A three phase screening strategy was used to identify relevant articles. Firstly, one investigator (KJ) identified potentially relevant studies by scanning their titles and abstracts. Secondly, remaining citations were examined independently by two investigators (KJ & SMc) and agreement reached on articles which did not meet the selection criteria.

Finally, this website both investigators (KJ & SMc) independently reviewed the full text of remaining articles against the selection criteria and consensus was reached for their inclusion in the review. In the event of disagreement, a third reviewer (JKM) arbitrated. The quality tool used in this review was modified from tools used in previous systematic reviews (Borghouts et al., 1998 and Scholten-Peeters et al., 2003). Since adherence was the focus of this study, “loss to follow-up” was eliminated as an item of assessment from the quality tool. Therefore the quality assessment tool consisted of 13 criteria (see Table 1). The standard of information required to meet each criterion was set a-priori. Criterion meeting the quality standard were given a score of 1, Selleck Tacrolimus while those not meeting the standard were given a zero score. Studies scoring ≥7 were considered ‘high quality’, while those scoring <7 were considered ‘low quality’ (Borghouts et al., 1998 and Scholten-Peeters et al., 2003). Multiple

publications derived from a single

cohort were awarded one quality score based on the information available from all the publications (Scholten-Peeters et al., 2003). Two reviewers (KJ & SMc) independently assessed and scored the included studies. Where there was disagreement a third reviewer (EG) made the final decision. A standardised template was used to extract data regarding the study population, study design, predictor variables, outcome measures, study quality, data analysis and results. Inter-observer agreement of quality assessment was determined by calculating percentage agreement and a kappa co-efficient (Viera and Garrett, 2005). Information extracted is presented in table format to highlight methodological quality, similarities and differences between the studies. Narrative summaries of the results are provided. Beta adrenergic receptor kinase Qualitative conclusions are based on levels of evidence (see Table 2) which have been used in previous reviews (Karjalainen et al., 2001 and Verhagen et al., 2004). Where possible, the significance of factors affecting adherence and the levels of evidence were derived from multivariate analyses. Significant associations of p < 0.05 or relevant estimated odds ratios or risk ratios were used; these were defined as meaningful when ≤0.5 or ≥2.0 ( Ariens et al., 2000). Fig. 1 shows the process of study selection. Initial searching identified 833 citations.

2 × 10 m3 s− 1 yr− 1.

The negative trend in net precipitation was due to a negative evaporation trend of approximately − 1.6 × 10 m3 s− 1 yr− 1 DAPT research buy together with a negative precipitation trend of − 3.8 × 10 m3 s− 1 yr− 1. The freshwater discharge into the EMB (i.e. via rivers of the Eastern Basin plus the Black Sea) also displayed a negative trend of –2.4 × 10 m3 s− 1 yr− 1, explained mainly by the building of the Aswan High Dam in 1964 (which reduced the River Nile’s discharge by approximately half) and decreasing net precipitation over the Black Sea Basin (the decrease in Black Sea discharge was estimated to be approximately − 9.8 × 10 m3 s− 1 yr− 1). The negative trends in the freshwater components indicating increasing EMB salinity agree with the findings of Skliris et al. (2007). The EMB monthly mean river runoff ranged from 0.006 × 106 m3 s− 1 in August to 0.018 × 106 m3 s− 1 in April, with an annual average of 0.011 × 106 m3 s− 1. Over the studied 52-year period, Qin – Qout averaged

0.023 ± 0.84 × 106 m3 s− 1, while As(P – E) averaged –0.03 ± 0.04 × 106 m3 s− 1, the difference being balanced by the river discharge ( Table 1). The monthly means of the heat budget components are presented in Table 2 and Figure 14, while the annual means of Fn, Fos and Floss are presented in Figure 15. The heat balance simulations indicate that the heat loss from the open sea was almost balanced by the solar radiation to the open water surface. Heat loss from the open sea ranged from 134.9 W m− 2 to 229.8 W m− 2, while solar radiation to the open water surface ranged from –300.3 W m− 2 in July to –73.3 W m− 2 in December. I-BET-762 manufacturer The total heat flux from the EMB surface was negative (indicating fluxes into the water body) from March to August, while it was positive in the rest of the year. Latent heat flux and net long-wave radiation are more important than sensible heat flux in controlling the variability of heat loss from the open sea. The annual average value of Floss was 8.7 W m − 2, which needs to be balanced by the difference in heat transported by the in- and outflowing

