Investigators performed patient enrollment, monitored by an interactive voice response system. Stratified block randomization was computer-generated centrally using 8 strata and a block size of 16. Patients were stratified by previous TNF antagonist status (failure/no experience), concomitant oral corticosteroid use (yes/no), and concomitant immunosuppressive use (yes/no). Randomization schedules were generated by Takeda Pharmaceuticals International Co (Cambridge, MA), and each treatment-qualified patient received a unique randomization number used to provide

treatment assignments for dose preparation via the interactive voice response system. Saline bag covers and labels maintained blinding. Only the study learn more site pharmacist was aware of treatment assignments. Patients (at 107 sites in North America, Selleck Tenofovir Europe, Asia, Africa, and Australia) were between 18 and 80 years of age and had a diagnosis of CD with known involvement of the ileum and/or colon at 3 or more months before enrollment (Table 1). Diagnosis was based on clinical and endoscopic evidence, corroborated by results of histopathology (diagnosis occurred at ≥6 months before enrollment if a histopathology report was unavailable).

All patients had CD that was moderately to severely active, as determined by a CDAI score of 220–400 points within 7 days before enrollment, and one of the following: a screening C-reactive protein (CRP) level greater than 2.87 mg/L,25 a colonoscopy within the previous 4 months that documented ulcerations, or a fecal calprotectin level greater than 250 μg/g stool during screening in conjunction with features of active CD supported by small-bowel imaging. All patients had experienced an inadequate response, loss of response, or intolerance to TNF antagonists, immunosuppressives, all or corticosteroids within the past 5 years (Supplementary Table 1). Exclusion criteria included previous vedolizumab, natalizumab, efalizumab,

or rituximab exposure, as well as concurrent lactation or pregnancy, unstable or uncontrolled medical condition, major neurologic disorder, general anesthesia within 30 days, or planned major surgery during the study. Previous malignancies with the exception of certain cancers for which the recurrence risk after adequate treatment is expected to be low (eg, nonmetastatic basal cell and squamous cell skin cancers, cervical carcinoma in situ) resulted in exclusion, as did active drug or alcohol dependence and active psychiatric disease or other complicating factor(s) that could result in nonadherence to study procedures. The primary efficacy analysis was restricted to patients with prior TNF antagonist failure (ie, TNF antagonist–failure population, prespecified as ∼75% of enrolled patients), among whom the proportion of patients in clinical remission at week 6 was assessed (Figure 2).

in the economic model. The total catch

feeds then back into the biological model affecting the stock dynamics. The two sub-models have been specifically estimated and calibrated for the NEA cod fishery using data from the time period 1978–2007 (Table 1). The biological sub-model is based on a previously published model [31], which is parameterized for NEA cod. The biological model is individual-based, age- and length-structured, and describes an individual’s life-cycle from birth to death through annual processes of maturation, growth, reproduction, and mortality [31] and [32]. This model includes stock-specific estimated relationships for maturation tendency, density-dependent growth, stock–recruitment, and energy allocation. Individuals NLG919 clinical trial vary in age, body size, and maturation status, which are tracked on an annual basis. Unlike some previous

models [31], [32], [33] and [34], this model reduces complexity by keeping life-history traits monomorphic and by not considering their evolutionary dynamics. The included life-history traits describe an individual’s maturation tendency, growth, and reproductive investment. All model parameters are based on empirical data (Table 1). Each year, the tendency that an immature individual will mature depends on a probabilistic maturation reaction norm [35], [36] and [37], which describes maturation probability pm(a,l) as a function of age a and body length l. This probability equals 50% at the length Non-specific serine/threonine protein kinase at age lP50(a)=i+sa, and is given by equation(1) pm(a,l)=1/(1+exp(−(l(a)−lP50(a))/c))pm(a,l)=1/(1+exp(−(l(a)−lP50(a))/c)) DZNeP The probabilistic maturation reaction norm thus has intercept i   and slope s  . Its width w  , spanning from the 25% to the 75% percentile of maturation probability [31] and [32], is determined by the parameter c   where c=w/[logit(pu)−logit(pl)]c=w/[logit(pu)−logit(pl)],

and pu and pl are the probabilities for the upper and lower bounds of the PMRN. The growth rate of individuals depends on the total biomass of the population, to account for reductions in growth expected when population density is high and resource availability consequently is low. Data from 1978–2009 on annual growth increments g  D,t in year t  , together with data on total stock biomass B  t of individuals aged 3 years or older in year t  , were used to estimate the two parameters g   and x   of an exponential relationship for density-dependent growth, equation(2) gD,t=gexp(−xBt),gD,t=gexp(−xBt),where g   is the maximum growth increment (realized at B  t=0) and x   determines the strength of density dependence in growth ( Table 1). For immature individuals, denoted by a superscript I, body length in year t   is determined by their length in the previous year enhanced by the corresponding growth increment, ltI=lt−1I+gD,t−1.

