FGFR2 mutations are rare across histologic subtypes of ovarian cancer

OBJECTIVE: Ovarian cancer is the leading cause of death from gynecologic malignancies in the Western world. Fibroblast growth factor receptor (FGFR) signaling has been implicated to play a role in ovarian tumorigenesis. Mutational activation of one member of this receptor family, FGFR2, is a frequent event in endometrioid endometrial cancer. Given the similarities in the histologic and molecular genetics of ovarian and endometrial cancers, we hypothesized that activating FGFR2 mutations may occur in a subset of endometrioid ovarian tumors, and possibly other histotypes. METHODS: Six FGFR2 exons were sequenced in 120 primary ovarian tumors representing the major histologic subtypes. RESULTS: FGFR2 mutation was detected at low frequency in endometrioid (1/46, 2.2%) and serous (1/41, 2.4%) ovarian cancer. No mutations were detected in clear cell, mucinous, or mixed histology tumors or in the ovarian cancer cell lines tested. Functional characterization of the FGFR2 mutations confirmed that the mutations detected in ovarian cancer result in receptor activation. CONCLUSIONS: Despite the low incidence of FGFR2 mutations in ovarian cancer, the two FGFR2 mutations identified in ovarian tumors (S252W, Y376C) overlap with the oncogenic mutations previously identified in endometrial tumors, suggesting activated FGFR2 may contribute to ovarian cancer pathogenesis in a small subset of ovarian tumors.

Advanced numerical characterization of mono-crystalline copper with defects

Based on the embedded atom method (EAM) and molecular dynamics (MD) method, the mono-crystalline copper with different defects is investigated through tension and nanoindentation simulation. The single-crystal copper nanowire with surface defects is firstly studied through tension. For validation, the tension simulations for nanowire without defect are carried out under different temperatures and strain rates. The defects on nanowires are then systematically studied in considering different defects orientation distribution. It is found that the Young’s modulus is insensitive of surface defects and centro-plane defects. However, the yield strength and yield point show a significant decrease due to the different defects. Specially, the 〖45〗^° defect in surface and in (200) plane exerts the biggest influence to the yield strength, about 34.20% and 51.45% decrease are observed, respectively. Different defects are observed to serve as a dislocation source and different necking positions of the nanowires during tension are found. During nanoindentation simulation, dislocation is found nucleating below the contact area, but no obvious dislocation is generated around the nano-cavity. Comparing with the perfect substrate during nanoindentation, the substrate with nano-cavities emerged less dislocations, it is supposed that the nano-cavity absorbed part of the indent energy, and less plastic deformation happened in the defected substrate.

Cloning and characterization of a novel human gene related to vascular endothelial growth factor

This paper describes the cloning and characterization of a new member of the vascular endothelial growth factor (VEGF) gene family, which we have designated VRF for VEGF-related-factor. Sequencing of cDNAs from a human fetal brain library and RT-PCR products from normal and tumor tissue cDNA pools indicate two alternatively spliced messages with open reading frames of 621 and 564 bp, respectively. The predicted proteins differ at their carboxyl ends resulting from a shift in the open reading frame. Both isoforms show strong homology to VEGF at their amino termini, but only the shorter isoform maintains homology to VEGF at its carboxyl terminus and conserves all 16 cysteine residues of VEGF165. Similarity comparisons of this isoform revealed overall protein identity of 48% and conservative substitution of 69% with VEGF189. VRF is predicted to contain a signal peptide, suggesting that it may be a secreted factor. The VRF gene maps to the D11S750 locus at chromosome band 11q13, and the protein coding region, spanning approximately 5 kb, is comprised of 8 exons that range in size from 36 to 431 bp. Exons 6 and 7 are contiguous and the two isoforms of VRF arise through alternate splicing of exon 6. VRF appears to be ubiquitously expressed as two transcripts of 2.0 and 5.5 kb; the level of expression is similar among normal and malignant tissues.

The genetics of cutaneous melanoma

Although germline mutations in CDKN2A are present in approximately 25% of large multicase melanoma families, germline mutations are much rarer in the smaller melanoma families that make up most individuals reporting a family history of this disease. In addition, only three families worldwide have been reported with germline mutations in a gene other than CDKN2A (i.e., CDK4). Accordingly, current genomewide scans underway at the National Human Genome Research Institute hope to reveal linkage to one or more chromosomal regions, and ultimately lead to the identification of novel genes involved in melanoma predisposition. Both CDKN2A and PTEN have been identified as genes involved in sporadic melanoma development; however, mutations are more common in cell lines than uncultured tumors. A combination of cytogenetic, molecular, and functional studies suggests that additional genes involved in melanoma development are located to chromosomal regions 1p, 6q, 7p, 11q, and possibly also 9p and 10q. With the near completion of the human genome sequencing effort, combined with the advent of high throughput mutation analyses and new techniques including cDNA and tissue microarrays, the identification and characterization of additional genes involved in melanoma pathogenesis seem likely in the near future.

