Top PDF A multi-cell, multi-scale model of vertebrate segmentation and somite formation.

A multi-cell, multi-scale model of vertebrate segmentation and somite formation.

A multi-cell, multi-scale model of vertebrate segmentation and somite formation.

A potential index copy that increases the effective energy, e.g., by increasing deviations from target values for cell volume or surface area or juxtaposing mutually repulsive cells, is improb- able. Thus, the pattern evolves in a manner consistent with the Figure 5. Initial conditions of our model. (A) Sketch of an experimental image of a chick embryo at HH stage 10 (dorsal view). Anterior end to the top and posterior end to the bottom. The modeled tissue extends approximately eight somite lengths posterior to the differentiation front. Cells in the modeled region have little intercellular ECM, so they contact each other directly. They adhere to one another and have limited motility. They do not transcribe fgf8 or wnt3a mRNA, though they translate FGF8 and Wnt3a protein from the temporally decaying mRNA. Each PSM cell contains a segmentation-clock network submodel that couples the clock submodels in neighboring cells via contact-dependent Delta/Notch signaling. (B, C, D) Initial model conditions, visualizing (B) cell types, (C) [FGF8] and (D) [Lfng]. Not shown: initially, the constraining walls extend the full AP length of the simulation. (E, F, G) The modeled PSM after reaching its full length (at 720 min), visualizing (E) cell types, (F) [FGF8] and (G) [Lfng]. The patterns present in the full-length PSM arise spontaneously from the model’s behavior. The first, ill-formed somite to the anterior of the full-length PSM results from the model’s non-biological initial conditions. Parameters are the same as in the reference simulation (Figure 7). In (B–G) white color indicates cell boundaries. Scale bars: (A) 330 mm (B–G) 40 mm. For more information see INTRODUCTION: Two-dimensional model of the PSM and METHODS: Initial conditions.
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Multi-scale and shape constrained localized region-based active contour segmentation of uterine fibroid ultrasound images in HIFU therapy.

Multi-scale and shape constrained localized region-based active contour segmentation of uterine fibroid ultrasound images in HIFU therapy.

In this paper, an accurate and efficient multi-scale and shape constrained localized region-based active contour model, called the MSLCV model, has been proposed to perform semi-automatic segmentation of uterine fibroid in ultrasound images for HIFU therapy. By incorporating a new shape constraint into the localized region-based active contour, we have obtained a more precise segmentation result, avoiding the problems of boundary leakage and excessive contraction due to the low SNR, weak boundaries and intensity inhomogeneity of HIFU ultrasound images. Further, to overcome the shortcomings of the large computation time and the time-consuming nature of the segmentation process in the localized region-based active contour model, we have proposed a multi-scale algorithm that greatly improves the segmentation efficiency. Meanwhile, to solve the problem of the selection of localizing radius and initialization sensitivity, we have discussed and analyzed the adaptive selection of the localizing radius and the formation of a zero narrow band. Compared with other well-known methods, the MSLCV model
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Timing embryo segmentation: dynamics and regulatory mechanisms of the vertebrate segmentation clock

Timing embryo segmentation: dynamics and regulatory mechanisms of the vertebrate segmentation clock

of maintaining stable expression but gradually become out- of-phase [49]. Hes1 cycles in dissociated PSM greatly varied in period and amplitude between individual cells showing that the oscillator is unstable in isolated cells [49]. Oscillations at the single cell level rely on negative feedback regulation and short lived mRNA and proteins. Hes genes encode nuclear proteins that act as transcriptional repressors and negatively regulate their expression via direct binding to their own promoter [97]. Thus, the oscillator period depends on the timing of transcription, translation, protein decay, and additional events such as splicing and posttranslation mod- ifications. For example, deletion of hes7 introns was shown to completely abolish oscillations [98]. Recently, microR- NAs have been implicated in posttranscriptional regulation of oscillatory genes in the segmentation clock, controlling genetic dynamic expression [99, 100]. Inhibition of mir- 125a-5p induces stabilization of chick lfng transcripts and subsequent loss of robust clock oscillations, associated with perturbations in somite formation and patterning [100]. Hes1 stability was shown to be regulated by miR-9, able to dampen gene oscillations when overexpressed or inhibited [99]. The authors describe a double negative feedback loop between hes1 and miR-9 and propose that this regulatory feedback may be responsible for termination of hes1 oscillations and further cellular differentiation [99].
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A multi-scale model of hepcidin promoter regulation reveals factors controlling systemic iron homeostasis.

