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by microsatellite markers in Western Ecuador. Genet Resour Crop Evol 53:1361–1373CrossRef Couvreur TLP, Hahn WJ, de Granville J-J, Pahm J-L, Ludeña B, Pintaud J-C (2007) Phylogenetic relationships of the cultivated Neotropical palm Bactris gasipaes (Arecaceae) with its wild relatives inferred from chloroplast and nuclear DNA polymorphisms. Syst Bot 32(3):519–530CrossRef Da Silva JBF, Clement CR (2005) Wild pejibaye (Bactris gasipaes Kunth var. chichagui) in Southeastern Amazonia. Acta Bot Bras 19(2):281–284 De Oliveira MKS, Martinez-Flores HE, de Andrade JS, Garnica-Romo MG, Chang YK (2006) Use of pejibaye flour (Bactris gasipaes Kunth) Tipifarnib concentration in the production of food pastas. Int J

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Therefore, we used a rather strict criterion for “normal hearing”

Therefore, we used a rather strict criterion for “normal hearing”, and more specific criteria for the degree of the noise notch. The following audiogram categorization was applied to the audiometric thresholds per ear: Normal hearing (N): hearing threshold levels better than or equal to 15dB HL at all measured frequencies (i.e. 0.5, 1, 2, 3, 4, 6, 8 kHz). Notch moderate (NM): maximum threshold level of 3, 4, and 6 kHz between 15 and 20 dB poorer than the pure-tone average of thresholds at 0.5, 1 and 2 kHz and at least 10 dB poorer than the threshold

level at 8 kHz. This is similar to Niskar et al. (2001) criterion of a noise notch in adolescents. Notch profound (NP): similar to NM, but maximum threshold level of 3, 4, 6 kHz at least 25 dB poorer than the pure-tone

Selleckchem Fosbretabulin average of thresholds at 0.5, 1 and 2 kHz. Sloping loss (SL): GDC 0032 maximum threshold level of 3, 4, 6 kHz at least 5 dB poorer than the pure-tone average of thresholds at 0.5, 1 and 2 kHz and threshold level at 8 kHz at least 5 dB poorer than the maximum threshold level at 3, 4, and 6 kHz. Flat loss (FL): audiograms which do not fall into the above mentioned categories, with no hearing thresholds exceeding 30dB at all measured frequencies. Rest (R): all audiograms that do not match the E1 Activating inhibitor characteristics of the above described categories. The corresponding average audiograms are shown in Fig. 1. The average audiogram in the group “Rest” turned out to have a steeply sloping curve. Most ears fell in the “Normal hearing” category (230 ears, 48%). The other ears were approximately equally divided over the other categories Y-27632 2HCl (NM = 53 ears, 11%, NP = 41 ears, 9%, SL = 64 ears, 13%, FL = 57 ears, 12%, R = 35 ears, 7%). If present, notches were mostly found at 6 kHz. Fig. 1 Musicians average audiograms according to the criteria for normal hearing (N), notch moderate (NM), notch profound (NP), sloping loss (SL), flat loss (FL), and a rest group (R) In the

“Normal hearing” category the average age of the ears was lowest (39.7 years), while it was highest in the “Sloping loss” category (52.2 years). For the category “Notch profound” (48.8 years) it was higher than for the category “Notch moderate” (45.1 years). A direct comparison of the distribution of audiometric categories across instruments groups could only be done with some caution, as there were large variations in the number of musicians in the instrument subgroups. However, when considering only the large groups, HS, LS, WW and BW, 40–52% of each of these groups fell into the audiogram category “Normal Hearing”. The percentages did not differ significantly (χ 2(3) = 2, p = 0.57). Hearing loss with sloping curves (SL) was found less among the brass wind players (2 ears, 3%) than in the other groups (HS = 28 ears, 14%, LS = 16 ears, 20%, and WW = 13 ears, 13%, χ 2(3) = 11.9, p = 0.007).

