0 (ABI). Figure 1A illustrates the structure of the SPARC gene and the topology of the BSP primer, indicating the Apoptosis inhibitor position of the CpG island containing 12 CpG sites and the BSP primers. Figure 1 Detection of SPARC gene TRR methylation. GSK690693 cell line (A) Illustration of the SPARC gene TRR and topology of the BSP primer. The black bar indicates the analyzed region. The bold “”G”" indicates the transcriptional start site. The bold italic “”CG”" indicates the location of 12 CpG island sites. The underlined sequence indicates the primers for BSP. Blue and red rectangles indicate the Sp1 and

AP1 binding consensus sequences, respectively. The red triangles indicate the region whose representative sequence analyses were

showed in Figure 1B. (B) Representative sequencing data of the SPARC gene TRR in four different groups of pancreatic tissues obtained using BSP PCR-based sequencing analysis. CpG dinucleotides see more “”C”" in the objective sequence are shown in red. The red, yellow, green, light blue, and deep blue dots under the analyzed sequence represent different methylation ratios, respectively. We next performed BSP PCR-based sequencing analysis to assess the methylation status of the SPARC gene TRR in four tissue groups: 40 pancreatic cancer samples and their corresponding adjacent normal pancreatic tissues, 6 chronic pancreatitis samples, and 6 real normal pancreatic tissue samples. Figure 1B shows representative BSP PCR-based sequencing analysis results for these four different groups of pancreatic tissues. The methylation pattern of the SPARC gene TRR in these four types of pancreatic tissues

is shown in Figure 2. According to the curve fitted to the mean percent methylation of pancreatic cancer tissue data by the MACD (moving average convergence/divergence) method, we found two hypermethylation wave peak regions in these CpG Demeclocycline islands. The first contained CpG site 1-7 (CpG Region 1) and the second contained CpG sites 8-12 (CpG Region 2). We searched the web site http://​www.​cbrc.​jp/​research/​db/​TFSEARCH.​html and found that CpG Region 1 contained two Sp1 sites while CpG Region 2 contained one Ap1 site (Figure 1A). Figure 3 shows the mean percentage of gene methylation and the 95% CI of these two hypermethylation wave peak regions in the four types of pancreatic tissues. Methylation of these two regions appeared to gradually increase from normal, chronic pancreatitis, and adjacent normal to pancreatic cancer tissues. Furthermore, CpG Region 2 was rarely methylated in real normal pancreatic tissues but CpG Region 1 was more frequently methylated in some of normal tissues. In addition, the methylation level of CpG Region 2 in the adjacent normal tissues was significantly increased compared with the normal tissues.

1993). However, the mutations may also cause local effects like spin redistributions within the BChl macrocycles or change the geometry of the BChl macrocycles. Since the hfcs

of the β-protons at positions 7, 8, 17, and 18 (Fig. 1c) are strongly dependent on Epigenetics inhibitor the geometry of the respective hydrated rings (Rautter et al. 1995), the EPR linewidth may be changed even without a spin redistribution selleck inhibitor between the two halves of the dimer. More definitive conclusions can, therefore, only be drawn if the resolution is increased significantly, e.g., by double and triple resonance experiments, yielding the individual nuclear hyperfine coupling constants. X-band CW 1H Special TRIPLE measurements P•+ in Wild-Type RCs Figure 3 compares the Special TRIPLE spectra www.selleckchem.com/products/ly3023414.html of WT 2.4.1 (bacteria grown photosynthetically) and WT-H7 (hepta-histidine tag, grown non-photosynthetically) at pH 8.0. The WT 2.4.1 spectrum is identical to that observed before (Geßner et al. 1992; Artz et al. 1997; Müh et al. 2002). The assignment of lines and hfcs (Table 1) follows that of our earlier work (Geßner et al. 1992; Lendzian et al. 1993). Most pronounced are the resonances of the protons of the four (freely rotating) methyl groups (positive hfcs)1 and the two β-protons (L-side, positive hfcs). As an indicator for the spin density distribution in the BChl macrocycle, the hfcs of the β-protons at the positions 7, 8, 17, and 18 are less suited,

since they are sensitive to the dihedral angle of the respective rings that can easily change (Käss et al. 1994; Rautter et al. 1995). The two spectra show some very small but distinct differences of the proton

