Determination of [N-13]-ammonia extraction fraction in patients with coronary artery disease by calibration to invasive coronary and fractional flow reserve.

BACKGROUND: This study presents a new extraction fraction (EF) model based on physiological measures of invasive coronary flow reserve (CFR) and fractional flow reserve (FFR) in patients with suspected coronary artery disease (CAD) and normal index microcirculatory resistance (IMR). To ascertain the clinical relevance of the new EFs, flow measurements using the newly patient-determined EFs were compared to flow measurements using traditional animal-determined EFs. METHODS: 39 patients were retrospectively selected that included a total of 91 vascular territories with invasive coronary angiography physiological measures. [N-13]-ammonia dynamic rest/adenosine-stress PET imaging was conducted in all patients and absolute myocardial flow was estimated using four published compartmental models. The extraction fraction during hyperemic flow was iteratively estimated by maximizing the agreement between invasive CFR and FFR with the non-invasive analogs myocardial flow reserve (MFR) and relative flow reserve (RFR) at similar physiological states, respectively. RESULTS: Using the new patient-determined EFs, agreement between CFR vs MFR for Model 1 and 2 was moderate and poor for Model 3 and 4. All models showed moderate agreement for FFR vs RFR. When using published models of animal-determined EFs, agreement between CFR vs MFR remained moderate for Model 1 and 2, and poor for Model 3 and 4. Similarly, all models showed moderate agreement for FFR vs RFR using animal-determined EF values. None of the observed differences were statistically significant. CONCLUSIONS: Flow measurements using extraction fraction correction for [N-13]-ammonia based on calibration to invasive intracoronary angiography physiological measures in patients with CAD were not discordant from those reported in the literature. Either patient-determined or traditional animal-determined EF correction, when used with the appropriate flow model, yields moderate agreement with invasive measurements of coronary flow reserve and fractional flow reserve.

Comparing statistical methods for detecting and estimating waning efficacy of rotavirus vaccines in developing countries.

INTRODUCTION: Vaccination has significantly reduced morbidity and mortality resulting from rotavirus infection worldwide. However, rotavirus vaccine efficacy (VE) appears to wane over the first 2 years since vaccination, particularly in developing countries. Statistical methods for detecting VE waning and estimating its rate have been used in a few studies, but comparisons of methods for evaluating VE waning have not yet been performed. In this work we present and compare three methods - Durham's method, Tian's method, and time-dependent covariate (TDC) method - based on generalizations of the Cox proportional hazard model. METHODS: We developed a new stochastic agent-based simulation model to generate data from a hypothetical rotavirus vaccine trial where the protective efficacy of the vaccine may vary over time. Input parameters to the simulation model were obtained from studies on rotavirus infections in four developing countries. We applied each of the methods to four simulated datasets and compared the type-1 error probabilities and the powers of the resulting statistical tests. We also compared estimated and true values of VE over time. RESULTS: Durham's method had the highest power of detecting true VE waning of the three methods. This method also provided quite accurate estimates of VE in each period and of the per-period drop in VE. CONCLUSIONS: Durham's method is somewhat more powerful than the other two Cox proportional hazards model-based methods for detecting VE waning and provides more information about the temporal behavior of VE.

Postvaccination Serum Antirotavirus Immunoglobulin A as a Correlate of Protection Against Rotavirus Gastroenteritis Across Settings.

BACKGROUND: A correlate of protection for rotavirus gastroenteritis would facilitate rapid assessment of vaccination strategies and the next generation of rotavirus vaccines. We aimed to quantify a threshold of postvaccine serum antirotavirus immunoglobulin A (IgA) as an individual-level immune correlate of protection against rotavirus gastroenteritis. METHODS: Individual-level data on 5074 infants in 9 GlaxoSmithKline Rotarix Phase 2/3 clinical trials from 16 countries were pooled. Cox proportional hazard models were fit to estimate hazard ratios (HRs) describing the relationship between IgA thresholds and occurrence of rotavirus gastroenteritis. RESULTS: Seroconversion (IgA ≥ 20 U/mL) conferred substantial protection against any and severe rotavirus gastroenteritis to age 1 year. In low child mortality settings, seroconversion provided near perfect protection against severe rotavirus gastroenteritis (HR, 0.04; 95% confidence interval [CI], .01-.31). In high child mortality settings, seroconversion dramatically reduced the risk of severe rotavirus gastroenteritis (HR, 0.46; 95% CI, .25-.86). As IgA threshold increased, risk of rotavirus gastroenteritis generally decreased. A given IgA threshold provided better protection in low compared to high child mortality settings. DISCUSSION: Postvaccination antirotavirus IgA is a valuable correlate of protection against rotavirus gastroenteritis to age 1 year. Seroconversion provides an informative threshold for assessing rotavirus vaccine performance.

