Tuning Superfast Curing Thiol-Norbornene-Functionalized Gelatin Hydrogels for 3D Bioprinting

Photocurable gelatin-based hydrogels have established themselves as powerful bioinks in tissue engineering due to their excellent biocompatibility, biodegradability, light responsiveness, thermosensitivity and bioprinting properties. While gelatin methacryloyl (GelMA) has been the gold standard for many years, thiol-ene hydrogel systems based on norbornene-functionalized gelatin (GelNB) and a thiolated crosslinker have recently gained increasing importance. In this paper, a highly reproducible water-based synthesis of GelNB is presented, avoiding the use of dimethyl sulfoxide (DMSO) as organic solvent and covering a broad range of degrees of functionalization (DoF: 20% to 97%). Mixing with thiolated gelatin (GelS) results in the superfast curing photoclick hydrogel GelNB/GelS. Its superior properties over GelMA, such as substantially reduced amounts of photoinitiator (0.03% (w/v)), superfast curing (1–2 s), higher network homogeneity, post-polymerization functionalization ability, minimal cross-reactivity with cellular components, and improved biocompatibility of hydrogel precursors and degradation products lead to increased survival of primary cells in 3D bioprinting. Post-printing viability analysis revealed excellent survival rates of > 84% for GelNB/GelS bioinks of varying crosslinking density, while cell survival for GelMA bioinks is strongly dependent on the DoF. Hence, the semisynthetic and easily accessible GelNB/GelS hydrogel is a highly promising bioink for future medical applications and other light-based biofabrication techniques

CFD modelling of wind farms in complex terrain

Modelling of entire wind farms in flat and complex terrain using a full 3D Navier–Stokes solver for incompressible flow is presented in this paper. Numerical integration of the governing equations is performed using an implicit pressure correction scheme, where the wind turbines (W/Ts) are modelled as momentum absorbers through their thrust coefficient. The k–ω turbulence model, suitably modified for atmospheric flows, is employed for closure. A correction is introduced to account for the underestimation of the near wake deficit, in which the turbulence time scale is bounded using a general “realizability” constraint for the fluctuating velocities. The second modelling issue that is discussed in this paper is related to the determination of the reference wind speed for the thrust calculation of the machines. Dealing with large wind farms and wind farms in complex terrain, determining the reference wind speed is not obvious when a W/T operates in the wake of another WT and/or in complex terrain. Two alternatives are compared: using the wind speed value at hub height one diameter upstream of the W/T and adopting an induction factor-based concept to overcome the utilization of a wind speed at a certain distance upwind of the rotor. Application is made in two wind farms, a five-machine one located in flat terrain and a 43-machine one located in complex terrain

Simulation of wind farms in flat and complex terrain using CFD

Use of computational fluid dynamic (CFD) methods to predict the power production from wind entire wind farms in flat and complex terrain is presented in this paper. Two full 3D Navier–Stokes solvers for incompressible flow are employed that incorporate the k–ε and k–ω turbulence models respectively. The wind turbines (W/Ts) are modelled as momentum absorbers by means of their thrust coefficient using the actuator disk approach. The WT thrust is estimated using the wind speed one diameter upstream of the rotor at hub height. An alternative method that employs an induction-factor based concept is also tested. This method features the advantage of not utilizing the wind speed at a specific distance from the rotor disk, which is a doubtful approximation when a W/T is located in the wake of another and/or the terrain is complex. To account for the underestimation of the near wake deficit, a correction is introduced to the turbulence model. The turbulence time scale is bounded using the general “realizability” constraint for the turbulent velocities. Application is made on two wind farms, a five-machine one located in flat terrain and another 43-machine one located in complex terrain. In the flat terrain case, the combination of the induction factor method along with the turbulence correction provides satisfactory results. In the complex terrain case, there are some significant discrepancies with the measurements, which are discussed. In this case, the induction factor method does not provide satisfactory results

Dual Targeting of Antioxidant and Metabolic Enzymes to the Mitochondrion and the Apicoplast of Toxoplasma gondii

Toxoplasma gondii is an aerobic protozoan parasite that possesses mitochondrial antioxidant enzymes to safely dispose of oxygen radicals generated by cellular respiration and metabolism. As with most Apicomplexans, it also harbors a chloroplast-like organelle, the apicoplast, which hosts various biosynthetic pathways and requires antioxidant protection. Most apicoplast-resident proteins are encoded in the nuclear genome and are targeted to the organelle via a bipartite N-terminal targeting sequence. We show here that two antioxidant enzymes—a superoxide dismutase (TgSOD2) and a thioredoxin-dependent peroxidase (TgTPX1/2)—and an aconitase are dually targeted to both the apicoplast and the mitochondrion of T. gondii. In the case of TgSOD2, our results indicate that a single gene product is bimodally targeted due to an inconspicuous variation within the putative signal peptide of the organellar protein, which significantly alters its subcellular localization. Dual organellar targeting of proteins might occur frequently in Apicomplexans to serve important biological functions such as antioxidant protection and carbon metabolism

Flow and wakes in large wind farms in complex terrain and offshore

Power losses due to wind turbine wakes are of the order of 10 and 20% of total power output in large wind farms. The focus of this research carried out within the EC funded UPWIND project is wind speed and turbulence modelling for large wind farms/wind turbines in complex terrain and offshore in order to optimise wind farm layouts to reduce wake losses and loads

A microRNA negative feedback loop downregulates vesicle transport and inhibits fear memory

The SNARE-mediated vesicular transport pathway plays major roles in synaptic remodeling associated with formation of long-term memories, but the mechanisms that regulate this pathway during memory acquisition are not fully understood. Here we identify miRNAs that are up-regulated in the rodent hippocampus upon contextual fear-conditioning and identify the vesicular transport and synaptogenesis pathways as the major targets of the fear-induced miRNAs. We demonstrate that miR-153, a member of this group, inhibits the expression of key components of the vesicular transport machinery, and down-regulates Glutamate receptor A1 trafficking and neurotransmitter release. MiR-153 expression is specifically induced during LTP induction in hippocampal slices and its knockdown in the hippocampus of adult mice results in enhanced fear memory. Our results suggest that miR-153, and possibly other fear-induced miRNAs, act as components of a negative feedback loop that blocks neuronal hyperactivity at least partly through the inhibition of the vesicular transport pathway.Brain & Behavior Research Foundation (Young Investigator Award)JPB Foundatio