双语新闻：科学家们发明AI工具，能在病毒变异出现之前预测
Scientists have created an artificial intelligence (AI) tool that aims to predict different virus versions, called variants, before they appear.
科学家们发明了一种人工智能(AI)工具，旨在在病毒出现之前预测不同的病毒版本，即变种。
Creators of the tool say it works by estimating the likelihood that a variant will permit it to escape the body's own immunity defenses.
该工具的创造者说，它的工作原理是通过估计一种变异使其逃脱人体自身免疫防御的可能性。
The tool is called EVEscape. It works by processing collected data on the development, or evolution, of a virus over time. The system also considers detailed biological and structural information related to the virus.
这个工具叫做EVEscape。它的工作原理是处理收集到的一段时间内病毒发展或进化的数据。该系统还考虑与病毒有关的详细生物学和结构信息。
The method is a form of "generative AI," a term describing technology tools designed to operate at human levels. EVEscape was developed by researchers from Britain's University of Oxford and Harvard Medical School in Boston, Massachusetts. The team's findings recently appeared in a study in the publication Nature.
这种方法是“生成式人工智能”的一种形式，这个术语描述的是设计用于在人类水平上运行的技术工具。EVEscape是由英国牛津大学和马萨诸塞州波士顿的哈佛医学院的研究人员开发的。该团队的研究结果最近发表在《自然》杂志上。
Many viruses repeatedly mutate in an effort to stay alive and strong. This requires viruses to infect living organisms. Once inside the body, viruses continue to reproduce and spread.
许多病毒为了生存和强壮而反复变异。这需要病毒感染生物体。病毒一旦进入人体，就会继续繁殖和传播。
The U.S. Centers for Disease Control and Prevention (CDC) explains that repeated mutating creates new variants. Some of these mutations permit the virus "to spread more easily or make it resistant to treatments or vaccines," the CDC said.
美国疾病控制与预防中心(CDC)解释说，反复突变会产生新的变异。美国疾病控制与预防中心表示，其中一些突变使病毒“更容易传播，或使其对治疗或疫苗产生抗药性”。
The researchers built on previous work involving a tool they created called EVE. This tool was designed to study gene mutations that can cause human disease. In a past study, the team said it successfully used EVE to identify mutations linked to conditions like cancer and heart disease.
研究人员在之前的工作基础上创造了一个名为EVE的工具。这个工具被设计用来研究可能导致人类疾病的基因突变。在过去的一项研究中，该团队表示，他们成功地利用EVE识别了与癌症和心脏病等疾病相关的突变。
During the COVID-19 pandemic, the scientists said they recognized a good chance to "rebuild" EVE into a new tool "for the purpose of predicting viral variants."
在2019冠状病毒病大流行期间，科学家们表示，他们认识到将EVE“重建”成一种“用于预测病毒变异”的新工具的好机会。
To do this, the team explained it "turned the clock back to January 2020, just before the COVID-19 pandemic started." The researchers asked the EVEscape tool to predict what mutations would develop from the SARS-CoV-2 virus that causes COVID-19.
为此，该团队解释说，他们“把时钟拨回到2020年1月，就在COVID-19大流行开始之前。”研究人员要求EVEscape工具预测导致COVID-19的SARS-CoV-2病毒会产生哪些突变。
The researchers reported the tool correctly predicted which SARS-CoV-2 mutations would appear and which would become most common, or dominant.
研究人员报告说，该工具正确地预测了哪些SARS-CoV-2突变会出现，哪些会变得最常见或占主导地位。
The team also said the tool predicted which antibody-based treatments "would lose their efficacy as the pandemic progressed and the virus developed mutations to escape these treatments."
该团队还表示，该工具预测了哪些基于抗体的治疗“随着大流行的发展和病毒产生突变以逃避这些治疗而失去功效”。
The study noted EVEscape can make predictions more quickly and effectively than lab-based methods. This is because the tool does not need "to wait for relevant antibodies to arise in the population and become available for testing."
该研究指出，EVEscape可以比基于实验室的方法更快、更有效地进行预测。这是因为该工具不需要“等待相关抗体在人群中出现并可用于测试”。
The team said the system was able to examine tens of thousands of new virus variants appearing each week and identified the ones most likely to become problematic.
该团队表示，该系统能够检查每周出现的数以万计的新病毒变体，并识别出最有可能成为问题的病毒。
Sarah Gurev is a student in the Electrical Engineering and Computer Science program at the Massachusetts Institute of Technoology (MIT). She was a leader of the research. Gurev said that by quickly identifying the threat level of new variants, "we can help inform earlier public health decisions."
Sarah Gurev是麻省理工学院电子工程与计算机科学专业的一名学生。她是这项研究的带头人。Gurev说，通过快速识别新变种的威胁级别，“我们可以帮助为早期的公共卫生决策提供信息。”
The team said it continuously uses the system to examine real-time data about the development of new variants of SARS-CoV-2. It then shares this information with the public and international agencies such as the World Health Organization (WHO).
该团队表示，他们不断使用该系统来检查有关SARS-CoV-2新变种发展的实时数据。然后，它与公众和世界卫生组织(世卫组织)等国际机构分享这些信息。
The researchers said their experiments also showed the EVEscape tool could successfully predict mutating behaviors for other common viruses, including HIV and the flu.
研究人员表示，他们的实验还表明，EVEscape工具可以成功预测其他常见病毒的变异行为，包括艾滋病毒和流感。
Debora Marks is a professor of systems biology at Harvard Medical School's Blavatnik Institute. She was a lead writer of the study. She said the researchers would continue to improve the tool's ability to predict new variants for a number of viruses. "Because if we can, that's going to be extremely important for designing vaccines and therapies."
黛博拉·马克斯是哈佛医学院布拉瓦特尼克研究所的系统生物学教授。她是这项研究的主要作者。她说，研究人员将继续提高该工具预测许多病毒新变种的能力。“因为如果我们能做到，这对设计疫苗和治疗方法将是极其重要的。”
科学家们发明了一种人工智能(AI)工具，旨在在病毒出现之前预测不同的病毒版本，即变种。
Creators of the tool say it works by estimating the likelihood that a variant will permit it to escape the body's own immunity defenses.
该工具的创造者说，它的工作原理是通过估计一种变异使其逃脱人体自身免疫防御的可能性。
The tool is called EVEscape. It works by processing collected data on the development, or evolution, of a virus over time. The system also considers detailed biological and structural information related to the virus.
这个工具叫做EVEscape。它的工作原理是处理收集到的一段时间内病毒发展或进化的数据。该系统还考虑与病毒有关的详细生物学和结构信息。
The method is a form of "generative AI," a term describing technology tools designed to operate at human levels. EVEscape was developed by researchers from Britain's University of Oxford and Harvard Medical School in Boston, Massachusetts. The team's findings recently appeared in a study in the publication Nature.
这种方法是“生成式人工智能”的一种形式，这个术语描述的是设计用于在人类水平上运行的技术工具。EVEscape是由英国牛津大学和马萨诸塞州波士顿的哈佛医学院的研究人员开发的。该团队的研究结果最近发表在《自然》杂志上。
Many viruses repeatedly mutate in an effort to stay alive and strong. This requires viruses to infect living organisms. Once inside the body, viruses continue to reproduce and spread.
许多病毒为了生存和强壮而反复变异。这需要病毒感染生物体。病毒一旦进入人体，就会继续繁殖和传播。
The U.S. Centers for Disease Control and Prevention (CDC) explains that repeated mutating creates new variants. Some of these mutations permit the virus "to spread more easily or make it resistant to treatments or vaccines," the CDC said.
美国疾病控制与预防中心(CDC)解释说，反复突变会产生新的变异。美国疾病控制与预防中心表示，其中一些突变使病毒“更容易传播，或使其对治疗或疫苗产生抗药性”。
The researchers built on previous work involving a tool they created called EVE. This tool was designed to study gene mutations that can cause human disease. In a past study, the team said it successfully used EVE to identify mutations linked to conditions like cancer and heart disease.
研究人员在之前的工作基础上创造了一个名为EVE的工具。这个工具被设计用来研究可能导致人类疾病的基因突变。在过去的一项研究中，该团队表示，他们成功地利用EVE识别了与癌症和心脏病等疾病相关的突变。
During the COVID-19 pandemic, the scientists said they recognized a good chance to "rebuild" EVE into a new tool "for the purpose of predicting viral variants."
在2019冠状病毒病大流行期间，科学家们表示，他们认识到将EVE“重建”成一种“用于预测病毒变异”的新工具的好机会。
To do this, the team explained it "turned the clock back to January 2020, just before the COVID-19 pandemic started." The researchers asked the EVEscape tool to predict what mutations would develop from the SARS-CoV-2 virus that causes COVID-19.
为此，该团队解释说，他们“把时钟拨回到2020年1月，就在COVID-19大流行开始之前。”研究人员要求EVEscape工具预测导致COVID-19的SARS-CoV-2病毒会产生哪些突变。
The researchers reported the tool correctly predicted which SARS-CoV-2 mutations would appear and which would become most common, or dominant.
研究人员报告说，该工具正确地预测了哪些SARS-CoV-2突变会出现，哪些会变得最常见或占主导地位。
The team also said the tool predicted which antibody-based treatments "would lose their efficacy as the pandemic progressed and the virus developed mutations to escape these treatments."
该团队还表示，该工具预测了哪些基于抗体的治疗“随着大流行的发展和病毒产生突变以逃避这些治疗而失去功效”。
The study noted EVEscape can make predictions more quickly and effectively than lab-based methods. This is because the tool does not need "to wait for relevant antibodies to arise in the population and become available for testing."
该研究指出，EVEscape可以比基于实验室的方法更快、更有效地进行预测。这是因为该工具不需要“等待相关抗体在人群中出现并可用于测试”。
The team said the system was able to examine tens of thousands of new virus variants appearing each week and identified the ones most likely to become problematic.
该团队表示，该系统能够检查每周出现的数以万计的新病毒变体，并识别出最有可能成为问题的病毒。
Sarah Gurev is a student in the Electrical Engineering and Computer Science program at the Massachusetts Institute of Technoology (MIT). She was a leader of the research. Gurev said that by quickly identifying the threat level of new variants, "we can help inform earlier public health decisions."
Sarah Gurev是麻省理工学院电子工程与计算机科学专业的一名学生。她是这项研究的带头人。Gurev说，通过快速识别新变种的威胁级别，“我们可以帮助为早期的公共卫生决策提供信息。”
The team said it continuously uses the system to examine real-time data about the development of new variants of SARS-CoV-2. It then shares this information with the public and international agencies such as the World Health Organization (WHO).
该团队表示，他们不断使用该系统来检查有关SARS-CoV-2新变种发展的实时数据。然后，它与公众和世界卫生组织(世卫组织)等国际机构分享这些信息。
The researchers said their experiments also showed the EVEscape tool could successfully predict mutating behaviors for other common viruses, including HIV and the flu.
研究人员表示，他们的实验还表明，EVEscape工具可以成功预测其他常见病毒的变异行为，包括艾滋病毒和流感。
Debora Marks is a professor of systems biology at Harvard Medical School's Blavatnik Institute. She was a lead writer of the study. She said the researchers would continue to improve the tool's ability to predict new variants for a number of viruses. "Because if we can, that's going to be extremely important for designing vaccines and therapies."
黛博拉·马克斯是哈佛医学院布拉瓦特尼克研究所的系统生物学教授。她是这项研究的主要作者。她说，研究人员将继续提高该工具预测许多病毒新变种的能力。“因为如果我们能做到，这对设计疫苗和治疗方法将是极其重要的。”