hfcs. Based upon previous studies, the shifts are unlikely to arise from a difference in the carotenoid composition, due to incorporation of spheroidene and spheroidenone in cultures grown under anaerobic and aerobic conditions, respectively, or differences in the preparations (Geßner et al. 1992; Rautter et al. 1994). The ENDOR/TRIPLE spectrum is sensitive to electrostatic interactions as indicated by the large changes observed upon introduction of hydrogen bonds or use of zwitterionic detergents (Rautter et al. 1995; Müh very et al. 1998; 2002). Thus, the most likely cause for the small spectral shift is addition of electrostatic interactions due to the presence of the hepta-histidine tag at the carboxyl terminus region of the M-subunit. For the discussion concerning the mutants, since the changes are very small, the two wild-type samples can be considered to be basically equivalent. Fig. 3 1H-Special TRIPLE spectra (X-band) of light-induced P•+ from RCs from Rb. sphaeroides wild type 2.4.1 (WT 2.4.1) (black line) and from wild type with hepta-histidine tag (WT-H7) (red line) at pH 8.0. The isotropic hyperfine couplings a iso are directly obtained from the Special TRIPLE frequency by ν ST = a iso/2 (for details see Lendzian et al. 1993).

J Appl Physiol 1998,84(6):2138–42.PubMed 35. Hickson RC, Bomze HA, Holloszy JO: Linear increase in Geneticin solubility dmso aerobic power induced by a strenuous program of endurance exercise.

J Appl Physiol 1977,42(3):372–6.PubMed 36. Keith SP, Jacobs I, McLellan TM: Adaptations to training at the individual anaerobic threshold. Eur J Appl Physiol Occup Physiol 1992,65(4):316–23.CrossRefPubMed 37. Rodas G, Ventura JL, Cadefau JA, Cusso R, Parra J: A short training programme for the rapid improvement of both aerobic and anaerobic metabolism. Eur J Appl Physiol 2000,82(5–6):480–6.CrossRefPubMed 38. Tabata I, Nishimura K, Kouzaki M, Hirai Y, Ogita F, Miyachi M, Yamamoto K: Effects of moderate-intensity endurance and high-intensity selleck kinase inhibitor intermittent training on anaerobic capacity and VO2max. Med Sci Sports Exerc 1996,28(10):1327–30.PubMed 39. Ray CA: Sympathetic adaptations to one-legged training. J Appl Physiol 1999,86(5):1583–7.PubMed 40. AG-881 order Hoogeveen AR: The effect of endurance training on the ventilatory response to exercise in elite cyclists. Eur J Appl Physiol 2000,82(1–2):45–51.CrossRefPubMed 41. Linossier MT, Denis C, Dormois D, Geyssant A, Lacour JR: Ergometric and metabolic adaptation to a 5-s sprint training programme. Eur J Appl Physiol Occup Physiol 1993,67(5):408–14.CrossRefPubMed 42. Nelson AG, Day R, Glickman-Weiss EL, Hegsted M, Kokkonen J, Sampson B: Creatine supplementation

alters the response to a graded cycle ergometer test. Eur J Appl Physiol 2000,83(1):89–94.CrossRefPubMed 43. Reardon TF, Ruell PA, Fiatarone Singh MA, Thompson CH, Rooney KB: Creatine supplementation does not enhance submaximal aerobic training adaptations in healthy young men and women. Eur J Appl Physiol 2006,98(3):234–41.CrossRefPubMed 44. Murphy AJ, Watsford ML, Coutts AJ, Richards DA: Effects of creatine supplementation on aerobic power and cardiovascular structure and function. J Sci Med Sport 2005,8(3):305–13.CrossRefPubMed 45. McConell GK, Shinewell J, Stephens

TJ, Stathis CG, Canny BJ, Snow RJ: Creatine supplementation reduces muscle inosine monophosphate during endurance exercise in humans. Med Sci Sports Exerc 2005,37(12):2054–61.CrossRefPubMed 46. Wasserman K, Beaver WL, Whipp BJ: Gas exchange theory IKBKE and the lactic acidosis (anaerobic) threshold. Circulation 1990,81(1 Suppl):II14–30.PubMed 47. Wasserman K, Whipp BJ, Koyl SN, Beaver WL: Anaerobic threshold and respiratory gas exchange during exercise. J Appl Physiol 1973,35(2):236–43.PubMed 48. Poole DC, Gaesser GA: Response of ventilatory and lactate thresholds to continuous and interval training. J Appl Physiol 1985,58(4):1115–21.PubMed 49. Acevedo EO, Goldfarb AH: Increased training intensity effects on plasma lactate, ventilatory threshold, and endurance. Med Sci Sports Exerc 1989,21(5):563–8.PubMed 50.

None of the “no greater benefits” studies were outside of normal distribution. high throughput screening However, three studies [22, 24, 25] had spreads that were higher than three studies [6, 8, 10] of the “muscular benefits” grouping. These seemed likely explained, however, by the fact that changes to habitual protein intake were much larger in the latter [6, 8, 10] than the former [22, 24, 25]. Protein change theory Only twelve studies

included in this review reported baseline dietary intakes. Among studies showing muscular benefits of increased protein intake, the three with the smallest increases from habitual protein intake (19.5-28.6%) were conducted on untrained participants [6, 8, 10]. Most studies were on trained participants and larger increases in protein intake. However the ~4 kcal/kg greater energy intake in one of these studies [10] or perhaps the longer duration of another study [8] may have made it easier for a smaller change to yield significant results. That said, total energy intake was higher in some higher protein groups than control and lower than control in EVP4593 cell line other studies (Table 1) making it hard to use energy intake as a clear predictor of results. Further supporting higher habitual protein intake during resistance training, Ratamess et al.’s strength/power athletes consuming 2.3 g/kg/day were significantly

leaner than those consuming 1.45 or 0.95 g/kg/day [28]. While monitored for 10 wk, the 2.3 g/kg/day group consumed

~400-700 kcal or ~6-10.5 kcal/kg/day more than the other tertiles, yet remained significantly leaner by ~5-8% bodyfat. Strong correlations have been shown between increased habitual protein intake [29], regular ingestion of quality protein [30], and muscle mass. In contrast, Thalacker-Mercer et al., found no association between habitual protein intakes of 0.97-1.07 g/kg/day and muscular gains [31]. However, since Ratamess et al. showed no differences between 0.95 and 1.45 g/kg/day [28], it seems unlikely that 0.97 versus 1.07 g/kg/day was enough difference to see a protein effect [31]. Variability in resistance this website training volume (1–5 sets/exercise), intensity (3–20 RM), and frequency Silibinin (3-5- day/wk) across studies in this review may also have interacted with response to protein supplementation. However, most studies used resistance training variables in the middle of these ranges and there was no pattern of a greater frequency of training programs employing certain variables within the benefits or no greater benefits groupings. Since protein benefits muscle mass in lieu of resistance training [32, 33], even if a training program was suboptimal, a higher protein intake should still offer a statistically significant benefit over a lower intake. The findings of Ratamess et al. and Thalacker-Mercer et al.

Bacterial cultures growing in TY medium for 48 h to an OD600 of 0.6 were diluted 1000-fold in M1 minimal medium supplemented with Dilworth’s vitamins, and 100 μl of Selleckchem Tipifarnib diluted cultures were added to each well and grown under static conditions at 28°C for up to 4 days. After 2 and 4 days, the contents of the wells were removed and each well was washed two times with 150 μl of sterile physiological saline solution, and then stained for 30 min with 100 μl of 25 μg/ml Calcofluor or 100 μl of 0.85% NaCl containing 5 μM Syto-9 and 30 μM propidium iodide. Next, dye solutions were removed and the wells were washed three times

with 150 μl of 0.85% NaCl, covered by 30 μl of fresh portion of physiological saline solution, and observed in a microscope. This experiment was repeated two times. To analyze different parameters of biofilm, 36 images from 3 wells of individual strain were collected. The ratio of live to dead cells was calculated using the ImageJ 1.43e software

