Visualizing the target estimand in comparative effectiveness studies with multiple treatments.

Aim: Comparative effectiveness research using real-world data often involves pairwise propensity score matching to adjust for confounding bias. We show that corresponding treatment effect estimates may have limited external validity, and propose two visualization tools to clarify the target estimand. Materials & methods: We conduct a simulation study to demonstrate, with bivariate ellipses and joy plots, that differences in covariate distributions across treatment groups may affect the external validity of treatment effect estimates. We showcase how these visualization tools can facilitate the interpretation of target estimands in a case study comparing the effectiveness of teriflunomide (TERI), dimethyl fumarate (DMF) and natalizumab (NAT) on manual dexterity in patients with multiple sclerosis. Results: In the simulation study, estimates of the treatment effect greatly differed depending on the target population. For example, when comparing treatment B with C, the estimated treatment effect (and respective standard error) varied from -0.27 (0.03) to -0.37 (0.04) in the type of patients initially receiving treatment B and C, respectively. Visualization of the matched samples revealed that covariate distributions vary for each comparison and cannot be used to target one common treatment effect for the three treatment comparisons. In the case study, the bivariate distribution of age and disease duration varied across the population of patients receiving TERI, DMF or NAT. Although results suggest that DMF and NAT improve manual dexterity at 1 year compared with TERI, the effectiveness of DMF versus NAT differs depending on which target estimand is used. Conclusion: Visualization tools may help to clarify the target population in comparative effectiveness studies and resolve ambiguity about the interpretation of estimated treatment effects.

Benefits of early treatment with natalizumab: a real-world study.

BACKGROUND: The impact of early versus later high-efficacy disease-modifying therapy (DMT) in patients with multiple sclerosis (MS) is uncertain. This study reported the association of early versus later natalizumab treatment with real-world clinical outcomes in MS patients. METHODS: The study included 661 participants diagnosed with MS in 1994 or later from 7 US centers participating in the MS Partners Advancing Technology for Health Solutions (MS PATHS) network. Time to natalizumab treatment between diagnosis and first infusion (TTNT) was determined from the Tysabri Outreach: Unified Commitment to Health (TOUCH) registry. Clinical outcomes were defined using neuroperformance tests included in the Multiple Sclerosis Performance Test. Associations were tested using TTNT as a categorical and continuous variable. Linear mixed models addressed within-subject and within-site clustering. RESULTS: TTNT varied from 0.1 to 19.8 years (median [interquartile range] 4.2 [1.8, 9.0] years). A significant association between later natalizumab use and worse outcomes was demonstrated for walking speed (p < 0.001), processing speed (p < 0.001), manual dexterity (p < 0.001), brain atrophy (p = 0.001), and T2 lesion volume (p = 0.02). Covariate-adjusted modelling of a sensitivity population diagnosed with MS in 2006 or later (n = 424) demonstrated significant associations between longer TTNT and worse walking speed (p < 0.05), processing speed (p < 0.001), and manual dexterity (p < 0.001). CONCLUSION: Later initiation of natalizumab was associated with worse clinical and radiologic imaging outcomes. Thus, high-efficacy DMT may have greater benefit when started earlier in MS patients. These results provide a rationale for randomized controlled trials to further assess the impact of early highly-effective DMT use versus later escalation of therapy.

Recommendations for the use of propensity score methods in multiple sclerosis research.

BACKGROUND: With many disease-modifying therapies currently approved for the management of multiple sclerosis, there is a growing need to evaluate the comparative effectiveness and safety of those therapies from real-world data sources. Propensity score methods have recently gained popularity in multiple sclerosis research to generate real-world evidence. Recent evidence suggests, however, that the conduct and reporting of propensity score analyses are often suboptimal in multiple sclerosis studies. OBJECTIVES: To provide practical guidance to clinicians and researchers on the use of propensity score methods within the context of multiple sclerosis research. METHODS: We summarize recommendations on the use of propensity score matching and weighting based on the current methodological literature, and provide examples of good practice. RESULTS: Step-by-step recommendations are presented, starting with covariate selection and propensity score estimation, followed by guidance on the assessment of covariate balance and implementation of propensity score matching and weighting. Finally, we focus on treatment effect estimation and sensitivity analyses. CONCLUSION: This comprehensive set of recommendations highlights key elements that require careful attention when using propensity score methods.