water. During the study period, the annual average values of Fn and Fos were 195.6 W m− 2 and − 186.9 W m− 2 respectively. Astemizole Modelled Fn data indicate an increasing trend of 0.07 W m− 2 yr− 1, while Fos data indicate a decreasing trend of approximately 0.07 W m− 2 yr− 1. This indicates an increase in solar radiation into the water body and an increase in net heat loss, probably due to reduced total cloud cover rates. Moreover, the figures indicate a close relationship between the ECMWF meteorological data and the present modelled heat balance components, i.e. Fn, Fos and Floss, with biases of 4, 2.7 and 3.2 W m− 2 respectively. In addition, the positive value of the annual average Floss, 8.7 W m− 2, implies that the EMB imports heat from the Western Basin ( Table 2).

A closer look at the high green region in Fig. 4A shows two peaks present: a lower intensity peak with a high percentage of high-green cell events (peak 1: 75.8 ± 2.0%), and a higher intensity peak with a low percentage of high-green

cell events (peak 2: 24.6 ± 2.0%). Since the green fluorescence intensity of JC-1 depends on the concentration of monomers, lower intensity events (peak 1, Fig. 4A), and higher intensity events (peak 2, Fig. 4A), with both being in the high-green region corresponding to cells, will depict cells with polarized and depolarized mitochondria respectively. Fig. 4B show the raw forward versus side scatter data of HUVEC control samples after the application of this fluorescence threshold with cells containing polarized (green) and depolarized Daporinad research buy mitochondria (orange) clearly distinguished from debris (grey). Cells with polarized mitochondria (green, Fig. 4B), show similar light scatter properties Selleck AG-14699 to membrane intact cells (green, Fig. 2C). Correspondingly, cells with depolarized mitochondria (orange, Fig. 4B), show similar light scatter properties to membrane compromised cells (red, Fig. 2C). This provides further evidence of the accuracy of fluorescence thresholds, as two separate assays were capable of not only discriminating

cells from debris but also identifying intact from damaged cells. Fig. 4C shows the JC-1 green fluorescence of HUVEC samples with the addition of the mitochondrial depolarization agent CCCP, used as a negative control for mitochondrial membrane potential without affecting the membrane integrity of the cell. Fig. 4C shows a fluorescence histogram separating low fluorescent intensity debris (low green) from high intensity cells (high green). Even after depolarization of mitochondria in all cells within the sample from incubation with CCCP, these cells were still readily identified from debris using a fluorescence threshold at the minimum between the low green and high green regions. A comparison of JC-1

green fluorescence shows only one peak present in the high green region (Fig. 4C), compared to the two peaks present in control samples (Fig. 4A). Fig. 4D shows the forward versus side scatter Verteporfin cost data of HUVEC samples after the application of a fluorescence threshold, identifying cells with depolarized mitochondria (orange) from debris (grey). Although the fluorescent properties of cells have changed (Fig. 4C), compared to untreated controls (Fig. 4A), the light scatter properties of both of these samples remain the same (Fig. 4B and D). A large population of cells with high forward and side scatter properties is still present along with a smaller population of cells with low forward and high side scatter corresponding to the events found in R1 and R2 (Fig. 1A), respectively. Fig. 4E and F show the JC-1 green fluorescence of HUVEC plunged samples. Fig. 4E shows a fluorescence histogram separating low intensity debris (low green), from high intensity cells (high green).

Incubation with d-Tc

produced the characteristic blockade that could be reversed by washing and there was no effect on the contractures to exogenous ACh and KCl (data not shown). In preparations pretreated with d-Tc followed by incubation with venom, subsequent washing partially restored the muscle twitch-tension (to 81 ± 7% of control; n = 3), in contrast to preparations treated with venom alone in which washing did not restore twitch-tension. In contrast, d-Tc did not affect the responses to exogenous agonists since there was still marked attenuation of the contractures to exogenous ACh (∼94% inhibition) and KCl (∼60% inhibition). The PLA2 activity of B. alcatraz venom was 0.06 ± 0.02 U/mg and was lower (p < 0.05) than that of Crotalus durissus terrificus (South American

