Each MG patient was matched by year of birth, sex and practice to

Each MG patient was matched by year of birth, sex and practice to up to six patients without a history of MG to generate a matched cohort. The index date of MG diagnosis was the date of the first record of MG after GPRD data collection had started. Each control patient was assigned

the same index date as his matched MG patient. The study patients were followed up from this index date to either the end of GPRD data collection, the date of transfer of the patient out of the practice area, the patient’s death or the occurrence of fracture, whichever came first. All types of fracture were included in the analyses and classified according to the International Classification of Diseases, Tenth Revision (ICD-10) categories (HES) and corresponding read codes (GPRD). A typical osteoporotic fracture was defined as a fracture of the radius/ulna, humerus, rib, femur/hip, pelvis or vertebrae (clinically symptomatic). Subsequently, #Selleck Belinostat randurls[1|1|,|CHEM1|]# this population was then divided into a group of probable MG cases (n = 834) with their matched controls and a group of possible MG cases (n = 232) with their matches controls. The following criteria were used to determine a probable MG case: a recording of MG in two different registries (GPRD and HES) (n = 205), or it has a recording of MG in at least one

registry with either a letter from a neurologist confirming the patient has seen a neurologist ever before or 1 year after the diagnostic code (n = 291), or a record of thymectomy (n = 48) any time during follow-up (recorded either

in GPRD or HES) or at least two prescriptions on different days of pyridostigmine, oral Epigenetics Compound Library high throughput glucocorticoids, azathioprine, methotrexate, ciclosporin or mycophenolate mofetil any time during enrolment (n = 754). Possible cases Resminostat were identified if they had a recording of MG in either GPRD or HES without the abovementioned prescription data, recording of thymectomy or a letter from a neurologist. Patients were excluded if they had a record of Lambert–Eaton type myasthenic syndrome, which mimics MG. Exposure The indicators of MG severity selected for the study were selected from the myasthenia gravis Foundation of America postintervention status that were also recorded in the GPRD [27]. Grade 1 included patients who did not use cholinesterase inhibitors or immunosuppressants during the past 6 months. Grade 2 included patients who used immunosuppressants, but not cholinesterase inhibitors during the past 6 months. Grade 3 included patients who used pyridostigmine only during the past 6 months (and no immunosupressants), and grade 4 included patients who had been on both immunosuppressants and cholinesterase inhibitors. MG severity grade may fluctuate over time. Potential confounders that were determined at baseline included body mass index (BMI), smoking status, alcohol status and occurrence of prior fractures.

5 and eGFR < 60 (Table 1) The parameters of histological evaluat

5 and eGFR < 60 (Table 1). The parameters of histological evaluation consisted of crescent formation and segmental/global glomerular sclerosis. Thus, histological severity was evaluated by the percentage of injured glomeruli in

the total number of glomeruli seen in renal biopsy. Histological grades (H-G I–IV) were defined as H-G I, <25 %; H-G II, 25–49.9 %; H-G III, 50–74.9 %; and H-G IV, ≥75 % (Table 2). Cellular and fibrocellular crescents were defined as acute lesions. Global/segmental glomerulosclerosis or fibrous crescents were defined as chronic lesions. From the clinical and histological grading, Tariquidar cell line dialysis induction risks were stratified and classified as low, moderate, high and very high click here risk groups as shown in Table 3. Treatment protocol The 208 patients

in this study were divided into 4 groups based on the treatment regimens as follows: (1) tonsillectomy alone (T group), (2) tonsillectomy followed by 40 mg/day of oral prednisolone (PSL) which was gradually tapered over 2 years (TOS group), (3) tonsillectomy plus steroid pulse of intravenous methylprednisolone 500 mg/day for 3 consecutive days, generally for 4 courses every 2 months which was discontinued at 3 courses if urinary findings showed remission, followed by oral PSL at an initial dose of 20 mg/day (TSP group), and (4) no particular therapy, in which patients received neither tonsillectomy nor steroid therapy (N group). All patients were given an antiplatelet agent, antithrombotic drugs, and antihypertensive agents according to the discretion of the physician. Among