Evaluating Confounding Control in Estimations of Influenza Antiviral Effectiveness in Electronic Health Plan Data.

Observational studies of oseltamivir use and influenza complications could suffer from residual confounding. Using negative control risk periods and a negative control outcome, we examined confounding control in a health-insurance-claims-based study of oseltamivir and influenza complications (pneumonia, all-cause hospitalization, and dispensing of an antibiotic). Within the Food and Drug Administration's Sentinel System, we identified individuals aged ≥18 years who initiated oseltamivir use on the influenza diagnosis date versus those who did not, during 3 influenza seasons (2014-2017). We evaluated primary outcomes within the following 1-30 days (the primary risk period) and 61-90 days (the negative control period) and nonvertebral fractures (the negative control outcome) within days 1-30. We estimated propensity-score-matched risk ratios (RRs) per season. During the 2014-2015 influenza season, oseltamivir use was associated with a reduction in the risk of pneumonia (RR = 0.72, 95% confidence interval (CI): 0.70, 0.75) and all-cause hospitalization (RR = 0.54, 95% CI: 0.53, 0.55) in days 1-30. During days 61-90, estimates were near-null for pneumonia (RR = 1.04, 95% CI: 0.95, 1.15) and hospitalization (RR = 0.94, 95% CI: 0.91, 0.98) but slightly increased for antibiotic dispensing (RR = 1.14, 95% CI: 1.08, 1.21). The RR for fractures was near-null (RR = 1.09, 95% CI: 0.99, 1.20). Estimates for the 2016-2017 influenza season were comparable, while the 2015-2016 season had conflicting results. Our study suggests minimal residual confounding for specific outcomes, but results differed by season.

Risk of hospitalized depression and intentional self-harm with brand and authorized generic sertraline.

BACKGROUND: Recent suggestions of therapeutic inequivalence of brand and generic sertraline have raised concerns about disproportionately higher adverse events among generic users. OBJECTIVE: To assess the impact of confounding in a comparison of the risks of worsening depression and intentional self-harm (ISH) between users of brand name sertraline and its pharmaceutically equivalent authorized generic (AG). METHODS: Using a retrospective new-user cohort design, we identified patients with a diagnosis code for depression aged ≥12 years who were continuously enrolled in a Sentinel Data Partner health plan for ≥180 days before their first sertraline dispensing between June 30, 2006 and September 30, 2015. New use was defined as no evidence of sertraline dispensing in the 180 days before index date. We matched each brand name user to up to 10 AG users using propensity scores (PS) and conducted case-centered logistic regression to assess the risks of hospitalized depression and ISH. RESULTS: Before PS matching, brand name users were significantly less likely to be hospitalized for depression [Hazard Ratio (HR) = 0.70 (95% confidence interval (CI): 0.53-0.94)]. However, in the matched analysis, we observed no statistical difference between brand and AG users [HR = 0.84 (95% CI: 0.59-1.21)]. The risk of ISH did not significantly differ between the exposure groups in unmatched (HR = 0.99 (95% CI: 0.60-1.62) and matched analyses [HR = 0.91 (95% CI: 0.49-1.70). CONCLUSION: In depressed patients receiving brand versus AG sertraline, patient characteristics confounded the association with hospitalization. Baseline differences were ameliorated by PS matching resulting in no statistical difference between brand and AG sertraline users.

Validation of an ICD-10-based algorithm to identify stillbirth in the Sentinel System.

