PenPC: A two-step approach to estimate the skeletons of high-dimensional directed acyclic graphs.

Estimation of the skeleton of a directed acyclic graph (DAG) is of great importance for understanding the underlying DAG and causal effects can be assessed from the skeleton when the DAG is not identifiable. We propose a novel method named PenPC to estimate the skeleton of a high-dimensional DAG by a two-step approach. We first estimate the nonzero entries of a concentration matrix using penalized regression, and then fix the difference between the concentration matrix and the skeleton by evaluating a set of conditional independence hypotheses. For high-dimensional problems where the number of vertices p is in polynomial or exponential scale of sample size n, we study the asymptotic property of PenPC on two types of graphs: traditional random graphs where all the vertices have the same expected number of neighbors, and scale-free graphs where a few vertices may have a large number of neighbors. As illustrated by extensive simulations and applications on gene expression data of cancer patients, PenPC has higher sensitivity and specificity than the state-of-the-art method, the PC-stable algorithm.

Large-area nanopatterning of self-assembled monolayers of alkanethiolates by interferometric lithography.

We demonstrate that interferometric lithography provides a fast, simple approach to the production of patterns in self-assembled monolayers (SAMs) with high resolution over square centimeter areas. As a proof of principle, two-beam interference patterns, formed using light from a frequency-doubled argon ion laser (244 nm), were used to pattern methyl-terminated SAMs on gold, facilitating the introduction of hydroxyl-terminated adsorbates and yielding patterns of surface free energy with a pitch of ca. 200 nm. The photopatterning of SAMs on Pd has been demonstrated for the first time, with interferometric exposure yielding patterns of surface free energy with similar features sizes to those obtained on gold. Gold nanostructures were formed by exposing SAMs to UV interference patterns and then immersing the samples in an ethanolic solution of mercaptoethylamine, which etched the metal substrate in exposed areas while unoxidized thiols acted as a resist and protected the metal from dissolution. Macroscopically extended gold nanowires were fabricated using single exposures and arrays of 66 nm gold dots at 180 nm centers were formed using orthogonal exposures in a fast, simple process. Exposure of oligo(ethylene glycol)-terminated SAMs to UV light caused photodegradation of the protein-resistant tail groups in a substrate-independent process. In contrast to many protein patterning methods, which utilize multiple steps to control surface binding, this single step process introduced aldehyde functional groups to the SAM surface at exposures as low as 0.3 J cm(-2), significantly less than the exposure required for oxidation of the thiol headgroup. Although interferometric methods rely upon a continuous gradient of exposure, it was possible to fabricate well-defined protein nanostructures by the introduction of aldehyde groups and removal of protein resistance in nanoscopic regions. Macroscopically extended, nanostructured assemblies of streptavidin were formed. Retention of functionality in the patterned materials was demonstrated by binding of biotinylated proteins.

A framework for revising preservice curriculum for nonphysician clinicians: The mozambique experience.

Mozambique, with approximately 0.4 physicians and 4.1 nurses per 10,000 people, has one of the lowest ratios of health care providers to population in the world. To rapidly scale up health care coverage, the Mozambique Ministry of Health has pushed for greater investment in training nonphysician clinicians, Tιcnicos de Medicina (TM). Based on identified gaps in TM clinical performance, the Ministry of Health requested technical assistance from the International Training and Education Center for Health (I-TECH) to revise the two-and-a-half-year preservice curriculum. A six-step process was used to revise the curriculum: (i) Conducting a task analysis, (ii) defining a new curriculum approach and selecting an integrated model of subject and competency-based education, (iii) revising and restructuring the 30-month course schedule to emphasize clinical skills, (iv) developing a detailed syllabus for each course, (v) developing content for each lesson, and (vi) evaluating implementation and integrating feedback for ongoing improvement. In May 2010, the Mozambique Minister of Health approved the revised curriculum, which is currently being implemented in 10 training institutions around the country. Key lessons learned: (i) Detailed assessment of training institutions' strengths and weaknesses should inform curriculum revision. (ii) Establishing a Technical Working Group with respected and motivated clinicians is key to promoting local buy-in and ownership. (iii) Providing ready-to-use didactic material helps to address some challenges commonly found in resource-limited settings. (iv) Comprehensive curriculum revision is an important first step toward improving the quality of training provided to health care providers in developing countries. Other aspects of implementation at training institutions and health care facilities must also be addressed to ensure that providers are adequately trained and equipped to provide quality health care services. This approach to curriculum revision and implementation teaches several key lessons, which may be applicable to preservice training programs in other less developed countries.

Impaired formation of beta-adrenergic receptor-nucleotide regulatory protein complexes in pseudohypoparathyroidism.

