55 resultados para Models, Molecular
Resumo:
Background: Pedigree reconstruction using genetic analysis provides a useful means to estimate fundamental population biology parameters relating to population demography, trait heritability and individual fitness when combined with other sources of data. However, there remain limitations to pedigree reconstruction in wild populations, particularly in systems where parent-offspring relationships cannot be directly observed, there is incomplete sampling of individuals, or molecular parentage inference relies on low quality DNA from archived material. While much can still be inferred from incomplete or sparse pedigrees, it is crucial to evaluate the quality and power of available genetic information a priori to testing specific biological hypotheses. Here, we used microsatellite markers to reconstruct a multi-generation pedigree of wild Atlantic salmon (Salmo salar L.) using archived scale samples collected with a total trapping system within a river over a 10 year period. Using a simulation-based approach, we determined the optimal microsatellite marker number for accurate parentage assignment, and evaluated the power of the resulting partial pedigree to investigate important evolutionary and quantitative genetic characteristics of salmon in the system.
Results: We show that at least 20 microsatellites (ave. 12 alleles/locus) are required to maximise parentage assignment and to improve the power to estimate reproductive success and heritability in this study system. We also show that 1.5 fold differences can be detected between groups simulated to have differing reproductive success, and that it is possible to detect moderate heritability values for continuous traits (h(2) similar to 0.40) with more than 80% power when using 28 moderately to highly polymorphic markers.
Conclusion: The methodologies and work flow described provide a robust approach for evaluating archived samples for pedigree-based research, even where only a proportion of the total population is sampled. The results demonstrate the feasibility of pedigree-based studies to address challenging ecological and evolutionary questions in free-living populations, where genealogies can be traced only using molecular tools, and that significant increases in pedigree assignment power can be achieved by using higher numbers of markers.
Resumo:
The reciprocal interaction between cancer cells and the tissue-specific stroma is critical for primary and metastatic tumor growth progression. Prostate cancer cells colonize preferentially bone (osteotropism), where they alter the physiological balance between osteoblast-mediated bone formation and osteoclast-mediated bone resorption, and elicit prevalently an osteoblastic response (osteoinduction). The molecular cues provided by osteoblasts for the survival and growth of bone metastatic prostate cancer cells are largely unknown. We exploited the sufficient divergence between human and mouse RNA sequences together with redefinition of highly species-specific gene arrays by computer-aided and experimental exclusion of cross-hybridizing oligonucleotide probes. This strategy allowed the dissection of the stroma (mouse) from the cancer cell (human) transcriptome in bone metastasis xenograft models of human osteoinductive prostate cancer cells (VCaP and C4-2B). As a result, we generated the osteoblastic bone metastasis-associated stroma transcriptome (OB-BMST). Subtraction of genes shared by inflammation, wound healing and desmoplastic responses, and by the tissue type-independent stroma responses to a variety of non-osteotropic and osteotropic primary cancers generated a curated gene signature ("Core" OB-BMST) putatively representing the bone marrow/bone-specific stroma response to prostate cancer-induced, osteoblastic bone metastasis. The expression pattern of three representative Core OB-BMST genes (PTN, EPHA3 and FSCN1) seems to confirm the bone specificity of this response. A robust induction of genes involved in osteogenesis and angiogenesis dominates both the OB-BMST and Core OB-BMST. This translates in an amplification of hematopoietic and, remarkably, prostate epithelial stem cell niche components that may function as a self-reinforcing bone metastatic niche providing a growth support specific for osteoinductive prostate cancer cells. The induction of this combinatorial stem cell niche is a novel mechanism that may also explain cancer cell osteotropism and local interference with hematopoiesis (myelophthisis). Accordingly, these stem cell niche components may represent innovative therapeutic targets and/or serum biomarkers in osteoblastic bone metastasis.
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This work aimed to evaluate whether ETS transcription factors frequently involved in rearrangements in prostate carcinomas (PCa), namely ERG and ETV1, regulate specific or shared target genes. We performed differential expression analysis on nine normal prostate tissues and 50 PCa enriched for different ETS rearrangements using exon-level expression microarrays, followed by in vitro validation using cell line models. We found specific deregulation of 57 genes in ERG-positive PCa and 15 genes in ETV1-positive PCa, whereas deregulation of 27 genes was shared in both tumor subtypes. We further showed that the expression of seven tumor-associated ERG target genes (PLA1A, CACNA1D, ATP8A2, HLA-DMB, PDE3B, TDRD1, and TMBIM1) and two tumor-associated ETV1 target genes (FKBP10 and GLYATL2) was significantly affected by specific ETS silencing in VCaP and LNCaP cell line models, respectively, whereas the expression of three candidate ERG and ETV1 shared targets (GRPR, KCNH8, and TMEM45B) was significantly affected by silencing of either ETS. Interestingly, we demonstrate that the expression of TDRD1, the topmost overexpressed gene of our list of ERG-specific candidate targets, is inversely correlated with the methylation levels of a CpG island found at -66 bp of the transcription start site in PCa and that TDRD1 expression is regulated by direct binding of ERG to the CpG island in VCaP cells. We conclude that ETS transcription factors regulate specific and shared target genes and that TDRD1, FKBP10, and GRPR are promising therapeutic targets and can serve as diagnostic markers for molecular subtypes of PCa harboring specific fusion gene rearrangements.
