Macrophage Immunomodulation Through New Polymers that Recapitulate Functional Effects of Itaconate as a Power House of Innate Immunity

Itaconate (ITA) is an emerging powerhouse of innate immunity with therapeutic potential that is limited in its ability to be administered in a soluble form. A library of polyester materials that incorporate ITA into polymer backbones resulting in materials with inherent immunoregulatory behavior is developed. Harnessing hydrolytic degradation release from polyester backbones, ITA polymers result in the mechanism specific immunoregulatory properties on macrophage polarization in vitro. In a functional assay, the polymer-released ITA inhibits bacterial growth on acetate. Translation to an in vivo model of biomaterial associated inflammation, intraperitoneal injection of ITA polymers demonstrate a rapid resolution of inflammation in comparison to a control polymer silicone, demonstrating the value of sustained biomimetic presentation of ITA.     

Quantum Sensing in a Physiological‐Like Cell Niche Using Fluorescent Nanodiamonds Embedded in Electrospun Polymer Nanofibers

Fluorescent nanodiamonds (fNDs) containing nitrogen vacancy (NV) centers are promising candidates for quantum sensing in biological environments. This work describes the fabrication and implementation of electrospun poly lactic‐co‐glycolic acid (PLGA) nanofibers embedded with fNDs for optical quantum sensing in an environment, which recapitulates the nanoscale architecture and topography of the cell niche. A protocol that produces uniformly dispersed fNDs within electrospun nanofibers is demonstrated and the resulting fibers are characterized using fluorescent microscopy and scanning electron microscopy (SEM). Optically detected magnetic resonance (ODMR) and longitudinal spin relaxometry results for fNDs and embedded fNDs are compared. A new approach for fast detection of time varying magnetic fields external to the fND embedded nanofibers is demonstrated. ODMR spectra are successfully acquired from a culture of live differentiated neural stem cells functioning as a connected neural network grown on fND embedded nanofibers. This work advances the current state of the art in quantum sensing by providing a versatile sensing platform that can be tailored to produce physiological‐like cell niches to replicate biologically relevant growth environments and fast measurement protocols for the detection of co‐ordinated endogenous signals from clinically relevant populations of electrically active neuronal circuits.     

Real-time organic aerosol chemical speciation in the indoor environment using extractive electrospray ionization mass spectrometry

Understanding the sources and composition of organic aerosol (OA) in indoor environments requires rapid measurements, since many emissions and processes have short timescales. However, real-time molecular-level OA measurements have not been reported indoors. Here, we present quantitative measurements, at a time resolution of five seconds, of molecular ions corresponding to diverse aerosol-phase species, by applying extractive electrospray ionization mass spectrometry (EESI-MS) to indoor air analysis for the first time, as part of the highly instrumented HOMEChem field study. We demonstrate how the complex spectra of EESI-MS are screened in order to extract chemical information and investigate the possibility of interference from gas-phase semivolatile species. During experiments that simulated the Thanksgiving US holiday meal preparation, EESI-MS quantified multiple species, including fatty acids, carbohydrates, siloxanes, and phthalates. Intercomparisons with Aerosol Mass Spectrometer (AMS) and Scanning Mobility Particle Sizer suggest that EESI-MS quantified a large fraction of OA. Comparisons with FIGAERO-CIMS shows similar signal levels and good correlation, with a range of 100 for the relative sensitivities. Comparisons with SV-TAG for phthalates and with SV-TAG and AMS for total siloxanes also show strong correlation. EESI-MS observations can be used with gas-phase measurements to identify co-emitted gas- and aerosol-phase species, and this is demonstrated using complementary gas-phase PTR-MS observations.     

Enhancing urban infrastructure investment planning practices for a changing climate.

Climate change raises many concerns for urban water management because of the effects on all aspects of the hydrological cycle. Urban water infrastructure has traditionally been designed using historical observations and assuming stationary climatic conditions. The capability of this infrastructure, whether for storm-water drainage, or water supply, may be over- or under-designed for future climatic conditions. In particular, changes in the frequency and intensity of extreme rainfall events will have the most acute effect on storm-water drainage systems. Therefore, it is necessary to take future climatic conditions into consideration in engineering designs in order to enhance water infrastructure investment planning practices in a long time horizon. This paper provides the initial results of a study that is examining ways to enhance urban infrastructure investment planning practices against changes in hydrologic regimes for a changing climate. Design storms and intensity-duration-frequency curves that are used in the engineering design of storm-water drainage systems are developed under future climatic conditions by empirically adjusting the general circulation model output, and using the Gumbel distribution and the Chicago method. Simulations are then performed on an existing storm-water drainage system from NE Calgary to investigate the resiliency of the system under climate change.     

