Pathophysiology of Amyloid Fibril Formation

All amyloid comprises fibrillar polymers of tightly associated protein monomers. Central to the fibril structure is a highly ordered β-pleated sheet domain although this interacting region may only be a relatively short stretch of each constituent polypeptide chain. Fibril formation begins as a nucleation event based either on the constituent monomer protein or its proteolytic fragment(s). The resulting fibrils are generally chemically inert and very stable

Influence of a magnetic field on the viscosity of a dilute gas consisting of linear molecules.

The viscomagnetic effect for two linear molecules, N2 and CO2, has been calculated in the dilute-gas limit directly from the most accurate ab initio intermolecular potential energy surfaces presently available. The calculations were performed by means of the classical trajectory method in the temperature range from 70 K to 3000 K for N2 and 100 K to 2000 K for CO2, and agreement with the available experimental data is exceptionally good. Above room temperature, where no experimental data are available, the calculations provide the first quantitative information on the magnitude and the behavior of the viscomagnetic effect for these gases. In the presence of a magnetic field, the viscosities of nitrogen and carbon dioxide decrease by at most 0.3% and 0.7%, respectively. The results demonstrate that the viscomagnetic effect is dominated by the contribution of the jj¯ polarization at all temperatures, which shows that the alignment of the rotational axes of the molecules in the presence of a magnetic field is primarily responsible for the viscomagnetic effect

Quantum annealing initialization of the quantum approximate optimization algorithm

The quantum approximate optimization algorithm (QAOA) is a prospective near-term quantum algorithm due to its modest circuit depth and promising benchmarks. However, an external parameter optimization required in QAOA could become a performance bottleneck. This motivates studies of the optimization landscape and search for heuristic ways of parameter initialization. In this work we visualize the optimization landscape of the QAOA applied to the MaxCut problem on random graphs, demonstrating that random initialization of the QAOA is prone to converging to local minima with sub-optimal performance. We introduce the initialization of QAOA parameters based on the Trotterized quantum annealing (TQA) protocol, parameterized by the Trotter time step. We find that the TQA initialization allows to circumvent the issue of false minima for a broad range of time steps, yielding the same performance as the best result out of an exponentially scaling number of random initializations. Moreover, we demonstrate that the optimal value of the time step coincides with the point of proliferation of Trotter errors in quantum annealing. Our results suggest practical ways of initializing QAOA protocols on near-term quantum devices and reveals new connections between QAOA and quantum annealing.Comment: 10 pages, 9 figures; typos corrected, references adde

The Concept of Photozymes: Short Peptides with Photoredox Catalytic Activity for Nucleophilic Additions to α-Phenyl Styrenes

Conventional photoredox catalytic additions of alcohols to olefins require additives, like thiophenol, to promote back electron transfer. The concept of “photozymes” assumes that forward and backward electron transfer steps in a photoredox catalytic cycle are controllable by substrate binding to photocatalytically active peptides. Accordingly, we synthesized a short tripeptide modified with 1,7-dicyano-perylene-3,4 : 9,10-tetracarboxylic acid bisimide as photoredox catalyst. This peptide undergoes an unconventional photoredox catalytic cycle with the radical anion and dianion of the perylene bisimide-peptide as intermediates. The photoredox catalytic reactions with α-phenyl styrenes as substrates require remarkably low catalyst loadings (0.5 mol%) and give the methoxylation products in high yields. The concept of “photozymes” for photoredox catalysis has significant potential for other photocatalytic reactions, in particular with respect to enantioselective photocatalysis

Understanding class representations: An intrinsic evaluation of zero-shot text classification

Frequently, Text Classification is limited by insufficient training data. This problem is addressed by Zero-Shot Classification through the inclusion of external class definitions and then exploiting the relations between classes seen during training and unseen classes (Zero-shot). However, it requires a class embedding space capable of accurately representing the semantic relatedness between classes. This work defines an intrinsic evaluation based on greater-than constraints to provide a better understanding of this relatedness. The results imply that textual embeddings are able to capture more semantics than Knowledge Graph embeddings, but combining both modalities yields the best performance

