PMCC PMCC

Search tips
Search criteria

Advanced
Results 1-25 (3064)
 

Clipboard (0)
None

Select a Filter Below

Journals
more »
Year of Publication
more »
1.  A variable selection method for genome-wide association studies 
Bioinformatics  2010;27(1):1-8.
Motivation: Genome-wide association studies (GWAS) involving half a million or more single nucleotide polymorphisms (SNPs) allow genetic dissection of complex diseases in a holistic manner. The common practice of analyzing one SNP at a time does not fully realize the potential of GWAS to identify multiple causal variants and to predict risk of disease. Existing methods for joint analysis of GWAS data tend to miss causal SNPs that are marginally uncorrelated with disease and have high false discovery rates (FDRs).
Results: We introduce GWASelect, a statistically powerful and computationally efficient variable selection method designed to tackle the unique challenges of GWAS data. This method searches iteratively over the potential SNPs conditional on previously selected SNPs and is thus capable of capturing causal SNPs that are marginally correlated with disease as well as those that are marginally uncorrelated with disease. A special resampling mechanism is built into the method to reduce false positive findings. Simulation studies demonstrate that the GWASelect performs well under a wide spectrum of linkage disequilibrium patterns and can be substantially more powerful than existing methods in capturing causal variants while having a lower FDR. In addition, the regression models based on the GWASelect tend to yield more accurate prediction of disease risk than existing methods. The advantages of the GWASelect are illustrated with the Wellcome Trust Case-Control Consortium (WTCCC) data.
Availability: The software implementing GWASelect is available at http://www.bios.unc.edu/~lin.
Access to WTCCC data: http://www.wtccc.org.uk/
Contact: lin@bios.unc.edu
Supplementary information: Supplementary data are available at Bioinformatics Online.
doi:10.1093/bioinformatics/btq600
PMCID: PMC3025714  PMID: 21036813
2.  A variable selection method for genome-wide association studies 
Biometrics  2011;27(1):1-8.
Motivation
Genome-wide association studies (GWAS) involving half a million or more single nucleotide polymorphisms (SNPs) allow genetic dissection of complex diseases in a holistic manner. The common practice of analyzing one SNP at a time does not fully realize the potential of GWAS to identify multiple causal variants and to predict risk of disease. Existing methods for joint analysis of GWAS data tend to miss causal SNPs that are marginally uncorrelated with disease and have high false discovery rates (FDRs).
Results
We introduce GWASelect, a statistically powerful and computationally efficient variable selection method designed to tackle the unique challenges of GWAS data. This method searches iteratively over the potential SNPs conditional on previously selected SNPs and is thus capable of capturing causal SNPs that are marginally correlated with disease as well as those that are marginally uncorrelated with disease. A special resampling mechanism is built into the method to reduce false-positive findings. Simulation studies demonstrate that the GWASelect performs well under a wide spectrum of linkage disequilibrium (LD) patterns and can be substantially more powerful than existing methods in capturing causal variants while having a lower FDR. In addition, the regression models based on the GWASelect tend to yield more accurate prediction of disease risk than existing methods. The advantages of the GWASelect are illustrated with the Wellcome Trust Case-Control Consortium (WTCCC) data.
doi:10.1093/bioinformatics/btq600
PMCID: PMC3025714  PMID: 21036813
3.  Efficient whole-genome association mapping using local phylogenies for unphased genotype data 
Bioinformatics  2008;24(19):2215-2221.
Motivation: Recent advances in genotyping technology has made data acquisition for whole-genome association study cost effective, and a current active area of research is developing efficient methods to analyze such large-scale datasets. Most sophisticated association mapping methods that are currently available take phased haplotype data as input. However, phase information is not readily available from sequencing methods and inferring the phase via computational approaches is time-consuming, taking days to phase a single chromosome.
Results: In this article, we devise an efficient method for scanning unphased whole-genome data for association. Our approach combines a recently found linear-time algorithm for phasing genotypes on trees with a recently proposed tree-based method for association mapping. From unphased genotype data, our algorithm builds local phylogenies along the genome, and scores each tree according to the clustering of cases and controls. We assess the performance of our new method on both simulated and real biological datasets.
Availability The software described in this article is available at http://www.daimi.au.dk/~mailund/Blossoc and distributed under the GNU General Public License.
Contact:mailund@birc.au.dk
doi:10.1093/bioinformatics/btn406
PMCID: PMC2553438  PMID: 18667442
4.  iFoldRNA: three-dimensional RNA structure prediction and folding 
Bioinformatics  2008;24(17):1951-1952.
Summary: Three-dimensional RNA structure prediction and folding is of significant interest in the biological research community. Here, we present iFoldRNA, a novel web-based methodology for RNA structure prediction with near atomic resolution accuracy and analysis of RNA folding thermodynamics. iFoldRNA rapidly explores RNA conformations using discrete molecular dynamics simulations of input RNA sequences. Starting from simplified linear-chain conformations, RNA molecules (<50 nt) fold to native-like structures within half an hour of simulation, facilitating rapid RNA structure prediction. All-atom reconstruction of energetically stable conformations generates iFoldRNA predicted RNA structures. The predicted RNA structures are within 2–5 Å root mean squre deviations (RMSDs) from corresponding experimentally derived structures. RNA folding parameters including specific heat, contact maps, simulation trajectories, gyration radii, RMSDs from native state, fraction of native-like contacts are accessible from iFoldRNA. We expect iFoldRNA will serve as a useful resource for RNA structure prediction and folding thermodynamic analyses.
Availability: http://iFoldRNA.dokhlab.org.
Contact: dokh@med.unc.edu
Supplementary information: Supplementary data are available at Bioinformatics online.
doi:10.1093/bioinformatics/btn328
PMCID: PMC2559968  PMID: 18579566
5.  Systematic biological prioritization after a genome-wide association study: an application to nicotine dependence 
Bioinformatics  2008;24(16):1805-1811.
Motivation: A challenging problem after a genome-wide association study (GWAS) is to balance the statistical evidence of genotype–phenotype correlation with a priori evidence of biological relevance.
Results: We introduce a method for systematically prioritizing single nucleotide polymorphisms (SNPs) for further study after a GWAS. The method combines evidence across multiple domains including statistical evidence of genotype–phenotype correlation, known pathways in the pathologic development of disease, SNP/gene functional properties, comparative genomics, prior evidence of genetic linkage, and linkage disequilibrium. We apply this method to a GWAS of nicotine dependence, and use simulated data to test it on several commercial SNP microarrays.
Availability: A comprehensive database of biological prioritization scores for all known SNPs is available at http://zork.wustl.edu/gin. This can be used to prioritize nicotine dependence association studies through a straightforward mathematical formula—no special software is necessary.
Contact: ssaccone@wustl.edu
Supplementary information: Supplementary data are available at Bioinformatics online.
doi:10.1093/bioinformatics/btn315
PMCID: PMC2610477  PMID: 18565990
6.  Comprehensive in silico mutagenesis highlights functionally important residues in proteins 
Bioinformatics  2008;24(16):i207-i212.
Motivation: Mutating residues into alanine (alanine scanning) is one of the fastest experimental means of probing hypotheses about protein function. Alanine scans can reveal functional hot spots, i.e. residues that alter function upon mutation. In vitro mutagenesis is cumbersome and costly: probing all residues in a protein is typically as impossible as substituting by all non-native amino acids. In contrast, such exhaustive mutagenesis is feasible in silico.
Results: Previously, we developed SNAP to predict functional changes due to non-synonymous single nucleotide polymorphisms. Here, we applied SNAP to all experimental mutations in the ASEdb database of alanine scans; we identified 70% of the hot spots (≥1 kCal/mol change in binding energy); more severe changes were predicted more accurately. Encouraged, we carried out a complete all-against-all in silico mutagenesis for human glucokinase. Many of the residues predicted as functionally important have indeed been confirmed in the literature, others await experimental verification, and our method is ready to aid in the design of in vitro mutagenesis.
Availability: ASEdb and glucokinase scores are available at http://www.rostlab.org/services/SNAP. For submissions of large/whole proteins for processing please contact the author.
Contact: yb2009@columbia.edu
doi:10.1093/bioinformatics/btn268
PMCID: PMC2597370  PMID: 18689826
7.  Systematic biological prioritization after a genome-wide association study 
Bioinformatics (Oxford, England)  2008;24(16):1805-1811.
Motivation
A challenging problem after a genome-wide association study (GWAS) is to balance the statistical evidence of geno-type-phenotype correlation with a priori evidence of biological relevance.
Results
We introduce a method for systematically prioritizing single nucleotide polymorphisms (SNPs) for further study after a GWAS. The method combines evidence across multiple domains, including statistical evidence of genotype-phenotype correlation, known pathways in the pathologic development of disease, SNP/gene functional properties, comparative genomics, prior evidence of genetic linkage, and linkage disequilibrium. We apply this method to a GWAS of nicotine dependence, and use simulated data to test it on several commercial SNP microarrays.
doi:10.1093/bioinformatics/btn315
PMCID: PMC2610477  PMID: 18565990
8.  LOT: a tool for linkage analysis of ordinal traits for pedigree data 
Bioinformatics  2008;24(15):1737-1739.
Summary: Existing linkage-analysis methods address binary or quantitative traits. However, many complex diseases and human conditions, particularly behavioral disorders, are rated on ordinal scales. Herein, we introduce, LOT, a tool that performs linkage analysis of ordinal traits for pedigree data. It implements a latent-variable proportional-odds logistic model that relates inheritance patterns to the distribution of the ordinal trait. The likelihood-ratio test is used for testing evidence of linkage.
Availability: The LOT program is available for download at http://c2s2.yale.edu/software/LOT/
Contact: heping.zhang@yale.edu
doi:10.1093/bioinformatics/btn258
PMCID: PMC2566542  PMID: 18535081
9.  Memory-efficient dynamic programming backtrace and pairwise local sequence alignment 
Bioinformatics (Oxford, England)  2008;24(16):1772-1778.
Motivation
A backtrace through a dynamic programming algorithm’s intermediate results in search of an optimal path, or to sample paths according to an implied probability distribution, or as the second stage of a forward–backward algorithm, is a task of fundamental importance in computational biology. When there is insufficient space to store all intermediate results in high-speed memory (e.g. cache) existing approaches store selected stages of the computation, and recompute missing values from these checkpoints on an as-needed basis.
Results
Here we present an optimal checkpointing strategy, and demonstrate its utility with pairwise local sequence alignment of sequences of length 10 000.
Availability
Sample C++-code for optimal backtrace is available in the Supplementary Materials.
doi:10.1093/bioinformatics/btn308
PMCID: PMC2668612  PMID: 18558620
10.  Modeling peptide fragmentation with dynamic Bayesian networks for peptide identification 
Bioinformatics (Oxford, England)  2008;24(13):i348-i356.
Motivation
Tandem mass spectrometry (MS/MS) is an indispensable technology for identification of proteins from complex mixtures. Proteins are digested to peptides that are then identified by their fragmentation patterns in the mass spectrometer. Thus, at its core, MS/MS protein identification relies on the relative predictability of peptide fragmentation. Unfortunately, peptide fragmentation is complex and not fully understood, and what is understood is not always exploited by peptide identification algorithms.
Results
We use a hybrid dynamic Bayesian network (DBN)/support vector machine (SVM) approach to address these two problems. We train a set of DBNs on high-confidence peptide-spectrum matches. These DBNs, known collectively as Riptide, comprise a probabilistic model of peptide fragmentation chemistry. Examination of the distributions learned by Riptide allows identification of new trends, such as prevalent a-ion fragmentation at peptide cleavage sites C-term to hydrophobic residues. In addition, Riptide can be used to produce likelihood scores that indicate whether a given peptide-spectrum match is correct. A vector of such scores is evaluated by an SVM, which produces a final score to be used in peptide identification. Using Riptide in this way yields improved discrimination when compared to other state-of-the-art MS/MS identification algorithms, increasing the number of positive identifications by as much as 12% at a 1% false discovery rate.
Availability
Python and C source code are available upon request from the authors. The curated training sets are available at http://noble.gs.washington.edu/proj/intense/. The Graphical Model Tool Kit (GMTK) is freely available at http://ssli.ee.washington.edu/bilmes/gmtk.
Contact
noble@gs.washington.edu
doi:10.1093/bioinformatics/btn189
PMCID: PMC2665034  PMID: 18586734
11.  Comprehensive in silico mutagenesis highlights functionally important residues in proteins 
Bioinformatics (Oxford, England)  2008;24(16):i207-i212.
Motivation
Mutating residues into alanine (alanine scanning) is one of the fastest experimental means of probing hypotheses about protein function. Alanine scans can reveal functional hot spots, i.e. residues that alter function upon mutation. In vitro mutagenesis is cumbersome and costly: probing all residues in a protein is typically as impossible as substituting by all non-native amino acids. In contrast, such exhaustive mutagenesis is feasible in silico.
Results
Previously, we developed SNAP to predict functional changes due to non-synonymous single nucleotide polymorphisms. Here, we applied SNAP to all experimental mutations in the ASEdb database of alanine scans; we identified 70% of the hot spots (≥1kCal/mol change in binding energy); more severe changes were predicted more accurately. Encouraged, we carried out a complete all-against-all in silico mutagenesis for human glucokinase. Many of the residues predicted as functionally important have indeed been confirmed in the literature, others await experimental verification, and our method is ready to aid in the design of in vitro mutagenesis.
Availability
ASEdb and glucokinase scores are available at http://www.rostlab.org/services/SNAP. For submissions of large/whole proteins for processing please contact the author.
Contact: yb2009@columbia.edu
doi:10.1093/bioinformatics/btn268
PMCID: PMC2597370  PMID: 18689826
12.  Powerful fusion: PSI-BLAST and consensus sequences 
Bioinformatics (Oxford, England)  2008;24(18):1987-1993.
Motivation
A typical PSI-BLAST search consists of iterative scanning and alignment of a large sequence database during which a scoring profile is progressively built and refined. Such a profile can also be stored and used to search against a different database of sequences. Using it to search against a database of consensus rather than native sequences is a simple add-on that boosts performance surprisingly well. The improvement comes at a price: we hypothesized that random alignment score statistics would differ between native and consensus sequences. Thus PSI-BLAST-based profile searches against consensus sequences might incorrectly estimate statistical significance of alignment scores. In addition, iterative searches against consensus databases may fail. Here, we addressed these challenges in an attempt to harness the full power of the combination of PSI-BLAST and consensus sequences.
Results
We studied alignment score statistics for various types of consensus sequences. In general, the score distribution parameters of profile-based consensus sequence alignments differed significantly from those derived for the native sequences. PSI-BLAST partially compensated for the parameter variation. We have identified a protocol for building specialized consensus sequences that significantly improved search sensitivity and preserved score distribution parameters. As a result, PSI-BLAST profiles can be used to search specialized consensus sequences without sacrificing estimates of statistical significance. We also provided results indicating that iterative PSI-BLAST searches against consensus sequences could work very well. Overall, we showed how a widely popular and effective method could be used to identify significantly more relevant similarities among protein sequences.
Availability
http://www.rostlab.org/services/consensus/
Contact:
dsp23@columbia.edu
doi:10.1093/bioinformatics/btn384
PMCID: PMC2577777  PMID: 18678588
13.  Efficient Whole-Genome Association Mapping using Local Phylogenies for Unphased Genotype Data 
Bioinformatics (Oxford, England)  2008;24(19):2215-2221.
