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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.  More Time with Tremor: The Experience of Essential Tremor Versus Parkinson's Disease Patients 
Background
A broad range of tremors occur in patients with essential tremor and Parkinson's disease; despite this, there are virtually no published data that focus on the patient perspective. The aims were to (1) assess the subjective experience of tremor, comparing essential tremor and Parkinson's disease patients, and (2) assess the clinical correlates of that experience (i.e., what specific clinical characteristics were associated with more experienced tremor)?
Methods
121 essential tremor and 100 Parkinson's disease cases enrolled in a cross-sectional, clinical-epidemiological study underwent a detailed clinical assessment, which included a series of standardized questionnaires and neurological examination. The question, “On a typical day, how many waking hours do you have tremor in any body part?”, was also administered.
Results
Essential tremor cases reported more than three times the median number of waking hours experiencing tremor than Parkinson's disease cases: 10.1 ± 7.8 (median 10.0) vs. 5.5 ± 6.3 (median 3.0) hours (p<0.001). A small number of cases (esp., essential tremor) reported spending ≥16 hours/day shaking. Greater number of hours experiencing tremor was associated with female gender, higher Center for Epidemiological Studies Depression Scale scores, greater perceived disability and, in essential tremor, higher Essential Tremor Embarrassment Assessment scores.
Conclusions
Essential tremor patients reported more than three times the median number of waking hours experiencing tremor than Parkinson's disease patients. Certain clinical characteristics tracked with more reported tremor, and the number of such hours had clear clinical ramifications - greater number of hours was associated with both psycho-social and functional consequences.
doi:10.1002/mdc3.12207
PMCID: PMC4943749  PMID: 27430000
essential tremor; Parkinson's disease; tremor; clinical
20.  Searching for Mr. Hyde: A Five-Factor Approach to Characterizing “Types of Drunks” 
Addiction research & theory  2015;24(1):1-8.
Some individuals “change” more dramatically than others when intoxicated, and the nature and magnitude of these changes can result in harmful outcomes. This study utilized reports (N¼374) of participants’ “typical” five-factor model (FFM) characteristics across sober and intoxicated states and assessed the degree to which these reports could be grouped into meaningful clusters, as well as the association of cluster membership with negative alcoholrelated consequences. Results from finite mixture model clustering revealed a four cluster solution. Cluster 1, “Hemingway,” was the largest and defined by intoxication-related decreases in Conscientiousness and Intellect that were below average; Cluster 2, “Mary Poppins,” was defined by being high in Agreeableness when sober, decreasing less than average in Conscientiousness and Intellect and increasing more than average in Extraversion when drunk; Cluster 3, “Mr. Hyde,” reported larger drunk decreases in Conscientiousness and Intellect and smaller increases in Extraversion; Cluster 4, “The Nutty Professor,” was defined by being low in Extraversion when sober, increasing more than average in Extraversion and decreasing less than average in Conscientiousness when drunk. Cluster membership was associated with experiencing more alcohol consequences. These results support use of the FFM to characterize clinically meaningful subgroups of sober-to-drunk differences in trait expression.
doi:10.3109/16066359.2015.1029920
PMCID: PMC4943844  PMID: 27429607
Alcohol consequences; drunk personality; drunk types; five-factor model
21.  Immunization and challenge shown by hamsters infected with Opisthorchis viverrini following exposure to gamma-irradiated metacercariae of this carcinogenic liver fluke 
Journal of helminthology  2014;90(1):39-47.
