Each of these second-order stratum factors can be measured by means of two or more subtests constructed by means of different approaches to automatic item generation (for an overview: Arendasy and Sommer, 2012, Arendasy and Sommer, 2013 and Irvine and Kyllonen, 2002). All subtests were calibrated by means of the 1PL Rasch model and exhibited good construct and criterion validities (for an overview: Arendasy et al., 2008). In order to obtain a screening measure of psychometric g the following four subtests were completed: figural-inductive

reasoning (FID), arithmetic Raf inhibitor review flexibility (NF), verbal short-term memory (VEK) and word meaning (WB). The subtests were selected to cover a broad range of stratum two factors to avoid construct-underrepresentation www.selleckchem.com/products/abt-199.html in estimating psychometric g (cf. Major, Johnson, & Bouchard, 2011). All subtests were presented as computerized adaptive tests with a target reliability corresponding to α = .60. Factor loadings obtained with a representative Austrian norm sample were used to estimate the g-factor score based on the subtest results. The factor scores were further converted into IQ scores using the Austrian norm sample. The DTI scans were collected on a 3-T Siemens Magnetom Skyra Scanner (Siemens Medical Systems, Erlangen, Germany), using a 32-channel head coil. A single shot echo planar imaging with a twice-refocused

spin echo pulse sequence, optimized to minimize eddy current-induced image distortions (Reese, Heid, Weisskoff, & Wedeen, 2003) was performed on all subjects with the following parameters: TR/TE = 6600/95 ms, voxel size 2 × 2 × 2 mm, FOV = 240 mm, slices = 50, b = 1000 s/mm2, diffusion directions = 64. To minimize movement artefacts, the head of the subject was firmly fixed with cushions.

All images were investigated to be free of motion, ghosting, high frequency Lck and/or wrap-around artefacts at the time of image acquisition. Diffusion tensor imaging analysis was performed using FDT 3.0 (fMRIB’s Diffusion Toolbox V3.0) and TBSS (Tract-Based Spatial Statistics; Smith et al., 2006), part of FSL 5.0.6 (Smith et al., 2004). First, raw images were preprocessed using Eddy Current correction and a binary brain mask was created using BET (Brain Extraction Tool; Jenkinson, Pechaud, & Smith, 2005). Eigenvalues (λ1, λ2, λ3) and eigenvectors (ε1, ε2, ε3) of the diffusion tensor matrix for each voxel were computed from the DTI volumes for each subject on a voxel-by-voxel basis using established reconstruction methods ( Basser & Jones, 2002). Thus, maps for fractional anisotropy (FA), axial diffusivity (AD = λ1), and radial diffusivity (RD = λ2 + λ3/2) could be generated to increase interpretability of our findings. All subjects’ FA data were then aligned into a common space using the nonlinear registration tool FNIRT ( Andersson et al., 2007a and Andersson et al., 2007b), which uses a b-spline representation of the registration warp field ( Rueckert et al., 1999).

5 h after eating, drinking, or tooth cleaning. Saliva samples were collected in sterile 50 mL polypropylene tubes, chilled in an ice bath or frozen at −20 °C. After 500 mL saliva had been collected, it was pooled and centrifuged (30 min, 4 °C, 27,000 × g); the supernatant was pasteurized (60 °C, 30 min) and re-centrifuged in sterile tubes. The resulting supernatant was stored into sterile 50 mL polypropylene tubes at −80 °C. The efficiency of the process was assessed Selleck NLG919 by plating processed saliva samples onto BHI agar; after 72 h at 37 °C no CFUs were observed on incubated

plates. Streptococcus mutans biofilms were grown on 96-wells microtiter plates through a methodology developed by Stepanovicet al. 33 and Islam et al. 34 with some modifications. In a first moment, 100 μL of processed saliva plus 100 μL of carbonate buffer pH 9.3 were added to each well and incubated at 4 °C for 2 h. After this period the wells were washed tree times with saline phosphate buffer pH 7.6. In sequence,

