J Oral Rehabil 31(8):733–737CrossRef van den Berg TI, Elders LA, de Zwart BC, Burdorf A (2009) The effects of work-related and individual factors on the work ability index: a systematic review. Occup Environ Med 66(4):211–220CrossRef van den Berg TI, Elders LA, de Zwart BC, Burdorf A (2011) The effects of work-related and individual factors on the work ability index: a systematic review. Occup Environ Med 66(4):211–220CrossRef Waghorn G, Chant D (2011) Receiving treatment, labour force activity, and work performance among people with psychiatric disorders: results from a population survey. J Occup Rehabil 21(4):547–558CrossRef Wahlstrom

J, Lindegard A, Ahlborg G Jr, Ekman A, Hagberg M (2003) Perceived muscular tension, emotional stress, psychological demands and physical load during VDU work. Int Arch Occup LY294002 ic50 Environ Health 76(8):584–590CrossRef”
“Introduction A return to work plays an important role in the occupational

health and rehabilitation of working-age post-stroke patients. Previous studies, including our own, identified determinants of early return to work in terms of functional and socioeconomic conditions of the patients (Saeki and Toyonaga 2010; Tanaka et al. 2011). These previous studies focused on the patient’s condition selleck in the pre-stroke, hospitalized, and at-discharge periods, since these will predict the functional recovery which is expected within 3–6 months after onset (Bonita and Beaglehole 1988). However, the impact of higher cortical dysfunction has been poorly studied apart from a study by Tanaka et al. (2011) in which the authors identified that higher cortical dysfunction significantly reduced the chance of very early return to work within 1 month after discharge in those with mild physical impairment. Since the recovery in higher cortical function is likely to be observed several months after a stroke and into the chronic period

after 6 months (Ferro and Crespo 1988), the influence of higher cortical dysfunction on return to work in the chronic mafosfamide phase could be more important than in the earlier phase. Furthermore, the earlier study did not specify what type of higher cortical function is related to return to work among those with different levels of physical impairment. In this study, we specifically focused on the impact of higher cortical dysfunction on return to work in the chronic phase, in addition to the functional and social factors discussed in previous studies. Since the rehabilitation of higher cortical dysfunction often requires a distinct set of resources compared with that required for physical dysfunction, we believe that the results of this study will provide information on the need for cognitive rehabilitation in the chronic stage of stroke recovery to enable return to work. Methods Participants The study was performed on the same prospective cohort as in Tanaka et al. (2011).

In this paper, we show that Eu silicate can be fabricated by optimizing the Eu2O3/Si multilayer nanostructure deposited on Si substrates. Both the structural and optical properties of nanostructures are studied in detail. Through precisely controlling the thickness of Eu2O3 and Si layer at nanometer scale, the Eu silicate with highly efficient room-temperature (RT) light emission associated to Eu2+ ions is obtained after annealing in N2 atmosphere.

Methods The Eu2O3 /Si multilayer films with five periods were grown on Si substrates at 400°C by RF magnetron sputtering. The thin films were deposited in 3.0-mTorr Ar atmosphere. The Eu2O3 layer and Si layer were prepared by alternately sputtering the Eu2O3 target and Si target. The thickness of Eu2O3 layers was kept the same in all samples, while the thickness of Si layers was varied in different samples, as shown in Table 1. After deposition, the samples were thermally treated at 1,000°C for 30 s in Dinaciclib ic50 N2 ambient by rapid thermal annealing. Transmission electron microscopy (TEM, Tecnai G2 F20 S-Twin, FEI Company, Hillsboro, OR, USA) was conducted to investigate the samples’ morphology. The distribution of elements selleck in the film was detected by scanning TEM (STEM), and crystallization

was demonstrated by selected area electron diffraction pattern (SAED). Rutherford backscattering spectrometry (RBS) was carried out to investigate the film composition. The samples’ crystalline phases were identified by X-ray diffraction (XRD, D/max 2400, Rigaku Corporation, Tokyo, Japan) measurements. RT photoluminescence (PL) and photoluminescence excitation (PLE) measurements were performed by using a spectrofluorometer (Nano Log, HORIBA Ltd., Minami-Ku, Kyoto, Japan) equipped with a 450-W Xe lamp. Table 1 Eu 2 O 3 /Si multilayer structure Sample Thickness of Eu2O3layer (nm) Thickness of Si layer (nm) 1 5 8 2 5 17 3 5 25 4 5 42 Results and discussion The cross-sectional TEM images of as-deposited sample

