{"id":13350,"date":"2024-07-09T18:26:52","date_gmt":"2024-07-09T18:26:52","guid":{"rendered":"https:\/\/dailyai.com\/?p=13350"},"modified":"2024-07-09T18:35:05","modified_gmt":"2024-07-09T18:35:05","slug":"ai-breakthrough-rapidly-identifies-drug-resistant-typhoid-without-antibiotic-exposure","status":"publish","type":"post","link":"https:\/\/dailyai.com\/pt\/2024\/07\/ai-breakthrough-rapidly-identifies-drug-resistant-typhoid-without-antibiotic-exposure\/","title":{"rendered":"A descoberta da IA identifica rapidamente a febre tifoide resistente aos medicamentos sem exposi\u00e7\u00e3o a antibi\u00f3ticos"},"content":{"rendered":"

Os investigadores da Universidade de Cambridge utilizaram a IA na luta contra a resist\u00eancia aos antibi\u00f3ticos.\u00a0<\/strong><\/p>\n

A equipa de investiga\u00e7\u00e3o, liderada pelo Professor Stephen Baker, criou uma ferramenta de aprendizagem autom\u00e1tica que utiliza apenas imagens de microscopia para distinguir entre bact\u00e9rias resistentes \u00e0 ciprofloxacina (um antibi\u00f3tico comum) e as suscept\u00edveis a ela.<\/span><\/p>\n

Isto poderia reduzir drasticamente o tempo necess\u00e1rio para diagnosticar a resist\u00eancia aos antibi\u00f3ticos, transformando potencialmente a forma como tratamos infec\u00e7\u00f5es perigosas como a febre tifoide.<\/span><\/p>\n

O <\/span>estudo<\/span><\/a>publicado na Nature Communications, centrou-se na Salmonella Typhimurium, uma bact\u00e9ria que causa doen\u00e7as gastrointestinais graves e pode levar a doen\u00e7as invasivas potencialmente fatais.\u00a0<\/span><\/p>\n

\"IA\"
A Salmonella \u00e9 uma bact\u00e9ria que normalmente infecta os seres humanos atrav\u00e9s de alimentos contaminados, e algumas estirpes ganharam resist\u00eancia aos antibi\u00f3ticos. Fonte: Universidade de Cambridge<\/a>.<\/figcaption><\/figure>\n

O Dr. Tuan-Anh Tran, um dos principais investigadores do projeto, explicou a abordagem numa <\/span>publica\u00e7\u00e3o no blogue<\/span><\/a>: \"A beleza do modelo de aprendizagem autom\u00e1tica \u00e9 que consegue identificar bact\u00e9rias resistentes com base em algumas caracter\u00edsticas subtis nas imagens de microscopia que os olhos humanos n\u00e3o conseguem detetar\".<\/span><\/p>\n

O processo de investiga\u00e7\u00e3o envolveu v\u00e1rias etapas fundamentais:<\/span><\/p>\n

    \n
  1. Prepara\u00e7\u00e3o de amostras bacterianas<\/strong>: A equipa cultivou amostras de S. Typhimurium em meios nutritivos l\u00edquidos, algumas expostas a diferentes concentra\u00e7\u00f5es de ciprofloxacina e outras n\u00e3o.<\/span><\/li>\n
  2. Imagiologia de alto conte\u00fado<\/strong>: Utilizando um microsc\u00f3pio sofisticado, os investigadores tiraram fotografias pormenorizadas das bact\u00e9rias em v\u00e1rios momentos.<\/span><\/li>\n
  3. An\u00e1lise de imagens<\/strong>: Um software especializado extraiu 65 caracter\u00edsticas diferentes de cada c\u00e9lula bacteriana, incluindo a forma, o tamanho e a intera\u00e7\u00e3o com corantes fluorescentes.<\/span><\/li>\n
  4. Desenvolvimento de modelos de aprendizagem autom\u00e1tica<\/strong>: Os investigadores introduziram estes dados em v\u00e1rios algoritmos de aprendizagem autom\u00e1tica, treinando-os para reconhecer padr\u00f5es associados \u00e0 resist\u00eancia aos antibi\u00f3ticos.<\/span><\/li>\n
  5. Sele\u00e7\u00e3o de caracter\u00edsticas<\/strong>: A equipa identificou as caracter\u00edsticas mais importantes para distinguir entre bact\u00e9rias resistentes e suscept\u00edveis.<\/span><\/li>\n<\/ol>\n

