The 16S rRNA gene was amplified using bacterial universal primers specific to the 16S rRNA gene (primers 9F and 1510R). The PCR product was sequenced using a BigDye Terminator v3.1 cycle sequencing kit (Applied Biosystems) and the DNA sequencer ABI PRISM 3130xl Genetic Analyzer (Applied Biosystems).

The primers 9F, 785F, 802R, and 1510R were used in the gene sequencing reaction learn more (Nakagawa & Kawasaki, 2001). Alignments were carried out using the clustal w tool in mega version 5.0 (Tamura et al., 2011). Phylogenetic trees were generated by the neighbor-joining (Saitou & Nei, 1987), maximum-parsimony (Fitch, 1971), and maximum-likelihood (Felsenstein, 1981) methods in mega version 5.0. The distance matrix was produced on the basis of Kimura’s two-parameter model (Kimura, 1980), and the topologies of the resultant trees were evaluated using bootstrap analysis (Felsenstein, 1985) of 1000 replicates. Sequence similarity values were calculated using genetyx-mac version 16 (Genetyx Corporation). The cell morphology of strain KU41ET was examined selleck chemical under a transmission electron microscope (JEM-2000EX; JEOL) (Fig. 1). Motility was examined on a semisolid

MB medium. Gram staining was performed using a Favor-G kit (Nissui), and the cells were observed under a light microscope (BX50F4; Olympus). Catalase and oxidase tests were performed as described by Barrow & Feltham (1993). Growth was tested at 25 °C Carnitine dehydrogenase on MA unless otherwise stated. Salinity requirements were tested using modified MA supplemented

with 0–6% (w/v) NaCl. The pH range for growth was determined on MA, and the pH was adjusted to 5.0–10.0. Susceptibility to antibiotics was determined by the diffusion method, using antibiotic disks (Nissui). Briefly, 100 μL of the bacterial suspension (0.5 McFarland standard) was plated onto MA plates and incubated for 3 days. The following antibiotics were tested: ampicillin (10 μg), chloramphenicol (30 μg), gentamicin (10 μg), kanamycin (30 μg), lincomycin (2 μg), nalidixic acid (30 μg), novobiocin (30 μg), penicillin G (10 U), polymyxin B (300 U), streptomycin (10 μg), and tetracycline (30 μg). Any sign of growth inhibition was scored as sensitivity to that antibiotic, and resistance to an antibiotic was indicated by the absence of an inhibition zone. Nitrate reduction; indole production; acid production from glucose (fermentation); hydrolysis of esculin and gelatin; and the presence of arginine dihydrolase, urease, and β-galactosidase was tested using the API 20NE (bioMérieux) according to the manufacturer’s instructions, but the cell suspensions were prepared using Daigo’s IMK-SP. The results were read after 48 h of incubation at 25 °C. Hydrolysis of starch, Tween 40, and Tween 80 was tested on MA, using the substrate concentrations described by Cowan & Steel (1965).

The 16S rRNA gene was amplified using bacterial universal primers specific to the 16S rRNA gene (primers 9F and 1510R). The PCR product was sequenced using a BigDye Terminator v3.1 cycle sequencing kit (Applied Biosystems) and the DNA sequencer ABI PRISM 3130xl Genetic Analyzer (Applied Biosystems).

The primers 9F, 785F, 802R, and 1510R were used in the gene sequencing reaction selleck screening library (Nakagawa & Kawasaki, 2001). Alignments were carried out using the clustal w tool in mega version 5.0 (Tamura et al., 2011). Phylogenetic trees were generated by the neighbor-joining (Saitou & Nei, 1987), maximum-parsimony (Fitch, 1971), and maximum-likelihood (Felsenstein, 1981) methods in mega version 5.0. The distance matrix was produced on the basis of Kimura’s two-parameter model (Kimura, 1980), and the topologies of the resultant trees were evaluated using bootstrap analysis (Felsenstein, 1985) of 1000 replicates. Sequence similarity values were calculated using genetyx-mac version 16 (Genetyx Corporation). The cell morphology of strain KU41ET was examined GDC-0980 under a transmission electron microscope (JEM-2000EX; JEOL) (Fig. 1). Motility was examined on a semisolid

