A plane wave source is simulated at normal incidence to the struc

A plane wave source is simulated at normal incidence to the structure. The computational domain (400 nm × 400 nm × 1,000 nm) has a perfectly matched layer (PML), absorbing boundaries in the z direction and periodic boundaries in the x-y plane [36]. A uniform FDTD mesh size is adopted. The mesh size is the same along all Cartesian axes: ∆x = ∆y = ∆z = 2 nm, which is sufficient to minimize the numerical errors arising from the FDTD method. Figure 1 Schematic of the proposed structure. (a) Schematic of the MDM structure AZD1390 cell line consisting of

a 60-nm-thick Bi2Se3 dielectric layer between two 30-nm-thick Au films perforated with a square array of elliptical holes suspended in air. The lattice constant is L = 400 nm, and hole diameters are d 1 = 240 nm and d 2 = 120 nm. (b) Illustration of the square lattice of ENA. The topological

insulator material Bi2Se3 was selected https://www.selleckchem.com/products/ve-822.html due to its significantly different optical properties between the trigonal and orthorhombic phases. The real (ϵ 1) and imaginary (ϵ 2) parts of the dielectric function for the different structural phases of Bi2Se3 were obtained from the published data in [28]; the NIR spectral region is shown in Figure  2. A large change in the dielectric function across the NIR is obtained after switching Bi2Se3 from trigonal to its orthorhombic phase. Figure 2 Dielectric constant of the Bi 2 Se 3 . (a) Real part of dielectric function ϵ 1(ω) for trigonal and orthorhombic phases of Bi2Se3. (b) Imaginary part of dielectric function ϵ 2(ω) for trigonal and orthorhombic selleck chemicals PAK5 phases of Bi2Se3. After the complex coefficients of transmission and reflection are obtained by the 3D EM Explorer Studio, in which T a is the amplitude and φ a is the phase of the transmission coefficient, and R a is the amplitude and φ ra is the phase of the reflection coefficient, the effective

optical parameters can be extracted using the Fresnel formula [37]. For an equivalent isotropic homogenous slab of thickness h surrounded by semi-infinite media with refractive index n 1 and n 3 under normal incidence, we have (1) (2) The so-called material parameters ϵ eff and μ eff of a single layer of a double-fishnet negative-index metamaterial are extracted using the well-known Nicholson-Ross-Weir (NRW) method [38–40]. Therefore, once n eff and η are evaluated, the effective permittivity and permeability are calculated using (3) where n eff is the effective refractive index, η is the impedance, h is the thickness of the structure, k = ω/c, c is the speed of light, m is an arbitrary integer, and n 1 = n 3 = 1 since the structure is suspended in a vacuum. The signs of n eff and η and the value of m are resolved by the passivity of the metamaterial that requires the signs of the real part of impedance η and imaginary part of effective index n eff to be positive, i.e., Real(η) > 0, Imag(n eff) > 0 which is consistent with the study described in [39, 40].

Cutis 2008;81(1):87–91 PubMed 28 Madaan A EpiCeram for the

Cutis. 2008;81(1):87–91.PubMed 28. Madaan A. EpiCeram for the treatment of atopic find more dermatitis. Drugs Today. 2008;44(10):751–5.PubMedCrossRef 29. Hon KL, Ching GK, Leung TF, Choi CY, Lee KK, Ng PC. Estimating emollient this website usage in patients with eczema. Clin Exp Dermatol. 2010;35(1):22–6.PubMedCrossRef 30. Kim HJ, Park HJ, Yun JN, Jeong SK, Ahn SK, Lee SH. Pseudoceramide-containing physiological lipid mixture reduces

adverse effects of topical steroids. Allergy Asthma Immunol Res. 2011;3(2):96–102.PubMedCrossRef 31. Roos TC, Geuer S, Roos S, Brost H. Recent advances in treatment strategies for atopic dermatitis. Drugs. 2004;64(23):2639–66.PubMedCrossRef 32. Baumer JH. Atopic eczema in children, NICE. Arch Dis Child Educ Pract Ed. 2008;93(3):93–7.PubMed”
“1 Introduction Bendamustine is a unique alkylating agent, which combines a nitrogen mustard moiety of mechlorethamine with a benzimidazole [1]. It has shown clinical activity against a variety of hematologic malignancies [2–5] and solid tumors [6, 7] as a single agent or in combination with other anticancer agents. Bendamustine is indicated

