scholarly journals Long-range interactions, wobbles, and phase defects in chains of model cilia

2016 ◽  
Vol 1 (8) ◽  
Author(s):  
Douglas R. Brumley ◽  
Nicolas Bruot ◽  
Jurij Kotar ◽  
Raymond E. Goldstein ◽  
Pietro Cicuta ◽  
...  
Biomolecules ◽  
2019 ◽  
Vol 9 (8) ◽  
pp. 371
Author(s):  
Koua

The Mn4CaO5 cluster site in the oxygen-evolving complex (OEC) of photosystem II (PSII) undergoes structural perturbations, such as those induced by Ca2+/Sr2+ exchanges or Ca/Mn removal. These changes have been known to induce long-range positive shifts (between +30 and +150 mV) in the redox potential of the primary quinone electron acceptor plastoquinone A (QA), which is located 40 Å from the OEC. To further investigate these effects, we reanalyzed the crystal structure of Sr-PSII resolved at 2.1 Å and compared it with the native Ca-PSII resolved at 1.9 Å. Here, we focus on the acceptor site and report the possible long-range interactions between the donor, Mn4Ca(Sr)O5 cluster, and acceptor sites.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
C. Metzner ◽  
F. Hörsch ◽  
C. Mark ◽  
T. Czerwinski ◽  
A. Winterl ◽  
...  

AbstractChemotaxis enables cells to systematically approach distant targets that emit a diffusible guiding substance. However, the visual observation of an encounter between a cell and a target does not necessarily indicate the presence of a chemotactic approach mechanism, as even a blindly migrating cell can come across a target by chance. To distinguish between the chemotactic approach and blind migration, we present an objective method that is based on the analysis of time-lapse recorded cell migration trajectories: For each movement step of a cell relative to the position of a potential target, we compute a p value that quantifies the likelihood of the movement direction under the null-hypothesis of blind migration. The resulting distribution of p values, pooled over all recorded cell trajectories, is then compared to an ensemble of reference distributions in which the positions of targets are randomized. First, we validate our method with simulated data, demonstrating that it reliably detects the presence or absence of remote cell-cell interactions. In a second step, we apply the method to data from three-dimensional collagen gels, interspersed with highly migratory natural killer (NK) cells that were derived from two different human donors. We find for one of the donors an attractive interaction between the NK cells, pointing to a cooperative behavior of these immune cells. When adding nearly stationary K562 tumor cells to the system, we find a repulsive interaction between K562 and NK cells for one of the donors. By contrast, we find attractive interactions between NK cells and an IL-15-secreting variant of K562 tumor cells. We therefore speculate that NK cells find wild-type tumor cells only by chance, but are programmed to leave a target quickly after a close encounter. We provide a freely available Python implementation of our p value method that can serve as a general tool for detecting long-range interactions in collective systems of self-driven agents.


2020 ◽  
Vol 2020 (8) ◽  
Author(s):  
B. Basu-Mallick ◽  
F. Finkel ◽  
A. González-López

Abstract We introduce a new class of open, translationally invariant spin chains with long-range interactions depending on both spin permutation and (polarized) spin reversal operators, which includes the Haldane-Shastry chain as a particular degenerate case. The new class is characterized by the fact that the Hamiltonian is invariant under “twisted” translations, combining an ordinary translation with a spin flip at one end of the chain. It includes a remarkable model with elliptic spin-spin interactions, smoothly interpolating between the XXX Heisenberg model with anti-periodic boundary conditions and a new open chain with sites uniformly spaced on a half-circle and interactions inversely proportional to the square of the distance between the spins. We are able to compute in closed form the partition function of the latter chain, thereby obtaining a complete description of its spectrum in terms of a pair of independent su(1|1) and su(m/2) motifs when the number m of internal degrees of freedom is even. This implies that the even m model is invariant under the direct sum of the Yangians Y (gl(1|1)) and Y (gl(0|m/2)). We also analyze several statistical properties of the new chain’s spectrum. In particular, we show that it is highly degenerate, which strongly suggests the existence of an underlying (twisted) Yangian symmetry also for odd m.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Di Zhu ◽  
Xinyue Ye ◽  
Steven Manson

AbstractWe describe the use of network modeling to capture the shifting spatiotemporal nature of the COVID-19 pandemic. The most common approach to tracking COVID-19 cases over time and space is to examine a series of maps that provide snapshots of the pandemic. A series of snapshots can convey the spatial nature of cases but often rely on subjective interpretation to assess how the pandemic is shifting in severity through time and space. We present a novel application of network optimization to a standard series of snapshots to better reveal how the spatial centres of the pandemic shifted spatially over time in the mainland United States under a mix of interventions. We find a global spatial shifting pattern with stable pandemic centres and both local and long-range interactions. Metrics derived from the daily nature of spatial shifts are introduced to help evaluate the pandemic situation at regional scales. We also highlight the value of reviewing pandemics through local spatial shifts to uncover dynamic relationships among and within regions, such as spillover and concentration among states. This new way of examining the COVID-19 pandemic in terms of network-based spatial shifts offers new story lines in understanding how the pandemic spread in geography.


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