MB medium. Gram staining was performed using a Favor-G kit (Nissui), and the cells were observed under a light microscope (BX50F4; Olympus). Catalase and oxidase tests were performed as described by Barrow & Feltham (1993). Growth was tested at 25 °C TCL on MA unless otherwise stated. Salinity requirements were tested using modified MA supplemented

with 0–6% (w/v) NaCl. The pH range for growth was determined on MA, and the pH was adjusted to 5.0–10.0. Susceptibility to antibiotics was determined by the diffusion method, using antibiotic disks (Nissui). Briefly, 100 μL of the bacterial suspension (0.5 McFarland standard) was plated onto MA plates and incubated for 3 days. The following antibiotics were tested: ampicillin (10 μg), chloramphenicol (30 μg), gentamicin (10 μg), kanamycin (30 μg), lincomycin (2 μg), nalidixic acid (30 μg), novobiocin (30 μg), penicillin G (10 U), polymyxin B (300 U), streptomycin (10 μg), and tetracycline (30 μg). Any sign of growth inhibition was scored as sensitivity to that antibiotic, and resistance to an antibiotic was indicated by the absence of an inhibition zone. Nitrate reduction; indole production; acid production from glucose (fermentation); hydrolysis of esculin and gelatin; and the presence of arginine dihydrolase, urease, and β-galactosidase was tested using the API 20NE (bioMérieux) according to the manufacturer’s instructions, but the cell suspensions were prepared using Daigo’s IMK-SP. The results were read after 48 h of incubation at 25 °C. Hydrolysis of starch, Tween 40, and Tween 80 was tested on MA, using the substrate concentrations described by Cowan & Steel (1965).

How quickly a new antiretroviral disseminates throughout a healthcare system may further depend on additional factors such as provider experience, local practices, facility case load, pharmacy restrictions, accumulation of clinical data and revisions of treatment guidelines. Overall trends in antiretroviral use identified from observational

databases, including trends in the use of different classes and combinations of antiretrovirals, have been described in the literature [1–3]. Information on the prescribing of individual Roscovitine ic50 antiretrovirals comes largely from reports from individual clinic settings or research-based cohorts [3–7]. Although initiation of antiretroviral therapy has been assessed relative to treatment guideline development and sociodemographic subgroups [8–10], little has been reported on recent uptake of individual agents after Food and Drug Administration (FDA) approval. In addition, regional variation in clinical care and prescribing has

been described for several other chronic diseases [11,12] but has selleck chemical rarely been addressed in studies of antiretroviral use. With almost 23 000 HIV-infected veterans in care each year across the country, the Department of Veterans Affairs (VHA) represents the largest and most geographically diverse provider of healthcare to HIV-infected individuals in the United States. As such, the VHA provides a unique opportunity to evaluate variation in the uptake of new

antiretrovirals based on provider and system factors; aspects of care generally not addressed in previous studies. Thus, we sought to provide Sulfite dehydrogenase a picture of antiretroviral uptake of four newer antiretroviral agents across the nation in the VHA system. Out-patient uptake of four antiretrovirals was evaluated across the VHA system using data from the VHA’s HIV Clinical Case Registry (CCR:HIV). The CCR:HIV is an observational registry database created through extraction of specific clinical data from the VHA’s electronic medical records, including out-patient prescription records, facility location and provider type. We examined prescribing of three recently approved protease inhibitors referred to as ‘target medications’: atazanavir, darunavir and tipranavir. The prescribing of lopinavir/ritonavir was chosen as a comparator as it is also a protease inhibitor and was not associated with issues of availability. As is often done within the VHA, following FDA approval of a complex, costly medication indicated for specialized populations, VHA criteria for use were developed for each target medication and disseminated to all VHA facilities. Darunavir and tipranavir were FDA approved for use in antiretroviral-experienced HIV-infected individuals while atazanavir (and lopinavir/ritonavir) was approved for use in both antiretroviral-naïve and antiretroviral-experienced HIV-infected individuals.

DdeI of Desulfovibrio desulfuricans (39% identity), whose MTase activity has been confirmed experimentally. Detailed analysis of the amino acid sequence of the ORF14-encoded protein revealed the presence of 6 (I, IV, VI, VIII, IX, and X) of the 10 motifs characteristic of m5C MTases, including an invariant Pro-Cys dipeptide from the catalytic motif IV (Neely & Roberts, 2008). The conserved order of these motifs as well as the overall sequence similarity led us to conclude

that ORF14 possibly encodes a protein belonging to the m5C subgroup of MTases (Fig. 1a). Comparative in silico analysis of ORF15 identified six related chromosomally encoded proteins, including the well characterized NcoI REase of Gordonia rubripertincta (previously Nocardia rubropertincta) (acc. selleckchem no. AAC23515) (33% identity) (Fig. 1c). In all cases, the homologous ORFs