in the USA for the treatment of chronic lymphocytic leukemia and for indolent B-cell non-Hodgkin’s lymphoma that has progressed during or within 6 months of treatment with rituximab or a rituximab-containing regimen. https://www.selleckchem.com/products/mk-5108-vx-689.html Like other alkylating agents, bendamustine causes cross-links between DNA bases, resulting in DNA damage. However, in vitro studies with human ovarian and breast cancer cell lines showed that the double-strand breaks caused by bendamustine are more extensive and durable than those produced by the alkylating agents cyclophosphamide and carmustine [8]. This, combined with unique mechanistic features, including activation of DNA damage stress response and apoptosis, inhibition of mitotic checkpoints, and induction of mitotic catastrophe [1], may explain the activity of bendamustine in drug-resistant cells in vitro [8] and in patients with therapy-refractory lymphoma [3]. Bendamustine was generally well tolerated in patients

with relapsed or refractory non-Hodgkin’s lymphoma or mantle cell lymphoma [3, 9–12]. The main toxicities observed were reversible myelosuppression, including leukocytopenia, neutropenia, thrombocytopenia, and anemia. Nonhematologic toxicities included mild gastrointestinal events and fatigue [3, nearly 9]. A major route of bendamustine metabolism is hydrolysis to the inactive products monohydroxy bendamustine (HP1) and dihydroxy bendamustine (HP2), which make little or no contribution to the anti-cancer effects of bendamustine (Fig. 1). Two phase I metabolites of bendamustine have been identified: γ-hydroxy-bendamustine (M3) and N-desmethyl-bendamustine (M4) [Fig. 1]. Both are formed via the cytochrome P450 (CYP) 1A2 oxidative pathway, and they have potency similar to that of bendamustine (M3) or 5- to 10-fold lower than that of bendamustine (M4) [13]. Fig.

This suggests that overfeeding on sugar results in body fat gains

This suggests that overfeeding on sugar results in body fat gains in contrast to consuming

a natural food comprised of unprocessed carbohydrate and fat. Furthermore, there may be no difference in overfeeding on fat or carbohydrate in terms of fat storage [13]. Presently, the effects of protein overfeeding in resistance-trained individuals is unknown. Therefore, the purpose of this investigation was to determine the effects of a high protein diet on body composition in resistance-trained men and women in the absence of changes in training volume. Methods Subjects Forty resistance-trained subjects volunteered for this investigation. Subjects were unequally randomized to a control (CON n = 10) or high 4EGI-1 cost protein diet (HP n = 20) group. The purpose of unequal randomization was to take into account the loss of subjects from potential lack of compliance due to the high protein diet as well as gaining additional information on the treatment itself [14]. Participants were otherwise healthy resistance-trained men Dinaciclib and women who had been resistance training regularly for the last 8.9 ± 6.7 years and an average of 8.5 ± 3.3 hours per week. Individuals in the control group were instructed to maintain the same dietary and training habits over the course of the study. On the other hand, the subjects in the high

protein diet group were instructed to consume 4.4 grams of protein equal to 4.4 g/kg/d. All procedures involving human subjects were approved by Nova Southeastern University’s Human Subjects Institutional Review Board in accordance with the Helsinki Declaration, and written Ilomastat informed consent was obtained prior to participation.

Food diary, workout Log, body composition Subjects kept a daily diary of their food intake via a smartphone app (MyFitnessPal®). The use of mobile apps for diet self-monitoring have been previously used [15]. If they did not use the mobile app, subjects instead kept a paper diary and their daily food intake was measured via the Nutribase® program. In order to maintain a high protein diet, subjects consumed commercially available whey and casein protein powder (MusclePharm® and Adept Nutrition [Europa®]). Otherwise, the rest of their dietary protein was obtained from their normal food intake. Height was measured using standard anthropometry and total body weight was measured using a calibrated Sorafenib in vitro scale. Body composition was assessed by whole body densitometry using air displacement via the Bod Pod® (COSMED USA, Concord, CA). All testing was performed in accordance with the manufacturer’s instructions. Briefly, subjects were tested while wearing only tight fitting clothing (swimsuit or undergarments) and an acrylic swim cap. The subjects wore the exact same clothing for all testing. Thoracic gas volume was estimated for all subjects using a predictive equation integral to the Bod Pod® software. The calculated value for body density used the Siri equation to estimate body composition.