100 μL of sterile BHI were distributed in a 96-wells polypropylene tissue culture plates HA-1077 in vitro (Orange Scientific®, Braine-l’Alleud, Belgium) (with flat-bottom) followed by placement of 100 μL of DC in concentrations that were prepared using a procedure similar to the one used in the antimicrobial activity tests (MIC) with same initial bacterial cells concentration. All the plates were incubated at 37 °C, CO2 10%, during 24 h for biofilm development. After biofilm growth in the presence or absence of CD concentrations, the content of each well was removed and the biofilms were washed twice RG7420 in vitro with 200 μL of sterilized water, to remove cells weakly adhered. The attached biofilm mass was quantified using crystal violet staining.35 Briefly, the plates containing

the biofilms were left to air dry for 30 min, and 200 μL of a solution sodium acetate/formalin 2% were distributed in each well, in order to fix the adhered cells, and left for 15 min. After this time, the solution sodium acetate/formalin 2% was removed and 200 μL of crystal violet 1% (Gram colour-staining set for microscopy – Merck©) were added to each well for 5 min. Following the staining step, the washing procedure, with sterile water, was repeated and the plates were left at room temperature for 1 h. To re-solubilize the dye bounded to biofilms, 200 μL of 95% ethylic alcohol (Merck©) were added to each well and submitted to agitation for 15 min. The crystal violet (CV) solutions obtained were transferred to a new sterile flat bottom 96-wells plate and the optical density of the content was measured using a microtiter plate spectrophotometer (Biotrak II Plate Reader – Amersham Biosciences©) at 570 nm. The biofilms were generated as described above and after 24 h of incubation at 37 °C, CO2 10%, the plates were washed twice using sterile distilled water to remove cells weakly adhered.

These sequences were learn more relatively short, with an average length of 102 bases. Oceanic environments contained distinct phage groups that

reflected the composition of the bacterial community in that niche, as well as some phages that were common to all or some environments. The diversity and richness of phage populations were different in the 4 environments described. These data suggest that phage communities in different ecologic niches will differ with respect to the environment in which they are found, in part reflecting the resident bacterial population and its functions. This work also suggests that the study of the viral populations in a variety of human body habitats will reveal an unappreciated diversity of common and specialized viruses. Early sequence-based analyses of this website the virome in samples from humans focused on bacteriophage populations. Bacteriophages influence their host bacteria and contribute genes that affect the structure and functions of microbial communities.35 and 36 Therefore, bacteriophages may be both important effectors and indicators

of human health and disease. In the first characterization of a bacteriophage community in a human stool sample, shotgun sequencing of 532 cloned viral DNA fragments from the stool of a healthy adult revealed that the majority of phage sequences were novel.37 The data suggested rich diversity of bacteriophage sequences, with approximately 2 to 5 times the number of bacteriophage genotypes as predicted bacterial genera in a stool community (∼1200–2000 genotypes predicted).37 In contrast, a simple but dynamic bacteriophage community (∼8 genotypes predicted) was observed by sequencing 477 viral DNA clones

from feces of a 1-week-old infant.38 These studies suggest that the diversity of bacteriophages in the gut expands as the bacterial community is established,38 but a larger group of adults and infants will need to be sampled and compared to validate this conclusion. In fact, more recent studies that include samples from more individuals and use deeper sequencing indicate that the richness of bacteriophage populations in stool communities varies greatly among adults. PIK3C2G In one study, Reyes et al39 found ∼10 to 984 genotypes per sample from 12 individuals. In another study, Minot et al40 found ∼19 to 785 genotypes per sample from 16 individuals. Thus, although important changes in the virome may occur as the infant gut matures, it is likely that the changes are more complex than simply increased diversity. The insights into the human virome (particularly the bacteriophage component) provided by studies by Reyes et al39 and Minot et al40 were made possible in large part because of newer sequencing technologies, especially the Roche 454 pyrosequencing platform. Consistent with the earlier studies, most viral sequences obtained were novel.

The joint moments generated during functional activities did not change with increasing age. The requirements of the tasks may remain the same and this is reflected in the lack of change in joint moments across the three age groups of older adults. During CR, carried out with a standard height chair (460 mm) the mean knee extensor demand was 72.8% and the hip extensor demand was 88.2%. High knee extensor relative effort reaching maximal capacity has been reported for older adults while performing a sit to stand task (Hortobágyi et al., 2003 and Hughes

et al., 1996). The present study also investigated the stand-to-sit phase and our findings suggest that CSt is equally demanding producing high extensor demands on knee (69%) and hip (74%) joints of older adults. In contrast the knee flexor and hip flexor demands during CR and CSt were low and did not appear to pose a problem. PF-01367338 chemical structure The results from the current study demonstrate that rising from a chair and sitting down are particularly demanding tasks for the older adults Selleck Rigosertib requiring a higher percentage of knee extensor and hip extensor muscle strength to perform the activity. Stair negotiation placed a high level of demand on the knee extensors with demand in SA reaching isometric capacity (103%) and during the eccentric phase of SD exceeding it by 20% (120%). Hip extensor demand was high during SA (89%)