Resumo:
Molecular Dynamics Simulations (MDS) are constantly being used to make important contributions to our fundamental understanding of material behaviour, at the atomic scale, for a variety of thermodynamic processes. This chapter shows that molecular dynamics simulation is a robust numerical analysis tool in addressing a range of complex nanofinishing (machining) problems that are otherwise difficult or impossible to understand using other methods. For example the mechanism of nanometric cutting of silicon carbide is influenced by a number of variables such as machine tool performance, machining conditions, material properties, and cutting tool performance (material microstructure and physical geometry of the contact) and all these variables cannot be monitored online through experimental examination. However, these could suitably be studied using an advanced simulation based approach such as MDS. This chapter details how MD simulation can be used as a research and commercial tool to understand key issues of ultra precision manufacturing research problems and a specific case was addressed by studying diamond machining of silicon carbide. While this is appreciable, there are a lot of challenges and opportunities in this fertile area. For example, the world of MD simulations is dependent on present day computers and the accuracy and reliability of potential energy functions [109]. This presents a limitation: Real-world scale simulation models are yet to be developed. The simulated length and timescales are far shorter than the experimental ones which couples further with the fact that contact loading simulations are typically done in the speed range of a few hundreds of m/sec against the experimental speed of typically about 1 m/sec [17]. Consequently, MD simulations suffer from the spurious effects of high cutting speeds and the accuracy of the simulation results has yet to be fully explored. The development of user-friendly software could help facilitate molecular dynamics as an integral part of computer-aided design and manufacturing to tackle a range of machining problems from all perspectives, including materials science (phase of the material formed due to the sub-surface deformation layer), electronics and optics (properties of the finished machined surface due to the metallurgical transformation in comparison to the bulk material), and mechanical engineering (extent of residual stresses in the machined component) [110]. Overall, this chapter provided key information concerning diamond machining of SiC which is classed as hard, brittle material. From the analysis presented in the earlier sections, MD simulation has helped in understanding the effects of crystal anisotropy in nanometric cutting of 3C-SiC by revealing the atomic-level deformation mechanisms for different crystal orientations and cutting directions. In addition to this, the MD simulation revealed that the material removal mechanism on the (111) surface of 3C-SiC (akin to diamond) is dominated by cleavage. These understandings led to the development of a new approach named the “surface defect machining” method which has the potential to be more effective to implement than ductile mode micro laser assisted machining or conventional nanometric cutting.
Resumo:
The introduction of predictive molecular markers has radically enhanced the identification of which patients may benefit from a given treatment. Despite recent controversies, KRAS mutation is currently the most recognized molecular predictive marker in colorectal cancer (CRC), predicting efficacy of anti-epidermal growth factor receptor (anti-EGFR) antibodies. However, other relevant markers have been reported and claimed to identify patients that will benefit from anti-EGFR therapies. This group of markers includes BRAF mutations, PI3KCA mutations, and loss of PTEN expression. Similarly, molecular markers for cytotoxic agents' efficacy also may predict outcome in patients with CRC. This review aims to summarize the most important predictive molecular classifiers in patients with CRC and further discuss any inconsistent or conflicting findings for these molecular classifiers.
Resumo:
Quantitative structure-property relationship (QSPR) models were firstly established for the hydrophobic substituent constant (πX) using the theoretical descriptors derived solely from electrostatic potentials (EPSs) at the substituent atoms. The descriptors introduced are found to be related to hydrogen-bond basicity, hydrogen-bond acidity, cavity, or dipolarity/polarizability terms in linear solvation energy relationship, which endows the models good interpretability. The predictive capabilities of the models constructed were also verified by rigorous Monte Carlo cross-validation. Then, eight groups of meta- or para- disubstituted benzenes and one group of substituted pyridines were investigated. QSPR models for individual systems were achieved with the ESP-derived descriptors. Additionally, two QSPR models were also established for Rekker's fragment constants (foct), which is a secondary-treatment quantity and reflects average contribution of the fragment to logP. It has been demonstrated that the descriptors derived from ESPs at the fragments, can be well used to quantitatively express the relationship between fragment structures and their hydrophobic properties, regardless of the attached parent structure or the valence state. Finally, the relations of Hammett σ constant and ESP quantities were explored. It implies that σ and π, which are essential in classic QSAR and represent different type of contributions to biological activities, are also complementary in interaction site.