CYC202 cost rattlesnake) venom (0.2 ± 0.03 U/mg, n = 4 each). There was a progressive increase in CK release by venom-treated preparations throughout the experiment, although the responses to the two venom concentrations tested (10 μg/ml and 100 μg/ml) were not significantly different (Fig. 1C). Control muscle incubated with Krebs solution showed normal morphology with regular diameter muscle fibers (Fig. 2A). Both of the venom concentrations analyzed (10 and 100 μg/ml) caused mild muscle fiber damaged that involved fiber hypercontraction and delta lesions (10 μg/ml; Fig. 2B) and edema formation, Sinomenine seen as fiber swelling

(100 μg/ml; Fig. 2C). The percentage of damaged fibers in venom-treated preparations was 18.1 ± 1.5% (10 μg/ml) and 24.7 ± 6.6% (100 μg/ml) compared Crenolanib mw to 7.9 ± 2.4% in control preparations. Pre-incubation of B. alcatraz venom (10 and 100 μg/ml) with commercial bothropic antivenom (BAV) at a venom:antivenom ratio of 1:5 (10 μg venom:2 μl antivenom) recommended by the manufacturer did not neutralize the neuromuscular blockade. However, when 10 μg of venom was pre-incubated with 30 μl of antivenom the blockade was attenuated by 81 ± 4%. In contrast, when 100 μg of venom was incubated with 300 μl of antivenom (same venom:antivenom proportion as used for 10 μg of venom) only partial protection was observed, with the blockade at t50 and t90 increasing from 20 ± 3 min and 38 ± 5 min ( Fig. 1A) to 45 ± 3 min and 66 ± 4 min ( Fig. 2E), respectively. Greater volumes of antivenom (≥1 ml) were not tested with this higher quantity of venom because they tended to have a deleterious effect on the preparations. Histological analysis of preparations incubated with the lower venom:antivenom concentrations revealed a normal muscle appearance, indicating effective protection by the antivenom ( Fig. 2D). Various Bothrops venoms, including Bothrops erythromelas ( Zamunér et al., 2004), Bothrops insularis ( Cogo et al., 1993, Cogo et al.

An MRI scan will be performed with diffusion weighted and perfusion weighted sequence to assess for the presence of a penumbra. Patients without penumbra will not be excluded, as there is evidence that there may be benefit to ischemic cells after reperfusion Ixazomib molecular weight [25] and [29], however the mechanism and effect could be quite different, and so these two groups should be considered separately. This will be recorded and patients will be later placed into two groups, penumbra and no penumbra for analysis. As it would be prohibitively time consuming to require reading the MRI for a diffusion perfusion mismatch

prior to randomization, the presence or absence of penumbra should be analyzed later through subgroup analysis. find more This would also avoid unnecessary HBO2T treatment delays. If no exclusion exists, patient will be randomized to standard of care plus HBO2T or standard of care plus a sham treatment of air at minimal pressure increase to maintain patient blinding. HBO2T will

consist of one session of 100% oxygen at 2.4 ATA for 90 min. The selection of this dose is based on several factors. First, the FDA has approved HBO2T at a dose of 2.4 ATA for 90 min for numerous conditions and it is well tolerated [30]. Second, this dose, and limitation to a single treatment, (a single exposure) at this pressure is also more consistent with animal studies which have shown efficacy of HBO2T in cerebral ischemia [13], [15], [16], [17], [18], [31], [32], [33], [34], [35], [36], [37] and [38]. All patients enrolled will undergo repeat NIHSS, mRS scale, Barthel index [39] and Glasgow outcomes scale [40] at 7 days performed by an examiner blinded to their treatment. These assessments will be repeated at 90 days with a follow-up appointment to clinic, similar to the outcomes in the NINDS (National Institute of Neurologic Diseases) trial which found tPA to be effective [3]. Primary outcome will be the mRS, and NIHSS scores as in the NINDS trial. Secondary outcomes will include the Barthel index score, Glasgow outcome scale score,

length of hospital stay, rates of ICH, mortality Cyclin-dependent kinase 3 and discharge location. Sample size would be determined based on a 20% absolute difference in good outcome (score 0–1 on the modified Rankin scale) at three months. In the original tPA trial, approximately 25–28% of the placebo group and 39–47% of the tPA group achieved this outcome [3]. If this 6 h trial shows safety and efficacy, a second tier could be added extending to 12 h for patients with a documented penumbra. To determine whether use of HBO2T in the acute state after traumatic brain injury is effective at improving functional and mortality outcomes. To determine whether use of HBO2T in the acute state after traumatic brain injury is effective at reducing elevated intracranial pressure (ICP).

Virk and Sogi (2004) extracted pectins from apple peel using HCl and citric acid and also observed that citric acid was more effective than HCl in terms of yield. As showed in Table 5, CA-HYP fraction presented low moisture content (2.7 g/100 g) with high carbohydrate content (64.0 g/100 g CA-HYP), followed by proteins and phenolics (13.8 and 9.4 g/100 g, respectively). Monosaccharide composition showed that CA-HYP contains mainly uronic acid (65.1 g/100 g fraction). Rhamnose and galactose were found in higher proportions than the other monosaccharides. Similar monosaccharide composition was found for pectins from sugar beet pulp (Morris & Ralet, 2011), Améliorée mango peels ( Koubala et al.,

2008), okra ( Sengkhamparn, Verhoef, Schols, Sajjanantakul, & Voragen, 2009) and optimized cacao pod this website husks pectin obtained with nitric acid ( Vriesmann, Teófilo, et al., 2011). The proportion of GalA ERK inhibitor units methyl-esterified at C-6 in relation to the total GalA units defines the degree of methyl-esterification (DE), which classifies pectins as high-methoxyl

(HM pectins, DE > 50%) and low-methoxyl (LM pectins, DE < 50%). Degree of acetylation (DA) is the proportion of acetyl groups in relation to the total GalA units of the pectin. Both the DE and DA have a significant impact on pectin functional properties, influencing solubilization and gelation properties (Rolin, 1993). In contrast to native pectins (very often HM with low acetyl content) (Voragen Meloxicam et al., 1995), CA-HYP contained low-methoxyl pectins with high acetyl content (DE: 40.3%; DA: 15.9%; Table 5). LM pectins highly acetylated were also obtained from sugar beet pulp (Yapo, Robert, Etienne, Wathelet, & Paquot, 2007) and okra (Sengkhamparn et al., 2009). 13C NMR spectroscopy of CA-HYP (Fig. 3) allowed the investigation of its chemical

structure. Signals of esterified and un-esterified units of α-d-GalA from homogalacturonans were identified at δ 100.0 and 99.3, respectively, with their respective C-6 signals at δ 170.6 and 173.5, from methyl ester carbonyl carbons and carboxyl carbons, respectively. Signals of methyl carbons of esterified carbonyls in GalA units appeared at δ 52.8, whereas those of acetyl groups appeared at δ 20.4. Rhamnogalacturonans were also identified in CA-HYP. Characteristic signals of C-1 and CH3-6 signals from Rha units appeared at δ 98.5 and 16.6, respectively. The anomeric region also showed signals at δ 103.3 and 102.4 from β-1,4-d-Gal units (substituted or not at O-6, respectively). In the aromatic carbons region, signals at δ 115.1, 116.2, 144.0 and 154.8 were identified, suggesting the presence of phenolic compounds. All assignments were based on literature values ( Vriesmann, Amboni, et al., 2011; Vriesmann, Teófilo, et al., 2011; Westereng, Michaelsen, Samuelsen, & Knutsen, 2008).

5° × 2.5°) and time (6 h), some regional details and cyclones could be missing. Therefore, for the wind-field snapshots during the maximum sea levels at Pärnu we have chosen the regional reanalysis Baltan65+ (Luhamaa et al. 2011), with a spatial resolution of 0.1°. We looked for deep cyclones that HKI 272 might cause high sea level events at Pärnu (above + 150 cm) and Tallinn (above + 100 cm): for only one case out of 31 was it not possible to detect the corresponding cyclone (1 November 1983, see Table 1). All the high sea level events listed in Table 1 took place during the storm season, i.e. from September to March. Extreme sea levels

were not always observed at both stations on the same days, however, as this depends on the cyclone’s exact position, lifecycle phase and velocity; but in really extreme cases, sea levels were high over a larger area of the sea along the entire Estonian coast. The cyclones that passed over the Baltic Sea and caused these 31 extreme events in 1948–2010 were not exclusively deep, and there was no obvious correlation between the minimum air pressure of the cyclones and the extreme sea level. Table 2 presents, separately for Tallinn and Pärnu, the average values of the cyclone characteristics for extreme sea level events. The atmospheric pressure at sea level at their centre is lower than the average value in the northern Baltic region – 985 hPa (Link & Post 2007). We counted the number

of cyclones in the research area during 60-day periods to test the hypothesis about the series of cyclones causing these high water events. Here we used two options: either the Fulvestrant extreme event was in the middle of the counting period (N 60_c) or we counted the cyclones that preceded the storm surge (N60_b). The number of cyclones was higher if the high sea level event was in the middle of the counting period (see Table 2). The same result is supported by Figure 1, where the secondary maximum sea levels are of the same magnitude before and after the main event. The average values of the real cyclone characteristics compared to the values modelled by Averkiev &