and the knee flexors also experienced a high level of demand during SD. The FD of knee extensors was higher during SD than SA. Hip flexor demands were relatively low for both SA (42.7) and SD (43.3) while knee flexor demand was higher for SD (73.3) compared to SA (42.2). Hence, SA placed a high demand on the knee extensors and hip extensors with relatively low demand on knee flexors and hip flexors. On the other hand, SD was found to be more demanding on the knee extensors and knee flexors than SA. The FD for both SA and SD were

higher in the present study compared to the relative effort values reported previously (Hortobágyi et al., 2003, Reeves et al., 2008 and Reeves et al., 2009). The demand values in the present study were higher for both activities than those reported earlier (Reeves et al., 2008 and Reeves et al., 2009), where concentric and eccentric muscle Protirelin strength was used to assess maximal capabilities at the knee and ankle joint. The higher FD values noted in the current study could be explained by differences in the method adopted for assessing maximal muscle strength. Our muscle strength values were obtained through isometric tests which is likely to reduce the maximal joint moments used in the divisor of the FD ratio for activities involving eccentric muscle activity, therefore increasing the relative effort or FD at each point in time. Also we used isometric strength through joint range rather than the peak point in the range.

, 2006). We have confirmed that the N450 is most Tanespimycin cost representative of general conflict detection (Szucs and Soltész, 2010a, Szucs and Soltész, 2010b, West et al., 2004 and West and Schwarb, 2006). Previously the N450 had been ambiguously related to both response conflict (Liotti, Woldorff, Perez, & Mayberg, 2000) and semantic conflict (Rebai et al., 1997). As we found no significant differences in the mean amplitude of the N450 in the SC and RC conditions we conclude that the N450 is

most sensitive to general conflict (Szucs and Soltesz, 2012, Szucs et al., 2009b and West et al., 2004). Our second objective was to map maturational changes in the N450. There were no differences between the adolescent and young adult groups in the topography of the N450 during congruent and SC conditions. However during the RC condition the topography of the N450 was focused on the right scalp in adolescents

and on the left scalp in young adults. In adults a similar left hemisphere effect during the N450 has been found in previous Stroop studies (Chen et al., 2011, Jongen and Jonkman, 2008 and Lansbergen et al., 2007). Adleman et al. (2002) found increased left hemisphere activation in adults when compared to adolescents specifically in the left middle frontal gyrus during colour word Stroop conflict. The left middle frontal gyrus has been associated with both word generation (Thompson-Schill, D’Esposito, Aguirre, & Farah, 1997) and generating colour names (Martin, Haxby, Lalonde, Wiggs, & Ungerleider, 1995). The left scalp activation found find more in adults could represent the increased use of a verbal strategy to resolve conflict. In adolescents the topography of the N450 was focused on the right scalp. Right scalp activity has also been observed in adolescence during a Stop task and a Go-No/go task (Rubia et al., 2000 and Stevens et al., 2007) as well as during a Stroop task in children (previously unrecorded in adolescence) (Jongen & Jonkman, 2008). These authors have concluded that this right scalp activity is indicative of improved performance

strategy. Orotidine 5′-phosphate decarboxylase For example Stevens et al. (2007) found that in adolescents increased frontal–parietal circuit activity was related to good performance however this was not found in adults. Therefore increased right scalp activation may recruit frontal–parietal circuitry and allow for improved performance. In terms of middle age adults a stimulus conflict deficit was expected. However there were no differences in the topography of the N450 during stimulus conflict detection for young adults and middle age adults. Nevertheless topographical examination of the N450 during the RC condition reveals dispersed and increased negative amplitude with a right scalp shift. In a middle age group (41–61-year olds) Mager et al. (2007) similarly found increased amplitude of the N450. Mathis et al.