all groups, the use of ACEIs or ARBs was defined as >6 months. Statistical analysis The endpoint PF-573228 price of renal survival was set as doubled creatinine levels compared with values at the time of renal biopsy. Cox’s proportional hazards model was used to explore the multiple covariates for renal survival. All continuous variables are presented as mean ± SD. Baseline clinical data among the groups were compared using the Kruskal–Wallis test, unpaired t test, and Mann–Whitney U test as appropriate for continuous data, and the Chi-squared statistic for categorical data. Cox’s regression proportional hazards model was used to estimate the relative risks associated with the baseline covariates of gender, Thiamet G age, histological activity, the dialysis induction risk, therapeutics, and the use of ACEIs or ARBs. A backward stepwise method was used to select the significant covariates. P < 0.05 was used to reject the null hypothesis of no statistical difference between-groups. For the comparison of four groups, Dunn’s test was performed. A P value < 0.0083 was considered statistically significant, as indicated by asterisks in the tables. All of the analyses were made using SPSS statistical software for Windows, release Ver.18. Results Study population The clinical features of the patients are shown in Table 4. The mean duration of follow up was 88.

The counties bordered in yellow in Texas indicate counties where

The counties bordered in yellow in Texas indicate counties where documented incidents of anthrax have occurred between 1974 and 2000. The numbers 1–4 indicate the counties in which the original Ames strain, 2 bovine samples and a goat sample have been analyzed by current genotyping methods as belonging to the Ames sub-lineage. The molecular analysis of more than 200 isolates from North and South Dakota indicates a pre-dominance of the sub-lineage WNA in this region. The gray colors indicate moderate to sparse outbreaks in the States adjoining the Dakotas

Proteasome inhibitor and Texas. An important feature of the outbreaks in Texas is that the “”modern”" outbreaks have occurred repeatedly in many of the same counties depicted in this historical map (Figure 6 and USDA Report: Epizootiology and Ecology of Anthrax: http://​www.​aphis.​usda.​gov/​vs/​ceah/​cei/​taf/​emerginganimalhe​althissues_​files/​anthrax.​pdf). A culture-confirmed study between 1974–2000 indicated that 179 isolates were spread across 39 Texas counties (counties outlined in yellow) that are in general agreement with the dispersal patterns observed in the early national surveys depicted in Figure 6. The one significant difference is a shift from the

selleck screening library historical outbreaks in the coastal regions to counties more central and southwesterly in “”modern”" times. Similarly, culture-confirmed isolates from a 2001 outbreak in Val Verde, Edwards, Real, Kinney and Uvalde counties in southwest Texas are similar to outbreaks in 2006 and 2007 when 4 Ames-like isolates were recovered from Real, Kinney, and Uvalde county [9]. It appears that B. anthracis was introduced into the Gulf Coast, probably by early European

settlers or traders through New Orleans and/or Galveston during the early to mid 1800s. The disease became established along the coastal regions and then became endemic to the regions of Texas where cattle and other susceptible animals are currently farmed. Are these B. anthracis, Ames-like genotypes from the Big Bend region (Real, Kinney, Uvalde counties) of Texas representative of Adenosine triphosphate the ancestral isolates brought to the Gulf Coast? Van Ert et al. [5] used synonymous SNP surveys to estimate the divergence times between the major groups of B. anthracis and these estimates suggest that the this website Western North American and the Ames lineages shared common ancestors between 2,825 and 5,651 years ago. Extrapolating to the much shorter SNP distances between the most recent Chinese isolate (A0728) and the recent Texas isolates on the Ames sub-lineage would approximate that these two shared a common ancestor between 145 to 290 years ago. These estimates would be consistent with the hypothesis that an Ames-like isolate was introduced into the Galveston and/or New Orleans area in the early to middle 1800s.