encoding a predicted REase are preceded by putative MTase genes, which suggests that these gene pairs constitute functional R-M systems. Interestingly, only one of the predicted MTases (encoded of B. formatexigens DSM 14469) was classified, together with ORF14 of pAMI7, into the m5C group of MTases (Fig. 1a), while the others belong to the N-4 cytosine-specific (m4C) subgroup of MTases. To test whether or not the putative R-M system of pAMI7 is able to protect bacterial cells against invasion by foreign DNA, restriction activity was measured by determining the plating efficiency of the Coliphage λvir. For this experiment, we used E. coli TOP10-derived strains carrying either plasmid pAMI702 JAK inhibitor (contains R-M of pAMI7) or a control plasmid pAMI703 (lacks the R-M module). The triclocarban number of plaque forming units in the case of the pAMI702-containing strain was reduced twofold compared with the control strain (Fig. 2), which unequivocally proved the functionality of the analyzed R-M module. The R-M system of pAMI7 has been designated PamI, and its MTase (ORF14) and REase (ORF15), M.PamI and R.PamI, respectively (in accordance with conventional nomenclature; Roberts et al., 2003). To confirm the activity of R.PamI, the protein was overproduced in E. coli MC1000 and its influence (in the absence of its cognate MTase) on the viability

and morphology of bacterial cells was tested. Overproduction of R.PamI was achieved by cloning of the R.PamI gene into expression vector pCF430, placing it under the transcriptional control of the tightly regulated, inducible PBAD promoter, derived from the arabinose operon of E. coli (resulting plasmid pCF430-END). Following induction with arabinose, overproduction of the endonuclease resulted in very efficient inhibition of cell growth, which was accompanied by a greater than 10 000-fold reduction in the number of colony forming units, compared with a strain carrying the empty vector pCF430. The ‘toxic’ effect of R.PamI (most probably resulting from cleavage of chromosomal DNA unprotected by methylation) was accompanied by filamentation of the bacterial cells.

6 × the resting motor threshold). Navigated brain stimulation was used to monitor

the coil position. A linear relationship was observed between test peak size and test TMS intensity, reflecting linear summation of excitatory inputs induced by TMS. SICI was estimated using the difference between conditioned (produced by the paired pulses) and test Entinostat peaks (produced by the isolated test pulse). Although the conditioning intensity (activating cortical inhibitory interneurons mediating SICI) was kept constant throughout the experiments, the level of SICI changed with the test peak size, in a non-linear fashion, suggesting that low-threshold cortical neurons (excitatory interneurons/pyramidal cells) are less sensitive to SICI than those of higher threshold. These findings provide the first experimental evidence, SAHA HDAC under physiological conditions, for non-linear input/output properties of a complex cortical network. Consequently, changes in the recruitment gain of cortical inhibitory interneurons can greatly modify the excitability of pyramidal cells and their response to afferent inputs. Recent advances in transcranial magnetic stimulation (TMS) have provided an indirect electrophysiological approach to human cortical networks (Hallett, 2007). In the paired pulse paradigms (Kujirai et al., 1993), a first (conditioning) TMS pulse modifies cortex excitability and influences the pyramidal cell transynaptic response to a second (test) pulse.

The motor-evoked potential (MEP), commonly used to evaluate cortical excitability, is influenced

by the conditions of electromyographic (EMG) recording and the spinal motoneurons participating in its amplitude (Lackmy & Marchand-Pauvert, 2010). In the same way, short-interval intracortical inhibition (SICI) depends on the size of the MEP evoked by an isolated test pulse, partly due to the origin of the TMS-induced corticospinal volleys (direct D-wave vs. indirect late I-waves; Garry & Thomson, 2009). The relationship between SICI and MEP size was also attributed to the spinal motoneuron properties, and probably to non-linear summation at cortical level, but the latter was difficult to estimate using variations in MEP amplitude (Lackmy & Marchand-Pauvert, 2010). Given the heterogeneous motoneuron pool properties and the different sensitivity of the corticospinal volleys to SICI, it is difficult Progesterone to distinguish the effects at cortical and spinal level. A method testing SICI on a single motoneuron and a single corticospinal volley, to avoid the effect due to their own properties, would be required to clarify summation at cortical level. Complex neural networks mediate the information in the cerebral cortex to pyramidal cells, whose intrinsic properties (Spruston, 2008) and synaptic input characteristics (DeFelipe & Fariñas, 1992) influence their input–output properties. Both electrophysiological (Oviedo & Reyes, 2005; Williams, 2005) and computational (Poirazi et al.

