Quantification of chromosomes in live cells.

<p>A: Refractive index tomogram of a T84 cell in metaphase measured at 633 nm. B: Dry mass of the entire cell and that of the condensed chromosomes for HT-29 and T84 cells in metaphase. C: Dispersion of chromosomes in eukaryotic cells. Sample images of the refractive index map (cross-section) for a HeLa cell in metaphase measured at (i) 442 nm and (ii) 325 nm, respectively; (iii) a corresponding fluorescence image with nucleic acid stained with Syto13. D: Histogram of the refractive index for chromosomes in HT-29 cells (i, ii) and cytoplasm (iii, iv) at the wavelength of 325 nm (i, iii) and 442 nm (ii, iv), respectively. E: Dispersion parameter estimated from Fig. 3D and Eq. (4). The two distributions are statistically different (<i>p</i> = 0.0133). F: Label-free imaging of cytokinesis in a HeLa cell using RTPM. Cross-sections of the 3-D refractive index map are shown at different time points. Colorbars in A, C and F represent the refractive index.</p

Schematic layout of the regularized tomographic phase microscope (RTPM) set-up.

<p>L: lens; P: pinhole; BF: back focal plane; CL: condenser lens; S: sample; OL: objective lens; TL: tube lens; GM: galvanometer mirror; BS: beam splitter. The open circles on the right represent a trace of the focused beam in the back focal plane of condenser lens when the angle of the incident beam is varied at the sample plane.</p

High Resolution Live Cell Raman Imaging Using Subcellular Organelle-Targeting SERS-Sensitive Gold Nanoparticles with Highly Narrow Intra-Nanogap

We report a method to achieve high speed and high resolution live cell Raman images using small spherical gold nanoparticles with highly narrow intra-nanogap structures responding to NIR excitation (785 nm) and high-speed confocal Raman microscopy. The three different Raman-active molecules placed in the narrow intra-nanogap showed a strong and uniform Raman intensity in solution even under transient exposure time (10 ms) and low input power of incident laser (200 μW), which lead to obtain high-resolution single cell image within 30 s without inducing significant cell damage. The high resolution Raman image showed the distributions of gold nanoparticles for their targeted sites such as cytoplasm, mitochondria, or nucleus. The high speed Raman-based live cell imaging allowed us to monitor rapidly changing cell morphologies during cell death induced by the addition of highly toxic KCN solution to cells. These results strongly suggest that the use of SERS-active nanoparticle can greatly improve the current temporal resolution and image quality of Raman-based cell images enough to obtain the detailed cell dynamics and/or the responses of cells to potential drug molecules

PCA decomposition of the spectral dataset.

<p>(A) The first four principal components corresponding to the entire spectral dataset acquired from the albumin and glycated albumin drop-coated deposition samples. These four principal components, combined, explain 99.74% of the net variance in the dataset. (B) Scores plot corresponding to principal components 2, 3 and 4 for the spectral dataset acquired from albumin and glycated albumin drop-coated rings. The albumin and glycated albumin samples are indicated by green circles and red squares, respectively. The optimal plane of separation, shown here, is constructed using a logistic regression algorithm (further details are noted in the text).</p

Measuring Uptake Dynamics of Multiple Identifiable Carbon Nanotube Species via High-Speed Confocal Raman Imaging of Live Cells

Carbon nanotube uptake was measured via high-speed confocal Raman imaging in live cells. Spatial and temporal tracking of two cell-intrinsic and nine nanotube-derived Raman bands was conducted simultaneously in RAW 264.7 macrophages. Movies resolved single (<i>n</i>, <i>m</i>) species, defects, and aggregation states of nanotubes transiently as well as the cell position, denoted by lipid and protein signals. This work portends the real-time molecular imaging of live cells and tissues using Raman spectroscopy, affording multiplexing and complete photostability

Relative standard deviation plot of precision for glycated albumin determination.

<p>Plot of precision as a function of reference glycated albumin concentration. The red circle gives the values computed from the experimental measurements and the solid black curve represents the best-fit exponential curve.</p

PLS prediction results of glycated albumin samples.

<p>Prediction results obtained using partial least squares (PLS) regression on glycated albumin samples. The solid line denotes y = x values.</p

Raman spectra acquired from the drop-coated albumin and glycated albumin samples.

<p>Raman spectra acquired from the drop-coated albumin and glycated albumin samples derived from their corresponding aqueous solutions, respectively (the spectra are normalized and offset for the sake of clarity). The asterisks indicate the principal peaks, namely the 1655 cm⁻¹ Amide-I band, the 1447 cm⁻¹ CH₂ deformation band, the 1002 cm⁻¹ phenylalanine band and the tyrosine doublet at 828 and 850 cm⁻¹.</p

Chemical assignments of vibrational modes for the Raman spectra acquired from drop-coated deposition of human serum albumin sample.

<p>Here, ν means stretching vibration; and δ deformation. Tyr, Trp and Phe refer to the tyrosine, tryptophan and phenylalanine residues, respectively.</p

Visualization 1: Digital micromirror device-based laser-illumination Fourier ptychographic microscopy

The reconstruction of the sample information in spatial and Fourier domain implemented by running the self-developed software written in Matlab Originally published in Optics Express on 19 October 2015 (oe-23-21-26999