Motivation
Recent advances in genotyping technology has made data acquisition for whole-genome association study cost effective, and a current active area of research is developing efficient methods to analyze such large-scale data sets. Most sophisticated association mapping methods that are currently available take phased haplotype data as input. However, phase information is not readily available from sequencing methods and inferring the phase via computational approaches is time-consuming, taking days to phase a single chromosome.
Results
In this paper, we devise an efficient method for scanning unphased whole-genome data for association. Our approach combines a recently found linear-time algorithm for phasing genotypes on trees with a recently proposed tree-based method for association mapping. From unphased genotype data, our algorithm builds local phylogenies along the genome, and scores each tree according to the clustering of cases and controls. We assess the performance of our new method on both simulated and real biological data sets.
doi:10.1093/bioinformatics/btn406
PMCID: PMC2553438  PMID: 18667442
14.  LOT 
Bioinformatics (Oxford, England)  2008;24(15):1737-1739.
Summary
Existing linkage-analysis methods address binary or quantitative traits. However, many complex diseases and human conditions, particularly behavioral disorders, are rated on ordinal scales. Herein, we introduce, LOT, a tool that performs linkage analysis of ordinal traits for pedigree data. It implements a latent-variable proportional-odds logistic model that relates inheritance patterns to the distribution of the ordinal trait. The likelihood-ratio test is used for testing evidence of linkage.
doi:10.1093/bioinformatics/btn258
PMCID: PMC2566542  PMID: 18535081
15.  iFoldRNA: Three-dimensional RNA Structure Prediction and Folding 
Bioinformatics (Oxford, England)  2008;24(17):1951-1952.
Summary
Three-dimensional RNA structure prediction and folding is of significant interest in the biological research community. Here, we present iFoldRNA, a novel web-based methodology for RNA structure prediction with near atomic resolution accuracy and analysis of RNA folding thermodynamics. iFoldRNA rapidly explores RNA conformations using discrete molecular dynamics simulations of input RNA sequences. Starting from simplified linear-chain conformations, RNA molecules (<50 nucleotides) fold to native-like structures within half an hour of simulation, facilitating rapid RNA structure prediction. All-atom reconstruction of energetically stable conformations generates iFoldRNA predicted RNA structures. The predicted RNA structures are within 2–5 Angstrom root mean square deviations from corresponding experimentally derived structures. RNA folding parameters including specific heat, contact maps, simulation trajectories, gyration radii, root mean square deviations from native state, fraction of native-like contacts are accessible from iFoldRNA. We expect iFoldRNA will serve as a useful resource for RNA structure prediction and folding thermodynamic analyses.
doi:10.1093/bioinformatics/btn328
PMCID: PMC2559968  PMID: 18579566
16.  Powerful fusion: PSI-BLAST and consensus sequences 
Bioinformatics  2008;24(18):1987-1993.
Motivation: A typical PSI-BLAST search consists of iterative scanning and alignment of a large sequence database during which a scoring profile is progressively built and refined. Such a profile can also be stored and used to search against a different database of sequences. Using it to search against a database of consensus rather than native sequences is a simple add-on that boosts performance surprisingly well. The improvement comes at a price: we hypothesized that random alignment score statistics would differ between native and consensus sequences. Thus PSI-BLAST-based profile searches against consensus sequences might incorrectly estimate statistical significance of alignment scores. In addition, iterative searches against consensus databases may fail. Here, we addressed these challenges in an attempt to harness the full power of the combination of PSI-BLAST and consensus sequences.
