This study was reviewed and approved by the ethics committee of the National Institute for Communicable Disease Control and Prevention, China CDC, according

to the medical research regulations of the National Health and Family Planning Commission of People’s Republic of China (permit number 2011-10-4). Acknowledgements This work was supported by grants from the National Basic Research Program of China (2011CB504901), the National Natural Science Foundation of China (81290340 and 81290345), the China Mega-Project for Infectious Disease (2013ZX10004-001 and 2012ZX10004-215), and the State Key Laboratory for Infectious Disease Prevention and Control (2012SKLID305). We appreciate Dr. Flemming Scheutz for helping us in FHPI Mocetinostat manufacturer stx subtyping and Dr. Mark Achtman for the support of MLST submission. Electronic supplementary material Additional file 1: Table S1: Antibiotic resistances of swine STEC isolates. (DOCX 163 KB) References 1. Nataro JP, Kaper JB: Diarrheagenic Escherichia coli . Clin Microbiol Rev 1998,11(1):142–201.PubMedCentralPubMed 2. Griffin PM, Tauxe RV: The epidemiology of infections caused by Escherichia coli O157:H7, other enterohemorrhagic E. coli, and the associated hemolytic uremic syndrome. Epidemiol Rev 1991, 13:60–98.PubMed 3. Bettelheim KA: The non-O157 shiga-toxigenic (verocytotoxigenic) Escherichia coli ; under-rated

pathogens. Crit Rev Microbiol 2007,33(1):67–87.PubMedCrossRef 4. Paton JC, Paton AW: Pathogenesis and diagnosis of Shiga toxin-producing Escherichia coli infections. Clin Microbiol Rev 1998,11(3):450–479.PubMedCentralPubMed 5. Savarino SJ, Fasano A, Watson J, Martin BM, Levine MM, Guandalini S, Farnesyltransferase Guerry P: Enteroaggregative Escherichia coli heat-stable enterotoxin 1 represents another subfamily of E. coli heat-stable toxin. Proc Natl Acad Sci USA 1993,90(7):3093–3097.PubMedCrossRef 6. Boyd EF, Hartl DL: Chromosomal regions specific to pathogenic isolates of Escherichia coli have a phylogenetically clustered distribution. J Bacteriol 1998,180(5):1159–1165.PubMedCentralPubMed

7. Cookson AL, Bennett J, Thomson-Carter F, Attwood GT: Molecular subtyping and genetic analysis of the enterohemolysin gene (ehxA) from Shiga toxin-producing Escherichia coli and atypical enteropathogenic E. coli. Appl Environ Microbiol 2007,73(20):6360–6369.check details PubMedCentralPubMedCrossRef 8. Batisson I, Guimond MP, Girard F, An H, Zhu C, Oswald E, Fairbrother JM, Jacques M, Harel J: Characterization of the novel factor paa involved in the early steps of the adhesion mechanism of attaching and effacing Escherichia coli . Infect Immun 2003,71(8):4516–4525.PubMedCentralPubMedCrossRef 9. Doughty S, Sloan J, Bennett-Wood V, Robertson M, Robins-Browne RM, Hartland EL: Identification of a novel fimbrial gene cluster related to long polar fimbriae in locus of enterocyte effacement-negative strains of enterohemorrhagic Escherichia coli . Infect Immun 2002,70(12):6761–6769.

Data represent the mean from three independent experiments, ± one standard deviation. Catabolic repression of aromatic compound degradation by TCA intermediates and glucose has been described in the β-proteobacterium Acidovorax sp. [29], and P. putida [15] respectively. In accordance

with these data we found that the PA catabolic pathway of B. selleck products cenocepacia K56-2 is subject to catabolic repression by glucose and succinate (Figure 3). Interestingly, P paaA is induced after 18 h of growth in SCFM probably as a result of the presence of phenylalanine (Figure 2). This observation is consistent with the recently reported B. cenocepacia global gene expression Selleck VS-4718 response to SCFM, which shows the induction of the PA catabolic pathway [30]. Whether this finding is relevant for pathogenesis of Bcc in Autophagy signaling pathway inhibitors the CF lung environment remains an unexplored point of interest. Conclusion We show that the PA gene promoters are responsive to PA, SCFM, and other compounds expected to proceed via the PA pathway. We also show the PA gene promoters are negatively regulated by PaaR, a TetR-type regulator, and are subjected to catabolic repression by succinate and glucose. Methods Bacterial strains, nematode strains and growth conditions Bacterial strains and plasmids are listed in Table 1. B. cenocepacia K56-2 was grown at 37°C in Luria Bertani (LB) or M9 minimal medium with 5 mM PA or 25 mM of the

