Collagen-mimetic peptide-modifiable hydrogels for articular cartilage regeneration

Regenerative medicine strategies for restoring articular cartilage face significant challenges to recreate the complex and dynamic biochemical and biomechanical functions of native tissues. As an approach to recapitulate the complexity of the extracellular matrix, collagen-mimetic proteins offer a modular template to incorporate bioactive and biodegradable moieties into a single construct. We modified a Streptococcal collagen-like 2 protein with hyaluronic acid (HA) or chondroitin sulfate (CS)-binding peptides and then cross-linked with a matrix metalloproteinase 7 (MMP7)-sensitive peptide to form biodegradable hydrogels. Human mesenchymal stem cells (hMSCs) encapsulated in these hydrogels exhibited improved viability and significantly enhanced chondrogenic differentiation compared to controls that were not functionalized with glycosaminoglycan-binding peptides. Hydrogels functionalized with CS-binding peptides also led to significantly higher MMP7 gene expression and activity while the HA-binding peptides significantly increased chondrogenic differentiation of the hMSCs. Our results highlight the potential of this novel biomaterial to modulate cell-mediated processes and create functional tissue engineered constructs for regenerative medicine applications

Uncertainty Aware ML-based surrogate models for particle accelerators: A Study at the Fermilab Booster Accelerator Complex

Standard deep learning methods, such as Ensemble Models, Bayesian Neural Networks and Quantile Regression Models provide estimates to prediction uncertainties for data-driven deep learning models. However, they can be limited in their applications due to their heavy memory, inference cost, and ability to properly capture out-of-distribution uncertainties. Additionally, some of these models require post-training calibration which limits their ability to be used for continuous learning applications. In this paper, we present a new approach to provide prediction with calibrated uncertainties that includes out-of-distribution contributions and compare it to standard methods on the Fermi National Accelerator Laboratory (FNAL) Booster accelerator complex

Improved liver R2* mapping by pixel-wise curve fitting with adaptive neighborhood regularization.

PURPOSE: To improve liver R2* mapping by incorporating adaptive neighborhood regularization into pixel-wise curve fitting. METHODS: Magnetic resonance imaging R2* mapping remains challenging because of the serial images with low signal-to-noise ratio. In this study, we proposed to exploit the neighboring pixels as regularization terms and adaptively determine the regularization parameters according to the interpixel signal similarity. The proposed algorithm, called the pixel-wise curve fitting with adaptive neighborhood regularization (PCANR), was compared with the conventional nonlinear least squares (NLS) and nonlocal means filter-based NLS algorithms on simulated, phantom, and in vivo data. RESULTS: Visually, the PCANR algorithm generates R2* maps with significantly reduced noise and well-preserved tiny structures. Quantitatively, the PCANR algorithm produces R2* maps with lower root mean square errors at varying R2* values and signal-to-noise-ratio levels compared with the NLS and nonlocal means filter-based NLS algorithms. For the high R2* values under low signal-to-noise-ratio levels, the PCANR algorithm outperforms the NLS and nonlocal means filter-based NLS algorithms in the accuracy and precision, in terms of mean and standard deviation of R2* measurements in selected region of interests, respectively. CONCLUSIONS: The PCANR algorithm can reduce the effect of noise on liver R2* mapping, and the improved measurement precision will benefit the assessment of hepatic iron in clinical practice. Magn Reson Med, 2018. © 2018 International Society for Magnetic Resonance in Medicine

An Analysis of Variability in Power Output During Indoor and Outdoor Cycling Time-Trials

PURPOSE::Regulation of power output during cycling encompasses the integration of internal and external demands to maximise performance. However, relatively little is known about variation in power output in response to the external demands of outdoor cycling. We compared mean power output and the magnitude of power output variability and structure during a 20-min time-trial performed indoors and outdoors.METHODS::Twenty male competitive cyclists (V̇O2peak 60.4 ± 7.1 mL·kg-1·min-1) performed two randomised maximal 20-min time-trial tests i) outdoors at a cycle-specific racing circuit or ii) indoors on a laboratory-based electromagnetically braked training ergometer, 7 days apart. Power output was sampled at 1 Hz and collected on the same bike equipped with a portable power meter in both tests.RESULTS::Twenty-min time-trial performance indoor (280 ± 44 W) was not different from outdoor (284 ± 41 W) (P = 0.256), showing a strong correlation (r = 0.94; P < 0.001). Within-person SD was greater outdoors (69 ± 21 W) compared to indoors (33 ± 10 W) (P < 0.001). Increased variability was observed across all frequencies in data from outdoor cycling compared to indoors (P < 0.001) except for the very slowest frequency bin (<0.0033 Hz, P = 0.930).CONCLUSIONS::Our findings indicate a greater magnitude of variability in power output during cycling outdoors. This suggests that constraints imposed by the external environment lead to moderate and high frequency fluctuations in power output. Therefore, indoor testing protocols should be designed to reflect the external demands of cycling outdoors

