TGF-beta activation by traction?

Transforming growth factor (TGF)-betas are powerful cytokines that are secreted as inactive (latent) precursors into the extracellular space. To exert their pleiotropic functions, latent TGF-betas require activation. This requisite restricts TGF-beta signaling to tissues that express TGF-beta-activating proteins such as the adhesion molecule alphavbeta6 integrin. Recent work has uncovered the molecular mechanism by which alphavbeta6 integrin activates latent TGF-beta. Latent-TGF-beta-binding protein 1 has been identified as being the major component of this process, and the integrin-interacting region has been mapped to a poorly conserved sequence stretch called the hinge region.     

A multi-body model for comparative study of cervical traction simulation – development,improvement and validation

A computer simulation model was developed to study the dynamic behavior of the cervical spine during cervical traction therapy in inclined and sitting traction positions. The model improved upon an old model with additional components to represent the behavior of the intervertebral discs and the posterior ligaments. The simulation result of the new model was compared against the cervical traction data from a radiographic experiment in both positions. The simulation results of the old model and new model were compared to illustrate the improvement. Using the new model, we compared the timing response of cervical traction in the inclined and sitting positions.     

Improved throughput traction microscopy reveals pivotal role for matrix stiffness in fibroblast contractility and TGF-β responsiveness

Lung fibroblast functions such as matrix remodeling and activation of latent transforming growth factor-β1 (TGF-β1) are associated with expression of the myofibroblast phenotype and are directly linked to fibroblast capacity to generate force and deform the extracellular matrix. However, the study of fibroblast force-generating capacities through methods such as traction force microscopy is hindered by low throughput and time-consuming procedures. In this study, we improved at the detail level methods for higher-throughput traction measurements on polyacrylamide hydrogels using gel-surface-bound fluorescent beads to permit autofocusing and automated displacement mapping, and transduction of fibroblasts with a fluorescent label to streamline cell boundary identification. Together these advances substantially improve the throughput of traction microscopy and allow us to efficiently compute the forces exerted by lung fibroblasts on substrates spanning the stiffness range present in normal and fibrotic lung tissue. Our results reveal that lung fibroblasts dramatically alter the forces they transmit to the extracellular matrix as its stiffness changes, with very low forces generated on matrices as compliant as normal lung tissue. Moreover, exogenous TGF-β1 selectively accentuates tractions on stiff matrices, mimicking fibrotic lung, but not on physiological stiffness matrices, despite equivalent changes in Smad2/3 activation. Taken together, these results demonstrate a pivotal role for matrix mechanical properties in regulating baseline and TGF-β1-stimulated contraction of lung fibroblasts and suggest that stiff fibrotic lung tissue may promote myofibroblast activation through contractility-driven events, whereas normal lung tissue compliance may protect against such feedback amplification of fibroblast activation.     

A scalable life cycle inventory of an electrical automotive traction machine—Part I: design and composition

Purpose

A scalable life cycle inventory (LCI) model of a permanent magnet electrical machine, containing both design and production data, has been established. The purpose is to contribute with new and easy-to-use data for LCA of electric vehicles by providing a scalable mass estimation and manufacturing inventory for a typical electrical automotive traction machine. The aim of this article (part I of two publications) is to present the machine design, the model structure, and an evaluation of the models’ mass estimations.

Methods

Data for design and production of electrical machines has been compiled from books, scientific papers, benchmarking literature, expert interviews, various specifications, factory records, and a factory site visit. For the design part, one small and one large reference machine were constructed in a software tool, which linked the machines’ maximum ability to deliver torque to the mass of its electromagnetically active parts. Additional data for remaining parts was then gathered separately to make the design complete. The two datasets were combined into one model, which calculates the mass of all motor subparts from an input of maximum power and torque. The range of the model is 20–200 kW and 48–477 Nm. The validity of the model was evaluated through comparison with seven permanent magnet electrical traction machines from established brands.

Results and discussion

The LCI model was successfully implemented to calculate the mass content of 20 different materials in the motor. The models’ mass estimations deviate up to 21% from the examples of real motors, which still falls within expectations for a good result, considering a noticeable variability in design, even for the same machine type and similar requirements. The model results form a rough and reasonable median in comparison to the pattern created by all data points. Also, the reference motors were assessed for performance, showing that the electromagnetic efficiency reaches 96–97%.

Conclusions

The LCI model relies on thorough design data collection and fundamental electromagnetic theory. The selected design has a high efficiency, and the motor is suitable for electric propulsion of vehicles. Furthermore, the LCI model generates representative mass estimations when compared with recently published data for electrical traction machines. Hence, for permanent magnet-type machines, the LCI model may be used as a generic component estimation for LCA of electric vehicles, when specific data is lacking.

     

Comment on “Modulating DNA configuration by interfacial traction: an elastic rod model to characterize DNA folding and unfolding”

In this comment, we point out that the tractions induced by interfacial energy, which are referred to as the tractions on the central axis curve of the DNA elastic rod presented by Huang (J. Biol. Phys. 37(1), 79–90, 2011), are incorrect. The correct tractions are provided in this literature. Further, with the use of the correct tractions, we present new numerical results, which for the values given by Zaixing Huang do not give rise to the physical behavior observed for DNA by the author.