Decreased activity of the guanine nucleotide regulatory protein (N) of the adenylate cyclase system is present in cell membranes of some patients with pseudohypoparathyrodism (PHP-Ia) whereas others have normal activity of N (PHP-Ib). Low N activity in PHP-Ia results in a decrease in hormone (H)-stimulatable adenylate cyclase in various tissues, which might be due to decreased ability to form an agonist-specific high affinity complex composed of H, receptor (R), and N. To test this hypothesis, we compared beta-adrenergic agonist-specific binding properties in erythrocyte membranes from five patients with PHP-Ia (N = 45% of control), five patients with PHP-Ib (N = 97%), and five control subjects. Competition curves that were generated by increasing concentrations of the beta-agonist isoproterenol competing with [125I]pindolol were shallow (slope factors less than 1) and were computer fit to a two-state model with corresponding high and low affinity for the agonist. The agonist competition curves from the PHP-Ia patients were shifted significantly (P less than 0.02) to the right as a result of a significant (P less than 0.01) decrease in the percent of beta-adrenergic receptors in the high affinity state from 64 +/- 22% in PHP-Ib and 56 +/- 5% in controls to 10 +/- 8% in PHP-Ia. The agonist competition curves were computer fit to a "ternary complex" model for the two-step reaction: H + R + N in equilibrium HR + N in equilibrium HRN. The modeling was consistent with a 60% decrease in the functional concentration of N, and was in good agreement with the biochemically determined decrease in erythrocyte N protein activity. These in vitro findings in erythrocytes taken together with the recent observations that in vivo isoproterenol-stimulated adenylate cyclase activity is decreased in patients with PHP (Carlson, H. E., and A. S. Brickman, 1983, J. Clin. Endocrinol. Metab. 56:1323-1326) are consistent with the notion that N is a bifunctional protein interacting with both R and the adenylate cyclase. It may be that in patients with PHP-Ia a single molecular and genetic defect accounts for both decreased HRN formation and decreased adenylate cyclase activity, whereas in PHP-Ib the biochemical lesion(s) appear not to affect HRN complex formation.

Task-driven adaptive statistical compressive sensing of gaussian mixture models

A framework for adaptive and non-adaptive statistical compressive sensing is developed, where a statistical model replaces the standard sparsity model of classical compressive sensing. We propose within this framework optimal task-specific sensing protocols specifically and jointly designed for classification and reconstruction. A two-step adaptive sensing paradigm is developed, where online sensing is applied to detect the signal class in the first step, followed by a reconstruction step adapted to the detected class and the observed samples. The approach is based on information theory, here tailored for Gaussian mixture models (GMMs), where an information-theoretic objective relationship between the sensed signals and a representation of the specific task of interest is maximized. Experimental results using synthetic signals, Landsat satellite attributes, and natural images of different sizes and with different noise levels show the improvements achieved using the proposed framework when compared to more standard sensing protocols. The underlying formulation can be applied beyond GMMs, at the price of higher mathematical and computational complexity. © 1991-2012 IEEE.

Integrated pathway and epistasis analysis reveals interactive effect of genetic variants at TERF1 and AFAP1L2 loci on melanoma risk.

Genome-wide association studies (GWASs) have characterized 13 loci associated with melanoma, which only account for a small part of melanoma risk. To identify new genes with too small an effect to be detected individually but which collectively influence melanoma risk and/or show interactive effects, we used a two-step analysis strategy including pathway analysis of genome-wide SNP data, in a first step, and epistasis analysis within significant pathways, in a second step. Pathway analysis, using the gene-set enrichment analysis (GSEA) approach and the gene ontology (GO) database, was applied to the outcomes of MELARISK (3,976 subjects) and MDACC (2,827 subjects) GWASs. Cross-gene SNP-SNP interaction analysis within melanoma-associated GOs was performed using the INTERSNP software. Five GO categories were significantly enriched in genes associated with melanoma (false discovery rate ≤ 5% in both studies): response to light stimulus, regulation of mitotic cell cycle, induction of programmed cell death, cytokine activity and oxidative phosphorylation. Epistasis analysis, within each of the five significant GOs, showed significant evidence for interaction for one SNP pair at TERF1 and AFAP1L2 loci (pmeta-int  = 2.0 × 10(-7) , which met both the pathway and overall multiple-testing corrected thresholds that are equal to 9.8 × 10(-7) and 2.0 × 10(-7) , respectively) and suggestive evidence for another pair involving correlated SNPs at the same loci (pmeta-int  = 3.6 × 10(-6) ). This interaction has important biological relevance given the key role of TERF1 in telomere biology and the reported physical interaction between TERF1 and AFAP1L2 proteins. This finding brings a novel piece of evidence for the emerging role of telomere dysfunction into melanoma development.

Evaluating marker-guided treatment selection strategies

© 2014, The International Biometric Society.A potential venue to improve healthcare efficiency is to effectively tailor individualized treatment strategies by incorporating patient level predictor information such as environmental exposure, biological, and genetic marker measurements. Many useful statistical methods for deriving individualized treatment rules (ITR) have become available in recent years. Prior to adopting any ITR in clinical practice, it is crucial to evaluate its value in improving patient outcomes. Existing methods for quantifying such values mainly consider either a single marker or semi-parametric methods that are subject to bias under model misspecification. In this article, we consider a general setting with multiple markers and propose a two-step robust method to derive ITRs and evaluate their values. We also propose procedures for comparing different ITRs, which can be used to quantify the incremental value of new markers in improving treatment selection. While working models are used in step I to approximate optimal ITRs, we add a layer of calibration to guard against model misspecification and further assess the value of the ITR non-parametrically, which ensures the validity of the inference. To account for the sampling variability of the estimated rules and their corresponding values, we propose a resampling procedure to provide valid confidence intervals for the value functions as well as for the incremental value of new markers for treatment selection. Our proposals are examined through extensive simulation studies and illustrated with the data from a clinical trial that studies the effects of two drug combinations on HIV-1 infected patients.