Ecophysiology and niche differentiation of Nitrospira-like bacteria, the key nitrite oxidizers in wastewater treatment plants.

Nitrite-oxidizing bacteria of the genus Nitrospira are key nitrifiers in wastewater treatment plants. Pure cultures of these organisms are unavailable, but cultivation-independent molecular methods make it possible to detect Nitrospira-like bacteria in environmental samples and to investigate their ecophysiology. Comprehensive screening of natural and engineered habitats and of public databases for 16S rRNA sequences of Nitrospira-like bacteria revealed a surprisingly high biodiversity in the genus Nitrospira, which comprises at least four phylogenetic sublineages. All Nitrospira-like bacteria detected in wastewater treatment plants belonged to the sublineages I and II. Subsequently, the population dynamics of different Nitrospira-like bacteria were monitored, by quantitative fluorescence in situ hybridization with rRNA-targeted probes, confocal laser scanning microscopy and digital image analysis, during incubation of nitrifying activated sludge in media containing different nitrite concentrations. These experiments showed that Nitrospira-like bacteria, which were affiliated with the phylogenetic sublineages I or II of the genus Nitrospira, responded differently to nitrite concentration shifts. Previously unknown properties of Nitrospira-like bacteria were discovered in the course of an environmental genomics project. Implications of the obtained results for fundamental understanding of the microbial ecology of nitrite oxidizers as well as for future improvement of nutrient removal in wastewater treatment plants are discussed.     

Optimizing the tapping regime on a blast furnace operating at variable speed

The main factors that determine the uniformity with which smelting products are tapped from a blast furnace are the rate of accumulation of the products in the hearth and the tapping rate. The first parameter is in turn determined by the stability of the furnace’s operation and can vary significantly even over the course of 24 h. The second parameter is determined mainly by the condition of the iron notch, the maintenance it receives, any changes that occur in the diameter of the channel of the notch, and the quality of the materials used to form the notch. Recommendations are presented to optimize tapping of the smelting products.     

The use of Kachkanar raw materials in the smelting of conversion pig iron

The Chelyabinsk Metallurgical Combine has periodically used Kachkanar agglomerate to make conversion pig iron since 1972. Use of this material reached a peak in 1998, when it comprised an average of 27.1% of the charge. In some months, the amount of this material charged into the furnace reached highs of 45.6 and 74.1% on certain furnaces. The coolers on the iron notches of furnaces 4 and 5 burned during that year, the quality of the smelting products and the condition of the ladles rapidly deteriorated, and the smelting rate declined. No Kachkanar agglomerate was used in 2000–2001, but it was again added to the charge in February 2002. The amount used was smaller than previously, averaging 10.7% for the shop as a whole. It was determined that using a charge with 15% Kachkanar agglomerate has both positive and negative consequences. N. N. Gorshkov, A. V. Denisov, and V. Kh. Barinov also participated in this study. __________ Translated from Metallurg, No. 3, pp. 43–45, March, 2006.     

Scalable phase extraction methods for phase plane motion estimation

To efficiently compute the phase difference (PD) between two complex numbers, two novel approaches are described. The problem of fast PD computation is central in many applications. As a case study, the main focus is on the phase correlation technique that is used for motion estimation. Starting from the problem statement, the system requirements are dealt with showing how PD requires a remarkable amount of computational resources. Reduced complexity techniques are then proposed and specifically tailored to suit the application needs. Each solution is completely implemented both in 0.25 mum as well as 0.13 mum CMOS. The so-called LUT-ROT exhibits noteworthy figures in terms of area occupation, delay and power dissipation, saving nearly 50% in terms of area and power when compared to recent work on this subject     

Reliable eye-diagram analysis of data links via device macromodels

This paper addresses the impact of device macromodels on the accuracy of signal integrity and performance predictions for critical digital interconnecting systems. It exploits nonlinear parametric models for both single-ended and differential devices, including the effects of power supply fluctuations and receiver bit detection. The analysis demonstrates that the use of well-designed macromodels dramatically speeds up the simulation as well it preserves timing accuracy even for long bit sequences.