Nanofluid optical property characterization: towards efficient direct absorption solar collectors

Suspensions of nanoparticles (i.e., particles with diameters < 100 nm) in liquids, termed nanofluids, show remarkable thermal and optical property changes from the base liquid at low particle loadings. Recent studies also indicate that selected nanofluids may improve the efficiency of direct absorption solar thermal collectors. To determine the effectiveness of nanofluids in solar applications, their ability to convert light energy to thermal energy must be known. That is, their absorption of the solar spectrum must be established. Accordingly, this study compares model predictions to spectroscopic measurements of extinction coefficients over wavelengths that are important for solar energy (0.25 to 2.5 μm). A simple addition of the base fluid and nanoparticle extinction coefficients is applied as an approximation of the effective nanofluid extinction coefficient. Comparisons with measured extinction coefficients reveal that the approximation works well with water-based nanofluids containing graphite nanoparticles but less well with metallic nanoparticles and/or oil-based fluids. For the materials used in this study, over 95% of incoming sunlight can be absorbed (in a nanofluid thickness ≥10 cm) with extremely low nanoparticle volume fractions - less than 1 × 10-5, or 10 parts per million. Thus, nanofluids could be used to absorb sunlight with a negligible amount of viscosity and/or density (read: pumping power) increase

Complement consumption in children with Plasmodium falciparum malaria

<p>Abstract</p> <p>Background</p> <p>Complement (C) can be activated during malaria, C components consumed and inflammatory mediators produced. This has potential to impair host innate defence.</p> <p>Methods</p> <p>In a case-control study, C activation was assessed by measuring serum haemolytic activity (CH50), functional activity of each pathway and levels of C3a, C4a and C5a in children presenting at Kisumu District Hospital, western Kenya, with severe malarial anaemia (SMA) or uncomplicated malaria (UM).</p> <p>Results</p> <p>CH50 median titers for lysis of sensitized sheep erythrocytes in SMA (8.6 U/mL) were below normal (34–70 U/mL) and were one-fourth the level in UM (34.6 U/mL (<it>P </it>< 0.001). Plasma C3a median levels were 10 times higher than in normals for</p> <p>SMA (3,200 ng/ml) and for UM (3,500 ng/ml), indicating substantial C activation in both groups. Similar trends were obtained for C4a and C5a. The activities of all three C pathways were greatly reduced in SMA compared to UM (9.9% vs 83.4% for CP, 0.09% vs 30.7% for MBL and 36.8% vs 87.7% for AP respectively, <it>P </it>< 0.001).</p> <p>Conclusion</p> <p>These results indicate that, while C activation occurs in both SMA and UM, C consumption is excessive in SMA. It is speculated that in SMA, consumption of C exceeds its regeneration.</p

MHCY haplotype impacts Campylobacter jejuni colonization in a backcross [(Line 61 x Line N) x Line N] population:Research Note

MHCY is a candidate region for influencing immune responses in chickens. MHCY contains multiple specialized, polymorphic MHC class I loci along with loci belonging to 4 additional gene families. In this study, MHCY haplotypes were tested for association with cecal colonization after Campylobacter jejuni infection of a backcross [(Line 6(1) × Line N) × Line N] population derived from 2 White Leghorn research lines, Line 6(1) and Line N, that were previously shown to exhibit heritable differences in colonization. Samples were obtained for 51 birds challenged with 10(8) CFU Campylobacter jejuni at 3 wk of age. Viable C. jejuni in the ceca were enumerated 5 d postinfection and counts were log-transformed for analysis. Birds were assigned to either low or high colonization groups based on the individual count being below or above the mean bacterial count for all birds. The mean bacterial count of the low infection group differed significantly from the high infection group. Sex and MHCB haplotype had similar distributions within the 2 groups. Overall, 7 MHCY haplotypes were found to be segregating. Two were significantly associated with C. jejuni colonization. MHCY Y18 was associated with low colonization (P = 3.00 × 10(−5)); whereas MHCY Y11a was associated with high colonization (P = 0.008). The MHCY haplotype impacted the mean bacterial count among all birds with MHCY Y18 having the lowest bacterial count compared with MHCY Y11a and all other MHCY (Y5, Y7, Y8, Y11b, and Y11c) haplotypes. These findings support further investigation of the contribution of chicken MHCY in resistance to Campylobacter colonization

Reconciling gene expression data with regulatory network models

The reconstruction of genome-scale metabolic models from genome annotations has become a routine practice in Systems Biology research. The potential of metabolic models for predictive biology is widely accepted by the scientific community, but these same models still lack the capability to account for the effect of gene regulation on metabolic activity. Our focus organism, Bacillus subtilis is most commonly found in soil, being subject to a wide variety of external environmental conditions. This reinforces the importance of the regulatory mechanisms that allow the bacteria to survive and adapt to such conditions. We introduce a manually curated regulatory network for Bacillus subtilis, tapping into the notable resources for B. subtilis regulation. We propose the concept of Atomic Regulon, as a set of genes that share the same ON and OFF gene expression profile across multiple samples of experimental data. Atomic regulon inference uses prior knowledge from curated SEED subsystems, in addition to expression data to infer regulatory interactions. We show how atomic regulons for B. subtilis are able to capture many sets of genes corresponding to regulated operons in our manually curated network. Additionally, we demonstrate how atomic regulons can be used to help expand/ validate the knowledge of the regulatory networks and gain insights into novel biology

Reconciling gene expression data with regulatory network models – a stimulon-based approach for integrated metabolic and regulatory modeling of Bacillus subtilis

