Nanofiber fabrication in a temperature and humidity controlled environment for improved fibre consistency

To fabricate nanofibers with reproducible characteristics, an important demand for many applications, the effect of controlled atmospheric conditions on resulting electrospun cellulose acetate (CA) nanofibers was evaluated for temperature ranging 17.5 - 35°C and relative humidity ranging 20% - 70%. With the potential application of nanofibers in many industries, especially membrane and filter fabrication, their reproducible production must be established to ensure commercially viability.
Cellulose acetate (CA) solution (0.2 g/ml) in a solvent mixture of acetone/DMF/ethanol (2:2:1) was electrospun into nonwoven fibre mesh with the fibre diameter ranging from 150nm to 1µm.
The resulting nanofibers were observed and analyzed by scanning electron microscopy (SEM), showing a correlation of reducing average fibre diameter with increasing atmospheric temperature. A less pronounced correlation was seen with changes in relative humidity regarding fibre diameter, though it was shown that increased humidity reduced the effect of fibre beading yielding a more consistent, and therefore better quality of fibre fabrication.
Differential scanning calorimetry (DSC) studies observed lower melt enthalpies for finer CA nanofibers in the first heating cycle confirming the results gained from SEM analysis. From the conditions that were explored in this study the temperature and humidity that gave the most suitable fibre mats for a membrane purpose were 25.0°C and 50%RH due to the highest level of fibre diameter uniformity, the lowest level of beading while maintaining a low fibre diameter for increased surface area and increased pore size homogeneity. This study has highlighted the requirement to control the atmospheric conditions during the electrospinning process in order to fabricate reproducible fibre mats

Pediatric Cushing disease: disparities in disease severity and outcomes in the Hispanic and African-American populations.

BackgroundLittle is known about the contribution of racial and socioeconomic disparities to severity and outcomes in children with Cushing disease (CD).MethodsA total of 129 children with CD, 45 Hispanic/Latino or African-American (HI/AA) and 84 non-Hispanic White (non-HW), were included in this study. A 10-point index for rating severity (CD severity) incorporated the degree of hypercortisolemia, glucose tolerance, hypertension, anthropomorphic measurements, disease duration, and tumor characteristics. Race, ethnicity, age, gender, local obesity prevalence, estimated median income, and access to care were assessed in regression analyses of CD severity.ResultsThe mean CD severity in the HI/AA group was worse than that in the non-HW group (4.9±2.0 vs. 4.1±1.9, P=0.023); driving factors included higher cortisol levels and larger tumor size. Multiple regression models confirmed that race (P=0.027) and older age (P=0.014) were the most important predictors of worse CD severity. When followed up a median of 2.3 years after surgery, the relative risk for persistent CD combined with recurrence was 2.8 times higher in the HI/AA group compared with that in the non-HW group (95% confidence interval: 1.2-6.5).ConclusionOur data show that the driving forces for the discrepancy in severity of CD are older age and race/ethnicity. Importantly, the risk for persistent and recurrent CD was higher in minority children

Bio-nanotechnology application in wastewater treatment

The nanoparticles have received high interest in the field of medicine and water purification, however, the nanomaterials produced by chemical and physical methods are considered hazardous, expensive, and leave behind harmful substances to the environment. This chapter aimed to focus on green-synthesized nanoparticles and their medical applications. Moreover, the chapter highlighted the applicability of the metallic nanoparticles (MNPs) in the inactivation of microbial cells due to their high surface and small particle size. Modifying nanomaterials produced by green-methods is safe, inexpensive, and easy. Therefore, the control and modification of nanoparticles and their properties were also discussed

The regulatory mechanism of fungal elicitor-induced secondary metabolite biosynthesis in medical plants.

A wide range of external stress stimuli trigger plant cells to undergo complex network of reactions that ultimately lead to the synthesis and accumulation of secondary metabolites. Accumulation of such metabolites often occurs in plants subjected to stresses including various elicitors or signal molecules. Throughout evolution, endophytic fungi, an important constituent in the environment of medicinal plants, have known to form long-term stable and mutually beneficial symbiosis with medicinal plants. The endophytic fungal elicitor can rapidly and specifically induce the expression of specific genes in medicinal plants which can result in the activation of a series of specific secondary metabolic pathways resulting in the significant accumulation of active ingredients. Here we summarize the progress made on the mechanisms of fungal elicitor including elicitor signal recognition, signal transduction, gene expression and activation of the key enzymes and its application. This review provides guidance on studies which may be conducted to promote the efficient synthesis and accumulation of active ingredients by the endogenous fungal elicitor in medicinal plant cells, and provides new ideas and methods of studying the regulation of secondary metabolism in medicinal plants

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente

A genetic algorithm-Bayesian network approach for the analysis of metabolomics and spectroscopic data: application to the rapid detection of Bacillus spores and identification of Bacillus species