I always admired Bill since he was such a thinker who persevered

I always admired Bill since he was such a thinker who persevered and solved complex problems like the mechanism of photorespiration that clearly is a landmark discovery. His

approach was the key to being a great scientist and the awards he has won, including this one, have been justly deserved. Along the way he also helped nurture a group of very astute researchers. George Bowes As noted in the write-up by Archie Portis (see Ogren and Bowes 1971; Bowes et al. 1971), the first observation that gave the idea that the same enzyme (known earlier as “carboxydismutase” in Melvin Calvin’s lab) was responsible for reaction with CO2 and O2 evolved in the work of Bill Ogren with George Bowes, who was a postdoctoral associate at the University of Illinois at Urbana, Illinois. Although George was unable to this website attend the ceremony, he was invited by the two of us to present his story. George

sent the following text to us. It reads: I was Bill’s first postdoc. I came to the US in 1968 at Richard (Dick) Hageman’s invitation, but when I arrived he gave me a choice—to work on nitrogen metabolism or work with Cell Cycle inhibitor a “young USDA scientist” (Bill Ogren) on photosynthesis. Knowing little about either topic I asked for a week to decide and Bill gave me some papers, including one by Olle Björkman that contained Chorioepithelioma a graph showing carboxydismutase (Rubisco) activity was directly related

to photosynthesis rate. It convinced us both that this was an important enzyme, and could be a productivity “marker” in soybean varieties—a topic we pursued prior to purifying the enzyme and investigating its kinetic characteristics.   Working with Bill was an enjoyable and productive learning experience. Coming from a largely self-directed PhD program, I appreciated being a collaborator, not someone to “direct”, and this laid-back leadership style of his has produced some remarkable scientists and discoveries. Bill was easy to talk with, very prescient and AZD2281 purchase direct and could take a half-baked idea and hone it into something useful. I recall Friday afternoons when we would chat about everything from English customs (Bill was an anglophile) to politics and sports. This Englishman/American learned a lot about American life from Bill. Inevitably, the talk turned to the recent discovery of C-4 photosynthesis and the mechanism of the Warburg effect (Warburg 1920). These casual conversations were some of the most productive times of sharing ideas to test experimentally. Later Bill Laing and then Ray Chollet joined the lively prolonged coffee hours.   I am thankful that neither Bill nor Dick gave up after the first year of research when I had no publishable results to report, and was quite discouraged.

Nat Rev Microbiol 2009, 7:237–245 PubMedCrossRef 6 Al-Maghrebi M

Nat Rev Microbiol 2009, 7:237–245.PubMedCrossRef 6. Al-Maghrebi M, Fridovich I, Benov L: Manganese supplementation relieves the phenotypic deficits seen in superoxide-dismutase-null Escherichia coli. Arch Biochem Biophys 2002, 402:104–109.PubMedCrossRef 7. Daly MJ, Gaidamakova EK, Matrosova VY, Vasilenko A, Zhai M, find more Leapman RD, Lai

B, Ravel B, Li S-MW, Kemner KM, Fredrickson JK: Protein Oxidation Implicated as the Primary Determinant of Bacterial Radioresistance. PLoS Biol 2007, 5:e92.PubMedCrossRef 8. Daly MJ, Gaidamakova EK, Matrosova VY, Vasilenko A, Zhai M, Venkateswaran A, Hess M, Omelchenko MV, Kostandarithes HM, Makarova KS, et al.: Accumulation of Mn(II) in Deinococcus radiodurans facilitates gamma-radiation resistance. Science 2004, 306:1025–1028.PubMedCrossRef 9. AZD1480 nmr Papp-Wallace KM, Maguire ME: Manganese transport and the role of manganese in virulence. Annu Rev Microbiol 2006, 60:187–209.PubMedCrossRef 10. Rosch JW, Gao G, Ridout G, Wang YD, Tuomanen EI: Role of the manganese efflux system mntE for signalling and pathogenesis in Streptococcus pneumoniae. Mol Microbiol 2009, 72:12–25.PubMedCrossRef 11. Chang S, Shu H, Li Z, Wang Y, Chen L, Hua Y, Qin G: Disruption of manganese ions [Mn(II)] transporter genes DR1709

