Unpaired multi-modal segmentation via knowledge distillation

Multi-modal learning is typically performed with network architectures containing modality-specific layers and shared layers, utilizing co-registered images of different modalities. We propose a novel learning scheme for unpaired cross-modality image segmentation, with a highly compact architecture achieving superior segmentation accuracy. In our method, we heavily reuse network parameters, by sharing all convolutional kernels across CT and MRI, and only employ modality-specific internal normalization layers which compute respective statistics. To effectively train such a highly compact model, we introduce a novel loss term inspired by knowledge distillation, by explicitly constraining the KL-divergence of our derived prediction distributions between modalities. We have extensively validated our approach on two multi-class segmentation problems: i) cardiac structure segmentation, and ii) abdominal organ segmentation. Different network settings, i.e., 2D dilated network and 3D U-net, are utilized to investigate our method's general efficacy. Experimental results on both tasks demonstrate that our novel multi-modal learning scheme consistently outperforms single-modal training and previous multi-modal approaches

BPS States in Omega Background and Integrability

We reconsider string and domain wall central charges in N=2 supersymmetric gauge theories in four dimensions in presence of the Omega background in the Nekrasov-Shatashvili (NS) limit. Existence of these charges entails presence of the corresponding topological defects in the theory - vortices and domain walls. In spirit of the 4d/2d duality we discuss the worldsheet low energy effective theory living on the BPS vortex in N=2 Supersymmetric Quantum Chromodynamics (SQCD). We discuss some aspects of the brane realization of the dualities between various quantum integrable models. A chain of such dualities enables us to check the AGT correspondence in the NS limit.Comment: 48 pages, 10 figures, minor changes, references added, typos correcte

New Method to Prepare Mitomycin C Loaded PLA-Nanoparticles with High Drug Entrapment Efficiency

The classical utilized double emulsion solvent diffusion technique for encapsulating water soluble Mitomycin C (MMC) in PLA nanoparticles suffers from low encapsulation efficiency because of the drug rapid partitioning to the external aqueous phase. In this paper, MMC loaded PLA nanoparticles were prepared by a new single emulsion solvent evaporation method, in which soybean phosphatidylcholine (SPC) was employed to improve the liposolubility of MMC by formation of MMC–SPC complex. Four main influential factors based on the results of a single-factor test, namely, PLA molecular weight, ratio of PLA to SPC (wt/wt) and MMC to SPC (wt/wt), volume ratio of oil phase to water phase, were evaluated using an orthogonal design with respect to drug entrapment efficiency. The drug release study was performed in pH 7.2 PBS at 37 °C with drug analysis using UV/vis spectrometer at 365 nm. MMC–PLA particles prepared by classical method were used as comparison. The formulated MMC–SPC–PLA nanoparticles under optimized condition are found to be relatively uniform in size (594 nm) with up to 94.8% of drug entrapment efficiency compared to 6.44 μm of PLA–MMC microparticles with 34.5% of drug entrapment efficiency. The release of MMC shows biphasic with an initial burst effect, followed by a cumulated drug release over 30 days is 50.17% for PLA–MMC–SPC nanoparticles, and 74.1% for PLA–MMC particles. The IR analysis of MMC–SPC complex shows that their high liposolubility may be attributed to some weak physical interaction between MMC and SPC during the formation of the complex. It is concluded that the new method is advantageous in terms of smaller size, lower size distribution, higher encapsulation yield, and longer sustained drug release in comparison to classical method

Breast cancer risk factors in relation to breast density (United States)