ostreatus was cultivated in substrates with seed cake added to different proportions of eucalypt sawdust, corncob, eucalypt bark and coffee husk. The purpose of adding these agroindustrial residues was to balance the carbon

and nitrogen ratio, which may stimulate the mycelial growth ( Nunes et al., 2012). The substrate compositions that were selected for this study were based on the results of these previous experiments were jatropha seed cake (Sc), Sc + 10 (g/100 g) of eucalypt sawdust (ScEs), Roxadustat molecular weight Sc + 10 (g/100 g) of eucalypt bark (ScEb) and Sc + 30 (g/100 g) of coffee husk + 30 (g/100 g) of rice bran (ScCh). In these substrates, the isolate Plo 6 had better biomass production and greater degradation rate of lignocellulosic compounds when compared to other tested substrates ( Da Luz, 2009). The substrates were humidified with water at 75% of the retention capacity and 1.5 kg of each substrate was placed in polypropylene bags. Next, the bags containing the substrates were autoclaved at 121 °C for 2 h. After sterilization, the substrates were inoculated with 70 g of spawn and incubated at 25 °C for 60 d. Samples for analyses

were taken at intervals of 15 d. Phytase activity (myo-inositol hexakisphosphate phosphohydrolase, EC 3.1.3.8) was determined using Taussky–Schoor PLX-4720 concentration reagent according to Harland and Harland (1980). To extract the enzyme, 3 g of the substrate was transferred to Erlenmeyer flasks (125 mL) containing 10 mL of sodium chloride (1 g/100 mL). The flasks were kept in a shaker for 1 h at 100 rpm, and the extracts were filtered through Millipore membranes (Whatman 1). The filtrate was centrifuged for 5 min at 2000 × g. The reaction to determine phytase activity contained 100 μL of the filtrate and 1 mL of sodium phytate solution (0.5 g/100 g, Sigma). This reaction was incubated in a water bath at 60 °C for 10 min, and then 1 mL of trichloroacetic acid (10 g/100 mL) and 5 mL of Taussky–Schoor

reagent were added. The phosphorus content was determined with a spectrophotometer (Thermo, Evolution 60) at 500 nm. The standard curve for phosphorus quantification was made using dibasic potassium phosphate (Sigma) with concentrations ADP ribosylation factor ranging from 0.004 to 0.02 g/100 mL. One unit of phytase was defined as the amount of enzyme required to release 1 μmol of inorganic phosphate per min from sodium phytate at 37 °C. To determine phytic acid content, 3 g of each substrate was transferred to Erlenmeyer flasks (125 mL) containing 25 mL hydrochloric acid (4 g/100 mL, Vetec). These flasks were kept in a shaker for 16 h at 220 rpm. The supernatants were transferred to centrifuge tubes (50 mL) containing 1 g of sodium chloride (Vetec), centrifuged at 1000 × g for 20 min and frozen at −20 °C for 30 min. After thawing, the supernatants were centrifuged under the same conditions and filtered through Millipore membranes (Whatman GF/D, 4.7 cm). The filtrate (1 mL) was diluted in 24 mL of deionized water.

Generally speaking, ligands act to buffer the dissolved Fe concentration by restricting its loss via scavenging and precipitation. Due to their role in governing the residence time of Fe in the ocean, varying the assumptions regarding the concentrations of ligands has significant impacts on atmospheric CO2 (Tagliabue et al., 2014). The electrochemical methods used to determine oceanic ligand concentrations

often discriminate between two ligand classes, a strong and weak ligand pool (Rue and Bruland, 1995). Surface water ligand concentrations are variable (from 0.2 to > 10 nmol L− 1) and their sources reflect the combination of a number of different production pathways (see: Gledhill and Buck (2012) and references therein). For example, the Fe stressed biota Selleck Pifithrin �� can ‘actively’ produce strong binding ligands (so-called L1 ligands with a conditional stability constant similar to known bacterial siderophores) to complex Fe (Wilhelm and Trick, 1994 and Gledhill et al., 2004). However, while recent work has identified siderophore-like groups in seawater (Macrellis et al., 2001 and Mawji et al., 2008), their concentrations are very low relative to the total ligand concentration. But there are also other pathways that may explain the observed covariance of ligands 17-AAG nmr with

phytoplankton (Gerringa et al., 2006): Weaker binding ligands can be produced by ‘passive’ processes linked to exudates