(Wayne Rasband, NIH, USA). Images of biofilms stained with Syto-9 were analyzed to calculate several morphological parameters. The percentage of area covered by biofilm, a fractal dimension, and the length 17-AAG of coastline were calculated using ImageJ 1.43e software according to [76, 77]. Three-dimensional images were reconstructed using the Laser Scanning Confocal Microscope LSC 5 PASCAL (Carl Zeiss, Germany) with 200x magnification. Plant tests Red clover (Trifolium pratense cv. Diana) seeds were surface sterilized, germinated and grown on Fåhraeus medium [66] slants. 5-day-old seedlings were inoculated with bacterial suspensions at an OD600 of 0.2 (200 μl/plant), and grown under natural light supplemented with artificial light (14 h day at 24°C and 10 h night at 18°C) in a greenhouse. The clover plants were inspected for root nodule formation and harvested after 4 weeks. Wet and dry masses of clover shoots were estimated. Plant competition assay For the competition assay, the Rt2472 and Rt2441 mutants, and the Megestrol Acetate wild type Rt24.2 were collected from TY

agar medium into sterile water to an OD600 of 0.1. The mutants and wild type suspensions were mixed in 1:1, 10:1, 100:1, and 1000:1 ratios, and 200 μl of each mixture were added per plant. Twenty seedlings were used for each treatment. 28 days after infection, nodules were surface sterilized, crushed in 20 μl of saline solution, and 10 μl selleck chemicals portions were plated on 79CA agar plates supplemented with nalidixic acid or kanamycin, and incubated at 28°C for 3 days. Ninety nodules per each mixture were examined. Bacteria growing exclusively on the medium supplemented with nalidixic acid corresponded to the wild type strain, and those growing on the medium supplemented with kanamycin corresponded to the rosR mutants. The competitive ability of rhizobia was expressed as the percentage of the particular strain in the analyzed nodules. Assays for root attachment and growth on the root surface Root attachment of the Rt2472 and the Rt24.

Oshima H, Kikuchi H, Nakao H, Itoh K, Kamimura T, Morikawa T, Umada T, Tamura H, Nishio K, Masuda H: Detecting dynamic signals of ideally ordered nanohole patterned disk media fabricated using nanoimprint lithography. Appl Phys Lett

2007,91(2): 22508.CrossRef 2. Zhao X, Wu* Y, Xiaopeng H: Electrodeposition synthesis of Au-Cu heterojunction nanowires and their buy C188-9 optical properties. Int J Electrochem Sci 2013, 8:1903–1910. 3. Liu H, Lu B, Wie S, Bao M, Wen Y, Wang F: Electrodeposited highly-ordered manganese oxide nanowire arrays for supercapacitors. Solid State Science 2012, 14:789–793.CrossRef 4. Buttard D, Dupré L, Bernardin T, Zelsmann M, Peyrade D, Gentile www.selleckchem.com/PARP.html P: Confined growth of silicon nanowires as a possible process for third generation solar cells. Phys Stat Solidi 2011,8(3): 812–815.CrossRef 5. Khorasaninejad M, Singh Saini S: Silicon nanowire optical waveguide (SNOW). Opt Express 2010,18(22): 23442–23457.CrossRef 6. Yogeswaran U, Chen SH: A review on the electrochemical sensors and biosensors composed of nanowires as sensing material. Sensors 2008, 8:290–313.CrossRef 7. Park M, Harrison C, Chaikin PM, Register RA, Adamson DH: Block copolymer lithography: periodic arrays of 1011 holes in 1 square centimeter. Science 1997,276(5317): 1401–1404.CrossRef 8. Segalman RA, Yokoyama H, Kramer EJ: Graphoepitaxy of spherical domain block copolymer films. Adv

Mater 2001,13(15): 1152–1155.CrossRef 9. Stoykovitch MP, buy Q-VD-Oph Muller M, Kim SO, Solak HH, Edwards EW, De Pablo JJ, Nealey PF: Directed assembly of block copolymer blends into nonregular device-oriented structures. Science 2005,308(5727): 1442–1446.CrossRef 10. Masuda H, Kukuda K: Ordered metal nanohole arrays made by a two-step replication of honeycomb structures of anodic alumina. Science 1995,268(5216): 1466–1468.CrossRef 11. Jessensky O, Muller F, Gosele U: Self-organized formation of hexagonal pore arrays in anodic alumina. Appl Phys Lett 1998,72(10): 1173–1175.CrossRef 12.