PURPOSE: To develop and validate an International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM)-based algorithm to identify cases of stillbirth using electronic healthcare data. METHODS: We conducted a retrospective study using claims data from three Data Partners (healthcare systems and insurers) in the Sentinel Distributed Database. Algorithms were developed using ICD-10-CM diagnosis codes to identify potential stillbirths among females aged 12-55 years between July 2016 and June 2018. A random sample of medical charts (N = 169) was identified for chart abstraction and adjudication. Two physician adjudicators reviewed potential cases to determine whether a stillbirth event was definite/probable, the date of the event, and the gestational age at delivery. Positive predictive values (PPVs) were calculated for the algorithms. Among confirmed cases, agreement between the claims data and medical charts was determined for the outcome date and gestational age at stillbirth. RESULTS: Of the 110 potential cases identified, adjudicators determined that 54 were stillbirth events. Criteria for the algorithm with the highest PPV (82.5%; 95% CI, 70.9%-91.0%) included the presence of a diagnosis code indicating gestational age ≥20 weeks and occurrence of either >1 stillbirth-related code or no other pregnancy outcome code (i.e., livebirth, spontaneous abortion, induced abortion) recorded on the index date. We found ≥90% agreement within 7 days between the claims data and medical charts for both the outcome date and gestational age at stillbirth. CONCLUSIONS: Our results suggest that electronic healthcare data may be useful for signal detection of medical product exposures potentially associated with stillbirth.

Complementary Use of U.S. FDA's Adverse Event Reporting System and Sentinel System to Characterize Direct Oral Anticoagulants-Associated Cutaneous Small Vessel Vasculitis.

BACKGROUND: Cutaneous small vessel vasculitis (CSVV) has been reported after exposure to direct oral anticoagulants (DOACs), such as dabigatran, rivaroxaban, apixaban, and edoxaban. OBJECTIVE: We used the U.S. Food and Drug Administration Adverse Event Reporting System (FAERS) to describe clinical characteristics associated with CSVV among DOAC-exposed patients. Furthermore, we characterized this signal in the Sentinel System to relate the clinical data from the individual FAERS cases to population-based electronic healthcare data. METHODS: We queried FAERS for all cases of CSVV associated with DOACs from U.S. approval date of each DOAC through March 16, 2018. Within the Sentinel System, we identified incident CSVV cases using ICD-9 and ICD-10 diagnosis codes among adults aged ≥ 30 years who received a DOAC in the prior 90 days between January 1, 2010, and June 30, 2018. We excluded patients with evidence of select autoimmune diagnoses in the 183 days prior to their CSVV diagnoses and reported patient characteristics in the 183-day period prior to CSVV diagnoses. RESULTS: In FAERS, we identified 50 cases of CSVV reported with rivaroxaban (n=26), apixaban (n=14), dabigatran (n=9), and edoxaban (n=1). Approximately 50% of the cases reported time to onset within 10 days after DOAC exposure. When specified, the predominant type of CSVV reported was leukocytoclastic vasculitis (n=31), followed by Henoch-Schonlein purpura (n=4). Hospitalization occurred in most of the cases (n=37). Switching of the offending agent after the development of CSVV was reported (n=26). Three rivaroxaban (n=3) cases and one dabigatran case (n=1) reported positive rechallenge. In the Sentinel system, we identified 3659 CSVV cases with prior DOAC exposure, with 85% of events occurring within 10 days. CONCLUSIONS: The assessment of FAERS cases, combined with the temporal clustering of the Sentinel System cases suggest a possible causal relationship of DOACs and CSVV. Future efforts should characterize the risk of CSVV among the various DOAC users.

Controlling Confounding in a Study of Oral Anticoagulants: Comparing Disease Risk Scores Developed Using Different Follow-Up Approaches.

