Prática de Shadowing: SOFI: Sequence-based, cross-sectoral, One-health surveillance of food-borne infections | IMMEM XIV - Aprenda a falar inglês com o YouTube

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Hello, my name is Kaspar Rømer-Willemsen and I'm with the SSI in Copenhagen, Denmark.
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Hello, my name is Kaspar Rømer-Willemsen and I'm with the SSI in Copenhagen, Denmark.
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I'm here to tell you about the SOFI,
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a platform for sequence-based cross-sectoral,
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one-health-based surveillance of foodborne infections in Denmark.
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But before I get started,
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I just want to thank the organizers of the MM conference
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for organizing a fantastic conference in an absolutely amazing location in Porto.
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Thank you so much.
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I also want to thank all the co-authors that are on this poster
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because essentially they were the ones involved in the design and the implementation of the SOFI platform.
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They're the ones that did the bulk of the work.
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I'm just basically allowed to come here and talk about it.
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So I'm very, very grateful.
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Thank you.
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So if we look at how surveillance
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or at least how investigation of outbreaks work in the Danish system in terms of foodborne bacterial infections,
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if we look at how that works before the implementation of SOFI,
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well, basically you have two different sectors.
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So we have three different actors here.
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We have the National Food Institute at DTU.
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There's the Danish Veterinary and Food Administration.
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And then there's us at the SSI.
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So constituting basically the public health side.
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And then there's also a food and veterinary side.
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So the way things would work before the implementation of SOFI was that you would have these two different silos.
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So there would be strong collaborations across.
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We have a central outbreak management group.
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They meet every week, basically just coordinating whatever comes in.
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Are there any signals?
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Are there any ongoing outbreaks? do we need to coordinate any efforts?
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But essentially the way that everything was analyzed was kind of siloed
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so that you would have these two sectoral silos where you would have samples coming in,
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DNA extracted, sequencing done, all the different analysis would then be run within each silo.
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If there's any suspicion of anything that might go across these two silos,
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then you would have ad hoc preparations for sharing of sequences
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so that you can do comparisons in a collaborative manner across from that.
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So what has actually changed now is that now we have this the SOFI platform.
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So certain things are the same
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so basically samples are still coming in to the respective institution
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public health side everything in terms of samples derived from patients come to us at SSI.
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We run the samples we do the sequencing
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but once the sequencing is instead of running everything in a
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continued siloed approach now everything is coming into this sophie platform
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so what is sophie
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so basically sophie is um at one on the one hand it's a data sharing platform
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so that basically means
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that prior to everything um you know everything had to be
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sorted out in terms of all the different legal aspects we're
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mixing like personal sensitive information sensitive information about food producers and stuff like that.
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So everything has to be completely sealed down in a legal manner,
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but also having to make sure that once we enter into this SOFI data sharing aspect,
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we need to make sure that it's very,
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very clear who has access to what,
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what is shared, what is common,
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what is open to common analysis,
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and what is absolutely not shared,
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what has to be completely cordoned off to each of the respective partner institutions.
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So, but from surveillance, or outbreak investigation standpoint,
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things are now coming into the same pipeline instead of having this siloed approach,
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it's the same pipeline.
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So now everything is being analyzed according to different analysis modules.
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So, and that ranges from initial quantity control,
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but also to all sorts of species specific modules.
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So like species specific toxin detection,
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virulence factors, stuff like that.
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But most importantly for this,
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actually also there's a CGMLST component.
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So once all this is done,
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now we end up with everything ending up in the same user interface down here.
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So what that means is that instead of having a siloed approach where ad hoc,
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we would have to make sure that we share relevant data
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and we like someone had to have the suspicion that there might be something going on,
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everything is now available in the same interface So that if I'm doing this like just routine surveillance,
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I actually have the access not only to every data point from the public health side,
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but also from the food and veterinary side.
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That means that we now have an even closer collaboration than we did before.
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And it also means that we have the possibility to be much quicker about cluster detection,
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outbreak investigation, and consequently quicker to implement any countermeasures.
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So all in all, a win-win-win situation.
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That was a very, very quick flydown.
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Check out the poster in the online collection from the conference.
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If there's any questions, absolutely feel free to contact us.
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Thank you for your attention.

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Por que praticar a conversação com este vídeo?

Praticar a conversação em inglês com vídeos como este é uma excelente maneira de aprimorar suas habilidades orais. O contexto de uma apresentação sobre a plataforma SOFI, que foca na vigilância de infecções alimentares, oferece vocabulário técnico e específico, ideal para quem deseja expandir seu conhecimento em situações formais. Além disso, a interação entre diferentes setores descrita no vídeo exemplifica como a comunicação clara é crucial em ambientes profissionais e de pesquisa. Ao se envolver com o conteúdo, você poderá não apenas aprender novas expressões, mas também entender melhor como estruturar suas ideias durante conversas sobre temas complexos.

Gramática & Expressões em Contexto

No vídeo, o apresentador utiliza várias estruturas gramaticais que são úteis para quem deseja melhorar a fluência. Aqui estão algumas delas:

  • Uso de termos de agradecimento: Expressões como “Thank you so much” e “I want to thank” demonstram como mostrar gratidão é fundamental na comunicação formal.
  • Apresentação de ideias: O uso de “if we look at” ao introduzir uma análise destaca como iniciar discussões de maneira clara e envolvente.
  • Estruturas condicionais: Frases como “If there’s any suspicion…” ilustram a importância de condições para desenvolver argumentos, uma técnica valiosa em debates e discussões.

Praticar essas estruturas através de shadowing em inglês, onde você repete o que ouve no vídeo, pode ajudá-lo a internalizar essas formas e utilizá-las em suas próprias conversas.

Armadilhas Comuns de Pronúncia

A pronúncia correta pode ser desafiadora, principalmente em palavras técnicas e terminologias específicas. Aqui estão algumas armadilhas a serem observadas:

  • “siloed”: O som pode ser enganoso; preste atenção na maneira como é pronunciado, especialmente o “s” inicial.
  • “sequences”: Certifique-se de articular claramente a sílaba “quens” para evitar confusões com sons semelhantes em inglês.
  • Termos de saúde pública como “outbreak”: A pronúncia pode variar regionalmente, então pratique ouvindo repetidamente e tentando replicar o tom.

Integrar técnicas de shadow speak, onde você imita a entonação e ritmo do falante, é uma maneira eficaz de melhorar sua pronúncia e fluência.

O que é a Técnica de Shadowing?

Shadowing é uma técnica de aprendizado de idiomas com base científica, originalmente desenvolvida para o treinamento de intérpretes profissionais. O método é simples, mas poderoso: você ouve áudio em inglês nativo e repete imediatamente em voz alta — como uma sombra seguindo o falante com 1-2 segundos de atraso. Pesquisas mostram melhora significativa na precisão da pronúncia, entonação, ritmo, sons conectados, compreensão auditiva e fluência na fala.

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