Mathematik digital erleben - Diskussion aktueller Projekte

Wichtige Basis für vielen Forschungsarbeiten und Lehrtätigkeiten der Mathematikdidaktik der Universität Siegen ist die Bedeutung von Auffassungen von Mathematik für die Entwicklung und Vermittlung mathematischen Wissens. Dabei beziehen wir uns insbesondere auf Arbeiten von Burscheid & Struve (2020), Tall (2013) und Schoenfeld (1985). Weniger Untersuchungen in Zusammenhang mit digitalen Medien und Werkzeugen im Mathematikunterricht beschäftigen sich derzeit mit den Beliefs von angehenden Lehrkräften, Studierenden oder Schüler/-innen.Projekte zu Mathematik digital erleben an der Universität Siegen nehmen diese Adressatengruppen besonders in den Blick. Diese wollen wir an dieser Stelle der Community zur Diskussion stellen und auf interessante Weiterentwicklungen aufmerksam machen

Proteome profiling of enzalutamide-resistant cell lines and serum analysis identified ALCAM as marker of resistance in castration-resistant prostate cancer

Enzalutamide (ENZA) is a frequently used therapy in metastatic castration‐resistant prostate cancer (mCRPC). Baseline or acquired resistance to ENZA have been observed, but the molecular mechanisms of resistance are poorly understood. We aimed to identify proteins involved in ENZA resistance and to find therapy‐predictive serum markers. We performed comparative proteome analyses on ENZA‐sensitive parental (LAPC4, DuCaP) and ‐resistant prostate cancer cell lines (LAPC4‐ENZA, DuCaP‐ENZA) using liquid chromatography tandem mass spectrometry (LC‐MS/MS). The top four most promising candidate markers were selected using bioinformatic approaches. Serum concentrations of selected markers (ALCAM, AGR2, NDRG1, IDH1) were measured in pretreatment samples of 72 ENZA‐treated mCRPC patients using ELISA. In addition, ALCAM serum levels were measured in 101 Abiraterone (ABI) and 100 Docetaxel (DOC)‐treated mCRPC patients' baseline samples. Results were correlated with clinical and follow‐up data. The functional role of ALCAM in ENZA resistance was assessed in vitro using siRNA. Our proteome analyses revealed 731 significantly differentially abundant proteins between ENZA‐sensitive and ‐resistant cells and our filtering methods identified four biomarker candidates. Serum analyses of these proteins revealed only ALCAM to be associated with poor patient survival. Furthermore, higher baseline ALCAM levels were associated with poor survival in ABI‐ but not in DOC‐treated patients. In LAPC4‐ENZA resistant cells, ALCAM silencing by siRNA knockdown resulted in significantly enhanced ENZA sensitivity. Our analyses revealed that ALCAM serum levels may help to identify ENZA‐ and ABI‐resistant patients and may thereby help to optimize future clinical decision‐making. Our functional analyses suggest the possible involvement of ALCAM in ENZA resistance

Comparative proteome analysis identified CD44 as a possible serum marker for docetaxel resistance in castration-resistant prostate cancer

Baseline or acquired resistance to docetaxel (DOC) represents a significant risk for patients with metastatic prostate cancer (PC). In the last years, novel therapy regimens have been approved providing reasonable alternatives for DOC‐resistant patients making prediction of DOC resistance of great clinical importance. We aimed to identify serum biomarkers, which are able to select patients who will not benefit from DOC treatment. DOC‐resistant PC3‐DR and DU145‐DR sublines and their sensitive parental cell lines (DU145, PC3) were comparatively analyzed using liquid chromatography‐coupled tandem mass spectrometry (LC‐MS/MS). Results were filtered using bioinformatics approaches to identify promising serum biomarkers. Serum levels of five proteins were determined in serum samples of 66 DOC‐treated metastatic castration‐resistant PC patients (mCRPC) using ELISA. Results were correlated with clinicopathological and survival data. CD44 was subjected to further functional cell culture analyses. We found at least 177 two‐fold significantly overexpressed proteins in DOC‐resistant cell lines. Our bioinformatics method suggested 11/177 proteins to be secreted into the serum. We determined serum levels of five (CD44, MET, GSN, IL13RA2 and LNPEP) proteins in serum samples of DOC‐treated patients and found high CD44 serum levels to be independently associated with poor overall survival (p = 0.001). In accordance, silencing of CD44 in DU145‐DR cells resulted in re‐sensitization to DOC. In conclusion, high serum CD44 levels may help identify DOC‐resistant patients and may thereby help optimize clinical decision‐making regarding type and timing of therapy for mCRPC patients. In addition, our in vitro results imply the possible functional involvement of CD44 in DOC resistance

