Characterization of IgG and IgE Binding to Parvalbumin Derived from Commercially Important Fish Species

Rationale: Parvalbumin is recognized as pan-allergen in fish and frog. However, previous studies demonstrated that the IgE- and IgG-binding patterns to parvalbumins vary depending on the fish species. We aimed to use 3 anti-parvalbumin IgG and human IgE to investigate the contributing factors for the binding differences. Methods: Indirect enzyme-linked immunosorbent assay (ELISA) and IgG immunoblotting were used to determine the reactivity of the polyclonal anti-cod parvalbumin antibody and the commercially available, monoclonal anti-frog and anti-carp parvalbumin antibodies against raw muscle extracts of 25 fish species. Additionally, sera from 46 individuals with clinical history of fish allergy were analyzed for IgE reactivity to parvalbumin using indirect ELISA. Inhibition ELISAwas performed to determine the effects of heating and calcium on IgG-binding to parvalbumin. Results: The 3 IgG antibodies demonstrated varying specificity for different fish species. Polyclonal anti-cod parvalbumin antibody showed reactivity to a wider range of species, whereas the monoclonal anti-frog parvalbumin antibody showed the least cross-reactivity. The binding of the 3 IgG antibodies to parvalbumin was unaffected by heating, but the absence of calcium abolished the binding. IgE reactivity to cod parvalbumin or cod extracts were observed in \u3e 50% of individuals’ sera, whereas \u3c 0.1% of the sera showed reactivity to tuna and swordfish extracts. Both IgG and IgE antibodies showed low reactivity to tuna and swordfish that are apparently deficient in parvalbumin. Conclusions: These results suggested that the antibodies’ specificity to parvalbumins in various fish species is associated with the parvalbumin expression, its structural conformation, and the primary structure of antigenic determinations on parvalbumin

Identification and Analysis of the IgE Binding by Parvalbumin and Other Potential Allergens in Different Fish and Frog Species

Rationale: Serological cross-reactivity to different fish and frog species is common among fish-allergic individuals.We examined the intra- and inter-individual diversity in IgE responses of fish-allergic subjects to various fish and frog species and identified novel allergens besides parvalbumin. Methods: Sera from 38 subjects with a clinical history of fish allergy were analyzed for IgE-binding profiles to crude extracts of 26 raw fish and frog species, and purified cod and carp parvalbumin using IgE-immunoblotting. Sera of 7 subjects showing similar IgE-binding profiles in the IgEimmmunoblotting were pooled to identify potential allergens in pilchard, herring, cod, cusk, and rainbow trout using two-dimensional electrophoresis (2D) combined with IgE-immunoblotting and liquid chromatography-tandem mass spectrometry. Results: IgE-immunoblotting demonstrated great diversity among the fish-allergic individuals with respect to the IgE-binding to the parvalbumins and non-parvalbumin proteins in fish and frog species. Of the 38 individuals, 26 (68%) and 21 (55%) reacted to cod and carp parvalbumin, respectively. However, low IgE reactivity to parvalbumin from frog, mahi-mahi, and swordfish was observed. The pooled sera showed IgE-binding to parvalbumin and its corresponding isoforms separated by 2D in all 5 species. The IgE from pooled sera also recognized several novel fish allergens, including alpha actin, enolase, creatine kinase, glyceraldehyde 3-phosphate dehydrogenase, and fast myosin light chain proteins. Conclusions: The variation in IgE-binding depended on the individuals and fish species analyzed. The results suggested parvalbumin as the major cross-reactive allergens among fish species. Further characterization of the novel fish allergens is warranted at the molecular level using sera from additional fish-allergic subjects

Genetic Variation in FADS Genes and Plasma Cholesterol Levels in 2-Year-Old Infants

Single nucleotide polymorphisms (SNPs) in genes involved in fatty acid metabolism (FADS1 FADS2 gene cluster) are associated with plasma lipid levels. We aimed to investigate whether these associations are already present early in life and compare the relative contribution of FADS SNPs vs traditional (non-genetic) factors as determinants of plasma lipid levels. Information on infants' plasma total cholesterol levels, genotypes of five FADS SNPs (rs174545, rs174546, rs174556, rs174561, and rs3834458), anthropometric data, maternal characteristics, and breastfeeding history was available for 521 2-year-old children from the KOALA Birth Cohort Study. For 295 of these 521 children, plasma HDLc and non-HDLc levels were also known. Multivariable linear regression analysis was used to study the associations of genetic and non-genetic determinants with cholesterol levels. All FADS SNPs were significantly associated with total cholesterol levels. Heterozygous and homozygous for the minor allele children had about 4% and 8% lower total cholesterol levels than major allele homozygotes. In addition, homozygous for the minor allele children had about 7% lower HDLc levels. This difference reached significance for the SNPs rs174546 and rs3834458. The associations went in the same direction for non-HDLc, but statistical significance was not reached. The percentage of total variance of total cholesterol levels explained by FADS SNPs was relatively low (lower than 3%) but of the same order as that explained by gender and the non-genetic determinants together. FADS SNPs are associated with plasma total cholesterol and HDLc levels in preschool children. This brings a new piece of evidence to explain how blood lipid levels may track from childhood to adulthood. Moreover, the finding that these SNPs explain a similar amount of variance in total cholesterol levels as the non-genetic determinants studied reveals the potential importance of investigating the effects of genetic variations in early life

