A Family of Maximum Margin Criterion for Adaptive Learning

In recent years, pattern analysis plays an important role in data mining and recognition, and many variants have been proposed to handle complicated scenarios. In the literature, it has been quite familiar with high dimensionality of data samples, but either such characteristics or large data have become usual sense in real-world applications. In this work, an improved maximum margin criterion (MMC) method is introduced firstly. With the new definition of MMC, several variants of MMC, including random MMC, layered MMC, 2D^2 MMC, are designed to make adaptive learning applicable. Particularly, the MMC network is developed to learn deep features of images in light of simple deep networks. Experimental results on a diversity of data sets demonstrate the discriminant ability of proposed MMC methods are compenent to be adopted in complicated application scenarios.Comment: 14 page

Host genetics and viral load in primary HIV-1 infection: clear evidence for gene by sex interactions

© 2014, The Author(s).Research in the past two decades has generated unequivocal evidence that host genetic variations substantially account for the heterogeneous outcomes following human immunodeficiency virus type 1 (HIV-1) infection. In particular, genes encoding human leukocyte antigens (HLA) have various alleles, haplotypes, or specific motifs that can dictate the set-point (a relatively steady state) of plasma viral load (VL), although rapid viral evolution driven by innate and acquired immune responses can obscure the long-term relationships between HLA genotypes and HIV-1-related outcomes. In our analyses of VL data from 521 recent HIV-1 seroconverters enrolled from eastern and southern Africa, HLA-A*03:01 was strongly and persistently associated with low VL in women (frequency = 11.3 %, P  0.50). In a reduced multivariable model, age, sex, geography (clinical sites), previously identified HLA factors (HLA-B*18, B*45, B*53, and B*57), and the interaction term for female sex and HLA-A*03:01 collectively explained 17.0 % of the overall variance in geometric mean VL over a 3-year follow-up period (P < 0.0001). Multiple sensitivity analyses of longitudinal and cross-sectional VL data yielded consistent results. These findings can serve as a proof of principle that the gap of “missing heritability” in quantitative genetics can be partially bridged by a systematic evaluation of sex-specific associations

Closing the sea surface mixed layer temperature budget from in situ observations alone: Operation Advection during BoBBLE

Sea surface temperature (SST) is a fundamental driver of tropical weather systems such as monsoon rainfall and tropical cyclones. However, understanding of the factors that control SST variability is lacking, especially during the monsoons when in situ observations are sparse. Here we use a ground-breaking observational approach to determine the controls on the SST variability in the southern Bay of Bengal. We achieve this through the first full closure of the ocean mixed layer energy budget derived entirely from in situ observations during the Bay of Bengal Boundary Layer Experiment (BoBBLE). Locally measured horizontal advection and entrainment contribute more significantly than expected to SST evolution and thus oceanic variability during the observation period. These processes are poorly resolved by state-of-the-art climate models, which may contribute to poor representation of monsoon rainfall variability. The novel techniques presented here provide a blueprint for future observational experiments to quantify the mixed layer heat budget on longer time scales and to evaluate these processes in models

Growth suppressive effect of pegylated arginase in malignant pleural mesothelioma xenografts