PURPOSE: Little is known about how disease risk score (DRS) development should proceed under different pharmacoepidemiologic follow-up strategies. In an analysis of dabigatran vs. warfarin and risk of major bleeding, we compared the results of DRS adjustment when models were developed under "intention-to-treat" (ITT) and "as-treated" (AT) approaches. METHODS: We assessed DRS model discrimination, calibration, and ability to induce prognostic balance via the "dry run analysis". AT treatment effects stratified on each DRS were compared with each other and with a propensity score (PS) stratified reference estimate. Bootstrap resampling of the historical cohort at 10 percent-90 percent sample size was performed to assess the impact of sample size on DRS estimation. RESULTS: Historically-derived DRS models fit under AT showed greater decrements in discrimination and calibration than those fit under ITT when applied to the concurrent study population. Prognostic balance was approximately equal across DRS models (-6 percent to -7 percent "pseudo-bias" on the hazard ratio scale). Hazard ratios were between 0.76 and 0.78 with all methods of DRS adjustment, while the PS stratified hazard ratio was 0.83. In resampling, AT DRS models showed more overfitting and worse prognostic balance, and led to hazard ratios further from the reference estimate than did ITT DRSs, across sample sizes. CONCLUSIONS: In a study of anticoagulant safety, DRSs developed under an AT principle showed signs of overfitting and reduced confounding control. More research is needed to determine if development of DRSs under ITT is a viable solution to overfitting in other settings.

Comparative effectiveness of generic and brand-name medication use: A database study of US health insurance claims.

BACKGROUND: To the extent that outcomes are mediated through negative perceptions of generics (the nocebo effect), observational studies comparing brand-name and generic drugs are susceptible to bias favoring the brand-name drugs. We used authorized generic (AG) products, which are identical in composition and appearance to brand-name products but are marketed as generics, as a control group to address this bias in an evaluation aiming to compare the effectiveness of generic versus brand medications. METHODS AND FINDINGS: For commercial health insurance enrollees from the US, administrative claims data were derived from 2 databases: (1) Optum Clinformatics Data Mart (years: 2004-2013) and (2) Truven MarketScan (years: 2003-2015). For a total of 8 drug products, the following groups were compared using a cohort study design: (1) patients switching from brand-name products to AGs versus generics, and patients initiating treatment with AGs versus generics, where AG use proxied brand-name use, addressing negative perception bias, and (2) patients initiating generic versus brand-name products (bias-prone direct comparison) and patients initiating AG versus brand-name products (negative control). Using Cox proportional hazards regression after 1:1 propensity-score matching, we compared a composite cardiovascular endpoint (for amlodipine, amlodipine-benazepril, and quinapril), non-vertebral fracture (for alendronate and calcitonin), psychiatric hospitalization rate (for sertraline and escitalopram), and insulin initiation (for glipizide) between the groups. Inverse variance meta-analytic methods were used to pool adjusted hazard ratios (HRs) for each comparison between the 2 databases. Across 8 products, 2,264,774 matched pairs of patients were included in the comparisons of AGs versus generics. A majority (12 out of 16) of the clinical endpoint estimates showed similar outcomes between AGs and generics. Among the other 4 estimates that did have significantly different outcomes, 3 suggested improved outcomes with generics and 1 favored AGs (patients switching from amlodipine brand-name: HR [95% CI] 0.92 [0.88-0.97]). The comparison between generic and brand-name initiators involved 1,313,161 matched pairs, and no differences in outcomes were noted for alendronate, calcitonin, glipizide, or quinapril. We observed a lower risk of the composite cardiovascular endpoint with generics versus brand-name products for amlodipine and amlodipine-benazepril (HR [95% CI]: 0.91 [0.84-0.99] and 0.84 [0.76-0.94], respectively). For escitalopram and sertraline, we observed higher rates of psychiatric hospitalizations with generics (HR [95% CI]: 1.05 [1.01-1.10] and 1.07 [1.01-1.14], respectively). The negative control comparisons also indicated potentially higher rates of similar magnitude with AG compared to brand-name initiation for escitalopram and sertraline (HR [95% CI]: 1.06 [0.98-1.13] and 1.11 [1.05-1.18], respectively), suggesting that the differences observed between brand and generic users in these outcomes are likely explained by either residual confounding or generic perception bias. Limitations of this study include potential residual confounding due to the unavailability of certain clinical parameters in administrative claims data and the inability to evaluate surrogate outcomes, such as immediate changes in blood pressure, upon switching from brand products to generics. CONCLUSIONS: In this study, we observed that use of generics was associated with comparable clinical outcomes to use of brand-name products. These results could help in promoting educational interventions aimed at increasing patient and provider confidence in the ability of generic medicines to manage chronic diseases.