Results: We studied alignment score statistics for various types of consensus sequences. In general, the score distribution parameters of profile-based consensus sequence alignments differed significantly from those derived for the native sequences. PSI-BLAST partially compensated for the parameter variation. We have identified a protocol for building specialized consensus sequences that significantly improved search sensitivity and preserved score distribution parameters. As a result, PSI-BLAST profiles can be used to search specialized consensus sequences without sacrificing estimates of statistical significance. We also provided results indicating that iterative PSI-BLAST searches against consensus sequences could work very well. Overall, we showed how a very popular and effective method could be used to identify significantly more relevant similarities among protein sequences.
Availability: http://www.rostlab.org/services/consensus/
Contact: dariusz@mit.edu
doi:10.1093/bioinformatics/btn384
PMCID: PMC2577777  PMID: 18678588
17.  Modeling peptide fragmentation with dynamic Bayesian networks for peptide identification 
Bioinformatics  2008;24(13):i348-i356.
Motivation: Tandem mass spectrometry (MS/MS) is an indispensable technology for identification of proteins from complex mixtures. Proteins are digested to peptides that are then identified by their fragmentation patterns in the mass spectrometer. Thus, at its core, MS/MS protein identification relies on the relative predictability of peptide fragmentation. Unfortunately, peptide fragmentation is complex and not fully understood, and what is understood is not always exploited by peptide identification algorithms.
Results: We use a hybrid dynamic Bayesian network (DBN)/support vector machine (SVM) approach to address these two problems. We train a set of DBNs on high-confidence peptide-spectrum matches. These DBNs, known collectively as Riptide, comprise a probabilistic model of peptide fragmentation chemistry. Examination of the distributions learned by Riptide allows identification of new trends, such as prevalent a-ion fragmentation at peptide cleavage sites C-term to hydrophobic residues. In addition, Riptide can be used to produce likelihood scores that indicate whether a given peptide-spectrum match is correct. A vector of such scores is evaluated by an SVM, which produces a final score to be used in peptide identification. Using Riptide in this way yields improved discrimination when compared to other state-of-the-art MS/MS identification algorithms, increasing the number of positive identifications by as much as 12% at a 1% false discovery rate.
Availability: Python and C source code are available upon request from the authors. The curated training sets are available at http://noble.gs.washington.edu/proj/intense/. The Graphical Model Tool Kit (GMTK) is freely available at http://ssli.ee.washington.edu/bilmes/gmtk.
Contact:noble@gs.washington.edu
doi:10.1093/bioinformatics/btn189
PMCID: PMC2665034  PMID: 18586734
18.  Memory-efficient dynamic programming backtrace and pairwise local sequence alignment 
Bioinformatics  2008;24(16):1772-1778.
Motivation: A backtrace through a dynamic programming algorithm's intermediate results in search of an optimal path, or to sample paths according to an implied probability distribution, or as the second stage of a forward–backward algorithm, is a task of fundamental importance in computational biology. When there is insufficient space to store all intermediate results in high-speed memory (e.g. cache) existing approaches store selected stages of the computation, and recompute missing values from these checkpoints on an as-needed basis.
Results: Here we present an optimal checkpointing strategy, and demonstrate its utility with pairwise local sequence alignment of sequences of length 10 000.
Availability: Sample C++-code for optimal backtrace is available in the Supplementary Materials.
Contact: leen@cs.rpi.edu
Supplementary information: Supplementary data is available at Bioinformatics online.
doi:10.1093/bioinformatics/btn308
PMCID: PMC2668612  PMID: 18558620
19.  Corrigendum 
RNA Biology  2015;12(9):1070.
doi:10.1080/15476286.2015.1082401
PMCID: PMC4615175  PMID: 26383778
20.  Exploring beyond norms: social capital of pregnant women in Sri Lanka as a factor influencing health 
SpringerPlus  2016;5:411.
Background
Social capital during pregnancy in low and middle-income countries is hardly discussed in scientific literature. In Sri Lanka, even though the maternal health indicators are exemplary, addressing social determinants in pregnancy to improve the quality of care remains at minimal levels. While social capital is found to be context dependent, a comprehensive approach on identification of its dimensions within the context will unravel its relationships to health. The present qualitative study protocol was developed to explore social capital related to health among pregnant women in Anuradhapura district Sri Lanka.