The second-strand cDNA was

synthesized with DNA polymeras

The second-strand cDNA was

synthesized with DNA polymerase I. Short fragments were purified with QiaQuick PCR extraction kit (Qiagen), and then were sequenced under the Illumina HiSeq™ 2000 platform at Shenzhen BGI. The full sequencing technical details can be inspected in the services of BGI (http://​www.​genomics.​cn). This yielded approximately six million 90-bp pair-end reads for each sample (Table 1). Then pair-end reads were mapped to the Prochlorococcus MED4 genome (accession number: NC_005072) using Bowtie2 [60] with at most one mismatch. The coverage of each nucleotide was calculated by counting the click here number of reads mapped at corresponding nucleotide learn more positions in the genome. The number of reads that were perfectly mapped to a gene region was calculated using BEDTools [61], and then it was normalized by gene length and total mapped CB-839 order reads, namely RPKM as the gene expression value [26]. The gene annotations for Prochlorococcus MED4 were downloaded from MicrobesOnline [62] with modifications for non-annotated

genes that were designated “HyPMM#”. New ORFs identified in this study were annotated with “TibPMM#” (Sheet 2 of Additional file 3). Sequences generated by this study are available in the Gene Expression Omnibus (GEO) under accession number GSE49517. Identification of operons and UTRs Using a priori knowledge of the translation start and stop site from Additional file 3, the coverage of ORF upstream and downstream regions was scanned to identify a point of sharp coverage

decline. To define the boundary, we applied criteria modified from Vijayan et al.[24]. Briefly, a transcript’s boundary (translation start or stop site was defined as i = 0, and “i + 1” is the upstream or downstream of position “i”) was defined when position “i” satisfied one of the following three criteria: (1) coverage(i)/coverage(i + 1) ≥ 2, binomialcdf (coverage(i + 1), coverage(i) + coverage(i + 1), 0.5) < 0.01 and coverage(i + 1) > coverage(i:(i-89))/(90 × 7); (2) Tolmetin coverage(i)/coverage(i + 1) ≥ 5 or coverage(i)/coverage(i + 2) ≥ 5, and coverage(i + 1) < coverage(i:(i-89))/(90 × 7); (3) coverage(i + 1) ≤ background. Where binomialcdf (x, n, p) is the probability of observing up to x successes in n independent trials when success probability for each trial is p. We assumed reads were uniformly distributed on position “i” and “i + 1” (p = 0.5). If a sharp coverage reduction occurred, coverage(i + 1) would be much smaller than coverage(i); that was, the success of coverage(i + 1) became a small probability event in the events of all reads mapped to “i” and “i + 1” (binomialcdf < 0.01). The strictest criterion (1) was used for highly transcribed genes.

Table 2 Cell surface hydrophobicity of Lactococcus strains Lactoc

Table 2 Cell surface hydrophobicity of Lactococcus strains Lactococcus Strain Actual Value† Hydrophobicity Index‡ L. lactis 1363 WT 59.7 ± 7.2 100 L. lactis 1363::pJRS525 56.6 ± 5.5 98 L. lactis 1363::pSl230 82.0 ± 2.6 **137 † Actual hydrophobicity values were calculated based on hexadecane binding as described in Methods. Values are representative of three separate experiments with ten replicates ± SD ‡ Hydrophobicity Index represents the ration of actual hydrophobicity value for each strain to that of the isogenic wild-type (WT) strain multiplied by 100 ** Asterisks denote a statistically significant difference of Δscl1 mutants versus

WTs at P ≤ CBL0137 datasheet 0.001 Discussion Group A Streptococcus strains vary because of the vast number of M-protein types, and this variation is associated with varying frequency of isolation and exacerbation of disease [40, 41]. The M41-, M28-, M3-, and M1-type strains selected for the current study represent a significant intraspecies diversity among clinical Selleck XAV-939 isolates of GAS. M41 GAS was a major causative agent of superficial skin infections [42–44], and strain MGAS6183, harboring the Scl1.41 protein, has been studied extensively [19, 21, 22]. M28-type GAS (strain MGAS6143) has historically been associated with puerperal fever and currently is responsible for extensive human infections world-wide [45]. M1T1 GAS, represented

by strain MGAS5005, is a globally disseminated clone responsible for both pharyngitis and invasive infections [46–48]. The M3-type strains of GAS cause a disproportionally large number of invasive GAS infections PLEKHM2 that are responsible for traumatic morbidity and death [49, 50]. Initial studies by Lembke et al. that characterized biofilm formation among various M types of GAS typically included several strains of the same M type [1, 28]. These studies reported a significant strain-to-strain variation in ability to form biofilms within each M type. Studies that followed compared biofilm formation by defined isogenic WT and mutant strains to assess the