Here we report findings to optimize and standardize conditions to attenuate metacercariae of Opisthorchis viverrini by ionizing radiation to elicit protective immune responses to challenge infection. Metacercariae were gamma-irradiated and the ability of irradiated metacercariae to prevent patent infection of challenge metacercariae in hamsters was determined, as well as their ability to induce a host antibody response. Metacercariae irradiated in a dose-dependent manner, with 3, 5, 10, 12, 20, 25 and 50 Gray, were used to infect Syrian golden hamsters by stomach gavage to ascertain the effect of irradiation on ability of the worms to establish infection. In addition, other hamsters were infected with metacercariae irradiated with 20–50 Gray, followed by challenge with intact/wild-type (non-irradiated) metacercariae to determine the protective effect as established by the numbers of adult flukes, eggs of O. viverrini in hamster faeces and anti-O. viverrini antibody titres. Significantly fewer worms were recovered from hamsters immunized with metacercariae irradiated at 20, 25 and 50 Gray than from control hamsters infected with intact metacercariae or 0 Gray, and the worms showed damaged reproductive organs. Faecal egg numbers were decreased significantly in hamsters immunized with 25 and 50 Gray metacercariae of O. viverrini. Moreover, hamsters administered metacercariae that were protected elicited a robust, specific anti-fluke immunoglobulin G response compared to control hamsters, suggesting a role for antibody in protection elicited by radiation-attenuated metacercariae.
doi:10.1017/S0022149X14000741
PMCID: PMC4943860  PMID: 25315797
22.  Population Pharmacokinetic Modeling of Cefadroxil Renal Transport in Wildtype and Pept2 Knockout Mice 
Cefadroxil is a broad-spectrum β-lactam antibiotic that is widely used in the treatment of various infectious diseases. Currently, poor understanding of the drug’s pharmacokinetic profiles and disposition mechanism(s) prevents determining optimal dosage regimens and achieving ideal antibacterial responses in patients. In the present retrospective study, we developed a population pharmacokinetic model of cefadroxil in wildtype and Pept2 knockout mice using the NONMEM approach.Cefadroxil pharmacokinetics were best described by a two-compartment model, with both saturable and nonsaturable elimination processes to/from the central compartment. Through this modeling approach, pharmacokinetic parameters in wildtype and Pept2 knockout mice were well estimated, respectively, as: volume of central compartment V1 (3.43 vs. 4.23 mL), volume of peripheral compartment V2 (5.98 vs. 8.61 mL), inter-compartment clearance Q (0.599 vs. 0.586 mL/min), and linear elimination rate constant K10 (0.111 vs. 0.070 min−1). Moreover, the secretion kinetics (i.e., Vm1 = 17.6 nmoL/min and Km1 = 37.1 μM) and reabsorption kinetics (i.e., Vm2 = 15.0 nmoL/min and Km2 = 27.1 μM) of cefadroxil were quantified in kidney, for the first time, under in vivo conditions.Our model provides a unique tool to quantitatively predict the dose-dependent nonlinear disposition of cefadroxil, as well as the potential for transporter-mediated drug interactions.
doi:10.3109/00498254.2015.1080881
PMCID: PMC4944204  PMID: 26372256
Disposition; kidney; mice; pharmacokinetics; transporters
23.  Central N/OFQ-NOP Receptor System in Pain Modulation 
It has been two decades since the peptide, nociceptin/orphanin FQ (N/OFQ), and its cognate (NOP) receptor were discovered. Although NOP receptor activation causes a similar pattern of intracellular actions as mu opioid (MOP) receptors, NOP receptor-mediated pain modulation in rodents are more complicated than MOP receptor activation. In this review, we highlight the functional evidence of spinal, supraspinal, and systemic actions of NOP receptor agonists for regulating pain. In rodents, effects of the N/OFQ-NOP receptor system in spinal and supraspinal sites for modulating pain are bidirectional depending on the doses, assays, and pain modalities. The net effect of systemically administered NOP receptor agonists may depend on relative contribution of spinal and supraspinal actions of the N/OFQ-NOP receptor signaling in rodents under different pain states. In stark contrast, NOP receptor agonists produce only antinociception and antihypersensitivity in spinal and supraspinal regions of nonhuman primates regardless of doses and assays. More importantly, NOP receptor agonists and a few bifunctional NOP/MOP receptor agonists do not exhibit reinforcing effects (abuse liability), respiratory depression, itch pruritus, nor do they delay the gastrointestinal transit function (constipation) in nonhuman primates. Depending upon their intrinsic efficacies for activating NOP and MOP receptors, bifunctional NOP/MOP receptor agonists warrant additional investigation in primates regarding their side effect profiles. Nevertheless, NOP receptor-related agonists display a much wider therapeutic window as compared to that of MOP receptor agonists in primates. Both selective NOP receptor agonists and bifunctional NOP/MOP receptor agonists hold a great potential as effective and safe analgesics without typical opioid-associated side effects in humans.
doi:10.1016/bs.apha.2015.10.001
PMCID: PMC4944813  PMID: 26920014
Analgesics; Bifunctional ligands; Neuropathic pain; NOP receptor; Opioids; Primate; Rodent; Spinal cord; Supraspinal regions; Translational research
24.  Prospective Study of a Proactive Palliative Care Rounding Intervention in a Medical ICU 
Intensive care medicine  2015;42(1):54-62.