We injected ILK KO and control mice with a single intraperitoneal

We injected ILK KO and control mice with a single intraperitoneal lethal

dose (0.4 μg/g) of Jo-2. There was 50% mortality in the ILK KO (5/10) at 24 hours after Jo-2 injection, while all the controls died much faster than the ILK KO mice, showing 100% mortality (10/10) by 7 h after challenge whereas ILK KO mice were still alive at this time point (Figure 1A). Next we analyzed the effect of a sublethal dose of Jo-2 antibody (0.16 μg/g) on the survival of ILK KO and control mice. With this lower dose of Jo-2, there was 20% mortality (2/10) in the ILK KO mice while there was 70% mortality (7/10) in control mice by 24 h (Figure 1A). These data suggested that genetic ablation of ILK from hepatocytes protected the mice against Fas-induced apoptosis. We then evaluated Trichostatin A mw the degree of hepatocellular damage in ILK KO and control mice in response to the sublethal dose of Jo-2. Histological examination of liver samples obtained Selonsertib research buy at 6 h after sublethal dose of Jo-2 showed a higher degree of liver injury and the presence of parenchymal hemorrhages in control mice but not in ILK KO mice (Figure 1B). The different response to Jo-2 observed in ILK KO and control mice could be attributable in part to reduced hepatic expression of Fas receptor, because the basal levels of Fas as determined by Western blotting

was lower in the livers of the ILK KO liver (Figure 1C). The expression was also lower in the hepatocytes LCZ696 isolated from ILK KO mice compared to WT mice (Figure 1C). Thus, it is likely that ILK regulates the expression of Fas receptor. Similarly, TUNEL assay of the liver sections demonstrated more abundant apoptotic nuclei in control mice than in ILK KO mice. Activation of capase3/7 was also higher in the control mice than ILK KO mice at 6 and 12 h after Jo-2 administration. In addition, expression of cleaved caspase 3 and PARP were also higher in the control than the ILK KO mice at both 6 and 12 h after

a sublethal dose of Jo-2 (Figure 2A, B and 2C). Figure 1 Protection of ILK KO mice against Fas-induced liver injury and apoptosis. A) Kaplan Meier survival curves after a sublethal (0.16 μg/g) (left graph) and a lethal dose (0.40 μg/g) (right graph) of Jo-2. B) Hematoxylin-eosin staining of liver sections at 6 h after a sublethal injection of Jo-2 shows reduced hemorrhage and apoptotic cell bodies in the ILK KO mice. Double arrow = 300 μm. C) Representative next Western blots of basal levels of Fas receptor in whole livers and hepatocytes isolated from WT and ILK KO mice. Figure 2 Proteins associated with apoptosis and survival pathways are differentially expressed in the ILK KO mice. A) Tunnel assay 6 h after a sublethal dose of Jo-2 showing increased number of apoptotic bodies in the WT mice as compared to the ILK KO mice. Double arrow = 300 μm. B) Caspase 3/7 activation after a sublethal dose of Jo-2. C) Expression of various apoptotic and antiapoptotic proteins after a sublethal dose of Jo-2.

J Med Microbiol 2004,53(7):609–615 PubMedCrossRef 24 Sham PC, Cu

J Med Microbiol 2004,53(7):609–615.PubMedCrossRef 24. Sham PC, Curtis D: Monte Carlo tests for associations between disease and alleles at highly polymorphic loci. Ann Hum Genet 1995, 59:97–105.PubMedCrossRef 25. Finck-Barbancon V, Smad activation Goranson J, Zhu L, Sawa T, Wiener-Kronish JP, Fleszig SM, Wu C, Mende-Mueller L, Frank DW: ExoU expression by Pseudomonas aeruginosa correlates with acute cytotoxicity and epithelial injury. Mol Microbiol 1997, 25:547–557.PubMedCrossRef selleck screening library 26. Feltman H, Schulert G, Khan S, Jain M, Peterson L, Hauser AR: Prevalence of type III secretion genes in clinical and environmental

isolates of Pseudomonas aeruginosa. Microbiol. 2001,147(10):2659–2669. 27. Harrison EM, Carter ME, Luck S, Ou HY, He X, Deng Z, O’Callaghan C, Kadioglu A, Rajakumar K: Pathogenicity islands PAPI-1 and PAPI-2 contribute individually and synergistically to the virulence of Pseudomonas aeruginosa strain PA14. Infect Immun 2010,78(4):1437–1446. Epub 2010 Feb 1PubMedCrossRef 28. Hogardt M, Heesemann J: Adaptation of Pseudomonas aeruginosa during persistence in the cystic fibrosis

