ITP in dynamically double-coated fused-silica capillaries

Bidirectional ITP in fused-silica capillaries double-coated with Polybrene and poly-(vinylsulfonate) is a robust approach for analysis of low-molecular-mass compounds. EOF towards the cathode is strong (mobility >4.0 x 10(-8) m(2)/Vs) within the entire pH range investigated (2.40-8.08), dependent on ionic strength and buffer used and, at constant ionic strength, higher at alkaline pH. Electrokinetic separations and transport in such coated capillaries can be described with a dynamic computer model which permits the combined simulation of electrophoresis and electroosmosis in which the EOF is predicted either with a constant (i.e. pH- and ionic strength-independent) or a pH- and ionic strength-dependent electroosmotic mobility. Detector profiles predicted by computer simulation agree qualitatively well with bidirectional isotachopherograms that are monitored with a setup comprising two axial contactless conductivity detectors and a UV absorbance detector. The varying EOF predicted with a pH- and ionic strength-dependent electroosmotic mobility can be regarded as being realistic.

Relative sensitivity factors of inorganic cations in frozen-hydrated standards in secondary ion MS analysis

We describe the measurement, at 100 K, of the SIMS relative sensitivity factors (RSFs) of the main physiological cations Na+, K+, Mg2+, and Ca2+ in frozen-hydrated (F-H) ionic solutions. Freezing was performed by either plunge freezing or high-pressure freezing. We also report the measurement of the RSFs in flax fibers, which are a model for ions in the plant cell wall, and in F-H ionic samples, which are a model for ions in the vacuole. RSFs were determined under bombardment with neutral oxygen (FAB) for both the fibers and the F-H samples. We show that referencing to ice-characteristic secondary ions is of little value in determining RSFs and that referencing to K is preferable. The RSFs of Na relative to K and of Ca relative to Mg in F-H samples are similar to their respective values in fiber samples, whereas the RSFs of both Ca and Mg relative to K are lower in fibers than in F-H samples. Our data show that the physical factors important for the determination of the RSFs are not the same in F-H samples and in homogeneous matrixes. Our data show that it is possible to perform a SIMS relative quantification of the cations in frozen-hydrated samples with an accuracy on the order of 15%. Referencing to K permits the quantification of the ionic ratios, even when the absolute concentration of the referencing ion is unknown. This is essential for physiological studies of F-H biological samples.

Indocyanine Green Loaded Biocompatible Nanoparticles: Stabilisation of Indocyanine Green (ICG) Using Biocompatible Silica-Poly (&epsilon-Caprolactone) Grafted Nanocomposites

Indocyanine green (ICG) is a chemically labile compound which needs to be stabilized in aqueous media to be used in biomedical applications. In the present study, poly(ε-caprolactone) (PCL), a semi-crystalline polyester, was used to encapsulate and stabilize ICG in a hydrophobic environment. A hydrophobic and biocompatible nanocomposite was obtained by the process of encapsulating inorganic silica. ICG was embedded in the hydrophobic polymer coating by starting from a well-defined silica (Si) core of either 80 nm or 120 nm diameter, which served as a template for a ‘grafting from’ approach using ε-caprolactone. The obtained nanocomposite Si grafted PCL/ICG was based on silica nanoparticles grafted with PCL, in which ICG was adsorbed. The nanoparticles were characterized by IR spectroscopy, thermogravimetric analysis (TGA) and scanning electron microscopy (SEM). The change in the surface charge and the colloidal stability of the nanoparticles was followed by zeta potential measurements. This approach of synthesizing nanocomposite-based ICG demonstrates a new route to stabilize ICG. We synthesized biocompatible nanoparticles containing a high ICG concentration and exhibiting excellent stability to aqueous decomposition.

Fourier transform infrared spectroscopy, a new method for rapid determination of total organic and inorganic carbon and biogenic silica concentration in lake sediments

Abstract We demonstrate the use of Fourier transform infrared spectroscopy (FTIRS) to make quantitative measures of total organic carbon (TOC), total inorganic carbon (TIC) and biogenic silica (BSi) concentrations in sediment. FTIRS is a fast and costeffective technique and only small sediment samples are needed (0.01 g). Statistically significant models were developed using sediment samples from northern Sweden and were applied to sediment records from Sweden, northeast Siberia and Macedonia. The correlation between FTIRS-inferred values and amounts of biogeochemical constituents assessed conventionally varied between r = 0.84–0.99 for TOC, r = 0.85– 0.99 for TIC, and r = 0.68–0.94 for BSi. Because FTIR spectra contain information on a large number of both inorganic and organic components, there is great potential for FTIRS to become an important tool in paleolimnology.

An in vitro toxicity evaluation of gold-, PLLA- and PCL-coated silica nanoparticles in neuronal cells for nanoparticle-assisted laser-tissue soldering.

The uptake of silica (Si) and gold (Au) nanoparticles (NPs) engineered for laser-tissue soldering in the brain was investigated using microglial cells and undifferentiated and differentiated SH-SY5Y cells. It is not known what effects NPs elicit once entering the brain. Cellular uptake, cytotoxicity, apoptosis, and the potential induction of oxidative stress by means of depletion of glutathione levels were determined after NP exposure at concentrations of 10(3) and 10(9)NPs/ml. Au-, silica poly (ε-caprolactone) (Si-PCL-) and silica poly-L-lactide (Si-PLLA)-NPs were taken up by all cells investigated. Aggregates and single NPs were found in membrane-surrounded vacuoles and the cytoplasm, but not in the nucleus. Both NP concentrations investigated did not result in cytotoxicity or apoptosis, but reduced glutathione (GSH) levels predominantly at 6 and 24h, but not after 12 h of NP exposure in the microglial cells. NP exposure-induced GSH depletion was concentration-dependent in both cell lines. Si-PCL-NPs induced the strongest effect of GSH depletion followed by Si-PLLA-NPs and Au-NPs. NP size seems to be an important characteristic for this effect. Overall, Au-NPs are most promising for laser-assisted vascular soldering in the brain. Further studies are necessary to further evaluate possible effects of these NPs in neuronal cells.

Independent measurement of biogenic silica in sediments by FTIR spectroscopy and PLS regression

We present an independent calibration model for the determination of biogenic silica (BSi) in sediments, developed from analysis of synthetic sediment mixtures and application of Fourier transform infrared spectroscopy (FTIRS) and partial least squares regression (PLSR) modeling. In contrast to current FTIRS applications for quantifying BSi, this new calibration is independent from conventional wet-chemical techniques and their associated measurement uncertainties. This approach also removes the need for developing internal calibrations between the two methods for individual sediments records. For the independent calibration, we produced six series of different synthetic sediment mixtures using two purified diatom extracts, with one extract mixed with quartz sand, calcite, 60/40 quartz/calcite and two different natural sediments, and a second extract mixed with one of the natural sediments. A total of 306 samples—51 samples per series—yielded BSi contents ranging from 0 to 100 %. The resulting PLSR calibration model between the FTIR spectral information and the defined BSi concentration of the synthetic sediment mixtures exhibits a strong cross-validated correlation ( R2cv = 0.97) and a low root-mean square error of cross-validation (RMSECV = 4.7 %). Application of the independent calibration to natural lacustrine and marine sediments yields robust BSi reconstructions. At present, the synthetic mixtures do not include the variation in organic matter that occurs in natural samples, which may explain the somewhat lower prediction accuracy of the calibration model for organic-rich samples.