Purpose
To evaluate the effects of a palliative care intervention on clinical and family outcomes, and palliative care processes.
Methods
Prospective, before-and-after interventional study enrolling patients with high risk of mortality, morbidity, or unmet palliative care needs in a 24-bed academic intensive care unit (ICU). The intervention involved a palliative care clinician interacting with the ICU physicians on daily rounds for high-risk patients.
Results
100 patients were enrolled in the usual care phase, and 103 patients were enrolled during the intervention phase. The adjusted likelihood of a family meeting in ICU was 63% higher (RR 1.63, 95% CI 1.14 to 2.07, p=0.01), and time to family meeting was 41% shorter (95% CI 52% to 28% shorter, p<0.001). Adjusted ICU length of stay (LOS) was not significantly different between the two groups (6% shorter, 95% CI 16% shorter to 4% longer, p=0.22). Among those who died in the hospital, ICU LOS was 19% shorter in the intervention (95% CI 33% to 1% shorter, p=0.043). Adjusted hospital LOS was 26% shorter (95% CI 31% to 20% shorter, p < 0.001) with the intervention. PTSD symptoms were present in 9.1% of family respondents during the intervention versus 20.7% prior to the intervention (p=0.09). Mortality, family depressive symptoms, family satisfaction and quality of death and dying did not significantly differ between groups.
Conclusions
Proactive palliative care involvement on ICU rounds for high-risk patients was associated with more and earlier ICU family meetings and shorter hospital LOS. We did not identify differences in family satisfaction, family psychological symptoms, or family-rated quality of dying, but had limited power to detect such differences.
doi:10.1007/s00134-015-4098-1
PMCID: PMC4945103  PMID: 26556622
End-of-life care; palliative care; ICU decision-making; family meetings; communication; family ICU syndrome
25.  Modeling Drinking Behavior Progression in Youth: a Non-identified Probability Discrete Event System Using Cross-sectional Data 
Current HIV research  2016;14(2):93-100.
Background
The probabilistic discrete event systems (PDES) method provides a promising approach to study dynamics of underage drinking using cross-sectional data. However, the utility of this approach is often limited because the constructed PDES model is often non-identifiable. The purpose of the current study is to attempt a new method to solve the model.
Methods
A PDES-based model of alcohol use behavior was developed with four progression stages (never-drinkers [ND], light/moderate-drinker [LMD], heavy-drinker [HD], and ex-drinker [XD]) linked with 13 possible transition paths. We tested the proposed model with data for participants aged 12–21 from the 2012 National Survey on Drug Use and Health (NSDUH). The Moore-Penrose (M-P) generalized inverse matrix method was applied to solve the proposed model.
Results
Annual transitional probabilities by age groups for the 13 drinking progression pathways were successfully estimated with the M-P generalized inverse matrix approach. Result from our analysis indicates an inverse “J” shape curve characterizing pattern of experimental use of alcohol from adolescence to young adulthood. We also observed a dramatic increase for the initiation of LMD and HD after age 18 and a sharp decline in quitting light and heavy drinking.
Conclusion
Our findings are consistent with the developmental perspective regarding the dynamics of underage drinking, demonstrating the utility of the M-P method in obtaining a unique solution for the partially-observed PDES drinking behavior model. The M-P approach we tested in this study will facilitate the use of the PDES approach to examine many health behaviors with the widely available cross-sectional data.
PMCID: PMC4945116  PMID: 26511344
Behavioral model; cross-sectional data; Moore-Penrose generalized inverse matrix; non-identifiable system PDES; transitional probability; underage drinking

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