mafosfamide are shown in Figure 1a,b. The film thickness is about 150 nm, with 5 nm in the Eu2O3 layer and 25 nm in the Si layer in one period. The interface between Eu2O3 and Si is very sharp and clear. Moreover, multicrystalline Si has formed in Si layers in the as-deposited sample, which has also been confirmed by SAED, as shown in Figure 1c. The interplanar spacing (d) is about 3.11 Å from the radius of the primary diffraction ring, which agrees with the d of the Si (111) plane. We think that the high substrate temperature and the Eu2O3 layer may induce Si crystallization. Figure 1 Cross-sectional TEM images of as-deposited sample 3. (a) Full view of the film, (b) partial enlarged view of the film, and (c) the SAED image of the film. Figure 2a,b shows the TEM cross section of the sample with a Si layer thickness of about 25 nm after annealing at 1,000°C for 30 s in N2 ambient. The interfaces between Eu2O3 layers and Si layers became blurry. This indicates that the strong reaction between Eu2O3 and Si has happened.

VEGF165 is mainly secreted, whereas VEGF189 is cell-associated and is almost completely sequestered in the extracellular matrix [23]. These VEGF isoforms probably have different functions in cancer tissues. Although several types of tumor cells express VEGF-A and its receptors, the VEGF-A receptor Smad inhibitor neuropilin-1 (NRP-1) is only expressed in the pancreatic carcinoma cell lines Panc-1 and MIA PaCa-2 [29]. Because NRP-1 only binds to VEGF165, one of the several isoforms of VEGF-A [21], it is possible that the binding of VEGF165 to NRP-1 causes cell progression in these pancreatic carcinoma cells. Furthermore, the results of studies on VEGF inhibition using Je-11 suggested that VEGF enhances cell proliferation

(Figure 3A). However, the inhibition of VEGF by Je-11 partially relieved the TZD-induced cells from growth arrest. Therefore, we believe that TZD treatment cause the growth arrest of NSCLC cells

by the mechanism containing VEGF-A (VEGF165) and NRP-1 interaction. High VEGF expression has been reported to be associated with poor prognosis in patients with breast carcinoma [30], prostate carcinoma [31], melanoma click here [32, 33], and lung carcinoma [20]. Thus, VEGF is a prognostic biomarker for NSCLC. On the other hand, lung cancer risk among subjects administered with TZDs is reduced by 33% [34] and in vitro studies indicate that TZDs inhibit the growth of NSCLC cells [27, 35]. Purified VEGF189 and VEGF165 induced cell progression in human umbilical vascular endothelial cells (HUVEC), the human metastatic breast cancer cell line MDA-MB-231, and the human pancreatic carcinoma cell line Panc-1 [36]. These reports indicated that one of the mechanisms as an anti-cancer effect of TZDs

was depressing the VEGF expression. However, some reports contradict the inductive effect 3-mercaptopyruvate sulfurtransferase of TZDs on VEGF [12–19], and this was also observed in the present study. Our results indicate that the interaction of the induced VEGF and NRP-1 may inhibit the growth of NSCLC cells. Taken together, these results suggest that rather than being a growth factor for NSCLC cells, troglitazone-induced VEGF may mediate cell growth arrest. It has been recently reported that the mechanism of VEGF action is complicated [37]. Deletion of myeloid-cell VEGF-A in multiple subcutaneous isograft models and in an autochthonous transgenic model of mammary tumorigenesis resulted in accelerated tumor progression; this process was accompanied by less overall tumor cell death and decreased tumor hypoxia. Administration of TZD to a lung cancer patient induces VEGF expression and prevents the maturation of the surrounding blood vessels, thereby leading to tumor suppression by hypoxia and lack of nutrition. Further, in this study, we showed that TZD-induced VEGF expression inhibited the growth of tumor cells. We think that both these effects prolong the survival of the lung cancer patients.

Brand C shows a bit more diversity, dominated clearly by Exiguobacterium though other genus are present including Raoultella, Pseudomonas, Lactococcus, selleck inhibitor Kurthia, and other Enterobacteriaceae.

