In addition the body fat content including the fat

In addition, the body fat content, including the fat-free mass and total body fat, reaches a peak in people between 40 and 70uyears of age in the US, depending on the ethnicity and gender (Chumlea et al., 2002). Aging reduces the sensitivity to sympathetic tone, and induces changes in the endocrine control of BAT formation, weakening the regeneration in brown adipogenic progenitor cells. In addition, mitochondrial biogenesis and bioenergetics are also reduced in these CI-1040 via the decline in the expression of uncoupling protein (UCP)-1 in the inner mitochondrial membrane (Graja and Schulz, 2014).
In order to determine the differences between BAT and WAT, previous study groups have analyzed the transcriptome of both tissues at specific time points following a high-fat diet, and investigated the pathways and functions of the differentially expressed genes. Whole-genome transcriptional analysis must be conducted at multiple time points since the analysis at single time points is not sufficient for the elucidation of the developmental status and differences between BAT and WAT. In order to identify the key genes regulating WAT and BAT development, we performed a serial genome-wide transcriptome analysis of WAT and BAT extracted from mice provided with a normal, as well as high-fat, diet for 24uweeks. Our results might provide new insights into the physiological basis of obesity.
2. Materials and methods
2.1. Animals and tissue collection
The animals were fed with normal (ND) and high-fat diet (HFD) in order to evaluate the changes in gene expression levels in the adipose tissues of C57BL/6J mice, a diet-induced obesity-prone animal model (Table S1). Eighteen mice from each of the ND and HFD groups were anesthetized with ether at 2, 4, 8, 20, and 24uweeks after a 12uh fasting period. Epididymal adipose tissue (WAT) and interscapular brown adipose tissue (BAT) were removed and stored in liquid nitrogen for RNA preparation. All experiments with animals were conducted using protocols approved by the Ethics Committee for animal studies of the Kyungpook National University.
2.2. RNA extraction and microarray
The WAT and BAT extracted from the 18 ND and HFD mice at each time point were homogenized using TRIzol reagent (Invitrogen, Carlsbad, CA, USA). The total RNA was isolated according to the manufacturer\’s protocols. The purity and integrity of the RNA samples were assessed using the Agilent 2100 Bioanalyzer (Agilent Technologies, Palo Alto, CA, USA). Total RNA from the ND and HFD groups were pooled within three sample sets, as described previously (Do et al., 2010). The pooled RNA was stored at u80uC until further experimentation. Total RNA from six sample sets for each time point was amplified and purified using the Ambion Illumina RNA amplification kit (Ambion, Foster City, CA, USA) as per the manufacturer\’s protocols, in order to yield biotinylated cRNA. Labeled cRNA samples were hybridized to a mouse-6 expression bead array (Illumina MouseWG-6 v2 Expression BeadChip; Illumina, San Diego, CA, USA) according to the manufacturer\’s protocols. The raw data of the spot fluorescent intensities was extracted using the Illumina Beadstudio software.

