Flexibles Überschlagsrechnen in der Grundschule – Ausgewählte Ergebnisse einer Interviewstudie im vierten Schuljahr

In diesem Beitrag werden ausgewählte Ergebnisse meines abgeschlossenen Promotionsprojekts zum Lösungsverhalten von Kindern beim Überschlagsrechnen (vgl. Hunke, 2012) präsentiert. Im Fokus steht dabei die Forschungsfrage: Inwiefern lassen sich bei Kindern des vierten Schuljahres flexible Rechenkompetenzen beim Überschlagsrechnen beobachten? Bevor ein Einblick in die Interviewstudie erfolgt, wird zunächst geklärt, was unter den Begriffen des Überschlagsrechnens und des flexiblen Rechnens verstanden wird und es wird aufgezeigt, was Flexibilität in Bezug auf das Überschlagsrechnen heißt

CD154 Expression Indicates T Cell Activation Following Tetanus Toxoid Vaccination of Horses.

Despite the relevance of adaptive immunity against equine pathogens antigen-specific T cell responses of horses are not well characterized and the lack of insight into T cell responses hampers the understanding of the pathogeneses of important diseases. In this study we used tetanus toxoid (TT) as a well-defined antigen to characterize antigen-reactive T cells. Six healthy adult horses received a routine booster against tetanus with an immune stimulating complex (ISCOM)-based vaccine and were followed for 28 days. TT-specific serum antibodies were quantified by ELISA and increased in all horses by day 7 after vaccination. CD154 is an established indicator of antigen-reactive T helper cells in other species, but has not been characterized in horses. CD154 detection in equine PBMC by an anti-human CD154 antibody (clone 5C8) was confirmed by Western blots and then applied for flow cytometry. As a common indicator of equine T cell activation, cytokine induction was studied in parallel. T cells were analyzed by multicolor flow cytometry of PBMC after re-stimulation with TT in vitro. Reactive T helper (Th) cells were characterized by increased frequencies of CD4+CD154+ lymphocytes in in vitro TT-re-stimulated PBMC on day 14 after vaccination of the horses compared to pre-vaccination. The majority of all CD154+ cells after TT re-stimulation were CD4+ Th cells, but CD154 was also induced on CD4- cells albeit in lower frequencies. CD154+CD4+ Th cells were enriched in cytokine-expressing cells compared to CD154-CD4+ Th cells. Similar to the CD4+CD154+ frequencies, CD4+IL-4+, CD4+IFN-γ+ and CD4+TNF-α+ were increased after vaccination, but IL-4+ increased later than IFN-γ+ and CD4+TNF-α+, which already exceeded pre-vaccination frequencies on day 7. CD4+CD154+ frequencies correlated positively with those of CD4+IL-4+ (Th2) on day 14, and negatively with CD4+IFN-γ+ induction on day 7, but did not correlate with CD4+TNF-α+ frequencies or TT-specific antibody concentrations. CD154 appears to be a useful marker of antigen-reactive equine Th cells in combination with cytokine expression. The T cell analyses established here with TT can be applied to other antigens relevant for infections or allergies of horses and in horse models for translational research

Comprehensive Flow Cytometric Characterization of Bronchoalveolar Lavage Cells Indicates Comparable Phenotypes Between Asthmatic and Healthy Horses But Functional Lymphocyte Differences

Equine asthma (EA) is a highly relevant disease, estimated to affect up to 20% of all horses, and compares to human asthma. The pathogenesis of EA is most likely immune-mediated, yet incompletely understood. To study the immune response in the affected lower airways, mixed leukocytes were acquired through bronchoalveolar lavage (BAL) and the cell populations were analyzed on a single-cell basis by flow cytometry (FC). Samples of 38 horses grouped as respiratory healthy or affected by mild to moderate (mEA) or severe EA (sEA) according to their history, clinical signs, and BAL cytology were analyzed. Using FC, BAL cells and PBMC were comprehensively characterized by cell surface markers ex vivo. An increased percentage of DH24A+ polymorphonuclear cells, and decreased percentages of CD14+ macrophages were detected in BAL from horses with sEA compared to healthy horses or horses with mEA, while lymphocyte proportions were similar between all groups. Independently of EA, macrophages in BAL were CD14+CD16+, which contrasts the majority of CD14+CD16- classical monocytes in PBMC. Percentages of CD16-expressing BAL macrophages were reduced in BAL from horses with sEA compared to healthy horses. While PBMC lymphocytes predominantly contain CD4+ T cells, B cells and few CD8+ T cells, BAL lymphocytes comprised mainly CD8+ T cells, fewer CD4+ T cells and hardly any B cells. These lymphocyte subsets' distributions were similar between all groups. After PMA/ionomycin stimulation in vitro, lymphocyte activation (CD154 and T helper cell cytokine expression) was analyzed in BAL cells of 26 of the horses and group differences were observed (p=0.01-0.11). Compared to healthy horses' BAL, CD154+ lymphocytes from horses with mEA, and CD4+IL-17A+ lymphocytes from horses with sEA were increased in frequency. Activated CD4+ T helper cells were more frequent in asthmatics' (mEA, sEA) compared to healthy horses' PBMC lymphocytes. In summary, FC analysis of BAL cells identified increased polymorphonuclear cells frequencies in sEA as established, while macrophage percentages were mildly reduced, and lymphocyte populations remained unaffected by EA. Cytokine production differences of BAL lymphocytes from horses with sEA compared to healthy horses' cells point towards a functional difference, namely increased local type 3 responses in sEA