Brand A shares Raoultella and Pseudomonas with Brand C and low amounts of Klebsiella, but it is still dominated by Clostridiaceae with trace amounts of a variety of genera. Brand A_rep1 shows more diversity than all the other Brand A replicates, as well as, all the other cheese brand replicates. Discussion This study provides the first Next-Generation Sequencing (NGS) survey of the bacterial community in Latin-style cheeses. The order Lactobacillales was present in significant abundance in all Brand C replicates, which is expected since lactic acid bacteria are known for their role in the production of fermented foods including cheese see more (Table 1). Renye et al. sampled queso fresco from Mexico, plated samples on selective agar, and subjected colonies to 16S rRNA sequencing [29]. Lactococcus lactis, of the order Lactobacillales, was found in the highest numbers in both the cheeses made with raw milk and those made with pasteurized

milk. Leuconostoc mesenteroides, another member of the Lactobacillales order, was also abundant [29]. The genus Exiguobacterium of the order Bacillales dominated all Brand B samples in this study; however, this genus has not been previously reported in cheese [29]. Food matrices in which this genus has been identified include raw milk [30, 31], however, as well as potato processing effluent and water-boiled salted duck [32, 33]. Exiguobacterium have been identified in a wide variety of non-food matrices including surface and pond water, oral cancer

tumors, hot springs in Yellowstone National Park, Siberian permafrost, coastal soil, and a saline Romanian through lake [34–39]. They have also been found to be useful in bioremediation efforts [40]. Serum dextrose broth (SDB) was used in this study due to ongoing research efforts in our laboratory to enrich Brucella species that might be associated with this type of soft cheese. However, SDB is not particularly selective and this rich nutrient source may have allowed uncommon bacteria to out-compete other components of the original metagenomic microflora. The Jameson Effect describes the phenomenon of low abundance microbial species ceasing growth in response to a dominant population’s arrival at stationary phase [41–44]. Tran et al. explored microflora and pathogen dynamics by using selective broth and agar to isolate Listeria from inoculated cheese. They found that ease of isolation was not correlated with concentration of inocula, which supports the theory that microbial community composition may play a bigger role in Listeria inhibition than initial concentrations [43].

1996; Kornyeyev et al. 2010); however,

the level of photoinhibition is inversely proportional to the level of photoprotection and to the ability to repair photodamaged PSII elements. Many studies show that both the photoprotection and the repair ability increase with longtime exposure to high excitation pressure, mostly at HL intensities (Tyystjärvi et al. 1992; Niinemets and Kull 2001). Together with a very low ETR and non-photochemical quenching (of Chl fluorescence), similar to that in sun plants, ML323 we could expect severe photoinhibitory damage in shade plants exposed to HL treatment. However, low differences in photoinhibitory effects (q I) between sun and shade leaves did not correspond with high differences in excitation pressure. One possible explanation is that the values of the excitation ATR inhibitor pressure may have been estimated inaccurately and 1-qP values are really not the true estimates of the PSII redox poise. Rosenqvist (2001) has discussed the possible “inaccuracy” of the calculated values of photochemical quenching, qP, as it probably inaccurately estimates the fraction of oxidized QA due to “connectivity among PSII units” (Joliot and Joliot 1964; Paillotin 1976; Joliot and Joliot 2003). The concept of connectivity among PSII units

is included in many models; however, there is still a lack of reliable data for the correct values of probability parameter p in different plant species. Kramer et al. (2004), based on the data published by Lazar (1999), have reported that the p value in higher Dynein plants is usually higher than 0.6 (supported by Joliot and Joliot 2003, who obtained p = 0.7); in such a case, the qL would

reflect fully the redox state of QA. On the other hand, the data published by Kroon (1994) show p values between 0.25 and 0.45. Further, Strasser and Stirbet (2001), using direct measurements of fast ChlF kinetics, found a value of p 2G around 0.25, using both ChlF curves in the presence and the absence of DCMU; it represents a p value of ~0.5 (Stirbet 2013). Although the connectivity is estimated from the initial part of chlorophyll fluorescence curve, it does not mean that it is valid only for the initial phase. According to the theory of PSII connectivity, the migration possibilities for excitons that are inferred from the sigmoidal shape of fluorescence induction also influence the efficiency of utilization of absorbed light for trapping electrons in the RC and hence, it has an effect on the entire fluorescence kinetics (Lavergne and Trissl 1995). Recently, Tsimilli-Michael and Strasser (2013) documented that the p 2G can be correctly calculated even if only some of the RCs are inactive as well as in the case when the true F m (all RCs closed) is not reached experimentally.

