A comparative study on the thermophysical properties for two bis[(trifluoromethyl)sulfonyl]imide-based ionic liquids containing the trimethyl-sulfonium or the trimethyl-ammonium cation in molecular solvents

Herein, we present a comparative study of the thermophysical properties of two homologous ionic liquids, namely, trimethyl-sulfonium bis[(trifluoromethyl) sulfonyl]imide, [S₁₁₁][TFSI], and trimethyl-ammonium bis[(trifluoromethyl)sulfonyl]imide, [HN₁₁₁][TFSI], and their mixtures with propylene carbonate, acetonitrile, or gamma butyrolactone as a function of temperature and composition. The influence of solvent addition on the viscosity, conductivity, and thermal properties of IL solutions was studied as a function of the solvent mole fraction from the maximum solubility of IL, x_s, in each solvent to the pure solvent. In this case, x_s is the composition corresponding to the maximum salt solubility in each liquid solvent at a given temperature from 258.15 to 353.15 K. The effect of temperature on the transport properties of each binary mixture was then investigated by fitting the experimental data using Arrhenius' law and the Vogel-Tamman-Fulcher (VTF) equation. The experimental data shows that the residual conductivity at low temperature, e.g., 263.15 K, of each binary mixture is exceptionally high. For example, conductivity values up to 35 and 42 mS·cm^-1 were observed in the case of the [S ₁₁₁][TFSI] + ACN and [HN₁₁₁][TFSI] + ACN binary mixtures, respectively. Subsequently, a theoretical approach based on the conductivity and on the viscosity of electrolytes was formulated by treating the migration of ions as a dynamical process governed by ion-ion and solvent-ion interactions. Within this model, viscosity data sets were first analyzed using the Jones-Dole equation. Using this theoretical approach, excellent agreement was obtained between the experimental and calculated conductivities for the binary mixtures investigated at 298.15 K as a function of the composition up to the maximum solubility of the IL. Finally, the thermal characterization of the IL solutions, using DSC measurements, showed a number of features corresponding to different solid-solid phase transitions, T_S-S, with extremely low melting entropies, indicating a strong organizational structure by easy rotation of methyl group. These ILs can be classified as plastic crystal materials and are promising as ambient-temperature solid electrolytes. © 2013 American Chemical Society.

Interventions Targeting Child Undernutrition in Developing Countries May Be Undermined by Dietary Exposure to Aflatoxin

Child undernutrition, a form of malnutrition, is a major public health burden in developing countries. Supplementation interventions targeting the major micronutrient deficiencies have only reduced the burden of child undernutrition to a certain extent, indicating that there are other underlying determinants that need addressed. Aflatoxin exposure, which is also highly prevalent in developing countries, may be considered to be an aggravating factor for child undernutrition. Increasing evidence suggests that aflatoxin exposure can occur in any stage of life including in utero through a trans-placental pathway and in early childhood (through contaminated weaning food and family food). Early life exposure to aflatoxin is associated with adverse effects on low birth weight, stunting, immune suppression and liver function damage. The mechanisms underlying impaired growth and aflatoxin exposure are still unclear but intestinal function damage, reduced immune function and alteration in the insulin-like growth factor axis caused by liver damage, are suggested hypotheses. Given the fact that both aflatoxin and child undernutrition are common in sub-Saharan Africa, effective interventions aimed at reducing undernutrition cannot be satisfactorily achieved until the interactive relationship between aflatoxin and child undernutrition is clearly understood, and an aflatoxin mitigation strategy has taken effect in those vulnerable mothers and children.

A review of rhizosphere carbon flow modelling

Rhizosphere processes play a key role in nutrient cycling in terrestrial ecosystems. Plant rhizodeposits supply low-molecular weight carbon substrates to the soil microbial community, resulting in elevated levels of activity surrounding the root. Mechanistic compartmental models that aim to model carbon flux through the rhizosphere have been reviewed and areas of future research necessary to better calibrate model parameters have been identified. Incorporating the effect of variation in bacterial biomass physiology on carbon flux presents a considerable challenge to experimentalists and modellers alike due to the difficulties associated with differentiating dead from dormant cells. A number of molecular techniques that may help to distinguish between metabolic states of bacterial cells are presented. The calibration of growth, death and maintenance parameters in rhizosphere models is also discussed. A simple model of rhizosphere carbon flow has been constructed and a sensitivity analysis was carried out on the model to highlight which parameters were most influential when simulating carbon flux. It was observed that the parameters that most heavily influenced long-term carbon compartmentalisation in the rhizosphere were exudation rate and biomass yield. It was concluded that future efforts to simulate carbon flow in the rhizosphere should aim to increase ecological realism in model structure.