indicated carbon sources, supplemented as required, with 100 μg/ml trimethoprim (Tp), Loperamide 50 μg/ml gentamicin (Gm) and 200 μg/ml chloramphenicol (Cm). E. coli was grown at 37°C in LB medium supplemented with 50 μg/ml Tp, 40 μg/ml kanamycin (Km) or 20 μg/ml Cm. Reporter

activity assays 96-well microplates containing 150 μl of M9 minimal media supplemented with indicated carbon source(s) were inoculated with 2 μl from an overnight culture grown in LB, washed with PBS and adjusted to an O.D. 600 of 2.0 with M9 minimal salts. 96-well microplates were incubated at 37°C with shaking at 200 rpm. eGFP protein has excitation/emission wavelengths of 488/509 [31]. Relative fluorescence, defined as the ratio between arbitrary fluorescence and optical density at 600 nm (O.D.600) was measured with a Biotek Synergy 2 plate reader, using excitation 485/20 and emission 528/20 filter sets. O.D. 600 values were converted to 1 cm path length O.D. 600 using a standard curve. Bioinformatics analysis BLAST searches of the genome sequence of B. cenocepacia strain J2315 were performed with the B. cenocepacia Blast Server at Sanger Institute http://​www.​sanger.​ac.​uk/​cgi-bin/​blast/​submitblast/​b_​cenocepacia. J2315 belongs to the same clonal lineage as strain K56-2 [32]. Gene clusters were visualized with Artemis software [33] and VectorNTI software (Invitrogen). PWM scores were calculated manually [25] (Additional file 2) as described by Hertz and Stormo [34] and Schnieder and Stephens [35]. Identification of binding sites using this PWM was achieved using the Target Explorer [36].

Leiber et al. (2005) discussed that changes in the ruminal ecosystem due to energy shortage or specific secondary plant metabolites may be possible causes for the high C18:3n-3 concentrations in alpine milk. Animals mix plant and biochemical diversity to enhance the nutritive value of the

diet as well as to maintain possible toxic concentrations of plants below critical levels (Provenza and Villalba 2010). Certain plants can also have health benefits for the animals. For example, legumes contain condensed tannins that may cause increased production of milk and wool, improve the lambing percentage and reduce bloating risk as well as intestinal parasites (Min et al. 2003). In addition, Martin et al. (2010) point out that adding tannin-rich legumes to animal

diets may decrease rumen methanogenesis and thus the production ASK inhibitor of the greenhouse gas methane. As reducing methane production during rumination also means decreasing energy losses by the animals, this is interesting from a production point of view as well. So far, the importance of diverse grasslands in this respect is not completely understood. Thus, despite unclear productivity effects, plant richness may have positive effects on product quality, animal health, nutrient and water retention as well as production stability. The latter may be especially important for sustainable production under changing TEW-7197 mw climatic conditions, but has so far mainly been studied in experimental plots. Livestock management to enhance grassland phytodiversity Extensive grazing has been suggested to be

a good means for enhancing and protecting grassland diversity (Dumont et al. 2007; Hart 2001; Loucougaray et al. 2004; Pykälä 2003; Rook et al. 2004; HAS1 Scimone et al. 2007; Tallowin et al. 2005). What is the advantage of grazers over mowing? How do the animals influence diversity over time and space? Grazing animals affect the distribution and occurrence of plants in several ways. Besides directly influencing competition between species, they also introduce more heterogeneity into the sward. The main mechanisms in this respect are selective grazing, nutrient redistribution, treading and seed distribution. As the complex actions of biting/defoliation/selection play the most important role in this process (Illius and Hodgson 1996), we will first concentrate on these before discussing the PLX3397 cell line influences of treading and excreta deposition and bringing this together in a discussion of livestock management for biodiversity. Selective grazing Selectively grazing animals preferrably feed on certain pasture areas (horizontal selection) or plant parts (vertical selection) (Arnold and Dudzinski 1978; Elsässer 2000). Given a free choice, they select a mixed diet rather than chosing one fodder species only (Villalba and Provenza 2009). The chosen biomass usually has higher concentrations of nitrogen, phosphorus and energy than avoided material (Wales et al. 1998).

The minor difference can be attributed to the different melting pathways (see Figure  4), which can be removed by employing much smaller ΔI for the microwire mesh with sacrifice of computational cost.