Methods
The study will be conducted in two phases. In the phase one, we will select different communities from Anuradhapura district. Five to seven pregnant women will be selected from each community to complete a two week solicited diary on their social relationships. After completion of the diaries they will be interviewed for further clarification of social capital based on their diary documentation. In the second phase, we will conduct in-depth interviews with Public Health Midwives and senior community dwellers from each community to discuss social capital of pregnant women in the respective communities in order to triangulate the information obtained from the diaries. A framework analysis will be conducted for each community and formulate a final framework for social capital among pregnant women and there possible effects on health.
Discussion
This study will focus on filling a research gap of social determinants pertaining to maternal health in Sri Lanka. The findings will be helpful in generating hypotheses on unidentified social risk factors and their pathways to maternal health. The results of this in-depth exploration will be utilized to formulate a culturally sensitive study instrument to assess social capital during pregnancy.
doi:10.1186/s40064-016-2063-2
PMCID: PMC4821848  PMID: 27069831
Social capital; Maternal health; Qualitative; Sri Lanka
21.  Lifetime Prevalence of Sexual Intercourse and Contraception Use at Last Sex Among Adolescents and Young Adults With Congenital Heart Disease 
Purpose
Because of the increased risks associated with unplanned pregnancy for males and females with congenital heart disease (CHD), we investigated sexual intercourse and contraception use in these adolescents and young adults (AYA) and compared the same with national and state population data.
Methods
We recruited 337 AYA with structural CHD aged 15–25 years (Mage = 19 years, standard deviation = 3.1; 53% male, 84% white) from an outpatient cardiology clinic to participate in a larger study assessing genetic knowledge and health behaviors. Cumulative lifetime prevalence of adolescent (aged 15–18 years) sexual intercourse was compared with the 2011 Youth Risk Behavior Surveillance System and the 2007 Ohio Youth Risk Behavior Survey. Cumulative lifetime prevalence of young adult (aged 19–25 years) sexual intercourse and contraception use at last sex were compared with the 2006–2008 National Survey of Family Growth.
Results
Reported rates of ever having sexual intercourse, 26% of adolescents and 74% of young adults with CHD, were significantly lower than general population rates (47% and 86% respectively; p < .001). Similar to the general population, 77% of previously sexually active young adults with CHD reported using at least one effective method of contraception at last intercourse, whereas 25% used dual effective methods and 23% used no effective method.
Conclusions
Lower rates of ever having sexual intercourse in this population suggest that the psychosexual development of AYA with CHD may lag behind their peers. As nearly one in four participants reported using no effective method of contraception, health care providers should increase discussions of contraception with males and females with CHD.
doi:10.1016/j.jadohealth.2014.12.013
PMCID: PMC4821850  PMID: 25797631
Adolescents; Congenital heart disease; Contraception; Pregnancy; Psychosexual development; Sexual behavior; Young adults
22.  Pentameric quaternary structure of the intracellular domain of serotonin type 3A receptors 
Scientific Reports  2016;6:23921.
In spite of extensive efforts over decades an experimentally-derived structure of full-length eukaryotic pentameric ligand-gated ion channels (pLGICs) is still lacking. These pharmaceutically highly-relevant channels contain structurally well-conserved and characterized extracellular and transmembrane domains. The intracellular domain (ICD), however, has been orphaned in structural studies based on the consensus assumption of being largely disordered. In the present study, we demonstrate for the first time that the serotonin type 3A (5-HT3A) ICD assembles into stable pentamers in solution in the absence of the other two domains, thought to be the drivers for oligomerization. Additionally, the soluble 5-HT3A-ICD construct interacted with the protein RIC-3 (resistance to inhibitors of cholinesterase). The interaction provides evidence that the 5-HT3A-ICD is not only required but also sufficient for interaction with RIC-3. Our results suggest the ICD constitutes an oligomerization domain. This novel role significantly adds to its known contributions in receptor trafficking, targeting, and functional fine-tuning. The innate diversity of the ICDs with sizes ranging from 50 to 280 amino acids indicates new methodologies need to be developed to determine the structures of these domains. The use of soluble ICD proteins that we report in the present study constitutes a useful approach to address this gap.
