Bayesian Approximate Kernel Regression with Variable Selection

Nonlinear kernel regression models are often used in statistics and machine learning because they are more accurate than linear models. Variable selection for kernel regression models is a challenge partly because, unlike the linear regression setting, there is no clear concept of an effect size for regression coefficients. In this paper, we propose a novel framework that provides an effect size analog of each explanatory variable for Bayesian kernel regression models when the kernel is shift-invariant --- for example, the Gaussian kernel. We use function analytic properties of shift-invariant reproducing kernel Hilbert spaces (RKHS) to define a linear vector space that: (i) captures nonlinear structure, and (ii) can be projected onto the original explanatory variables. The projection onto the original explanatory variables serves as an analog of effect sizes. The specific function analytic property we use is that shift-invariant kernel functions can be approximated via random Fourier bases. Based on the random Fourier expansion we propose a computationally efficient class of Bayesian approximate kernel regression (BAKR) models for both nonlinear regression and binary classification for which one can compute an analog of effect sizes. We illustrate the utility of BAKR by examining two important problems in statistical genetics: genomic selection (i.e. phenotypic prediction) and association mapping (i.e. inference of significant variants or loci). State-of-the-art methods for genomic selection and association mapping are based on kernel regression and linear models, respectively. BAKR is the first method that is competitive in both settings.Comment: 22 pages, 3 figures, 3 tables; theory added; new simulations presented; references adde

Uncovering Scaling Laws to Infer Multi-drug Response of Resistant Microbes and Cancer Cells

Drug resistance in bacterial infections and cancers constitutes a major threat to human health. Treatments often include several interacting drugs, but even potent therapies can become ineffective in resistant mutants. Here we simplify the picture of drug resistance by identifying scaling laws that unify the multi-drug responses of drug sensitive and drug resistant cells. Based on these scaling relationships, we are able to infer the two-drug response of resistant mutants in previously unsampled regions of dosage space in clinically relevant microbes such as E. coli, E. faecalis, S. aureus and S. cerevisiae, as well as in human non-small cell lung cancer, melanoma, and breast cancer stem cells. Importantly, we find that scaling relations also apply across evolutionarily close strains. Finally, scaling allows one to rapidly identify new drug combinations and predict potent dosage regimes for targeting resistant mutants without any prior mechanistic knowledge of the specific resistance mechanism.Molecular and Cellular Biolog

Discrete Multi-Material Selective Laser Sintering (M2 SLS): Development for an Application in Complex Sand Casting Core Arrays

Conventional sand casting processes often take many weeks or months to produce the tooling required for a casting, in particular the fabrication of sand core arrays for hollow features in a casting. SLS is already being applied to produce complex sand core geometries and reduce production times, but a new development of discretely laying down two different materials and removing one after sintering will allow even more complex geometries and drastically decrease the production times of sand cores. Two of the most significant problems in the current use of SLS for sand cores are the mechanical removal of unsintered powder and damage during part breakout. The second discrete material serves as a support medium through the build and fabrication of the sand core and is removed before casting; the sacrificial second material increases green strength and eliminates time consuming post-processing. The development and plan for implementation of the discrete M2 SLS process is presented.Mechanical Engineerin

Nanostructured gene and drug delivery systems based on molecular self-assembly

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 2007.Includes bibliographical references.Molecular self-assembly describes the assembly of molecular components into complex, supramolecular structures governed by weak, non-covalent interactions. In recent years, molecular self-assembly has been used extensively as a means of creating materials and devices with well-controlled, nanometer-scale architectural features. In this thesis, molecular self-assembly is used as a tool for the fabrication of both gene and drug delivery systems which, by virtue of their well-controlled architectural features, possess advantageous properties relative to traditional materials used in these applications. The first part of this thesis describes the solution-phase self-assembly of a new family of linear-dendritic "hybrid" polymers with plasmid DNA for applications in gene therapy. It begins with an overview of the design of next-generation, non-viral gene delivery systems and continues through the synthesis and validation of hybrid polymer systems, which possess modular functionalities for DNA binding, endosomal escape, steric stabilization, and tissue targeting. This part of the thesis concludes with applications of these systems to two areas of clinical interest: DNA vaccination and tumor targeted gene therapy.(cont.) The second part of this thesis describes the directed self-assembly of polymeric thin films which are capable of degrading in response to either passive or active stimuli to release their contents. It begins with a description of passive release thin films which degrade by basic hydrolysis to release precise quantities of model drug compounds. These systems can be engineered to release their contents on time scales ranging from hours to weeks and can also be designed to release multiple drugs either in series or in parallel. Later, field-activated thin films which release their contents in response to an external, electrical stimulus are described and characterized in detail. Together, these approaches combine rapid and inexpensive processing, the ability to conformally coat any surface regardless of composition, size, or shape, and the ability to release multi-drug or multi-dose schedules, and as such they may find applications in a range of areas.by Kris Cameron Wood.Ph.D

