Reversible Control of Gelatin Hydrogel Stiffness by Using DNA Crosslinkers**

Biomaterials with dynamically tunable properties are critical for a range of applications in regenerative medicine and basic biology. In this work, we show the reversible control of gelatin methacrylate (GelMA) hydrogel stiffness through the use of DNA crosslinkers. We replaced some of the inter-GelMA crosslinks with double-stranded DNA, allowing for their removal through toehold-mediated strand displacement. The crosslinks could be restored by adding fresh dsDNA with complementary handles to those on the hydrogel. The elastic modulus (G’) of the hydrogels could be tuned between 500 and 1000 Pa, reversibly, over two cycles without degradation of performance. By functionalizing the gels with a second DNA strand, it was possible to control the crosslink density and a model ligand in an orthogonal fashion with two different displacement strands. Our results demonstrate the potential for DNA to reversibly control both stiffness and ligand presentation in a protein-based hydrogel, and will be useful for teasing apart the spatiotemporal behavior of encapsulated cells.     

Modelling the combined effect of surface roughness and topography on bacterial attachment

Bacterial attachment is a complex process affected by flow conditions,imparted stresses,and the sur-face properties and structure of both the supporting material and the cell.Experiments on the initial attachment of cells of the bacterium Streptococcus gordonii (S.gordonii),an important early coloniser of dental plaque,to samples of stainless steel (SS) have been reported in this work.The primary aim motivating this study was to establish what affect,if any,the surface roughness and topology of sam-ples of SS would have on the initial attachment of cells of the bacterium S.gordonii.This material and bacterium were chosen by virtue of their relevance to dental implants and dental implant infections.Prior to bacterial attachment,surfaces become conditioned by the interfacing environment (salivary pellicle from the oral cavity for instance).For this reason,cell attachment to samples of SS pre-coated with saliva was also studied.By implementing the Extended Derjaguin Landau Verwey and Overbeek(XDLVO) theory coupled with convection-diffusion-reaction equations and the surface roughness infor-mation,a computational model was developed to help better understand the physics of cell adhesion.Surface roughness was modelled by reconstructing the surface topography using statistical parame-ters derived from atomic force microscopy (AFM) measurements.Using this computational model,the effects of roughness and surface patterns on bacterial attachment were examined quantitatively in both static and flowing fluid environments.The results have shown that rougher surfaces (within the sub-microscale) generally increase bacterial attachment in static fluid conditions which quantitatively agrees with experimental measurements.Under flow conditions,computational fluid dynamics (CFD) simula-tions predicted reduced convection-diffusion inside the channel which would act to decrease bacterial attachment.When combined with surface roughness effects,the computational model also predicted that the surface topographies discussed within this work produced a slight decrease in overall bacterial attachment.This would suggest that the attachment-preventing effects of surface patterns dominate over the adhesion-favourable sub-microscale surface roughness;hence,producing a net reduction in adhered cells.This qualitatively agreed with experimental observations reported here and quantitatively matched experimental observations for low flow rates within measurement error.     

Effect of network mesh size and swelling to the drug delivery from pH responsive hydrogels

pH responsive hydrogels are ideal platforms for numerous therapeutic delivery applications, including oral delivery, as they are capable of overcoming the many barriers that must be considered when creating an effective drug delivery system. Understanding of the innate hydrogel network structure and its swelling behavior at environmentally relevant conditions is vital for designing hydrogel network capable of effective controlled drug release. Herein, we explored how to expand traditional techniques of swelling and pore characterization to gain better insight into the performance of anionic microparticles composed of the poly(methyl methacrylate-co-acrylic acid) with varying molar percentage of 10, 20, and 30 mol% of MMA, for controlled release of low-molecular-weight drugs. By evaluating these carrier systems at environmental conditions, we can observe changes in swelling and pore size of the anionic hydrogel networks as a function of MMA, which was then correlated with the release profiles of the small-molecular-weight drug sodium nitrate. With the correlation of the swelling behavior of the networks and the release profiles, we demonstrated how the expansion of swelling parameters at relevant pH values provides further incite for evaluating for the optimal blend for controlled release. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2020 , 137, 48767.     