Ultrashort self-assembling peptidomimetic nanomaterials target resistant pathogenic infections

The impending and increasing threat of antimicrobial resistance has led to a greater focus into developing alternative therapies as substitutes for traditional antibiotics for the treatment of multi-drug resistant infections.1 Our group has developed a library of short, cost-effective, diphenylalanine-based peptides (X1-FF-X2) which selective eradicate (viability reduced >90% in 24 hours) the most resistant biofilm forms of a range of Gram-positive and negative pathogens including: methicillin resistant and sensitive Staphyloccoccus aureus and Staphyloccoccus epidermidis; Pseudomonas aeruginosa, Proteus mirabilis and Escherichia coli. They demonstrate a reduced cell cytotoxic profile (NCTC929 murine fibroblast) and limited haemolysis.2 Our molecules have the ability respond to subtle changes in pH, associated with bacterial infection, self-assembling to form β-sheet secondary structures and supramolecular hydrogels at low concentrations (~0.5%w/v). Conjugation of variety of aromatic-based drugs at the X1 position, including non-steroidal anti-inflammatories (NSAIDs), confer further pharmacological properties to the peptide motif enhancing their therapeutic potential. In vivo studies using waxworms (Galleria mellonella) provide promising preliminary results demonstrating the low toxicity and high antimicrobial activity of these low molecular weight gelators in animal models. This work shows biofunctional peptide-based nanomaterials hold great promise for future translation to patients as antimicrobial drug delivery and biomaterial platforms.3 [1] G. Laverty, S.P. Gorman and B.F. Gilmore. Int.J.Mol.Sci. 2011, 12, 6566-6596. [2] G. Laverty, A.P. McCloskey, B.F. Gilmore, D.S. Jones, J Zhou, B Xu. Biomacromolecules. 2014, 15, 9, 3429-3439. [3] A.P. McCloskey, B.F. Gilmore and G.Laverty. Pathogens. 2014, 3, 791-821.

Comparative Study of Different Methods for the Prediction of Drug− Polymer Solubility

In this study, a comparison of different methods to predict drug−polymer solubility was carried out on binary systems consisting of five model drugs (paracetamol, chloramphenicol, celecoxib, indomethacin, and felodipine) and polyvinylpyrrolidone/vinyl acetate copolymers (PVP/VA) of different monomer weight ratios. The drug−polymer solubility at 25 °C was predicted using the Flory−Huggins model, from data obtained at elevated temperature using thermal analysis methods based on the recrystallization of a supersaturated amorphous solid dispersion and two variations of the melting point depression method. These predictions were compared with the solubility in the low molecular weight liquid analogues of the PVP/VA copolymer (N-vinylpyrrolidone and vinyl acetate). The predicted solubilities at 25 °C varied considerably depending on the method used. However, the three thermal analysis methods ranked the predicted solubilities in the same order, except for the felodipine−PVP system. Furthermore, the magnitude of the predicted solubilities from the recrystallization method and melting point depression method correlated well with the estimates based on the solubility in the liquid analogues, which suggests that this method can be used as an initial screening tool if a liquid analogue is available. The learnings of this important comparative study provided general guidance for the selection of the most suitable method(s) for the screening of drug−polymer solubility.

Multigenerational Undernutrition Increases Susceptibility to Obesity and Diabetes that Is Not Reversed after Dietary Recuperation

People in developing countries have faced multigenerational undernutrition and are currently undergoing major lifestyle changes, contributing to an epidemic of metabolic diseases, though the underlying mechanisms remain unclear. Using a Wistar rat model of undernutrition over 50 generations, we show that Undernourished rats exhibit low birth-weight, high visceral adiposity (DXA/MRI), and insulin resistance (hyperinsulinemic-euglycemic clamps), compared to age-/gender-matched control rats. Undernourished rats also have higher circulating insulin, homocysteine, endotoxin and leptin levels, lower adiponectin, vitamin B12 and folate levels, and an 8-fold increased susceptibility to Streptozotocin-induced diabetes compared to control rats. Importantly, these metabolic abnormalities are not reversed after two generations of unrestricted access to commercial chow (nutrient recuperation). Altered epigenetic signatures in insulin-2 gene promoter region of Undernourished rats are not reversed by nutrient recuperation, and may contribute to the persistent detrimental metabolic profiles in similar multigenerational undernourished human populations.

Optimised Multiplication Architectures for Accelerating Fully Homomorphic Encryption

Large integer multiplication is a major performance bottleneck in fully homomorphic encryption (FHE) schemes over the integers. In this paper two optimised multiplier architectures for large integer multiplication are proposed. The first of these is a low-latency hardware architecture of an integer-FFT multiplier. Secondly, the use of low Hamming weight (LHW) parameters is applied to create a novel hardware architecture for large integer multiplication in integer-based FHE schemes. The proposed architectures are implemented, verified and compared on the Xilinx Virtex-7 FPGA platform. Finally, the proposed implementations are employed to evaluate the large multiplication in the encryption step of FHE over the integers. The analysis shows a speed improvement factor of up to 26.2 for the low-latency design compared to the corresponding original integer-based FHE software implementation. When the proposed LHW architecture is combined with the low-latency integer-FFT accelerator to evaluate a single FHE encryption operation, the performance results show that a speed improvement by a factor of approximately 130 is possible.