Electric monopole transitions from low energy excitations in nuclei

Electric monopole (E0) properties are studied across the entire nuclear mass surface. Besides an introductory discussion of various model results (shell model, geometric vibrational and rotational models, algebraic models), we point out that many of the largest E0 transition strengths, $\rho^2$(E0), are associated with shape mixing. We discuss in detail the manifestation of E0 transitions and present extensive data for~: single-closed shell nuclei, vibrational nuclei, well-deformed nuclei, nuclei that exhibit sudden ground-state changes, and nuclei that exhibit shape coexistence and intruder states. We also give attention to light nuclei, odd-A nuclei, and illustrate a suggested relation between $\rho^2$(E0) and isotopic shifts

Particle-hole excitations in the interacting boson model; 4, the U(5)-SU(3) coupling

In the extended interacting boson model (EIBM) both particle- and hole-like bosons are incorporated to encompass multi-particle-multi-hole excitations at and near to closed shells.We apply the group theoretical concepts of the EIBM to the particular case of two coexisting systems in the same nucleus exhibiting a U(5) (for the regular configurations) and an SU(3) symmetry (for the intruder configurations).Besides the description of ``global'' symmetry aspects in terms of I-spin , also the very specific local mixing effects characteristic for the U(5)-SU(3) symmetry coupling are studied.The model is applied to the Po isotopes and a comparison with a morerealistic calculation is made

A p300/GATA6 axis determines differentiation and Wnt dependency in pancreatic cancer models

Wnt signaling regulates the balance between stemness and differentiation in multiple tissues and in cancer. RNF43-mutant pancreatic cancers are dependent on Wnt production, and pharmacologic blockade of the pathway, e.g., by PORCN inhibitors, leads to tumor differentiation. However, primary resistance to these inhibitors has been observed. To elucidate potential mechanisms, we performed in vivo CRISPR screens in PORCN inhibitor–sensitive RNF43-mutant pancreatic cancer xenografts. As expected, genes in the Wnt pathway whose loss conferred drug resistance were identified, including APC, AXIN1, and CTNNBIP1. Unexpectedly, the screen also identified the histone acetyltransferase EP300 (p300), but not its paralog, CREBBP (CBP). We found that EP300 is silenced due to genetic alterations in all the existing RNF43-mutant pancreatic cancer cell lines that are resistant to PORCN inhibitors. Mechanistically, loss of EP300 directly downregulated GATA6 expression, thereby silencing the GATA6-regulated differentiation program and leading to a phenotypic transition from the classical subtype to the dedifferentiated basal-like/squamous subtype of pancreatic cancer. EP300 mutation and loss of GATA6 function bypassed the antidifferentiation activity of Wnt signaling, rendering these cancer cells resistant to Wnt inhibition

A Comparison of Creativity and Innovation Metrics and Sample Validation Through in-­class Design Projects

This paper introduces a new perspective/direction on assessing and encouraging creativity in concept design for application in engineering design education and industry. This research presents several methods used to assess the creativity of similar student designs using metrics and judges to determine which product is considered the most creative. Two methods are proposed for creativity concept evaluation during early design, namely the Comparative Creativity Assessment (CCA) and the Multi-Point Creativity Assessment (MPCA) methods. A critical survey is provided along with a comparison of prominent creativity assessment methods for personalities, products, and the design process. These comparisons culminate in the motivation for new methodologies in creative product evaluation to address certain shortcomings in current methods. The paper details the creation of the two creativity assessment methods followed by an application of the CCA and MPCA to two case studies drawn from engineering design classes.Keywords: engineering design, creativity assessment, innovation, concept desig

Feasibility and clinical impact of sharing patient-reported symptom toxicities and performance status with clinical investigators during a phase 2 cancer treatment trial

Clinicians can miss up to half of patients’ symptomatic toxicities in cancer clinical trials and routine practice. Although patient-reported outcome questionnaires have been developed to capture this information, it is unclear whether clinicians will make use of patient-reported outcomes to inform their own toxicity documentation, or to prompt symptom management activities