In Situ Attenuated Total Reflection (ATR/FT-IR) Tribometry: A Powerful Tool for Investigating Tribochemistry at the Lubricant–Substrate Interface

To investigate the chemical changes occurring at metal/lubricant interfaces under tribological conditions in the boundary-lubrication regime, an in situ system for conducting quantitative tribological measurements has been constructed by combining an attenuated total reflection Fourier-transform infrared (ATR/FT-IR) spectrometer with a reciprocating tribometer. By periodically acquiring ATR/FT-IR spectra during sliding, spectroscopic changes due to thermal and/or tribochemical reactions occurring at the metal/oil interface can be monitored and correlated with friction measurements. The usefulness of this tribological test system has been demonstrated by performing ATR tribological experiments in the presence of a poly-α-olefin base oil at high temperature (423 K) on iron-coated germanium ATR crystals.     

KEMNAD: A KNOWLEDGE ENGINEERING METHODOLOGY FOR NEGOTIATING AGENT DEVELOPMENT

Automated negotiation is widely applied in various domains. However, the development of such systems is a complex knowledge and software engineering task. So, a methodology there will be helpful. Unfortunately, none of existing methodologies can offer sufficient, detailed support for such system development. To remove this limitation, this paper develops a new methodology made up of (1) a generic framework (architectural pattern) for the main task, and (2) a library of modular and reusable design pattern (templates) of subtasks. Thus, it is much easier to build a negotiating agent by assembling these standardized components rather than reinventing the wheel each time. Moreover, because these patterns are identified from a wide variety of existing negotiating agents (especially high impact ones), they can also improve the quality of the final systems developed. In addition, our methodology reveals what types of domain knowledge need to be input into the negotiating agents. This in turn provides a basis for developing techniques to acquire the domain knowledge from human users. This is important because negotiation agents act faithfully on the behalf of their human users and thus the relevant domain knowledge must be acquired from the human users. Finally, our methodology is validated with one high impact system.     

The effectiveness of Light Rail transit in achieving regional CO<Subscript>2</Subscript> emissions targets is linked to building energy use: insights from system dynamics modeling

Cities worldwide face the challenges of accommodating a growing population, while reducing emissions to meet climate mitigation targets. Public transit investments are often proposed as a way to curb emissions while maintaining healthy urban economies. However, cities face a system-level challenge in that transportation systems have cascading effects on land use and economic development. Understanding how an improved public transit system could affect urban growth and emissions requires a system-level view of a city, to anticipate side effects that could run counter to policy goals. To address this knowledge gap, we conducted a case study on the rapidly growing Research Triangle, North Carolina (USA) region, which has proposed to build a Light Railway by 2026 along a heavily used transportation corridor between the cities of Durham and Chapel Hill. At the same time, Durham County has set a goal of lowering greenhouse gas emissions by 30% from a 2005 baseline by 2030. In collaboration with local stakeholders, we developed a system dynamics model to simulate how Light Rail transit and concurrent policies could help or hinder these sustainable growth goals. The Durham–Orange Light Rail Project (D–O LRP) model simulates urban–regional dynamics between 2000 and 2040, including feedbacks from energy spending on economic growth and from land scarcity on development. Counter to expectations, model scenarios that included Light Rail had as much as 5% higher regional energy use and CO₂ emissions than business-as-usual (BAU) by 2040 despite many residents choosing to use public transit instead of private vehicles. This was largely due to an assumption that Light Rail increases demand for commercial development in the station areas, creating new jobs and attracting new residents. If regional solar capacity grew to 640 MW, this would offset the emissions growth, mostly from new buildings, that is indirectly due to Light Rail. National trends in building and automobile energy efficiency, as well as federal emissions regulation under the Clean Power Plan, would also allow significant progress toward the 2030 Durham emissions reduction goal. By simulating the magnitude of technology and policy effects, the D–O LRP model can enable policy makers to make strategic choices about regional growth.     

Conceptualizing models using multidimensional constructs: a review and guidelines for their use

While information on multidimensional constructs and empirical methods has become more accessible, there remain substantial challenges to theorizing about their form and implications. There are at least two ostensible reasons for such difficulties. First is the issue of terminology; many different terms are currently used to represent the same structural concept, and there is no evidence of standardization taking place around a single set of terms. Second, many studies do not clearly explain the theoretical reasons for choosing the specific multidimensional form of their constructs. To address these deficiencies, we use concepts from the research methods literature, and illustrations from the information systems (IS) literature, to review definitions and issues related to conceptualizing and operationalizing structural models that include multidimensional constructs. Such advice is necessary if we are going to develop and test increasingly sophisticated theoretical models in IS research. We also offer guidelines about how to conceptualize specific forms of multidimensional constructs. By lending greater conceptual clarity to the literature, we believe that this paper provides a foundation for future research incorporating multidimensional constructs in empirical analysis.