contribution of specific GAS surface components responsible for a biofilm phenotype, including M and M-like proteins, hyaluronic acid capsule, lipoteichoic acid, and pili [12, 13]. In the current study, we have assessed the role and contribution of the surface protein Scl1 in the ability to support biofilm formation by GAS strains of four distinct M types. Recent Z-IETD-FMK mouse advances in molecular mega- and pathogenomics has enabled the characterization of numerous M3-type strains with a single nucleotide resolution [51, 52]. Interestingly, all five M3-type strains MGAS158, 274, 315, 335, and 1313 that were originally used for scl1-gene sequencing [14], plus an additional strain MGAS2079 (not reported) harbor the same scl1.

The impact of the use of multiple risk indicators for fracture on

The impact of the use of multiple risk indicators for fracture on case-finding strategies: a mathematical approach. Osteoporos Int 2005 Mar; 16(3): 313–8PubMedCrossRef 13. González Macías J, Guañabens Gay N, Gómez Alonso C, et al. Guías de práctica clínica en la osteoporosis posmenopáusica, glucocorticoidea y del varón. R788 molecular weight Sociedad Española De Investigación Ósea Y Del Metabolismo Mineral. Rev Clin Esp 2008 May; 208 (Suppl. 1): 1–24CrossRef 14. Watts NB, Bilezikian JP, Camacho PM, et al. American Association of Clinical Endocrinologists medical guidelines

for clinical practice for the diagnosis and treatment of postmenopausal osteoporosis: executive summary of recommendations. Endocr Pract 2010 Nov–Dec; 16(6): 1016–9PubMedCrossRef 15. Papaioannou A, Morin S, Cheung AM, et al. 2010 clinical practice guidelines for the diagnosis and management of osteoporosis in Canada: summary. CMAJ 2010 Nov 23; 182(17): 1864–73PubMedCrossRef 16. Compston J, Cooper A, Cooper C, selleck chemical et al. Guidelines for the diagnosis and management of osteoporosis in postmenopausal women and men from the age of 50 years in the UK. Maturitas 2009 Feb 20; 62(2): 105–8PubMedCrossRef 17. Kanis JA, Burlet N, Cooper C, et al. European guidance for the diagnosis and management of osteoporosis in postmenopausal women. Osteoporos Int

2008 Apr; 19(4): 399–428PubMedCrossRef 18. Kanis JA, Torgerson D, Cooper C. Comparison of the European and USA practice guidelines for osteoporosis. Trends Endocrinol Metab 2000 Jan–Feb; 11(1): 28–32PubMedCrossRef

19. Vos E. Osteoporosis guidelines AR-13324 order miss big picture. CMAJ 2011 Apr 5; 183(6): 695PubMed 20. Crabtree NJ, Bebbington NA, Chapman DM, et al. Impact of UK national guidelines based Cell press on FRAX®—comparison with current clinical practice. Clin Endocrinol (Oxf) 2010 Oct; 73(4): 452–6 21. Jódar Gimeno E. Conclusiones consensuadas del I Foro Multidisciplinar en el Manejo del Paciente con Alto Riesgo de Fractura (ARF) Osteoporótica. Rev Osteoporos Metab Miner 2010 Jul; 2(2): 79–86 [online]. Available from URL: http://​www.​revistadeosteopo​rosisymetabolism​omineral.​com/​pdf/​articulos/​1201002020079008​6.​pdf [Accessed 2012 Nov 15] 22. Hosking D, Alonso CG, Brandi ML. Management of osteoporosis with PTH: treatment and prescription patterns in Europe. Curr Med Res Opin 2009 Jan; 25(1): 263–70PubMedCrossRef 23. Jódar-Gimeno E. Full length parathyroid hormone (1–84) in the treatment of osteoporosis in postmenopausal women. Clin Interv Aging 2007; 2(1): 163–74PubMedCrossRef 24. Gil VF, Belda J, Munoz C, et al. Validity of four indirect methods which evaluate therapeutic compliance for arterial hypertension. Rev Clin Esp 1993 Nov; 193(7): 363–7PubMed 25. Appraisal of Guidelines, Research, and Evaluation in Europe (AGREE) Collaborative Group. Guideline development in Europe: an international comparison. Int J Technol Assess Health Care 2000 Autumn; 16(4): 1039–49CrossRef 26. AGREE Collaboration.