BACKGROUND: Malignant pleural mesothelioma (MPM) is a difficult-to-treat global disease. Pegylated arginase (BCT-100) has recently shown anti-tumor effects in hepatocellular carcinoma, acute myeloid leukemia and melanoma. This study aims to investigate the effects of PEG-BCT-100 in MPM. METHODS: A panel of 5 mesothelioma cell lines (H28, 211H, H226, H2052 and H2452) was used to study the in vitro effects of BCT-100 by crystal violet staining. The in vivo effects of BCT-100 were studied using 211H and H226 nude mice xenografts. Protein expression (argininosuccinate synthetase, ornithine transcarbamylase, cleaved PARP, cleaved caspase 3, cyclins (A2, D3, E1 and H), CDK4 and Ki67) and arginine concentration were evaluated by Western blot and ELISA respectively. Cellular localization of BCT-100 was detected by immunohistochemistry and immunoflorescence. TUNEL assay was used to identify cellular apoptotic events. RESULTS: Argininosuccinate synthetase was expressed in H28, H226, and H2452 cells as well as 211H and H266 xenografts. Ornithine transcarbamylase was undetectable in all cell lines and xenograft models. BCT-100 reduced in vitro cell viability (IC50 values at 13-24 mU/ml, 72 h) across different cell lines and suppressed tumor growth in both 211H and H226 xenograft models. BCT-100 (60 mg/kg) significantly suppressed tumor growth (p < 0.01) with prolonged median survival (p < 0.01) in both xenograft models. Combining BCT-100 with pemetrexed or cisplatin conferred no additional benefits over single agents. Serum and intratumoral arginine levels were effectively decreased by BCT-100, associated with cytosolic accumulation of BCT-100 within tumor cells. Apoptosis (PARP cleavage in 211H xenografts; Bcl-2 downregulation, and cleavage of PARP and caspase 3 in H226 xenografts; positive TUNEL staining in both) and G1 arrest (downregulation of cyclin A2, D3, E1 and CDK4 in 211H xenografts; suppression of cyclin A2, E1, H and CDK4 in H226 xenografts) were evident with BCT-100 treatment. Furthermore, proliferative factor Ki67 was downregulated in BCT-100 treatments arms. CONCLUSIONS: BCT-100 suppressed tumor growth with prolonged median survival partially mediated by intratumoral arginine depletion resulting in apoptosis and G1 arrest in mesothelioma xenograft models. The findings provide scientific evidence to support further clinical development of BCT-100 in treatment of MPM.published_or_final_versio

Manifold Elastic Net: A Unified Framework for Sparse Dimension Reduction

It is difficult to find the optimal sparse solution of a manifold learning based dimensionality reduction algorithm. The lasso or the elastic net penalized manifold learning based dimensionality reduction is not directly a lasso penalized least square problem and thus the least angle regression (LARS) (Efron et al. \cite{LARS}), one of the most popular algorithms in sparse learning, cannot be applied. Therefore, most current approaches take indirect ways or have strict settings, which can be inconvenient for applications. In this paper, we proposed the manifold elastic net or MEN for short. MEN incorporates the merits of both the manifold learning based dimensionality reduction and the sparse learning based dimensionality reduction. By using a series of equivalent transformations, we show MEN is equivalent to the lasso penalized least square problem and thus LARS is adopted to obtain the optimal sparse solution of MEN. In particular, MEN has the following advantages for subsequent classification: 1) the local geometry of samples is well preserved for low dimensional data representation, 2) both the margin maximization and the classification error minimization are considered for sparse projection calculation, 3) the projection matrix of MEN improves the parsimony in computation, 4) the elastic net penalty reduces the over-fitting problem, and 5) the projection matrix of MEN can be interpreted psychologically and physiologically. Experimental evidence on face recognition over various popular datasets suggests that MEN is superior to top level dimensionality reduction algorithms.Comment: 33 pages, 12 figure

Using Neural Networks for Relation Extraction from Biomedical Literature

Using different sources of information to support automated extracting of relations between biomedical concepts contributes to the development of our understanding of biological systems. The primary comprehensive source of these relations is biomedical literature. Several relation extraction approaches have been proposed to identify relations between concepts in biomedical literature, namely, using neural networks algorithms. The use of multichannel architectures composed of multiple data representations, as in deep neural networks, is leading to state-of-the-art results. The right combination of data representations can eventually lead us to even higher evaluation scores in relation extraction tasks. Thus, biomedical ontologies play a fundamental role by providing semantic and ancestry information about an entity. The incorporation of biomedical ontologies has already been proved to enhance previous state-of-the-art results.Comment: Artificial Neural Networks book (Springer) - Chapter 1

Quantitative principles of cis-translational control by general mRNA sequence features in eukaryotes.