Antirotavirus IgA seroconversion rates in children who receive concomitant oral poliovirus vaccine: A secondary, pooled analysis of Phase II and III trial data from 33 countries.

BACKGROUND: Despite the success of rotavirus vaccines over the last decade, rotavirus remains a leading cause of severe diarrheal disease among young children. Further progress in reducing the burden of disease is inhibited, in part, by vaccine underperformance in certain settings. Early trials suggested that oral poliovirus vaccine (OPV), when administered concomitantly with rotavirus vaccine, reduces rotavirus seroconversion rates after the first rotavirus dose with modest or nonsignificant interference after completion of the full rotavirus vaccine course. Our study aimed to identify a range of individual-level characteristics, including concomitant receipt of OPV, that affect rotavirus vaccine immunogenicity in high- and low-child-mortality settings, controlling for individual- and country-level factors. Our central hypothesis was that OPV administered concomitantly with rotavirus vaccine reduced rotavirus vaccine immunogenicity. METHODS AND FINDINGS: Pooled, individual-level data from GlaxoSmithKline's Phase II and III clinical trials of the monovalent rotavirus vaccine (RV1), Rotarix, were analyzed, including 7,280 vaccinated infants (5-17 weeks of age at first vaccine dose) from 22 trials and 33 countries/territories (5 countries/territories with high, 13 with moderately low, and 15 with very low child mortality). Two standard markers for immune response were examined including antirotavirus immunoglobulin A (IgA) seroconversion (defined as the appearance of serum antirotavirus IgA antibodies in subjects initially seronegative) and serum antirotavirus IgA titer, both collected approximately 4-12 weeks after administration of the last rotavirus vaccine dose. Mixed-effect logistic regression and mixed-effect linear regression of log-transformed data were used to identify individual- and country-level predictors of seroconversion (dichotomous) and antibody titer (continuous), respectively. Infants in high-child-mortality settings had lower odds of seroconverting compared with infants in low-child-mortality settings (odds ratio [OR] = 0.48, 95% confidence interval [CI] 0.43-0.53, p < 0.001). Similarly, among those who seroconverted, infants in high-child-mortality settings had lower IgA titers compared with infants in low-child-mortality settings (mean difference [ß] = 0.83, 95% CI 0.77-0.90, p < 0.001). Infants who received OPV concomitantly with both their first and their second doses of rotavirus vaccine had 0.63 times the odds of seroconverting (OR = 0.63, 95% CI 0.47-0.84, p = 0.002) compared with infants who received OPV but not concomitantly with either dose. In contrast, among infants who seroconverted, OPV concomitantly administered with both the first and second rotavirus vaccine doses was found to be positively associated with antirotavirus IgA titer (ß = 1.28, 95% CI 1.07-1.53, p = 0.009). Our findings may have some limitations in terms of generalizability to routine use of rotavirus vaccine because the analysis was limited to healthy infants receiving RV1 in clinical trial settings. CONCLUSIONS: Our findings suggest that OPV given concomitantly with RV1 was a substantial contributor to reduced antirotavirus IgA seroconversion, and this interference was apparent after the second vaccine dose of RV1, as with the original clinical trials that our reanalysis is based on. However, our findings do suggest that the forthcoming withdrawal of OPV from the infant immunization schedule globally has the potential to improve RV1 performance.

Challenges in estimating influenza vaccine effectiveness.