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H, Xu G, Zhao Y, Tian B, Lu H, Yu X, Xu Z, Vasopressin Receptor Ying N, Hu S, Hua Y: A novel OxyR sensor and regulator of hydrogen peroxide stress with one cysteine residue in Deinococcus radiodurans. PLoS One 2008, 3:e1602.PubMedCrossRef 14. Haney CJ, Grass G, Franke S, Rensing C: New developments in the understanding of the cation diffusion facilitator family. J Ind Microbiol Biotechnol 2005, 32:215–226.PubMedCrossRef 15. Kehres DG, Maguire ME: Emerging themes in manganese transport, biochemistry and pathogenesis in bacteria. FEMS Microbiol Rev 2003, 27:263–290.PubMedCrossRef 16. Kloosterman TG, van der Kooi-Pol MM, Bijlsma JJ, Kuipers OP: The novel transcriptional regulator SczA mediates protection against Zn2+ stress by activation of the Zn2+-resistance gene czcD in Streptococcus pneumoniae. Mol Microbiol 2007, 65:1049–1063.PubMedCrossRef 17. McAllister LJ, Tseng HJ, Ogunniyi AD, Jennings MP, McEwan AG, Paton JC: Molecular analysis of the psa LY2606368 mw permease complex of Streptococcus pneumoniae. Mol Microbiol 2004, 53:889–901.PubMedCrossRef 18. Rosch JW, Sublett J, Gao G, Wang YD, Tuomanen EI: Calcium efflux is essential for bacterial survival in the eukaryotic host. Mol Microbiol 2008, 70:435–444.PubMedCrossRef 19.

Understanding the energy transfer network with qE on requires a m

Understanding the energy transfer network with qE on requires a mathematical framework that

incorporates that information. The equation describing the changes in excitation population on any node in the network is given by the master equation: Nec-1s $$ \frac\rm dP(t)\rm dt = KP(t), $$ (6)where P(t) is a vector containing the populations of each node at a time t and K is a rate matrix that contains all of the information regarding energy transfer connectivity and rates, qE and RC quenching rates, and fluorescence and ISC rates. The fluorescence decay F(t) in this formalism is simply the sum of P(t) over all nodes in the network, weighted by the rate of fluorescence at each node (Yang et al. 2003). Knowing K is equivalent to knowing the

energy transfer network, and a full understanding of qE requires characterizing the changes in K between dark- and light-adapted grana membranes (see Fig. 6). To determine K in grana membranes with qE on, Holzwarth and coworkers measured and fit fluorescence lifetimes on quenched and unquenched leaves with closed RCs of wild type and npq4, npq1, and L17 leaves from A. thaliana. A kinetic model for energy quenching in thylakoid selleck chemicals membranes was fit to the fluorescence lifetime data using target analysis (Holzwarth et al. 2009). The kinetic model (K) contained the assumption that all the pigments in the grana membrane are connected, with excitation energy transfer between them occurring much faster Molecular motor than Batimastat nmr charge separation. The model was first fit to dark-acclimated leaves. Fitting the model with the data from light-acclimated

leaves required increasing the non-radiative decay rate of the antenna compartment and including an additional compartment with a decay time of ∼400 ps. The increase in the non-radiative decay rate correlated positively with the amount of zeaxanthin, and the amplitude of the detached compartment correlated positively with the amount of PsbS. These correlations led to the proposal that there are two mechanisms of qE: one that was zeaxanthin dependent that occurred in the antenna of the PSII supercomplex, and one that was PsbS dependent that occurred by detachment of LHCII trimers from PSII. A more complex model for energy transfer in the thylakoid membrane compared to that in Gilmore et al. (1995) resulted in more detailed information about the energy transfer network. It is still unclear what the appropriate model is for describing energy transfer in grana membranes. Recent work by van Oort et al. (2010) has suggested that the migration time of excitations in thylakoid membranes makes up ∼50 % of the average chlorophyll fluorescence lifetime. This result suggests that models that assume that energy transfer is instantaneous may not be sufficiently detailed to accurately describe energy transfer in grana membranes.