6 × the resting motor threshold). Navigated brain stimulation was used to monitor

the coil position. A linear relationship was observed between test peak size and test TMS intensity, reflecting linear summation of excitatory inputs induced by TMS. SICI was estimated using the difference between conditioned (produced by the paired pulses) and test AZD2014 ic50 peaks (produced by the isolated test pulse). Although the conditioning intensity (activating cortical inhibitory interneurons mediating SICI) was kept constant throughout the experiments, the level of SICI changed with the test peak size, in a non-linear fashion, suggesting that low-threshold cortical neurons (excitatory interneurons/pyramidal cells) are less sensitive to SICI than those of higher threshold. These findings provide the first experimental evidence, click here under physiological conditions, for non-linear input/output properties of a complex cortical network. Consequently, changes in the recruitment gain of cortical inhibitory interneurons can greatly modify the excitability of pyramidal cells and their response to afferent inputs. Recent advances in transcranial magnetic stimulation (TMS) have provided an indirect electrophysiological approach to human cortical networks (Hallett, 2007). In the paired pulse paradigms (Kujirai et al., 1993), a first (conditioning) TMS pulse modifies cortex excitability and influences the pyramidal cell transynaptic response to a second (test) pulse.

The motor-evoked potential (MEP), commonly used to evaluate cortical excitability, is influenced

by the conditions of electromyographic (EMG) recording and the spinal motoneurons participating in its amplitude (Lackmy & Marchand-Pauvert, 2010). In the same way, short-interval intracortical inhibition (SICI) depends on the size of the MEP evoked by an isolated test pulse, partly due to the origin of the TMS-induced corticospinal volleys (direct D-wave vs. indirect late I-waves; Garry & Thomson, 2009). The relationship between SICI and MEP size was also attributed to the spinal motoneuron properties, and probably to non-linear summation at cortical level, but the latter was difficult to estimate using variations in MEP amplitude (Lackmy & Marchand-Pauvert, 2010). Given the heterogeneous motoneuron pool properties and the different sensitivity of the corticospinal volleys to SICI, it is difficult Vitamin B12 to distinguish the effects at cortical and spinal level. A method testing SICI on a single motoneuron and a single corticospinal volley, to avoid the effect due to their own properties, would be required to clarify summation at cortical level. Complex neural networks mediate the information in the cerebral cortex to pyramidal cells, whose intrinsic properties (Spruston, 2008) and synaptic input characteristics (DeFelipe & Fariñas, 1992) influence their input–output properties. Both electrophysiological (Oviedo & Reyes, 2005; Williams, 2005) and computational (Poirazi et al.

During growth, chitin disappeared from the agarose beads, while the agarose itself was not utilized. Chitin had completely disappeared from the agarose beads after 15 days of incubation.

At this point of time, strain AH-1N had reached a final number of 3 × 108 CFUs mL−1 in the suspended fraction and 2.2 × 108 CFUs mL−1 in the biofilm fraction (Fig. 2a). Cleavage of 4-MU-(GlcNAc)2 (0.032 mU mL−1) and of 4-MU-GlcNAc (0.013 mU mL−1), indicating the presence of a released chitinase and chitobiase, respectively, could only be detected in Fulvestrant datasheet the biofilm fraction while it was below the detection limit in the culture supernatant. When cell-free culture supernatant of strain AH-1N containing chitinolytic enzymes was incubated with embedded chitin, only about 40% of the activity disappeared from the culture supernatant within short time (Fig. 3a). This activity was recovered from the agarose beads at the end of the incubation (not shown). These results indicate that physicochemical interactions alone are not sufficient to cause the see more strong accumulation of enzymes at the agarose beads in cultures of strain AH-1N. Rather, biofilm formation by strain AH-1N could serve as a strategy for minimizing diffusive loss of released enzymes and degradation products and for preventing exploitation by opportunistic bacteria. Flavobacterium sp. strain

