Publications

Enzymatic nanomotors harvest kinetic energy through the catalysis of chemical fuels. When a drop containing nanomotors is placed in a fuel-rich environment, they assemble into ordered groups and exhibit intriguing collective behaviour akin to the bioconvection of aerobic microorganismal suspensions. This collective behaviour presents numerous advantages compared to individual nanomotors, including expanded coverage and prolonged propulsion duration. However, the physical mechanisms underlying the collective motion have yet to be fully elucidated. Our study investigates the formation of enzymatic swarms using experimental analysis and computational modelling. We show that the directional movement of enzymatic nanomotor swarms is due to their solutal buoyancy. We investigate various factors that impact the movement of nanomotor swarms, such as particle concentration, fuel concentration, fuel viscosity, and vertical confinement. We examine the effects of these factors on swarm self-organization to gain a deeper understanding. In addition, the urease catalysis reaction produces ammonia and carbon dioxide, accelerating the directional movement of active swarms in urea compared with passive ones in the same conditions. The numerical analysis agrees with the experimental findings. Our findings are crucial for the potential biomedical applications of enzymatic nanomotor swarms, ranging from enhanced diffusion in bio-fluids and targeted delivery to cancer therapy.

JTD Keywords: Ammonia, Carbon dioxide, Catalysis, Computer simulation, Kinetics, Motion, Nanostructures, Urease, Viscosity

Underpowered trials risk inaccurate results. Recruitment to stroke rehabilitation randomised controlled trials (RCTs) is often a challenge. Statistical simulations offer an important opportunity to explore the adequacy of sample sizes in the context of specific outcome measures. We aimed to examine and compare the adequacy of stroke rehabilitation RCT sample sizes using the Barthel Index (BI) or modified Rankin Scale (mRS) as primary outcomes.We conducted computer simulations using typical experimental event rates (EER) and control event rates (CER) based on individual participant data (IPD) from stroke rehabilitation RCTs. Event rates are the proportion of participants who experienced clinically relevant improvements in the RCT experimental and control groups. We examined minimum sample size requirements and estimated the number of participants required to achieve a number needed to treat within clinically acceptable boundaries for the BI and mRS.We secured 2350 IPD (18 RCTs). For a 90% chance of statistical accuracy on the BI a rehabilitation RCT would require 273 participants per randomised group. Accurate interpretation of effect sizes would require 1000s of participants per group. Simulations for the mRS were not possible as a clinically relevant improvement was not detected when using this outcome measure.Stroke rehabilitation RCTs with large sample sizes are required for accurate interpretation of effect sizes based on the BI. The mRS lacked sensitivity to detect change and thus may be unsuitable as a primary outcome in stroke rehabilitation trials.Copyright © 2021 Elsevier Inc. All rights reserved.

JTD Keywords:  , barthel index, design, increasing value, modified rankin scale, randomised controlled trials, recruitment, reducing waste, reliability, sample size calculations, simulations, stroke rehabilitation, Adult, Article, Barthel index, Calculation, Computer simulation, Controlled study, Effect size, Female, Human, Human experiment, Major clinical study, Male, Modified rankin scale, Numbers needed to treat, Outcome assessment, Randomised controlled trials, Randomized controlled trial, Randomized controlled-trials, Rankin scale, Recruitment, Rehabilitation, Sample size, Sample size calculations, Simulations, Stroke rehabilitation

The mechanical properties of the living cell are intimately related to cell signaling biology through cytoskeletal tension. The tension borne by the cytoskeleton (CSK) is in part generated internally by the actomyosin machinery and externally by stretch. Here we studied how cytoskeletal tension is modified during stretch and the tensional changes undergone by the sites of cell-matrix interaction. To this end we developed a novel technique to map cell-matrix stresses during application of stretch. We found that cell-matrix stresses increased with imposition of stretch but dropped below baseline levels on stretch release. Inhibition of the actomyosin machinery resulted in a larger relative increase in CSK tension with stretch and in a smaller drop in tension after stretch release. Cell-matrix stress maps showed that the loci of cell adhesion initially bearing greater stress also exhibited larger drops in traction forces after stretch removal. Our results suggest that stretch partially disrupts the actin-myosin apparatus and the cytoskeletal structures that support the largest CSK tension. These findings indicate that cells use the mechanical energy injected by stretch to rapidly reorganize their structure and redistribute tension.

JTD Keywords: Cell Line, Computer Simulation, Cytoskeleton/ physiology, Elasticity, Epithelial Cells/ physiology, Extracellular Matrix/ physiology, Humans, Mechanotransduction, Cellular/ physiology, Models, Biological, Stress, Mechanical

Shape-dependent local differentials in cell proliferation are considered to be a major driving mechanism of structuring processes in vivo, such as embryogenesis, wound healing, and angiogenesis. However, the specific biophysical signaling by which changes in cell shape contribute to cell cycle regulation remains poorly understood. Here, we describe our study of the roles of nuclear volume and cytoskeletal mechanics in mediating shape control of proliferation in single endothelial cells. Micropatterned adhesive islands were used to independently control cell spreading and elongation. We show that, irrespective of elongation, nuclear volume and apparent chromatin decondensation of cells in G1 systematically increased with cell spreading and highly correlated with DNA synthesis (percent of cells in the S phase). In contrast, cell elongation dramatically affected the organization of the actin cytoskeleton, markedly reduced both cytoskeletal stiffness (measured dorsally with atomic force microscopy) and contractility (measured ventrally with traction microscopy), and increased mechanical anisotropy, without affecting either DNA synthesis or nuclear volume. Our results reveal that the nuclear volume in G1 is predictive of the proliferative status of single endothelial cells within a population, whereas cell stiffness and contractility are not. These findings show that the effects of cell mechanics in shape control of proliferation are far more complex than a linear or straightforward relationship. Our data are consistent with a mechanism by which spreading of cells in G1 partially enhances proliferation by inducing nuclear swelling and decreasing chromatin condensation, thereby rendering DNA more accessible to the replication machinery.

JTD Keywords: Cell Line, Cell Nucleus/ physiology, Cell Proliferation, Cell Size, Computer Simulation, Endothelial Cells/ cytology/ physiology, G1 Phase/ physiology, Humans, Mechanotransduction, Cellular/ physiology, Models, Biological, Statistics as Topic