This relatively large value compared to the previous measurement

This relatively large value compared to the previous measurement on sapphire (0.61°) [11] can be attributed to the AlN buffer layer epitaxial

quality and to the nucleation on the defects. HRTEM cross-section observations have been performed to investigate the epitaxial relationship in between the GaN wire/AlN buffer/Si substrate. The observation was made with a JEOL 3010 (JEOL Ltd., Tokyo, Japan) operating at 200 kV along the zone axis. Figure 3a shows the base of a GaN wire grown on Si with an AlN buffer layer of 10-nm nominal thickness. As shown by the detailed view of Figure 3b, four distinct layers are observed. A 2-nm-thick ACY-1215 price amorphous (or nanocrystallized) layer is observed directly on top of the Si substrate. This layer can be attributed to the spontaneous SiN x formation resulting from the high-temperature growth of the AlN buffer on silicon as already reported by Radtke et al. [15]. The AlN seeds probably nucleate through this non-continuous thin silicon nitride layer, and a planar growth develops laterally to form an almost single-crystalline AlN epitaxial layer for further growth. To confirm these assumptions, the in-plane epitaxial relationships have been studied at the European

Synchrotron Radiation Facility (ESRF, Grenoble, France) on the French BM32 CRG beamline with a 0.1204-nm wavelength. Grazing incidence X-ray diffraction (GIXRD) has been performed with 0.18° incidence to check the AlN

epitaxy on SiN x /Si (111). The usual orientations [17] have been measured corresponding to the AlN //Si and AlN //Si alignments. These measurements check details Lumacaftor confirm also the complete registry of GaN wires with the AlN layer (see for example the scans along the Si direction shown in Figure 2c,d). The AlN layer has been formed at high temperature (approximately 1,100°C) in the 10- to 50-nm range to sufficiently protect the surface and maintain the epitaxy. The study of the epitaxial relationship at lower growth temperature and different thicknesses could be interesting in further studies. Figure 2 X-ray diffraction measurements of GaN wires grown on Si (111) with an intermediate AlN layer. (a) Symmetric Θ-2Θ scan performed on a laboratory setup (approximately 0.179 nm Co-wavelength) and indexed with Si, GaN and AlN Bragg Kα1 reflections. Dots and squares correspond respectively to the Kα2 and Kβ excitation wavelengths. The broad and low intensity peak around 51° (see the triangle) is attributed to a diffraction tail of the Si substrate. (b) Rocking curves (Δω-scan) of the GaN (0002) and (0004) peaks. (c,d) Grazing incidence X-ray diffraction performed at ESRF along the silicon direction (approximately 0.1203 nm wavelength and 0.18° incidence). Figure 3 HRTEM imaging of the GaN/AlN/Si interface (a,b). Observation along the zone axis showing the materials stacking.

PubMedCrossRef 12 Zarivach R, Ben-Zeev E, Wu N, Auerbach T, Bash

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In our previous research, we have developed a method to optimize

In our previous research, we have developed a method to optimize the GaAs-on-Si substrate, which has greatly reduced their residual stress and surface defect density [11]. In this work, based on the surface optimization technology that we developed, the RTD Geneticin ic50 structure was then grown on the optimized substrate; combining Raman spectroscopy and I-V characterizations, the stress–strain coupling effect from the Si substrate to GaAs-based RTD was tested. Finally, the piezoresistive coefficient of the RTD was characterized. This method gives us a solution to optimize the epitaxy GaAs layers on the Si substrate, which also proved the possibility

of our future process of integrating GaAs-based RTD on the Si substrate for MEMS sensor applications. Experimental Commercially available GaAs-on-Si wafers were selleck chemical used as the initial substrates in this experiment, AG-881 purchase which were purchased from Spire Corp., Bedford, MA, USA. The GaAs layers were grown directly on 3-in. Si wafers (with N+ doping concentrations of 5 × 1016 cm−2 and 350 μm in thickness). GaAs epilayers with a thickness of 2 μm were grown on (100)-oriented Si with 4° misorientation toward the (111) Si substrate. The initial density of the lattice defect of the purchased

