20 resultados para Multiple-trait analysis


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To evaluate the influence of a fluorescent dye (rhodamine B) on the physical and mechanical properties of three different luting cements: a conventional adhesive luting cement (RelyX ARC, 3M/ESPE), a self-adhesive luting cement (RelyX U-200, 3M/ESPE), and a self-etching and self-adhesive luting cement (SeT PP, SDI). The cements were mixed with 0.03 wt% rhodamine B, formed into bar-shaped specimens (n = 10), and light cured using an LED curing unit (Radii, SDI) with a radiant exposure of 32 J/cm(2) . The Knoop hardness (KHN), flexural strength (FS), and Young's modulus (YM) analyses were evaluated after storage for 24 h. Outcomes were subjected to two-way ANOVA and Tukey's test (P = 0.05) for multiple comparisons. No significant differences in FS or YM were observed among the tested groups (P ≥ 0.05); the addition of rhodamine B increased the hardness of the luting cements tested. The addition of a fluorescent agent at 0.03 wt% concentration does not negatively affect the physical-mechanical properties of the luting cement polymerization behavior.

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Multiple sclerosis, which is the most common cause of chronic neurological disability in young adults, is an inflammatory, demyelinating, and neurodegenerative disease of the CNS, which leads to the formation of multiple foci of demyelinated lesions in the white matter. The diagnosis is based currently on magnetic resonance image and evidence of dissemination in time and space. However, this could be facilitated if biomarkers were available to rule out other disorders with similar symptoms as well as to avoid cerebrospinal fluid analysis, which requires an invasive collection. Additionally, the molecular mechanisms of the disease are not completely elucidated, especially those related to the neurodegenerative aspects of the disease. The identification of biomarker candidates and molecular mechanisms of multiple sclerosis may be approached by proteomics. In the last 10 years, proteomic techniques have been applied in different biological samples (CNS tissue, cerebrospinal fluid, and blood) from multiple sclerosis patients and in its experimental model. In this review, we summarize these data, presenting their value to the current knowledge of the disease mechanisms, as well as their importance in identifying biomarkers or treatment targets.

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The efficacy of the human papillomavirus type 16 (HPV-16)/HPV-18 AS04-adjuvanted vaccine against cervical infections with HPV in the Papilloma Trial against Cancer in Young Adults (PATRICIA) was evaluated using a combination of the broad-spectrum L1-based SPF10 PCR-DNA enzyme immunoassay (DEIA)/line probe assay (LiPA25) system with type-specific PCRs for HPV-16 and -18. Broad-spectrum PCR assays may underestimate the presence of HPV genotypes present at relatively low concentrations in multiple infections, due to competition between genotypes. Therefore, samples were retrospectively reanalyzed using a testing algorithm incorporating the SPF10 PCR-DEIA/LiPA25 plus a novel E6-based multiplex type-specific PCR and reverse hybridization assay (MPTS12 RHA), which permits detection of a panel of nine oncogenic HPV genotypes (types 16, 18, 31, 33, 35, 45, 52, 58, and 59). For the vaccine against HPV types 16 and 18, there was no major impact on estimates of vaccine efficacy (VE) for incident or 6-month or 12-month persistent infections when the MPTS12 RHA was included in the testing algorithm versus estimates with the protocol-specified algorithm. However, the alternative testing algorithm showed greater sensitivity than the protocol-specified algorithm for detection of some nonvaccine oncogenic HPV types. More cases were gained in the control group than in the vaccine group, leading to higher point estimates of VE for 6-month and 12-month persistent infections for the nonvaccine oncogenic types included in the MPTS12 RHA assay (types 31, 33, 35, 45, 52, 58, and 59). This post hoc analysis indicates that the per-protocol testing algorithm used in PATRICIA underestimated the VE against some nonvaccine oncogenic HPV types and that the choice of the HPV DNA testing methodology is important for the evaluation of VE in clinical trials. (This study has been registered at ClinicalTrials.gov under registration no. NCT00122681.).

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ANKHD1 (Ankyrin repeat and KH domain-containing protein 1) is highly expressed and plays an important role in the proliferation and cell cycle progression of multiple myeloma (MM) cells. ANKHD1 downregulation modulates cell cycle gene expression and upregulates p21 irrespective of the TP53 mutational status of MM cell lines. The present study was aimed to investigate the role of ANKHD1 in MM in vitro clonogenicity and in vivo tumourigenicity, as well as the role of ANKHD1 in p21 transcriptional regulation. ANKHD1 silencing in MM cells resulted in significantly low no. of colonies formed and in slow migration as compared to control cells (p < 0.05). Furthermore, in xenograft MM mice models, tumour growth was visibly suppressed in mice injected with ANKHD1 silenced cells compared to the control group. There was a significant decrease in tumour volume (p = 0.006) as well as in weight (p = 0.02) in the group injected with silenced cells compared to those of the control group. Co-immunoprecipitation and chromatin immunoprecipitation (ChIP) assays confirmed the interaction between p21 and ANKHD1. Moreover, overexpression of ANKHD1 downregulated the activity of a p21 promoter in luciferase assays. Decrease in luciferase activity suggests a direct role of ANKHD1 in p21 transcriptional regulation. In addition confocal analysis after U266 cells were treated with Leptomycin B (LMB) for 24 h showed accumulation of ANKHD1 inside the nucleus as compared to untreated cells where ANKHD1 was found to be predominantly in cytoplasm. This suggests ANKHD1 might be shuttling between cytoplasm and nucleus. In conclusion, ANKHD1 promotes MM growth by repressing p21 a potent cell cycle regulator.

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A common breeding strategy is to carry out basic studies to investigate the hypothesis of a single gene controlling the trait (major gene) with or without polygenes of minor effect. In this study we used Bayesian inference to fit genetic additive-dominance models of inheritance to plant breeding experiments with multiple generations. Normal densities with different means, according to the major gene genotype, were considered in a linear model in which the design matrix of the genetic effects had unknown coefficients (which were estimated in individual basis). An actual data set from an inheritance study of partenocarpy in zucchini (Cucurbita pepo L.) was used for illustration. Model fitting included posterior probabilities for all individual genotypes. Analysis agrees with results in the literature but this approach was far more efficient than previous alternatives assuming that design matrix was known for the generations. Partenocarpy in zucchini is controlled by a major gene with important additive effect and partial dominance.