The optical constants, n and k, are required to model the reflection, refraction and transmission of light at the first surface interface of a material, as well as its propagation through the material; here n corresponds to the real component and k the imaginary component of the refractive index. Several spectroscopic methods have been used to determine the n and k values for different materials, including single-angle reflectance spectroscopy and ellipsometry. The single-angle reflectance method quantitatively records the specular reflectance R(ṽ) from a plane parallel face of the material and uses the Kramers-Kronig transform to extract the n and k values. For most compounds, however, it is difficult to obtain a single crystal or high-quality window of sufficient planarity and of the appropriate dimensions (several mm) to make the measurement. For this reason, we further investigate the use of pressed pellets of neat powdered substances to measure optical constants of these substances using the single-angle reflectance method. We have found that surface roughness can significantly influence the measured quantitative reflectance spectrum R(ṽ) and, consequently, the derived n and k values. A collaborative study between Defence Research and Development Canada - Valcartier Research Center (DRDC-VRC) and Pacific Northwest National Laboratory (PNNL) has been carried out using different pellets of neat ammonium sulfate [(NH4)2SO4] to show how parameters, such as the particle size composition and the grinding process, can affect the reflectance spectrum used to derive the optical constants. All pressed pellets were characterized by single-angle reflectance spectroscopy.
Several biotechnologies are currently available to quantify how cells allocate resources between growth and carbon storage, such as mass spectrometry. However, such biotechnologies require considerable amounts of cellular biomass to achieve adequate signal-to-noise ratio. In this way, existing biotechnologies inevitably operate in a ‘population averaging’ mode and, as such, they cannot unmask how cells allocate resources between growth and storage in a high-throughput fashion with single-cell, or subcellular resolution. This methodological limitation inhibits our fundamental understanding of the mechanisms underlying resource allocations between different cellular metabolic objectives. In turn, this knowledge gap also pertains to systems biology effects, such as cellular noise and the resulting cell-to-cell phenotypic heterogeneity, which could potentially lead to the emergence of distinct cellular subpopulations even in clonal cultures exposed to identical growth conditions. To address this knowledge gap, we applied a high-throughput quantitative phase imaging strategy. Using this strategy, we quantified the optical-phase of light transmitted through the cell cytosol and a specific cytosolic organelle, namely the lipid droplet (LD). With the aid of correlative secondary ion mass spectrometry (NanoSIMS) and transmission electron microscopy (TEM), we determined the protein content of different cytosolic organelles, thus enabling the conversion of the optical phase signal to the corresponding dry density and dry mass. The high-throughput imaging approach required only 2 μL of culture, yielding more than 1,000 single, live cell observations per tested experimental condition, with no further processing requirements, such as staining or chemical fixation.
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