Introduction: Influenza vaccination is regarded as the most effective way to prevent influenza infection. Due to the rapid genetic changes that influenza viruses undergo, seasonal influenza vaccines must be reformulated and re-administered annually necessitating the evaluation of influenza vaccine effectiveness (VE) each year. The estimation of influenza VE presents numerous challenges. Areas Covered: This review aims to identify, discuss, and, where possible, offer suggestions for dealing with the following challenges in estimating influenza VE: different outcomes of interest against which VE is estimated, study designs used to assess VE, sources of bias and confounding, repeat vaccination, waning immunity, population level effects of vaccination, and VE in at-risk populations. Expert Opinion: The estimation of influenza VE has improved with surveillance networks, better understanding of sources of bias and confounding, and the implementation of advanced statistical methods. Future research should focus on better estimates of the indirect effects of vaccination, the biological effects of vaccination, and how vaccines interact with the immune system. Specifically, little is known about how influenza vaccination impacts an individual's infectiousness, how vaccines wane over time, and the impact of repeated vaccination.

Effect of propensity of seeking medical care on the bias of the estimated effectiveness of rotavirus vaccines from studies using a test-negative case-control design.

BACKGROUND: Rotavirus is the leading cause of severe diarrhea among children worldwide, and vaccines can reduce morbidity and mortality by 50-98%. The test-negative control (TNC) study design is increasingly used for evaluating the effectiveness of vaccines against rotavirus and other vaccine-preventable diseases. In this study design, symptomatic patients who seek medical care are tested for the pathogen of interest. Those who test positive (negative) are classified as cases (controls). METHODS: We use a probability model to evaluate the bias of estimates of rotavirus vaccine effectiveness (VE) against rotavirus diarrhea resulting in hospitalization in the presence of possible confounding and selection biases due to differences in the propensity of seeking medical care (PSMC) between vaccinated and unvaccinated children. RESULTS: The TNC-based VE estimate corrects for confounding bias when the confounder's effects on the probabilities of rotavirus and non-rotavirus related hospitalizations are equal. If this condition is not met, then the estimated VE may be substantially biased. The bias is more severe in low-income countries, where VE is known to be lower. Under our model, differences in PSMC between vaccinated and unvaccinated children do not result in selection bias when the TNC study design is used. CONCLUSIONS: In practice, one can expect the association of PSMC (or other potential confounders) with the probabilities of rotavirus and non-rotavirus related hospitalization to be similar, in which case the confounding effects will only result in small bias in the VE estimate from TNC studies. The results of this work, along with those of our previous paper, confirm the TNC design can be expected to provide reliable estimates of rotavirus VE in both high- and low-income countries.

Bias of influenza vaccine effectiveness estimates from test-negative studies conducted during an influenza pandemic.

Test-negative (TN) studies have become the most widely used study design for the estimation of influenza vaccine effectiveness (VE) and are easily incorporated into existing influenza surveillance networks. We seek to determine the bias of TN-based VE estimates during a pandemic using a dynamic probability model. The model is used to evaluate and compare the bias of VE estimates under various sources of bias when vaccination occurs after the beginning of an outbreak, such as during a pandemic. The model includes two covariates (health status and health awareness), which may affect the probabilities of vaccination, developing influenza and non-influenza acute respiratory illness (ARI), and seeking medical care. Specifically, we evaluate the bias of VE estimates when (1) vaccination affects the probability of developing a non-influenza ARI; (2) vaccination affects the probability of seeking medical care; (3) a covariate (e.g. health status) is related to both the probabilities of vaccination and developing an ARI; and (4) a covariate (e.g. health awareness) is related to both the probabilities of vaccination and of seeking medical care. We considered two outcomes against which the vaccine is supposed to protect: symptomatic influenza and medically-attended influenza. When vaccination begins during an outbreak, we found that the effect of delayed onset of vaccination is unpredictable. VE estimates from TN studies were biased regardless of the source of bias present. However, if the core assumption of the TN design is satisfied, that is, if vaccination does not affect the probability of non-influenza ARI, then TN-based VE estimates against medically-attended influenza will only suffer from small (<0.05) to moderate bias (≥0.05 and <0.10). These results suggest that if sources of bias listed above are ruled out, TN studies are a valid study design for the estimation of VE during a pandemic.

Longer-term Direct and Indirect Effects of Infant Rotavirus Vaccination Across All Ages in the United States in 2000-2013: Analysis of a Large Hospital Discharge Data Set.

