSxAnXh5OPk957Pm6O15Nzvnv8A3/hxw+KAYAqEep8zRwuti3ww4/i+8fPew9nxSHPVwoy92sABER6ny0T1BUXteMHiQIJfm10jrAZLLsDuBe03nTbVrEo64+CSAQqLwYYEnCNPgBSsFYyH/cIg0EP5ensnZ/mq23+mjHjBavcdWhG9UNeeCyCtC1etYgd5cndaGii2vQaPHHo5FrttaK0d9Y2dIpONE39cLpgWOhX6N/YxSNXUtQ1+74twnuRvbz15z7fJ7z2fK4xxMaJsh5ExF1LD5DA/hddsDJzN4JU+045s9Pmp2iomTDj+L7x897D2fFjasJR5N/XDrC6YaTV7eOOLzIGw9PkdmCwxlOGOvbGCTAKARdXofTHMXiyrta23d8XHMJBrmTHjCbKrEjtv08NYFBqGpk6a3m+lWh3cu1Wq7uOJ0Gtol7eeNRLsLgrVgEi9MHkavV17ef8AD09k7P8ANOi918jHjEbBCSD5ZM/46c8fDwR9Q6PzhyNgXp1+1xEjmAKLsTUp9M6R0C4JHRyreenye89nz+/9/wDwetdtnMmHH8X3j572Hs+Mkl0NVZo9c4ExgGgLn05YNTUCtr1vR3Jg0MCAAlUjWDt9MZANEAEK7Bh1zqTyoG2oJQrgshTQFMRKqj0wW+RJFBe3XXw4Hb+zEJVkRb8VA3nI8NDw7+vwWtFcDuECq6X4ebhhSrGy1ewKYaiqNJyOpRo9M4WAWyameEf4ensnZ/k41khsdlzkyrZOjx0Y5s+ADY7vwa4gBrra/fK7jprN3fQ8jWRBuV8Xb+McyReKhAvmX0xHwii0X4LWc7mOQUmvvTGkOp1TOFQ/0K2HYG3DMRDiAceFX6Z7z2fP7/3/APBk2wRFuHH8X3j572Hszaf5EH3xkvASgh4TvmpHgci6+Tgl1is4oy9NAeRj+krg6gsrym++IKFYhEjSJ3V83Bm0QLuZ4b6YBFjkTns/TCcO3+34cTsv6Mtid23T4t6U2vDt64AcfBtQRs093IfCGT+Hp7J2f5EwWgcLgUehDo6vpg3WzejRr84jJFSeO+AABSiC/tvEoQqdg8vUzR+o2U4n2wWDoVyr/q4Bi63PkZ2Ao+Eu3BZ4SSXpj4I+lA2HDtj9Mm7dBABwXjdfDPWQgMZRh8Paez5/f+//AIPQ8nyYcfxfePnvYezAVoRxUR4eJ93HIQBh1KOKFDTwZpkQ0H2prhrz+c8SwTUaXOFNjifMD8P0+JueBch4dfTJ0aK1TvvDaKoabc4vgfszi60oc4UNqiAZ1BYWU3jfveKMmqTbiwxE762kdXCIIBA+BtMsg7HOUtRopMHZ0oedwocHQSXej+Hp7J2f5HjEAghaiBR6URjLJqgSAIhsnkcERsrSpScEIJ36YbBBJaVjRyEKeLkXG9FWRr2gQwxHlL9d555p5H/Zn368jb/nrmrvo+XL/nriiGKmtEwGXUCB2Q5PPNneRFWpx5uQ4lKVVVaqvL8Peez5/f8Av8tQ5xVyyAQ9cXkHJCnp8kyhY+Lv6FfTDhgCoxewQbvtjkUg5VsrSPhgQsmiBG0d6vr4YZYRddky2/g5xhStaHlhx/F94+WqMVnFyCynYWmh6GWpoBAA7syNvICB2mk4Y78MoJCDGE8VCHriwqoASjwNG/TDUZEkJZEvGDSRNB6PbNM4fo9H0/PwuWFMh3TUp54TWbAqvXZPDNHfEro78bw0j5YXpNvBlpFEEtc3mL6Ec+GQx6KGV8Dw64o6E5vOQGBVe2XUcGqE6nT4mGE8Edc4HECDyrlvd74TMEB4H8PT2Ts/yFgHq3YG43wYUI8ARJWuGu+kzYEEAhJ3JsJ7/bDnr3N6lB5Rdd86xgQ4eD84qjmphiOAmeGCH+38Z4NM+fL+PpngNnz5fx9M8G30j/tyQ8gTY0IdqrXSYIAoxVkhzZODezIKK0bBtTxr6XrlwWTsRaEeNCqc0yCXDQbiwODiXfz+/wDf5ZojDSwFKXxKeuL5JqtxyE4LrywnCPqCrWheO78keXkEj3154+g7NYhz3sMbWJwjRo9ZgtEP8vFxP2VBz7rnFVEEtcOP4vvHzUyMJaiykwx3DZagCW9Tg1aKA6GtQ6HI6yhPIqKoCScmGmEw5REqu+rg7k0PDv6f1iCjFE88YFczs6OF8k6R9Qv0zybwChpiFDhv7scF5TchO3nmqIAGE1rfhhAjYv2YGKB9aGuvPhlSDpOcXABIuyGdQ79sJwjEgOhG7+O1Cmh3c5xdy7v8fT2Ts/yJMXCN0dZzHrPDDWiAAuiaO+Pz6L7iDx0ye51f+Zt2C+9/GKCXgMo8yL9d54tB8zlz1T7r/rgUmQa8dTgLkzQWFVexjITAYkKNNlGYuDYoU22JoZPpm3qI5DvxkeuxJ0fP7/3yrsQvIxkGkQKtVvSzhwQRM5ANp6TK0oGKs3RSb5vwtozXY4/gh5jn4HiAQL1VgYqkFK8EK/2YIgBJ0UouPGAB0Cb3iKlyByTXBzrD4Smwvyaw4/i+8fPew9uLI4BB1LD75FrUTvfGXIjkaizzm8X7awbrn/uFrAKf1j7k2vx6YZTo0e6/z/cAcSgZgcEDWvY9vPHRuX9ATEolzfpNj0wc5EY6HB9MMjimcEh4dcSovNLIjvyLjqiuz7h032xkRu0n2vnktFFkQh+cJjS0KE/OAwaiONPOBnw4L0O/m/xdLhSZsvJRtOxrJYEIH0PSfn+Q04XGhJZBIi74dj1uGKVoBsBZrWlHPuz+jNuwP7H85t2y/QT84rHlH18/a4YXC18j/szz69A/7M8Ii/N0fnCb5E8A6+v+YYjmkSJEPCO/PJSAGCIrt9XeTcPfA876urhjyVCgNTvkIwo10c/K4C0USdtRHh/eCRnndeiYzqVBzHIhpKIATs12ftkvzEHIaa4Jx4uS1JHRxmwId9fE3HRp5P8An9fDesuokGRPGfTECjSjSRHrpBHsbwgVlDaGFe25jAmtOjqQBq5piIBGLYV6nHl8LjBha0susOP4vvHyVRk2RNXQSzc1rC/IFK85BOzD4FAwTCljOD/MdJDgpQqPQTH/AIx2o0Ed+NP2yzhVEgdBJyh04biC9ZoughYAwU9dhyHqh661gSseUdHvloA1PvpjUktl7U+2FXZytSbPDeAN8OUgc4YezCPRA8mBQHEqL6Kdz75TGiYKDRc1emtGON3v+MUeF2dJ/wAxXwWYd3xyOh0Sb8umdc6QUyAA4AaXBx/D0ISgVv5Dq/XFYaD8U6gpHR9smeydn+NKRLIM7G+Lj8bdMdSdTtPrk39sJHKOTKJ0hk9HhLuY3mW0E0Jo7f1lKyPcXg+2UDY0SuDg89OCgrHnzn7/ANYqQQITUX03reCkNJXh+kPXCAuL8J77ZC+PCAOXWF1/WOoEqO5Ws8p/3KKEEdIBwccvHBgmgmKpS6RROrcnrYLb3Xbi014fINMjor3OUQPFMKKoz14AB8ecme/9/k2PCLp/3BKUePgv/bBhE8C+Xx3ycdbp/wC34OmeANIap4u9+GCEAEBER2bCh2ywOlHQXp3ftnflp54cfLfl+8fJMkbBKABsA1cQ0G7KPC/D2Hs+QCdqpdHuZytKPrhoBNLy4JLQcqD5JyZT0ArPZ3wyElDcI74/OLoHat1z4cYnShq3t93A3PW9PLFf6hdwnGDZQwbyffJKAk2wcjyJhQseXX0PDeIlqLEeXidplnwjseOHF6Qef+/xdHGkxUsAbLvpgsAFF5W0cjx+HsnZ/gHAPAWX4LTFlXNgiVAX6YQOibZnMyVSU3HnOZmtbeTw0ybYA2Fz0y4qs6kb1zZ3RPoL+cRk3jOFge95vuA+q/7iY9AINOVevf64A/SafZ9fzid6N+Hd9DD6haxYgku0tDrz067w2I06qERAHL4Yk9IgbAFtEl46uMqpKaa03xsfr8mxMglS1Q265VHQdQnDsH4IHeD+/O55kVy4KQQvTywWE0NpB03WknNcSwWjti3I/v64fBqooQEXsL7Mk7koA1qPBb584IgnHw9+bqfn1+Pgkr/s/p+uXEvOMGgkezVwJgEYF2LNYcfGa20C7C4mjiankeSg9PHB8FENQ8fL94+SItgjxLDnRcvz3FNjT6/D2HtymUymAq4CuWZVWV3bOh/WTUCBtcpklQ0OjzsxEOw4I9QO2Mboa4rx59fphAYIB/2c9cVIQjpRW+aeeAUEV9T64FNoKOp3v2wRBHrujB8n8YkBaUTa9NY0QmxAXu9+enbFvG3CchPrrXhkAl2xCQH6uN3gy9Cmp9Mv8PTfpm5HHrwuCtsOWo7vweydn+AhIgFnT3dZB0AvdwCNYeHUw1BGjrZ1vhvrlYHFJunbt44IyUxy6qYpwyUe+mXpVfcFvHh08sMXJE2o96whcgjeOQwdnVFBTv5OeDj7XH3/AKw6qkDZX5sxwKG46XoenP0xEjOEejofHmrJOxG/jDUsE4AfvPaez5GzqocHUEx/0EQCE6/D2fvlQRgtac9/u/XAjyAhoOI50nsini88X0doXnnXq/XGofYEMcnzbd3by7fA072g79z6YQpRKfBFdg8zeXooSHmdvXAaBk075r7QZ+cuMHgHTi6w4+JBtEAlq4MDIANHY8MBAAIAaPl+8fJH3KgCCajwmsS+TkIKPAOTp8JBmitQzBs1g0O0WGjp3mJDRALgj6D7M04wOownYUWud4aBFo+AMZtZy5LAJTipvXB4zCwMoFKf6xVl12q6k4GoHTIcNu3rcWB1Ts6328PDNPAO006WcGRPZWD4p31iDQiSdjs4AEyF1sX/AEx4SpAyH32ub1Y2X19MOm0jl23rRN5FuwnSvL5ZrDAN0dbryw1F3RU2PLnAldL5vF985KopgaPQIaenz9CKNpBaISBOFx4dOzIXYI7O58PZOz/AnMNUzngoexPzh4jT6GdTI8E0Idj141mwBJPqMHloQdB0jvN/CQsiFPXeCtQDVTe2ccmASEvbo3QZo7B2gg897ir2S3CHjvA3ATy9B7criQA5DgZIqivqT8/T4c9kPILikLO8g5HsDru4ItoIa0PXteuCPQL3PD2mvrgRJCLWoZri/I6JfQQ6Khm3nETKgKKUiD7l+Hv/AH+W6FXv85nhRfXDLXvdH+5p/XFPJ9OOmbdwfQf+/B4zTuD0dPsnwgzmk88CWRTdupZ64krK5b8K9+M4fHlOdPG9X8fX5/vHySwDUtbz0R+2F8q2c2u4C54PgVxaHoBx1i7AEKNqTbgh6AtqUa9FxxuWSJ1v+zDQ6uAhEik24spl+TLL5lsMo3ReKN+u8nHuAd914XvjmRFEdPxgF4i0RoaW9pwawSWCzSeR776OCuN6g83j/wBxpoWwHF7AVDg1X+sgk8bw50eOWCVhXX18cu1Goizp98DY7Ik79ujmt7fNDg47r2wbZWAhe3n8ClLA9TKiym1DsfP0NpNK4zZTj74hJPpWuQBDxfpjoAhDqOeydn5BYvsIo6kG2djCnX2ABNjTTe2E2g8wkVAdhrvbxjJOQHoiXjQHfFx4kBTEbX69MYcfbVeA+WHDaAQMYdpj4XV++WUhLZrsmD3FQtA3r6ZrS3k+jDRA2PCmtemBAJvDCuTz5xFApmpzu/X+snTr/B2H+4KqCAdInv1xlBLvie/PGQFQBKvL4bxI5JmhHw3vFC8CagJVnBe+OEICA3oA5qcHXAFEnkANjkDXOB7Hb0AlXkAPpm4+pTAFQeK7+SWKc1CjpGP9ZbZ0SA8NIH3w4z2fvmKkMDTaTjrD1zQ9dbQKhKujWucmdAhgNR5EEm++LmaBJhrhepoMvfAAXhFg9nWODqafXxPHAvA7Dke+MXTyeJ3M4nlb8er/AH0wM4TAKrwwm5ajSI9nJyBmG6Xf9GHHco0961gJGgTv/Mpsx2hc40QQHIm/pgz5Q/3+cEECWE+c7eONldMa8Y98IwgED5/vHyVVl2hnOg983kQsonXIPR31nwG8aMkA1e2UnISNWqF3a/YwERVLKCS9in0y7glkIUaTng34eOTLE5cStv5zWdsQJ2cMPH5yeCLBa5P+GLnJzaURJ44jEES+IV65rhvN9R55TJB127FwKv8AEh68mPfft6eLiQqnpvg/bCNaSXapy/XND1MQj/eKQoBUTW/7yOK0wdeGu3XIkkdiF5nU8MZvtII02Xww4/h6JYjEC6MfXMRioCMDcPUzZFgHEz2Ts/IWCKl6ZW+mJrweWJClG01uTp4axpG4OACHrDAkAKqd1q/C92RjtIo6O02OO2gOw8R58YzBUJKzrHpdYQNH3HDINhjDvtPGTJlEIzlsB8By+gToTnLnJgV1U87D7YP6AVHTr1nX64TOgSu3X1Ya19kfV3ygBsBisdeyatRrsOeG0x8MmztNdzlxMRjkJGJDlouutDITcgtMqrvupgpVEa1gPkU8Wh2qwgbzWOCbEbSjsjOeuHGe/wDfMOXC4DlC+TzxUvQUle3ngiDELWwfDL7R4SJhrW8HT/hxWVHj6+J44SCd/gcJ6RNJ0cSkWRKHieWvTANwuoPswIQIxR7cP2ceXcyH0YryAgZjQNMKs24kgWwkTZ4mNIEUUEGouKFUitA7px5GMRdnj032xUKaAy4lKC8b5+b7x8kRyBPEJeDbrXhcEDQ4DyEeoqr1vwauWHgFwKgAwKnjwP8AuPUBVAQKG+Wbxy2qokC+nbGicBNhgr009e+asECUqLOZSXwwwI2urvudnA3R0hHbwTHSihy7wTnvh7IOA9c738YGbsyx+vLm7YRDbuvOAm3NniHXHs4hpnVzi0yWbwi5uYRvYPHwwAmbQOzlxY0Ygrur/XH4xack703/AGBjTPIo+QHW7zMEiJeQJejx/D0Ygbc4RpjV2mQsK0cvLr8HsnZ+eBNf1gNN+h/18EER4cYlQQQC8pw+uFCYtXf/AExAxsjqo477FVvYa8eusjHZPbywQ4UdnPTiYKjG6CJu9NdsRolZgzc8dzIQoI6AdHitPIxJcNDNM13DQrb/AEYAczJyL0zih3L4snpxuXIuyq4pZLuhOOh4Y58wM6QLpHdfHGE6Rl0XONhWtG/DKLzSsIa7iTfl8jAE3PT30mMD/mQUmGyEeCIanS+OOhAUBvGV6rvWCoG394TeBokA4PnkAVVQki2FirhilerCUiTZXwxyK0QVSL1Ap0++Kui8An+mJDSaR6eZl1t7vL/oxS4mwceI8cizuROI7eeAavC9MjbxyXC2ShHkTkw22CRz1Heg/WAmpSEu8awMpNcDV+nXLD4CsmtbxbvCB7OYeua6ERolD9deuLp4g3ddL64qQFjnm++Q9CDjoXw4tyHhB3Gc/L94+SY3Fpl3wuUR/SSqiHGp8NgOIp0m8bwpdsxXYUDjc88DQtCCzgs2jDXPG8D1tgt1EB3pucuSVGhqHAQO25j4IarbVQl6vPfC6ZFeiu52cOaS4ur4PZw9mBVlt19944s/SJ4f7i7gQIHfNOmJGIXa6e3A0jGhH65tFo46lzgMLoY124yhqAHHPOUCgrDst48s3wxbhrZ5bwY2SVXQpxr7Y+1ekd4BwdF6Kh6X+HpC3fIXnO2KzjtJbocvweydn5mmsgLCvfFqSZSw7+GQrtbE/swXbC9kfnKSBXq7J265dPUjw1i+KTH2On0j9OcKsio1bLl4IiuoB+tw5OZRxR0uTmzR0A7gzBaasq58M2hYU6vQPGYFDABtKcj9iYJSQKR8z643ttyQPGuR7vpnydvPB0wTYqhxXo89chdaYI2pw5x1g0ilSoNI3qa474QCYw9Kf2Oe2UwEFCEADqjrv3+TYpqOXZuW24lujYDxzmRkQL657/3+HWMxJA8V4+s5xGUsgJqMYzBEm1Nucu8AQSvCW/7l8H2HqdMvZEdt6fLs4ASFVG9FMA2evUf5Kf5hFaN+o63rgggjsTrhTI2MrJPsfXEwfsE2+jG4jKEBa34HOCoIRHTXR65RSmlDO+BqayG364xgQUIAl566wzBq33T+8ioOtT6ZDGXUq9sIAV1AccJrM0cG+7rvLhUoyugND1n1y4HYWKGQTgucgmRcAGqMOVfp8jYiVuwJr64YI8JnMF1nAkftiRlKcEBfWlwyU1dktdXW26yW8LAgK77814wIVNnMgheQw51gYQ0L31v1xpUKGptpcLhIQlVwnjj8pqAgOGLz3xgWwRuMk++OkL1dUzVAKV39ZiqtCJs3vjWB/Clw0bfS4UAbtaIq4F2qbT6XID5BTk3pcKTDmJenBghUGjazt25wqEKFQDpp8cddIruQyh6c/wAPRx+1evDav5+HsnZ+ZnBAdFtwbzIa0+N6ZupLPYHjzqdcirx13xJIWt3p7d+28UsMvZEdAmtXGPij4bsvGucRghTLG4GYKpUoPHjr6ZYiQeTl32xM1UyoSUOjvPGpAtVkebk7ZxtoDc6cGsYYDPttsr5/bJqpmI3qjr4YsVoDY9f8w2Gwyzgu+xDzyhGkxs0UTImA12L71hZpTJiA78In1wYLggkDkv1/rFioNlat+ifI3IauFTA+Hv8A3+EgEoxSx8sC/pNKdU7O4HExJQGs7UbOmgwTnc5INAocwvnnNGEU0yYBgqO/brZrnvkRLkCL28Tw5ynvHOzTjFN9fYO30N4yl/r5+3HTnCQLAF5AcZXHe4Ebp8H1yiR0HSYtr4C6WoYfclSGgvD1fTCcaHgPM9DFag0VJNw664woAwRSO/jdrhtpt2WQ9cLANmy7d6/OWYg5leJiFQ9CbOTJh+o+WeM12XpInHDt7uBvHQTesAw35zTRcVTtD1MphLNQDRaqE3rpm4pYl2TQ6EvrnOLsoR5O9cby6GUjn174Ai+pBe5vEroJG875xjJVksOi8XZiogTumnE0EUa2C83GgAja92KjQOAuzGZFLpNXvgNm4CkxrHeZ4cYBhJ6+X3xGRui6Z+sL8xTXOLqLYlPMwCbQANHwaCDlWBgUicI0f4OkCC7eDPdOz/BMQRtDbmotoXePDJ/cJoOH65q1WUKCSergSCiE0+GAwHU7L0yE4heYwX0xCylXvkSwJC3rjEAmlc3+stojfR4z+8gQcRnJPZj7nAdTyvIZHxAR2LfXzzkSYXK+E3l+NjxU5+m7cWl6T6Aya1rBqRGzb4F1oBjPirIpX0Cusd6FCRg521xEFEWG+XtioXAHZ5/L7/3zSSLIpLlDcsPC4mVGaCDdfDp3p44ZaEes0V6JXEmIIFDv8RbVCnOsZEcWNcfXeMwhgS7emHnmR1s8/rh8hwEomh045yr8ySnj456fTASUqS7rw7mMKaWuMQ5NKzQfXzyIdl1cOvb84RCpgNehhrI0eg9e2HHN5WhzJ1pry+mLHHW6d43f0yQ+Bsu+fffAcQ1ZB4p0wzQ1gcPgfn5PvHz3sPZkxgZQdbBkvbvrEJRKKdHGWQhDpet/3CARrW7OsynG3FD4tdemDUvWkt8vtgylUp1ev9ZACpNtTIhA0jHnARBE0dsFlVKA8HvWcorohb38shvSJdV8sVKkBqCcPHH31hi8dlYa10zRQ2fIW2TWAYJlClcW936YSjo3SH7wURqCMd3GiogFgZ/240pUA0ED8fP06YwCIIS6dG2h374LNAgfQ9b+Pnp3weEAkVC7njM2BgovLeD6ZuNKs0b5nafSYEcxZhxPr45bDq6aB5eGAgQHQPrhCLIAyhB9phCQDaKXt78MKqUgiJ0uVvJAZivan3temJ0lIKhJzq7+2EVrDdmg6/bLvCQUOo9HlnEpiUW2Xlsl8cAE7kIdQboAVO+AWa2lL59MCfaEupFjDXTjH8bWUtvG7V+2PLJWADwgPGy4pQtUusq3XUOeXCzsRQjS3XK879Pl9/75153RqaeTXTCgwpP6+WLtkgvBxcVohoFn1wYEXZH65/YSj/cSJCkR29HAprGjrtvAAEtPeNYGpridia89ZqTZwmkwnIdtF3pnprGXQdAd/X+8I6oaLY+GbaBLDoTjKb2YF0Y3IVrxi7d+uSZ9CNI9mdMCnWGNAc+XTK3Wl1j4ZvXHvuqQ74KOCqNPq635fvHz3sPZ8KQlC7PTHhwPNrpw7wANcYBACJscU7gd4Bl88eJGJng9PPEOQbBCb6dcWkEM6v8AM3GgGp/zDcATUsXywCtvtn94VQISt48vrklR1pN+zEtDInH2yQIrZNdcedLobTq38eeDBXprT1dcYwIKJSJ1b15w9BI4t9PtfXDJEpnT1wuYQOwfxdPZOz87enPJ1bs9Oc6I0695v4HmFeyX6sB6CAcC/jEeBeD26YG2AUP3wBbpO1V/P9ZMiIhvX69cegAQApiW7AbL0bHLoI7rs8LN4RqJ1x7OtyQCw2gb+uJBybQbOJ6dsCn0Du27rByEg2ArK9MFxwWXVGB2dd+uWWA2UQALt5E5xFfzQqtKOk5PPFRppbJvE0u3r4fOpAHn888KKBZcHEQ5b4xIqzh750B4cBBjk9sTRLhvnKUW2YAc1wYpDwJ5jv0wKl5NNXkLjHQQFnEI8ZeYouFAJ4XHZJtiACPM7+mArxoAge/xg2tGJud8VJ2wbt7f1rN8gCuVNvP8ZIy+B26a9MuwBHg259dYe5MLX259cfqTlFN+95VSEAXQ713v2wBQqTxJ9sTZ0h759oODIdYe2IiQOHjhyUqnb572Hs+MO2bNYrYwdfWYq7yHdDX16ZeSQY3cNeeHrk79AoCKwjfb0zSayEN+mBKIoDrVmdZfrXfhich6CXBZwLyimsKBxRDqvlxhznIJd/8AJjIBxF5e/wB8Y5mBZYdddMNIUrRF8+L/AJhJIiNLwXtrG3CMDQd6ceOSDuRoAapQvp4fFYCBeL1/h6eydn5bvUC6yxINno2lx1jzmE8elzxT4oYw09dAB2wNswelf7xWxIBd+GUCTw7Xrj0IVViHfLxXUcSv26+udz7acDFYYBALy6t6YywgUKaxWiUbAWb5zQk5liXjZ1wuIa1QNF1xzx3zWxSPE64zaWKxXy7fTFYoY3g8bl9beV40idDQ67wZKhjQ7AzrTNGYOoV4HQRiARNFItyIRNaPn9/75Nh11G18e/4xZ9Itvyg9UERMWtE50mb9XD+MCqI5CwKCQTpOtv8AeLvoJrXrDjRvfE65HA0ah0Cul08+OE3C6KvQvDLx3wgCBDCIvRG9euVAKV30F2dG/XWHKno07QiUrdlxQKOxAU6raeHGCBoBCWPZ34GSjASCdzwLziZRfQBOL4Wcf7lAKBpodm6nbr64MUChnqYi4SSCUH+z5PvHzwDBLuk0zb0HHf8AbNN5nH64Sprl6Mc1EugdOmjK96QTqHTxj3qKPR0AnV74mNClbFGus5+mCoYxBpdBvjiY0/Qo7NL6dMTpYhFNuny64OU922Bz0t/3FHpgXX49ftziQzuOAvDvf9x8RwAN1wAawfK2AJpxOW9MuXhIfPwYOBvYaTo9nEM3yffj1o6w4gIRhO3fljOelsB5XCLLhpX8YxpsbOn7YQA4NJ7XtjOBC9b6YxonUdP2x1p9jjICPp18p7J2fkcCkuEs+L0yBnQ9m7r1xlIkugGJcUlOnJ9Mp6h/XiPBKEa0z8YIGTYmXfjy4ogC4CGjwxTsqnU8/DDvQpevp642aVsHPJX74/ggU0HwMGTsg3odHC1MSqcenbAAENxTp6YANga+HT1xzWdQKOyrkEE8A/3GVbEvR55JEKrlyw2wHGBI1JDsAdTXVxZlJwMEh0kZGocd846Rk6d8wDCNo0j2z3/v8sQsQDq4ABSbUR4bhG2ICu0NHVyxJIi7VsefF30wDqULCjc7SPDzvGMPUNTMKEdYUaUIk5G+OQYW3rYRIb+xiwkE5QaEeB0zY1KWG6j37eFecQcUBpTtTvP7ziJJNrqHrYYBMMKQ0vq7RZzgD0Aw4bdb1Wm+MGI2wNG8ne3jyxfQC6UabcKR9OMLTWoxsO0Wa0VxcOh0s7jjipiD4uxnUIY7wzYjaFJJ3W8/D7x897D2fI45FKWTV1HprUxFd6MUekvHUXxMtR0rEBAnJf6xBCi+6WWlvf6u8NRVObdD4i9P8yaXANETUbApPC9M0CA6BJquih5uS2kBC15E69fpmsew0mA6trOhxkGwElA1l9xOcbDULUEKp388g9BmAh0WpGnff1yKOQoC06dZ054wWFKCzdQ6KtOjguwwMiZH0ddfN/5gfyTaIcqa/wCYIgnD/F0Nip1DycbA4/HOp6F1nFPXudPT8ecJipSb3nGevc4N759coSiWBwk7ueMBWVARlDXTwPDEzRtdmOfr1/5lCA6sQNF7u9gd817r3WOpR6th38MU8PAKN0AuGA7hxHf0eOBl6bsEdWzXJL2zqPg7n+p5d8RyWna2Rb4mvRx8PtMHi7nRuDm5FErj6N/ftjRAp1xs2LrvpyeKVUMQ2HX64AMJPLXQ8wxvGoFgfEVyCPfXnnGmsHQLTz3veUaDCujWvsY3hpi26d/m3d7PhluLa+mS/K7uS0jEe+b3QBXRpLrXbxxTCi7pKeCaaeOax4LQA6Bg0reLU4qH5wangpiIh4hpuD9MW0QeU56o+GKEWdapYHpor2mdE1SFxg9ZXHY69itB1qb5uvPDIUmmlRvvWkM0KZgBWHDoPDEaBKLw51y16/jAFE19TnfIQdmMpRShAEJpJTpjiFKQU/YdvliZggOiWecA48HFGRdZd+F4GR+mKgbECsUvbt6TKNqEfQ367x5P8ol+H3j572Hs+WZDAouQGkCg8C+ubmYKUaLU4jX6YELgoB2gXoOQAuXKppLp345LDI37Oyncuv8AMAlnFqwInPDzTtjCWdzCPn3dU7Yo6QAQalY/3xiIQgJ0ZKN1/rvgSX62TLQW9a565oyMRBkHoq65v3wIIq0IgdZCaTt3wdQgOinROO9/zFRbCW7m8ERENiQlMC0hC+H8XT2Ts/Ppw3Tcw27x7/jCIUghEQM24ks77yTeUArvzQFvi5LeqgYK0NJp16mEoxSFARvl7g/TvkhBZAgPMb1ODesFulWorOBczBA0vHlQHLOePTnCxIUm7S7kWeOLhKNgpAPc1ECOQlYfbeEc7day6INAAoCaKIFvhj5PELH8WkdOcpprw2AiIdIxZ64T/uOFJudt885bhrZF1BilrDl2l3ZWPQXvcjlRyVQIA2gr6YswMQFLqe7DprxxvCu0dKk8Th18/v8A3+a8ZWp6lWlb2HwwnslexG/1CYkuwTYVYAmzt1EwiJiLXk8O56zINUNKp23nQ8ZzkdOK1Zdy2O73yH4LFZqE9CPS1wgOBulStDY3n/cSeAAxAua7u5LcYqLqBNzweeFdi3iTXHTjnJhlsy/N03zknmdh3rzpp5/bA2ZmKA10aYp6YDO6qHd4dxPLjBVQCux13XUNXgyyIBQxrDALUg109dfAmKKGxz7z897D2fKDoAKr0wYpvAx6f+zGKVp0vPA6s1kCBDLTojenGSwrlAd7JaGzpiBa7SChrl9fFxbkCappJR4hz3xEC1SiOvNtHevXCEiJVRzE1vFjJWt3Jp1PB+mWonSBO8bNh++G0Q7cM6bzf6y65gAOdrONw9C4DmGx59Guq4xL2pGlTooccawxuNg3u1Ng73vFXZvVdyBrHLFVB1pmvD+Lp7J2fnAWgXQ3qC9Dn6ZpmK4EDync/rBtC32CO14nhjHJSoKqLTz1gE5JSoLCkxVAC3XiCPVEu8iYB3BN289kxVLbCtrzePM74Ak6uDsATbh5zvYBKFS26nUx1BOdOm0G7bcEBFOaQmpsXRxgzaZKpqa/DKml9UEFt2n4yVuoQI+Yg6tvXWMplXF4GHT7+OA10KdDsDp4OsH5ZCuq1312YoK5s8gPHfsZrOEittp9+M4kx1OjovB4Hz+/9/niirUK+j0zYhFYU7Y/YqCcmgBFN9demCJEpvSsd8XWDeYSBEW9WgdeWCCyio01Ug9N98PI74Kjd899ycYKASIotkHqhz0ytZIqVETsmKXGL7V611vcmGspus2Yk6Tvimff8KBBrq9jtgsmbB7GrxOHp2xUElOqhN8BXXrkyid5PLaPZyY01VulduprjLnvSqb1vvj4slNQGnk32M+8fPew9nyiBQRPBxNCQQLpNvXTi+orQoO3H9ffDfQSBTvIdeefDEI3tQqVyuFu82hWCGzgdB4ZsnwvhG6spfLjJsesA7bqIm11s4xeHB8aoIbw7zWwOUV5H16eODSU2sBYh22zx684kK9F3Bk5rdvbtmhMA20EN6QXfhhDUBTUd1A4Jvr640A1hfRN8dHGNBRUpOqcYcHTkWYCEBADR/F09k7Pz6zc6ZEBS8dddsiACQkQ6j48ffLVklUCUGmxfDOCUnCpG78eeuID7a5NDSLrnxyoHFA8dnjkPpm3bQLWlHinhlSJhWsWG8G+q4FneB0JoLpOvi4VxekA5AdXdvhxnKYRBHTSx6a8MYJKJKxDOix+njjJOg20naXZxFwZpBpEvF7Su/6x6OyN+pXN4Rvg75oIQ2oonTh3hUAXcWiE1f7MMuhIMFBFZ3hvFUhyjej5/f8Av80rBHnzTtw7tuNR1dcQAXr3PMqHb8YCjbSdY8rptPzgHFJMFZV41+cFwcLdUsrbEP1hdU9BbdOmdqS8YwAHRLdqRCznk6dMpOAQRAaepXCWwA8s5eW3nE7iODDZEw4vtlgYnG+0nGRgCdWb6bUcVxljooy2y0prWVGxTT2vUnGMJRBsDw3FtyBfM4dlH6/fDqI1FX5PvHz3sPZ8wQbnGyaxe6kq10incKy03dIpXnzcFkKFGiwwFRLhBG2oggEa1zfVzpswPA6hNbR8tYJ6xaiC7uopDHHQJik3F4QQ43vJGjoE0m1YWwN4SQ15cGPpd4Dmoaacq9l0ydMKTqEq1wb6c+eddhFtO2+mANECVtFe8NeuTPEp2/k6eydn+AmdSHgeNmvAMGx5w1Uv0MC/lHxjrmr44nNVG0CES+BJ14xcoIRgpdVJTsfjAKiIODs8gU8+cev4EAHRzAvSYJ0iNQLLw53qeWL4sAErQOZbtpiSJzDAvANQm7kQRFnzfPU1/WIp2BFPFicb3vpMGAuXXQWYhI8YcEgaAFJDrWz1zkxUGxCje6anAZw+NhA2uudhzveO5swtjDg6gHf9MZrG3rgeFGYUYSQthuavz+/9/mwzjBre9GxB/C4DQ0qCBk23Vi7kwuelgOFUd9HD0cWszW+haHTfRw5SxpOtSpN66mXLPBK+GuJOeMQr/bUIthU2Up44Ei8RUUUi979JhRWw6qbJ5nB44UbYaC5FTyO2IumjVEsJY85ctzTDoF3wjy+WN1QCAZaFo6TyzeowkSNkvnvLhwBRZ0N651z8v3j572Hs+YUjw4VC5zXTr074RzsYsHv0XENpxuIXmQ+uRwoIHMIeadXvjiaQsILoL5bNY4MygEHt0cb1PHKKodhRWoHXfXtMtnzgwMtXSjNXviYIwbXU7Wf0weIPEJEQATbzhdkuzZ58tZVdnLNfSTIOzUiz+Xp7J2f4VQl5HAZlN9q1d2nHXFbmrZCZ2dT74tRY6BZ1Dd3rT0wSEmt5B9I5OcuDfSsV6tOtXXTCQAdrK0Q4TbI9MEqIHRRqD5648sD2dv0JsQlLuHfrjRBqHR4LsLccAAgY8PNrXrh+82bb1fx5vz+89nz+/wDf+CTgIkR6mFHIQMQPvrhjbFuxk0+uEqChO8hT05p983cmkachHno9+OMHEKuSq30XOJQEUOhkqca7774DNLoeQQlLx64BoSnW7Hm8D64yDY4hWvLjxeLiEFa0TSDptPrvBj+QexCckD7YOQUkVJBNIO/TOmClBwtvl+8fNGqMowY57n2/wIhFER64QwXds04q03vWBZDPSLzRk0/VxoAoUAyPeFXs4ODDSAwLtv8A554SnJNq7Ve7oYTGAYIun6I+HfGlyp210h0F6eZgUTmxVBOprnAAgTIfy9OVrAK+me6dn+J4wQQge5Nrqb6bwh1CjQDyPdNSfbHxXCSuqGhrtrrkrxApCOhOpvCFnYgvp4befHB2BAUBN7UWz+7hO5dCdW9zVNamOxAIS9wfw+89nzDA9iRT0z3/AL/x4ZzwQwQ1NU1rHG4qUPRDp10eHbH0kQhXm+HHe4RpOqk6gzW/cxToBqqtdG3aYMfwlGm0/brknpUFUOgetPH1wjUAXNRlKGIEiapWEK3p8/3j5ZKJ3y8oJt1dRy3jCrhWA8e38TA/ggzAwYhMB2vOLBvyQq3+8HhEMJjRNHF75YPceAJYe3HGbkaVila75/8AB0naxI7qujrbh2LLoDT1l/jmQckQWJc5UhYc9kWm3kcZZXVtnIDx1oyL0KavadTCBXwEP4/eez5XFeiEHZjSeE/rNonMBPJP5tKBPEwbOwAx/vGNX0d3wHVTneDYRsIiveLt749TvVyWS78Mn8H3j55lMqBl0z2F+c9hfnPYX5z2F+c9xfnPYX5z2F+c9hfnPYX5z2F+c9hfnPYX5wi81w7z2F+c9hfnPYX5z2F+c9hfnPYX5z2F+c9hfnBuPof9z2F+c9hfnPYX5z2F+cVDg1JnyhQqoqBpz2F+c9hfnPYX5z2F+c9hfnPYX5z2F+c9hfnPYX5z2F+c9hfnPYX5z2F+c4BeTvR457C/OewvznsL857C/OewvznsL85+g/7n6D/uewvznsL857C/OewvzhxAQCunznxkxIOc+wvznsL857C/OewvznsL857C/Oewvzn6D/uewvznsL857C/OewvznsL857C/OewvzgF0Fw7++EML2F+c9hfnPYX5z2F+c9hfnPYX5z2F+c/Uf9z2F+cp0hhr88hVPdM/Ts/Ts/Ts/TsSlr5vdJ6G+cMgQh4+N9M/Ts/Ts/Ts/Ts/Ts/Tsa6ZO28f04KgR5Pr5z9Oz9Oz9Oz9Oz9Oz9OwsCdHP+spBKUeuv25mH/HZ+nZ+nZ+nZTlXYnygQCdnP07P07P07P07GP42FZmOrsv0mCQsjRK28E3w4MCb8fp2fp2fp2fp2IBDhz9fLBDQkddA59MXAhjx8eufp2fp2fp2fp2MfxsUiNE6df3vD9MRxKvGtb4eMECaXoz9Oz9Oz9OyLQXyfPw9Hcufp2fp2fp2fp2fp2fp2DXBVRoxmVmWwqBJz+8X4GkXjzrXDzn6dn6dn6dn6dn6dn6dgajZPT0fOZF1Azl59uNO8EEQdmmfp2fp2fp2fp2fp2BRY11Yg91UXtHz1hc6C01+snXBlE9w/jJ+BI7mLpsk3SLK86xZtKS89/HXxEVB4+FxLo5nPXAhRNDatSfXAXvDG6+xzigbYZfioc9fhAsNCkEcsglWNiSvph/MSA04j/pjwrq42AtfTN1+zZAg884VNICuXxxQlefigd9ckn0AvBZ46xdJsa7iUj65pJfhCBDBGx4+QQacFTG0DaAa9ucUAAFWkq78d47qyFdf/FflNVQ1OLMNhoKRQNehj3ElUNRdW8N38akCb24gKusig9ccVnjeNlm/jDU2dyQJvfO8ANoQ9MUBXQYN+QWJVJSjcEDKlxLVUO3OIRkEiFs57ya/wDDKZ648SeuVboE5CTqdB0rqwpTlygQkl55yT6KmRbTJaV47TA+QlAW96PGFwlZBZXT+necY6A6xVNmo75uss7Ai8RCiNvZXjAjZUsOFUvHRMYNaQ0TtLuHndZJIZShUNA6Gue+NWSKb/8AK+0JEA6jk4nyGiN7sho3vNr4sQ4Wl6DbvAas5Q1KI8SB642Qz0pOCXqqaJvGUlnFvZvevDjrjxDlVRJtrqs5ZitLp0RLZwacXJq0iphoENPCqY+4isMEmp1cFZiONWS0RRseU1xN4wb+rqD6r9f/ADuJAAAvjYGTkEpvFy+Ns6YBggagNAfR2YjGkEAIEERJU+uXk9IiwQ1s7b55zg/VgQFd9kd83WaypFQG3vzTXErgSnqFeFxqbK6lw8s3O0A3JythgU7fZitl5U1xMbPs8lJQ0FOnLG6xnWgLoFB9QP8AzqNRe8xyFhaVTYibHAtZhV0Gqb0/rthwkKnitfvgRAD0wLgC+GblhXnWLcg+ZnhH0yaUFBVHlB0YSoIk0KNL6/8AmAQD55Dga41jsQRDkiJmKQFEHIrS7vObrC98UmjXGsTyB8zI7HfAOAemb9Sto0eRmHBAAcB0wAYI7tVav/n4QfMxcBBROnbJFQiqB0V0beO+NjCkEHo1m5Yb51zm6wveYsihTrM8I4nGBcAemATaKSxDZeDmiayTTPPBuDAdA/8ApkZMhu9SZGIER4x16f8ApdCHKQMQQKyzab9XDGYGgt6HfFbwAN28YaXuAq/+vVjtgguQkRw8YAEFCco7v/vdKAqrAMi1CwO3fC0dRSWC/wBC+mR/nVpuzOKerumAgJBdocvpnB2EN8nf5DnkXbrJy4afITmCp/6UHkuBWLCTkf8AGKXQ1PZHbxYFeGpnjkfWu3QRWni74v8A6zSOUywxIEx6de2OGGkDw0/95sJWVIpnXV11wKjjuMGl7vbwxL1EU5kB6D6smIuWpAuSaR3awq4KGYjBOkKG6vLSkw4+RZm0hgJp33/7BAgQIECBAgQIECBAgQIECBAgQIECGDBAB/8AUAgQIECBAgQIECBAgQIECBAgQIECBAgqlAOQbJF7PxGKdHqpcMohdAOaPk4daUAiuv8AT65Il1R3GP8AX/qPlrgR2vXyz3f+s29/2657/wD1nv8A/WHvn5xbXzAee8bbBtUPvnv/APWave++WAWFMlfJ+Lw59i/jlyphWbwYgi6J2y5cuXLkWdcuXBahLKOXBkByJeMuXLgiy7/mr8FbwAwLgIeCfz1VTryIPJETtmhnWgoCDZrTxlz3lAlDr6frmrsyKSVWff4PGH0t91Wt7o5smJMzRYJTV2To7YBBKECRo6d8PcwiAL1TgC6684JoHxGSiMNTNg1aisR0+GbcgpoSG7rlzkCVtAJxOeifTDmGOPLRvQTr3y0vqYuQRdf8cDefFLSmnTvripWYrEimpsE9cZb2hPmf1Yx0MASPK7dZJOgkJSHmuz7OcIpldWPL7sIVDRp37g+Fe1x0T5iqQ1b032yzyKgEqKjA2yw1CEdOx3xtOMtwm8Dd1NeOmUIgSjl3V0gr6YwRbay+xbIGLUpDoJDjzzZyYimznHuGeIYpjYIoF6YC29EeEwNbOc8QwgbMYm/7T4vDn2b+O4MPSIHm+GLUjp+4AATSjTv4YbkLKEUYccl9Ml5+SV1vZ9MCHGYj1eGns6y5yGsNwQU9eidzEqRQFIjk4a1veJNiBXI+24rvF64wERBRs3Te9P3jRlpTYuR7yeMvXOVYoppnmHLl49chNJs27iYjdnvpw2DMCABPD41MSjOJqBCH23x1xEf6lEr39Z5dMX7uAHQNdXo12yJYFdKR5Xj6/Mx8AQbJVU9DwyRCKKB4E7zpjZNdSBIv9bxaqgBp5PTNTQYa8+0+uISAoidIx+jkZPUNUZ/eDLKJAUWXeRZjapaZE8z64iAbtBSuj1H6YmtMlTyin1j9MWJMCheeP6fpkSpJRS2D2mCEjim4s+m8BBzbYopfCDvFRr8DNlPhBwfqTaOZf6wRBOH56osijIOsMbPIRPBZb45MRA5eSlwTBAlsEpv4iuhBVJ0CwvhiKEd5S4dTuw57YIlrOgqA3QOwJiildhWzlN6vWc4vwSV2t3nyY0lZldhA9DKlIaIRFhupXebzvCAMXe473hA0ICEpURu65pZiYUC7pZrFeCD5PAurMVQJkAVQHh7ATAUlUxdcn+mAVG4BEza9DWKAFOhbs54u5xhZiG7Gl+quW0sKmuFLudLgZIIqQspdyvOMShnAJLI2krxhmpCiBOKXcrzkBQ7Xk4U4Z0uCSTw2ttJxPDF9DwSEEsI0Su+d4w1JHQw648nnj8C0YUCgy4vIryvfOjzPgcGcfd2fF4c+zfAfkuDf4HSUEvM+F2BWsJv5wJQBeWc/wk6PZBpTT1K/XOoCvFUfVBT1wLtCZcB3dHh98aGWggCxq+Lv+suLcHfYGnbo5U8HGsvFnmPpiFKOwaWQ3rlLigt1hL/dcXEpBABK0u/tgIoVVXWkUeN8NxeMVJEAHfPd4YuwMHEEbiP1dOuQE/Q5EsThrkU4uedu8ZgIWKYOeY9/bBOlSB0d6vj/ABhaeEeUDRER1+8tCgFeX435KrDWAN3iY+Mhz5u849ZkhYo0nEwNBLUAV7/BSxCNmhZc37qlBQBBt6ZvAQBEKcGo44IVNQJZ35MdEDoRtEzmb8sSzXYE16ebGgABQaKMejMPRAQEm9Cbsfpjtgtb0T+sTDQXACl10NhNuENcG8FwADExBISiWd5TNsUBAgXU7I+uXUBLqKBrmbxD2GiE6k7dDA56+WNCs4X3rOrNSA7ad5HjIa+RMpKvFmsZRdCUpAvjMVHFWxNSHo4msxdMDoPZfHHyBgwl2VOLMsJQklNwHeDrpioaar9oomCPWjimF3i7PPFxJQDEOBA0dmdc6PMy4OjOPu7PgNz2KAqaK8f8xQDcKSAUefn1x10SnT0wAqgFcbnQkhwA0sa1swcBToluJbyE31t4xiWCBVON3dH7ZEud3R2Dd7LmrZTuIlHXS/rCQ0qVaqNVsnazFnrk3oG297X0xFcAWgoUrdB0vfj5gHEGH10/19//AHJHFG+MG7dCL169X7ZQIgRNJwaXTN+s5dIIK+RH1xYUXkjfyERFmw6efyVbxzCcvgeZrPFZNN3tkshgXZ2HyMuBJAqFr46E9cM36vdGODWE7vVadI+GN5Ec2yRdRxkpQQGBFmvAxY3oTqv6djDYFBHkwemASWW6AgGsLPoI0VXHO2HiIOOPoze8XCPYFqLOG5wsj5JVcY6UhM8IXp3DJMowhio4J2HiZEigeNpgiffGjB07c4E8vRO9Ba4q/XNIEHiK7erNgYRoPU10y0BIOOpddL4YKCEOrqpSR5c364cCkBrsn3ZRy08roOsxoKBUugJ6Br1wDgIQDcajXa3IMtu6juZs4PpiKaOe2InB9MtQNZNmRIIazZwfTA1o5zwD6YQNH0wk0P8AqfCYmnPs2S5DIYMUSFOw/rJN6VqytYdK9shkMhkPm8FVfk/9D/3fe8glax6Oc/XA47T/AA+mS39omjj/AA+mRKvYfJ7z2fJV4CQHL4Hji3VHZr3s5zcSDuO4+ODVKKKjkw/nZ7M6w3fpMjTgW4gLpwbN5qxo6eYHobwtrObRLBdaF0Lzk/FRrVTo3HGkSeFrNEd3eIJtfJIQdyMUuRFXYJiS8HBTfGLuUVdgqkOMbxuoJdcIb03HyRVwio4L6QEx582PHw6vPOudHmfA4M4+7s+Lw59i+Qh4Xm9X5iqAqrAwJTeUmfIo3Mp59MMXgD8vi4BTAgE4Ro40Cuqhlj11VP4VDnAPD8FDnBHj4CPHwvwvw+941BYD1d8cA6uTh1frh4yB4nZzsTz3emCzgaK8v1cSeNwXxTnnWnGuji7x5AJIbcRU3eek+HvvZ8lUReDwhszxwcjbtMI2lHuWZAeC0EKMIzpGnXDX87lwEQ4QJHw3gWHBWCNhHsjhxJokK14vGSiQOnUta68d8VI3VQTc+kxmiAIFIeD2cqnNh1ig34XALWAiqoIo3qYyTVJoByG7DniYD4MYJeLjiby7sBjtC6cY6UBqpiNeeIyMBvzyLga8zIwEMIHs7Pi8OfZvk+p/sfm0BJyhex9MCs6J9nTfy6u7zydn9/KJ6agtV6Hp9M7KhghPtgdP4FRZuYndyCLLWfT5gaKN9GLUMAk4Hs/Ad4YOAPXodww6QZWNbqFIx4OMTd+wFCIn9Ex6ZcFKjidleXWGBAJIDadUn2waKlHmgQKaM2UEk3gdF1v0N7zQxCOoRXSQOlxmwCch0jwDy+7FsuyqqKBozxOjN4bKwuQtCbcK/fBIDhEnIRNG9zW95p1986V2b8XplsbwUAikNb2Z004AOws6arNBdBAdJAVejkyytBJEC17cz0wEG0o6fA9k7MoI7LyXUnN1y8MRoSEeTZ8tX+kbf1wJ/Dt+easO2OpBelRDfejnaLYjhYPkvGBIjo7nZ3p1hJMqEDo24MIzBNTu70YgFpjSey3nOLNgSee/HDLhCESUjeJ1xZhEEihkDOe4IE8/bjBhJVZMcze8SDQELyzykxS7LdOdA3oKe4dcEGlFFPAxkOhIADw3s4QJhAbulTpgDqAjRKzrhLcOYWYDQRNJ8OrzzrnR5nwODOPu7MvweHPs3yHPyf2/PGA3iWaX8ZxIIgHnhnybTpH1N/l+W5QHQqyXw/OObOpOEPlckscXTDzeMG4giPDhZCqmh+I26OsSgH1MC4xASKqAd7H+8XdH1OpN9tji+wRtyuuzzYhtU93kXzw4dFXSDo3uLg0AqiLGNzU9HV+SQ8bhqroD1tN9tiYEQUAQD4fe/jMmT4BJAF5ZznvvZ/PVUlTFFlzkRWqqVNJpU64xMDnWr1zS1N3DhoUDTyXkHnNBDorT58Jk+g4yGJqzUmjePxd6aupE8UdOMDa271o+u8kg3bxKTnrbk2bsAoRSDe59ME0ABNWhe8/pkG3YUajCG16j98QAzVatRiOvW4XcAHQeQml7NeGGddmpamgDnrfvl94IlvpLq3DgGBzWGHsrjOnAS7v0iD28TBAbaUi2WK/3nLly8YKjiKlDczhy/XOTbznLl+uDjbznmfrhobfrghs/9TBRctxFQCgePPBod2twJqP/AFjWrlXD14659i+Tp9ufnehfo4mC6jyvrjxlUJCBs74i5E0dqZqRyj0dftc3z5oAHTXW4EEYR2fiNKmgTMBcAggfK4YIJGNV6nObSWBXrMQZSkd3NIdiKidddJ8eRJVaFt1ulUyNawQGMRihpwR2Ka016TtgIYUQ8p+PLSBCLJNQDjAIoqMbEw8Uv174MgtQOrWU1vtmpo9gvJ23vvcAY1gISit41t6TDj4fe8MO4xJw8PnPTHAJAd25W8zphpFQaV0rp1q67Yd1ULGPClvq7/RqAulDjcbbbqTj4+89n/jqoyDqfodvDAUhsEQcICO148MDEdwE5prjjrvHduyisoOnY3/zJh0BuKjTPYxFgrtQOqJxOzj15aCzxTp66uVqBChVSRmLbHBQXZfN2xFDZq6mcoQC9d64y7K4qLUs41zle4HknUTZH64NQQjUIFBm3E+stiqkITcTfhhJI0OKtzrjyeePwIhJ0LnXOjzPgcGcfd2ZTC7P95KGn0x4JSXizlzycznK0ggHlA5esmtYIVWHbz8j95/ZmyvBue9ZzwKieJ8nPQIB3VmBS6Dc+/n8Tvf1Of8AcCEMBEUSOWnXQD5H0yylRRSo0Um2Na+oHgu/QybW0JELb0MEQFnIoV+2KHRiLotfCGfRGcvbEaogC10PD60wUDkRaHhMXAWCo6qPlrAeLyTwWfbJSLRmkW/TFbki2j8BEpcobfjMQLHTB8XjDZ8vGEGQQuu7HQ+T73gIkAq9si6nQSO59c5ioXLnCDAdmB8feez/AMdVotIyJedDzLjubXSIILTXEHeMgk6FtQ132hg5hmwCjrVx+IG4Iajbv/jIpCwtg6AiXcZRVQKX0iHG3ZrxzUBDteQyXA9MnNGgDeOTN8Q0Rnan9OSlyUCi4QQ288ZRrWlJFrtw+mcWDCguGuNbtPrg21NQNUEpWxxi/C0AAXyKPSZG8sRptiPdkZyySgqVjAClDnA68WR7sBhtgZt+0xiW3PRU6pvTiili2bAOm9J1x4c+xfJr4n9xhIBoEjO2OtYKAsO7hYBUTqfHqoEYSC6FKzt8x6keMspX4wbHDZsCHPngtMJ7A+VbnpmHjOUNYvK73e2WhdEA4NpuEwqk5icriN4zUFxewNHH5NdsFZNkUoMoj0tEzYfzB7utxKoRsQcXe38MgT3bEHW6h4o4fsLeOsyVcSSSJ8rxVKO6d6yW7AHy/Wfr/wAfL97xmNCJ3xlKrQx215HOI6czZs9DeI1dOi9uePk957P5auxIhV1dGCCAAXqvBlMauAqvQxOgJ2Op3wCU4xnpgBiHCnoYEhiIFaESfRzUQNKzvfXHy5Qi1qfnEyjwK7j8MsByKQ5b8MHjDYoI8h4mABswl0tF92IgefN4RO3BgAhsdkyH0xJaDNcblDjdfrjIFS2UAP8AWFb7TtTqBzwfgweYjasiIHlGSU2Stw648nnjnTBCnjnXOjzPgcGcfd2Yrkqgu7oTXWdbhGELdQa32kx4c+zfKN0zR4AFdOuECoMr1/i8tU8n/s+AtILYNHnnTD8SW6oMBofPDUMko4I3zs+uQHBpgAs7bpvxwovkB00Trp5J5YuTKEoQzm3HyCuilQl3udtXeATrGUKxe8NHWOFCM77Rf6HAtBQlTRSdCJ6uLBdR1KR4bz3n8Kh2nweOcQR9/l+94n8YG5jolKJBSdnO4+mdwOSy9gYjYoOoFPHhJ9N7+T3ns/lqkbZLYpAnkv2xNE6DoeXisvr4ZA1tD0CnXenn2wJGEFbBCviI4G0iHoDPV3nQmOIR4mGgjwf9uU0stMIIeQXCaTtbq9eB6eOT0E1OgNOfxgJWi3ZsHeO5274xtrFVWc+eTtWQqlI63g48cusLR+pZYdcohYx4UEwOgJW7uvofSzCtD6REsAO2gxg1l2qhOvcXrLijyhEUodeI5YdREu/2FIeDmngggntOW0U/BMJVXKLQ3bnLk+mOxs57Y+I+meY+mKAquwawyCLN6zg2c9s8x9MNOT6ZUpP+pjQQxS6U0Xe+2BdCgt1jw59i+T2jw/li/Ka8+mGL0XLdxeHs9MhqTgOyc4gCOLUiACdpDeDiAtDogm+YOEgiu6JJu861MKskEBQEK62H0wgsDblgk/GEmmLYIejDiTGgAEI88L9c5gXSQJbzxcXsXk6O7eq6+hm28wYrYHG5ci+3u8jkmORIKVA9k8sHBppzbLPOdMi0SVGCBX7DkbOxVw9viCKwDbiMcdA9P+vm+95EXgC8FZX64bR3E7LSHhi+HCXAa67yEC7obVR14J8nvPZ8lUkAvlGohDu1NYgN7cGGvHRh6mFq24vAaah29ucotwOtxHHj/DPiNNcgdmHGLMQUQDrg34xYF7uKTeS4FRGa0/HSzPvmHXFKeePwHPnnXOjzPgcGcfd2ZxBPmN66DLw3kxkt4SmPDn2L5PtPw/lc3eTeTv4G48U8nP2/rHQk0ic42l2F69H+ZI4qUGnfQfPxyhYXqKIYgFnLx3w3jKHQCP3nmZCIYGwpZtby7dpnPSh4E6dfB1wsiq0DNN8Oy/fKaFqzJTyT+zHdaFNDYDx0cUF0sdQI95swWaKNI1O8jBE6w9D5iOB8vLBPndgqADg2nGcUb3U0DvtrR0y5c4DpPj7GBPm+94gWCaXbUx0Rdb8rfHplzkpp80x2rABEBYP1fk957PkqsNCKXI9/MwYR17benlnkc4ZrNUR0AZ2/jKJxGns4CxpUKxoLyZqPfGwCejUT1B98VV0QSupfZ5YqI7FUeC3X3PTDU4iNQNZ4XE0Nhrpolp2