lung. Int J Med Microbiol. 2010,300(8):557–62.PubMedCrossRef 29. Lavenir R, Jocktane D, Laurent F, Nazaret S, Cournoyer B: Improved reliability of Pseudomonas aeruginosa PCR detection by the use of the species-specific ecfx gene target. J Microbiol Methods 2007,70(1):20–9.PubMedCrossRef 30. this website Parkinson H, Sarkans U, Kolesnikov N, Abeygunawardena N, Burdett T, Dylag M, Emam I, Farne A, Hastings E, Holloway E, Kurbatova N, Lukk M, Malone J, Mani R, Pilicheva E, Rustici

G, Sharma A, Williams E, Adamusiak T, Brandizi M, Sklyar N, Brazma A: ArrayExpress update – an archive of microarray and high-throughput sequencing-based functional genomics experiments. Nucl Acids Res 2011,39(Database issue):D1002-D1004.PubMedCrossRef 31. Ratnaningsih E, Dharmsthiti S, Krishnapillai V, Morgan A, Sinclair M, Holloway BW: A combined physical and genetic map of Pseudomonas Tangeritin aeruginosa PAO. J. Gen. Micro. 1990, 136:2351–2357.CrossRef 32. Tenover FC, Arbeit RD, Goering RV, Mickelsen PA, Murray BE, Persing DH, Swaminathan B: Interpreting chromosomal DNA Restriction Patterns Produced by pulsed-field gel electrophoresis: criteria for bacterial strain typing. Microbiology 1995,33(9):2233–2239. 33. Maatallah M, Cheriaa J, Backhrouf A, Iversen A, Grundmann H, Do T, Lanotte P, Mastouri M, Elghmati MS, Rojo F, Mejdi S, Giske CG: Population structure of Pseudomonas aeruginosa from five mediterranean countries: evidence for frequent recombination and epidemic occurrence of CC235. PLoS One 2011, 6:e25617.PubMedCrossRef 34. Curran B, Jonas D, Grundmann H, Pitt T, Dowson CG: Development of a multilocus sequence typing scheme for the opportunistic pathogen Pseudomonas aeruginosa. J Clin Microbiol 2004,42(12):5644–5649.PubMedCrossRef 35.

Diversity Indices Observed richness, Chao1 estimator, abundance-b

Diversity Indices Observed richness, Chao1 estimator, abundance-based coverage estimator CH5183284 (ACE), jackknife estimator, and bootstrap estimator were used to evaluate community richness. Community diversity was described using Shannon, non-parametric Shannon, and Simpson indices within Mothur v 1.5.0 [40]. Sampling coverage was calculated

using Good’s coverage for the given operational taxonomic unit (OTU) definition, while the Boneh estimate was used to calculate the number of additional OTUs that would be observed for an additional 500 SSU reads. The aforementioned rRNA diversity indices and rarefaction curves were calculated using Mothur v 1.5.0 program with default parameters [40] and calculations for each index can found in the Mothur manual (http://​www.​mothur.​org/​wiki/​Mothur_​manual). Functional diversity was assessed using SEED Subsystems [41], COG, and Pfam abundances from all available gut metagenomes. Diversity estimators used included Shannon-Weiner, Simpson’s lambda, and Pielou’s evenness analyses for measuring species richness and evenness. Functional diversity estimates, K- dominance plots, Principal Components Analysis, and clustering were performed using the PRIMER-E ecological software package [42]. Acknowledgements The

U.S. Environmental Protection Agency, through its Office of Research and Development, funded and managed, BMS-907351 molecular weight or partially funded and collaborated in, the research described herein. It has been subjected to the Agency’s administrative review and has been approved for external publication.

