An Entropy-based gene selection method for cancer classification using microarray data

BACKGROUND: Accurate diagnosis of cancer subtypes remains a challenging problem. Building classifiers based on gene expression data is a promising approach; yet the selection of non-redundant but relevant genes is difficult. The selected gene set should be small enough to allow diagnosis even in regular clinical laboratories and ideally identify genes involved in cancer-specific regulatory pathways. Here an entropy-based method is proposed that selects genes related to the different cancer classes while at the same time reducing the redundancy among the genes. RESULTS: The present study identifies a subset of features by maximizing the relevance and minimizing the redundancy of the selected genes. A merit called normalized mutual information is employed to measure the relevance and the redundancy of the genes. In order to find a more representative subset of features, an iterative procedure is adopted that incorporates an initial clustering followed by data partitioning and the application of the algorithm to each of the partitions. A leave-one-out approach then selects the most commonly selected genes across all the different runs and the gene selection algorithm is applied again to pare down the list of selected genes until a minimal subset is obtained that gives a satisfactory accuracy of classification. The algorithm was applied to three different data sets and the results obtained were compared to work done by others using the same data sets CONCLUSION: This study presents an entropy-based iterative algorithm for selecting genes from microarray data that are able to classify various cancer sub-types with high accuracy. In addition, the feature set obtained is very compact, that is, the redundancy between genes is reduced to a large extent. This implies that classifiers can be built with a smaller subset of genes

Cross-borehole delineation of a conductive ore deposit in a resistive host-experimental design

Journal ArticleThe finite-difference time-domain method is used for high-resolution full-wave analysis of cross-borehole electromagnetic surveys of buried nickel sulfide deposits. The method is validated against analytical methods for simple cases, but is shown to be a valuable tool for analysis of complicated geological structures such as faulted or layered regions. The magnetic fields generated by a wire loop in a borehole near a nickel sulfide deposit are presented for several cases. The full-wave solution is obtained up to 200 MHz, where quasi-static methods would have failed. The dielectric response is included in the solution, and the diffractive nature of the field is observed. The sensitivity of each receiver in a vertical line in the cross borehole is presented and analyzed to provide an optimal weighting for receivers that can be applied to an experimental study

Identification of Hepta- and Octo-Uridine stretches as sole signals for programmed +1 and −1 ribosomal frameshifting during translation of SARS-CoV ORF 3a variants

Programmed frameshifting is one of the translational recoding mechanisms that read the genetic code in alternative ways. This process is generally programmed by signals at defined locations in a specific mRNA. In this study, we report the identification of hepta- and octo-uridine stretches as sole signals for programmed +1 and −1 ribosomal frameshifting during translation of severe acute respiratory syndrome coronavirus (SARS-CoV) ORF 3a variants. SARS-CoV ORF 3a encodes a minor structural protein of 274 amino acids. Over the course of cloning and expression of the gene, a mixed population of clones with six, seven, eight and nine T stretches located 14 nt downstream of the initiation codon was found. In vitro and in vivo expression of clones with six, seven and eight Ts, respectively, showed the detection of the full-length 3a protein. Mutagenesis studies led to the identification of the hepta- and octo-uridine stretches as slippery sequences for efficient frameshifting. Interestingly, no stimulatory elements were found in the sequences upstream or downstream of the slippage site. When the hepta- and octo-uridine stretches were used to replace the original slippery sequence of the SARS-CoV ORF 1a and 1b, efficient frameshift events were observed. Furthermore, the efficiencies of frameshifting mediated by the hepta- and octo-uridine stretches were not affected by mutations introduced into a downstream stem–loop structure that totally abolish the frameshift event mediated by the original slippery sequence of ORF 1a and 1b. Taken together, this study identifies the hepta- and octo-uridine stretches that function as sole elements for efficient +1 and −1 ribosomal frameshift events

Mucosal Immunization Induces a Higher Level of Lasting Neutralizing Antibody Response in Mice by a Replication-Competent Smallpox Vaccine: Vaccinia Tiantan Strain