GaAs/Si wafers was about 108 cm−2. The GaAs-based optimization superlattice layers and RTD heterostructures were fabricated by molecular beam epitaxy using Veeco Mod-GEN II, Plainview, NY, USA. InGaAs/GaAs strain superlattice was used as the buffer

layer to optimize the defects and residual stress of the substrate, and then the RTD heterostructures were grown on top as the strain sensing element. The surface topography and IKBKE cross-section of the epilayers were characterized by transmission electron microscopy (FEI Tecnai G2 F20, Hillsboro, OR, USA) and scanning electron microscopy (KYKY-1000B, Beijing, China). The stress–strain coupling effect was characterized by residual stress using the Renishaw inVia Raman microscope system (Gloucestershire, UK; the laser line is 514.5 nm, and the excitation beam power is 5 mW). The luminescence characteristics of the quantum well were observed using Fourier transform infrared spectrometer (Nicolet FTIR760, Appleton, WI, USA) with a power of 1 W and a wavelength of 632.8 nm. The samples were cut into pieces of 0.5 cm × 2 cm for the stress–strain coupling effect test. The schematic of the setup used to strain the samples is provided in Figure 1. The sample was fixed on a homemade test setup from one end. The other end of the substrate was free to move. The micrometer was used to stress the sample from the free end. By tuning the micrometer, different stresses were applied.

(C) AFM image of the (MTX + PEG)-CS-NPs Scale bars = 500 nm Ins

(C) AFM image of the (MTX + PEG)-CS-NPs. Scale bars = 500 nm. Inset: TEM image of the (MTX + PEG)-CS-NPs. Scale bars = 50 nm.

(D) Particle size distribution of the (MTX + PEG)-CS-NPs. (E) Zeta potential distribution of the (MTX + PEG)-CS-NPs. (F) In vitro stability tests of the (MTX + PEG)-CS-NPs in PBS (mean ± SD, n = 3). (G) In vitro stability tests of the (MTX + PEG)-CS-NPs in 10% plasma in PBS (mean ± SD, n = 3). Drug-loading S3I-201 content. CS-NPs possessing peripheral amino groups provided us great opportunities to easy surface biofunctionalization. In our study, the γ-carboxyl groups of MTX were conjugated to the residual amino groups of the PEGylated CS-NPs. The drug-loading content of the (MTX + PEG)-CS-NPs was calculated as 7.23 ± 0.11%. The simple conjugation chemistry and appropriate drug-loading content could favor the dual-acting role of Janus-like MTX. In vitro stability tests No significant variation of the particle size was observed in the (MTX + PEG)-CS-NPs even after incubation with PBS for a long period of time (Figure 4F). Notably, the CS-NPs (without

PEGylation) could precipitate after 48 h in the presence of salts. It was implied that PEG could protect the SIS3 concentration (MTX + PEG)-CS-NP against ionic strength. No significant change of the particle size was also shown in the (MTX + PEG)-CS-NPs after incubation with 10% plasma for 120 h (Figure 4G). It should be inferred that PEG could reduce the plasma proteins adsorption, and more importantly, preserve the targeting potential of MTX. All of the results suggested that the (MTX + PEG)-CS-NPs were sufficiently buy MG-132 stable to sustain physiological conditions for extended blood circulation. In vitro drug release profiles In vitro drug release profiles of the tuclazepam free MTX and (MTX + PEG)-CS-NPs were presented in Figure 5. To mimic the physiological conditions of the bloodstream, the (MTX + PEG)-CS-NPs were incubated with 10% plasma at pH 7.4. In sharp contrast to the free MTX with accumulated release amounts of almost 90% within 6 h,

a more sustained release of the NPs was clearly observed due to the slow hydrolysis of amide bonds. Nevertheless, within 48 h, only no more than 10% of MTX from NPs was released at pH 7.4. Once intravenously administrated, the NPs could ensure minimal premature release of MTX during the circulation, and thereby greatly reduces the systemic toxicity. It was expected that the NPs will accumulate at the tumor site by the EPR effect. Once inside the tumor tissue, these MTX-targeted PEG-CS-NPs will be internalized by the tumor cells, largely via FA receptor-mediated endocytosis (discussed below). Figure 5 In vitro drug release profiles of the (MTX + PEG)-CS-NPs in different physiological media (mean ± SD, n  = 3). It was well established that the amide bonds could be selectively cleaved at acidic pH by proteases (also called proteolytic enzymes) overexpressed in the tumor cells [33–36].