Figure 5 Variation of Z with n b in the melting process of both meshes. Generally, for the same material, T m, ρ, λ, and A are dependent on wire size, while S is dependent on mesh structure. For a given mesh structure with a known S, the find more smaller A results in smaller T m and λ but larger ρ, and therefore smaller I m according to Equation 10. This point is the same with the above numerical results where the I m of the microwire mesh is significantly higher than that of the nanowire mesh (see Figure  3a). Therefore, it is expected that the obtained melting behavior of the microwire mesh can be used to predict that of the wire mesh with same

structure at the same working selleck chemicals condition even if made from a different wire (i.e., different size, different material) through simple conversion with the known Z. Taking the Ag nanowire mesh as an example, the conversion process is summarized here. First, the melting current I m for the nanowire mesh can be calculated from Equation 10 with the known Z. Second, the variation of the R m for nanowire mesh can be calculated from that for the microwire mesh in Figure  3b as (11) because of the same melting process. Note that ‘|NW’ and ‘|MW’ indicate the case for the Ag nanowire mesh and Ag microwire mesh, respectively. Third, the variation of V m for the Ag nanowire mesh can be calculated by multiplying the obtained R m and I m

from the above two steps. The predicted melting behavior of the Ag nanowire mesh derived from the above indirect conversion is shown in Figure  6, which indicates good agreement with that obtained from direct numerical Fenbendazole simulation, and therefore validates the selleck inhibitor feasibility of the present conversion method. Figure  6 also gives the predicted melting behavior of the Al nanowire mesh with the same structure through indirect conversion. Obviously, the melting behavior of the mesh is largely dependent on the physical properties of the wire itself. Figure 6 Predicted melting behavior of Ag and Al nanowire meshes by conversion. It should be noted that the present boundary conditions and mesh structure are only one example. Certainly, boundary conditions and mesh structure will have great effect on the melting behavior of the wire mesh as well as physical properties of the wire itself. However, the consistent feature in the melting behavior among the wire meshes with the same structure under the same boundary conditions will not change. Therefore, the present findings can provide meaningful insight for the experimental investigation on the reliability of the metallic nanowire mesh-based TCE.

Only genes that showed differential expression at least by two-fold were incorporated in the results. Real-time PCR Genes were chosen randomly

HDAC inhibitor for real-time PCR analysis, and SYBR technology was used. Run protocol for the LightCycler was as follows: denaturation 95°C for 5 min; amplification and quantification repeated for 35 times: 95°C for 30 sec, 59°C for 30 sec and 72°C for 1 min with one fluorescence measurement followed by 72°C for 5 min and 4°C. Table 5 shows the sense and anti-sense plasmid. Table 5 Sense and antisense primers for real-time PCR Target Primers PCR product (bp) β-actin 5′-TGATGGTGGGCATGGGTCAGA-3′ 5′-CCCATGCCAATCTCATCTTGT-3′ 800 GRK4 5′-AATGTATGCCTGCAAAAAGC-3′ 5′-GATTGCCCAGGTTGTAAATG-3′ 235 DGKD 5′-CTCGGCTTACGGTTATTCCAG-3′ 5′-CCATCTCCATCTTCAGCCTCC-3′ 656 LCP2 5′-CACTGAGGAATGTGCCCTTTC-3′ 5′-GTGCCTCTTCCTCCTCATTGG-3′ 408 Complemented 2D6 mutant had similar results to the wild-type bacterium. Y = Yes; N = No The threshold cycle

(Ct) is defined as the fractional cycle number at which the fluorescence reaches 10× the standard deviation of the baseline and was quantified as described in User Bulletin #2 for ABI PRIMS 7700 sequence detection system (ABI). The fold change in gene expression was determined using an amplification-based strategy. For each Wnt pathway gene amplification, before calculating the fold change, the Ct values were normalized to the Ct of β-actin using the following formula: Quantitative analysis was performed using iCycler I software (BIORAD, Hercules, CA). A relative quantification

was used in which the expression levels of macrophage target genes were compared to data from a standard curve generated by amplifying several dilutions of a known quantity of amplicons. Real-time PCR efficiency was determined using a dilution series of cDNA template with a fixed concentration of the primers. Slopes calculated by the LightCycler software were used to calculate efficiency using the following formula: Phosphoglycerate kinase E = 10(-1/slope). These calculations indicated high real-time efficiency with a high linearity. Because expression of β-actin is constant, independent of conditions, target genes from both control and experimental groups were normalized to the expression level of the β-actin gene. Phagosome isolation and microscopy Phagosomes containing M. avium 109 and 2D6 mutant were isolated according to a protocol described previously [4], with minor modifications [11]. LCZ696 ic50 Briefly, infected macrophages were added to homogenization buffer and scraped from tissue culture flasks. The cells were lysed by approximately 30 passages through a tuberculin syringe (at least 90% of the cells were lysed), and the lysate was carefully deposited over a 12% to 15% sucrose gradient. The preparation was then centrifuged at 2000 rpm for 40 min at 4°C.