Background The rapid identification of Bacillus spores and bacterial identification are paramount because of their implications in food poisoning, pathogenesis and their use as potential biowarfare agents. Many automated analytical techniques such as Curie-point pyrolysis mass spectrometry (Py-MS) have been used to identify bacterial spores giving use to large amounts of analytical data. This high number of features makes interpretation of the data extremely difficult We analysed Py-MS data from 36 different strains of aerobic endospore-forming bacteria encompassing seven different species. These bacteria were grown axenically on nutrient agar and vegetative biomass and spores were analyzed by Curie-point Py-MS. Results We develop a novel genetic algorithm-Bayesian network algorithm that accurately identifies sand selects a small subset of key relevant mass spectra (biomarkers) to be further analysed. Once identified, this subset of relevant biomarkers was then used to identify Bacillus spores successfully and to identify Bacillus species via a Bayesian network model specifically built for this reduced set of features. Conclusions This final compact Bayesian network classification model is parsimonious, computationally fast to run and its graphical visualization allows easy interpretation of the probabilistic relationships among selected biomarkers. In addition, we compare the features selected by the genetic algorithm-Bayesian network approach with the features selected by partial least squares-discriminant analysis (PLS-DA). The classification accuracy results show that the set of features selected by the GA-BN is far superior to PLS-DA

Value Creation from Big Data: Looking Inside the Black Box

The advent of big data is fundamentally changing the business landscape. We open the ‘black box’ of the firm to explore how firms transform big data in order to create value and why firms differ in their abilities to create value from big data. Grounded in detailed evidence from China, the world’s largest digital market, where many firms actively engage in value creation activities from big data, we identify several novel features. We find that it is not the data itself, or individual data scientists, that generate value creation opportunities. Rather, value creation occurs through the process of data management, where managers are able to democratize, contextualize, experiment and execute data insights in a timely manner. We add richness to current theory by developing a conceptual framework of value creation from big data. We also identify avenues for future research and implications for practicing managers

Real-time observation of multiexcitonic states in ultrafast singlet fission using coherent 2D electronic spectroscopy.

Singlet fission is the spin-allowed conversion of a spin-singlet exciton into a pair of spin-triplet excitons residing on neighbouring molecules. To rationalize this phenomenon, a multiexcitonic spin-zero triplet-pair state has been hypothesized as an intermediate in singlet fission. However, the nature of the intermediate states and the underlying mechanism of ultrafast fission have not been elucidated experimentally. Here, we study a series of pentacene derivatives using ultrafast two-dimensional electronic spectroscopy and unravel the origin of the states involved in fission. Our data reveal the crucial role of vibrational degrees of freedom coupled to electronic excitations that facilitate the mixing of multiexcitonic states with singlet excitons. The resulting manifold of vibronic states drives sub-100 fs fission with unity efficiency. Our results provide a framework for understanding singlet fission and show how the formation of vibronic manifolds with a high density of states facilitates fast and efficient electronic processes in molecular systems.This is the author accepted manuscript. The final version is available from NPG via http://dx.doi.org/10.1038/nchem.237

Measurement of the Bottom-Strange Meson Mixing Phase in the Full CDF Data Set

We report a measurement of the bottom-strange meson mixing phase \beta_s using the time evolution of B0_s -> J/\psi (->\mu+\mu-) \phi (-> K+ K-) decays in which the quark-flavor content of the bottom-strange meson is identified at production. This measurement uses the full data set of proton-antiproton collisions at sqrt(s)= 1.96 TeV collected by the Collider Detector experiment at the Fermilab Tevatron, corresponding to 9.6 fb-1 of integrated luminosity. We report confidence regions in the two-dimensional space of \beta_s and the B0_s decay-width difference \Delta\Gamma_s, and measure \beta_s in [-\pi/2, -1.51] U [-0.06, 0.30] U [1.26, \pi/2] at the 68% confidence level, in agreement with the standard model expectation. Assuming the standard model value of \beta_s, we also determine \Delta\Gamma_s = 0.068 +- 0.026 (stat) +- 0.009 (syst) ps-1 and the mean B0_s lifetime, \tau_s = 1.528 +- 0.019 (stat) +- 0.009 (syst) ps, which are consistent and competitive with determinations by other experiments.Comment: 8 pages, 2 figures, Phys. Rev. Lett 109, 171802 (2012

Structure-based programming of lymph-node targeting in molecular vaccines

In cancer patients, visual identification of sentinel lymph nodes (LNs) is achieved by the injection of dyes that bind avidly to endogenous albumin, targeting these compounds to LNs, where they are efficiently filtered by resident phagocytes1, 2. Here we translate this ‘albumin hitchhiking’ approach to molecular vaccines, through the synthesis of amphiphiles (amph-vaccines) comprising an antigen or adjuvant cargo linked to a lipophilic albumin-binding tail by a solubility-promoting polar polymer chain. Administration of structurally optimized CpG-DNA/peptide amph-vaccines in mice resulted in marked increases in LN accumulation and decreased systemic dissemination relative to their parent compounds, leading to 30-fold increases in T-cell priming and enhanced anti-tumour efficacy while greatly reducing systemic toxicity. Amph-vaccines provide a simple, broadly applicable strategy to simultaneously increase the potency and safety of subunit vaccines.David H. Koch Institute for Integrative Cancer Research at MIT (Koch Institute Support (core) Grant P30-CA14051)National Cancer Institute (U.S.)National Institutes of Health (U.S.) (grant AI091693)National Institutes of Health (U.S.) (grant AI104715)National Institutes of Health (U.S.) (AI095109)United States. Dept. of Defense (contract W911NF-13-D-0001)United States. Dept. of Defense (contract W911NF-07-D-0004)Ragon Institute of MGH, MIT, and Harvar