Technische Universität Darmstadt

About: Technische Universität Darmstadt is a education organization based out in Darmstadt, Germany. It is known for research contribution in the topics: Neutron & Finite element method. The organization has 17316 authors who have published 40619 publications receiving 937916 citations. The organization is also known as: Darmstadt University of Technology & University of Darmstadt.

Substrate-targeting γ-secretase modulators

Abstract: Selective lowering of Abeta42 levels (the 42-residue isoform of the amyloid-beta peptide) with small-molecule gamma-secretase modulators (GSMs), such as some non-steroidal anti-inflammatory drugs, is a promising therapeutic approach for Alzheimer's disease. To identify the target of these agents we developed biotinylated photoactivatable GSMs. GSM photoprobes did not label the core proteins of the gamma-secretase complex, but instead labelled the beta-amyloid precursor protein (APP), APP carboxy-terminal fragments and amyloid-beta peptide in human neuroglioma H4 cells. Substrate labelling was competed by other GSMs, and labelling of an APP gamma-secretase substrate was more efficient than a Notch substrate. GSM interaction was localized to residues 28-36 of amyloid-beta, a region critical for aggregation. We also demonstrate that compounds known to interact with this region of amyloid-beta act as GSMs, and some GSMs alter the production of cell-derived amyloid-beta oligomers. Furthermore, mutation of the GSM binding site in the APP alters the sensitivity of the substrate to GSMs. These findings indicate that substrate targeting by GSMs mechanistically links two therapeutic actions: alteration in Abeta42 production and inhibition of amyloid-beta aggregation, which may synergistically reduce amyloid-beta deposition in Alzheimer's disease. These data also demonstrate the existence and feasibility of 'substrate targeting' by small-molecule effectors of proteolytic enzymes, which if generally applicable may significantly broaden the current notion of 'druggable' targets.

Charged-particle multiplicity measurement in proton-proton collisions at $\sqrt{s}=7$ TeV with ALICE at LHC

Abstract: Charged-particle production was studied in proton-proton collisions collected at the LHC with the ALICE detector at centre-of-mass energies 0.9 TeV and 2.36 TeV in the pseudorapidity range vertical bar eta vertical bar < 1.4. In the central region (vertical bar eta vertical bar < 0.5), at 0.9 TeV, we measure charged-particle pseudo-rapidity density dN(ch)/d eta = 3.02 +/- 0.01(stat.)(-0.05)(+0.08)(syst.) for inelastic interactions, and dN(ch)/d eta = 3.58 +/- 0.01 (stat.)(-0.12)(+0.12)(syst.) for non-single-diffractive interactions. At 2.36 TeV, we find dN(ch)/d eta = 3.77 +/- 0.01(stat.)(-0.12)(+0.25)(syst.) for inelastic, and dN(ch)/d eta = 4.43 +/- 0.01(stat.)(-0.12)(+0.17)(syst.) for non-single-diffractive collisions. The relative increase in charged-particle multiplicity from the lower to higher energy is 24.7% +/- 0.5%(stat.)(-2.8)(+5.7)%(syst.) for inelastic and 23.7% +/- 0.5%(stat.)(-1.1)(+4.6)%(syst.) for non-single-diffractive interactions. This increase is consistent with that reported by the CMS collaboration for non-single-diffractive events and larger than that found by a number of commonly used models. The multiplicity distribution was measured in different pseudorapidity intervals and studied in terms of KNO variables at both energies. The results are compared to proton-antiproton data and to model predictions.

Face masks considerably reduce COVID-19 cases in Germany.

Abstract: We use the synthetic control method to analyze the effect of face masks on the spread of COVID-19 in Germany. Our identification approach exploits regional variation in the point in time when wearing of face masks became mandatory in public transport and shops. Depending on the region we consider, we find that face masks reduced the number of newly registered severe acute respiratory syndrome coronavirus 2 infections between 15% and 75% over a period of 20 days after their mandatory introduction. Assessing the credibility of the various estimates, we conclude that face masks reduce the daily growth rate of reported infections by around 47%.