Martín J, Manzano CV, Caballero-Calero O, Martín-González M: High-aspect-ratio and highly ordered 15-nm porous alumina Dehydratase templates. ACS Appl Mater Interfaces 2013,5(1): 72–79.CrossRef 13. Bogart TE, Dey S, Lew KK, Mohney SE, Redwing JM: Diameter-controlled synthesis of silicon nanowires using nanoporous alumina membranes. Adv Mater 2005,17(1): 114–117.CrossRef 14. Byun J, Lee JI, Kwon S, Jeon G, Kim JK: Highly ordered nanoporous alumina on conducting substrates with adhesion enhanced by surface modification: universal templates for ultrahigh-density arrays of nanorods. Adv Mater 2010,22(18): 2028–2032.CrossRef 15. Keller F, Hunter MS, Robinson DL: Structural features of oxide coatings on aluminium. J Electrochem Soc 1953,100(9): 411–419.CrossRef 16. Shimizu T, Xie T, Nishikawa J, Shingubara S, Senz S, Gösele U: Synthesis of vertical high-density epitaxial Si(100) nanowire arrays on a Si(100) substrate using an anodic aluminum oxide template. Adv Mater 2007,19(7): 917–920.CrossRef 17.

However, our results suggest that even in the absence of recent bouts of antibiotic-mediated selection, we find that persister fractions differ considerably among different genotypes, suggesting that variation in persister-forming ability is harbored naturally in populations. Previous studies have indirectly implied that mechanisms of persister CDK inhibition formation may differ between strains

for different antibiotics. Keren et al. [7] showed that one strain of E. coli K12 (AT984 dapA zde-264::Tn10) exhibited a higher fraction of persisters in ofloxacin compared to ampicillin, whereas Spoering et al. [24] showed the reverse: E. coli K12 wildtype exhibits a lower fraction of persisters in ofloxacin than ampicillin. For both studies, the drugs were used at identical concentrations (5 ug/ml and 100 ug/ml, GS-7977 cost respectively).

Again, this result suggests that even for E. coli K12, closely related mutants do not necessarily produce large or small persister fractions, but these fractions depend specifically on the type of antibiotic and strain used. To our knowledge, the effect of pairwise combinations of antibiotics has not been investigated with respect to bacterial persistence. We found that the killing dynamics under combinations was qualitatively similar to that observed under a single antibiotic, with biphasic kill curves. Furthermore, the observation of co-incident persister fractions provide evidence that there is a small number of persister cells

that exhibit multidrug resistance, and are thus persistent to all combinations of antibiotics (Figure 5). Fosbretabulin ic50 However, the majority of persister cells do not exhibit multidrug-resistance. Carbachol Conclusions The results of our study clearly show that the fraction of persisters within an isogenic culture is highly dependent on the antimicrobial compound and the bacterial strain. Importantly, differences in persister fractions exist even for antibiotics of the same class. This contrasts markedly with the majority of laboratory studies of E. coli K12, which have generally found that persister phenotypes are characterized by multi drug tolerance. These results complicate the search for persister mechanisms, since even within the same strain different types of persister cells exist, with none clearly dominating. Methods Strains The E. coli natural isolates used in this study were selected from a collection of 456 E. coli sampled from a watershed of Lake Superior, Minnesota, USA (46°42’04′N, and 92°12’26′W [26]; Additional file 2: Table S1). For this study, all strains were treated with ampicillin (100 μg/ml) for 24 h, and 11 strains that showed marked differences in survival (as measured by colony counts) were selected. Media M9 salts supplemented with 0.2% glucose was used as a growth medium in all experiments. Determination of minimum inhibitory concentrations (MICs) Single colonies were used to inoculate 200 μl of M9 salts supplemented with 0.2% glucose in 96-well plates.

As a result, the plasma expands outward faster and to the larger radius exerting more pressure in the surrounding including onto the redeposited plasma vapor condensates on the target surface. This creates the external pressure approximately similar to or higher than the internal pressure of the redeposited material, hence hindering the formation of stems, stage 4 of Figure 8. The this website excessive temperature of the plasma species and the target can also remelt the deposited material as well as previously grown stems and tips. The SEM image of the target

irradiated with 13-MHz repetition rate for the dwell time of 0.75 ms depicted in Figure 9c is the perfect example of the stage 4 illustrated in Figure 8. For 8-MHz Ipatasertib manufacturer repetition rate at 0.75-ms dwell time, most of the redeposited material Quizartinib in vivo must be experiencing approximately equal internal and external pressure resulting in the formation of just circular micronanoparticles rather than the formation of stems. There is an evident of the formation of very few tips from bulk droplets in Figure 9b. If we follow the