(such as exopolysaccharides, Hassler et al., 2011) or the cellular debris arising from mortality and heterotrophic activity (e.g., the chlorophyll breakdown product phaeophytin or hemes and other porphyrins, Hutchins et al. (1999)), similar to dissolved organic carbon (DOC) L-NAME HCl cycling. Indeed, ligand concentrations have increased following enhanced biological activity in Fe addition experiments (e.g., Boye et al., 2005) and in response to increased grazing rates in shipboard experiments (Sato et al., 2007). Further support for ‘passive’ production similar to DOC comes from Mediterranean mesocosm observations of a strong covariance between ligands and DOC (Wagener et al., 2008). Away from the surface, vertical profiles of ligands from the Southern (e.g., Ibisanmi et al., 2011) and Atlantic Oceans (e.g. Mohamed et al., 2011) show elevated concentrations of ligands at mid water depth coincident with macronutrient maxima, implying a remineralisation source (Wu et al., 2001). This is supported by the first measurements of ligand production rates from particle degradation during incubation experiments (Boyd et al., 2010) and in situ correlations between nitrate (NO3−) or phosphate (PO43−) and Fe solubility (indicative of ligand concentrations, e.g. Schlosser and Croot (2009)).

Commercial carriers Kaldnes™ K1 (Anoxkaldnes™, Sweden), made of high density polyethylene (density 950 kg/m3; surface area 500 m2/m3), were used as inert supports. The carriers were autoclaved at 121 °C for 20 min until used. Sunflower (Helianthus annuus) seeds were obtained from a local market Nutlin-3 and the shells were collected after normal human consumption of the seeds. The sunflower seed shells (SS) were autoclaved at 121 °C for 20 min before use. The chemical

composition of the SS according to Gullón et al. [6] is 23 ± 0.15% glucan, 29.4 ± 0.0016% klason lignin, 25.8 ± 0.07% hemicelluloses, 5.40 ± 0.03% extractives and 4 ± 0.15% ash. Cultivation was carried out in cotton-plugged Erlenmeyer flasks (250 mL) containing 3 g of Kaldnes™ K1 carriers or 1.5 g SS, according to the experiment, and 20 mL of culture medium. The culture medium composition was the same as that of the medium M1 described in Rodriguez-Couto [16] and consisted of 10 g/L glucose, 20 g/L yeast extract, 0.9 g/L

(NH4)2SO4, 2 g/L KH2PO4, 0.5 g/L MgSO4·7H2O, 0.1 g/L CaCl2·2H2O, 0.5 g/L KCl and 0.5 g/L thiamine hydrochloride in 0.05 M citrate–phosphate buffer (pH 4.5). To boost laccase production 0.5 mM Cu+2 was added to the cultures on the 3rd cultivation day [18]. Inoculation was carried out directly in the Erlenmeyer flasks. Three agar plugs (diameter, 7 mm), from a 7-day grown fungus on PDA, per Erlenmeyer were used as inoculum. The Erlenmeyer flasks were incubated statically under an air atmosphere at 30 °C and in complete darkness. Glucose consumption, SCH727965 measured as reducing sugars, was determined with the dinitrosalicylic acid reagent (DNS) using d-glucose as a standard according to the method described by Miller [11]. Laccase activity

was spectrophotometrically determined as described by Niku-Paavola et al. [12] with 2,2′-azino-di-[3-ethyl-benzo-thiazolin-sulphonate] (ABTS) as a substrate. One activity unit (U) was defined as the amount of enzyme SSR128129E that oxidised 1 μmol of ABTS per min. The activities were expressed in U/L. Manganese-dependent peroxidase activity was spectrophotometrically assayed at 468 nm by the method of Kuwahara et al. [9]. The reaction was started by adding 0.4 mM H2O2. One activity unit (U) was defined as 1 μmol of 2,6-dimethoxyphenol oxidised per minute and the activities were expressed in U/L. Lignin peroxidase activity was spectrophotometrically determined at 310 nm according to Tien and Kirk [22]. The reaction was starting by adding 0.4 mM H2O2. One activity unit (U) was defined as 1 μmol of veratryl alcohol oxidised in 1 min and the activities were reported as U/L. The dyes used were the textile dyes Bemaplex Navy M-T (CI Acid Blue 193), an acid chromium-complex dye and Bezaktiv Blue BA (CI Reactive Blue 235), a reactive copper-complex dye. They were a kind gift of CTH R. Beilich GmbH (Barcelona, Spain). They were used as received, without further purification.