Any GF120918 supplier opinions expressed Fenbendazole in this paper are those of the author(s) and do not necessarily reflect the views of the Agency, therefore, no official endorsement should be inferred. Any mention of trade names or commercial products does not constitute endorsement or recommendation for use. This work was also partly funded by the United States Environmental Protection Agency Traineeship and National Science Foundation grant to DBO. Electronic supplementary material Additional file 1: Figures S1-S13. Fig. S1. Taxonomic distribution of viral sequences from swine feces. The percent of viral sequences retrieved from swine fecal GS20 (A) and FLX (B) metagenomes. Using the “”Phylogenetic Analysis”" tool within MG-RAST, the GS20 and FLX sequencing runs were searched against the SEED database using the BLASTx algorithm. The e-value cutoff for a hit to the database was 1×10-5 with a minimum alignment length of 30 bp. Fig. S2. Taxonomic distribution of bacterial orders from swine and other currently available gut microbiomes within MG-RAST. The percent of sequences assigned to each bacterial order from swine and other gut metagenomes is shown. Using the “”Phylogenetic Analysis”" tool within MG-RAST, each gut metagenome was searched against the RDP and greengenes databases using the BLASTn algorithm.

However, the lessons learned from the studies of other particulat

However, the lessons learned from the studies of other particulates (e.g., asbestos and fine particulates in air) suggested that early attention to the health effects in the context of epidemiologic studies should be considered as soon as possible [8]. In order to take preventive measures, EPZ015666 ic50 reduce and eliminate adverse effects on health, and provide a theoretical basis for the safety SB525334 mouse evaluation of nanomaterials, further research should consider epidemiological study to explore the association between nanomaterials and health effects. Acknowledgments This work was supported by the major national scientific research programs (grant no. 2011CB933404). References 1. Murashov V: Occupational

exposure to nanomedical applications. Wiley Interdiscip Rev Nanomed Nanobiotechnol 2009, 1:203–213.CrossRef 2. Schulte PA, Schubauer-Berigan MK, Mayweather C, Geraci CL, Zumwalde NVP-HSP990 price R, McKernan JL: Issues in the development of epidemiologic studies of workers exposed to engineered nanoparticles. J Occup Environ Med 2009, 51:323–335.CrossRef

3. Ayoub M, Ahmed N, Kalaji N, Charcosset C, Magdy A, Fessi H, Elaissari A: Study of the effect of formulation parameters/variables to control the nanoencapsulation of hydrophilic drug via double emulsion technique. J Biomed Nanotechnol 2011, 7:255–262.CrossRef 4. Menard A, Drobne D, Jemec A: Ecotoxicity of nanosized TiO 2 . Review of in vivo data. Environ Pollut 2011, 159:677–684.CrossRef 5. Boccuni F, Rondinone B, Petyx C, Iavicoli S: Potential occupational exposure to manufactured nanoparticles in Italy. J Clean Prod 2008, 16:949–956.CrossRef 6. Van Broekhuizen P, van Broekhuizen F, Cornelissen R, Reijnders L: Use of nanomaterials in the European construction industry and some occupational health aspects thereof. J Nanopart Res 2011, 13:447–462.CrossRef 7. Hougaard KS, Jackson Idoxuridine P, Jensen KA, Sloth JJ, Loeschner K, Larsen EH, Birkedal RK, Vibenholt

A, Boisen A-MZ, Wallin H, Vogel U: Effects of prenatal exposure to surface-coated nanosized titanium dioxide (UV-Titan). A study in mice. Part Fibre Toxicol 2010, 7:16.CrossRef 8. Laney AS, McCauley LA, Schubauer-Berigan MK: Workshop summary: epidemiologic design strategies for studies of nanomaterial workers. J Occup Environ Med 2011, 53:S87-S90.CrossRef 9. Vamanu CI, Cimpan MR, Hol PJ, Sornes S, Lie SA, Gjerdet NR: Induction of cell death by TiO 2 nanoparticles: studies on a human monoblastoid cell line. Toxicol Vitr 2008, 22:1689–1696.CrossRef 10. Karlsson HL, Gustafsson J, Cronholm P, Moller L: Size-dependent toxicity of metal oxide particles – a comparison between nano- and micrometer size. Toxicol Lett 2009, 188:112–118.CrossRef 11. Tedja R, Marquis C, Lim M, Amal R: Biological impacts of TiO 2 on human lung cell lines A549 and H1299: particle size distribution effects. J Nanopart Res 2011, 13:3801–3813.CrossRef 12.