(2012). The core of the Pelops anticyclonic eddy (Figures 2f–j) displays insignificant warming relative to the surrounding area, indicating an insignificant change in the intensity of the Pelops eddy. Moreover, the grouping of eddies in the western Levantine basin (Millot, 2005 and Poulain et al., 2012) is less obvious, as there is only one anticyclonic eddy south of Crete in autumn (warm core, 21.8 °C). The core of this anticyclonic eddy displays more significant (insignificant) warming than does the surrounding area in summer, autumn and winter (spring), indicating the dominance of this eddy

and suggesting that it may become more intense in the future. In addition, about three obvious anticyclonic eddies are attributable trans-isomer nmr Dolutegravir supplier to the seasonal warming gradient over the western Levantine, especially in summer and autumn, indicating that the western Levantine eddies may become more significant in the

near future. The eastern Levantine eddies (Poulain et al. 2012) are not obvious from the seasonal average SST gradient, as a 1/4° projection grid was used. Poulain et al. (2012) described the eastern Levantine eddies using altimetry data with 1/8° gridded resolutions. There is an obvious grouping of eddies in the eastern Levantine attributable to the seasonal warming gradient, especially in summer and autumn, indicating more intense eastern Levantine eddies in the future. The

Ionian sub-basin SST increases zonally from north (Gulf of Taranto) to south (west of Gulf of Sidra, Libya) in winter (13.9–17.4 °C) and autumn (18.1–22.2 °C), and from north-east (24.2 °C) to south-west (28 °C; Gulf of Gabes, Tunisia) in summer. In spring, however, the Ionian SST displays a mixed zonal and meridional gradient, ranging from 18.2 °C off the north-western Ionian coast to 20.8 °C in the Gulf of Bay 11-7085 Gabes, Tunisia. Ionian mesoscale structures do not generally become more obvious with the seasonal SST increase, although the Ionian mesoscale eddies do become more obvious with the seasonal warming. The latter may indicate a significant increase in the intensity of Ionian mesoscale eddies in the near future. The Mid-Ionian Jet (Poulain et al. 2012) is generally obvious in the annual SST distribution (SST, 20.2 °C), most markedly in summer (SST, 25.5 °C). There is a significant difference in the SST gradient between the northern (meridional distribution) and southern (zonal distribution) Tyrrhenian sub-basin, partly due to the surface water circulation. The northern Tyrrhenian SST increases from north-east to south-west as follows: 13.6–14.6 °C (winter), 17.6–19 °C (spring), 23.2–26 °C (summer), and 16.4–19.8 °C (autumn). However, the southern Tyrrhenian SST increases zonally from south to north. The northern Tyrrhenian gyre (Poulain et al.

So to summarize, SCH-900776 to which extent EVs contain truly distinct types of vesicles requires further investigation, and at present no tools are available to purify a single type or population of vesicle based on size or density.3 EVs expose tissue/cell type-specific marker proteins of their parent cell.[3], [4] and [44] When a sufficient number of such marker proteins are exposed, the cellular origin of a vesicle can be determined

by e.g. flow cytometry using antibodies directed against such marker proteins. This is illustrated in Table 2, in which a shortlist of commonly used marker proteins is summarized for analysis of vesicles in human blood (CD: cluster of differentiation). The numbers, cellular origin, composition and functional properties of EVs are not only disease (state) dependent, but also depend on the body fluids being studied. The major populations of EVs in a body fluid usually reflect the cells that are present in that particular body fluid and that surround the body fluid. Examples of the latter are vesicles from synoviocytes which are present in joint (synovial) fluid, and vesicles from endothelial cells (ECs) in blood. We will briefly summarize the cellular origin presence of EVs in blood, urine, saliva, cerebrospinal and synovial fluids in the following paragraphs. In peripheral blood of a healthy subject, platelets and erythrocytes

are the major sources of EVs, but in certain disease states such as sepsis, cardiovascular disease (CVD), or cancer, also MVs from monocytes, granulocytes, lymphocytes, ECs, and cancer cells can be present.45 Peripheral blood also contains exosomes,46 although the cellular Kinase Inhibitor Library purchase origin of these vesicles is unknown. Urine of healthy humans and amniotic fluid both

contain significant numbers of exosomes or exosome-like vesicles.47 These exosomes expose CD24 and aquaporin-2, therefore, are likely to originate from kidney cells48 and from epithelial cells Carnitine palmitoyltransferase II facing the renal tubule lumen.49 Urine contains also larger vesicles, but thus far the characterization of these two types of vesicles in urine has been problematic.50 In saliva from healthy individuals, the larger vesicles, MVs, are derived mainly from epithelial cells and granulocytes, whereas the smaller vesicles, i.e. exosomes or vesicles resembling exosomes, are mainly from epithelial cell origin.51 Cerebrospinal fluid also contains EVs.52 In vitro, various types of brain cells such as astrocytes, microglia, oligodendrocytes and neurons release exosomes.53 The source of the EVs in cerebrospinal fluid, however, is presently unknown. Synovial fluid of rheumatoid arthritis (RA) patients and patients with other types of arthritis contain MVs.[18] and [54] Most of these MVs originate from cells associated with inflammation, such as monocytes and granulocytes. In addition, synovial fluid also contains vesicles from synovial fibroblasts.55 Taken together, every body fluid has a clearly distinct vesicle profile.