    Os resultados deste processo foram impressionantes. O sistema de IA identificou corretamente as bact\u00e9rias resistentes aos antibi\u00f3ticos em cerca de 87% das vezes.\u00a0<\/span><\/p>\n

    Talvez mais significativo, os investigadores descobriram que as bact\u00e9rias resistentes e suscept\u00edveis tinham padr\u00f5es visuais distintos que a IA conseguia detetar, mesmo quando n\u00e3o tinham sido expostas a antibi\u00f3ticos.\u00a0<\/span><\/p>\n

    Isto sugere que a resist\u00eancia aos antibi\u00f3ticos altera o aspeto das bact\u00e9rias de formas demasiado subtis para os humanos verem, mas que a IA consegue detetar.<\/span><\/p>\n

    Os m\u00e9todos actuais requerem normalmente v\u00e1rios dias de cultura bacteriana e testes contra v\u00e1rios agentes antimicrobianos. Em contrapartida, o novo m\u00e9todo baseado em IA pode potencialmente fornecer resultados em poucas horas.\u00a0<\/span><\/p>\n

    Um diagn\u00f3stico mais r\u00e1pido permite aos m\u00e9dicos prescrever mais cedo os antibi\u00f3ticos mais eficazes, melhorando potencialmente os resultados dos doentes e reduzindo a propaga\u00e7\u00e3o de bact\u00e9rias resistentes.<\/p>\n

    Para o futuro, a equipa de investiga\u00e7\u00e3o pretende expandir a sua abordagem a amostras cl\u00ednicas mais complexas, como sangue ou urina, e test\u00e1-las noutros tipos de bact\u00e9rias e antibi\u00f3ticos. Est\u00e3o tamb\u00e9m a trabalhar para tornar a tecnologia mais acess\u00edvel a hospitais e cl\u00ednicas de todo o mundo.<\/span><\/p>\n

    Como explica o Professor Baker: \"O que seria realmente importante, especialmente num contexto cl\u00ednico, seria poder recolher uma amostra complexa - por exemplo, sangue, urina ou expetora\u00e7\u00e3o - e identificar a suscetibilidade e a resist\u00eancia diretamente a partir dessa amostra.\"<\/p>\n

    \"Trata-se de um problema muito mais complicado e que ainda n\u00e3o foi resolvido, nem mesmo no diagn\u00f3stico cl\u00ednico num hospital. Se consegu\u00edssemos encontrar uma forma de o fazer, poder\u00edamos reduzir o tempo necess\u00e1rio para identificar a resist\u00eancia aos medicamentos e a um custo muito inferior. Isso poderia ser verdadeiramente transformador\".<\/span><\/p>\n

    A Dr.\u00aa Sushmita Sridhar resumiu os impactos, afirmando: \"Dado que esta abordagem utiliza imagens com resolu\u00e7\u00e3o de uma \u00fanica c\u00e9lula, ainda n\u00e3o \u00e9 uma solu\u00e7\u00e3o que possa ser prontamente implementada em todo o lado. Mas mostra uma promessa real de que, ao captar apenas alguns par\u00e2metros sobre a forma e a estrutura das bact\u00e9rias, pode dar-nos informa\u00e7\u00f5es suficientes para prever a resist\u00eancia aos medicamentos com relativa facilidade\".<\/span><\/p>\n

    Dado que a resist\u00eancia aos antibi\u00f3ticos continua a representar uma amea\u00e7a crescente para a sa\u00fade mundial, abordagens inovadoras como esta t\u00e9cnica de imagiologia baseada em IA oferecem uma nova esperan\u00e7a.\u00a0<\/span><\/p>\n

    Isto faz parte de uma tend\u00eancia mais alargada de inova\u00e7\u00f5es impulsionadas pela IA na investiga\u00e7\u00e3o de antibi\u00f3ticos. No MIT, os investigadores utilizaram modelos de aprendizagem profunda para descobrir um classe inteiramente nova de antibi\u00f3ticos<\/a>.<\/p>\n