Based on this trial, the U S FDA approved pemetrexed for second-

Based on this trial, the U.S. FDA approved pemetrexed for second-line treatment of locally advanced or metastatic NSCLC [6]. In our study, 53 patients were enrolled. All patients had experienced platinum-based chemotherapy. Most of patients CA3 cost (>70%) had good clinical conditions (ECOG PS 0 or 1). The patients treated with pemetrexed plus platinum were supplemented with dexamethasone, folic acid and vitamin B12. The addition of folic acid and

vitamin B12 supplementation markedly reduced the toxicity profile of pemetrexed, as shown in a previous trial comparing pemetrexed administered with or without vitamins [30]. The median number of cycles received was 3. No patient achieved CR. Seven of the 53 patients (13.2%) showed PR. The ORR (13.2%) is higher than that of single pemetrexed (8.8%) reported by Hanna et al. The stable disease rate was 67.9% in this study, which was markedly higher than that of single pemetrexed (45.8%) in Hanna’s study. The DCR for pemetrexed plus cisplatin/carboplatin selleck chemicals in this study and single pemetrexed in Hanna’s study were 81.1% and 54.6%, respectively, which also have a significant difference. The median progression-free survival was 6.0 months, which was two times longer than that of single pemetrexed (2.9 months) in Hanna’s study. The median OS time

was 10.0 months, which was also longer than that of single pemetrexed (8.3 months). The 1-year survival rate was 40.9%, which was higher than that of single pemetrexed (29.7%) in Hanna’s study. Compared with pemetrexed Ribonucleotide reductase single agent chemotherapy, our study showed that locally advanced or metastatic NSCLC patients having experienced platinum-based GSK126 research buy chemotherapy might acquire a higher objective response rate, higher disease control rate, longer PFS, longer OS and higher 1-year survival rate from pemetrexed combined with platinum chemotherapy. The main reason we achieved better results should be due to the addition of platinum chemotherapy drugs. Of course, to exclude the impact of

race factor, we need further randomized controlled study. In our study, the most frequent hematological toxicities were neutropenia and thrombocytopenia (any grade) and the most frequent nonhematological toxicities were nausea/vomiting, fatigue, pyrexia and rash (any grade). The incidence of grade 3/4 neutropenia and thrombocytopenia was 9.5% and 7.6%, which was higher than that of pemetrexed single agent chemotherapy in Hanna’s randomized phase III study (5.3% and 1.9%). The incidence of grade 3/4 Anemia was 0, which was 4.2% in that randomized phase III study. The nonhematological toxicities were similar to single pemetrexed observed in Hanna’s study. Although the incidence of neutropenia and thrombocytopenia in pemetrexed plus cisplatin/carboplatin chemotherapy for previously treated locally advanced or metastatic NSCLC patients was slightly higher than pemetrexed single chemotherapy, the adverse events were tolerable. After treated, all patients acquired recovery from hematological toxicities.

Anal Chem 2008, 80:4651–4658 CrossRef 29 Fologea D, Ledden B, Mc

Anal Chem 2008, 80:4651–4658.CrossRef 29. Fologea D, Ledden B, McNabb DS, Li J: Electrical characterization of signaling pathway protein molecules by a solid-state nanopore. Appl Phys Lett 2007, 91:539011.CrossRef 30. Hyun C, Kaur H, Rollings R, Xiao M, Li J: Threading immobilized DNA molecules through a LY3039478 solid-state nanopore at >100 μs per base rate. ACS Nano 2013, 7:5892–5900.CrossRef 31. Niedzwiecki DJ, Grazul J, Movileanu L: Single-molecule

observation of protein adsorption onto an inorganic surface. J Am Chem Soc 2010, 132:10816–10822.CrossRef 32. Sexton LT, Mukaibo H, Katira P, Hess H, Sherrill SA, Horne LP, Martin CR: An adsorption-based model for pulse duration in resistive-pulse protein sensing. J Am Chem Soc 2010, 132:6755–6763.CrossRef 33. Tsutsui M, He Y, Furuhashi M, Rahong S, Taniguchi M, Kawai T: Transverse electric field dragging of DNA in a nanochannel. Sci Rep 2012, 2:394. 34. Yeh LH, Fang KY, Hsu JP, Tseng S: Influence of boundary

