THE EFFECT OF KINETIC MECHANISM AND TURBULENCE ON THE COMBUSTION PROCESS

Abstract The modelisation of combustion is central problem in most practical combustion system. In this work, turbulent combustion is discussed with a lagrangian model, which is useful for the study of turbulent combustion problem. A coupling between this lagrangian model and the presumed probability density function (pdf) method is used with complex chemistry. The validation of the kinetic mechanism was envisaged before integrated it in the computer code for reciprocating engines. The results of computations with the present models are compared with the experimental results obtained from experience obtained in our laboratory and from PSA (Peugeot -Citroen) engine. The comparisons between the results of the modeling and the experiments showed a good agreement

Dissecting the First Transcriptional Divergence During Human Embryonic Development

The trophoblast cell lineage is specified early at the blastocyst stage, leading to the emergence of the trophectoderm and the pluripotent cells of the inner cell mass. Using a double mRNA amplification technique and a comparison with transcriptome data on pluripotent stem cells, placenta, germinal and adult tissues, we report here some essential molecular features of the human mural trophectoderm. In addition to genes known for their role in placenta (CGA, PGF, ALPPL2 and ABCG2), human trophectoderm also strongly expressed Laminins, such as LAMA1, and the GAGE Cancer/Testis genes. The very high level of ABCG2 expression in trophectoderm, 7.9-fold higher than in placenta, suggests a major role of this gene in shielding the very early embryo from xenobiotics. Several genes, including CCKBR and DNMT3L, were specifically up-regulated only in trophectoderm, indicating that the trophoblast cell lineage shares with the germinal lineage a transient burst of DNMT3L expression. A trophectoderm core transcriptional regulatory circuitry formed by 13 tightly interconnected transcription factors (CEBPA, GATA2, GATA3, GCM1, KLF5, MAFK, MSX2, MXD1, PPARD, PPARG, PPP1R13L, TFAP2C and TP63), was found to be induced in trophectoderm and maintained in placenta. The induction of this network could be recapitulated in an in vitro trophoblast differentiation model

Transcriptome Analysis during Human Trophectoderm Specification Suggests New Roles of Metabolic and Epigenetic Genes

In humans, successful pregnancy depends on a cascade of dynamic events during early embryonic development. Unfortunately, molecular data on these critical events is scarce. To improve our understanding of the molecular mechanisms that govern the specification/development of the trophoblast cell lineage, the transcriptome of human trophectoderm (TE) cells from day 5 blastocysts was compared to that of single day 3 embryos from our in vitro fertilization program by using Human Genome U133 Plus 2.0 microarrays. Some of the microarray data were validated by quantitative RT-PCR. The TE molecular signature included 2,196 transcripts, among which were genes already known to be TE-specific (GATA2, GATA3 and GCM1) but also genes involved in trophoblast invasion (MUC15), chromatin remodeling (specifically the DNA methyltransferase DNMT3L) and steroid metabolism (HSD3B1, HSD17B1 and FDX1). In day 3 human embryos 1,714 transcripts were specifically up-regulated. Besides stemness genes such as NANOG and DPPA2, this signature included genes belonging to the NLR family (NALP4, 5, 9, 11 and 13), Ret finger protein-like family (RFPL1, 2 and 3), Melanoma Antigen family (MAGEA1, 2, 3, 5, 6 and 12) and previously unreported transcripts, such as MBD3L2 and ZSCAN4. This study provides a comprehensive outlook of the genes that are expressed during the initial embryo-trophectoderm transition in humans. Further understanding of the biological functions of the key genes involved in steroidogenesis and epigenetic regulation of transcription that are up-regulated in TE cells may clarify their contribution to TE specification and might also provide new biomarkers for the selection of viable and competent blastocysts

Transcriptome Profiling of Human Pre-Implantation Development

BACKGROUND: Preimplantation development is a crucial step in early human development. However, the molecular basis of human preimplantation development is not well known. METHODOLOGY: By applying microarray on 397 human oocytes and embryos at six developmental stages, we studied the transcription dynamics during human preimplantation development. PRINCIPAL FINDINGS: We found that the preimplantation development consisted of two main transitions: from metaphase-II oocyte to 4-cell embryo where mainly the maternal genes were expressed, and from 8-cell embryo to blastocyst with down-regulation of the maternal genes and up-regulation of embryonic genes. Human preimplantation development proved relatively autonomous. Genes predominantly expressed in oocytes and embryos are well conserved during evolution. SIGNIFICANCE: Our database and findings provide fundamental resources for understandin