Enhancing the efficacy of cytotoxic agents for cancer therapy using photochemical internalisation.

Photochemical internalisation (PCI) is a technique for improving cellular delivery of certain bioactive agents which are prone to sequestration within endolysosomes. There is a wide range of agents suitable for PCI-based delivery including toxins, oligonucleotides, genes and immunoconjugates which demonstrates the versatility of this technique. The basic mechanism of PCI involves triggering release of the agent from endolysosomes within the target cells using a photosensitiser which is selectively retained with the endolysosomal membranes. Excitation of the photosensitiser by visible light leads to disruption of the membranes via photooxidative damage thereby releasing the agent into the cytosol. This treatment enables the drugs to reach their intended subcellular target more efficiently and improves their efficacy. In this review we summarise the applications of this technique with the main emphasis placed on cancer chemotherapy

The continuing evolution of Energy Policy

As the world confronts the Covid-19 pandemic, we hope that all of you are doing well. We know that many lives have been greatly disrupted, and that world economic activity is slowing and maybe declining in some places. We have read reports that energy consumption has been greatly affected by the slowdown in world economic activity—likely contributing to the sharp plunge in oil prices earlier this year. We do not know how long this pandemic may last. As we look forward to the end of the pandemic and a recovering world economy, however, we wonder if and how energy systems may have to be transformed, and whether new energy policy needs and approaches will emerge. Will we see any change in the trajectory of adopting sustainable energy systems and reducing carbon emissions?In the academic world, many of us are now teleworking and teaching our courses online. This transition has proved time consuming—so we want to thank our many reviewers who are staying on or close to schedule. So far, Energy Policy has been mostly unaffected by the pandemic, but we must recognize that the Elsevier employees who are responsible for the operations side of the journal may at some time be affected by Covid-19.In the meantime, we want to keep you informed about some recent developments regarding Energy Policy, including a little about its history and our editorial priorities

Institutional Export Barriers on Exporters from Emerging Markets: Evidence from China

The emerging markets have become the increasingly important trading nations in the global economy. Given its significance to practitioners and policymakers, export barriers has been the popular topic in the international business studies. However, research about export barriers caused by the local institutions are under developed, though institutional voids and institutional inefficiency are reported as the major determinants for business development in emerging markets. This paper aims to fill in this gap by exploring the institutional export barriers in emerging markets. Based on existing studies on export barriers and institutional perspective, a conceptual framework is initially developed by separating formal and informal institutional export barriers. Then three specific institutional export barriers are identified, including government policy, weak legal system and informal and personal networks. In the meanwhile, this paper sheds light on how the institutional export barriers are developed and obstruct exporting in emerging markets

Simplistic Attachment and Multispectral Imaging with Semiconductor Nanocrystals

Advances in spectral deconvolution technologies are rapidly enabling researchers to replace or enhance traditional epifluorescence microscopes with instruments capable of detecting numerous markers simultaneously in a multiplexed fashion. While significantly expediting sample throughput and elucidating sample information, this technology is limited by the spectral width of common fluorescence reporters. Semiconductor nanocrystals (NC’s) are very bright, narrow band fluorescence emitters with great potential for multiplexed fluorescence detection, however the availability of NC’s with facile attachment chemistries to targeting molecules has been a severe limitation to the advancement of NC technology in applications such as immunocytochemistry and immunohistochemistry. Here we report the development of simple, yet novel attachment chemistries for antibodies onto NC’s and demonstrate how spectral deconvolution technology enables the multiplexed detection of 5 distinct NC-antibody conjugates with fluorescence emission wavelengths separated by as little as 20 nm