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We study the evolution of a 2D vortex layer at high Reynolds number. Vortex layer flows are characterized by intense vorticity concentrated around a curve. In addition to their intrinsic interest, vortex layers are relevant configurations because they are regularizations of vortex sheets. In this paper, we consider vortex layers whose thickness is proportional to the square-root of the viscosity. We investigate the typical roll-up process, showing that crucial phases in the initial flow evolution are the formation of stagnation points and recirculation regions. Stretching and folding characterizes the following stage of the dynamics, and we relate these events to the growth of the palinstrophy. The formation of an inner vorticity core, with vorticity intensity growing to infinity for larger Reynolds number, is the final phase of the dynamics. We display the inner core's self-similar structure, with the scale factor depending on the Reynolds number. We reveal the presence of complex singularities in the solutions of Navier–Stokes equations; these singularities approach the real axis with increasing Reynolds number. The comparison between these singularities and the Birkhoff–Rott singularity seems to suggest that vortex layers, in the limit $Re\rightarrow \infty$ , behave differently from vortex sheets.

While being a thoroughly studied model of dynamic allostery in a small protein, the pathway of signal transduction in the PDZ3 domain has not been fully determined. Here, we investigate peptide binding to the PDZ3 domain by conventional and fully data-driven analyses of molecular dynamics simulations. First, we identify isoleucine 37 as a key residue by widely used computational procedures such as cross-correlation and community network analysis. Simulations of the Ile37Ala mutant show disruption of the coordinated movements of spatially close regular elements of secondary structure. Then, we employ a recently developed unsupervised, data-driven procedure to determine an optimized reaction coordinate (slowest-relaxation eigenvector) of peptide binding. We use this reaction coordinate to improve sampling by restarting additional simulations from the transition state region. Significant differences in the distributions of some of the pairwise residue distances in the bound and unbound states emerge from the projection onto the optimized reaction coordinate. The unsupervised analysis shows that allosteric signaling is transduced from the β2 strand, which forms part of the peptide binding site, to the spatially adjacent β3 and β4 strands, and from there to the α3 helix. The domino-like transmission of a (peptide binding) signal along β strands and α helices that are close in three-dimensional space is likely to be a general mechanism of allostery in single-domain proteins.

Misfolding of the cellular prion protein (PrP

Targeting the interaction between the spike protein receptor binding domain (S-RBD) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and angiotensin-converting enzyme 2 (ACE2) is a potential therapeutic strategy for treating coronavirus disease 2019 (COVID-19). However, we still lack small-molecule drug candidates for this target due to the missing knowledge in the hot spots for the protein-protein interaction. Here, we used NanoBiT technology to identify three Ginkgolic acids from an in-house traditional Chinese medicine (TCM) library, and they interfere with the S-RBD/ACE2 interplay. Our pseudovirus assay showed that one of the compounds, Ginkgolic acid C17:1 (GA171), significantly inhibits the entry of original SARS-CoV-2 and its variants into the ACE2-overexpressed HEK293T cells. We investigated and proposed the binding sites of GA171 on S-RBD by combining molecular docking and molecular dynamics simulations. Site-directed mutagenesis and surface plasmon resonance revealed that GA171 specifically binds to the pocket near R403 and Y505, critical residues of S-RBD for S-RBD interacting with ACE2. Thus, we provide structural insights into developing new small-molecule inhibitors and vaccines against the proposed S-RBD binding site.

The cellular prion protein PrPC mediates the neurotoxicity of prions and other protein aggregates through poorly understood mechanisms. Antibody-derived ligands against the globular domain of PrPC (GDL) can also initiate neurotoxicity by inducing an intramolecular R208-H140 hydrogen bond (“H-latch”) between the α2-α3 and β2-α2 loops of PrPC. Importantly, GDL that suppress the H-latch prolong the life of prion-infected mice, suggesting that GDL toxicity and prion infections exploit convergent pathways. To define the structural underpinnings of these phenomena, we transduced nineteen individual PrPC variants to PrPC-deficient cerebellar organotypic cultured slices using adenovirus-associated viral vectors (AAV). We report that GDL toxicity requires a single N-proximal cationic residue (K27 or R27) within PrPC. Alanine substitution of K27 also prevented the toxicity of PrPC mutants that induce Shmerling syndrome, a neurodegenerative disease that is suppressed by co-expression of wild-type PrPC. K27 may represent an actionable target for compounds aimed at preventing prion-related neurodegeneration.