Effect of Lawyer-Submitted Reports on Signals of Disproportional Reporting in the Food and Drug Administration's Adverse Event Reporting System.

INTRODUCTION: Lawyer-submitted reports may have unintended consequences on safety signal detection in spontaneous adverse event reporting systems. OBJECTIVE: Our objective was to assess the impact of lawyer-submitted reports primarily for one adverse event (AE) on the ability to detect a signal of disproportional reporting for another AE for the same drug in the US FDA Adverse Event Reporting System (FAERS). METHODS: FAERS reports from January 2004 to September 2015 were used to estimate yearly cumulative proportional reporting ratios (PRRs) for three known drug-AE pairs-isotretinoin-birth defects, atorvastatin-rhabdomyolysis, and rosuvastatin-rhabdomyolysis-with and without lawyer-submitted reports. Isotretinoin and atorvastatin have been the subject of high-profile tort litigation regarding other AEs. A lower bound of the 95% confidence interval (CI) of one or more based on three or more reports defined a signal. RESULTS: Cumulative PRRs met signaling criteria in all analyses. For isotretinoin, lawyer-submitted reports increased PRRs for birth defects before 2008, with the largest increase in 2006 (2.9 [95% CI 2.4-3.5] to 3.3 [95% CI 2.8-3.9]); lawyer-submitted reports decreased PRRs for birth defects after 2011, with the largest decrease in 2013 (2.2 [95% CI 2.0-2.5] to 1.9 [95% CI 1.7-2.1]). For atorvastatin, lawyer-submitted reports reduced PRRs for rhabdomyolysis after 2013, with the largest decrease in 2015 (18.0 [95% CI 17.1-19.1] to 15.4 [95% CI 14.5-16.2]). Lawyer-submitted reports had little impact on PRRs for rosuvastatin and rhabdomyolysis. CONCLUSIONS: Inclusion of lawyer-submitted reports in FAERS did not meaningfully distort known safety signals for two drugs subject to high-profile tort litigation for other AEs.

Extension of Disease Risk Score-Based Confounding Adjustments for Multiple Outcomes of Interest: An Empirical Evaluation.

Use of disease risk score (DRS)-based confounding adjustment when estimating treatment effects on multiple outcomes is not well studied. We designed an empirical cohort study to compare dabigatran initiators and warfarin initiators with respect to risks of ischemic stroke and major bleeding in 12 sequential monitoring periods (90 days each), using data from the Truven Marketscan database (Truven Health Analytics, Ann Arbor, Michigan). We implemented 2 approaches to combine DRS for multiple outcomes: 1) 1:1 matching on prognostic propensity scores (PPS), created using DRS for bleeding and stroke as independent variables in a propensity score (PS) model; and 2) simultaneous 1:1 matching on DRS for bleeding and stroke using Mahalanobis distance (M-distance), and compared their performance with that of traditional PS matching. M-distance matching appeared to produce more stable results in the early marketing period than both PPS and traditional PS matching; hazard ratios from unadjusted analysis, traditional PS matching, PPS matching, and M-distance matching after 4 periods were 0.72 (95% confidence interval (CI): 0.51, 1.03), 0.61 (95% CI: 0.31, 1.09), 0.55 (95% CI: 0.33, 0.91), and 0.78 (95% CI: 0.45, 1.34), respectively, for stroke and 0.65 (95% CI: 0.53, 0.80), 0.78 (95% CI: 0.60, 1.01), 0.75 (95% CI: 0.59, 0.96), and 0.78 (95% CI: 0.64, 0.95), respectively, for bleeding. In later periods, estimates were similar for traditional PS matching and M-distance matching but suggested potential residual confounding with PPS matching. These results suggest that M-distance matching may be a valid approach for extension of DRS-based confounding adjustments for multiple outcomes of interest.