1 M cacodylate buffer (Agar Scientific Ltd., Stansted, Essex, UK) overnight and then dehydrated through a series of ethanol solutions, 20%, 50%, 70%, 90% and 3 changes in absolute ethanol. The discs were then placed for 2 min in Hexamethyldisilazane (Agar Scientific Ld, UK), removed and allowed to dry. They were then attached to aluminium stubs with adhesive carbon tabs (both Agar Scientific Ltd, UK), sputter coated with gold/palladium (Polaron E5OO, Bio-Rad, Dolutegravir mouse Richmond, Surrey UK) and viewed in a JEOL JSM-5410LV SEM

microscope (JEOL UK Ltd, Welwyn, Herts, UK) operating at 10 kV and 10 mm working distance. SEM images would also reveal the roughness of the coating; which might influence the cell’s shape and ability to differentiate. After 48 h of growth on SCH 900776 in vitro the test samples the cells were lysed with Passive lysis buffer (Promega), the lysate was brought in a black 96-well and the Dual Luciferase Reporter™ assay was performed using a Labsystems Luminoskan Ascent Plate Luminometer [43]. The Gli-responsive firefly luciferase was measured manually and

immediately after adding the Luciferase Assay Reagent II. Subsequently, the Stop&Glo component was added to measure the constitutive Renilla expression. A relative Gli expression was obtained by dividing the firefly by the Renilla luminescence. As described in Paul and Sharma, 1999; the HA-beads were prepared by mixing 5 g hydroxyapatite (Sigma-Aldrich, Dorset, UK) with 10 ml of a 2% chitosan (Sigma) solution in 2% (v/v) acetic acid. The Fludarabine solution was poured in sunflower-oil and stirred to dispense the chitosan-HA-solution into small bubbles. The

bifunctional cross-linking reagent gluturaldehyde (Sigma) was added to cross-link the chitosan and the formed beads were filtered, washed with acetone and sintered at 1300 °C for 2 h. As the chitosan was burned away, pure porous HA-beads were left over [44]. The beads were soaked in 200 μM purmorphamine in PBS for 24 h and control beads were soaked in PBS only; while this Pur concentration is 100 × higher than the in vitro concentration tested it was expected that the amount would be sufficient to achieve a measurable effect. Fertilized eggs (J.K. Needle and Co., Herts, UK) were incubated at 39 °C within the first week upon arrival. A host egg was windowed at day 3 [45] to be able to use the chicken chorioallantoic membrane (CAM) as a culture substrate at day 7. The femurs were isolated from donor eggs at day 14. All soft tissues were removed from the femur and a small defect was made with a tip of a needle (BD Microlance 3). 10 beads were taken with a micropipette and injected onto the defect and pushed further into the defect with a needle-tip. This was performed using beads soaked in purmorphamine and control beads without purmorphamine (n = 3). The femur with the implant was brought on the CAM of the host egg, the window was sealed with plastic tape and the host egg was incubated for another 7 days.

The modifications included changes of the trap and temperature purge/retention program of the gas chromatograph. The traps used in both systems were Vocarb® 3000, with a trap temperature of − 5 °C for the custom-made system and ambient temperature for the Tekmar system. The desorption temperature

Docetaxel mw was 225 °C. The systems were connected to gas chromatographs with electron-capture detectors (Varian 3800). Separations of halocarbons were performed using an Agilent DB-624 wide-bore column (60 m, I.D. 0.32 mm, film 1.80 μm). The chromatographic conditions were a starting temperature of 30 °C at a hold time of 7.23 min, followed by an increase in temperature to 55 °C at a rate of 5 °C min− 1, raised to 69 °C at a rate of 2 °C min− 1, raised to 100 °C at a rate of 5 °C min− 1, raised to 140 °C at a rate of 10 °C min− 1 and raised to 255 °C at a rate of 30 °C min− 1, with a hold time of 1.50 min. The systems were calibrated with external standards