4. The combined discharge rates

are shown in Fig. 5. An accumulation-balancing rate of 107 Gt/yr is given by Rignot et al. (2008). The effect of increased snow accumulation on Antarctica during the immediate future (as indicated by observations Church et al., 2013) would mean a larger potential value for D. Measurements from Rignot and Kanagaratnam, 2006 and Rignot et al., 2008 are shown as well in Fig. 5. More recent overviews ( Shepherd and Wingham, 2007 and Shepherd et al., 2012) show considerable variation in the Greenland and Antarctic mass balance measurements. Because the sampling was performed during different periods and does not include all ice sheets, we have left these from further consideration. The progression of D   in Fig. 4 shows the collapse of the West-Antarctic

ice sheet. The discharge rate Adriamycin increases dramatically with this event. With the ice sheet gone, calved icebergs drift more easily. We expect basal melt to decrease then. On the other SCR7 datasheet hand, more land ice is in contact with the ocean, which should increase the absolute amount of melt taking place. Without any way of quantifying either effect, we suggest that after a collapse event the basal melt amount returns to pre-collapse levels. The expression becomes equation(14) Nsi(t)=μi·Dsi(t)t⩽30μi·Dsi(30)t>30Gt/yrfor the WAIS (region i), where μW=0.30μW=0.30. Similar considerations to those above lead us to keep the amount of basal melt steady at the 2030 levels for the other two regions, which then give the exact same form as Eq. (14) with the appropriate μμ values ( Table 2). Far deposition is allocated to all mass loss not already claimed by basal melt. The expression for Antarctic

F   is then simply equation(15) Fs(t)=(1-μs)·Ds(t)t⩽30Ds(t)-μs·Ds(30)t>30Gt/yr.for all three regions with μsμs replaced by the appropriate basal melt fraction and rsrs the corresponding discharge rate. Table 4 gives a summary of the melt scenario features on which our projections are based. In Table 5 a break-down of mass loss expressed as sea-level equivalent is given. We can compare with some other severe scenarios, see Fig. 6. The most recent scenarios are by Pfeffer et al., 2008 and Katsman et al., 2011. A projection close to Palmatine the values given by Pfeffer et al. (2008) as upper bounds would tax the rate of retreat of the tidewater glacier to nonphysical limits. The lower bound from Fettweis et al. (2013) only takes meltwater into account. The projections for ice discharge dominate this by an order of magnitude. To illustrate the effect of the freshwater protocol outlined above, we ran a RCP8.5 experiment with the CCM EC-Earth (Hazeleger et al., 2010). One simulation was run without the extra freshwater forcing applied (control) and one with additional freshwater forcing included (forced) to allow for a sensitivity experiment. The control run is part of the CMIP5 archive and both runs use the RCP8.

g., Huttenlocher & Dabholkar, 1997). One interpretation of our finding of increased grey matter in the left posterior

IFG (i.e., Broca’s area) in SLI is that cortex in this region has not undergone the normal maturation processes at the same rate as in the sibling or typical groups. Whether this is the cause of the lack of functional specialisation (and activation) of this area, or a consequence BYL719 price of it, remains uncertain. In typical development, the IFG is linked with the STS/G via at least two streams that are important for auditory language processing in the left hemisphere (Rauschecker & Scott, 2009). In our study of SLI, the reduced grey matter and reduced activity in the STS/G occurred bilaterally and was specific to language processing and not more general auditory processes, given similar between group activations in the Reversed Speech condition. Regular firing of neural pathways leads to strengthening,

maintenance, and building of connections, so reductions in volume Venetoclax manufacturer to the STS/G may derive from underactivity in this area (synaptic elimination; Huttenlocher & Dabholkar, 1997), potentially driven by a system that is less stimulated by speech specific stimuli. Alternatively, a causal hypothesis is that experience has not altered the cortex and that less grey matter in the STS/G underpins the language difficulties. Longitudinal investigations have been informative regarding other developmental disorders and could help distinguish these possibilities (Giedd & Rapoport, 2010). The patterns of activation in the SLI group are more heterogeneous relative to both the unaffected siblings and typical MycoClean Mycoplasma Removal Kit groups. This is clearly visible in the laterality indices (see Fig. 6) with a greater number of SLI individuals demonstrating atypical lateralisation (i.e., more bilateral to rightward). This is consistent with the majority of existing research (Bernal and Altman, 2003,

