Rhabdomyolysis and Acute Renal Failure After Fire Ant Bites

We describe a 59-year-old patient who developed acute renal failure because of rhabdomyolysis after extensive red fire ant bites. This case illustrates a serious systemic reaction that may occur from fire ant bites. Consistent with the clinical presentation in rhabdomyolysis associated with non-traumatic causes, hyperkalemia, hypophosphatemia, hypocalcemia, and high anion gap acidosis were not observed in this patient. While local allergic reactions to fire ant bites are described in the literature, serious systemic complications with rhabdomyolysis and renal failure have not been previously reported. It is our effort to alert the medical community of the possibility of such a complication that can occur in the victims of fire ant bites

Adenosine-mono-phosphate-activated protein kinase-independent effects of metformin in T cells

The anti-diabetic drug metformin regulates T-cell responses to immune activation and is proposed to function by regulating the energy-stress-sensing adenosine-monophosphate-activated protein kinase (AMPK). However, the molecular details of how metformin controls T cell immune responses have not been studied nor is there any direct evidence that metformin acts on T cells via AMPK. Here, we report that metformin regulates cell growth and proliferation of antigen-activated T cells by modulating the metabolic reprogramming that is required for effector T cell differentiation. Metformin thus inhibits the mammalian target of rapamycin complex I signalling pathway and prevents the expression of the transcription factors c-Myc and hypoxia-inducible factor 1 alpha. However, the inhibitory effects of metformin on T cells did not depend on the expression of AMPK in T cells. Accordingly, experiments with metformin inform about the importance of metabolic reprogramming for T cell immune responses but do not inform about the importance of AMPK

Neutralino versus axion/axino cold dark matter in the 19 parameter SUGRA model

We calculate the relic abundance of thermally produced neutralino cold dark matter in the general 19 parameter supergravity (SUGRA-19) model. A scan over GUT scale parameters reveals that models with a bino-like neutralino typically give rise to a dark matter density \Omega_{\tz_1}h^2\sim 1-1000, i.e. between 1 and 4 orders of magnitude higher than the measured value. Models with higgsino or wino cold dark matter can yield the correct relic density, but mainly for neutralino masses around 700-1300 GeV. Models with mixed bino-wino or bino-higgsino CDM, or models with dominant co-annihilation or A-resonance annihilation can yield the correct abundance, but such cases are extremely hard to generate using a general scan over GUT scale parameters; this is indicative of high fine-tuning of the relic abundance in these cases. Requiring that m_{\tz_1}\alt 500 GeV (as a rough naturalness requirement) gives rise to a minimal probably dip in parameter space at the measured CDM abundance. For comparison, we also scan over mSUGRA space with four free parameters. Finally, we investigate the Peccei-Quinn augmented MSSM with mixed axion/axino cold dark matter. In this case, the relic abundance agrees more naturally with the measured value. In light of our cumulative results, we conclude that future axion searches should probe much more broadly in axion mass, and deeper into the axion coupling.Comment: 23 pages including 17 .eps figure

Two‑Dimensional Copper Coordination Polymer Assembled with Fumarate and 5,5’‑Dimethyl‑2,2’‑bipyridine: Synthesis, Crystal Structure and Magnetic Properties

[[Cu(fum)(dmb)]·H2O]n, exhibiting weak antiferromagnetic interactions, displays a two-dimensional array comprised of rhombic dinuclear units, where the carboxylate moieties of fumarate bridging ligand displays monodentate and oxo-bridging coordination modes connecting two Cu centers.[[Cu(fum)(dmb)]·H2O]n (1) (fum = fumarate; dmb = 5,5’-dimethyl-2,2’-bipyridine) was obtained by a self-assembly solution reaction, at ambient conditions, and characterized by elemental analysis, IR spectroscopy and X-ray single crystal diffraction. Crystallographic studies show that 1 crystallizes in a triclinic system with a P-1 space group, with a = 8.2308(2) Å, b = 9.7563(2) Å, c = 10.3990(2) Å; α = 80.3444(4)°, β = 77.9517(4)°, γ = 82.0440(5)°; V = 800.45(3) Å3. The Cu(II) centers are five-coordinated with a distorted square pyramidal configuration. The formation of a two-dimensional (2D) array in 1 can be explained by the presence of two different coordination modes in the fumarate ligand: μ-η1:η0 and μ2-η2:η0, both in a bridging monodentate manner, the latter generating distinctive rhombic-dinuclear units. The thermal stability of 1 has also been analyzed. Magnetic measurements revealed that this polymer exhibits weak antiferromagnetic ordering.Universidad Autonoma del Estado de México Universidad Nacional Autónoma de Méxic

Optimising biocatalyst design for obtaining high transesterification activity by α-chymotrypsin in non-aqueous media