Accelerated leap methods for simulating discrete stochastic chemical kinetics

Biologists are increasingly conscious of the critical role that noise plays in cellular functions such as genetic regulation, often in connection with fluctuations in small numbers of key regulatory molecules. This has inspired the development of models that capture this fundamentally discrete and stochastic nature of cellular biology - most notably the Gillespie stochastic simulation algorithm (SSA). The SSA simulates a temporally homogeneous, discrete-state, continuous-time Markov process, and of course the corresponding probabilities and numbers of each molecular species must all remain positive. While accurately serving this purpose, the SSA can be computationally inefficient due to very small time stepping so faster approximations such as the Poisson and Binomial τ-leap methods have been suggested. This work places these leap methods in the context of numerical methods for the solution of stochastic differential equations (SDEs) driven by Poisson noise. This allows analogues of Euler-Maruyuma, Milstein and even higher order methods to be developed through the Itô-Taylor expansions as well as similar derivative-free Runge-Kutta approaches. Numerical results demonstrate that these novel methods compare favourably with existing techniques for simulating biochemical reactions by more accurately capturing crucial properties such as the mean and variance than existing methods.

Supplement : Efficient weak second-order stochastic Runge-Kutta methods for non-commutative Stratonvich stochastic differential equations

This paper gives a modification of a class of stochastic Runge–Kutta methods proposed in a paper by Komori (2007). The slight modification can reduce the computational costs of the methods significantly.

On a Syntactic Characterization of Classification with a Mind Change Bound

Most learning paradigms impose a particular syntax on the class of concepts to be learned; the chosen syntax can dramatically affect whether the class is learnable or not. For classification paradigms, where the task is to determine whether the underlying world does or does not have a particular property, how that property is represented has no implication on the power of a classifier that just outputs 1’s or 0’s. But is it possible to give a canonical syntactic representation of the class of concepts that are classifiable according to the particular criteria of a given paradigm? We provide a positive answer to this question for classification in the limit paradigms in a logical setting, with ordinal mind change bounds as a measure of complexity. The syntactic characterization that emerges enables to derive that if a possibly noncomputable classifier can perform the task assigned to it by the paradigm, then a computable classifier can also perform the same task. The syntactic characterization is strongly related to the difference hierarchy over the class of open sets of some topological space; this space is naturally defined from the class of possible worlds and possible data of the learning paradigm.

Investigation of methods for increasing the energy efficiency on unmanned aerial vehicles (UAVS)

In recent years, development of Unmanned Aerial Vehicles (UAV) has become a significant growing segment of the global aviation industry. These vehicles are developed with the intention of operating in regions where the presence of onboard human pilots is either too risky or unnecessary. Their popularity with both the military and civilian sectors have seen the use of UAVs in a diverse range of applications, from reconnaissance and surveillance tasks for the military, to civilian uses such as aid relief and monitoring tasks. Efficient energy utilisation on an UAV is essential to its functioning, often to achieve the operational goals of range, endurance and other specific mission requirements. Due to the limitations of the space available and the mass budget on the UAV, it is often a delicate balance between the onboard energy available (i.e. fuel) and achieving the operational goals. This thesis presents an investigation of methods for increasing the energy efficiency on UAVs. One method is via the development of a Mission Waypoint Optimisation (MWO) procedure for a small fixed-wing UAV, focusing on improving the onboard fuel economy. MWO deals with a pre-specified set of waypoints by modifying the given waypoints within certain limits to achieve its optimisation objectives of minimising/maximising specific parameters. A simulation model of a UAV was developed in the MATLAB Simulink environment, utilising the AeroSim Blockset and the in-built Aerosonde UAV block and its parameters. This simulation model was separately integrated with a multi-objective Evolutionary Algorithm (MOEA) optimiser and a Sequential Quadratic Programming (SQP) solver to perform single-objective and multi-objective optimisation procedures of a set of real-world waypoints in order to minimise the onboard fuel consumption. The results of both procedures show potential in reducing fuel consumption on a UAV in a ight mission. Additionally, a parallel Hybrid-Electric Propulsion System (HEPS) on a small fixedwing UAV incorporating an Ideal Operating Line (IOL) control strategy was developed. An IOL analysis of an Aerosonde engine was performed, and the most efficient (i.e. provides greatest torque output at the least fuel consumption) points of operation for this engine was determined. Simulation models of the components in a HEPS were designed and constructed in the MATLAB Simulink environment. It was demonstrated through simulation that an UAV with the current HEPS configuration was capable of achieving a fuel saving of 6.5%, compared to the ICE-only configuration. These components form the basis for the development of a complete simulation model of a Hybrid-Electric UAV (HEUAV).

Novel numerical methods for time-space fractional reaction diffusion equations in two dimensions

We consider time-space fractional reaction diffusion equations in two dimensions. This equation is obtained from the standard reaction diffusion equation by replacing the first order time derivative with the Caputo fractional derivative, and the second order space derivatives with the fractional Laplacian. Using the matrix transfer technique proposed by Ilic, Liu, Turner and Anh [Fract. Calc. Appl. Anal., 9:333--349, 2006] and the numerical solution strategy used by Yang, Turner, Liu, and Ilic [SIAM J. Scientific Computing, 33:1159--1180, 2011], the solution of the time-space fractional reaction diffusion equations in two dimensions can be written in terms of a matrix function vector product $f(A)b$ at each time step, where $A$ is an approximate matrix representation of the standard Laplacian. We use the finite volume method over unstructured triangular meshes to generate the matrix $A$, which is therefore non-symmetric. However, the standard Lanczos method for approximating $f(A)b$ requires that $A$ is symmetric. We propose a simple and novel transformation in which the standard Lanczos method is still applicable to find $f(A)b$, despite the loss of symmetry. Numerical results are presented to verify the accuracy and efficiency of our newly proposed numerical solution strategy.