Chancen und Herausforderungen fachdidaktischverbindender Elemente in der Lehramtsausbildung

Im vorliegenden Beitrag werden Rahmenbedingungen und Ergebnisse des ersten Durchgangs des Projekts FäMaPdi (Fächerverbindendes Seminar für Mathematik- und Physikdidaktik an der Universität Siegen) vorgestellt und daran Chancen und Herausforderungen fachdidaktischverbindender Vorhaben in der Lehramtsausbildung diskutiert. Die daraus resultierenden Erkenntnisse, die im Beitrag abschließend dargestellt werden, führten zur Konzeption des Folgeseminars InForM PLUS (Interdisziplinäres Forschungsseminar zur Mathematik- und Physikdidaktik in der Lehramtsausbildung an der Universität Siegen), welches FäMaPdi ab dem SoSe2017 ablöst

Inhibition of the Gastric H,K-ATPase by Clotrimazole

The antimycotic drug clotrimazole inhibits the function of the gastric H,K-ATPase in a manner similar to that observed for the Na,K-ATPase. Because of the high hydrophobicity of the compound, the interaction between clotrimazole and the ion pump occurs at the membrane domain in the apolar core of the membrane. The enzymatic activity was inhibited with a half-saturating concentration of 5.2 μM. Various partial reactions of the pump cycle were analyzed with the electrochromic styryl dye RH421 that has been widely used to study the transport mechanism of P-type ATPases. We discovered that the interaction of clotrimazole with the H,K-ATPase introduces a single “dead-end” branch added to the Post-Albers scheme in the E1 state of the pump. In this inhibiting state, the ion binding sites have a significantly enhanced affinity for protons and bind up to two protons even at pH 8.5. Inhibition of the pump can be reversed by a decreased pH or increased K+ concentrations. The mechanistic proposal that allows an explanation of all experiments presented is similar to that published for the Na,K-ATPase

Quantitative Secretome Analysis of Activated Jurkat Cells Using Click Chemistry-Based Enrichment of Secreted Glycoproteins

Quantitative secretome analyses are a high-performance tool for the discovery of physiological and pathophysiological changes in cellular processes. However, serum supplements in cell culture media limit secretome analyses, but serum depletion often leads to cell starvation and consequently biased results. To overcome these limiting factors, we investigated a model of T cell activation (Jurkat cells) and performed an approach for the selective enrichment of secreted proteins from conditioned medium utilizing metabolic marking of newly synthesized glycoproteins. Marked glycoproteins were labeled via bioorthogonal click chemistry and isolated by affinity purification. We assessed two labeling compounds conjugated with either biotin or desthiobiotin and the respective secretome fractions. 356 proteins were quantified using the biotin probe and 463 using desthiobiotin. 59 proteins were found differentially abundant (adjusted <i>p</i>-value ≤0.05, absolute fold change ≥1.5) between inactive and activated T cells using the biotin method and 86 using the desthiobiotin approach, with 31 mutual proteins cross-verified by independent experiments. Moreover, we analyzed the cellular proteome of the same model to demonstrate the benefit of secretome analyses and provide comprehensive data sets of both. 336 proteins (61.3%) were quantified exclusively in the secretome. Data are available via ProteomeXchange with identifier PXD004280

Plasma Proteomics Enable Differentiation of Lung Adenocarcinoma from Chronic Obstructive Pulmonary Disease (COPD)

Chronic obstructive pulmonary disease (COPD) is a major risk factor for the development of lung adenocarcinoma (AC). AC often develops on underlying COPD; thus, the differentiation of both entities by biomarker is challenging. Although survival of AC patients strongly depends on early diagnosis, a biomarker panel for AC detection and differentiation from COPD is still missing. Plasma samples from 176 patients with AC with or without underlying COPD, COPD patients, and hospital controls were analyzed using mass-spectrometry-based proteomics. We performed univariate statistics and additionally evaluated machine learning algorithms regarding the differentiation of AC vs. COPD and AC with COPD vs. COPD. Univariate statistics revealed significantly regulated proteins that were significantly regulated between the patient groups. Furthermore, random forest classification yielded the best performance for differentiation of AC vs. COPD (area under the curve (AUC) 0.935) and AC with COPD vs. COPD (AUC 0.916). The most influential proteins were identified by permutation feature importance and compared to those identified by univariate testing. We demonstrate the great potential of machine learning for differentiation of highly similar disease entities and present a panel of biomarker candidates that should be considered for the development of a future biomarker panel