    Na mesma linha, outra equipa de cientistas anunciou em maio do ano passado que tinha utilizado a IA para identificar um novo antibi\u00f3tico<\/a> eficaz contra bact\u00e9rias resistentes a medicamentos.<\/p>\n

    A IA permite uma identifica\u00e7\u00e3o mais r\u00e1pida e precisa das infec\u00e7\u00f5es resistentes aos medicamentos, abrindo caminho a tratamentos mais eficazes e a melhores resultados para os doentes.\u00a0<\/span><\/p>\n

    Os pr\u00f3ximos anos ser\u00e3o cruciais, uma vez que a equipa trabalha para traduzir o seu sucesso laboratorial em aplica\u00e7\u00f5es cl\u00ednicas no mundo real.<\/span><\/p>","protected":false},"excerpt":{"rendered":"

    Os investigadores da Universidade de Cambridge utilizaram a IA na luta contra a resist\u00eancia aos antibi\u00f3ticos. A equipa de investiga\u00e7\u00e3o, liderada pelo Professor Stephen Baker, criou uma ferramenta de aprendizagem autom\u00e1tica que utiliza apenas imagens de microscopia para distinguir entre bact\u00e9rias resistentes \u00e0 ciprofloxacina (um antibi\u00f3tico comum) e as suscept\u00edveis a ela. Isto poder\u00e1 reduzir drasticamente o tempo necess\u00e1rio para diagnosticar a resist\u00eancia aos antibi\u00f3ticos, transformando potencialmente a forma como tratamos infec\u00e7\u00f5es perigosas como a febre tifoide. O estudo, publicado na revista Nature Communications, centrou-se na Salmonella Typhimurium, uma bact\u00e9ria que causa doen\u00e7as gastrointestinais graves e pode conduzir a doen\u00e7as invasivas potencialmente fatais. O Dr. Tuan-Anh Tran, um dos principais investigadores do estudo<\/p>","protected":false},"author":2,"featured_media":13352,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[88],"tags":[353,105],"class_list":["post-13350","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ethics","tag-biology","tag-machine-learning"],"yoast_head":"\nAI breakthrough rapidly identifies drug-resistant typhoid without antibiotic exposure | DailyAI<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/dailyai.com\/pt\/2024\/07\/ai-breakthrough-rapidly-identifies-drug-resistant-typhoid-without-antibiotic-exposure\/\" \/>\n<meta property=\"og:locale\" content=\"pt_PT\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"AI breakthrough rapidly identifies drug-resistant typhoid without antibiotic exposure | DailyAI\" \/>\n<meta property=\"og:description\" content=\"Researchers at the University of Cambridge have harnessed AI in the fight against antibiotic resistance.\u00a0 The research team, led by Professor Stephen Baker, created a machine learning tool using only microscopy images to distinguish between bacteria resistant to ciprofloxacin (a common antibiotic) and those susceptible to it. This could dramatically reduce the time required for diagnosing antibiotic resistance, potentially transforming how we treat dangerous infections like typhoid fever. The study, published in Nature Communications, focused on Salmonella Typhimurium, a bacterium that causes severe gastrointestinal illness and can lead to life-threatening invasive disease.\u00a0 Dr. Tuan-Anh Tran, a key researcher on the\" \/>\n<meta property=\"og:url\" content=\"https:\/\/dailyai.com\/pt\/2024\/07\/ai-breakthrough-rapidly-identifies-drug-resistant-typhoid-without-antibiotic-exposure\/\" \/>\n<meta property=\"og:site_name\" content=\"DailyAI\" \/>\n<meta property=\"article:published_time\" content=\"2024-07-09T18:26:52+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2024-07-09T18:35:05+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/dailyai.com\/wp-content\/uploads\/2024\/07\/DALL\u00b7E-2024-07-09-19.25.37-A-high-tech-nightcore-themed-image-focusing-on-Salmonella-bacteria.-The-bacteria-should-be-prominently-displayed-with-a-background-infused-with-red.webp\" \/>\n\t<meta property=\"og:image:width\" content=\"1792\" \/>\n\t<meta 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