above four stages, there should not be any tip growth for 13-MHz repetition rate for the dwell time of 0.75 ms. However from Figure 9c, it can be seen that a significant number of nanotips grew on the target. This happened because the 13-MHz repetition rate provides a much larger number of pulses and the machining is performed way beyond stage 4 of the growth mechanism. When the plasma reaches stage 4, it will exert excessive pressure and temperature on previously

deposited material resulting in remelting and formation of micronanoparticles. But at the same time, since plasma is continuously being heated by incoming pulses, plasma will rapidly expand outward. There will be a point in time where the plasma has expanded far enough from the redeposition RVX-208 site relieving excessive pressure and temperature. From this point onward, the transmission of the subsequent laser pulses will improve, and the new material will be ablated from the target forming new plasma over the target surface. This whole phenomenon must be occurring in the last part of the 0.75-ms dwell time during which the growth mechanism starts back at stage 1 and forms nanotips on previously deposited material, as seen in Figure 9c. Figure 9 Effect of excessive machining of irradiation spot corresponding to various repetition rates. Nanostructures generated at the dwell time of 0.75 ms for the repetition rates of (a) 4, (b) 8, and (c) 13 MHz for 214 fs. Effect of laser polarization All the experiments discussed above were performed by circular polarization of femtosecond laser pulses. We also wanted to investigate whether the linear polarization changes the growth mechanism of nanostructures on the laser-irradiated target glass. The effect of laser polarization on the ablation of various materials has been studied by many researchers. Hee et al.

Nakamura S, Kuroda T, Sugai T, Ono S, Yoshida T, Akasaka I, Nakashima F, Sasou S: The first reported case of intestinal spirochaetosis in Japan. Pathol Int 1998, 48:58–62.PubMedCrossRef 41. Chauvatcharin S, Siripatana C, Seki T, Takagi M, Yoshida T: Metabolism analysis and on-line physiological state diagnosis of acetone-butanol fermentation. Biotechnol Bioeng 1998, 58:561–571.PubMedCrossRef Competing interests The authors declare that they

have no competing interests. Author’s contributions WR, RMG, DXS, ABT and GSF Trichostatin A order designed the study and acquired the data; SG, AP, LFB and TAR interpreted and analysed the data; PCFM and JCde check details O drafted and wrote the manuscript; JCde O, TAR, LFB and PCFM revised intellectual and critically the manuscript. All of the authors approve the final version of the manuscript.”
“Introduction Exercise in hot environments can cause a reduction in plasma

volume due in part to the thermoregulation via sweating, which can decrease the blood supply to the muscle tissue. If fluid loss continues and is not replaced with water and electrolytes, body fluid distribution will then limit the appropriate delivery of oxygen and substrate to the working Selleckchem GSK1838705A muscle [1]. Furthermore, heat exposure, hyperthermia, and dehydration affect the brain’s ability to function normally and can adversely impact cognitive performance whereby thermal sensation and mood state may be altered. While much is known regarding the physiology of dehydration, the psychological effects are less clear due in part to inconsistent data in the experimental literature. Dehydration and other adverse physiological stressors MycoClean Mycoplasma Removal Kit have been shown to have a negative impact on mood state [2, 3]. Such mood changes can then impact cognitive function [4, 5]. Exercise can also impact blood glucose levels, as the body requires the use of glucose to fuel physical

activity [6]. Strenuous, prolonged exercise can result in hypoglycemia, as the blood’s level of glucose may become lower because it is utilized to allow for continued physical activity. Reduced levels of glucose may exhibit as physical symptoms including shakiness, hunger, nervousness, sweating, dizziness, confusion, visual disturbance, and weakness [7]. Reduced blood sugar and the subsequent symptoms have been observed across a variety of populations following strenuous exercise, including both professional and amateur athletes [8–10]. Existing literature also indicates glucose does not directly affect hydration status. A study by Hargreaves and colleagues reported that after 40 minutes of exercise in the heat, continuous administration of glucose did not alter plasma volume or hydration status [11]. These results may be attributes to experimental methodologies, such as timing of fluid replacement and environmental conditions (i.e., temperature and exercise duration), both of which can impact fluid homeostasis.

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