Inhibition of FcepsilonRI-dependent mediator release and calcium flux from human mast cells by sialic acid-binding immunoglobulin-like lectin 8 engagement

BACKGROUND: Sialic acid-binding immunoglobulin-like lectins (Siglecs) are a family of glycan-binding inhibitory receptors, and among them, Siglec-8 is selectively expressed on human eosinophils, basophils, and mast cells. On eosinophils, Siglec-8 engagement induces apoptosis, but its function on mast cells is unknown. OBJECTIVE: We sought to study the effect of Siglec-8 engagement on human mast cell survival and mediator release responses. METHODS: Human mast cells were generated from CD34+ precursors. Apoptosis was studied by using flow cytometry. Mast cell mediator release or human lung airway smooth muscle contraction was initiated by FcepsilonRI cross-linking with or without preincubation with Siglec-8 or control antibodies, and release of mediators was analyzed along with Ca++ flux. RBL-2H3 cells transfected with normal and mutated forms of Siglec-8 were used to study how Siglec-8 engagement alters mediator release. RESULTS: Siglec-8 engagement failed to induce human mast cell apoptosis. However, preincubation with Siglec-8 mAbs significantly (P < .05) inhibited FcepsilonRI-dependent histamine and prostaglandin D(2) release, Ca++ flux, and anti-IgE-evoked contractions of human bronchial rings. In contrast, release of IL-8 was not inhibited. Siglec-8 ligation was also shown to inhibit beta-hexosaminidase release and Ca++ flux triggered through FcepsilonRI in RBL-2H3 cells transfected with full-length human Siglec-8 but not in cells transfected with Siglec-8 containing a tyrosine to phenylalanine point mutation in the membrane-proximal immunoreceptor tyrosine-based inhibitory motif domain. CONCLUSION: These data represent the first reported inhibitory effects of Siglec engagement on human mast cells.

Small aliquot and single grain IRSL and post-IR IRSL dating of fluvial and alluvial sediments from the Pativilca valley, Peru

Infrared stimulated luminescence (IRSL) and post-IR IRSL are applied to small aliquots and single grains to determine the equivalent dose (De) of eleven alluvial and fluvial sediment samples collected in the Pativilca valley, Central Peru at ca. 10°S latitude. Small aliquot De distributions are rather symmetric and display over-dispersion values between 15 and 46%. Small aliquot g-values range between 4 and 8% per decade for the IRSL and 1 and 2% per decade for the post-IR IRSL signal. The single grain De distributions are highly over-dispersed with some of them skewed to higher doses, implying partial bleaching; this is especially true for the post-IR IRSL. Measurements of a modern analog reveal that residuals due to partial bleaching are present in both the IRSL as well as the post-IR IRSL signal. The g-values of individual grains exhibit a wide range with high individual uncertainties and might contribute significantly to the spread of the single grain De values, at least for the IRSL data. Electron Microprobe Analysis performed on single grains reveal that a varying K-content can be excluded as the origin of over-dispersion. Final ages for the different approaches are calculated using the Central Age Model and the Minimum Age Model (MAM). The samples are grouped into well-beached, potentially well-bleached and partially bleached according to the evaluation of the single grain distributions and the agreement of age estimates between methods. The application of the MAM to the single grain data resulted in consistent age estimates for both the fading corrected IRSL and the post-IR IRSL ages, and suggests that both approaches are suitable for dating these samples. Keywords

Estimating Annual CO2 Flux for Lutjewad Station Using Three Different Gap-Filling Techniques

Long-term measurements of CO2 flux can be obtained using the eddy covariance technique, but these datasets are affected by gaps which hinder the estimation of robust long-term means and annual ecosystem exchanges. We compare results obtained using three gap-fill techniques: multiple regression (MR), multiple imputation (MI), and artificial neural networks (ANNs), applied to a one-year dataset of hourly CO2 flux measurements collected in Lutjewad, over a flat agriculture area near the Wadden Sea dike in the north of the Netherlands. The dataset was separated in two subsets: a learning and a validation set. The performances of gap-filling techniques were analysed by calculating statistical criteria: coefficient of determination (R2), root mean square error (RMSE), mean absolute error (MAE), maximum absolute error (MaxAE), and mean square bias (MSB). The gap-fill accuracy is seasonally dependent, with better results in cold seasons. The highest accuracy is obtained using ANN technique which is also less sensitive to environmental/seasonal conditions. We argue that filling gaps directly on measured CO2 fluxes is more advantageous than the common method of filling gaps on calculated net ecosystem change, because ANN is an empirical method and smaller scatter is expected when gap filling is applied directly to measurements.