4D9 grew similar to strain AH-1N with suspended Carnitine palmitoyltransferase II chitin and reached numbers of about 1.1 × 109 CFUs mL−1

within 170 h concomitant with chitin degradation (Fig. 1). In cell-free supernatants of strain 4D9, no chitinolytic activities could be detected. A low 4-MU-GlcNAc-cleaving activity of 7 mU (mg protein)−1 was detectable when cells of strain 4D9 and chitin were centrifuged and resuspended in fresh medium with 0.1% of the detergent Triton X-100 for solubilizing particle-associated enzymes (Rath & Herndl, 1994). This result indicates that chitinolytic enzymes of strain 4D9 are either cell- or chitin-associated. With embedded chitin, CFUs of strain 4D9 had increased only slightly in the suspended and the biofilm fraction after 32 days of incubation (Fig. 2a), and chitin did not disappear from the agarose beads. Apparently, strain 4D9 was not able to grow with embedded chitin. If strain 4D9 released chitinases, these enzymes would certainly have reached chitin within the agarose beads (Svitil & Kirchman, 1998). Thus, these results indicated that the chitinolytic enzymes of strain 4D9 were associated with the cells, which is in agreement with genome analyses of F. johnsoniae and other Bacteroidetes. The fact that strain 4D9 could not access embedded chitin clearly illustrated a disadvantage of this chitin degradation mechanism. To investigate whether strain 4D9 had strategies to overcome this disadvantage in co-culture with enzyme-releasing bacteria, strains AH-1N and 4D9 were incubated in co-culture with embedded chitin.

From the systematic literature review (Appendix 2) 10 RCTs were identified, investigating the use of either LPV/r or DRV/r in stable, virologically suppressed patients without active hepatitis B coinfection [78-90].

Assessment of virological suppression showed significantly fewer patients on PI monotherapy maintaining virological suppression compared with those continuing on standard combination ART (RR 0.95, 95% CI 0.9, 0.99), although the difference IWR-1 cell line was small. A similar result has previously been reported in a meta-analysis [91]. VL rebound is usually at low level, and is easily reversed by reintroduction of NRTIs. The long-term consequences of this viral rebound and re-suppression are unknown. There were no differences in the frequency of emergence of viral resistance, or of serious adverse events, although few patients developed drug resistance and thus confidence in the estimate of this effect is low. One potential concern is the development of CNS disease in patients on PI monotherapy [83, 88]; however, we did not identify a difference in this outcome although the quality of the evidence is low. Further data are required. Overall, there is no significant clinical benefit of PI monotherapy compared with standard combination ART, which might offset the disadvantage of a lower rate of viral suppression with PI monotherapy. For this reason PI monotherapy

should not be used in unselected patient populations for maintaining virological suppression where standard ART is an acceptable alternative.

There may be potential benefits of PI monotherapy, find more in terms of drug resistance, long-term drug toxicity and cost [92] but further data are required. The ongoing ‘Protease Inhibitor monotherapy vs. Ongoing Triple therapy in the long-term management of HIV infection’ (PIVOT) trial has been designed to address these issues [93]. The primary endpoint is drug resistance. We recognize that PI monotherapy may well be an acceptable option in some specific patient populations but there are few data to provide recommendations. Clinicians Lumacaftor might consider PI monotherapy in patients who are unable to tolerate NRTIs due to toxicities or as a short-term measure to manage or bridge complex clinical scenarios (e.g. stopping certain NNRTI-containing regimens or managing toxicity overdose or acute illness). Where PI monotherapy is considered, DRV/r (dosed once or twice daily) or LPV/r (dosed twice daily) should be used. ATV/r monotherapy is not recommended as it has been associated with higher rates of virological failure [94, 95]. PI monotherapy is not recommended in patients with active hepatitis B coinfection. We recommend against treatment interruption or intermittent therapy in patients stable on a virally suppressive ART regimen (1A). Proportion of patients with a CD4 cell count <350 cells/μL not on ART.

Intra- and interassay coefficients of variation were, respectively: IL-6, 6.8 and 9.4%; MCP-1, 4.0 and <7.5%; sVCAM, 5.9 and 10.2%; sICAM, 4.8 and 10.1%; E-selectin, 5.0 and 8.8%; and P-selectin, 4.2 and 9.8%. Using the Kruskal–Wallis test for continuous variables and the χ2 test for categorical variables, the four study groups were compared by age, sex and race/ethnicity; Tanner stage; height, weight and BMI z-scores; lipids; and biomarkers of vascular dysfunction. For each biomarker, we evaluated differences among the four study groups using the Wilcoxon rank sum test. When waist:hip ratio, lipids and biomarkers of vascular dysfunction were the outcome variables, they were log10-transformed