BACKGROUND: Rotavirus disease rates dramatically declined among children <5 years of age since the rotavirus vaccine was introduced in 2006; population-level impacts remain to be fully elucidated. METHODS: Data from the Healthcare Cost and Utilization Project State Inpatient Databases were used to conduct a time-series analysis of monthly hospital discharges across age groups for acute gastroenteritis and rotavirus from 2000 to 2013. Rate ratios were calculated comparing prevaccine and postvaccine eras. RESULTS: Following vaccine introduction, a decrease in rotavirus hospitalizations occurred with a shift toward biennial patterns across all ages. The 0-4-year age group experienced the largest decrease in rotavirus hospitalizations (rate ratio, 0.14; 95% confidence interval, .09-.23). The 5-19-year and 20-59-year age groups experienced significant declines in rotavirus hospitalization rates overall; the even postvaccine calendar years were characterized by progressively lower rates, and the odd postvaccine years were associated with reductions in rates that diminished over time. Those aged ≥60 years experienced the smallest change in rotavirus hospitalization rates overall, with significant reductions in even postvaccine years compared with prevaccine years (rate ratio, 0.51; 95% confidence interval, .39-.66). CONCLUSIONS: Indirect impacts of infant rotavirus vaccination are apparent in the emergence of biennial patterns in rotavirus hospitalizations that extend to all age groups ineligible for vaccination. These observations are consistent with the notion that young children are of primary importance in disease transmission and that the initial postvaccine period of dramatic population-wide impacts will be followed by more complex incidence patterns across the age range in the long term.

A Dynamic Model for Evaluation of the Bias of Influenza Vaccine Effectiveness Estimates From Observational Studies.

Given that influenza vaccination is now widely recommended in the United States, observational studies based on patients with acute respiratory illness (ARI) remain as the only option to estimate influenza vaccine effectiveness (VE). We developed a dynamic probability model to evaluate bias of VE estimates from passive surveillance cohort, test-negative, and traditional case-control studies. The model includes 2 covariates (health status and health awareness) that might affect the probabilities of vaccination, developing ARI, and seeking medical care. Our results suggest that test-negative studies produce unbiased estimates of VE against medically attended influenza when: 1) Vaccination does not affect the probability of noninfluenza ARI; and 2) health status has the same effect on the probability of influenza and noninfluenza ARIs. The same estimate might be severely biased (i.e., estimated VE - true VE ≥ 0.20) for estimating VE against symptomatic influenza if the vaccine affects the probability of seeking care against influenza ARI. VE estimates from test-negative studies might also be severely biased for both outcomes of interest when vaccination affects the probability of noninfluenza ARI, but estimates from passive surveillance cohort studies are unbiased in this case. Finally, VE estimates from traditional case-control studies suffer from bias regardless of the source of bias.

A comparison of the test-negative and traditional case-control study designs with respect to the bias of estimates of rotavirus vaccine effectiveness.

Estimation of the effectiveness of rotavirus vaccines via the test-negative control study design has gained popularity over the past few years. In this study design, children with severe diarrhea who test positive for rotavirus infection are considered as cases, while children who test negative serve as controls. We use a simple probability model to evaluate and compare the test-negative control and the traditional case-control designs with respect to the bias of resulting estimates of rotavirus vaccine effectiveness (VE). Comparisons are performed under two scenarios, corresponding to studies performed in high-income and low-income countries. We consider two potential sources of bias: (a) misclassification bias resulting from imperfect sensitivity and specificity of the test used to diagnose rotavirus infection, and (b) selection bias associated with possible effect of rotavirus vaccination on the probability of contracting severe non-rotavirus diarrhea. Our results suggest that both sources of bias may produce VE estimates with substantial bias. Particularly, lack of perfect specificity is associated with severe negative bias. For example, if the specificity of the diagnostic test is 90% then VE estimates from both types of case-control studies may under-estimate the true VE by more than 20%. If the vaccine protects children against non-rotavirus diarrhea then VE estimates from test-negative control studies may be close to zero even though the true VE is 50%. However, the sensitivity and specificity of the enzyme immunoassay test currently used to diagnose rotavirus infections are both over 99%, and there is no solid evidence that the existing rotavirus vaccines affect the rates of non-rotavirus diarrhea. We therefore conclude that the test-negative control study design is a convenient and reliable alternative for estimation of rotavirus VE.

Maximum likelihood estimation of influenza vaccine effectiveness against transmission from the household and from the community.