Microhabitat use and seasonality of the sexually dimorphic West African centaurus beetle Augosoma centaurus

The sexually dimorphic dynastine centaurus beetle, genus Augosoma (Coleoptera: Scarabeidae), is endemic to tropical Africa where two species are found (A. centaurus and A. hippocrates). These beetles are consumed by rural populations, cause damage in plantations and are targets of insect collectors and traders. We present information on size differences and analyzed intersexual niche divergence and seasonality of A. centaurus in seven study sites in three West African countries (Ivory Coast, Togo and Nigeria). We recorded 711 light-attracted and/or opportunistically encountered individuals, as well as another 97 beetles in standardized transect surveys. In the latter, we found the adult sex ratio was equal, but was significantly skewed towards females in light-attracted and/or opportunistically encountered individuals. In a sample of 298 adult beetles, males were significantly larger than females, with almost no size overlap between sexes. Beetle activity was highly seasonal with most animals observed in November, active from 19:00 h to 24:00 h. Differences in habitat use were not significant between sexes, with most individuals observed in secondary forest. Males were found higher on vegetation than females and beetles of both sexes were found on Pandanus and raffia palms. Beetles were larger in sites with more vegetation cover, and there was a significant effect of tree species on body size of both sexes. Study area or country had no effect on any of the studied parameters. Our study confirms that transect surveys without light trapping can be an effective tool for understanding large-sized tropical beetles of similar ecological characteristics

Antibody-Directed Lentiviral Gene Transduction for Live-Cell Monitoring and Selection of Human iPS and hES Cells

The identification of stem cells within a mixed population of cells is a major hurdle for stem cell biology–in particular, in the identification of induced pluripotent stem (iPS) cells during the reprogramming process. Based on the selective expression of stem cell surface markers, a method to specifically infect stem cells through antibody-conjugated lentiviral particles has been developed that can deliver both visual markers for live-cell imaging as well as selectable markers to enrich for iPS cells. Antibodies recognizing SSEA4 and CD24 mediated the selective infection of the iPS cells over the parental human fibroblasts, allowing for rapid expansion of these cells by puromycin selection. Adaptation of the vector allows for the selective marking of human embryonic stem (hES) cells for their removal from a population of differentiated cells. This method has the benefit that it not only identifies stem cells, but that specific genes, including positive and negative selection markers, regulatory genes or miRNA can be delivered to the targeted stem cells. The ability to specifically target gene delivery to human pluripotent stem cells has broad applications in tissue engineering and stem cell therapies

An embryonic stem cell–like gene expression signature in poorly differentiated aggressive human tumors

Cancer cells possess traits reminiscent of those ascribed to normal stem cells. It is unclear, however, whether these phenotypic similarities reflect the activity of common molecular pathways. Here, we analyze the enrichment patterns of gene sets associated with embryonic stem (ES) cell identity in the expression profiles of various human tumor types. We find that histologically poorly differentiated tumors show preferential overexpression of genes normally enriched in ES cells, combined with preferential repression of Polycomb-regulated genes. Moreover, activation targets of Nanog, Oct4, Sox2 and c-Myc are more frequently overexpressed in poorly differentiated tumors than in well-differentiated tumors. In breast cancers, this ES-like signature is associated with high-grade estrogen receptor (ER)-negative tumors, often of the basal-like subtype, and with poor clinical outcome. The ES signature is also present in poorly differentiated glioblastomas and bladder carcinomas. We identify a subset of ES cell-associated transcription regulators that are highly expressed in poorly differentiated tumors. Our results reveal a previously unknown link between genes associated with ES cell identity and the histopathological traits of tumors and support the possibility that these genes contribute to stem cell–like phenotypes shown by many tumors

CD133, CD15/SSEA-1, CD34 or side populations do not resume tumor-initiating properties of long-term cultured cancer stem cells from human malignant glio-neuronal tumors