<p>Abstract</p> <p>Background</p> <p>Enzymes are often used in organic solvents for catalyzing organic synthesis. Two enzyme preparations, EPRP (enzyme precipitated and rinsed with n-propanol) and PCMC (protein coated microcrystals) show much higher activities than lyophilized powders in such systems. Both preparations involve precipitation by an organic solvent. The clear understanding of why these preparations show higher catalytic activity than lyophilized powders in organic solvents is not available.</p> <p>Results</p> <p>It was found that EPRPs of α-chymotrypsin prepared by precipitation with <it>n</it>-propanol in the presence of trehalose contained substantial amount of trehalose (even though trehalose alone at these lower concentrations was not precipitated by <it>n</it>-propanol). The presence of trehalose in these EPRPs resulted in much higher transesterification rates (45.2 nmoles mg^-1min^-1) as compared with EPRPs prepared in the absence of trehalose (16.6 nmoles mg^-1min^-1) in octane. Both kinds of EPRPs gave similar initial transesterification rates in acetonitrile. Use of higher concentrations of trehalose (when trehalose alone also precipitates out), resulted in the formation of PCMCs, which showed higher transesterification rates in both octane and acetonitrile. SEM analysis showed the relative sizes of various preparations. Presence of trehalose resulted in EPRPs of smaller sizes.</p> <p>Conclusion</p> <p>The two different forms of enzymes (EPRP and PCMC) known to show higher activity in organic solvents were found to be different only in the way the low molecular weight additive was present along with the protein. Therefore, the enhancement in the transesterification activity in EPRPs prepared in the presence of trehalose was due to: (a) better retention of essential water layer for catalysis due to the presence of the sugar. This effect disappeared where the reaction media was polar as the polar solvent (acetonitrile) is more effective in stripping off the water from the enzyme; (b) reduction in particle size as revealed by SEM. In the case of PCMC, the enhancement in the initial rates was due to an increase in the surface area of the biocatalyst since protein is coated over the core material (trehalose or salt).</p> <p>It is hoped that the insight gained in this work would help in a better understanding for designing high activity biocatalyst preparation of non-aqueous media.</p

A high-performance matrix-matrix multiplication methodology for CPU and GPU architectures

Current compilers cannot generate code that can compete with hand-tuned code in efficiency, even for a simple kernel like matrix–matrix multiplication (MMM). A key step in program optimization is the estimation of optimal values for parameters such as tile sizes and number of levels of tiling. The scheduling parameter values selection is a very difficult and time-consuming task, since parameter values depend on each other; this is why they are found by using searching methods and empirical techniques. To overcome this problem, the scheduling sub-problems must be optimized together, as one problem and not separately. In this paper, an MMM methodology is presented where the optimum scheduling parameters are found by decreasing the search space theoretically, while the major scheduling sub-problems are addressed together as one problem and not separately according to the hardware architecture parameters and input size; for different hardware architecture parameters and/or input sizes, a different implementation is produced. This is achieved by fully exploiting the software characteristics (e.g., data reuse) and hardware architecture parameters (e.g., data caches sizes and associativities), giving high-quality solutions and a smaller search space. This methodology refers to a wide range of CPU and GPU architectures

Removal of Hepatitis B virus surface HBsAg and core HBcAg antigens using microbial fuel cells producing electricity from human urine

© 2019, The Author(s). Microbial electrochemical technology is emerging as an alternative way of treating waste and converting this directly to electricity. Intensive research on these systems is ongoing but it currently lacks the evaluation of possible environmental transmission of enteric viruses originating from the waste stream. In this study, for the first time we investigated this aspect by assessing the removal efficiency of hepatitis B core and surface antigens in cascades of continuous flow microbial fuel cells. The log-reduction (LR) of surface antigen (HBsAg) reached a maximum value of 1.86 ± 0.20 (98.6% reduction), which was similar to the open circuit control and degraded regardless of the recorded current. Core antigen (HBcAg) was much more resistant to treatment and the maximal LR was equal to 0.229 ± 0.028 (41.0% reduction). The highest LR rate observed for HBsAg was 4.66 ± 0.19 h−1 and for HBcAg 0.10 ± 0.01 h−1. Regression analysis revealed correlation between hydraulic retention time, power and redox potential on inactivation efficiency, also indicating electroactive behaviour of biofilm in open circuit control through the snorkel-effect. The results indicate that microbial electrochemical technologies may be successfully applied to reduce the risk of environmental transmission of hepatitis B virus but also open up the possibility of testing other viruses for wider implementation

Is EC class predictable from reaction mechanism?

We thank the Scottish Universities Life Sciences Alliance (SULSA) and the Scottish Overseas Research Student Awards Scheme of the Scottish Funding Council (SFC) for financial support.Background: We investigate the relationships between the EC (Enzyme Commission) class, the associated chemical reaction, and the reaction mechanism by building predictive models using Support Vector Machine (SVM), Random Forest (RF) and k-Nearest Neighbours (kNN). We consider two ways of encoding the reaction mechanism in descriptors, and also three approaches that encode only the overall chemical reaction. Both cross-validation and also an external test set are used. Results: The three descriptor sets encoding overall chemical transformation perform better than the two descriptions of mechanism. SVM and RF models perform comparably well; kNN is less successful. Oxidoreductases and hydrolases are relatively well predicted by all types of descriptor; isomerases are well predicted by overall reaction descriptors but not by mechanistic ones. Conclusions: Our results suggest that pairs of similar enzyme reactions tend to proceed by different mechanisms. Oxidoreductases, hydrolases, and to some extent isomerases and ligases, have clear chemical signatures, making them easier to predict than transferases and lyases. We find evidence that isomerases as a class are notably mechanistically diverse and that their one shared property, of substrate and product being isomers, can arise in various unrelated ways. The performance of the different machine learning algorithms is in line with many cheminformatics applications, with SVM and RF being roughly equally effective. kNN is less successful, given the role that non-local information plays in successful classification. We note also that, despite a lack of clarity in the literature, EC number prediction is not a single problem; the challenge of predicting protein function from available sequence data is quite different from assigning an EC classification from a cheminformatics representation of a reaction.Publisher PDFPeer reviewe