Differences in rates of switchbacks after switching from branded to authorized generic and branded to generic drug products: cohort study.

OBJECTIVES: To compare rates of switchbacks to branded drug products for patients switched from branded to authorized generic drug products, which have the same active ingredients, appearance, and excipients as the branded product, with patients switched from branded to generic drug products, which have the same active ingredients as the branded product but may differ in appearance and excipients. DESIGN: Observational cohort study. SETTING: Private (a large commercial health plan) and public (Medicaid) insurance programs in the US. PARTICIPANTS: Beneficiaries of a large US commercial health insurer between 2004 and 2013 (primary cohort) and Medicaid beneficiaries between 2000 and 2010 (replication cohort). MAIN OUTCOME MEASURES: Patients taking branded products for one of the study drugs (alendronate tablets, amlodipine tablets, amlodipine-benazepril capsules, calcitonin salmon nasal spray, escitalopram tablets, glipizide extended release tablets, quinapril tablets, and sertraline tablets) were identified when they switched to an authorized generic or a generic drug product after the date of market entry of generic drug products. These patients were followed for switchbacks to the branded drug product in the year after their switch to an authorized generic or a generic drug product. Cox proportional hazard models were used to estimate hazard ratios and 95% confidence intervals after adjusting for demographics, including age, sex, and calendar year. Inverse variance meta-analysis was used to pool adjusted hazard ratios across all drug products. RESULTS: A total of 94 909 patients switched from branded to authorized generic drug products and 116 017 patients switched from branded to generic drug products and contributed to the switchback analysis. Unadjusted incidence rates of switchback varied across drug products, ranging from a low of 3.8 per 100 person years (for alendronate tablets) to a high of 17.8 per 100 person years (for amlodipine-benazepril capsules), with an overall rate of 8.2 per 100 person years across all drug products. Adjusted switchback rates were consistently lower for patients who switched from branded to authorized generic drug products compared with branded to generic drug products in the primary cohort (pooled hazard ratio 0.72, 95% confidence interval 0.64 to 0.81). Similar results (0.75, 0.62 to 0.91) were observed in the replication cohort. CONCLUSION: Switching from branded to authorized generic drug products was associated with lower switchback rates compared with switching from branded to generic drug products.

Conducting Privacy-Preserving Multivariable Propensity Score Analysis When Patient Covariate Information Is Stored in Separate Locations.

Distributed networks of health-care data sources are increasingly being utilized to conduct pharmacoepidemiologic database studies. Such networks may contain data that are not physically pooled but instead are distributed horizontally (separate patients within each data source) or vertically (separate measures within each data source) in order to preserve patient privacy. While multivariable methods for the analysis of horizontally distributed data are frequently employed, few practical approaches have been put forth to deal with vertically distributed health-care databases. In this paper, we propose 2 propensity score-based approaches to vertically distributed data analysis and test their performance using 5 example studies. We found that these approaches produced point estimates close to what could be achieved without partitioning. We further found a performance benefit (i.e., lower mean squared error) for sequentially passing a propensity score through each data domain (called the "sequential approach") as compared with fitting separate domain-specific propensity scores (called the "parallel approach"). These results were validated in a small simulation study. This proof-of-concept study suggests a new multivariable analysis approach to vertically distributed health-care databases that is practical, preserves patient privacy, and warrants further investigation for use in clinical research applications that rely on health-care databases.

