No abstract

We introduce inline digital holographic microscopy (in-line DHM) as a label-free technique for detecting tumor cells in blood. The optimized DHM platform fingerprints every cell flowing through a microchannel at 10 000 cells per second, based on three features - size, maximum intensity and mean intensity. To identify tumor cells in a background of blood cells, we developed robust gating criteria using machine-learning approaches. We established classifiers from the features extracted from 100 000-cell training sets consisting of red blood cells, peripheral blood mononuclear cells and tumor cell lines. The optimized classifier was then applied to targeted features of a single cell in a mixed cell population to make quantitative cell-type predictions. We tested our classification system with tumor cells spiked at different levels into a background of lysed blood that contained predominantly peripheral blood mononuclear cells. Results show that our holographic screening method can readily detect as few as 10 tumor cells per mL, and can identify tumor cells at a false positive rate of at most 0.001%. This purely optical approach obviates the need for antibody labeling and allows large volumes of sample to be quickly processed. Moreover, our in-line DHM approach can be combined with existing circulation tumor cell enrichment strategies, making it a promising tool for label-free analysis of liquid-biopsy samples.

Using porous hollow fiber membranes, this study illustrates a novel technique to continuously synthesize polymer-coated drug crystals by antisolvent crystallization. The synthesized polymer-coated drug crystals involve crystals of the drug Griseofulvin (GF) coated by a thin layer of the polymer Eudragit RL100. The process feed, an acetone solution of the drug GF containing the dissolved polymer, was passed through the shell side of a membrane module containing many porous hollow fibers of Nylon-6. Through the lumen of the hollow fibers, the antisolvent water was passed at a higher pressure to inject water jets through every pore in the fiber wall into the shell-side acetone feed solution, creating an extremely high level of supersaturation and immediate crystallization. It appears that the GF crystals are formed first and serve as nuclei for the precipitation of the polymer Eudragit, which forms a thin coating around the GF crystals. The polymer-coated drug crystals were collected by a filtration device at the shell-side outlet of the membrane module, and the surface morphology, particle size distribution, and the polymer coating thickness were then characterized by scanning electron microscopy (SEM), scanning transmission electron microscopy (STEM), laser diffraction spectroscopy (LDS), and thermogravimetric analysis (TGA). To study the properties of the coated drug crystals, X-ray diffraction (XRD), Raman spectroscopy, and dissolution tests were implemented. These results indicate that a polymer-coated, free-flowing product was successfully developed under appropriate conditions in this novel porous hollow fiber antisolvent crystallization (PHFAC) method. The coated drug particles can be potentially used for controlled release. The molecular and the crystal structures of GF were not affected by the PHFAC method, which may be easily scaled up.

Large-scale and label-free phenotyping of cells holds great promise in medicine, especially in cancer diagnostics and prognosis. Here, we introduce inline digital holography microscopy for volumetric imaging of cells in bulk flow and fingerprinting of flowing tumor cells based on two metrics, in-focus scattered intensity and cell diameter. Using planar distribution of immobilized particles, we identify the optimal recording distance and microscope objective magnification that minimizes the error in measurement of particle position, size and scattered intensity. Using the optimized conditions and the two metrics, we demonstrate the capacity to enumerate and fingerprint more than 100,000 cells. Finally, we highlight the power of our label-free and high throughput technology by characterizing breast tumor cell lines with different metastatic potentials and distinguishing drug resistant ovarian cancer cells from their parental cell line.

No abstract