Learning Rich Geographical Representations: Predicting Colorectal Cancer Survival in the State of Iowa

Neural networks are capable of learning rich, nonlinear feature representations shown to be beneficial in many predictive tasks. In this work, we use these models to explore the use of geographical features in predicting colorectal cancer survival curves for patients in the state of Iowa, spanning the years 1989 to 2012. Specifically, we compare model performance using a newly defined metric -- area between the curves (ABC) -- to assess (a) whether survival curves can be reasonably predicted for colorectal cancer patients in the state of Iowa, (b) whether geographical features improve predictive performance, and (c) whether a simple binary representation or richer, spectral clustering-based representation perform better. Our findings suggest that survival curves can be reasonably estimated on average, with predictive performance deviating at the five-year survival mark. We also find that geographical features improve predictive performance, and that the best performance is obtained using richer, spectral analysis-elicited features.Comment: 8 page

New interpretation of matter-antimatter asymmetry based on branes and possible observational consequences

Motivated by the AMS project, we assume that after the Big Bang or inflation epoch, antimatter was repelled onto one brane which is separated from our brane where all the observational matter resides. It is suggested that CP may be spontaneously broken, the two branes would correspond to ground states for matter and antimatter respectively. Generally a complex scalar field which is responsible for the spontaneous CP violation, exists in the space between the branes and causes a repulsive force against the gravitation. A possible potential barrier prevents the mater(antimatter) particles to enter the space between two branes. However, by the quantum tunnelling, a sizable anti-matter flux may come to our brane. In this work by considering two possible models, i.e. the naive flat space-time and Randall-Sundrum models and using the observational data on the visible matter in our universe as inputs, we derive the antimatter flux which would be observed by the AMS detector.Comment: 10 pages, 4 figures and 2 tables. Replaced by new versio

The statistical properties of galaxy morphological types in compact groups of Main galaxies from the SDSS Data Release 4

In order to explore the statistical properties of galaxy morphological types in compact groups (CGs), we construct a random group sample which has the same distributions of redshift and number of member galaxies as those of the CG sample. It turns out that the proportion of early-type galaxies in different redshift bins for the CG sample is statistically higher than that for random group sample, and with growing redshift z this kind of difference becomes more significant. This may be due to the existence of interactions and mergers within a significant fraction of SDSS CGs. We also compare statistical results of CGs with those of more compact groups and pairs, but do not observe as large statistical difference as Hickson (1982)'results.Comment: 12 pages, 9 figure

PEGylated graphene oxide for tumor-targeted delivery of paclitaxel.

AIM: The graphene oxide (GO) sheet has been considered one of the most promising carbon derivatives in the field of material science for the past few years and has shown excellent tumor-targeting ability, biocompatibility and low toxicity. We have endeavored to conjugate paclitaxel (PTX) to GO molecule and investigate its anticancer efficacy. MATERIALS & METHODS: We conjugated the anticancer drug PTX to aminated PEG chains on GO sheets through covalent bonds to get GO-PEG-PTX complexes. The tissue distribution and anticancer efficacy of GO-PEG-PTX were then investigated using a B16 melanoma cancer-bearing C57 mice model. RESULTS: The GO-PEG-PTX complexes exhibited excellent water solubility and biocompatibility. Compared with the traditional formulation of PTX (Taxol®), GO-PEG-PTX has shown prolonged blood circulation time as well as high tumor-targeting and -suppressing efficacy. CONCLUSION: PEGylated graphene oxide is an excellent nanocarrier for paclitaxel for cancer targeting

Antibunching photons in a cavity coupled to an optomechanical system

We study the photon statistics of a cavity linearly coupled to an optomechanical system via second order correlation functions. Our calculations show that the cavity can exhibit strong photon antibunching even when optomechanical interaction in the optomechanical system is weak. The cooperation between the weak optomechanical interaction and the destructive interference between different paths for two-photon excitation leads to the efficient antibunching effect. Compared with the standard optomechanical system, the coupling between a cavity and an optomechanical system provides a method to relax the constraints to obtain single photon by optomechanical interaction.Comment: 7 papes, 5 figure

SplitTester : software to identify domains responsible for functional divergence in protein family

BACKGROUND: Many protein families have undergone functional divergence after gene duplications such that current subgroups of the family carry out overlapping but distinct biological roles. For the protein families with known functional subtypes (a functional split), we developed the software, SplitTester, to identify potential regions that are responsible for the observed distinct functional subtypes within the same protein family. RESULTS: Our software, SplitTester, takes a multiple protein sequences alignment as input, generated from protein members of two subgroups with known functional divergence. SplitTester was designed to construct the neighbor joining tree (a split cluster) from variable-sized sliding windows across the alignment in a process called split-clustering. SplitTester identifies the regions, whose split cluster is consistent with the functional split, but may be inconsistent with the phylogeny of the protein family. We hypothesize that at least some number of these identified regions, which are not following a random mutation process, are responsible for the observed functional split. To test our method, we used reverse transcriptase from a group of Pseudoviridae retrotransposons: to identify residues specific for diverged primer recognition. Candidate regions were then mapped onto the three dimensional structures of reverse transcriptase. The locations of these amino acids within the enzyme are consistent with their biological roles. CONCLUSION: SplitTester aims to identify specific domain sequences responsible for functional divergence of subgroups within a protein family. From the analysis of retroelements reverse transcriptase family, we successfully identified the regions splitting this family according to the primer specificity, implying their functions in the specific primer selection