A multi-scale model of hepcidin promoter regulation reveals factors controlling systemic iron homeostasis.

Our model suggests that BRE2 enhances transcription with similar or higher efficiency than BRE1 (Fig. 3, Supplemental Fig. S4), thus raising the question of how a sequence element located as far as 2 kb away from the TSS enhances transcription with high efficiency. The 2 kb distance from the TSS corresponds to a length of 680 nm along the strand; this number exceeds the length of the mediator complex (,40 nm) which links RNA polymerase to transcription factors [47]. Thus, BRE2-mediated transcription initiation likely involves DNA looping. Our current model neglects the details of DNA looping, but could be extended by existing quantitative modeling approaches taking into account the thermodynamics of DNA bending [48,49]. Such a detailed promoter model should also consider that the BRE2 element of the hepcidin promoter is flanked by bZIP, HNF4alpha/COUP binding sites in the immediate neighborhood [17]. The single deletion of the bZIP or HNF4alpha/COUP sites reduces the BMP responsiveness of the hepcidin promoter. This indicates that a complex of multiple transcription factors cooperates at the BRE2 site to recruit RNAP which may explain the apparently high efficiency of BRE2 in driving transcription. Another prediction of our model is that the strong impact of the BRE1 in the basal state is due to its high affinity for phospho-SMAD binding when compared to BRE2 (Supplemental Fig. S4, Fig. 3E). Both BREs are characterized by the same sequence motif (GGCGCC), suggesting that epigenetic differences in the chromatin state may be responsible for the apparently different affinity of BRE1 and BRE2. Taken together, the present model is likely to be a simplified representation of the real events at the promoter. Future studies are required to model individual events which are currently lumped into overall interaction energies.
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A multi-scale decision-support model to integrate energy in urban planning

A multi-scale decision-support model to integrate energy in urban planning

However, the level of detail at which the model is being applied leads to some constraints on data availability. The closest indicators to the variables initially considered were: the resident population; the average construction period of buildings; and the percentage of active population (as proxy of the occupancy of dwellings and mobility patterns of active vs. non-active population, i.e. employed vs. children, unemployed and retired people). The economic indicators (PP and GDP) were only available for the city as a whole. After running several iterations, this last modelling option was dropped because it didn’t return significant improved results (higher coefficients of determination or lower errors), comparing to the base model including only variables of urban form. Table 23 presents the results for the best ANN model including social indicators. It shows that not only were the individual relationships and respective prediction errors less interesting, but also that the overall model accuracy significantly decreased (given by the higher MSE) by adding the new variables. These results may be explained by the fact that, thermal energy needs in buildings, as given by the building certification system, reflect the characteristics of the building itself, instead of real occupancy patterns (more related to the resident population and the percentage of active population). As for the construction period, one can consider that the urban form indicators used for the base model already describe the existing building types, which may turn this indicator somehow redundant. In the case of mobility, one may infer that economic and behavioural factors play a more significant role, which isn’t captured by the indicators that were available.
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Segmentation and fishery characteristics of the mixed-species multi-gear portuguese fleet

Segmentation and fishery characteristics of the mixed-species multi-gear portuguese fleet