The percentage of 15N in the labeled media is more than 98% (Sila

The percentage of 15N in the labeled media is more than 98% (Silantes GmbH, München, Germany). The cultures were inoculated with a starter culture grown in normal (14N) or 15N-labeled media until

mid-log phase. Two hundred fifty milliliter culture medium was inoculated with each starter VRT752271 order culture and grown at 37°C with shaking at 225 rpm for 4 h. 15N-labeled culture was treated with 5 mM H2O2, which is well below the minimal inhibition concentration (MIC) of SE2472 (20 mM), and both cultures were grown for 2 h following the addition of H2O2. Protein extraction was performed with B-PER® CYT387 bacterial protein extraction reagent (Thermo Fisher Scientific, Rockford, IL) and quantified with Dc Protein Assay Kit (Bio-Rad, Hercules, CA), which has an error rate Selleckchem WZB117 of 2.5% in our experiments. We took this error rate into consideration by classifying any protein that had a 5% change or less as unchanged (having a 0% change). Two-dimensional gel electrophoresis and visualization of bacterial

proteins Protein samples were further solubilized in rehydration buffer (8 M urea, 2% CHAPS, 50 mM DTT, 0.2% Bio-Lyte® 3/10 ampholytes [Bio-Rad, Hercules, CA] and trace amount of Bromophenol Blue). ReadyStrip™ IPG strips (Bio-Rad, Hercules, CA) were loaded with 200 μg of protein samples (either normal or 1:1 mixture of normal and 15N-labeled samples) for preparative 2 D gels, and allowed to rehydrate for 18-22 h. Isoelectric focusing (IEF) was performed at 20°C using PROTEAN® IEF cell (Bio-Rad, Hercules,

CA). A 3-step protocol (250 V-20 min/8,000 V-2.5 h/8,000 V-10,000 V.h) was used for the IEF procedure following manufacturer’s recommendations (Bio-Rad, Hercules, CA). After the IEF procedure, the IPG strips were reduced in Equilibration Buffer I (6 M urea, 2% SDS, http://www.selleck.co.jp/products/erastin.html 0.375 M Tris-HCl [pH 8.8], 20% glycerol, 2% DTT) and alkylated in Equilibration Buffer II (6 M urea, 2% SDS, 0.375 M Tris-HCl [pH 8.8], 20% glycerol, 0.25% iodoacetamide). Strips were loaded onto 8-16% Criterion™ Tris-HCl SDS gel (Bio-Rad, Hercules, CA) and electrophoresed at 200 V for 65 min. Gels were visualized using Coomassie Brilliant Blue R-250 or silver staining (Invitrogen, Carlsbad, CA). Mass spectrometric identification of proteins Gels were scanned and protein spots of interest were excised using the Xcise automated gel processor (Proteome Systems, North Ryde, Australia). Gel spots were destained and washed, followed by in-gel tryptic digestion using proteomic grade trypsin (Sigma-Aldrich, St. Louis, MO). Peptide fragments were collected and purified using ZipTip™ C18 reverse-phase prepacked resin (Millipore, Billerica, MA) and mixed with an equal volume of 10 mg/ml α-cyano-4-hydroxy-trans-cinnamic acid (Sigma-Aldrich, St. Louis, MO) in 0.1% trifluoroacetic acid (TFA)/50% acetonitrile solution and directly spotted onto a stainless steel target plate for mass analysis.

Nevertheless, further analysis showed that two or more amplificat

Nevertheless, further analysis showed that two or more amplification in triplicate reactions is a reliable indicator of positive fungal DNA detection, irrespective of Ct-value(s) obtained (Table 5). These results held for both of the reaction volumes tested. We also calculated the false negative rate for FungiQuant using the sensitivity associated with 1.8 copies of positive target, a template concentration that provided relatively poor determination.

