Impaired responses of leukemic dendritic cells derived from a human myeloid cell line to LPS stimulation

Several myeloid leukemia-derived cells have been reported to possess the ability to differentiate into dendritic cells (DC). MUTZ-3, a myeloid leukemia cell line, responds to GM-CSF, IL-4 and TNF-alpha, and acquires a phenotype similar to immature monocyte-derived DC (MoDC). In the present study, MUTZ-3-derived DC (MuDC) showed high level expression of HLA class II molecules, CD80 and CD86, and were able to function as potent antigen presenting cells as previously reported. Interestingly, MuDC maturation was induced by CD40- mediated stimulation, but not by LPS stimulation. We analyzed CCR1, CCR7 and Toll-like receptor (TLR) expressions in MuDC, and measured IL-10 and IL-12 production after maturation stimuli. Although MuDC expressed the mRNA for TLR4, a major component of the LPS receptor system, they did not show an enhanced level of CCR7 or cytokine production after LPS stimulation. In contrast, they responded to CD40 stimulation, which resulted in increased levels of CD83, CD86 and CCR7. Moreover, while LPS- stimulated MoDC could potently stimulate NK cells in a DC-NK cell co-culture, LPS-stimulated MuDC failed to stimulate primary NK cells. Taken together, our findings suggest that, although MuDC express TLR4, unlike TNF-alpha and IL-1beta, LPS does not stimulate MuDC to acquire mature phenotypes, and they may have impaired activity to initiate innate immune response.     

A Relation Between Closure Operators on a Small Category and Its Category of Presheaves

In this paper we show that each factorization structure on a small category , satisfying certain conditions, yields a presheaf on and a morphism of presheaves . We then give connections, and set up one to one correspondences, between subclasses of the following classes: (a) closure operators on (b) subobjects of (c) morphisms from to (d) weak Lawvere–Tierney topologies (e) weak Grothendieck topologies (f) closure operators on .     

Raman labeled nanoparticles: characterization of variability and improved method for unmixing

Raman spectroscopy can differentiate the spectral fingerprints of many molecules, resulting in potentially high multiplexing capabilities of Raman‐tagged nanoparticles. However, an accurate quantitative unmixing of Raman spectra is challenging because of potential overlaps between Raman peaks from each molecule, as well as slight variations in the location, height, and width of very narrow peaks. If not accounted for properly, even minor fluctuations in the spectra may produce significant error that will ultimately result in poor unmixing accuracy. The objective of our study was to develop and validate a mathematical model of the Raman spectra of nanoparticles to unmix the contributions from each nanoparticle allowing simultaneous quantitation of several nanoparticle concentrations during sample characterization. We developed and evaluated an algorithm for quantitative unmixing of the spectra called narrow peak spectral algorithm (NPSA). Using NPSA, we were able to successfully unmix Raman spectra of up to seven Raman nanoparticles after correcting for spectral variations of 30% intensity and shifts in peak locations of up to 10 cm⁻¹, which is equivalent to 50% of the full width at half maximum (FWHM). We compared the performance of NPSA to the conventional least squares (LS) analysis. Error in the NPSA is approximately 50% lower than in the LS. The error in estimating the relative contributions of each nanoparticle with the use of the NPSA are in the range of 10–16% for equal ratios and 13–19% for unequal ratios for the unmixing of seven composite organic–inorganic nanoparticles (COINs); whereas, the errors from using the traditional LS approach were in the range of 25–38% for equal ratios and 45–68% for unequal ratios. Here, we report for the first time the quantitative unmixing of seven nanoparticles with a maximum root mean square of the percentage error (RMS%) error of less than 20%. Copyright © 2012 John Wiley & Sons, Ltd.