A probabilistic pathway score (PROPS) for classification with applications to inflammatory bowel disease.

Summary: Gene-based supervised machine learning classification models have been widely used to differentiate disease states, predict disease progression and determine effective treatment options. However, many of these classifiers are sensitive to noise and frequently do not replicate in external validation sets. For complex, heterogeneous diseases, these classifiers are further limited by being unable to capture varying combinations of genes that lead to the same phenotype.

Practical considerations when analyzing discrete survival times using the grouped relative risk model.

The grouped relative risk model (GRRM) is a popular semi-parametric model for analyzing discrete survival time data. The maximum likelihood estimators (MLEs) of the regression coefficients in this model are often asymptotically efficient relative to those based on a more restrictive, parametric model. However, in settings with a small number of sampling units, the usual properties of the MLEs are not assured.

Biological and functional relevance of CASP predictions.

Our goal is to answer the question: compared with experimental structures, how useful are predicted models for functional annotation? We assessed the functional utility of predicted models by comparing the performances of a suite of methods for functional characterization on the predictions and the experimental structures. We identified 28 sites in 25 protein targets to perform functional assessment. These 28 sites included nine sites with known ligand binding (holo-sites), nine sites that are expected or suggested by experimental authors for small molecule binding (apo-sites), and Ten sites containing important motifs, loops, or key residues with important disease-associated mutations.

Shallow Representation Learning via Kernel PCA Improves QSAR Modelability.

Linear models offer a robust, flexible, and computationally efficient set of tools for modeling quantitative structure-activity relationships (QSARs) but have been eclipsed in performance by nonlinear methods. Support vector machines (SVMs) and neural networks are currently among the most popular and accurate QSAR methods because they learn new representations of the data that greatly improve modelability. In this work, we use shallow representation learning to improve the accuracy of L1 regularized logistic regression (LASSO) and meet the performance of Tanimoto SVM.

Glucose consumption in carbohydrate mixtures by phosphotransferase-system mutants of Escherichia coli.

Escherichia coli lacking the glucose phosphotransferase system (PTS), mannose PTS and glucokinase are supposedly unable to grow on glucose as the sole carbon source (Curtis SJ, Epstein W. J Bacteriol 1975;122:1189-1199). We report that W ptsG manZ glk (ALS1406) grows slowly on glucose in media containing glucose with a second carbon source: ALS1406 metabolizes glucose after that other carbon source, including arabinose, fructose, glycerol, succinate or xylose, is exhausted.

Working toward precision medicine: Predicting phenotypes from exomes in the Critical Assessment of Genome Interpretation (CAGI) challenges.

Precision medicine aims to predict a patient's disease risk and best therapeutic options by using that individual's genetic sequencing data. The Critical Assessment of Genome Interpretation (CAGI) is a community experiment consisting of genotype-phenotype prediction challenges; participants build models, undergo assessment, and share key findings. For CAGI 4, three challenges involved using exome-sequencing data: Crohn's disease, bipolar disorder, and warfarin dosing.

The ex-pat effect: presence of recent Western immigrants is associated with changes in age at first birth and birth rate in a Maya population from rural Guatemala.

Background: Economic transitions expose indigenous populations to a variety of ecological and cultural challenges, especially regarding diet and stress. These kinds of challenges are predicted by evolutionary ecological theory to have fitness consequences (differential reproduction) and, indeed, are often associated with changes in fertility dynamics. It is currently unclear whether international immigration might impact the nature of such an economic transition or its consequences for fertility.

Appropriate Use Criteria for Hyaluronic Acid in the Treatment of Knee Osteoarthritis in the United States.

Objective: A workgroup of clinical experts has developed an Appropriate Use Criteria (AUC) for the use of hyaluronic acid (HA) in the treatment of osteoarthritis (OA) of the knee. The increasingly broad and varied use of HA injections, lack of published clinical guidance, and limited coverage for their use has created the imperative to establish appropriateness criteria.

Methods: The experts of this workgroup represent rheumatology, orthopedic surgery, physiatry, sports medicine, and nursing clinicians with substantive knowledge of intra-articular HA therapy.

3D deep convolutional neural networks for amino acid environment similarity analysis.

Background: Central to protein biology is the understanding of how structural elements give rise to observed function. The surfeit of protein structural data enables development of computational methods to systematically derive rules governing structural-functional relationships. However, performance of these methods depends critically on the choice of protein structural representation.

Pseudoknot Formation Seeds the Twister Ribozyme Cleavage Reaction Coordinate.

The twister RNA is a recently discovered nucleolytic ribozyme that is present in both bacteria and eukarya. While its biological role remains unclear, crystal structure analyses and biochemical approaches have revealed critical features of its catalytic mechanism. Here, we set out to explore dynamic aspects of twister RNA folding along the cleavage reaction coordinate.