Importance: In educational settings, children are under pressure to finish their work successfully within required time frames. Existing tools for assessing graphomotor skills measure either quality or speed of performance, and the speed–accuracy trade-off (SAT) in such tools has never been investigated. Objective: We aimed to evaluate a newly developed tool for measuring graphomotor skills, the Zurich Graphomotor Test (ZGT), that assesses both speed and quality of performance. We also explored whether graphomotor tests are affected by the SAT and, if so, the effects it has on graphomotor test results. Design: Cross-sectional study. Setting: Educational institutions in Switzerland. Participants: Children, adolescents, and young adults (N = 547) ages 4–22 yr (50.3% female). Outcomes and Measures: Graphomotor performance was measured with the ZGT and the Developmental Test of Visual Perception, Second Edition (DVTP–2). Standard deviation scores were used to quantify performance. We combined ZGT speed and quality measurements into a performance score adjusted for age and sex. Results: ZGT results indicated a marked developmental trend in graphomotor performance; older children were faster than younger children. Girls showed higher overall performance than boys. The pattern of making more mistakes when being faster and making fewer mistakes when being slower was observed for both graphomotor tests, regardless of time pressure, indicating that the SAT affected the children’s scores on both tests. Conclusions and Relevance: SAT is influential in graphomotor assessment. The ZGT captures this trade-off by combining accuracy and speed measurements into one score that provides a realistic assessment of graphomotor skills. What This Article Adds: The newly developed ZGT provides occupational therapy practitioners with more precise information on graphomotor skills in children, adolescents, and young adults than currently available tools.

Relatively few coronavirus disease cases and deaths have been reported from sub-Saharan Africa, although the extent of its spread remains unclear. During August 10–September 11, 2020, we recruited 2,214 participants for a representative household-based cross-sectional serosurvey in Juba, South Sudan. We found 22.3% of participants had severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) receptor binding domain IgG titers above prepandemic levels. After accounting for waning antibody levels, age, and sex, we estimated that 38.3% (95% credible interval 31.8%–46.5%) of the population had been infected with SARS-CoV-2. At this rate, for each PCR–confirmed SARS-CoV-2 infection reported by the Ministry of Health, 103 (95% credible interval 86–126) infections would have been unreported, meaning SARS-CoV-2 has likely spread extensively within Juba. We also found differences in background reactivity in Juba compared with Boston, Massachusetts, USA, where the immunoassay was validated. Our findings underscore the need to validate serologic tests in sub-Saharan Africa populations.

The hippocampus and amygdala are functionally coupled brain regions that play a crucial role in processes involving memory and learning. Because inter-areal communication has been reported both during specific sleep stages and in awake, behaving animals, these brain regions can serve as an archetype to establish that measuring functional interactions is important for comprehending neural systems. To this end, we analyze here a public data set of local field potentials (LFPs) recorded in rats simultaneously from the hippocampus and amygdala during different behaviors. Employing a specific, time-lagged embedding technique, named topological causality, we infer directed interactions between the LFP band powers of the two regions across six frequency bands in a time-resolved manner. The combined power and interaction signals are processed with our own unsupervised tools developed originally for the analysis of molecular dynamics simulations to effectively visualize and identify putative, internal states that are visited by the animals repeatedly. Our proposed methodology minimizes impositions onto the data, such as isolating specific epochs, or averaging across externally annotated behavioral stages, and succeeds in separating internal states by external labels such as sleep or stimulus events. We show that this works better for 2 of the 3 rats we analyzed, and highlight the need to acknowledge individuality in analyses of this type. Importantly, we demonstrate that the quantification of functional interactions is a significant factor in discriminating these external labels, and we suggest our methodology as a general tool for large, multi-site recordings. Significance statement We develop an analysis pipeline for neuroscience data sets. We test it on a published example of multi-electrode recordings of rats in a range of behaviors: running on a track, sleeping, collecting rewards, etc. We adopt nonlinear analysis techniques that are able to quantify directed interactions between different signals, here oscillations of two brain regions in different frequency bands. Using the entire recordings and, importantly, distinguishing each animal, we provide a high-resolution overview of the functional interplay of the two regions. Putative neural states that the animals can be in are derived from a time-aware clustering of the large data sets. When discriminating experimental annotations like run speed, we provide evidence that our methodology outperforms common clustering techniques.