on the effect of double-layer polarization and the electrophoretic behavior of soft biocolloids. Colloids Surf B: Biointerfaces 2011, 88:559–567.CrossRef 35. Wanunu M, Morrison W, Rabin Y, Grosberg AY, Meller A: Electrostatic focusing of unlabelled DNA into nanoscale pores using a salt gradient. Nat Nanotechnol 2010, 5:160–165.CrossRef selleck chemicals llc 36. Jiang DE, Jin Z, Wu J: Oscillation of capacitance inside nanopores. Nano Lett 2011, 11:5373–5377.CrossRef 37. Luan B, Stolovitzky G: An electro-hydrodynamics-based model for the ionic conductivity of solid-state nanopores during DNA translocation. Nanotechnology 2013, 24:195702.CrossRef Tideglusib 38. Kocer A, Tauk L, Dejardin P: Nanopore sensors: from hybrid to abiotic systems. Biosens Bioelectron 2012, 38:1–10.CrossRef 39. Liu L, Zhu LZ, Ni ZH, Chen YF: Detecting a single molecule using a micropore-nanopore hybrid chip. Nanoscale Res Lett 2013, 8:498.CrossRef 40. Liu Q, Wu H, Wu L, Xie X, Kong J, Ye X, Liu L: Voltage-driven translocation of DNA through

a high throughput conical solid-state nanopore. PLoS One 2012, 7:e46014.CrossRef 41. Hall AR, van Dorp S, Lemay SG, Dekker C: Electrophoretic force on a protein-coated DNA molecule in a solid-state nanopore. Nano Lett 2009, 9:4441–4445.CrossRef 42. Yusko EC, Johnson JM, Majd S, Prangkio P, Rollings RC, Li J, Yang J, Mayer M: Controlling protein translocation through nanopores with bio-inspired fluid walls. Nat Nanotechnol 2011, 6:253–260.CrossRef 43. Yeh LH, Zhang M, Qian S: Ion transport in a pH-regulated nanopore. Anal Chem 2013, 85:7527–7534.CrossRef 44. Gershow M, Golovchenko JA: Recapturing and trapping single molecules with a solid-state nanopore. Nat Nanotechnol 2007, 2:775–779.CrossRef 45. Smeets RMM, Keyser UF, Dekker NH, Dekker C: Noise in solid-state nanopores. PNAS 2008, 105:417–421.CrossRef 46.

The material porosity was 63% and was verified by using the well-

The material porosity was 63% and was verified by using the well-known three-weight measurement method. The average pore diameter was 6 nm (mesoporous material). The steady-state direct current (dc) method, described in detail in [18] and [21], was used to determine porous Si thermal conductivity. This method is based on the measurement of the temperature difference across a Pt resistor lying on the porous Si layer in response to an applied

heating power. A similar resistor on bulk crystalline Si served as a temperature reference. Figure  1 shows schematically the locally formed porous Si layer with the Pt resistor on top, while the second resistor on bulk Si is also depicted. Scanning electron microscopy buy Volasertib (SEM) images of Selleck CBL-0137 the specific porous Si material are also depicted in the same figure. The SEM image in the inset was obtained after a slight plasma etching of the porous Si surface in order to better reveal the porous Si structure. Figure 1 Schematic representation of the test structure.

The figure shows a schematic representation of the locally formed porous Si layer on the p-type wafer and SEM images of the porous Si surface. The SEM image in the inset of the principal one was obtained after a slight plasma etching of the porous Si surface in order to better reveal the porous structure. Two resistors, one on porous Si and one on bulk Si, are also depicted in the schematic of the test structure. Results and discussion For the extraction of the substrate thermal conductivity, a combination of experimental results and finite selleck kinase inhibitor element method (FEM) analysis was

used. The obtained results in the temperature range 5 to 20 K are depicted by full black circles in Figure  2 and in the inset of this figure. Plateau-like temperature dependence at a mean value of approximately 0.04 W/m.K was obtained. These results are the first in the literature in the 5 to 20 K temperature range. For the sake of completeness, our previous results for temperatures between 20 and 350 K are also presented in the same Amino acid figure by open rectangles. A monotonic increase of the thermal conductivity as a function of temperature is obtained for temperatures above 20 K and up to 350 K, without any maximum as that obtained, in the case of bulk crystalline Si. Figure 2 Temperature dependence of porous Si thermal conductivity. The graph shows experimental results of thermal conductivity of porous Si for temperatures between 5 and 20 K (present results, full points in the main figure and in the inset) and for temperatures in the range 20 to 350 K (open rectangles; previous results by the authors [18]). The plateau-like behavior for the 5 to 20 K temperature range is illustrated, with a mean value of 0.04 W/m.K.