Chiron et al., 1999, Lou et al., 1990, Ors et al., 2005, Shafer et al., 2000 and Whitehouse and Bishop, 2008) and suggests that the reduced activity noted at the group level is not the defining feature. It is worth noting that only one SLI participant shows reliably right-lateralised speech for the comparison of Speech with baseline and with Reversed Speech and for both the frontal and the temporal lobe areas considered. Another left-handed participant with SLI shows more left-lateralised activation for Reversed Speech than Speech resulting in a rightwards LI for the Speech contrast with Reversed Speech. Finally, a few of the right-handed controls (TYP and SIB) and one right-handed individual with SLI also show a pattern of rightwards lateralisation. Further research is needed to examine whether the increased variability in SLI is also seen from stimulus to stimulus or session to session. Our implementation of the covert naming task was designed to be easy so that all participants could provide equivalent behavioural responses.

In this study, two paths were explored. First, the correlation between the behavioral indicators was used to infer the coefficients (or loadings) of these indicators and the relationship between mice. Second, the correlation between

mice was used to infer the relationship between the behavioral indicators. The Pearson’s correlation coefficient between the indicators was favored over the covariances to level the impact of indicators despite differences in magnitude. For dimension reduction purposes, the components or scales considered were limited to those that explained most and together accounted for at least 70% of the variance of the original measurements. The relationship between sickness and depression-like indicators and the relationship between mice within and across BCG-treatment groups was investigated through the evaluation this website of the coefficients of the variables in the first principal components together with the visualization of the relative location of the mice from different BCG-treatment groups along pairs of major principal components. An analysis comparable to PCA was implemented using multidimensional scaling. mTOR inhibitor This approach relied on the distances between items and double-centering of the distance matrix instead of correlations used in PCA. Thus, the consistency between MDS and PCA outputs depended on the properties

and structure of the original measurements. Implementation of PCA includes PROC PRINCOMP

and the princomp function in SAS and R, respectively. Implementation of MDS includes PROC MDS and the cmdscale function in Ribociclib cost SAS and R, respectively. Supervised learning approaches that account for the known BCG-treatment assignment were used to develop decision rules that assigned mice to classes (i.e. BCG-treatment groups) with maximum possible accuracy (Zuur et al., 2007). Supervised prediction of mice classification into BCG-treatment groups was based on weight change between Day 0 and Day 2, weight change between Day 2 and Day 5, locomotor activity, rearing, tail suspension immobility, forced swim immobility and sucrose preference. Consideration of the coefficients of the behavioral indicators in the classification functions offered insights into the relationship between indicators. Two complementary supervised learning methods, linear discriminant analysis (LDA) and k-nearest neighbor (KNN), were evaluated. In LDA, the resulting indices of the behavioral indicators offered the maximum distance between the observed classes and the minimum variation within class. Mice were assigned to the class that was most proximal to the LDA index value. In the KNN approach, mice were assigned to the class of all or most of the closest neighboring mice based on the Euclidean distance. The LDA and KNN approaches are implemented in the PROC CLUSTER and LDA and KNN functions in SAS and R, respectively.

Some examples are given of its current application in clinical use, thereby pointing out some pearls and pitfalls. In addition, learn more new techniques for MRS and their

potential for and impact on clinical use are discussed. Daniel Louis Polders and Johannes Marinus Hoogduin Chemical exchange saturation transfer (CEST) measurements hold great promise as the next step in magnetization transfer imaging and possibly allow for in vivo quantification of many clinically relevant parameters, including pH, temperature, and amide concentration. Therefore, it is a valuable method to add to the MR imaging toolbox. The aim of this article was to review the methods for the acquisition of CEST data and necessary postprocessing. CEST research is very much a field still in development, and initial R428 chemical structure explorations in clinical applications are shown to illustrate the potential of CEST as a new contrast mechanism. Dow-Mu Koh, Nina Tunariu, Matthew Blackledge, and David J. Collins Whole-body diffusion-weighted (DW) imaging is