Investigating fourth graders' conceptual understanding of computational estimation using indirect estimation questions

International audienceThis paper presents selected findings from a qualitative study that has the main goal to investigate the procedures and concepts of fourth grade pupils solving computational estimations problems within the context of spending money. It gives theoretical background with respect to understanding computational estimation, and it points out a hitherto unmentioned concept underlying computational estimation – the interrelation of an estimate and the exact calculation – which is closely related to task characteristics. Therefore, the data analysis and the discussion focus on the role of this concept as well as of the role of task characteristics

Decoding the consecutive lysosomal degradation of 3-O-sulfate containing heparan sulfate by Arylsulfatase G (ARSG)

Kowalewski B, Lange H, Galle S, Dierks T, Lübke T, Damme M. Decoding the consecutive lysosomal degradation of 3-O-sulfate containing heparan sulfate by Arylsulfatase G (ARSG). Biochemical Journal. 2021.The lysosomal degradation of heparan sulfate is mediated by the concerted action of nine different enzymes. Within this degradation pathway, Arylsulfatase G (ARSG) is critical for removing 3-O-sulfate from glucosamine, and mutations in ARSG are causative for Usher syndrome type IV. We developed a specific ARSG enzyme assay using sulfated monosaccharide substrates, which reflect derivatives of its natural substrates. These sulfated compounds were incubated with ARSG, and resulting products were analyzed by reversed-phase HPLC after chemical addition of the fluorescent dyes 2-aminoacridone or 2-aminobenzoic acid, respectively. We applied the assay to further characterize ARSG regarding its hydrolytic specificity against 3-O-sulfated monosaccharides containing additional sulfate-groups and N-acetylation. The application of recombinant ARSG and cells overexpressing ARSG as well as isolated lysosomes from wildtype and Arsg knockout mice validated the utility of our assay. We further exploited the assay to determine the sequential action of the different sulfatases involved in the lysosomal catabolism of 3-O-sulfated glucosamine residues of heparan sulfate. Our results confirm and extend the characterization of the substrate specificity of ARSG and help to determine the sequential order of the lysosomal catabolic breakdown of (3-O-)sulfated heparan sulfate

Sampling sites of African bats in the Republic of Congo.

<p>Parc National d’Odzala-Kokoua (PNOK); Industrie forestière d’Ouesso (IFO).</p

Occurrence of <i>E</i>. <i>coli</i> in different African bat species.

<p>Occurrence of <i>E</i>. <i>coli</i> in different African bat species.</p

Distribution of virulence associated genes among <i>E</i>. <i>coli</i> from African fruit bats.

<p>Distribution of virulence associated genes among <i>E</i>. <i>coli</i> from African fruit bats.</p

Virulence gene pattern and characteristic features of 39 <i>E</i>. <i>coli</i> and one <i>E</i>. <i>albertii</i> strain.

<p>Strains of the EcoR group B2 are indicated in red, D in green, B1 in orange, A in dark blue, AxB1 in grey and ABD in light blue; genes absent among strains (<i>afa/dra</i>, <i>bmaE</i>, <i>gafD</i>, <i>iha</i>, <i>nfaE</i>, <i>tsh</i>, <i>eitA</i>, <i>eitC</i>, <i>ireA</i>, <i>iucD</i>, <i>iutA</i>, <i>sitD epi</i>, <i>neuC</i>, <i>ompT</i>, <i>cnf1/2</i>, <i>hlyF</i>, <i>sat</i>, <i>stx1</i>, <i>stx2</i>, <i>cvaA</i>, <i>cvi/cva</i>, <i>etsB</i>, <i>gimB</i>, <i>puvA)</i> are not shown. Abbreviations: ST = sequence type; STC = ST complex; In = intestines; Li = liver; Lu = lung; Ki = kidney; M = <i>Myonycteris</i>; Ei = <i>Eidolon</i>; Ep = <i>Epomops;</i> H = <i>Hypsignathus</i>; R = <i>Rousettus</i>; RC = Republic of Congo; PNOK = Park National d’Odzala Kokoua (Odzala National Park); IFO = Industrie Forestière d’Ouesso. ** Newly assigned STs are indicated by a diamond.</p