Substructure in the stellar halo near the Sun:I. Data-driven clustering in integrals-of-motion space

Aims: Develop a data-driven and statistically based method for finding such clumps in Integrals of Motion space for nearby halo stars and evaluating their significance robustly. Methods: We use data from Gaia EDR3 extended with radial velocities from ground-based spectroscopic surveys to construct a sample of halo stars within 2.5 kpc from the Sun. We apply a hierarchical clustering method that uses the single linkage algorithm in a 3D space defined by the commonly used integrals of motion energy $E$, together with two components of the angular momentum, $L_z$ and $L_\perp$. To evaluate the statistical significance of the clusters found, we compare the density within an ellipsoidal region centered on the cluster to that of random sets with similar global dynamical properties. We pick out the signal at the location of their maximum statistical significance in the hierarchical tree. We estimate the proximity of a star to the cluster center using the Mahalanobis distance. We also apply the HDBSCAN clustering algorithm in velocity space. Results: Our procedure identifies 67 highly significant clusters ($> 3\sigma$), containing 12\% of the sources in our halo set, and in total 232 subgroups or individual streams in velocity space. In total, 13.8\% of the stars in our data set can be confidently associated to a significant cluster based on their Mahalanobis distance. Inspection of our data set reveals a complex web of relationships between the significant clusters, suggesting that they can be tentatively grouped into at least 6 main structures, many of which can be associated to previously identified halo substructures, and a number of independent substructures. This preliminary conclusion is further explored in an accompanying paper by Ruiz-Lara et al., where we also characterize the substructures in terms of their stellar populations. Conclusions: We find... (abridged version)Comment: 16 pages, 14 figures, 2 tables. Accepted for publication in A&A. This is the first in a series of papers, the second (Ruiz-Lara et al.) can be found in https://ui.adsabs.harvard.edu/abs/2022arXiv220102405R/abstract Code of the clustering algorithm can be found in https://github.com/SofieLovdal/IOM_clusterin

Practical solutions for sampling alternatives in large-scale models

Many large-scale real-world transport applications have choice sets that are so large as to make model estimation and application computationally impractical. The ability to estimate models on subsets of the alternatives is thus of great appeal, and correction approaches have existed since the late 1970s for the simple multinomial logit (MNL) model. However, many of these models in practice rely on nested logit specifications, for example, in the context of the joint choice of mode and destination. Recent research has put forward solutions for such generalized extreme value (GEV) structures, but these structures remain difficult to apply in practice. This paper puts forward a simplification of the GEV method for use in computationally efficient implementations of nested logit. The good performance of this approach is illustrated with simulated data, and additional insights into sampling error are also provided with different sampling strategies for MNL

Association of Interacting Genes in the Toll-Like Receptor Signaling Pathway and the Antibody Response to Pertussis Vaccination

BACKGROUND: Activation of the Toll-like receptor (TLR) signaling pathway through TLR4 may be important in the induction of protective immunity against Bordetella pertussis with TLR4-mediated activation of dendritic and B cells, induction of cytokine expression, and reversal of tolerance as crucial steps. We examined whether single nucleotide polymorphisms (SNPs) in genes of the TLR4 pathway and their interaction are associated with the response to whole-cell vaccine (WCV) pertussis vaccination in 490 one-year-old children. METHODOLOGY/PRINCIPAL FINDINGS: We analyzed associations of 75 haplotype-tagging SNPs in genes in the TLR4 signaling pathway with pertussis toxin (PT)-IgG titers. We found significant associations between the PT-IgG titer and SNPs in CD14, TLR4, TOLLIP, TIRAP, IRAK3, IRAK4, TICAM1, and TNFRSF4 in one or more of the analyses. The strongest evidence for association was found for two SNPs (rs5744034 and rs5743894) in TOLLIP that were almost completely in linkage disequilibrium, provided statistically significant associations in all tests with the lowest p-values, and displayed a dominant mode of inheritance. However, none of these single gene associations would withstand correction for multiple testing. In addition, Multifactor Dimensionality Reduction Analysis, an approach that does not need correction for multiple testing, showed significant and strong two and three locus interactions between SNPs in TOLLIP (rs4963060), TLR4 (rs6478317) and IRAK1 (rs1059703). CONCLUSIONS/SIGNIFICANCE: We have identified significant interactions between genes in the TLR pathway in the induction of vaccine-induced immunity. These interactions underline that these genes are functionally related and together form a true biological relationship in a protein-protein interaction network. Practically all our findings may be explained by genetic variation in directly or indirectly interacting proteins at the extra- and intracytoplasmic sites of the cell membrane of antigen-presenting cells, B cells, or both. Fine tuning of interacting proteins in the TLR pathway appears important for the induction of an optimal vaccine response

Galactic potential constraints from clustering in action space of combined stellar stream data

Galaxie