Tyrosine phosphorylation and dephosphorylation in Burkholderia cenocepacia affect biofilm formation, growth under nutritional deprivation, and pathogenicity

Burkholderia cenocepacia, a member of the B. cepacia complex (Bcc), is an opportunistic pathogen causing serious chronic infections in patients with cystic fibrosis. Tyrosine phosphorylation has emerged as an important post-translational modification modulating the physiology and pathogenicity of Bcc bacteria. Here, we investigated the predicted bacterial tyrosine kinases BCAM1331 and BceF, and the low molecular weight protein tyrosine phosphatases BCAM0208, BceD and BCAL2200 of B. cenocepacia K56-2. We show that BCAM1331, BceF, BCAM0208 and BceD contributed to biofilm formation, while BCAL2200 was required for growth in nutrient-limited conditions. Multiple deletions of either tyrosine kinase or low molecular weight protein tyrosine phosphatases genes resulted in attenuation of B. cenocepacia intramacrophage survival and reduced pathogenicity in the Galleria mellonella larvae infection model. Experimental evidence indicates that BCAM1331 displays a reduced
tyrosine autophosphorylation activity compared to BceF. Using the artificial substrate p-nitrophenyl phosphate, the phosphatase activity of the three low molecular weight protein tyrosine phosphatases demonstrated similar kinetic parameters. However, only BCAM0208 and BceD could dephosphorylate BceF. Further, BCAL2200 becomes tyrosine phosphorylated in vivo and catalyzes its auto-dephosphorylation. Together, our data suggest that despite having similar biochemical activities low molecular weight protein tyrosine phosphatases and tyrosine kinases have both overlapping and specific roles in the physiology of B. cenocepacia.

Energy versus data integrity trade-offs in embedded high-density logic compatible dynamic memories

Current variation aware design methodologies, tuned for worst-case scenarios, are becoming increasingly pessimistic from the perspective of power and performance. A good example of such pessimism is setting the refresh rate of DRAMs according to the worst-case access statistics, thereby resulting in very frequent refresh cycles, which are responsible for the majority of the standby power consumption of these memories. However, such a high refresh rate may not be required, either due to extremely low probability of the actual occurrence of such a worst-case, or due to the inherent error resilient nature of many applications that can tolerate a certain number of potential failures. In this paper, we exploit and quantify the possibilities that exist in dynamic memory design by shifting to the so-called approximate computing paradigm in order to save power and enhance yield at no cost. The statistical characteristics of the retention time in dynamic memories were revealed by studying a fabricated 2kb CMOS compatible embedded DRAM (eDRAM) memory array based on gain-cells. Measurements show that up to 73% of the retention power can be saved by altering the refresh time and setting it such that a small number of failures is allowed. We show that these savings can be further increased by utilizing known circuit techniques, such as body biasing, which can help, not only in extending, but also in preferably shaping the retention time distribution. Our approach is one of the first attempts to access the data integrity and energy tradeoffs achieved in eDRAMs for utilizing them in error resilient applications and can prove helpful in the anticipated shift to approximate computing.

The welfare implications of large litter size in the domestic pig I:Biologica factors

Increasing litter size has long been a goal of pig breeders and producers, and may have implications for pig (Sus scrofa domesticus) welfare. This paper reviews the scientific evidence on biological factors affecting sow and piglet welfare in relation to large litter size. It is concluded that, in a number of ways, large litter size is a risk factor for decreased animal welfare in pig production. Increased litter size is associated with increased piglet mortality, which is likely to be associated with significant negative animal welfare impacts. In surviving piglets, many of the causes of mortality can also occur in non-lethal forms that cause suffering. Intense teat competition may increase the likelihood that some piglets do not gain adequate access to milk, causing starvation in the short term and possibly long-term detriments to health. Also, increased litter size leads to more piglets with low birth weight which is associated with a variety of negative long-term effects. Finally, increased production pressure placed on sows bearing large litters may produce health and welfare concerns for the sow. However, possible biological approaches to mitigating health and welfare issues associated with large litters are being implemented. An important mitigation strategy is genetic selection encompassing traits that promote piglet survival, vitality and growth. Sow nutrition and the minimisation of stress during gestation could also contribute to improving outcomes in terms of piglet welfare. Awareness of the possible negative welfare consequences of large litter size in pigs should lead to further active measures being taken to mitigate the mentioned effects. © 2013 Universities Federation for Animal Welfare.