Using a threshold of ≤ 1 positive amplification used for rejecting triplicate results as noise, we determined that the false negative rate could be as high as 80% for samples containing ≤ 1.8 copies when 10 μl reactions are used, and even higher at 87% for samples analyzed using 5 μl reactions. click here We found that the false negative rate decreased significantly for samples containing 10 and 5 copies, with false negative rates ranging from 0.0% to 0.1%. We also wanted to determine the utility of Ct-values for delineating true detection

in low concentration samples from noise. The means and medians of the Ct-values from amplified wells in the LOD experiments are shown in Additional file 1: Table S3. The medians of the 10 copies and 5 copies samples in 10 μl reaction were statistically lower than water-only or human-only samples. However, the 1.8 copy samples did not have a median value that could be discriminated from the negative control distributions in either reaction volume, despite the approximately one cycle earlier amplifications Selleckchem CBL-0137 observed for 5 and 10 copies in 5 μl reactions. Given these results, and the distribution of the Ct-values from each condition GSK690693 in vitro tested, we determined the Ct-values for ≥ 5 copies template (Additional file 8: Figure S4). Based on this, we further determined D-malate dehydrogenase that a one standard deviation cutoff could be used to remove outlying values from a set of triplicate test result. The Ct-value distribution also supports an averaging approach of non-outlying quantified values to determine the best estimate

of the true Ct-value using the FungiQuant triplicates in analysis. Discussion In the current manuscript, we present our design and validation of FungiQuant, a broad-coverage TaqMan® qPCR assay for quantifying total fungal load and reproducibly detecting 5 copies of the fungal 18S rRNA gene using triplicate 10 μl reactions. The in silico analysis was an important component of our validation of FungiQuant against diverse fungal sequence types, even though sequence matching is not a perfect predictor of laboratory performance [38]. Many factors are known to affect reaction efficiency, such as oligonucleotide thermodynamics, the type of PCR master mix used, and the template DNA extraction method. Thus, given the range of FungiQuant reaction efficiency against different fungal species, we expect FungiQuant to be more accurate in longitudinal than cross-sectional studies.

The infection activity of ϕSpn_200 was tested on the pneumococcal

The infection activity of ϕSpn_200 was tested on the pneumococcal strain Rx1 [59]. Results obtained demonstrated that ϕSpn_200 induced the formation of lysis plaques click here on the Rx1 culture plates (Additional file 5). Conclusions The number of sequences of bacterial genomes has been rapidly increasing in the last years thanks to the use of new technologies, such as the high-throughput Roche 454 pyrosequencing [60, 61]. S. pneumoniae serotype 11A is

becoming an emergent serotype in the post-PCV7 era and data concerning its genetic characteristics can be of importance for future vaccines. The reasons determining the increase in the incidence of pneumococcal infections due to non vaccine-serotypes, including serotype 11A, are complex and not yet fully understood. Multiple factors could take part in this phenomenon, such as geographical and temporal trends, the prevalence of these serotypes in the community, the ability to evade host defenses, the acquisition of new genetic material that could potentially increase their invasive capacity or their resistance to antibiotics [62]. In this study, the entire genomic sequence

of S. pneumoniae AP200, belonging to serotype 11A and ST62, has been obtained. EGFR phosphorylation Sequence analysis revealed chromosomal rearrangements and horizontal gene transfers. A large chromosomal inversion across the replication axis was found: it is likely that this inversion

originated to maintain the genome stability affected by horizontal gene transfer events, as suggested by Ding et al. [28]. The presence of large genomic inversions is a phenomenon observed in other streptococcal species, where it could contribute to generate chromosomal shuffling and create novel genetic pools [63–65]. Horizontal gene transfer events involved mainly two mobile elements, the erm(TR)-carrying genetic GSK2126458 molecular weight element Tn1806 and the functional prophage ϕSpn_200. The modular organization recognized inside the two exogenous elements, and their similarity to other elements of different bacterial species, confirm that they have undergone frequent DNA exchanging events, that appear to be the major contributors to the overall diversity of the genome of S. pneumoniae AP200. Although the availability of complete pneumococcal Olopatadine genomes cannot provide a full explanation for the evolution and spread of a particular serotype or clone, it can contribute information on the pathogenic potential of this important microorganism. Regarding AP200, the presence of pilus islet 2 could confer a selective fitness advantage, mediating adherence to the nasopharingeal epithelium and could represent a target for future vaccines [24, 38]. In addition, the presence of the transposon Tn1806, conferring erythromycin-resistance, is an advantage to the microorganism in view of the large use of macrolides in the community.