The reconstruction of genome-scale metabolic models from genome annotations has become a routine practice in Systems Biology research. The potential of metabolic models for predictive biology is widely accepted by the scientific community, but these same models still lack the capability to account for the effect of gene regulation on metabolic activity. Our focus organism, Bacillus subtilis is most commonly found in soil, being subject to a wide variety of external environmental conditions. This reinforces the importance of the regulatory mechanisms that allow the bacteria to survive and adapt to such conditions. Existing integrated metabolic regulatory models are currently available for only a small number of well-known organisms (e.g E. coli and B. subtilis). The E. coli integrated model was proposed by Covert et al in 2004 and has slowly improved over the years. Goelzer et al. introduced the B. subtilis integrated model in 2008, covering only the central metabolic pathways. Different strategies were used in the two modeling efforts. The E. coli model is defined by a set of Boolean rules (turning genes ON and OFF) accounting mostly for transcription factors, gene interactions, involved metabolites, and some external conditions such as heat shock. The B. subtilis model introduces a set of more complex rules and also incorporates sigma factor activity into the modeling abstraction. Here we propose a genome-scale model for the regulatory network of B. subtilis, using a new stimulon-based approach. A stimulon is defined as the set of genes (that can be a part of the same operon(s) and regulon(s)) that respond in the same set of stimuli. The proposed stimulon-based approach allows for the inclusion of more types of regulation in the model. This methodology also abstracts away much of the complexity of regulatory mechanisms by directly connecting the activity of genes to the presence or absence of associated stimuli, a necessity in the many cases where details of regulatory mechanisms are poorly understood. Our model integrates regulatory network data from the Goelzer et al model, in addition to other available literature data. We then reconciled our model against a large set of high-quality gene expression data (tiled microarrays for 104 different conditions). The stimulons in our model were split or extended to improve consistency with our expression data, and the stimuli in our model were adjusted to improve consistency with the conditions of our expression experiments. The reconciliation with gene expression data revealed a significant number of exact or nearly exact matches between the manually curated regulons/stimulons and pure correlation-based regulons. Our reconciliation analysis of the 2011 SubtiWiki regulon release suggested many gene candidates for regulon extension that were subsequently included in the 2013 SubtiWiki update. Our enhanced model also includes an improved coverage of a wide range of different stress conditions. We then integrated our regulatory model with the latest metabolic reconstruction for B. subtilis, the iBsu1103V2 model (Tanaka et al. 2012). We applied this integrated metabolic regulatory model to the simulation of all growth phenotype data currently available for B. subtilis, demonstrating how the addition of regulatory constraints improved consistency of model predictions with experimentally observed phenotype data. This analysis of growth phenotype data unveiled phenotypes that could only be characterized with the addition of regulatory network constraints. All tools applied in the reconstruction, simulation, and curation of our new regulatory model are now publicly available as a part of the KBase framework. These tools permit the direct simulation of gene expression data using the regulon model alone, as well as the simulation of phenotypes and growth conditions using an integrated metabolic and regulatory model. We will highlight these new tools in the context of our reconstruction and analysis of the B. subtilis regulatory model

Knowledge-based patient screening for rare and emerging infectious/parasitic diseases: a case study of brucellosis and murine typhus.

Many infectious and parasitic diseases, especially those newly emerging or reemerging, present a difficult diagnostic challenge because of their obscurity and low incidence. Important clues that could lead to an initial diagnosis are often overlooked, misinterpreted, not linked to a disease, or disregarded. We constructed a computer-based decision support system containing 223 infectious and parasitic diseases and used it to conduct a historical intervention study based on field investigation records of 200 cases of human brucellosis and 96 cases of murine typhus that occurred in Texas from 1980 through 1989. Knowledge-based screening showed that the average number of days from the initial patient visit to the time of correct diagnosis was significantly reduced (brucellosis-from 17.9 to 4.5 days, p = 0.0001, murine typhus-from 11.5 to 8.6 days, p = 0.001). This study demonstrates the potential value of knowledge-based patient screening for rare infectious and parasitic diseases

The decline and rise of neighbourhoods: the importance of neighbourhood governance

There is a substantial literature on the explanation of neighbourhood change. Most of this literature concentrates on identifying factors and developments behind processes of decline. This paper reviews the literature, focusing on the identification of patterns of neighbourhood change, and argues that the concept of neighbourhood governance is a missing link in attempts to explain these patterns. Including neighbourhood governance in the explanations of neighbourhood change and decline will produce better explanatory models and, finally, a better view about what is actually steering neighbourhood change

Coherent, mechanical control of a single electronic spin

The ability to control and manipulate spins via electrical, magnetic and optical means has generated numerous applications in metrology and quantum information science in recent years. A promising alternative method for spin manipulation is the use of mechanical motion, where the oscillation of a mechanical resonator can be magnetically coupled to a spins magnetic dipole, which could enable scalable quantum information architectures9 and sensitive nanoscale magnetometry. To date, however, only population control of spins has been realized via classical motion of a mechanical resonator. Here, we demonstrate coherent mechanical control of an individual spin under ambient conditions using the driven motion of a mechanical resonator that is magnetically coupled to the electronic spin of a single nitrogen-vacancy (NV) color center in diamond. Coherent control of this hybrid mechanical/spin system is achieved by synchronizing pulsed spin-addressing protocols (involving optical and radiofrequency fields) to the motion of the driven oscillator, which allows coherent mechanical manipulation of both the population and phase of the spin via motion-induced Zeeman shifts of the NV spins energy. We demonstrate applications of this coherent mechanical spin-control technique to sensitive nanoscale scanning magnetometry.Comment: 6 pages, 4 figure