Therefore, the downregulation of TGF-β2 protein by miR-141 may be an important step in the excessive inflammation progression during influenza A virus infection, particularly in H5N1 infection. However, whether the recovery of TGF-β2 expression by anti-miR miR-141 inhibitor could resolve the hypercytokinemia SRT1720 supplier stage of H5N1 infection needs to be further studied. Although our findings were obtained from an in vitro model, we could apply these to the real situation of an in vivo model or tissue comprised of different cell types. In real bronchial environments, lung epithelial cells are the key target of influenza viruses [33, 34]. After these cells are infected, they will activate an

inflammatory cascade which launches a quick antimicrobial reaction and directs adaptive immunity to mount a protective response. Bronchial epithelial cells therefore modulate the activation of monocytes, macrophages,

dendritic cells (DC), and T lymphocytes through cytokines and chemokines. Cytokines and chemokines generally function in an autocrine (on the producing cell itself) or paracrine (on nearby cells) manner. These mediators will contribute to the generation of a specific bronchial homeostatic microenvironment that affects the way in which the body copes with the selleck compound library viruses. This homeostatic “circuit” can inhibit excessive inflammatory response in lung tissues [35]. For example, TGF-β Fossariinae had been reported to mediate a cross-talk between alveolar macrophages and epithelial cells [36]. However, our findings show that, during highly pathogenic H5N1 avian virus infection, miR-141 would be induced shortly after infection. With high level of miR-141, the expression of TGF-β would be suppressed from the lung epithelial cells. Without sufficient TGF- β, the pro-inflammatory

response might not be tightly controlled in cases of highly pathogenic H5N1 avian virus infection. This might explain the mechanism concerning bronchial infiltration of inflammatory cells, particularly lymphocytes and eosinophils, and the subsequent hyperresponsiveness of the bronchial wall induced by viral infection. Our study has some limitations that will need to be LXH254 order addressed in future studies. Firstly, we did not assess the roles of other miRNAs whose expression were also altered after infection. The miRNA microarrays that we used did not contain probes for every known miRNA; thus it is possible that influenza A virus infection affects the expression of some other miRNAs not yet covered by the kit used in the current study. Secondly, the virus may interact with miRNA regulatory pathways differently in other cell or tissue types, or in other physiological status. Conclusions In conclusion, based on the broad-catching miRNA microarray approach, we found that dysregulation of miRNA expression is mainly observed in highly pathogenic avian influenza infection.

The CMY region sequence is indicated in italics, and the duplicated sequences generated during the transposition events are highlighted in boldface. On the other hand, transconjugant IIIC10, positive for the six pX1 PCR markers and harboring a short version of the CMY region, was selected to determine the site of CMY insertion, using the same approach as for IC2. The cloning and sequencing of the CMY region showed that in this plasmid the CMY region was inserted into the stbE gene, which

is part of the stbDE operon coding for the toxin-antitoxin segregation selleck system of pX1 [13]. Based on this result, we designed primers to amplify the stbDE operon, and these were used along with the short CMY region primers to test the other pX1::CMY transconjugants (Figure 1C; PCRs J and K). Positive Selleck RG7420 results for pX1::CMY transconjugants IIIC10, IVD8 and IIE2 demonstrated the presence of the CMY-stbDE junction (Table 3). Careful revision of the sequences showed that the target site of insertion was nucleotide 26,431 and the signature left by the transposition event A-1210477 concentration was a five

bp repeat sequence (TTTTT) spanning from nucleotides 26,432 to 26,436 in the pOU1114 sequence annotation. In these short CMY regions the sugE ORF (441 pb) was truncated at nucleotide 367 (Figure 2B). The insertion site for pX1::CMY transconjugants IIC1 and IIIE4 could not be determined, despite several efforts carried out using the above mentioned approaches (Table 3). Restriction profiles for the eight pX1 transconjugant plasmids using BamHI-NcoI enzymes displayed marked differences in comparison with the profile of wild-type YU39 pX1 transformed into DH5α (DH5α-pX1; Figure 3). These differences could be related to distinct insertion sites of the CMY region and other re-arrangements within pX1 and await further studies. Figure 3 Representative restriction profiles for pX1 + CMY transconjugants. Double digestions with BamHI-NcoI were generated for the wild-type YU39 pX1 (DH5α-pX1) and representative Florfenicol transconjugant plasmids. The