Prioritizing disease-linked variants, genes, and pathways with an interactive whole-genome analysis pipeline.

Whole-genome sequencing (WGS) studies are uncovering disease-associated variants in both rare and nonrare diseases. Utilizing the next-generation sequencing for WGS requires a series of computational methods for alignment, variant detection, and annotation, and the accuracy and reproducibility of annotation results are essential for clinical implementation. However, annotating WGS with up to date genomic information is still challenging for biomedical researchers. Here, we present one of the fastest and highly scalable annotation, filtering, and analysis pipeline-gNOME-to prioritize phenotype-associated variants while minimizing false-positive findings. Intuitive graphical user interface of gNOME facilitates the selection of phenotype-associated variants, and the result summaries are provided at variant, gene, and genome levels. Moreover, the enrichment results of specific variants, genes, and gene sets between two groups or compared with population scale WGS datasets that is already integrated in the pipeline can help the interpretation. We found a small number of discordant results between annotation software tools in part due to different reporting strategies for the variants with complex impacts. Using two published whole-exome datasets of uveal melanoma and bladder cancer, we demonstrated gNOME's accuracy of variant annotation and the enrichment of loss-of-function variants in known cancer pathways. gNOME Web server and source codes are freely available to the academic community (http://gnome.tchlab.org).

Analysis of heterogeneity in nonspecific PEGylation reactions of biomolecules.

The compositional heterogeneity associated with polymer conjugation reactions of biomolecules is analyzed for the particular case of nonspecific PEGylation reactions. It is shown that the distribution of the number of PEG moieties grafted to biomolecules such as proteins is a binomial-type function of two parameters-the reaction efficiency as well as the number of binding sites per biomolecule. The nature of this distribution implies that uniform compositions are favored for increasing number of coupling sites per biomolecule as well as for increasing efficiency of the modification process. Therefore, the binomial distribution provides a rationale for the pronounced heterogeneity that is observed for PEGylated small enzyme systems even at high coupling efficiencies. For the particular case of PEGylated trypsin it is shown that the heterogeneity results in a broad distribution of deactivation times that is captured by a stretched exponential decay model. The presented analysis is expected to apply to general modification processes of compounds in which partial functionalization of a fixed number of reactive sites is achieved by means of a nonspecific coupling reaction.

gSearch: a fast and flexible general search tool for whole-genome sequencing.

BACKGROUND: Various processes such as annotation and filtering of variants or comparison of variants in different genomes are required in whole-genome or exome analysis pipelines. However, processing different databases and searching among millions of genomic loci is not trivial. RESULTS: gSearch compares sequence variants in the Genome Variation Format (GVF) or Variant Call Format (VCF) with a pre-compiled annotation or with variants in other genomes. Its search algorithms are subsequently optimized and implemented in a multi-threaded manner. The proposed method is not a stand-alone annotation tool with its own reference databases. Rather, it is a search utility that readily accepts public or user-prepared reference files in various formats including GVF, Generic Feature Format version 3 (GFF3), Gene Transfer Format (GTF), VCF and Browser Extensible Data (BED) format. Compared to existing tools such as ANNOVAR, gSearch runs more than 10 times faster. For example, it is capable of annotating 52.8 million variants with allele frequencies in 6 min. AVAILABILITY: gSearch is available at http://ml.ssu.ac.kr/gSearch. It can be used as an independent search tool or can easily be integrated to existing pipelines through various programming environments such as Perl, Ruby and Python.

Can survival processing enhance story memory? Testing the generalizability of the adaptive memory framework.