uFZwJUupfDnnWOFWHRI6HoYRSoRdijX1cYNKxWTseffbj+8m5hHdcvOXOMZiMQru73s+mEEAlInOj24412xFC2AtA9Os6N788tArjQU7EzQwLNYRIu+GnTPRnJxznLpnBxznow06Zcqf9TKvsWDfeHliEiJyEDbP9chC02nQ33bf6xRLEuz5Pu/6fE2CiR3hchIFZ2A170GTDUqmzQCat1PHJB5iSLkvG68zD1hKFOQE9DTHph0cbHHmMDAI6HQGjzvTEtggLeDm9p44gWDVOohXXgZqYoaGw0OtXEFWN8lnpvWV6VAdx17dvgj9V6mGDwLiSbynfqPfbEAjR2YxkHxMANAQmhrmHOMD0tEBiiAl7jEFRQNAXvxP74xQpMWpznjx8fDIbdQujoHfB6owUTdO2RZtsoZHp/uLIPrTXL0aemOPFY0CTdf0HywQdFCHYDZoZiA7ghDvacCa8cIkPTarUj1yGdQo6Qc06vs1Fq2u78+qePJI1ERBG5pmZRSOO0LgCDQVeBG63znNptsVbWrvymfpefrefreBtCIBeHyVbCcR98opwn3w/lmAWAXb45MmTIZMmTJkyZDJn3zDrjAwt5+PV551zo8z4HBnH3dmN3QFgrolG41COjjO8dzzyaJMjG3PsXyfcP7fG/MFrtSY2uRtKNPCI+hhaqxBioQ8Ub4GI8ZSbXQF8a9XHiqbXHAYWeiQLf1/rhkBwVwJ+ieuFjERwoafQMsTIzYAQHyI/3mwRS0NI277PvhNJWJypP34wtzGkjmrDSyl1g0vw8P8A/Ufn1+G08fZ6np8GNK9n/Zm7OtQK99dcUNFtqBZ/bvneWCmQZp1wHg9TQ4kyWiFQulJr06cYZQlQaeeEOPGO6eOLpMpTOTtljRyAH0woEVAEMdRbvHPnm4NASL3b44wmyYnmAYEXQB1OSPXEUjRiTz2xsrSFUrOPPOr8ifV2wRUAVBo75AXoT6Ms7KmhUc1KzFEXhjxMbOhRSeenOrKoiw5cPiMQwDSkwi07CX6ZDsZDsZDsfJVr+0ZJ5wHIjN45VH0cuT1IDqBe4NynHrnhmP8A4Q9SyYVOJ1zj/wDBVGPuCfnplpFC0sbsngeeHWXAFKRrq+O+2Dr5Ex14n1a4wMJT5lV6GE7Ha4uJBNAkvTW59cIshcKk7HFPqxGUeildTK3/AFitNdcVx4JiY665W8ffE9uvfK/tgs/1iZp+0+HXHhz7N8n3L+38JAgStOJXWqfk+yc+3/18PuP9vhyfbT8HNS6Gh20fK7z7N8jRRm+EABAPgHFLbhars7cH0xz0So3Z3h3BgG/E+hhBHQFR7mIhMaiUzIMGi2dHGNcysTTvjwQQFBjCPNCiamnFABVA535yHM2il7Hq/XKIlEY2kdfnq8Xlg088QFCnCnGMXrc6w4/8LznX5TOufcP7Z1x5PPOmTjOrzzrnR5/A4z3XuZ//2Q==)
Associações de expressão gênica de VAT (tecido adiposo visceral) e domínios cognitivos na coorte de descoberta. Gráficos de vulcão de genes diferencialmente expressos no VAT associados a (A) os testes de interferência STROOP, (B) a parte B do teste de trilha (TMTB) e (C) pontuações de recordação imediata do teste de aprendizagem verbal da Califórnia (CVLT_IR) na coorte de descoberta ( IRONMET, n = 17) identificados por análise limma-voom controlando idade, IMC, sexo e anos de escolaridade. A mudança log 2 vezes associada a uma mudança unitária na pontuação do teste cognitivo e o log 10Os valores de P ajustados para testes múltiplos (pFDR) são plotados para cada gene. Genes expressos diferencialmente (pFDR <0,05) são coloridos em vermelho e verde indicando regulação negativa e regulação positiva, respectivamente. (D) Gráfico de vias semelhante a Manhattan significativamente associado (q <0,1) ao TMTB no VAT identificado a partir de uma análise de super-representação de vias mapeando genes significativos para os bancos de dados Reactome e WikiPathways. (E) Gráfico de pontos de vias significativamente associadas (q <0,1) com o CVLT_IR no VAT identificado a partir de uma análise de super-representação de vias mapeando genes significativos para o banco de dados Reactome. Os pontos são coloridos pelo valor q. (F) Gráfico de caminhos semelhante a Manhattan significativamente associado (q <0. 1) com a interferência STROOP no VAT identificada a partir de uma análise de super-representação de vias mapeando genes significativos para os bancos de dados Reactome e WikiPathways. Nos gráficos do tipo Manhattan, o tamanho da bolha representa a proporção de genes de entrada que são anotados em um caminho (GeneRatio). CREB, proteína de ligação ao elemento de resposta à adenosina 3?,5?-monofosfato; tRNA, RNA de transferência; NCAM1, Molécula de Adesão de Células Neurais 1; TP53, Proteína Tumoral 53; PKA, subunidade catalítica alfa ativada por proteína quinase CAMP. Crédito: Subunidade catalítica alfa ativada por proteína quinase CAMP. Crédito: Subunidade catalítica alfa ativada por proteína quinase CAMP. Crédito:Avanços da Ciência (2023). DOI: 10.1126/sciadv.adg4017
Em camundongos, o declínio cognitivo é influenciado pela obesidade devido à potencial associação de um eixo adiposo-cérebro. Para examinar esta proposta, Núria Olivera-Canellas e uma equipa de investigadores dos departamentos de medicina e diabetes da Universidade de Girona, Espanha, identificaram 188 genes através da sequenciação de ARN do tecido adiposo em três coortes de pacientes associados ao desempenho cognitivo. Os genes tiveram associações com função sináptica, sinalização antiinflamatória, metabolismo de vitaminas, metabolismo de fosfatidilinositol e cascata do complemento.
A equipe traduziu essas descobertas no metaboloma plasmático e relacionou os níveis de expressão dos genes no sangue circulante com vários domínios cognitivos em uma coorte de 816 participantes. Eles mostraram como a expressão incorreta dos ortólogos do gene candidato no corpo gorduroso da Drosophila alterou significativamente a memória e o aprendizado nas moscas.
Além disso, a regulação negativa de um gene associado ao ciclo de liberação de neurotransmissores melhorou as habilidades cognitivas de moscas Drosophila e camundongos. Os resultados mostraram conexões até então não identificadas entre o transcriptoma do tecido adiposo e a função cerebral para obter uma visão sem precedentes sobre os alvos diagnósticos e terapêuticos no tecido adiposo. O estudo foi publicado na Science Advances .
O impacto da obesidade no cérebro
Os tecidos periféricos podem regular a função cerebral para moldar diferentes domínios cognitivos. Biólogos conduziram estudos em ratos para revelar como a restauração do metabolismo da glicose nas células mieloides reverteu o declínio cognitivo no envelhecimento . Além disso, a ablação seletiva dos nervos aferentes vagais gastrointestinais prejudicou a memória episódica e espacial dependente do hipocampo em ratos . Esses estudos destacaram que o fígado desempenha um papel importante na determinação do comportamento alimentar em camundongos .
Embora a obesidade esteja associada a riscos de comprometimento cognitivo, o aumento do índice de massa corporal durante a meia-idade prevê diminuição das capacidades cognitivas, que incluem principalmente memória, funcionamento executivo e aprendizagem. No entanto, os mecanismos precisos subjacentes ao processo permanecem em grande parte desconhecidos.
O cérebro pode regular o desempenho do tecido adiposo. Olivera-Canellas e sua equipe estudaram, portanto, os mecanismos subjacentes às interações direcionais entre a expressão gênica do tecido adiposo e a função cognitiva neste trabalho. Eles usaram a análise de sequenciamento de RNA do tecido adiposo para mostrar genes associados a diversos domínios cognitivos. Os cientistas também exploraram a expressão de vários genes nas células mononucleares do sangue periférico em associação com funções cognitivas em humanos.
Genes envolvidos com obesidade e cognição
Os pesquisadores obtiveram informações sobre o eixo gordura-cérebro realizando transcriptômica após sequenciamento de RNA do tecido adiposo visceral obtido de 17 indivíduos com índice de obesidade grave com idades entre 28 e 60 anos. , função executiva e atenção. Os desfechos não mostraram associações significativas com atividade física, macronutrientes, glicemia ou ingestão de álcool.
A equipe observou associações significativas com transcrições genéticas para todos os testes cognitivos, que incluíam variantes em diversos domínios cognitivos. As proteínas codificadas por esses genes apresentaram funções no sistema nervoso central, embora sua expressão no tecido adiposo em associação com a cognição seja inédita.
Dos genes identificados, o gene NUDT2 está associado à deficiência intelectual , o AMPH codifica uma proteína que está alterada no líquido cefalorraquidiano de pacientes com comprometimento cognitivo leve e Alzheimer . OAT é outro gene que desempenha um papel cognitivo significativo , enquanto os genes KYNU e INMT estão envolvidos no metabolismo do triptofano . Indivíduos obesos tinham memória prejudicada e metabolismo alterado do triptofano .
Para interpretar e identificar com precisão a via do tecido adiposo associada à função cognitiva, Olivera-Canellas e sua equipe mapearam genes significativos nos bancos de dados Reactome e WikiPathways incluídos no ConsensusPathDB . A equipe observou uma representação excessiva de vias com papel importante no sistema nervoso central associadas ao controle inibitório, memória de trabalho, memória imediata e atenção. Eles também notaram uma super-representação de vias associadas a domínios cognitivos ligados à inflamação, bem como alterações na sinalização de entalhe e associações de ativação do complemento com a memória de trabalho.
A expressão genética do tecido adiposo está associada a diversas funções cognitivas mais tarde na vida
Olivera-Canellas e colegas validaram os resultados realizando sequenciamento de RNA do tecido adiposo visceral e do tecido adiposo subcutâneo em 22 indivíduos com obesidade grave com idades entre 23 e 57 anos. A coorte de pacientes foi submetida à mesma bateria de testes cognitivos, realizados dois a três anos após a coleta da amostra de tecido adiposo. Como antes, os cientistas não observaram uma associação significativa entre atividade física, dieta, ingestão de álcool e níveis de glicose ou hemoglobina. Eles notaram uma associação genética significativa com o teste cognitivo.
No total, a equipe observou a orientação dos axônios, o desenvolvimento do sistema nervoso, o sistema neuronal e as vias do triptofano associadas à atenção, enquanto o sistema complemento foi ativado no tecido adiposo visceral para indicar uma forte associação com o desempenho em vários domínios cognitivos. As vias do tecido adiposo subcutâneo foram associadas à transmissão sináptica, ao sistema neuronal e ao metabolismo de um carbono em relação à memória de longo e curto prazo.
Outras experiências sobre cognição e genes relacionados ao tecido adiposo no eixo adiposo-cérebro
Os cientistas notaram ainda a associação de genes do tecido adiposo ligados à função cognitiva no sistema neuronal e durante a formação sináptica das vias. Esses genes super-representados mostraram papéis fundamentais na função sináptica e na inflamação.
A equipe conduziu experimentos adicionais para vincular o tecido adiposo à cognição, juntamente com suas associações com a inflamação. Os resultados destacaram que a obesidade mórbida influencia a associação entre os genes do tecido adiposo e a cognição, ao mesmo tempo que vincula os níveis de expressão sanguínea dos genes ao desempenho cognitivo .
Os pesquisadores usaram moscas da fruta (Drosophila melanogaster) para experimentar o efeito causal da expressão de genes candidatos relacionada ao tecido adiposo para promover a cognição. A análise adicional incluiu testes de cognição em tecido adiposo de camundongos ou corpo gorduroso de Drosophila para compreender o conjunto de genes envolvidos na liberação de neurotransmissores.
Panorama
Desta forma, Núria Olivera-Canellas e colegas mostraram como o cérebro regulava o desempenho do tecido adiposo , embora o inverso também seja plausível. A expressão de genes relacionados à orientação dos axônios, ao desenvolvimento do sistema nervoso, ao sistema neuronal, ao triptofano e à inflamação foram todos ligados à cognição em três coortes diferentes.
Juntamente com estudos adicionais em modelos animais, os investigadores sugerem um processo de desenvolvimento sistémico que mudou em diversos tecidos e células, conforme refletido nas redes neuronais. Os resultados fornecem biomarcadores úteis para prever o declínio cognitivo e monitorar a resposta ao tratamento.
Mais informações: Núria Oliveras-Cañellas et al, O tecido adiposo co-regula a função cognitiva, Science Advances (2023). DOI: 10.1126/sciadv.adg4017
Paras S. Minhas et al, Restaurar o metabolismo das células mieloides reverte o declínio cognitivo no envelhecimento, Nature (2021). DOI: 10.1038/s41586-020-03160-0
Informações do periódico: Science Advances , Nature