nomenclature of the transconjugants is shown in Table 3. TheYU39 pX1 mobilized in cis the bla CMY-2-carrying pA/C to DH5α and few of the other recipient strains During the PCR screening of the pX1 transconjugants we discovered that all the pA/C transconjugants from DH5α were positive for the six pX1 markers. The few pA/C positive transconjugants from HB101 were also positive for the six pX1 markers, with the exception of transconjugant IIID8 which was positive only for oriX1 and ydgA (Table 4). In the SO1 recipient only pA/C positive transconjugants were obtained (Table 2); although the PCR screening for pX1 in the 34 transconjugants showed that only IIIA4 was positive (Table 2 and Table 4).

We adjusted urine samples to pH 7 with 1 M NaOH or 1 M HCl. We performed the LC/MS analyses through a Waters Acquity ultra-performance liquid chromatography (UPLC) system connected with a high performance Quattro Micro triple quadruple mass spectrometer designed for LC/MS-MS operation. We performed the analytical separations on the UPLC system using an Acquity UPLC BEH C18 1.7 μm column (1 × 100 mm) at a flow rate of 0.15 ml/min. We then moved the elutions from the UPLC column to the Quattro

Micro mass spectrometer. The ionization method used for MS analysis was Electrospray ionization (ESI) in both the positive ion (PI) and BKM120 price negative ion (NI) mode with an ESI-MS capillary voltage of 3.0 kV, an extractor cone voltage of 3 V, and a detector voltage www.selleckchem.com/products/lee011.html of 650 V. We performed the MS-MS in the multiple reaction monitoring (MRM) mode to produce structural information about the analytes by fragmenting the SN-38 clinical trial parent ions inside the mass spectrometer and identifying the resulting daughter/fragment

ions. We processed the resulting data and quantified the estrogen metabolites using the QuanLynx software (Waters). To calculate limits of detection, we injected various concentrations of the analytes to LC/MS-MS. The detection limit was considered to be the injected amount that resulted in a peak with a height at least two or three times higher than the baseline. The detection limits of 2-OHE1 and 16α-OHE1 were 18 fmol and 349 fmol, respectively. Intra-assay Progesterone coefficients of variation for 2-OHE1 and 16α-OHE1 were 3.2% and 3.0%, respectively. Inter-assay coefficients of variation were 1.9% and 3.5%, respectively. We had previously measured the intra- and inter-individual variability for 2-OHE1, 16α-OHE1 determinations and their ratio over a one year period [13]. The intra-class correlation coefficients (ICCs) and lower limit

of 95% CI (in parentheses) were 0.70 (0.46), 0.63 (0.35) and 0.78 (0.62), respectively. We had previously provided a detailed description of the procedures related to the reliability assessment [13]. Systematic Review We conducted a systematic search of the literature to identify additional studies published up to August 2009 which examined the association between estrogen metabolites and Pca risk using our standard methods [19–22]. We searched MEDLINE (January 1966 onwards) and EMBASE (January 1980 onwards). An expert librarian designed a search strategy combining terms for estrogens, estrogen metabolites and prostate specific antigen (PSA) with terms for Pca (available upon request). We screened titles and abstracts in duplicate using the following inclusion criteria: observational studies investigating prostate cancer risk in relation to estrogen metabolism. We included studies providing at least one measure of either urinary or circulating levels of 2-OHE1, 16α-OHE1 and the 2-OHE1 to 16α-OHE1 ratio.