The possible bioterrorism threat using the variola virus, the causative agent of smallpox, has promoted us to further investigate the immunogenicity profiles of existing vaccines. Here, we study for the first time the immunogenicity profile of a replication-competent smallpox vaccine (vaccinia Tiantan, VTT strain) for inducing neutralizing antibodies (Nabs) through mucosal vaccination, which is noninvasive and has a critical implication for massive vaccination programs. Four different routes of vaccination were tested in parallel including intramuscular (i.m.), intranasal (i.n.), oral (i.o.), and subcutaneous (s.c.) inoculations in mice. We found that one time vaccination with an optimal dose of VTT was able to induce anti-VTT Nabs via each of the four routes. Higher levels of antiviral Nabs, however, were induced via the i.n. and i.o. inoculations when compared with the i.m. and s.c. routes. Moreover, the i.n. and i.o. vaccinations also induced higher sustained levels of Nabs overtime, which conferred better protections against homologous or alternating mucosal routes of viral challenges six months post vaccination. The VTT-induced immunity via all four routes, however, was partially effective against the intramuscular viral challenge. Our data have implications for understanding the potential application of mucosal smallpox vaccination and for developing VTT-based vaccines to overcome preexisting antivaccinia immunity

Learning with Logical Constraints but without Shortcut Satisfaction

Recent studies in neuro-symbolic learning have explored the integration of logical knowledge into deep learning via encoding logical constraints as an additional loss function. However, existing approaches tend to vacuously satisfy logical constraints through shortcuts, failing to fully exploit the knowledge. In this paper, we present a new framework for learning with logical constraints. Specifically, we address the shortcut satisfaction issue by introducing dual variables for logical connectives, encoding how the constraint is satisfied. We further propose a variational framework where the encoded logical constraint is expressed as a distributional loss that is compatible with the model's original training loss. The theoretical analysis shows that the proposed approach bears salient properties, and the experimental evaluations demonstrate its superior performance in both model generalizability and constraint satisfaction.Comment: Published as a conference paper at ICLR 2023, and code is available at https://github.com/SoftWiser-group/NeSy-without-Shortcut

Fully Band Resolved Scattering Rate in MgB2 Revealed by Nonlinear Hall Effect and Magnetoresistance Measurements

We have measured the normal state temperature dependence of the Hall effect and magnetoresistance in epitaxial MgB2 thin films with variable disorders characterized by the residual resistance ratio RRR ranging from 4.0 to 33.3. A strong nonlinearity of the Hall effect and magnetoresistance have been found in clean samples, and they decrease gradually with the increase of disorders or temperature. By fitting the data to the theoretical model based on the Boltzmann equation and ab initio calculations for a four-band system, for the first time, we derived the scattering rates of these four bands at different temperatures and magnitude of disorders. Our method provides a unique way to derive these important parameters in multiband systems.Comment: 4 pages, 4 figure

Numerical Simulation of the Solid Particle Sedimentation and Bed Formation Behaviors Using a Hybrid Method

In the safety analysis of sodium-cooled fast reactors, numerical simulations of various thermal-hydraulic phenomena with multicomponent and multiphase flows in core disruptive accidents (CDAs) are regarded as particularly difficult. In the material relocation phase of CDAs, core debris settle down on a core support structure and/or an in-vessel retention device and form a debris bed. The bed’s shape is crucial for the subsequent relocation of the molten core and heat removal capability as well as re-criticality. In this study, a hybrid numerical simulation method, coupling the multi-fluid model of the three-dimensional fast reactor safety analysis code SIMMER-IV with the discrete element method (DEM), was applied to analyze the sedimentation and bed formation behaviors of core debris. Three-dimensional simulations were performed and compared with results obtained in a series of particle sedimentation experiments. The present simulation predicts the sedimentation behavior of mixed particles with different properties as well as homogeneous particles. The simulation results on bed shapes and particle distribution in the bed agree well with experimental measurements. They demonstrate the practicality of the present hybrid method to solid particle sedimentation and bed formation behaviors of mixed as well as homogeneous particles