大学英语听力练习双语文本

大学英语听力练习双语文本

Astronomers And Cancer Researchers Work Together To Fight Cancer

At first glance, astronomers and cancer researchers may not seem to have a lot in common. After all, astronomers spend their time gazing at distant stars and galaxies, while oncologists fight tumors.

But at the University of Cambridge in the UK, astronomers and cancer researchers have joined forces. Specifically, astronomers there repurposed image analysis algorithms they use to spot distant galaxies to help oncologists diagnose aggressive tumors.

Here is How It Works

Astronomers use the algorithms to analyze faint,

indistinct images captured by large telescopes. Powerful computers help identify these images as galaxies, stars, planets, and other celestial bodies.

When cancer researchers study tumors, they stain samples to pick out subtle differences that clue them in to what types of proteins a given tumor harbors. Identifying the proteins helps researchers know if a tumor is especially aggressive.

This process typically involves individual scientists peering at tumor samples under microscopes, which is time consuming and laborious. But using reconfigured image analysis algorithms to identify tumor proteins can speed up the process significantly.

Testing The Process

To test the process, the researchers used the adapted algorithms on samples from more than 2,000 breast cancer patients. They found that computer analysis was just as accurate at detecting specific proteins as scientists peering through microscopes. And the computer was much faster.

The researchers plan to further refine the computerized method by testing it on samples from more than 20,000 breast cancer patients.

天文学家和癌症研究者共同抗击癌症

乍一看，天文学家和癌症研究者似乎没有什么共同点。毕竟，天

文学家致力于观察遥远的星体和星系，而肿瘤学家则治疗肿瘤。

但是，在英国的剑桥大学，天文学家和癌症研究者已经开始合作了。具体来说，天文学家改进了过去曾用于观测遥远星系的影像分析法，来协助肿瘤学家诊断恶性肿瘤。

如何实现

天文学家用这种影像分析方法分析由大型望远镜捕捉到的微弱，

模糊的星体图像。强大的计算机能够协助辨认这些图像是星系，恒星，行星还是其它天体。

当癌症研究者研究肿瘤时，对样本染色，进而辨别出微小的差异，染色能够显示出肿瘤样本的蛋白质类型。鉴别蛋白质能够协助研究人

员确定肿瘤是否是恶性的。

这个过程通常需要专业的科学家在显微镜下观察肿瘤样本，既费

时又费力。但是使用改良后的图像分析方法鉴别肿瘤蛋白质，速度就

显著加快了。

程序测试

为了测试这种方法，研究人员对2000多名乳腺癌患者的样本使用改良后的算法分析。他们发现，电脑分析和科学家通过显微镜的观察在鉴别特定蛋白质时同样精确。而且计算机的速度更快。

研究人员计划通过测试20000多名乳腺癌患者样本，进一步改进计算机算法。