Resumo:
The frog skin host-defense peptide tigerinin-1R stimulates insulin release in vitro and improves glucose tolerance and insulin sensitivity in animal models of type 2 diabetes. This study extends these observation by investigating the molecular mechanisms of action underlying the beneficial metabolic effects of the analogue [Arg4]tigerinin-1R in mice with diet induced obesity, glucose intolerance and insulin resistance. The study also investigates the electrophysiological effects of the peptide on KATP and L-type Ca2+ channels in BRINBD11 clonal β cells. Non-fasting plasma glucose and glucagon concentrations were significantly (P<0.05) decreased and plasma insulin increased by twice daily treatment with [Arg4]tigerinin-1R (75 nmol.kg-1 body weight) for 28 days. Oral and intraperitoneal glucose tolerance were significantly (P < 0.05) improved accompanied by enhanced secretion and action of insulin. The peptide blocked KATP channels and, consistent with this, improved beta cell responses of isolated islets to a range of secretagogues. Peptide administration resulted in up-regulation of key functional genes in islets involved insulin secretion (Abcc8, Kcnj11, Cacna1c and Slc2a2) and in skeletal muscle involved with insulin action (Insr, Irs1, Pdk1, Pik3ca, and Slc2a4). These observations encourage further development of tigerinin-1R analogues for the treatment of patients with type 2 diabetes.
Resumo:
We calculate near-threshold bound states and Feshbach resonance positions for atom–rigid-rotor models of the highly anisotropic systems Li+CaH and Li+CaF. We perform statistical analysis on the resonance positions to compare with the predictions of random matrix theory. For Li+CaH with total angular momentum J=0 we find fully chaotic behavior in both the nearest-neighbor spacing distribution and the level number variance. However, for J>0 we find different behavior due to the presence of a nearly conserved quantum number. Li+CaF (J=0) also shows apparently reduced levels of chaotic behavior despite its stronger effective coupling. This may indicate the development of another good quantum number relating to a bending motion of the complex. However, continuously varying the rotational constant over a wide range shows unexpected structure in the degree of chaotic behavior, including a dramatic reduction around the rotational constant of CaF. This demonstrates the complexity of the relationship between coupling and chaotic behavior.
Resumo:
We propose a mechanism for testing the theory of collapse models such as continuous spontaneous localization (CSL) by examining the parametric heating rate of a trapped nanosphere. The random localizations of the center-of-mass for a given particle predicted by the CSL model can be understood as a stochastic force embodying a source of heating for the nanosphere. We show that by utilising a Paul trap to levitate the particle and optical cooling, it is possible to reduce environmental decoher- ence to such a level that CSL dominates the dynamics and contributes the main source of heating. We show that this approach allows measurements to be made on the timescale of seconds, and that the free parameter λcsl which characterises the model ought to be testable to values as low as 10^{−12} Hz.
Resumo:
We have used whole exome sequencing to compare a group of presentation t(4;14) with t(11;14) cases of myeloma to define the mutational landscape. Each case was characterized by a median of 24.5 exonic nonsynonymous single-nucleotide variations, and there was a consistently higher number of mutations in the t(4;14) group, but this number did not reach statistical significance. We show that the transition and transversion rates in the 2 subgroups are similar, suggesting that there was no specific mechanism leading to mutation differentiating the 2 groups. Only 3% of mutations were seen in both groups, and recurrently mutated genes include NRAS, KRAS, BRAF, and DIS3 as well as DNAH5, a member of the axonemal dynein family. The pattern of mutation in each group was distinct, with the t(4;14) group being characterized by deregulation of chromatin organization, actin filament, and microfilament movement. Recurrent RAS pathway mutations identified subclonal heterogeneity at a mutational level in both groups, with mutations being present as either dominant or minor subclones. The presence of subclonal diversity was confirmed at a single-cell level using other tumor-acquired mutations. These results are consistent with a distinct molecular pathogenesis underlying each subgroup and have important impacts on targeted treatment strategies. The Medical Research Council Myeloma IX trial is registered under ISRCTN68454111.