Assessment of menstrual function during the intervention Menstrual function was monitored daily during the intervention selleckchem by assessing JQ1 order urinary excretion of E1G, PdG, and LH metabolites and the presence of menses as self-reported on monthly calendars. The methods used for the assessment and categorization of menstrual cycles are detailed and have previously been published [2]. Recovery of menstrual function categories To describe

the recovery of menstrual function, we classified recovery using several definitions of recovery that ranged in hormonal and clinical relevance. Recovery Category 1 was described simply as “recovery of menses.” The successful recovery of menses after the baseline period was defined as the first occurrence of menstrual bleeding during the intervention. For further analysis of the recovery of menstrual function, Recovery Category 2 was described as resumption of menses preceded by ovulation based on increases in urinary E1G (above 35 ng/ml), PdG (above 2.5 μg/ml), and mid-cycle LH (above 25 mIU/ml) concentrations [2, 14]. Recovery Category

3 was described as resumption of menses followed by at least 2 menstrual cycles of less than 36 days each. Anthropometrics Total body weight was measured by a digital scale during each week of the baseline period and every two weeks during GSK2245840 in vivo the intervention. Height was measured during the screening period, and BMI was calculated as a ratio of weight to height (kg/m2). Baseline values for body weight and BMI were reported as the average of all baseline and screening measurements. Eating behavior assessment Participants completed the Three Factor Eating Questionnaire (TFEQ) and Eating Disorder Inventory-2 (EDI-2) at screening and at months 2, 3, 6, 9, and 13 (post-study) to assess eating behavior. The TFEQ

is a 51-item questionnaire with three subscales – cognitive dietary restraint (CDR), disinhibition, and hunger. Cognitive dietary restraint from was evaluated according to the following ranges established by Stunkard and Messick [15]: 0–10 indicated low CDR, 11–13 indicated high CDR, and 14–21 indicated the clinical range. The EDI-2 is a 91-item questionnaire with 8 subscales and 3 provisional subscales, as previously reported [16]. Scores on the first 8 subscales were compared to published means and 95% confidence intervals of eating disorder patients and non-patient college females to assess for symptoms of disordered eating and associated psychological features [17]. Body composition and bone mineral density DXA scans of the total body, lumbar spine, and dual femur were performed to assess body composition and BMD. Body composition was measured at screening and baseline and during months 1, 2, 3, 6, 9, and 13 (post-study). BMD was assessed at all three sites at screening, month 6, and month 13 (post-study).

Nevertheless, the studies on the oxidation mechanisms of Si NWs have been focused mostly on the formation of thick oxide layers at relatively high temperatures and long times, overlooking the

early stages of oxidation which involve removal of surface functionalities and suboxides formation. In this article, thermal stability of hydrogen-terminated Si NWs of 85-nm average diameter was investigated by means of the surface-sensitive X-ray photoelectron spectroscopy (XPS) for a variety of temperatures and times. H-terminated surfaces are of importance since they are considered as the starting surfaces for further functionalization of Si NWs [11–15]. The different kinetic behavior for the three transient silicon suboxides and SiO2 has been Selleck Entinostat shown. Growth regimes were mainly addressed by four different phenomena including Si-Si backbond oxidation, surface bond propagation, suboxide growth site formation, and self-limited oxidant diffusion. A preliminary oxidation mechanism, elucidating the influence of time and temperature on the role of latter factors, is outlined. Methods Synthesis of initial Si NWs To produce Si NWs, the vapor–selleck products liquid-solid (VLS) technique for silane (SiH4) gas, assisted by gold (Au) as silane decomposition catalyst, was employed. Prior to the VLS process, the native oxides on substrates of Si(111)

have to be P-gp inhibitor removed through etching in diluted Casein kinase 1 HF. A thin gold layer of 2 nm in thickness was then sputtered on the etched substrates. After being transferred to the VLS operation chamber, the substrates were subjected to temperature and pressure of ≈580°C and ≈

5 × 10−7 mbar for 10 min, as to be annealed. Subsequently, to grow nanowires on the surface, temperature was reduced to ≈520°C and a gas mixture of 5 to 10 ccm (standard cm3 min−1) Ar and 5 ccm SiH4 was introduced for 20 min at a pressure ranging from 0.5 to 2 mbar. Si NWs hydrogen termination The grown Si NWs has to be treated on their surface. Si NW were first cleaned by N2(g) flow for several seconds and then exposed in a sequence to buffered HF solution (pH = 5) and NH4F (40% in water) for 30 to 50 s and 30 to −180 s, respectively. H-terminated Si NWs were rinsed by water for less than 10 s per side to prevent the oxidation and dried in N2(g) for 10 s. Oxide growth in Si NWs To evaluate the thermal stability of hydrogen atoms bonded to NWs’ surfaces and find dominant oxidation mechanisms, H-Si NWs were annealed at atmospheric condition in six distinct temperatures of 50°C, 75°C, 150°C, 200°C, 300°C, and 400°C, each for five different time-spans: 5, 10, 20, 30, and 60 min. The annealing and hydrogen-termination processes were gentle in the sense that they did not melt the Si NWs or change their diameters.