LIN lab Where light interacts with nanomaterials

Projects

Deep Raman techniques for in vivo detection

Deep Raman techniques for in vivo detection

  • Tissue optics simulation of light transportation
  • Transmission Raman spectroscopy (TRS)
  • Spatially-offset Raman spectroscopy (SORS)
  • TRS setup implementation for non-invasive in vivo detection

Non-invasive localization of human lesions remains a long-standing pursuit for clinical applications. Optical modalities are widely used for biomedical imaging and diagnosing. But due to the strong photon absorption and scattering of biological tissues, it is challenging to realize in vivo non-invasive detection via optical modalities.We address this issue with the use of in vivo surface-enhanced deep Raman spectroscopy (SEDRS) with a series of advancements toward non-invasive localization of deep lesions hidden in living animals. We made the first quantitative assessments of Raman spectroscopic detection depth into the biological tissues. We developed high-brightness SERS nanotags and a home-built transmission Raman system, enabling detection through >10 cm of biological tissue under safe laser exposure (Small Methods, 2022). We put forward a depth-prediction method based on Raman spectral peak ratios, leveraging tissue optical properties to accurately determine the depth of lesion phantoms, achieving the mean error of <11.8% . Based on this, the non-invasive localization of lesion phantom using multi-peak information of Raman spectra in ex vivo tissues or in live animals was achieved. We completed the first SEDRS-guided peri-operative lymph node biopsy on pig models.

Representative papers:

Label-free Raman spectroscopy for cancer diagnosis

Label-free Raman spectroscopy for cancer diagnosis

Modern cancer diagnosis requires histological, molecular and genomic tumor analysis. These approaches are usually resource-intensive and time-consuming. We use highly specific Raman spectroscopy to differentiate the diseased part by the contribution of Raman-active molecules in different tissues. The detected signal provides molecular information that enables accurate cancer diagnosis and prognosis. Our label-free detection research often push the limits of existing technologies. We thus use the computational power of machine learning and artificial intelligence to improve our understanding of the spectral properties of biomolecules.

  • Fiber-optics Raman probe for in situ diagnosis
  • Euclidean distance-based Raman spectroscopy (EDRS)
  • Raman spectral processing and information extraction

Representative papers:

Inventing plasmonic nanomaterials

Inventing plasmonic nanomaterials

Plasmonic nanostructures exhibit a unique combination of physical, chemical, and biological properties, such as large absorption and scattering cross-sections, high sensitivity to the local dielectric environment, and an enhanced electric field at the surface. We use surface-enhanced Raman spectroscopy (SERS) as a bioimaging modality for spectral-guided surgery. We fabricate plasmonic nanomaterials with tunable optical properties by adjusting the surface chemistry and texture of designer materials. The integration of metal structures and organic materials form a powerful platform for a wide variety of applications including plasmonic photovoltaics, chemical and biological sensors, bioimaging, and therapeutics.

  • Design and fabrication of plasmonic nanostructure
  • Surface-enhanced Raman spectroscopy (SERS) substrate
  • Invention of ultrabright SERS nanotag for therapy and diagnosis

Representative papers:

Exploring bio-material interfaces in cellular scenarios

Exploring bio-material interfaces in cellular scenarios

Nanomaterials have emerging applications in medical implants, cell delivery, and in vivo neuromodulation. The interaction of biomolecules with metal nanostructures can be studied by investigating the near-field plasmon effects. We rationally design the plasmonic nanomaterials that serve as miniaturized antennas to display the biological activity for the investigation of cellular metabolism or phenotype development in living and non-living matter.

  • Biocompatible surface functionalization
  • Selective biomolecule sensing
  • Cellular or subcellular metabolism study

Representative papers: