Description: The concentrations of sulfate, black carbon (BC) and other aerosols in the Arctic are characterized by high values in late winter and spring (so-called Arctic Haze) and low values in summer. Models have long been struggling to capture this seasonality and especially the high concentrations associated with Arctic Haze. In this study, we evaluate sulfate and BC concentrations from eleven different models driven with the same emission inventory against a comprehensive pan-Arctic measurement data set over a time period of 2 years (2008–2009). The set of models consisted of one Lagrangian particle dispersion model, four chemistry transport models (CTMs), one atmospheric chemistry-weather forecast model and five chemistry climate models (CCMs), of which two were nudged to meteorological analyses and three were running freely. The measurement data set consisted of surface measurements of equivalent BC (eBC) from five stations (Alert, Barrow, Pallas, Tiksi and Zeppelin), elemental carbon (EC) from Station Nord and Alert and aircraft measurements of refractory BC (rBC) from six different campaigns. We find that the models generally captured the measured eBC or rBC and sulfate concentrations quite well, compared to previous comparisons. However, the aerosol seasonality at the surface is still too weak in most models. Concentrations of eBC and sulfate averaged over three surface sites are underestimated in winter/spring in all but one model (model means for January–March underestimated by 59 and 37% for BC and sulfate, respectively), whereas concentrations in summer are overestimated in the model mean (by 88 and 44% for July–September), but with overestimates as well as underestimates present in individual models. The most pronounced eBC underestimates, not included in the above multi-site average, are found for the station Tiksi in Siberia where the measured annual mean eBC concentration is 3 times higher than the average annual mean for all other stations. This suggests an underestimate of BC sources in Russia in the emission inventory used. Based on the campaign data, biomass burning was identified as another cause of the modeling problems. For sulfate, very large differences were found in the model ensemble, with an apparent anticorrelation between modeled surface concentrations and total atmospheric columns. There is a strong correlation between observed sulfate and eBC concentrations with consistent sulfate/eBC slopes found for all Arctic stations, indicating that the sources contributing to sulfate and BC are similar throughout the Arctic and that the aerosols are internally mixed and undergo similar removal. However, only three models reproduced this finding, whereas sulfate and BC are weakly correlated in the other models. Overall, no class of models (e.g., CTMs, CCMs) performed better than the others and differences are independent of model resolution.

Description: The capability of a recombinant mucin-like fusion protein, P-selectin glycoprotein ligand-1/mouse IgG2b (PSGL-1/mIgG2b), carrying Galα1,3Galβ1,4GlcNAc determinants to bind and inhibit Clostridium difficile toxin A (TcdA) was investigated. The fusion protein, produced by a glyco-engineered stable CHO-K1 cell line and designated C-PGC2, was purified by affinity and gel filtration chromatography from large-scale cultures. Liquid chromatography-mass spectrometry was used to characterize O -glycans released by reductive β-elimination, and new diagnostic ions to distinguish Galα1,3Gal- from Galα1,4Gal-terminated O -glycans were identified. The C-PGC2 cell line, which was 20-fold more sensitive to TcdA than the wild-type CHO-K1, is proposed as a novel cell-based model for TcdA cytotoxicity and neutralization assays. The C-PGC2-produced fusion protein could competitively inhibit TcdA binding to rabbit erythrocytes, making it a high-efficiency inhibitor of the hemagglutination property of TcdA. The fusion protein also exhibited a moderate capability for neutralization of TcdA cytotoxicity in both C-PGC2 and CHO-K1 cells, the former with and the latter without cell surface Galα1,3Galβ1,4GlcNAc sequences. Future studies in animal models of C. difficile infection will reveal its TcdA-inhibitory effect and therapeutic potential in C. difficile -associated diseases.

Description: The binding of Shiga-like toxin 1 (Stx1) and Shiga-like toxin 2 (Stx2) to a mucin-like fusion protein, P-selectin glycoprotein ligand-1/mouse IgG 2b (PSGL-1/mIgG 2b ), carrying multiple copies of the blood group P1 determinant on O -glycans was investigated with western blot and the biosensor Biacore. Chinese hamster ovary K-1 (CHO-K1) cells were stably transfected with linearized plasmids encoding the PSGL-1/mIgG 2b fusion protein, the pigeon α1,4-galactosyltransferase (α4Gal-T) and the core 2 β1,6- N -acetylglucosaminyltransferase (C2GnT-I). Western blot analyses of purified PSGL-1/mIgG 2b and liquid chromatography—mass spectrometry (LC-MS) of released O -glycans confirmed the presence of the P1 determinant. Western blot analysis indicated strong binding of Stx1, but not Stx2, to PSGL-1/mIgG 2b . In a Biacore assay, Stx1 and Stx2 were immobilized on a dextran chip and the binding of purified PSGL-1/mIgG 2b and a P k -albumin neoglycoprotein was analyzed. Stx1 and Stx2 bound with high avidity to both PSGL-1/mIgG 2b and P k -albumin, while the Stx1 binding was the strongest. In summary, we have shown that the pigeon α4Gal-T can be aberrantly expressed in CHO cells together with the core 2 enzyme to generate multiple, O-linked P1 determinants on a simultaneously expressed mucin-type fusion protein. P1-decorated PSGL-1/mIgG 2b bound with high avidity to both Stx1 and Stx2, and as such constitutes a potential therapeutic inhibitor of these toxins.

Description: We examined the effects of two over-the-counter H1-antihistamines on the progression of fatty liver disease in male C57Bl/6 wild-type and apolipoprotein E (ApoE)–/– mice. Mice were fed a high-fat diet (HFD) for 3 mo, together with administration of either cetirizine (4 mg/kg body wt) or fexofenadine (40 mg/kg body wt) in drinking water. Antihistamine treatments increased body weight gain, gonadal fat deposition, liver weight, and hepatic steatosis in wild-type mice but not in ApoE–/– mice. Lobular inflammation, acute inflammation, and necrosis were not affected by H1-antihistamines in either genotype. Serum biomarkers of liver injury tended to increase in antihistamine-treated wild-type mice. Serum level of glucose was increased by fexofenadine, whereas lipase was increased by cetirizine. H1-antihistamines reduced the mRNA expression of ApoE and carbohydrate response element-binding protein in wild-type mice, without altering the mRNA expression of sterol regulatory element-binding protein 1c, fatty acid synthase, or ApoB100, in either genotype. Fexofenadine increased both triglycerides and cholesterol ester, whereas cetirizine increased only cholesterol ester in liver, with a concomitant decrease in serum triglycerides by both antihistamines in wild-type mice. Antihistamines increased hepatic levels of conjugated bile acids in wild-type mice, with the effect being significant in fexofenadine-treated animals. The increase was associated with changes in the expression of organic anion transport polypeptide 1b2 and bile salt export pump. These results suggest that H1-antihistamines increase the progression of fatty liver disease in wild-type mice, and there seems to be an association between the severity of disease, presence of ApoE, and increase in hepatic bile acid levels.

Description: Extreme precipitation is a weather phenomenon with tremendous damaging potential for property and human life. As the intensity and frequency of such events is projected to increase in a warming climate, there is an urgent need to advance the existing knowledge on extreme precipitation processes, statistics and impacts across scales. To this end, a working group within the Germany-based project, ClimXtreme, has been established to carry out multidisciplinary analyses of high-impact events. In this work, we provide a comprehensive assessment of the 29 June 2017 heavy precipitation event (HPE) affecting the Berlin metropolitan region (Germany), from the meteorological, impacts and climate perspectives, including climate change attribution. Our analysis showed that this event occurred under the influence of a mid-tropospheric trough over western Europe and two shortwave surface lows over Britain and Poland (Rasmund and Rasmund II), inducing relevant low-level wind convergence along the German–Polish border. Over 11 000 convective cells were triggered, starting early morning 29 June, displacing northwards slowly under the influence of a weak tropospheric flow (10 m s−1 at 500 hPa). The quasi-stationary situation led to totals up to 196 mm d−1, making this event the 29 June most severe in the 1951–2021 climatology, ranked by means of a precipitation-based index. Regarding impacts, it incurred the largest insured losses in the period 2002 to 2017 (EUR 60 million) in the greater Berlin area. We provide further insights on flood attributes (inundation, depth, duration) based on a unique household-level survey data set. The major moisture source for this event was the Alpine–Slovenian region (63 % of identified sources) due to recycling of precipitation falling over that region 1 d earlier. Implementing three different generalised extreme value (GEV) models, we quantified the return periods for this case to be above 100 years for daily aggregated precipitation, and up to 100 and 10 years for 8 and 1 h aggregations, respectively. The conditional attribution demonstrated that warming since the pre-industrial era caused a small but significant increase of 4 % in total precipitation and 10 % for extreme intensities. The possibility that not just greenhouse-gas-induced warming, but also anthropogenic aerosols affected the intensity of precipitation is investigated through aerosol sensitivity experiments. Our multi-disciplinary approach allowed us to relate interconnected aspects of extreme precipitation. For instance, the link between the unique meteorological conditions of this case and its very large return periods, or the extent to which it is attributable to already-observed anthropogenic climate change.