OBJECTIVES: Evaluate known breast cancer risk factors in relation to breast density. METHODS: We examined factors in relation to breast density in 144,018 New Hampshire (NH) women with at least one mammogram recorded in a statewide mammography registry. Mammographic breast density was measured by radiologists using the BI-RADS classification; risk factors of interest were obtained from patient intake forms and questionnaires. RESULTS: Initial analyses showed a strong inverse influence of age and body mass index (BMI) on breast density. In addition, women with late age at menarche, late age at first birth, premenopausal women, and those currently using hormone therapy (HT) tended to have higher breast density, while those with greater parity tended to have less dense breasts. Analyses stratified on age and BMI suggested interactions, which were formally assessed in a multivariable model. The impact of current HT use, relative to nonuse, differed across age groups, with an inverse association in younger women, and a positive association in older women (p < 0.0001 for the interaction). The positive effects of age at menarche and age at first birth, and the inverse influence of parity were less apparent in women with low BMI than in those with high BMI (p = 0.04, p < 0.0001 and p = 0.01, respectively, for the interactions). We also noted stronger positive effects for age at first birth in postmenopausal women (p = 0.004 for the interaction). The multivariable model indicated a slight positive influence of family history of breast cancer. CONCLUSIONS: The influence of age at menarche and reproductive factors on breast density is less evident in women with high BMI. Density is reduced in young women using HT, but increased in HT users of age 50 or more

The Use of a Stringent Selection System Allows the Identification of DNA Elements that Augment Gene Expression

The use of high stringency selection systems often results in the induction of very few recombinant mammalian cell lines, which limits the ability to isolate a cell line with favorable characteristics. The employment of for instance STAR elements in DNA constructs elevates the induced number of colonies and also the protein expression levels in these colonies. Here, we describe a method to systematically identify genomic DNA elements that are able to induce many stably transfected mammalian cell lines. We isolated genomic DNA fragments upstream from the human Rb1 and p73 gene loci and cloned them around an expression cassette that contains a very stringent selection marker. Due to the stringency of the selection marker, hardly any colony survives without flanking DNA elements. We tested fourteen ~3500 bp DNA stretches from the Rb1 and p73 loci. Only two ~3500 bp long DNA fragments, called Rb1E and Rb1F, induced many colonies in the context of the stringent selection system and these colonies displayed high protein expression levels. Functional analysis showed that the Rb1 DNA fragments contained no enhancer, promoter, or STAR activity. Our data show the potential of a methodology to identify novel gene expression augmenting DNA elements in an unbiased manner

Application of Biomarkers in Cancer Risk Management: Evaluation from Stochastic Clonal Evolutionary and Dynamic System Optimization Points of View

Aside from primary prevention, early detection remains the most effective way to decrease mortality associated with the majority of solid cancers. Previous cancer screening models are largely based on classification of at-risk populations into three conceptually defined groups (normal, cancer without symptoms, and cancer with symptoms). Unfortunately, this approach has achieved limited successes in reducing cancer mortality. With advances in molecular biology and genomic technologies, many candidate somatic genetic and epigenetic “biomarkers” have been identified as potential predictors of cancer risk. However, none have yet been validated as robust predictors of progression to cancer or shown to reduce cancer mortality. In this Perspective, we first define the necessary and sufficient conditions for precise prediction of future cancer development and early cancer detection within a simple physical model framework. We then evaluate cancer risk prediction and early detection from a dynamic clonal evolution point of view, examining the implications of dynamic clonal evolution of biomarkers and the application of clonal evolution for cancer risk management in clinical practice. Finally, we propose a framework to guide future collaborative research between mathematical modelers and biomarker researchers to design studies to investigate and model dynamic clonal evolution. This approach will allow optimization of available resources for cancer control and intervention timing based on molecular biomarkers in predicting cancer among various risk subsets that dynamically evolve over time

Search for Gravitational Waves from Primordial Black Hole Binary Coalescences in the Galactic Halo

We use data from the second science run of the LIGO gravitational-wave detectors to search for the gravitational waves from primordial black hole (PBH) binary coalescence with component masses in the range 0.2--$1.0 M_\odot$. The analysis requires a signal to be found in the data from both LIGO observatories, according to a set of coincidence criteria. No inspiral signals were found. Assuming a spherical halo with core radius 5 kpc extending to 50 kpc containing non-spinning black holes with masses in the range 0.2--$1.0 M_\odot$, we place an observational upper limit on the rate of PBH coalescence of 63 per year per Milky Way halo (MWH) with 90% confidence.Comment: 7 pages, 4 figures, to be submitted to Phys. Rev.

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente