Nitrogen Dissolution in Liquid Ga and Fe: Comprehensive Ab Initio Analysis,Relevance for Crystallization of GaN

The dissolution of molecular nitrogen in Ga and Fe was investigated by ab initio calculations and some complementary experiments. It was found that the N bonding inside these solvents is fundamentally different. For Ga, it is between Ga4s and Ga4p and N2p states whereas for Fe this is by N2p to Fe4s, Fe4p and Fe3d states. Accordingly, the energy of dissolution of N2 for arbitrarily chosen starting atomic configurations was 0.535 eV/mol and −0.299 eV/mol for Ga and Fe, respectively. For configurations optimized with molecular dynamics, the difference between the corresponding energy values, 1.107 eV/mol and 0.003 eV/mol, was similarly large. Full thermodynamic analysis of chemical potential was made employing entropy-derived terms in a Debye picture. The entropy-dependent terms were obtained via a normal conditions path to avoid singularity of ideal gas entropy at zero K. Nitrogen solubility as a function of temperature and N2 pressure was evaluated, being much higher for Fe than for Ga. For T=1800 K and p=104 bar, the N concentration in Ga was 3×10−3 at. fr. whereas for Fe, it was 9×10−2 at. fr. in very good agreement with experimental data. It indicates that liquid Fe could be a prospective solvent for GaN crystallization from metallic solutions.     

Antimicrobial resistance in urinary bacterial isolates from pregnant women in rural Tanzania: implications for public health

Treatment of asymptomatic bacteriuria and urinary tract infections in pregnancy can prevent adverse outcome for mother and child. However, antimicrobial resistance can impede effective chemotherapy. From April 1995 to March 1996, urine specimens from 5153 pregnant women in a rural area in northern Tanzania were inoculated on dip slides. Bacterial isolates from 101 positive dip slides were identified and tested for susceptibility to antimicrobial agents by disc diffusion. In total, 107 bacterial isolates were recovered, 71 Gram-negative and 36 Gram-positive. The most frequent isolates were Escherichia coli (n=27) and enterococci (n=15). E. coli isolates showed low rates of resistance to ampicillin (17%), mecillinam (9%), cefalexin (0%), nitrofurantoin (4%), trimethoprim-sulfamethoxazole (0%), trimethoprim (13%) and sulfamethoxazole (0%). Other Gram-negative bacteria displayed higher rates of resistance to these drugs. All enterococcal isolates were sensitive to ampicillin and only 2 were resistant to nitrofurantoin. Growth of E. coli from urine culture was correlated with adverse outcome of pregnancy (relative risk 4.13, 95% confidence interval 1.50-11.38). Antimicrobial susceptibility prevails in urinary isolates of E. coli and enterococci from rural areas of northern Tanzania. Susceptibility data from both rural and urban areas should be taken into account when planning antibiotic policies.     

Interferon response factor 3 is crucial to poly-I:C induced NK cell activity and control of B16 melanoma growth

Interferon Response Factor 3 (IRF3) induces several NK-cell activating factors, is activated by poly-I:C, an experimental cancer therapeutic, but is suppressed during many viral infections. IRF3 Knockout (KO) mice exhibited enhanced B16 melanoma growth, impaired intratumoral NK cell infiltration, but not an impaired poly-I:C therapeutic effect due to direct suppression of B16 growth. IRF3 was responsible for poly-I:C decrease in TIM-3 expression by intratumoral dendritic cells, induction of NK-cell Granzyme B and IFN-γ, and induction of macrophage IL-12, IL-15, IL-6, and IRF3-dependent NK-activating molecule (INAM). Thus, IRF3 is a key factor controlling melanoma growth through NK-cell activities, especially during poly-I:C therapy.     

Transmission of Facial Expressions of Emotion Co-Evolved with Their Efficient Decoding in the Brain: Behavioral and Brain Evidence

Competent social organisms will read the social signals of their peers. In primates, the face has evolved to transmit the organism's internal emotional state. Adaptive action suggests that the brain of the receiver has co-evolved to efficiently decode expression signals. Here, we review and integrate the evidence for this hypothesis. With a computational approach, we co-examined facial expressions as signals for data transmission and the brain as receiver and decoder of these signals. First, we show in a model observer that facial expressions form a lowly correlated signal set. Second, using time-resolved EEG data, we show how the brain uses spatial frequency information impinging on the retina to decorrelate expression categories. Between 140 to 200 ms following stimulus onset, independently in the left and right hemispheres, an information processing mechanism starts locally with encoding the eye, irrespective of expression, followed by a zooming out to processing the entire face, followed by a zooming back in to diagnostic features (e.g. the opened eyes in “fear”, the mouth in “happy”). A model categorizer demonstrates that at 200 ms, the left and right brain have represented enough information to predict behavioral categorization performance.