doi:10.1038/srep23921
PMCID: PMC4820698  PMID: 27045630
23.  Utilizing Biopsychosocial and Strengths-Based Approaches Within the Field of Child Health: What We Know and Where We Can Grow 
We continue to increase our understanding of the experiences and settings that contribute to positive developmental outcomes in childhood, and those that confer greater risk. Although the mechanisms by which the risk and protective factors affect developmental outcomes need to be further elucidated through research, converging findings from the field of child health (spanning both physical and mental health) indicate that a biopsychosocial approach is useful. Here, we examine the evidence that early experiences confer both risk and protective processes on biopsychosocial development in childhood, and touch on some implications for the life course. Although this interdisciplinary field of research has already garnered substantial attention, here we aim to highlight the opportunity to use a strengths-based approach with the biopsychosocial model, with particular focus on children who experience prolonged stress. We close with consideration for future directions with an emphasis on policy and practice in clinical and educational settings to improve well-being in these early stages of the life course.
doi:10.1002/cad.20089
PMCID: PMC4367185  PMID: 25732011
24.  Web-based Tailored Intervention for Preparation of Parents and Children for Outpatient Surgery (WebTIPS): Development 
Anesthesia and analgesia  2015;120(4):905-914.
Background
Due to cost-containment efforts, preparation programs for outpatient surgery are currently not available to the majority of children and parents. The recent dramatic growth in the Internet presents a unique opportunity to transform how children and their parents are prepared for surgery. In this article we describe the development of a Web-based tailored preparation program for children and parents undergoing surgery (WebTIPS).
Development of Program
A multidisciplinary taskforce agreed that a Web-based tailored intervention comprised of intake, matrix and output modules was the preferred approach. Next, the content of the various intake variables, the matrix logic and the output content was developed. The output product has a parent component and a child component and is described in http://surgerywebtips.com/about.php. The child component makes use of preparation strategies such as information provision, modeling, play and coping skills training. The parent component of WebTIPS includes strategies such as information provision, coping skills training, relaxation and distraction techniques. A reputable animation and Web-design company developed a secured Web-based product based on the above description.
Conclusions
In this article we describe the development of a Web-based tailored preoperative preparation program that can be accessed by children and parents multiple times before and after surgery. A follow-up article in this issue of Anesthesia & Analgesia describes formative evaluation and preliminary efficacy testing of this Web-based tailored preoperative preparation program.
doi:10.1213/ANE.0000000000000610
PMCID: PMC4367194  PMID: 25790212
25.  Effect of environment on the long-term consequences of chronic pain 
Pain  2015;156(0 1):S42-S49.
Much evidence from pain patients and animal models shows that chronic pain does not exist in a vacuum, but has varied co-morbidities and far-reaching consequences. Patients with long-term pain often develop anxiety and depression and can manifest changes in cognitive functioning, particularly with working memory. Longitudinal studies in rodent models also show the development of anxiety-like behavior and cognitive changes weeks to months after an injury causing long-term pain. Brain imaging studies in pain patients and rodent models find that chronic pain is associated with anatomical and functional alterations in the brain. Nevertheless, studies in humans reveal that life-style choices, such as the practice of meditation or yoga, can reduce pain perception and have the opposite effect on the brain as does chronic pain. In rodent models, studies show that physical activity and a socially enriched environment reduce pain behavior and normalize brain function. Together, these studies suggest that the burden of chronic pain can be reduced by non-pharmacological interventions.
doi:10.1097/01.j.pain.0000460347.77341.bd
PMCID: PMC4367197  PMID: 25789436

Results 1-25 (3064)