for analysis to normalize the this website distribution. When lipids were predictor variables, each lipid was categorized into quartiles based on the distribution in the HIV-infected children. Cut-offs were based on the distribution in the HIV-infected children to be consistent across models, because one set of models included only HIV-infected and another included HIV-infected and HEU children (see analyses below). We evaluated differences between all HIV-infected children and HEU children on anthropometric and lipid outcomes using multivariable general linear regression. Waist:hip ratio, per cent body fat and the lipid outcomes were adjusted for potential confounding by age,

race/ethnicity, sex and Tanner stage, while weight, height, and BMI z-score were

adjusted for race/ethnicity and Tanner stage only because z-scores are standardized for age and sex. We compared levels of each CH5424802 datasheet biomarker of vascular dysfunction in the four study groups by multivariable linear regression adjusted for sex, age, race/ethnicity, Tanner stage and BMI z-score. Among HIV-infected children only, we determined the association of each metabolic and HIV disease-specific variable including individual lipids, HIV viral load (≤ 400, 400–5000 and > 5000 HIV-1 RNA copies/mL), CD4 count (< 200 and ≥ 200 cells/μL), CDC stage (N/A, B and C) and current use or non-use of each ARV class [protease inhibitor (PI), nonnucleoside AZD9291 cell line reverse transcriptase inhibitor (NNRTI) and nucleoside reverse transcriptase inhibitor (NRTI)] separately with each biomarker outcome adjusted for age, sex, race/ethnicity and BMI z-score. Variables that were significant at P ≤ 0.1 or that were confounders were retained in the final model. Models were examined for influential points using standardized residuals, and assumptions of linearity between age and BMI z-score were evaluated. For presentation, the antilog was taken for each beta coefficient and 95% confidence interval (CI) in each model. The interpretation of the antilog is as follows: if the estimate presented for HIV-infected vs. HEU children was 0.9 in the model of CRP, the interpretation would be that the average CRP in the HIV-infected children is 0.

rTMS was then applied in two of the three groups (Group 1, rTMS + iHFS; Group 2, rTMS w/o iHFS), whereas in the third group iHFS alone was applied instead. After this first intervention session, the tactile discrimination and SEP recordings were reassessed. After this second assessment, tactile iHFS was applied to Group learn more 1 for 20 min, whereas in Group 2 a wait period was allowed to pass before the third assessment, but without applying the iHFS protocol. Then, in a third assessment,

discrimination thresholds and SEPs were again recorded. The total time between the second and third assessments was approximately 25 min. In Group 3 only the iHFS protocol was applied. Two-point discrimination thresholds for each subject were measured once during the second and third assessment, but measured three times at the baseline assessment. This was to familiarize subjects with the discrimination tasks and to obtain a stable baseline performance. All statistical analyses, apart from calculation of two-point

discrimination thresholds, were performed using Graphpad Prism v 5.0. All data are expressed as mean ± SEM. The change in SEP amplitude for P1 and P2, as well as the paired-pulse ratio (PPR) between the different time points, was tested with a one-way repeated-measures (RM)-anova for Groups 1 and 2. The effect of iHFS alone on the PPR (Group 3) was tested with a paired Student’s Sulfite dehydrogenase t-test. In order to compare differences in the responses elicited by rTMS and iHFS between Groups 1 and 2, the ratios were normalized to the baseline condition, with the baseline value being selleck chemical expressed as 1. Data were analysed using a two-way anova, using ‘Time’ (each of the three SEP measurements) as the within-subjects factor, and ‘Group’ (with or without iHFS) as the between-subjects factor. The same analyses were repeated to test the effect of rTMS/iHFS on two-point discrimination. In order to investigate correlations between changes in the PPR across conditions, we used a Pearson correlation analysis plotting the change in the PPR

for each subject between different conditions vs. the PPR in the baseline condition. These changes were expressed as percentage changes relative to the baseline PPR. The change in the PPR measured immediately after rTMS plotted against the baseline ratio assessment was denoted as ‘∆ rTMS – baseline’, and the PPR measured after iHFS in the rTMS + iHFS group, or after a 25-min wait period in the rTMS w/o iHFS group plotted against the baseline ratio assessment was denoted as ‘∆ last – baseline’. In addition, to look for a possible correlation between changes in cortical excitability and tactile acuity, changes in the PPR were plotted against changes in two-point discrimination. Comparison of the normalized PPRs of the rTMS + iHFS and rTMS w/o iHFS groups with two-way anova (Fig.