of CH3I (Fluka (> 99.5%), CH3CH2I (Merck, 99%), CH3CHICH2 (Fluka, > 98%), CH2Br2 (Merck, 99%), CH3CH2CH2I (Aldrich, 99%), CHBrCl2 (Fluka, > 98%), CH2ClI (Fluka, > 97%), CH3CHICH2CH3 (Fluka, > 99%), CHBr2Cl (Fluka, > 97%), CH2ICH2CH2CH3 (Fluka, > 99%), CH2BrCH2Br (unknown), CH2BrI (Fluka), CHBr3 (Merck, > 98%) and CH2I2 (Merck, > 98%) diluted from a stock Dolutegravir cost solution in methanol (Sigma-Aldrich, suitable for purge and trap analysis) in seawater to give final concentrations of pmol L− 1 in the purge chamber. The systems were calibrated with standards every 5 days, and no drift was observed during the duration of the cruise. The absolute detection limits for the compounds are in the fmol L− 1 range (Supplementary material), and the overall precision for the biogenic halocarbons were between Progesterone 1 and 5%. Halocarbon data from the OSO07 expedition is archived at the PANGEA information system, http://doi.pangaea.de/10.1594/PANGAEA.779087. Water samples

were collected for chlorophyll a, photosynthetic pigments and microscopic analysis. All filtrations were completed using low (⅓ atm) vacuum through 25 mm Whatman GF/F filters. Samples for chlorophyll were placed in 7 mL 90% acetone, extracted for at least 24 h in cold (~− 10 °C) dark conditions, the filters removed, and the extracts read before and after acidification on a Turner Designs Model 700 fluorometer (Knap et al., 1996). The fluorometer was calibrated before and after the cruise using commercially purified chlorophyll a (Sigma), which in turn was checked using high performance liquid chromatography (HPLC). Samples for pigment analysis were collected and filtered, wrapped in aluminum foil and frozen at − 80 °C. Samples were returned to the laboratory frozen and processed on Waters Millenium HPLC equipped with dual-beam photocells and a fluorescence detector.

There Enzalutamide nmr are some limitations in the present study. The lack of inundation at the coastlines, coupled with the minimum depth requirement, means that the true free-surface variation at an arbitrary coastal location cannot yet be represented. Fluidity is capable of simulating inundation in a limited region (Funke

et al., 2011) and work is ongoing to link this technology to large-scale simulations. The virtual wave gauges must be contained within the mesh to record the free surface variations at a given location. As we varied coastlines and resolution, wave gauges were moved slightly between simulations to ensure they were not on land. Bondevik et al. (2005) used a similar methodology as the gauges specified there were not within their computational domain. They do not report the true location as the effect of this shift was thought to be small. The largest difference in the present study was less than 1 degree for the 50 km resolution simulation with the coarsest GSSHS coastline. All other simulations had differences of much less than 1 degree. The current model does not include inundation as the wave reaches the coastline. Therefore

Sunitinib price comparisons are made between the estimated run-up height from sedimentary deposits and the maximum wave height in the vicinity of the deposit. The difference between the two estimates will depend on local factors, such as vegetation and small-scale (i.e. unresolved) bathymetric/topographic changes. We aim to include this in future work. Perhaps the most important simplifying assumption within this study is that the Storegga Slide moved as a single rigid block. This a priori   assumption is important because the way in which the original slide moves determines the initial dimensions of the resulting tsunami. Field observations ( Haflidason et al., 2005) suggest that much of the slide mass disintegrated, such that it was not a single rigid block. Moreover, there is evidence that Baricitinib slope failure

started in deep water and moved retrogressively upslope ( Masson et al., 2010). This modelling also assumes a priori   that the slide accelerated to a speed of ∼∼35 m/s over 3365 s. The acceleration trajectory of the slide is unknown, although previous modelling suggests that such fast speeds are needed to generate a large far field tsunami. We have based our model on the work of ( Harbitz, 1992). This was later refined in terms of both the slide shape and initiation by Bondevik et al. (2005) but no comparison to Harbitz (1992) was carried out and hence it is difficult to ascertain what effect these modifications had on the model results. Bondevik et al. (2005) do not give an analytical expression for the modified slide and hence it could not be used in this study. In addition, Bondevik et al. (2005) also increased resolution of the mesh from 12.5 km to 2.08 km, possibly confounding any comparison.