Acta Mater 2008, 56:2929–2936 CrossRef 5 Hu N, Karube Y, Arai M,

Acta Mater 2008, 56:2929–2936.CrossRef 5. Hu N, Karube Y, Arai M, Watanabe T, Yan C,

Li Y, Liu Y, Fukunaga H: Investigation on sensitivity of a polymer/carbon selleck inhibitor nanotube composite strain sensor. Carbon 2010, 48:680–687.CrossRef 6. Seidel GD, Stephens SN: Analytical and computational micromechanics analysis of the effects of interphase regions on the effective coefficient of thermal expansion of carbon nanotube-polymer nanocomposites. In Proceedings of the KPT-8602 solubility dmso 51st AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference: April 12–15 2010; Orlando. Reston: AIAA; 2010:2010–2809. 7. Wei C: Thermal expansion and diffusion coefficients of carbon nanotube-polymer composites. Nano Lett 2002, 2:647–650.CrossRef 8. Hu N, Fukunaga H, Lu C, Kameyama M, Yan B: Prediction of elastic properties of carbon nanotube-reinforced composites. Proc R Soc Lond A Math Phys Sci 2005, 461:1685–1710.CrossRef 9. Hu B, Hu N, Li Y, Akagi K,

Yuan W, Watanabe T, Cai Y: Multi-scale numerical simulations on piezoresistivity of CNT/polymer nanocomposites. Nanoscale Res Lett 2012, 7:402.CrossRef 10. Clancy TC, Frankland SJV, Hinkley JA, Gates TS: Multiscale modeling of thermal conductivity of polymer/carbon nanocomposites. Int J Therm Sci 2010, 49:1555–1560.CrossRef 11. Park C, Wilkinson J, Banda S, Ounaies Z, Wise KE, Sauti Selleckchem INK1197 G, Lillehei PT, Harrison JS: Aligned single wall carbon nanotube polymer composites using an electric field. J Polym Sci, Part B: Polym Phys 2006, 44:1751–1762.CrossRef 12. Okabe T, Motani T, Nishikawa M, Hashimoto M: Numerical simulation of microscopic damage and strength of fiber-reinforced plastic composites. Adv Compos Mater 2012, 21:147–163.CrossRef 13. Huang H, Talreja R: Numerical simulation of matrix micro-cracking in short fiber reinforced polymer composites: initiation and propagation. Compos Sci Technol 2006, 66:2743–2757.CrossRef 14. Alamusi , Hu N, Jia B, Arai M, Yan C, Li J, Liu Y, Atobe S, Fukunaga H: Prediction of thermal expansion properties of carbon nanotubes using molecular dynamics simulations.

Comput Mater Sci 2012, 54:249–254.CrossRef 15. Yamamoto G, Liu S, Hu N, Hashida T, Liu Y, Yan C, Li Y, Cui H, Ning H, Wu L: Prediction of pull-out force of multi-walled carbon nanotube (MWCNT) in sword-in-sheath mode. Comput Mater Sci 2012, 60:607–612.CrossRef 16. Hu N, Fukunaga H, Lu C, Kameyama M, Yan B: Prediction of Tryptophan synthase elastic properties of carbon nanotube-reinforced composites. Proc R Soc A 2005, 461:1685–1710.CrossRef 17. Hu N, Wang B, Tan GW, Yao ZH, Yuan W: Effective elastic properties of 2-D solids with circular holes: numerical simulations. Compos Sci Technol 2000, 60:1811–1823.CrossRef 18. Wang YQ, Zhang MD, Zhou BL, Shi CX: A theoretical model of composite thermal expansion. Mater Sci Prog 1989, 3:442–446. 19. Hu N, Masuda Z, Yamamoto G, Fukunaga H, Hashida T, Qiu J: Effect of fabrication process on electrical properties of polymer/multi-wall carbon nanotube nanocomposites. Composites: Part A 2008, 39:893–903.