BackgroundGeneral translational cis-elements are present in the mRNAs of all genes and affect the recruitment, assembly, and progress of preinitiation complexes and the ribosome under many physiological states. These elements include mRNA folding, upstream open reading frames, specific nucleotides flanking the initiating AUG codon, protein coding sequence length, and codon usage. The quantitative contributions of these sequence features and how and why they coordinate to control translation rates are not well understood.ResultsHere, we show that these sequence features specify 42-81% of the variance in translation rates in Saccharomyces cerevisiae, Schizosaccharomyces pombe, Arabidopsis thaliana, Mus musculus, and Homo sapiens. We establish that control by RNA secondary structure is chiefly mediated by highly folded 25-60 nucleotide segments within mRNA 5' regions, that changes in tri-nucleotide frequencies between highly and poorly translated 5' regions are correlated between all species, and that control by distinct biochemical processes is extensively correlated as is regulation by a single process acting in different parts of the same mRNA.ConclusionsOur work shows that general features control a much larger fraction of the variance in translation rates than previously realized. We provide a more detailed and accurate understanding of the aspects of RNA structure that directs translation in diverse eukaryotes. In addition, we note that the strongly correlated regulation between and within cis-control features will cause more even densities of translational complexes along each mRNA and therefore more efficient use of the translation machinery by the cell

The Minimal Solution to the mu/B_mu Problem in Gauge Mediation

We provide a minimal solution to the mu/B_mu problem in the gauge mediated supersymmetry breaking by introducing a Standard Model singlet filed S with a mass around the messenger scale which couples to the Higgs and messenger fields. This singlet is nearly supersymmetric and acquires a relatively small Vacuum Expectation Value (VEV) from its radiatively generated tadpole term. Consequently, both mu and B_mu parameters receive the tree-level and one-loop contributions, which are comparable due to the small S VEV. Because there exists a proper cancellation in such two kinds of contributions to B_mu, we can have a viable Higgs sector for electroweak symmetry breaking.Comment: 15 pages, 2 figures, version published on JHE

Submillimeter Studies of Prestellar Cores and Protostars: Probing the Initial Conditions for Protostellar Collapse

Improving our understanding of the initial conditions and earliest stages of protostellar collapse is crucial to gain insight into the origin of stellar masses, multiple systems, and protoplanetary disks. Observationally, there are two complementary approaches to this problem: (1) studying the structure and kinematics of prestellar cores observed prior to protostar formation, and (2) studying the structure of young (e.g. Class 0) accreting protostars observed soon after point mass formation. We discuss recent advances made in this area thanks to (sub)millimeter mapping observations with large single-dish telescopes and interferometers. In particular, we argue that the beginning of protostellar collapse is much more violent in cluster-forming clouds than in regions of distributed star formation. Major breakthroughs are expected in this field from future large submillimeter instruments such as Herschel and ALMA.Comment: 12 pages, 9 figures, to appear in the proceedings of the conference "Chemistry as a Diagnostic of Star Formation" (C.L. Curry & M. Fich eds.

Resolving the far-IR line deficit : photoelectric heating and far-IR line cooling in NGC 1097 and NGC 4559

The physical state of interstellar gas and dust is dependent on the processes which heat and cool this medium. To probe heating and cooling of the interstellar medium over a large range of infrared surface brightness, on sub-kiloparsec scales, we employ line maps of [C II] 158 mu m, [O I] 63 mu m, and [N II] 122 mu m in NGC 1097 and NGC 4559, obtained with the Photodetector Array Camera & Spectrometer on board Herschel. We matched new observations to existing Spitzer Infrared Spectrograph data that trace the total emission of polycyclic aromatic hydrocarbons (PAHs). We confirm at small scales in these galaxies that the canonical measure of photoelectric heating efficiency, ([C II] + [O I])/TIR, decreases as the far-infrared (far-IR) color, nu f(nu)(70 mu m) nu f(nu)(100 mu m), increases. In contrast, the ratio of far-IR cooling to total PAH emission, ([C II] + [O I])/PAH, is a near constant similar to 6% over a wide range of far-IR color, 0.5 , derived from models of the IR spectral energy distribution. Emission from regions that exhibit a line deficit is characterized by an intense radiation field, indicating that small grains are susceptible to ionization effects. We note that there is a shift in the 7.7/11.3 mu m PAH ratio in regions that exhibit a deficit in ([C II] + [O I])/PAH, suggesting that small grains are ionized in these environments