Klevannyy (2010) are presented in Table 2 and Figure 2. The dangerous cyclones for Tallinn and Pärnu sea levels are slightly different: Vasopressin Receptor for Tallinn the position of the deepest phase of the cyclone should be shifted to the north by about two degrees, but the longitudes are considered to be the same. The ideal Pärnu cyclone has a stronger meridional track component (the slope of the trajectory is 0.304 instead of 0.223). On average, the most accurately predicted characteristic of a dangerous cyclone is the latitude of the deepest state; at both sites this coincides with the modelled value within one degree. In fact, the cyclones propagate somewhat more slowly than predicted and therefore their minimum pressure also occurs some 4–5 degrees farther to the west than predicted.

A reduction of the intensity of the HN resonances of protein B upon irradiation of protein A identifies the region of B in contact with A ( Fig. 2). In this experiment protein A is unlabelled, while protein B is 2H, 15N labelled, such that the saturation transfer is specific for the protein–protein interaction interface. Another version of this experiment can be designed that detects the methyl groups of protein B while saturating the aromatic or aliphatic resonances of protein A, or even detect the saturation CH5424802 datasheet transfer to the RNA aromatic protons upon saturation of protein side-chain resonances.

Dependent on the scheme of saturation and detection, the experiment can be performed either in D2O or in a mixture D2O/H2O to reduce dilution of the signal due to H2O mediated spin diffusion. Ferroptosis assay We have applied this methodology to the ternary hPrp31 (human Prp31)–15.5K–U4

5′-SL (stem–loop) spliceosomal complex, which, due to its large size and instability, is not suitable for a complete structure determination by NMR [29]. We designed an experimental protocol where the protein–protein interaction surface is defined for 15.5 K by cross-saturation NMR data, while the relative orientation of the U4 RNA and the hPrp31 protein are described by mutational and cross-linking data. The decrease of the intensity of the HN resonances of 2D, 15N-labelled 15.5 K upon saturation of the methyl resonances of hPrp31 in the hPrp31–15.5K–U4 5′-SL complex was quantified and translated into distances. Using these data in a restrained ensemble docking protocol, we obtained a model for the ternary complex; comparison of the docking model with the crystal structure of a truncated version of the complex reveals that the docking model is accurate and reproduces all the features of the complex three-dimensional architecture ADP ribosylation factor ( Fig.

2). Furthermore, the atomic details of the protein–protein interaction surface, both in terms of electrostatics and van der Waals contacts, also show excellent agreement to the crystal structure, demonstrating that good accuracy can be obtained at an atomic level even when using sparse and highly ambiguous NMR restraints. Once the mutual interaction surfaces have been defined by chemical shift mapping and cross-saturation experiments, the single components need to be placed in the correct mutual orientation. To this end, one can use residual dipolar couplings (RDCs) [30] measured for each component of the complex under the same alignment conditions. RDCs report on the orientation of internuclear vectors with respect to the magnetic field; therefore, if the structure of the single components is known, the data can be used to orient the components with respect to each other. In high-molecular weight RNP complexes 15N–HN and 13C–1H RDCs of amide and methyl groups [31], respectively, are likely to be available for proteins, while for the nucleic acid components 15N–H and 13C–1H RDCs are available at most for the aromatic rings.