Child mortality, hypothalamic-pituitary-adrenal axis activity and cellular aging in mothers.

Unlabelled: Psychological challenges, including traumatic events, have been hypothesized to increase the age-related pace of biological aging. Here we test the hypothesis that psychological challenges can affect the pace of telomere attrition, a marker of cellular aging, using data from an ongoing longitudinal-cohort study of Kaqchikel Mayan women living in a population with a high frequency of child mortality, a traumatic life event. Specifically, we evaluate the associations between child mortality, maternal telomere length and the mothers' hypothalamic-pituitary-adrenal axis (HPAA), or stress axis, activity.

Exploiting the unusual effects of fluorine in methodology.

Fluorination of organic molecules significantly impacts the basic physicochemical properties of small and large biologically active molecules, agrichemicals, and materials. Thus, the development of synthetic reactions to access these substructures is important for many applied fields of chemistry. However, these fluorine-induced perturbations of chemical properties can inhibit standard chemical transformations, which provides unique challenges for synthetic organic chemists.

Decaying relevance of clinical data towards future decisions in data-driven inpatient clinical order sets.

Objective: Determine how varying longitudinal historical training data can impact prediction of future clinical decisions. Estimate the "decay rate" of clinical data source relevance.

Materials And Methods: We trained a clinical order recommender system, analogous to Netflix or Amazon's "Customers who bought A also bought B.

Assessing the Impact of a Novel Smartphone Application Compared With Standard Follow-Up on Mobility of Patients With Knee Osteoarthritis Following Treatment With Hylan G-F 20: A Randomized Controlled Trial.

Background: Osteoarthritis (OA) is a leading cause of disability in the United States. Although no disease-modifying therapies exist, patients with knee OA who increase walking may reduce risk of functional limitations.

Objective: The objective of the study is to evaluate the impact of a mobile app (OA GO) plus wearable activity monitor/pedometer (Jawbone UP 24) used for 90 days on the mobility of patients with knee OA treated with hylan G-F 20.

Flexible Analog Search with Kernel PCA Embedded Molecule Vectors.

Studying analog series to find structural transformations that enhance the activity and ADME properties of lead compounds is an important part of drug development. Matched molecular pair (MMP) search is a powerful tool for analog analysis that imitates researchers' ability to select pairs of compounds that differ only by small well-defined transformations. Abstraction is a challenge for existing MMP search algorithms, which can result in the omission of relevant, inexact MMPs, and inclusion of irrelevant, contextually dissimilar MMPs.

Opportunities for developing therapies for rare genetic diseases: focus on gain-of-function and allostery.

Background: Advances in next generation sequencing technologies have revolutionized our ability to discover the causes of rare genetic diseases. However, developing treatments for these diseases remains challenging. In fact, when we systematically analyze the US FDA orphan drug list, we find that only 8% of rare diseases have an FDA-designated drug.

Pharmacogenomics-Based Point-of-Care Clinical Decision Support Significantly Alters Drug Prescribing.

Changes in behavior are necessary to apply genomic discoveries to practice. We prospectively studied medication changes made by providers representing eight different medicine specialty clinics whose patients had submitted to preemptive pharmacogenomic genotyping. An institutional clinical decision support (CDS) system provided pharmacogenomic results using traffic light alerts: green = genomically favorable, yellow = genomic caution, red = high risk.

Mirror self-face perception in individuals with schizophrenia: Feelings of strangeness associated with one's own image.

Self-face recognition is crucial for sense of identity and for maintaining a coherent sense of self. Most of our daily life experiences with the image of our own face happen when we look at ourselves in the mirror. However, to date, mirror self-perception in schizophrenia has received little attention despite evidence that face recognition deficits and self abnormalities have been described in schizophrenia.

Electronic tuning of self-healing fluorophores for live-cell and single-molecule imaging.

Bright, long-lasting organic fluorophores enable a broad range of imaging applications. "Self-healing" fluorophores, in which intra-molecularly linked protective agents quench photo-induced reactive species, exhibit both enhanced photostability and biological compatibility. However, the self-healing strategy has yet to achieve its predicted potential, particularly in the presence of ambient oxygen where live-cell imaging studies must often be performed.

Development of an automated assessment tool for MedWatch reports in the FDA adverse event reporting system.

Objective: As the US Food and Drug Administration (FDA) receives over a million adverse event reports associated with medication use every year, a system is needed to aid FDA safety evaluators in identifying reports most likely to demonstrate causal relationships to the suspect medications. We combined text mining with machine learning to construct and evaluate such a system to identify medication-related adverse event reports.

Methods: FDA safety evaluators assessed 326 reports for medication-related causality.