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 AWARDS

2023 - Life Sciences Invention of the Year---Ming Zheng
    
  Life Sciences Invention of the Year
Detection of Ovarian Cancer via the Spectral Fingerprinting of Quantum-Defect-Modified Carbon Nanotubes in Serum by Machine Learning
Winner's Name
                                Ming Zheng

Awarded
                                May 3, 2023

Awarding Organization
      
                          University of MarylandMing Zheng holding Carbon NanotubeMing Zheng of the NIST Material Measurement Laboratory holding carbon nanotube.
                    Credit:
          
  Rich Press
  
      Annually, ovarian cancer is responsible for 184,000 deaths worldwide. Survival rates are strongly linked to the stage at which the disease is detected, with just a 29% five-year survival rate if the cancer has metastasized—the stage at which most cases are diagnosed. But the survival rate rises to more than 90% if the disease is caught before the cancer has spread outside the ovaries. However, few serum biomarker tests—blood tests that reveal tumor development—are highly specific yet sufficiently sensitive enough to detect early-stage disease.

Researchers YuHuang Wang, a professor of chemistry and biochemistry, Daniel Heller and Mijin Kim of Memorial Sloan-Kettering Cancer Center, Anand Jagota of Lehigh University, and Ming Zheng of the NIST Material Measurement Laboratory (pictured above) have addressed this problem by using a new type of sensor technology. Based on quantum defect-tailored carbon nanotubes augmented by machine learning algorithms, this new sensor technology can detect the "disease fingerprint" of high-grade serous ovarian carcinoma in serum samples, providing a much more accurate and reliable diagnosis. This breakthrough has the potential to save lives by allowing doctors to catch ovarian cancer early, when it is most treatable.

**To See Life in a Drop of Blood**
Blog post by Ming Zheng
  Materials
      
            Life Sciences Invention of the Year
Detection of Ovarian Cancer via the Spectral Fingerprinting of Quantum-Defect-Modified Carbon Nanotubes in Serum by Machine Learning
Winner's Name
                                Ming Zheng

Awarded
                                May 3, 2023

Awarding Organization
      
                          University of Maryland
                          Organizations
      
      NIST HeadquartersLaboratory ProgramsMaterial Measurement LaboratoryMaterials Science and Engineering DivisionPolymers and Complex Fluids Group

    
    Contact
      
        

Vivek M. Prabhu
    
      
  vivek.prabhu@nist.gov
  (301) 975-3657

Created May 3, 2023, Updated June 24, 2023
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