As we have illustrated, a number of more general methods (not designed specifically for toxins) lack predictive power, while specific tests to identify toxins (Saha and Raghava, 2007) fail to distinguish between different toxic functions. Among the methods not currently accessible, some reported success in prediction of myotoxic, presynaptic neurotoxic and anticoagulant functions was achieved by examining subsets of highly similar toxins (found by sequence similarity searches of databases) (Chioato and Ward, GW-572016 cost 2003). However, the assumption that sequences with high similarity share a similar function has been shown to be flawed in this study, where we find that similar functions

may have evolved independently in structurally different sequences, while some novel functions have arisen among clusters of highly similar sequence, making it difficult to identify functional relationships among sequences grouped by similarity alone. This is illustrated by clusters C and D in Figs. 3 and 4, both containing largely myotoxic/oedematous PLA2s as well as a number of neurotoxic PLA2s. However, this underlying similarity in physiological effect

is clearly achieved through different biochemical pathways, as PLA2s in cluster D are all highly catalytically active, and the neurotoxicity is achieved through dimerisation SB203580 research buy with a non-toxic chaperone protein. Members of cluster C, on the other hand, all have mutations that have abolished or considerably reduced the catalytic activity, and when neurotoxic, can express

this activity in the monomeric form. The presence of both these activities in both these structurally distinct clusters may be one reason that considerable overlap was found in the surface residues implicated in myotoxicity and neurotoxicity (Chioato and Ward, 2003). The paucity of existing data on some particular functions (e.g., hypotensive PLA2s, where we were only able to find experimental evidence for this activity for seven isoforms among all viperids) also challenges the ability of any method to classify them. A particularly encouraging feature of the current analysis is the good agreement between cluster membership in the PNJ trees, based isothipendyl on sequence profiles, and the functional predictions from the DFA based on physico-chemical properties, which have different underlying bases. We also found good internal consistency between our predictions and in vitro tests of activity. For example, venom from specimen T208 (V. stejnegeri from Taiwan) is known from the proteomic analysis to contain major PLA2s that match the MW of sequenced isoforms A241_9 and B344_LT2. The third major isoform present matches the MW of Q6H3D4, which was tested as part of this study and showed no distinct activity.

The test section of this tunnel is rectangular with a length of 2.6 m, a width of 0.6 m and a height Target Selective Inhibitor Library cost of 0.6 m. The maximum flow speed is 12 m/s, and the pressure can vary from 10 to 200 kPa. A schematic diagram of the MOERI medium-sized tunnel is shown in Fig. 7. A wake screen composed of a brass wire mesh was made to reproduce the nominal wake flow measured

behind the model ship in the MOERI towing tank. The propeller configurations and the nominal wake distributions measured at the propeller plane inside the cavitation tunnel are shown in Fig. 8. The pressure fluctuation is measured on a flat plate above the model propeller. The flat plate is away from the model propeller tip, which corresponds to the vertical clearance MAPK inhibitor of the hull. Pressure transducers, model XTM-190-25A, were used to measure the pressure values. The computation and the five measured positions on the plate are shown in Fig. 9. Using the method recommended by ITTC (1987), the full-scale pressure fluctuation amplitudes can be predicted from the model scale measurement according to the following formula. equation(9) PS=PM×ρSρM(nSnM)2(DSDM)2fSfM=nSnMwhere ρρ is the density, nn is the rotational speed, and D is the diameter; suffix S represents the ship, and M represents the model.

The cavitation patterns of the model propellers are obtained for the selected blade′s angular position, and the corresponding numerical flow analysis results are shown in Fig. 10, Fig. 11 and Fig. 12. The angular positions of a key blade shown in these figures are measured from the vertically upward position in a clockwise direction when the propeller is viewed from behind. Fig. 13 shows the computed sheet cavitation volume variations. Fig. 14, Fig. 15 and Fig. 16 are the comparison results. The experimental result, the potential-based prediction results, and the results of the newly developed time domain prediction method are compared at positions ‘P’, ‘C’, and ‘S’. As shown Table 4 and Fig. 17, the maximum value of the pressure fluctuation is experimentally measured

and numerically predicted at a slightly starboard side of the propeller. There are two reasons. The first reason is that sheet cavitation volume is occurred analogously symmetric shape whose maximum volume is located slightly starboard side as shown in Fig. 13. The second reason is Immune system the source movement. Because sources are moving from port side to starboard side, induced pressure fluctuation at the starboard side is higher than that of port side. The newly developed time domain prediction results show good agreement with the experimental results, and the developed method is qualitatively and quantitatively superior to the potential-based prediction method. A new time domain prediction method has been presented with the aim of computing the pressure fluctuation induced by a propeller sheet cavitation. Modern acoustic theory is applied to the source modeling of the pressure fluctuation.