Fleet segmentation and knowledge of fishing fleet dynamics are essential to move from single species to fishery/fleet-based advice. The coastal mixed-species multi-gear Portuguese fleet comprises medium-sized (.12 m) vessels, using a diversity of passive gears, and is economically important. For hake (under a recovery plan) and monkfish (overexploited), it contributes .50% to their total annual landings. Commercial daily landings in 2005 from 271 vessels were analysed by region using non-hierarchical cluster analysis and multi- variate regression trees. The cluster analysis allowed the identification of regional fleet segments with a low mixture of species through- out the year. The multivariate regression trees were applied to clusters of vessels with a high mixture of species, to explain weekly landing profiles (species) by vessel technical characteristics, fishing license, and main landing port. The results showed a link between exploited species and geographic location, and in the north between vessel size and depth and an inshore/offshore range. Finally, from the analysis and for the most important species exploited by the Portuguese multi-gear fleet, it was possible to define two or three vessel groups that accounted for at least 50% of the landed value.
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Multi-scale inference of interaction rules in animal groups using Bayesian model selection.

Multi-scale inference of interaction rules in animal groups using Bayesian model selection.

To identify a better model we first visually inspected the interactions between the prawns. These observations suggested a ‘memory effect’, whereby a prawn would remain influenced by individuals beyond the moment of interaction. The resulting models, D1–D4, are both consistent with the polarisation condition and superior at predicting the fine-scale interactions, providing strong evidence for non-Markovian dynamics within this system. More generally, we would expect other examples of animal motion to be non-Markovian, with individuals taking time to react to others, to complete their own actions and also potentially reacting through memory of past situations. In this context, it is important to consider the limitations of recent studies identifying rules of interaction of fish [18,19]. These studies concentrated on quantifying local interactions, but do not try to Figure 7. Simulation results for model D1. (A) Proportion of six-prawn simulations (n~1000) of non-Markovian model D1 with a given number of prawns moving CW over time, showing weak bifurcation to either a CW or an anti-CW polarised state, with most experiments ending with five or six prawns travelling in the same direction. (B) Final distribution of simulations by number of CW moving prawns for simulations with three, six and twelve prawns. Error bars represent the mean and standard deviation for each proportion as calculated from the final ten seconds of the simulations. (C) The average polarisation over time, adjusted by the expected polarisation of randomly oriented prawns, for simulations of three, six and twelve prawns. The KL divergence between the experimental and simulated results is 2.32 bits.
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A multi-agent based cell controller

A multi-agent based cell controller

The proposed architecture, designated by ADACOR (Adaptive and Cooperative Control Architecture for Distributed Manufacturing Systems), is based on a set of autonomou[r]

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Aerosol indirect effects in a multi-scale aerosol-climate model PNNL-MMF

Aerosol indirect effects in a multi-scale aerosol-climate model PNNL-MMF

shortwave and longwave cloud forcing. Simulated sulfate, BC, POM and SOA burdens are larger in the MMF than in CAM5, which can be explained in part by the smaller wet removal rate in the MMF. Simulated aerosol size distributions in the marine boundary layer in the MMF are similar with those in CAM5, and agree slightly better with obser- vations. BC concentrations in the polar regions in the MMF are much higher than that

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Multi-scale keypoints in V1 and face detection

Multi-scale keypoints in V1 and face detection

Owing to the impressive performance of current computers, it is now possi- ble to test Rensink’s [21] triadic architecture in terms of e.g. Deco and Rolls’ [8] cortical architecture. The ventral WHAT data stream (V1, V2, V4, IT) is sup- posed to be involved in object recognition, independently of position and scaling. The dorsal WHERE stream (V1, V2, MT, PP) is responsible for maintaining a spatial map of an object’s location and/or the spatial relationship of an object’s parts as well as moving the spatial allocation of attention. Both data streams are bottom-up and top-down. Apart from input via V1, both streams receive top-down input from a postulated short-term memory for shape features or ob- jects in prefrontal cortex area 46, i.e. the more ventral part PF46v generates an object-based attentional component, whereas the more dorsal part PF46d spec- ifies the location. As for now, we do not know how PF46 works. It might be the neurophysiological equivalent of the cognitive Scene Schema system mentioned above, but apparently the WHAT and WHERE data streams are necessary for obtaining view-independent object detection through cells with receptive fields of 50 degrees or more [8]. However, instead of receiving input directly from sim- ple cells, the data streams should receive input from feature extraction engines, including end-stopped cells.
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Water and nutrient balances in a large tile-drained agricultural catchment: a distributed modeling study

Water and nutrient balances in a large tile-drained agricultural catchment: a distributed modeling study

The present modeling study was carried out on the Upper Sangamon River Basin (USRB) in central Illinois, which is representative of the processes and problems associated with agricultural landscapes in the Mid-West region. USRB, with a drainage area of 3600 km 2 , is an agricultural basin with in- tensive row-crop production. Soil in this basin is dominated by poorly drained silt clay loams and silt loams, which are very fertile due to the high organic content (Demissie and Keefer, 1996). The topography is very flat, with the aver- age slope of the main channel being 0.00049. According to Demissie and Keefer (1996), in 1994, row crops (corn and soybean) covered 85.3% of the whole basin area and grassy crops (small grains and hay) covered 2.4%. Corn and soy- bean almost equally share the row crop land area. The per- centage of area covered by corn is 42.0%, and by soybean is 43.3%, respectively. The biogeochemistry of USRB is altered annually in the spring and fall with widespread yet highly variable applications of nitrogen and phosphorus fer- tilizers. Current land and watershed management practices, such as dredging of channels, produce rapid transmission of nitrogen and phosphorus from the land surface through soils, riparian areas, and small streams to larger streams and rivers. The extensive production of corn and soybeans, substantial inputs of urban wastewater and agricultural runoff, and mod- ification of the drainage network have altered patterns and rates of nitrogen and phosphorus cycling.
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Estimating NH<sub>3</sub> emissions from agricultural fertilizer application in China using the bi-directional CMAQ model coupled to an agro-ecosystem model

Estimating NH<sub>3</sub> emissions from agricultural fertilizer application in China using the bi-directional CMAQ model coupled to an agro-ecosystem model

similar, and the emissions from Henan, Shandong, Jiangsu, Hebei, and Anhui provinces dominate the country’s annual total emissions. At the same time, some discrepancy also ex- ists for the specific provinces among the different studies, which may be caused by distinct fertilizer consumptions and emission rates employed. For example, for Henan province, the estimation of X. Huang et al. (2012) is the highest among these studies. A possible reason for this difference is that al- kaline soil is dominant in Henan province and X. Huang et al. (2012) set a uniform high emission factor for alkaline soil, which is twice as high as that in Dong et al. (2010). Com- pared with provincial distributions, the difference of seasonal variations among these studies is larger. The seasonal profile in Zhao et al. (2013) is based on temperature variations. In addition to temperature, others also considered the impacts of fertilizer application timing. It is indeed difficult to cap- ture the exact date of fertilization for all of China, which may have created this large discrepancy amongst studies. For ex- ample, X. Huang et al. (2012) states that the basal fertilizer and topdressing fertilizer of winter wheat are conducted in September and November. However, basal fertilizer was ap- plied in October in our study and in the Zhang et al. (2011), and the topdressing fertilizer is mainly used in March of the next year. The diversity of seasonal fertilization among dif-
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Multi-Scale Genomic, Transcriptomic and Proteomic Analysis of Colorectal Cancer Cell Lines to Identify Novel Biomarkers.

Multi-Scale Genomic, Transcriptomic and Proteomic Analysis of Colorectal Cancer Cell Lines to Identify Novel Biomarkers.

A number of genes were amplified, overexpressed, and associated with therapeutic responses. By adopting a functional multiscale analytical approach, a list of 20 candidate pre- dictive biomarkers for 5-FU, L-OHP, and BEZ235 was generated. 5-FU-sensitive cell lines had higher programmed cell death 6 (PDCD6) gene expression than less sensitive cell lines. PDCD6, located on cytoband 5p15.33-p14.1, is known to be involved in apoptosis survival [63] and is implicated in migration and invasion in ovarian cancers [64]. Furthermore, there was a statistically significant difference with respect to treatment responses for the three treatments examined in this study. It has recently been demonstrated that PDCD6 accumulates in the nucleus and induces apoptosis in response to DNA damage [65]. Moreover, Rho and col- leagues found that over-expressed PDCD6 inhibits angiogenesis through the PI3K/mToR/ p70S6K pathway by interacting with VEGFR-2 [66], while Park et al. showed that PDCD6 exerts its anti-tumor potency by activating the p53-p21 protein for G 1 phase of cell cycle pro-
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A CFD analysis on the effect of ambient conditions on the hygro-thermal stresses distribution in a planar ambient air-breathing PEM fuel cell

A CFD analysis on the effect of ambient conditions on the hygro-thermal stresses distribution in a planar ambient air-breathing PEM fuel cell

The need for improved lifetime of air-breathing proton exchange membrane (PEM) fuel cells for portable applications necessitates that the failure mechanisms be clearly understood and life prediction models be developed, so that new designs can be introduced to improve long-term performance. An operating air- breathing PEM fuel cell has varying local conditions of temperature and humidity. As a result of in the changes in temperature and moisture, the membrane, GDL and bipolar plates will all experience expansion and contraction. Because of the different thermal expansion and swelling coefficients between these materials, hygro-thermal stresses are introduced into the unit cell during operation. In addition, the non-uniform current and reactant flow distributions in the cell result in non-uniform temperature and moisture content of the cell which could in turn, potentially causing localized increases in the stress magnitudes, and this leads to mechanical damage, which can appear as through-the-thickness flaws or pinholes in the membrane, or delaminating between the polymer membrane and gas diffusion layers. Therefore, in order to acquire a complete understanding of these damage mechanisms in the membranes and gas diffusion layers, mechanical response under steady-state hygro-thermal stresses should be studied under real cell operation conditions.
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Quantitative assessment of Southern Hemisphere ozone in chemistry-climate model simulations

Quantitative assessment of Southern Hemisphere ozone in chemistry-climate model simulations

Figures 1–2 show that some models (MAECHAM4- CHEM, MRI) strongly overestimate total ozone globally while others (SOCOL, UMETRAC) strongly underestimate it in the extratropics. Some models (E39C, LMDZrepro) un- derestimate total ozone in SH mid- and high-latitudes while overestimating it elsewhere. In many models the errors typ- ically exceed 3σ , and are therefore very unlikely to be ex- plained by sampling variability associated with the particu- lar 5-yr period chosen for comparison. Eyring et al. (2006) identified the causes of some model errors, like the positive biases in the extratropics in some models which is likely due to the simulated Brewer-Dobson circulation being too strong. However in most cases the causes are not straightforward to identify. MULTI tends to overestimate total ozone, es- pecially in the SH mid-latitudes where several models show strong positive biases. In general there are no consistent bi- ases in total ozone across the models.
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Braz. J. Chem. Eng.  vol.27 número3

Braz. J. Chem. Eng. vol.27 número3

traditionally has been based on the synthesis of a large number of compounds in the laboratory and exhaustive testing), has been presented. This approach relies first on the application of GC + property models within the CAMD technique (software) for the identification of the polymer repeat-unit structure, thereby enhancing the range of problems that can be handled. Next, the model-based approach incorporates a micro-scale analysis since the macro-scale CAMD algorithm is not able to give complete information on how the basic polymer repeat-units should be arranged for the resulting polymeric structure to satisfy all the desired target properties. A link is therefore provided for simulations at the micro-scale, which is capable of providing reliable estimates of the desired target (barrier) properties based on the principles of quantum and statistical mechanics and statistical thermodynamics. The application of this multi-scale model-based approach has been illustrated through a case study aimed at designing a polymer that can be used as a hermetic stopper (sealant). One of the basic polymer repeat-units identified from the macro- meso-scale approach (adapted CAMD technique) for such an application was polyisobutylene. In comparison to other elastomers and based on literature data, this polymer is characterized by a low glass transition temperature and have markedly low permeability to O 2 and N 2 (thus also to air). Building
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Multi-scale cortical keypoint representation for attention and object detection

Multi-scale cortical keypoint representation for attention and object detection

In this paper we will focus on keypoints, for which Heitger et al. [4] developed a single-scale basis model of single and double end-stopped cells. W¨ urtz and Lourens [15] presented a multi-scale approach: spatial stabilization is obtained by averaging keypoint positions over a few neighboring micro-scales. We [13] also applied multi-scale stabilization, but focused on integrating line/edge, keypoint and disparity detection, including the classification of keypoint structure (e.g. T, L, K junctions). Although the approaches in [13, 15] were multi-scale, the aim was stabilization at one (fine) scale. Here we will go into a truly multi- scale analysis: we will analyze the multi-scale keypoint representation, from very fine to very coarse scales, in order to study its importance and possibilities for developing a cortical architecture, with an emphasis on FoA. In addition, we will include a new aspect, i.e. the application of non-classical receptive field (NCRF) inhibition [3] to keypoint detection, in order to distinguish between object structure and surface textures.
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Value-Added Business Based On Small Scale Of Fisheries A Case Study On Nortern And Shouthern Coasts Of  Java Lamongan And Pelabuhanratu Regency Indonesia

Value-Added Business Based On Small Scale Of Fisheries A Case Study On Nortern And Shouthern Coasts Of Java Lamongan And Pelabuhanratu Regency Indonesia

The development of fisheries sector was expected to keep the economy growth stable, to absorb more labor forces, to produce high foreign exchange, and the most important thing is to increase the income per capita as well as to give a muliplier effects to the society. The effect of economy from an economy activity is usually performed with input-output analysis approach (I-O) and Computable Geberal Equlibrium (CGE) to know the direct, indirect and induced impacts [4]. The impact of economy in a productive activity, for example fisheries can be grouped into three catergories, i.e. direct advantage, indirect advantage, and induced advantage [4]. Direct advantage is triggered from the fishing activity that needs input like labor force/ ship’s crew, fuel, Ice, clean water, supplies/ ration etc. That input can be obtained from other sector. This can cause indirect advantage. If ship’s crew is from local area, the expense of the crew can create induced benefit in that area. Not all the benefits or the impact can be felt by local society. Does the input come from the other area or imported one, the rotation of money can cause indirect benefit then. This is a leakage of benefit. The flow of the money from the fisheries activity to the local society at last creates the impact of economy and economy leakage. Even though it is a little, the empirical studies that try to count the downstream and upstream linkage in small scale fishing in a developing country tend to show that the number of added work is created through the downstream and upstream linkage that is significant enought [5]. Downstream and upstream linkage is stated in Table 1. Generally, the international value chain for economic commodities is important for sellers, such as, tuna, salmon, skipjack tuna, shrimp and tilapia, which consist of some nodal with a product that passes over longer to achieve consumers. Whereas some species that is not economically important is important to the sustainability for local food which is part of the shorter value chain [5]. Small scale fishing is very important as a source of livelihood, earning, production and world fish supply. Besides that, small scale fishing provides fish that directly gives contribution to increase the food and nutrition sustainability [6].
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Fibronectin cues during somite formation

Fibronectin cues during somite formation

In order to assess whether perturbing the FN matrix also affects the apical polarization of N-cadherin, embryo explants were cultured for 6 hours with BSA (n = 4; Figure 4A) or the 70 kDa FN fragment (n = 6; Figure 4D) and immunostained for N-cadherin. Analysis of our results showed that in control explants, s0 cells have started to polarize their N-cadherin apically (Figure 4A9) and sIII cells are elongated, aligned and have apically polarized N- cadherin (Figure 4A9). In contrast, in fragment-treated explants (n = 6; Figure 4D), the axial equivalent to s0 of controls have an ‘‘s- III’’ morphology and do not show any sign of epithelialization (Figure 4D9). The axial equivalent to control sIII cells have only reached an ‘‘s0’’ morphology with cuboidal medial cells and present only a slight apical enrichment of N-cadherin (Figure 4D0). 3D reconstruction of the N-cadherin labeling further confirms the differences between control and 70 kDa fragment-treated explants. The s0 in control embryos has a ‘‘3D adhesion basket’’ opened their surroundings. E) 3D surface reconstruction of the rostral PSM and sI showing a dorsal (E) and medial view (E9). Transparent surface represents the epithelium and in dark gray the mesenchymal core. The s0 somite is still inserted in the ‘‘socket-like’’ PSM [1], but indentations (arrowheads) reveal where the inter-somitic cleft will soon appear. The rostral and lateral sides of s0 are still mesenchymal. As a result of cell rearrangements between s-II and sI, the PSM narrows medio-laterally and thickens dorso-ventrally (dotted lines in E and E9). F) 3D surface reconstruction (white transparent surface) of s0 somite viewed medially (F), rostrally (F9) and dorsally (F0), showing a volume reconstruction of N-cadherin immunostaining (green) inside. N-cadherin is enriched in the medial, dorsal, ventral and caudal sides, and less so in rostral and lateral sides. Thus the N-cadherin- staining forms a 3D ‘‘adhesion basket’’ in s0. G) 3D surface
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Multi-compartment T2 relaxometry using a spatially constrained multi-Gaussian model.

Multi-compartment T2 relaxometry using a spatially constrained multi-Gaussian model.

Unlike the whole brain coverage we demonstrate, previous T2 relaxometry studies of MS are generally reported on selected slices [33,34], hence preclude the quantification of diffuse or systemic pathologies. Our processing time is roughly 5 times shorter than local implementation of NNLS, increasing its routine clinical applicability. Significantly shorter processing time has been reported for NNLS [15] using more powerful hardware and parallel processing techniques, but the above comparison remains valid because presumably our method too could benefit similarly from hardware and parallelization. Our MWF maps have similar range as prior reports [10,14,16], but better visual quality in terms of smoothness and delineation of brain structures. The mean MWF values of major WM structures (Table 2) are consistent with the literature [3,10,15,28], but our numbers are generally higher, e.g. in the genu of corpus callosum and in deep gray matter. There is also discrepancy in the internal capsule specific to MESE results, where both conventional and multi-Gaussian MWF values are low compared to all other data. We do not fully understand the reason, but note that the occlusion with basal ganglia makes ROI drawing difficult and operator dependent. There is no unanimity in the true value of MWF in normal brain tissue, hence it is difficult to assess accuracy on in vivo human data. In any case, absolute agreement in MWF numbers between studies is probably unrealistic due to differences in hardware, study subjects, pulse sequence, etc. Exchange between compartments might affect MWF. Interesting- ly, our results are similar to mcDESPOT [30,31], both numer- ically and visually; in fact our numbers are generally intermediate between NNLS and mcDESPOT. Since both mcDESPOT and our multi-Gaussian approaches rely on pre-defining the number of distinct pools, this might perhaps explain the similarity in their visual appearance, and their distinct appearance compared to NNLS methods which are non-parametric. Until a clear in vivo gold standard emerges for human tissue, we must rely on statistical Table 4. P-values of MWF difference between normal WM and WM lesion detected by two methods.
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