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Veins in vascular networks, such as in blood vasculature or leaf networks, continuously reorganize, grow or shrink, to minimize energy dissipation. Flow shear stress on vein walls has been set forth as the local driver for a vein's continuous adaptation. Yet, shear feedback alone cannot account for the observed diversity of vein dynamics - a puzzle made harder by scarce spatiotemporal data. Here, we resolve network-wide vein dynamics and shear rate during spontaneous reorganization in the prototypical vascular networks of Physarum polycephalum. Our experiments reveal a plethora of vein dynamics (stable, growing, shrinking) where the role of shear is ambiguous. Quantitative analysis of our data reveals that (a) shear rate indeed feeds back on vein radius, yet, with a time delay of 1-3 min. Further, we reconcile the experimentally observed disparate vein fates by developing a model for vein adaptation within a network and accounting for the observed time delay. The model reveals that (b) vein fate is determined by parameters - local pressure or relative vein resistance - which integrate the entire network's architecture, as they result from global conservation of fluid volume. Finally, we observe avalanches of network reorganization events that cause entire clusters of veins to vanish. Such avalanches are consistent with network architecture integrating parameters governing vein fate as vein connections continuously change. As the network architecture integrating parameters intrinsically arise from laminar fluid flow in veins, we expect our findings to play a role across flow-based vascular networks.

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Wavelike patterns driving transport are ubiquitous in life. Peristaltic pumps are a paradigm of efficient mass transport by contraction driven flows-often limited by energetic constraints. We show that a cost-efficient increase in pumping performance can be achieved by modulating the phase difference between harmonics to increase occlusion. In experiments we find a phase difference shift in the living peristalsis model P. polycephalum as dynamic response to forced mass transport. Our findings provide a novel metric for wavelike patterns and demonstrate the crucial role of nonlinearities in life.

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An asymmetric methanolysis of glutaric anhydride and 6 ensuing steps gave veratrol-annulated dimethylcyclo-heptenone diastereomers with 99% ee; ring closures occurred by Friedel-Crafts acylations of carboxylic acids obtained by stereospecific hydrogenolyses of a pair of diastereomeric δ-lactones. The mentioned cycloheptenones and Ph-NH-NH2 underwent Fischer indole syntheses providing the tetracyclic indoles cis- and trans-14a, respectively. Double lithiations with BuLi and quenchings with ClPPh2 furnished the diphosphanes cis- and trans-15 with perfect (P)- and (M)-atropselectivity, respectively.

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For over a century, enzymatic activity has been studied in vitro, assuming similar activity in the crowded cellular milieu. Here, we determined in real time the catalytic activity of TEM1-ß-lactamase inside living cells and compared the values to those obtained in vitro We found the apparent in vivo catalytic efficiency, kcat/Km , to be lower than in vitro, with significant cell-to-cell variability. Surprisingly, the results show that inside the cell the apparent catalytic efficiency decreases, and Km increases with increasing enzyme concentration. To rationalize these findings, we measured enzyme and substrate diffusion rates in the cell and found the latter to be slower than expected. Simulations showed that for attenuated diffusion the substrate flux becomes rate-limiting, explaining why reaction rates in vivo can be independent on enzyme concentrations. The octanol/water partition of the substrate is 4.5, which is in the range of Food and Drug Administration-approved drugs. This suggests substrate-limited reaction rates to be common. These findings indicate that in vitro data cannot be simply extrapolated to the crowded in vivo environment.

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With computer-based data-fitting methods becoming a standard tool in biochemistry, progress curve analysis of enzyme kinetics is a feasible, yet seldom used tool. Here we present a versatile Matlab-based tool (PCAT) to analyze catalysis progress curves with three complementary model approaches. The first two models are based on the known closed-form solution for this problem: the first describes the required Lambert W function with an analytical approximation and the second provides a numerical solution of the Lambert W function. The third model is a direct simulation of the enzyme kinetics. Depending on the chosen model, the tools excel in speed, accuracy or initial value requirements. Using simulated and experimental data, we show the strengths and pitfalls of the different fitting models. Direct simulation proves to have the highest level of accuracy, but it also requires reasonable initial values to converge. Finally, we propose a standard procedure to obtain optimized enzyme kinetic parameters from single progress curves.

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