a recent development. The image contrast is based on differences in mobility of water between tissues and reflects tissue cellularity and integrity of cell membranes. The tissue water diffusivity is quantified by the apparent diffusion coefficient. By performing imaging at multiple imaging stations, whole-body DW imaging has been applied to improve tumor staging, disease characterization, as well during as for the assessment of treatment response. Information from DW imaging studies could be combined with those using PET imaging tracers to further refine and

improve the assessment of patients with cancer. Sjoerd B. Vos, Chantal M.W. Tax, and Alexander Leemans Diffusion magnetic resonance (MR) imaging is sensitive to microstructural changes in tissue. Diffusion tensor MR imaging, the most commonly used method, can estimate the magnitude and anisotropy of diffusion. These tensor-based diffusion parameters have been shown to change in many neuropathologic conditions. Recent advances in diffusion MR imaging techniques may provide quantitative measures that are more specific to the underlying tissue change. Diffusion MR imaging data can also be used to provide fiber tractography. In this article, an overview of the basic principles of these techniques is provided, and their current and potential uses in clinical research and clinical practice are discussed. Jill B. De Vis, Esben T. Petersen, and Jeroen Hendrikse Arterial spin labeling (ASL) magnetic resonance (MR) imaging enables evaluation of perfusion. Because of its noninvasiveness, this technique is particularly useful in vulnerable patient populations such as infants or patients with kidney disease. This article describes the commonly used ASL techniques and gives an overview of clinical applications.

Here we describe an in vivo and ex vivo simulated papilla by using live pig stomach and rectum easily created by injection of 0.4% hyaluronate solution that allows ES and EP. A 0.4% hyaluronate solution could create hemispheroidal bulgings similar to a human papillae. This study was performed in accordance with the rules for the protections of animals and approved by the Animal Ethical and Welfare Committee of Tokyo Medical University. A live 36-kg mixed Landrace and Yorkshire pig was

used as the animal model. www.selleckchem.com/products/MS-275.html The animal was fasted 24 hours before the procedure. Intravenous ketamine (0.2 mg/kg) and 0.2% xylazine (Selactar; Bayer Yakuhin, Tokyo, Japan) (0.1 mg/kg) were used to induce general anesthesia, which was maintained by using 2% to 5% isoflurane. Atropine (1 mg) was administered to reduce

secretions. We used ex vivo methods as used for training in endoscopic submucosal dissection (ESD).14 We prepared a metal container with normal saline solution that stabilizes the pig stomach and allows electrocautery devices to be used (Johnson & Johnson, Tokyo, Japan) (Fig. 1). An overtube was sutured to the gastric antrum, allowing insertion of the duodenoscope. A resected porcine rectum was placed in an ESD container that allows the use of electrical cautery devices (ERBE Elektromedizin GmbH, Tubingen, Germany) (Fig. 2). One experienced ERCP endoscopist (T.I.) created all blebs. MucoUp, 1.5 to 2.5 mL (20 mL/V, 0.4% hyaluronic acid diluted with sodium chloride) (Johnson & Johnson) was injected submucosally by using a 25-gauge sclerotherapy needle (Hiflow, H-type; Top Co Ltd, Tokyo, Ribonucleotide reductase Japan) to create a mucosal bleb as a simulated major duodenal Tenofovir papilla mound (Fig. 3, upper left). For the stomach model, the solution was mixed with 0.1% indigo carmine. As an alternative to MucoUp, 1% hyaluronic acid (Bioventus LLC, Durham, NC) can be diluted to 0.4%. For ES training, 3 more injections were made in the lesser and greater curvature and the anterior and posterior walls of the proximal gastric body of the in vivo

and ex vivo stomach models. An approximately 2-mm orifice was made in the mucosal bleb by using a needle-knife (KD-1L-1; Olympus Medical Systems, Tokyo, Japan) to simulate a papillary os (Fig. 3, upper right). In the ex vivo rectum model, the mucosal bleb was circumferentially and longitudinally created by means of to-and-fro movements of the duodenoscope and rotation of the box containing the pig rectum. In the in vivo model, ERCP was performed with the animal placed in the supine position and by using a conventional therapeutic duodenoscope (ED-530X T8; Fujifilm, Tokyo, Japan). A standard grounding pad was placed under the mid-dorsum of the animal. In the ex vivo stomach or rectum model, a conventional therapeutic duodenoscope (TJF-260V; Olympus Medical Systems) was used for ES and EP. Electrosurgical generators (VIO300D and ICC200; ERBE Elektromedezin, GmbH) were used to perform ES.