Undefined indicates that there were no AF events in the placebo arm of the study, although there may have been an event in the alendronate arm Other endpoints The endpoints of CA, CVA, and CHF were examined in the meta-analysis using the same studies and the LY2835219 same patient populations as were used for the atrial fibrillation endpoint: 32 trials including 9,518 participants on alendronate and 7,773 on placebo. Cardiac arrhythmias The estimated relative risk for all AEs of cardiac arrhythmia (including AF) was 0.92 (95% CI = 0.79, 1.07; p = 0.31), and

the estimated odds ratio was 0.91 (95% CI = 0.78, 1.06; p = 0.23). The estimated relative risk for SAEs was 1.18 (95% CI = 0.87, 1.61; p = 0.31), and the estimated odds ratio was 1.17 (95% CI = 0.87, 1.59; p = 0.30). There were 360 AEs and 98 SAEs of cardiac arrhythmia for alendronate, occurring in 26 trials (Online Table A). There were 346 AEs and 78 SAEs of cardiac arrhythmia for placebo, occurring in 24 trials. Thirty trials had at least one event in either treatment group; two trials had no events. As seen with the AF endpoint, FIT accounted for two thirds of see more the arrhythmia events (study 51.1—alendronate = 85, placebo = 78, RR = 1.06; study 51.2—alendronate = 159, placebo = 162, RR = 0.99). Non-hemorrhagic cerebrovascular accidents (CVA) The estimated relative risk for all CVA AEs was

0.85 (95% CI = 0.65, 1.11; p = 0.25), and the estimated odds ratio was 0.84 (95% CI = 0.65, 1.10; p = 0.21). There were 108 CVA AEs for alendronate occurring in 11 trials, compared with 122 CVA AEs for placebo occurring in nine trials (Online Table A). Thirteen trials

had CVA AEs; 19 trials had no CVA events. Congestive heart failure (CHF) The estimated relative risk for all CHF AEs was 0.96 (95% CI = 0.71, 1.30; p = 0.84), PLEK2 and the estimated odds ratio was 0.95 (95% CI = 0.71, 1.28; p = 0.75). There were 91 CHF AEs for alendronate occurring in 11 trials compared with 91 AEs for placebo occurring in eight trials (Online Table A). Thirteen trials had an AE in one or both treatment groups; 19 trials had no CHF events. Myocardial infarctions and cardiovascular deaths in FIT As FIT was the largest trial included in this meta-analysis and as it was the only trial to adjudicate CV AEs, only MIs and CV deaths from FIT are summarized. An analysis of the adjudicated results of all FIT SAEs attributed to coronary heart disease (CHD) in the combined cohort did not demonstrate a significant increase in risk of MI with alendronate compared with placebo (1.4% vs. 1.1%, RR 1.28, 95% CI = 0.82, 2.00). All CV deaths that occurred during FIT, as well as all deaths reported with the term “sudden death,” were included in the adjudication. There were 23 CV deaths in the placebo group and 28 in the alendronate group [RR = 1.22 (95% CI = 0.68, 2.21), p = 0.578 for alendronate vs.

0.2, as implemented in MacOS operating system. For each lysogen strain or experimental treatment, the means and standard deviations (SDs) were extracted from the data set according to the date the data were collected and were treated as replicates. Pairwise comparisons of the means (using the Tukey-Kramer HSD test) showed that, for more than half of the cases, p38 MAPK signaling pathway at least one mean was significantly different from the others. Since we were mainly interested in the variation, we subsequently converted all values into their corresponding residuals (centered by their corresponding means). We also tested the homogeneity of variance

from each date replicate, using O’Brien’s test, Brown-Forsythe test, Levene’s test, and Bartlett’s test, all implemented in JMP. Not surprisingly, more than half of the cases showed that at least one replicate variance was significantly different from the others. Although we did not have an a priori expectation of lysis time distribution, we Fludarabine manufacturer nonetheless tested to see if the lysis time in each replicate is normally distributed or not, using the Shapiro-Wilk W test. Again, in many cases, the replicates do not show a normal distribution. Despite variability in our data set, none of our conclusions were fundamentally changed. Therefore,

for the presented results, the mean and standard deviation for each lysogen strain or experimental treatment were calculated based on the following criteria: (i) if the means and variances were the same among all blocks, then all the data would be pooled together to estimate the combined means and SDs, (ii) if the means were significantly different, but the variances were the same among all blocks, then the mean would be estimated by averaging the block means while the SDs would be estimated by pooled residuals, and (iii) if the means and variances were significantly different among all blocks, then the means and SDs would be estimated by averaging block means and SDs. For details of our data set, see additional file 1. Acknowledgements The authors are grateful for insightful comments these from Tom Caraco, Andrew Rutenberg, Gillian Ryan, Samuel

