Combining vancomycin-modified gold nanorod arrays and colloidal nanoparticles as a sandwich model for the discrimination of Gram-positive bacteria and their detection via surface-enhanced Raman spectroscopy (SERS).

This study reports the development of a highly sensitive antibiotic-based discrimination and sensor platform for the detection of Gram-positive bacteria through surface-enhanced Raman spectroscopy (SERS). Herein, a combination of gold nanorod arrays (GNAs) and colloidal gold nanoparticles (AuNPs) was used as a SERS platform. To specifically capture Gram-positive bacteria, both GNAs and AuNPs were functionalized with thiol-modified vancomycin (HS-Van) molecules.

Bright-field holography: cross-modality deep learning enables snapshot 3D imaging with bright-field contrast using a single hologram.

Digital holographic microscopy enables the 3D reconstruction of volumetric samples from a single-snapshot hologram. However, unlike a conventional bright-field microscopy image, the quality of holographic reconstructions is compromised by interference fringes as a result of twin images and out-of-plane objects. Here, we demonstrate that cross-modality deep learning using a generative adversarial network (GAN) can endow holographic images of a sample volume with bright-field microscopy contrast, combining the volumetric imaging capability of holography with the speckle- and artifact-free image contrast of incoherent bright-field microscopy.