<p>Abstract</p> <p>Background</p> <p>Tumor initiating cells (TICs) provide a new paradigm for developing original therapeutic strategies.</p> <p>Methods</p> <p>We screened for TICs in 47 human adult brain malignant tumors. Cells forming floating spheres in culture, and endowed with all of the features expected from tumor cells with stem-like properties were obtained from glioblastomas, medulloblastoma but not oligodendrogliomas.</p> <p>Results</p> <p>A long-term self-renewal capacity was particularly observed for cells of malignant glio-neuronal tumors (MGNTs). Cell sorting, karyotyping and proteomic analysis demonstrated cell stability throughout prolonged passages. Xenografts of fewer than 500 cells in Nude mouse brains induced a progressively growing tumor. CD133, CD15/LeX/Ssea-1, CD34 expressions, or exclusion of Hoechst dye occurred in subsets of cells forming spheres, but was not predictive of their capacity to form secondary spheres or tumors, or to resist high doses of temozolomide.</p> <p>Conclusions</p> <p>Our results further highlight the specificity of a subset of high-grade gliomas, MGNT. TICs derived from these tumors represent a new tool to screen for innovative therapies.</p

A Gene Expression Signature of Acquired Chemoresistance to Cisplatin and Fluorouracil Combination Chemotherapy in Gastric Cancer Patients

We initiated a prospective trial to identify transcriptional alterations associated with acquired chemotherapy resistance from pre- and post-biopsy samples from the same patient and uncover potential molecular pathways involved in treatment failure to help guide therapeutic alternatives.A prospective, high-throughput transcriptional profiling study was performed using endoscopic biopsy samples from 123 metastatic gastric cancer patients prior to cisplatin and fluorouracil (CF) combination chemotherapy. 22 patients who initially responded to CF were re-biopsied after they developed resistance to CF. An acquired chemotherapy resistance signature was identified by analyzing the gene expression profiles from the matched pre- and post-CF treated samples. The acquired resistance signature was able to segregate a separate cohort of 101 newly-diagnosed gastric cancer patients according to the time to progression after CF. Hierarchical clustering using a 633-gene acquired resistance signature (feature selection at P<0.01) separated the 101 pretreatment patient samples into two groups with significantly different times to progression (2.5 vs. 4.7 months). This 633-gene signature included the upregulation of AKT1, EIF4B, and RPS6 (mTOR pathway), DNA repair and drug metabolism genes, and was enriched for genes overexpressed in embryonic stem cell signatures. A 72-gene acquired resistance signature (a subset of the 633 gene signature also identified in ES cell-related gene sets) was an independent predictor for time to progression (adjusted P = 0.011) and survival (adjusted P = 0.034) of these 101 patients.This signature may offer new insights into identifying new targets and therapies required to overcome the acquired resistance of gastric cancer to CF

Empirical comparison of cross-platform normalization methods for gene expression data

<p>Abstract</p> <p>Background</p> <p>Simultaneous measurement of gene expression on a genomic scale can be accomplished using microarray technology or by sequencing based methods. Researchers who perform high throughput gene expression assays often deposit their data in public databases, but heterogeneity of measurement platforms leads to challenges for the combination and comparison of data sets. Researchers wishing to perform cross platform normalization face two major obstacles. First, a choice must be made about which method or methods to employ. Nine are currently available, and no rigorous comparison exists. Second, software for the selected method must be obtained and incorporated into a data analysis workflow.</p> <p>Results</p> <p>Using two publicly available cross-platform testing data sets, cross-platform normalization methods are compared based on inter-platform concordance and on the consistency of gene lists obtained with transformed data. Scatter and ROC-like plots are produced and new statistics based on those plots are introduced to measure the effectiveness of each method. Bootstrapping is employed to obtain distributions for those statistics. The consistency of platform effects across studies is explored theoretically and with respect to the testing data sets.</p> <p>Conclusions</p> <p>Our comparisons indicate that four methods, DWD, EB, GQ, and XPN, are generally effective, while the remaining methods do not adequately correct for platform effects. Of the four successful methods, XPN generally shows the highest inter-platform concordance when treatment groups are equally sized, while DWD is most robust to differently sized treatment groups and consistently shows the smallest loss in gene detection. We provide an R package, CONOR, capable of performing the nine cross-platform normalization methods considered. The package can be downloaded at <url>http://alborz.sdsu.edu/conor</url> and is available from CRAN.</p