Apollo: Twitter stream analyzer of trending hashtags: A case-study of #COVID-19

This poster introduces a new tool named Apollo which analyzes textual information in the geo-tagged twitter streams of trending hashtags using sliding time window. It performs sentiment analysis as well as emotion detection of the opinions of the masses about a trending world wide topic such as #COVID-19, #ClimateChange, #Black-LivesMatter, etc. based on Knowledge Graphs. Apollo currently pro- vides an interactive visualization of the analysis of the trending hashtag #COVID-19

The tarantula toxin GxTx detains K+ channel gating charges in their resting conformation.

Allosteric ligands modulate protein activity by altering the energy landscape of conformational space in ligand-protein complexes. Here we investigate how ligand binding to a K+ channel's voltage sensor allosterically modulates opening of its K+-conductive pore. The tarantula venom peptide guangxitoxin-1E (GxTx) binds to the voltage sensors of the rat voltage-gated K+ (Kv) channel Kv2.1 and acts as a partial inverse agonist. When bound to GxTx, Kv2.1 activates more slowly, deactivates more rapidly, and requires more positive voltage to reach the same K+-conductance as the unbound channel. Further, activation kinetics are more sigmoidal, indicating that multiple conformational changes coupled to opening are modulated. Single-channel current amplitudes reveal that each channel opens to full conductance when GxTx is bound. Inhibition of Kv2.1 channels by GxTx results from decreased open probability due to increased occurrence of long-lived closed states; the time constant of the final pore opening step itself is not impacted by GxTx. When intracellular potential is less than 0 mV, GxTx traps the gating charges on Kv2.1's voltage sensors in their most intracellular position. Gating charges translocate at positive voltages, however, indicating that GxTx stabilizes the most intracellular conformation of the voltage sensors (their resting conformation). Kinetic modeling suggests a modulatory mechanism: GxTx reduces the probability of voltage sensors activating, giving the pore opening step less frequent opportunities to occur. This mechanism results in K+-conductance activation kinetics that are voltage-dependent, even if pore opening (the rate-limiting step) has no inherent voltage dependence. We conclude that GxTx stabilizes voltage sensors in a resting conformation, and inhibits K+ currents by limiting opportunities for the channel pore to open, but has little, if any, direct effect on the microscopic kinetics of pore opening. The impact of GxTx on channel gating suggests that Kv2.1's pore opening step does not involve movement of its voltage sensors

Synthetic interaction and focused activity in sustainment of the rational task-group

"A control of natural interaction (36 groups), a technique of simple synthetic interactivity (distributed processing - 36 groups), and a technique of synthetic interactivity which focuses individual contribution through facilitated knowledge elicitation (braided - 36 groups) were compared in the collaboration of three-member task-groups facing a complex discovered problem (Getzels, 1982). Additional structure tested factors of coactivity (same vs. separate locations) and communication modality (written vs. oral). The task involved management (public policy) of a simulated city facing the onset of a health epidemic (Doerner, Schaub & Badke-Schaub, 1990). Several measures of group performance were obtained both from raw group output and resulting simulation values. Results indicate: 1.) no important differences between communication modalities or coactivity level, 2.) freely collaborating groups (control) performed similarly to randomized baseline trials of the simulation, and 3.) collaborative structure enabled large performance elevation with braided groups outperforming distributed groups and both techniques outperforming the control." (author's abstract

Leveraging multilingual descriptions for link prediction: Initial experiments

In most Knowledge Graphs (KGs), textual descriptions ofentities are provided in multiple natural languages. Additional informa-tion that is not explicitly represented in the structured part of the KGmight be available in these textual descriptions. Link prediction modelswhich make use of entity descriptions usually consider only one language.However, descriptions given in multiple languages may provide comple-mentary information which should be taken into consideration for thetasks such as link prediction. In this poster paper, the benefits of mul-tilingual embeddings for incorporating multilingual entity descriptionsinto the task of link prediction in KGs are investigate