Sheppard and several anonymous reviewers. The authors would also like to thank Yongping Shao for the initial setup of the experimental apparatus and Kuangnan Xiong for technical assistance. This work was supported by grant GM072815 from the National Institutes of Health to INW. During manuscript preparation, JJD was supported by grants from the Professional Staff Congress of the City University of New York and the National Science Foundation (Division of Environmental Biology Award #0804039 and Division of Molecular and Cellular Biosciences Award #0918199). Electronic supplementary material Additional file 1: Sample sizes and standard deviations. More detailed data sets for both Table 1 and Table 2. (DOC 86 KB) References 1.

Nitrogen metabolism and Spore coat formation (M5) This module includes 39 genes and was divided into two sub-modules, each having related functions. The first set of four genes encode proteins that participate in nitrogen metabolism, co-regulated by the nitrogen utilization protein TnrA [23]. The second sub-module comprises 35 genes involved in the spore coat formation. A unique property of this sub-module is that all genes

are regulated by the protein Sigma K, encoded by the genes spoIIIC and spoIVCB [24, 25]. As all the Vistusertib mw genes belonging to this sub-module were shown to be repressed, this indicates that the sporulation regulatory program is governed by a hierarchical cascade, consisting of the transcription factors: Sigma E, Sigma K, GerE, GerR, and SpoIIID. This observed response is in accordance with previous reports [21] SOS and prospore formation (M6) Is constituted by 14 genes (Table 1) and the clustering method divided the module into two functionally defined sub-modules. The SOS sub-module possesses three genes regulated by LexA, which participate in DNA repair [26]. We found a second subunit, comprising 10 genes, regulated by Sigma E,

which is the earliest-acting factor, specific to the mother-cell line of gene expression on the cascade forming the prospore [21]. As is evident in Table 1, 12 of the 14 genes participating in the cluster appear to be repressed. As previously mentioned there are two mini-modules (MM) embedded within the giant component. The first one (MM1, Table 1), possesses the genes which encode NVP-BSK805 for Sigma

X and Spo0A TFs and which are involved in the sporulation process. The second mini-module (MM2 Table 1) has genes relating to glycerophospholipid metabolism that are entirely regulated by PhoP. We found several mini-modules and two modules, separated from the giant component. The existence of these topological structures is likely to be a consequence of the fact that knowledge of the network is incomplete, the absence of genes or because certain TFs are not included in the sub-network or because of the existence of other regulatory structures, such as antiterminators, terminators and regulatory RNAs which are not considered in the network construction. For these reasons, Isoconazole some very well studied functions (see Table 1) such as glycolysis (MM3), respiratory function control by FNR (MM4), peroxide stress (MM5), the PTS system dependent on glucose (MM7), competence regulated by ComK (M7), the cystein module (M8) and a topological structure dependent on the sigma factor W (M9) were excluded from the giant component. Comparison of the glucose responsive networks found in E. coli and B. subtilis The structure of complex transcriptional regulatory networks has been studied extensively in certain model organisms.

There is a large component of ecological restoration that still places considerable value on past ecosystems and seeks to restore the system’s characteristics to its past state. Valuing the past when the past is not an accurate indicator for the future may fulfill a nostalgic need but may ultimately be counterproductive in terms of achieving realistic and lasting restoration outcomes. Our results indicate a significant gap

between theory and practice—understandable for the early stages of climate adaptation. We hypothesize that climate adaptation in reality may require a greater preponderance of transformative strategies, and that scientists and institutions should accelerate exploring such approaches to define and develop the next generation of conservation strategies. Acknowledgements We would like to express AZD4547 appreciation

to everyone involved in the Caspase activation climate adaptation process and workshop, especially the 20 conservation project teams and class facilitators and knowledge managers who contributed their ideas and experiences to the collective wisdom presented in this paper. Appreciation goes to Kristin Richards Betz and Anne Wallach Thomas for building and maintaining TNC’s climate adaptation website (http://​conserveonline.​org/​workspaces/​climateadaptatio​n) before, during, and after the workshop. This paper also benefitted from the input of our colleagues Peter Kareiva, Stacey Solie, Karen Lombard, and Dan Majka, and all the participants of the January 2010 TNC writing workshop in Tucson, Palbociclib datasheet Arizona. Open Access This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium,

