Browsing by Author "Qian, Yun"
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- Peptide-based hydrogen sulphide-releasing gelsCarter, Jennifer M.; Qian, Yun; Foster, Jeffrey C.; Matson, John B. (The Royal Society of Chemistry, 2015-07-20)An aromatic peptide amphiphile was designed for delivery of the signaling gas H2S. The peptide self-assembled in water into nanofibers that gelled upon charge screening. The non-toxic gel slowly released H2S over 15 hours, and the presence of H2S in endothelial cells was verified using a fluorescent H2S probe.
- Peripheral loss of EphA4 ameliorates TBI-induced neuroinflammation and tissue damageKowalski, Elizabeth A.; Chen, Jiang; Hazy, Amanda; Fritsch, Lauren E.; Gudenschwager-Basso, Erwin K.; Chen, Michael; Wang, Xia; Qian, Yun; Zhou, Mingjun; Byerly, Matthew; Pickrell, Alicia M.; Matson, John B.; Allen, Irving C.; Theus, Michelle H. (2019-11-11)Background The continuum of pro- and anti-inflammatory response elicited by traumatic brain injury (TBI) is suggested to play a key role in the outcome of TBI; however, the underlying mechanisms remain ill -defined. Methods Here, we demonstrate that using bone marrow chimeric mice and systemic inhibition of EphA4 receptor shifts the pro-inflammatory milieu to pro-resolving following acute TBI. Results EphA4 expression is increased in the injured cortex as early as 2 h post-TBI and on CX3CR1gfp-positive cells in the peri-lesion. Systemic inhibition or genetic deletion of EphA4 significantly reduced cortical lesion volume and shifted the inflammatory profile of peripheral-derived immune cells to pro-resolving in the damaged cortex. These findings were consistent with in vitro studies showing EphA4 inhibition or deletion altered the inflammatory state of LPS-stimulated monocyte/macrophages towards anti-inflammatory. Phosphoarray analysis revealed that EphA4 may regulate pro-inflammatory gene expression by suppressing the mTOR, Akt, and NF-κB pathways. Our human metadata analysis further demonstrates increased EPHA4 and pro-inflammatory gene expression, which correlates with reduced AKT concurrent with increased brain injury severity in patients. Conclusions Overall, these findings implicate EphA4 as a novel mediator of cortical tissue damage and neuroinflammation following TBI.
- Self-assembled Peptide Hydrogels for Therapeutic H2S DeliveryQian, Yun (Virginia Tech, 2019-06-21)Hydrogen sulfide (H2S) is a gasotransmitter that is produced endogenously and freely permeates cell membranes. It plays important roles in many physiological pathways, and by regulating these pathways, it provides many therapeutic effects. For example, H2S dilates vascular vessels, promotes angiogenesis, and protects cells from oxidative stress. Due to its therapeutic effects, H2S has been used as a potential treatment for diseases like diabetes, ischemia-reperfusion injuries, lung diseases, ulcers and edemas, among others. To apply H2S for therapeutic applications, two challenges need to be addressed. The first challenge is the H2S donor, which not only provides H2S but must be stable enough to avoid side effects caused by overdose; and the second challenge is the delivery strategies, which transport the H2S to the target sites. A series of S-aroylthiooximes (SATOs), an H2S releasing compound, were synthesized and conjugated to peptide sequences to form H2S-releasing aromatic peptide amphiphile (APA) hydrogels. APAs formed nanofibers, which were stabilized by beta-sheets and aromatic stacking. The self-assembled structures were affected by the substituents on the aromatic rings of SATOs, leading to the formation of twisted nanofibers. After the addition of cysteine, H2S was released from the APAs with half-lives ranging from 13 min to 31 min. The electron-donating groups slowed down the H2S release rate, while the electron-withdrawing groups accelerated the release rate. Therefore, the release rates of H2S were controlled by electronic effects. When self-assembled structures were formed, the H2S release rate was slowed down even more, due to the difficulties in cysteine diffusion into the core of the structures. Antimicrobial effects were also discovered using the H2S releasing APA hydrogels. The H2S-releasing dipeptides S-FE and S-YE formed self-assembled twisted nanoribbons and nanotubes, respectively. The non H2S-releasing control oxime dipeptides C-FE and C-YE were also synthesized. The C-FE formed nanoribbons while the C-YE only showed non-specific aggregates. S-FE and S-YE released H2S with peaking times of about 41 and 39 min. Both the self-assembled structures and the release rates were affected by their packing differences. In vitro and ex vivo experiments with Staphylococcus aureus (Xen29), a commonly found bacterium on burn wounds, showed significant antimicrobial effects. APAs S-FE and C-FE eliminated Xen29 and inhibited the biofilm formation, while S-FE always showed better effects than C-FE. These antimicrobial H2S-releasing APA hydrogels provide a new approach to treat burn wound infections, and provide healing benefits due to the therapeutic effects of H2S.