The annotation of the HB genome compared to P

The annotation of the HB01 genome compared to P. multocida strains 36950 and Pm70, A. pleuropneumoniae JL03, and H. parasuis SH0165 is summarized in Table 1. The complete HB01 genome contains 2248 potential genes responsible for protein encoding. However, thirty-six of them were likely to be non-functional due to gene mutation. There were 56 tRNA genes corresponding to the 20 common amino acids, and 19 rRNA genes on 6 ribosomal rRNA operons. Furthermore, a distinct selenocysteine tRNA gene (PMCN01_R52) containing the UCA CI-1040 was identified. This tRNA gene is absent in the 36950 genome. It is adjacent to the selA gene (PMCN01_1532) encoding L-seryl-tRNA (Sec) selenium transferase. A similar tRNA gene is found in A. pleuropneumoniae JL03 and Haemophilus influenzae 86-028NP ( Xu et al., 2008).
There are 2212 coding DNA sequences (CDSs) representing approximately 95.0% of the total genes in HB01 genome. Of these, 212 were annotated as hypothetical proteins. Surprisingly, the number of shared proteins between the bovine strain HB01 and the porcine strain HN06 (1964 orthologous CDSs) is greater than between the two bovine isolates HB01 and 36950 (1956 orthologous CDSs) (Table 3). Moreover, analysis demonstrates that P. multocida HB01 shares a greater number of orthologous proteins with A. pleuropneumoniae JL03 (1025 orthologous CDSs) than with H. parasuis SH0165 (979 orthologous CDSs) ( Table 3), even though the phylogenetic relationship within Pasteurellaceae family based on 16S rRNA genes suggests that Pasteurella spp. isolates are more closely related to isolates of the genus Haemophilus ( Wilson and Ho, 2013).
3.2. Major metabolic pathways
A set of predicted genes in the HB01 genome encode the phosphotransferase system (PTS), allowing HB01 to utilize various carbon sources, including mannitol (mtlADR, PMCN01_0150a0152), mannose (manXYZ, PMCN01_0843a0845), glucose (pstHI-crr, PMCN01_0909a0911), sorbitol (gutMSrlABDE, PMCN01_1290a1294), sucrose (scrKABR, PMCN01_1463a1466), and fructose (fruABK, PMCN01_1515a1517) ( Fig. 3). Two identified genes, treB (PMCN01_1241) and treC (PMCN01_1239), play a role in trehalose uptake and hydrolysis. Both of these genes have been shown to be important for biofilm formation in Klebsiella pneumonieae, which aids in protecting bacteria from phagocytosis and toxic molecules ( Wu et al., 2011). This suggests that HB01 may have a significant ability to survive in the environment. The HB01 genome also encoded complete sets of enzymes involved in the pentose phosphate pathway, glycolysis, and gluconeogenesis, as well as an intact TCA cycle (Fig. 3). Genes encoding enzymes required for these metabolic pathways are conserved between the other two P. multocida genomes. This pattern of metabolism is quite different from the closely related organisms H. influenzae, Haemophilus ducreyi, Haemophilus somnus, and A. pleuropneumoniae, as the TCA pathway in these Pasteurellaceae family members is incomplete ( Xu et al., 2008).

As a first step in implementing g Spike

As a first step in implementing g-Spike, an appropriate scheme to store the tridiagonal matrix had to be chosen. In order for our implementation to keep the same function call notation as cuSPARSE, we used three separate CI-1040 for the diagonals, as shown in Fig. 4 and one more vector for the right hand side of the system. Due to the fact that the matrices Rj produced in step 2 of g-Spike (cf. Section 2.1) have bandwidth 3 and thus have a nonzero second superdiagonal, a fifth vector is allocated as soon as the function implementing g-Spike is entered. Furthermore, some elements at the borders of partitions are not included in any partition and these have to be handled separately. These elements are leading to the creation of the spikes. The size of the left and right side spikes that will appear is known a priori, but fortunately there is no reason to allocate further vectors to store them. As computations proceed, elements of the subdiagonal of the original matrix start being replaced by zeroes. In their place the left side spikes are stored. Similarly, when right side spikes are created, the second superdiagonal elements created earlier are not needed anymore and these spikes are stored in their place. Finally, some additional storage is required to mark whether a partition has been found that is singular. Overall, the temporary storage space required for our algorithm is 5n+O(p)5n+O(p). By contrast, the gtsv routine from NVIDIA needs space for 8(n + 3) temporary elements when n > 8. That is, g-Spike has significantly smaller storage costs, which allows solving much larger systems on the limited memory of the GPU.

All the metadata analyzed in this study

All the metadata analyzed in this study were collected or derived from the publications presenting the EwE models. However, detailed information on some metadata was sometimes missing for many models, which prevented us from using the whole collection of metadata initially envisaged. Besides, lack of information was sometimes observed for metadata of potentially high relevance to the EwE modeling approach. For instance, we obtained 5% of missing data regarding the time period represented by the models, and 17% for the area covered by the models. Though, it is critical to clearly define and indicate the temporal and spatial scales when developing a model. When the geographic extent of the models was poorly described, no spatial shape could be defined for these models. Likewise, several metadata describing the physical characteristics of the modeled ecosystems were considered in EcoBase (e.g., temperature, depth, salinity, oxygen, primary production), but information on abiotic conditions was lacking for most models. Remarkably, information on minimum and maximum depths of the area covered by the models, which is critical to determine the type of CI-1040 represented by the models, was sometimes not provided in sufficient details. As a result, the proportion of models with non-available information was too high for the metadata to be representative. This was also the case with the version of the software used by the modeler. Since the EwE software evolved with time and upgraded versions were successively released, we intended to analyze the evolution of the use of the different versions. The first version of EwE, ECOPATH, was used only in the early 1980s (Polovina, 1984), and the development of a user-friendly software in the early 1990s (version 2, Christensen and Pauly, 1992) rapidly led to a broader use of the model (67 models, 15% of the models). Versions 3 and 4 only had limited use (respectively 3 and 5% of the models) and were rapidly replaced by version 5 used to develop 17% of the models (Christensen et al., 2005), which is now itself replaced by version 6 (8% of the models, Christensen et al., 2008). However, the EwE software versions were only specified by modelers for half of the models, so that the percentages obtained were not representative and we could not explore this aspect of the modeling approach much further. Likewise, the pedigree index could not be analyzed in many details since it was provided for only 8% of the models. Moreover, the compilation of the metadata was sometimes challenging due to some ambiguity in the description of the model. Some models included functional groups labeled as stanzas, but which were not always properly defined as multi-stanzas groups. Thus, we were not able to analyze in many details the usage of multi-stanzas groups.

Adult heads used in the head

Adult heads used in the head impact tests.Specimen IDAgeSexRaceCause of deathHead drop mass (kg)Head length (mm)Head width (mm)Head circum. (mm)A01M61-year-oldMCaucasianUnknown3.16185163565A02M53-year-oldMCaucasianRespiratory failure3.27195143565A04M59-year-oldMHispanicSeptic shock3.21195163583A05M58-year-oldMCaucasianChronic obstructive pulmonary disease3.08187147615A06M67-year-oldMCaucasianRespiratory failure3.41203150611A07M67-year-oldMCaucasianUnknown3.45210155599Full-size tableTable optionsView in workspaceDownload as CSVTable 2.
Average adult peak displacement for each drop. The standard deviations CI-1040 in parentheses.Drop heightImpact location15 cm30 cmOcciput3.82 (0.39)4.62 (0.74)Forehead3.21 (0.48)4.53 (1.07)Vertex3.02 (0.43)3.76 (0.46)Right parietal3.25 (0.43)4.86 (0.48)Left parietal3.84 (0.67)4.76 (0.76)Full-size tableTable optionsView in workspaceDownload as CSVTable B.1.Table B.1.
The average peak resultant acceleration (g) for the 15 cm and 30 cm impacts for the ATD heads. The standard deviations are macrophages in parentheses.ATD headDrop heightVertexOcciputForeheadRight parietalLeft parietal6-month CRABI15 cm3440376711612-month CRABI53 (1)37 (.1)62 (2)63 (5)72 (6)3-year HIII103 (4)57 (7)95 (2)83 (2)92 (2)3-year Q3141 (2)161 (6)122 (9)102 (5)103 (6)6-year HIII102 (4)128 (7)98 (2)115 (3)126 (4)10-year HIII131 (5)157 (6)104 (3)126 (14)123 (13)Adult HIII118 (8)135 (4)112 (4)103 (9)96 (4)6-month CRABI30 cm52628514521412-month CRABI86 (1)56 (3)110 (12)106 (7)117 (2)3-year HIII169 (10)83 (1)160 (1)142 (11)154 (4)3-year Q3234 (4)255 (3)203 (15)174 (20)181 (17)6-year HIII184 (1)218 (7)174 (12)209 (10)190 (11)10-year HIII230 (8)285 (8)193 (2)197 (11)207 (12)Adult HIII208 (6)235 (6)189 (7)174 (7)166 (4)Full-size tableTable optionsView in workspaceDownload as CSVTable B.2.Table B.2.