provided the original author(s) and source are credited. Electronic supplementary material Below is the link to the electronic supplementary material. Supplementary material 1 (PDF 324 kb) Supplementary material 2 (PDF 182 kb) References Araujo MB, Rahbek C (2006) How does climate change affect biodiversity? Science 313:1396–1397PubMedCrossRef Bierwagen BG, Thomas R, Kane A (2008) Capacity of management plans for aquatic invasive species to integrate climate change. Conserv Biol 22:568–574PubMedCrossRef CMP (2007) Open standards for the practice of conservation. Version 2.0. http://​www.​conservationmeas​ures.​org/​CMP/​Site_​Docs/​CMP_​Open_​Standards_​Version_​2.​0.​pdf. Cited 22 Apr 2010 Dunwiddie PW, Hall SA, Ingraham MW, Bakker JD, Nelson KS, Fuller R, Gray E (2009) Rethinking conservation practice in light of climate change. Ecol Restor 27:320–329CrossRef Galatowitsch S, Frelich L, Phillips-Mao L (2009) Regional climate change adaptation strategies for biodiversity conservation in a midcontinental region of North America. Biol Conserv 142:2012–2022CrossRef Girvetz EH, Zganjar C, Raber GT, Maurer EP, Kareiva P, Lawler JJ (2009) Applied climate-change analysis: the Climate Wizard tool.

At zinc concentrations of 0.4 mM and higher, however, the protective effect was lost, resulting in a U-shaped curve in Figure  1F (data not shown for concentrations greater than 0.4 mM). The U shape in Figure  1F seemed to mirror the arch shape of the curves in Figure  1D and E, and suggested that C188-9 datasheet zinc might have interesting protective effects against insults to the intestinal epithelium. Figure 1 Effect of zinc acetate on

hydrogen peroxide-induced intestinal damage and Stx2 translocation in T84 cells. T84 cells grown to confluency in Transwell inserts were treated with various concentrations of hydrogen peroxide and barrier function monitored by measuring trans-epithelial electrical resistance (TER) and translocation of Stx2 across the monolayers. Stx2 itself does not damage T84 cells due to lack of expression of the Gb3 receptor in this cell line. Panel A, time course of TER in response to H2O2 added to final concentrations of 1 to 5 mM. Panel B, effect of Belinostat H2O2 on translocation of Stx2 and on fluorescein-labeled dextran-4000. Stx2 was added to the upper chamber 2 hours after the addition of H2O2, and Stx2 was measured by EIA in the lower chamber. H2O2 at concentrations of 3 mM and higher induced significant translocation of Stx2 into the lower chamber. The amount of Stx2 translocated to the lower chamber after

24 in response to 5 mM H2O2 was 3.5% of the total Stx2 added. Panel B, Inset, shows that H2O2 also triggers a translocation of FITC-dextran-4000 across

the monolayer, which is abolished by addition of 1200 U/mL of catalase; *significant compared to H2O2 alone. Panels C, effect of zinc acetate on Δ TER in undamaged T84 cell monolayers. Δ TER is defined as the TERfinal – TERinitial, which is determined separately for each well, then averaged. Using the Δ TER helps to compensate for well-to-well variation in the starting TER, because each well serves as its own control. Panel D, effect of zinc acetate on Δ TER in cells treated with 2% DMSO. Panel E, effect of zinc on T84 cell monolayers treated pheromone with 3 mM H2O2. Panel F, protection by zinc against Stx2 translocation induced by exposure to H2O2. In Figure  1 the hydrogen peroxide was added once at fairly high concentrations, but in an actual infection the hydrogen peroxide (and other oxidants, such as superoxide and sodium hypochlorite) is generated gradually from enzymatic conversion of substrates over many hours. Therefore we repeated experiments similar to those shown in Figure  1, but instead using H2O2 we added hypoxanthine plus XO. Figure  2A shows that, in the presence of XO, hypoxanthine has a concentration-dependent effect on ∆ TER. Adding 100 μM hypoxanthine actually increased TER compared to vehicle control, with higher concentrations of hypoxanthine inducing a progressive fall in TER. The increase in TER observed in Figure  2A at 100 μM hypoxanthine was reminiscent of the small increase in TER seen with 1 mM H2O2 in Figure  1A (top curve).