Research from the adaptive memory framework shows that thinking about words in terms of their survival value in an incidental learning task enhances their free recall relative to other semantic encoding strategies and intentional learning (Nairne, Pandeirada, & Thompson, 2008). We found similar results. When participants used incidental survival encoding for a list of words (e.g., "Will this object enhance my survival if I were stranded in the grasslands of a foreign land?"), they produced better free recall on a surprise test than did participants who intentionally tried to remember those words (Experiment 1). We also found this survival processing advantage when the words were presented within the context of a survival or neutral story (Experiment 2). However, this advantage did not extent to memory for a story's factual content, regardless of whether the participants were tested by cued recall (Experiment 3) or free recall (Experiments 4-5). Listening to a story for understanding under intentional or incidental learning conditions was just as good as survival processing for remembering story content. The functionalist approach to thinking about memory as an evolutionary adaptation designed to solve reproductive fitness problems provides a different theoretical framework for research, but it is not yet clear if survival processing has general applicability or is effective only for processing discrete stimuli in terms of fitness-relevant scenarios from our past.

Colloidal crystal growth monitored by Bragg diffraction interference fringes.

We monitored the crystal growth kinetics of crystallization of a shear melted crystalline colloidal array (CCA). The fcc CCA heterogeneously nucleates at the flow cell wall surface. We examined the evolution of the (1 1 1) Bragg diffraction peak, and, for the first time, quantitatively monitored growth by measuring the temporal evolution of the Bragg diffraction interference fringes. Modeling of the evolution of the fringe patterns exposes the time dependence of the increasing crystal thickness. The initial diffusion-driven linear growth is followed by ripening-driven growth. Between 80 and 90 microM NaCl concentrations the fcc crystals first linearly grow at rates between 1.9 and 4.2 microm/s until they contact homogeneously nucleated crystals in the bulk. At lower salt concentrations interference fringes are not visible because the strong electrostatic interactions between particles result in high activation barriers, preventing defect annealing and leading to a lower crystal quality. The fcc crystals melt to a liquid phase at >90 microM NaCl concentrations. Increasing NaCl concentrations slow the fcc CCA growth rate consistent with the expectation of the classical Wilson-Frenkel growth theory. The final thickness of wall-nucleated CCA, that is determined by the competition between growth of heterogeneously and homogenously nucleated CCA, increases with higher NaCl concentrations.

Monodisperse, high refractive index, highly charged ZnS colloids self assemble into crystalline colloidal arrays.

We developed an efficient synthesis of monodisperse, highly surface charged, high refractive index ZnS spherical particles by using a gel-sol method. Concentrated solutions of zinc-ammonia-NTA (nitrilotriacetic acid) were reacted with thioacetamide in the presence of gelatin which stabilized the growing particles. We dramatically increased the particle surface charge density by condensing silica and silylated phosphonate groups on the particle surface. These monodisperse highly charged ZnS particles are somewhat porous and have a refractive index of 1.868. These are the highest refractive index, monodisperse, highly charged spherical particles to self assemble into non-close-packed crystalline colloidal arrays which Bragg diffract light.

Charge stabilized crystalline colloidal arrays as templates for fabrication of non-close-packed inverted photonic crystals.

We developed a straightforward method to form non-close-packed highly ordered fcc direct and inverse opal silica photonic crystals. We utilize an electrostatically self assembled crystalline colloidal array (CCA) template formed by monodisperse, highly charged polystyrene particles. We then polymerize a hydrogel around the CCA (PCCA) and condense silica to form a highly ordered silica impregnated (siPCCA) photonic crystal. Heating at 450 degrees C removes the organic polymer leaving a silica inverse opal structure. By altering the colloidal particle concentration we independently control the particle spacing and the wall thickness of the inverse opal photonic crystals. This allows us to control the optical dielectric constant modulation in order to optimize the diffraction; the dielectric constant modulation is controlled independently of the photonic crystal periodicity. These fcc photonic crystals are better ordered than typical close-packed photonic crystals because their self assembly utilizes soft electrostatic repulsive potentials. We show that colloidal particle size and charge polydispersity has modest impact on ordering, in contrast to that for close-packed crystals.