- Understanding Model Uncertainty – An Application of Uncertainty Quantification to Wind EnergyBerg, Larry; Yang, Ben; Qian, Yun; Ma, Po-lun; Wharton, Sonia; Bulaevskaya, Vera; Yan, Huiping; Shaw, William (Virginia Tech, 2015-06)Wind resource characterization and short-term wind power forecasts often utilize mesoscale meteorological models such as the Weather Research and Forecasting (WRF) model. Because of the finite nature of the model grid, parameterizations must be used to represent processes that are sub-grid scale, such as those associated with planetary boundary layer (PBL) turbulence. Few published studies have attempted to rigorously define the uncertainty in the simulated wind speed, wind shear, and wind power associated with the assumed constants applied in the PBL and surface layer parameterizations. Likewise, the design of most field studies with the goal of improving PBL parameterizations are based on the intuition of the investigator, rather than an explicit analysis of the causes of uncertainty within the parameterization. In this study we use uncertainty quantification (UQ) to address these shortcomings and provide guidance for the instrument deployments that will be part of the second Department of Energy Wind Forecast Improvement Project (WFIP 2). The most widely used sensitivity analysis (SA) approach is to conduct "one-at-a-time" (OAT) sensitivity tests that systematically investigate departures of model behavior from the baseline simulation by varying one parameter at a time. However, OAT tests can only evaluate a limited number of parameters at the same time, consider only a small fraction of the total parameter uncertainty space, and are computationally expensive. Another critical limitation of the OAT approach is that it does not allow for the quantification of the effects of interaction among parameters. A more comprehensive method is to populate the statistical distribution of model outputs by simultaneously sampling hundreds or thousands of possible configurations of multiple parameters. The SA, such as analysis of variance and variance decomposition, then use the output distributions to understand the contribution of each parameter (along with any interaction effects it has with other parameters) to the overall variance. The UQ analysis will be used to document the uncertainty in hub-height wind, wind shear across the rotor diameter, and wind power for WRF simulations completed using the Mellor-Yamada-Nakanishi-Niino (MYNN) PBL parameterization and the recently revised Mesoscale Model 5 (MM5) surface layer scheme for a location in the Pacific Northwest. The UQ results will be used to develop recommendations for the WFIP 2 instrument deployment. An example WRF time series of simulated 80 m wind speed and wind power is shown in the figure below, with each time series resulting from one of 256 individual WRF simulations completed using combinations of different values for 12 PBL parameters. The figure highlights how the uncertainty in the wind speed gives rise to large variations in the wind power that can range from approximately the rated power of 1.6 MW to less than 0.4 MW for a given point in time. Our analysis shows that the WRF simulations of hub-height wind speed are ultimately sensitive to a relatively small number of parameters, including surface roughness length (z0), the von Karman constant, the turbulence kinetic energy (TKE) dissipation rate, the Prandlt Number, parameters associated with the length scales applied in the MYNN PBL parameterization, and to a lesser extent Monin-Obukhov similarity functions during nighttime. These results argue for the measurement of TKE and TKE dissipation rates over the depth of the PBL (or deeper in stable conditions during which the PBL might be quite thin) at a number of locations over the WFIP 2 domain. The day-night changes in the sensitivity point to the need for measurements of the surface sensible heat flux to help determine the static stability at any given time. The relative importance of the various parameters also changes as a function of terrain slope. For example, the relative contribution of the variance associated with changes of a parameter related to the TKE dissipation rate, ranges from 30% in daytime conditions for gentle slopes to nearly 50% during daytime conditions and steep slopes. Overall, the results presented in this work quantify the uncertainty in WRF simulations of hub-height wind speed and wind power in a region of complex terrain, and point to key measurements that should be included as part of WFIP 2.