Influenza vaccination is recommended as the best way to protect against influenza infection and illness. Due to seasonal changes in influenza virus types and subtypes, a new vaccine must be produced, and vaccine effectiveness (VE) must be estimated, annually. Since 2010, influenza vaccination has been recommended universally in the United States, making randomized clinical trials unethical. Recent studies have used a monitored household cohort study design to determine separate VE estimates against influenza transmission from the household and community. We developed a probability model and accompanying maximum likelihood procedure to estimate vaccine-related protection against transmission of influenza from the household and the community. Using agent-based stochastic simulations, we validated that we can obtain maximum likelihood estimates of transmission parameters and VE close to their true values. Sensitivity analyses to examine the effect of deviations from our assumptions were conducted. We used our method to estimate transmission parameters and VE from data from a monitored household study in Michigan during the 2012-2013 influenza season and were able to detect a significant protective effect of influenza vaccination against community-acquired transmission.

A comparison of the test-negative and the traditional case-control study designs for estimation of influenza vaccine effectiveness under nonrandom vaccination.

BACKGROUND: As annual influenza vaccination is recommended for all U.S. persons aged 6 months or older, it is unethical to conduct randomized clinical trials to estimate influenza vaccine effectiveness (VE). Observational studies are being increasingly used to estimate VE. We developed a probability model for comparing the bias and the precision of VE estimates from two case-control designs: the traditional case-control (TCC) design and the test-negative (TN) design. In both study designs, acute respiratory illness (ARI) patients seeking medical care testing positive for influenza infection are considered cases. In the TN design, ARI patients seeking medical care who test negative serve as controls, while in the TCC design, controls are randomly selected individuals from the community who did not contract an ARI. METHODS: Our model assigns each study participant a covariate corresponding to the person's health status. The probabilities of vaccination and of contracting influenza and non-influenza ARI depend on health status. Hence, our model allows non-random vaccination and confounding. In addition, the probability of seeking care for ARI may depend on vaccination and health status. We consider two outcomes of interest: symptomatic influenza (SI) and medically-attended influenza (MAI). RESULTS: If vaccination does not affect the probability of non-influenza ARI, then VE estimates from TN studies usually have smaller bias than estimates from TCC studies. We also found that if vaccinated influenza ARI patients are less likely to seek medical care than unvaccinated patients because the vaccine reduces symptoms' severity, then estimates of VE from both types of studies may be severely biased when the outcome of interest is SI. The bias is not present when the outcome of interest is MAI. CONCLUSIONS: The TN design produces valid estimates of VE if (a) vaccination does not affect the probabilities of non-influenza ARI and of seeking care against influenza ARI, and (b) the confounding effects resulting from non-random vaccination are similar for influenza and non-influenza ARI. Since the bias of VE estimates depends on the outcome against which the vaccine is supposed to protect, it is important to specify the outcome of interest when evaluating the bias.

On the bias of estimates of influenza vaccine effectiveness from test-negative studies.

Estimates of the effectiveness of influenza vaccines are commonly obtained from a test-negative design (TND) study, where cases and controls are patients seeking care for an acute respiratory illness who test positive and negative, respectively, for influenza infection. Vaccine effectiveness (VE) estimates from TND studies are usually interpreted as vaccine effectiveness against medically-attended influenza (MAI). However, it is also important to estimate VE against any influenza illness (symptomatic influenza (SI)) as individuals with SI are still a public health burden even if they do not seek medical care. We present a numerical method to evaluate the bias of TND-based estimates of influenza VE with respect to MAI and SI. We consider two sources of bias: (a) confounding bias due to a (possibly unobserved) covariate that is associated with both vaccination and the probability of the outcome of interest and (b) bias resulting from the effect of vaccination on the probability of seeking care. Our results indicate that (a) VE estimates may suffer from substantial confounding bias when a confounder has a different effect on the probabilities of influenza and non-influenza ARI, and (b) when vaccination reduces the probability of seeking care against influenza ARI, then estimates of VE against MAI may be unbiased while estimates of VE against SI may be have a substantial positive bias.

Estimating Direct and Indirect Protective Effect of Influenza Vaccination in the United States.

With influenza vaccination rates in the United States recently exceeding 45% of the population, it is important to understand the impact that vaccination is having on influenza transmission. In this study, we used a Bayesian modeling approach, combined with a simple dynamical model of influenza transmission, to estimate this impact. The combined framework synthesized evidence from a range of data sources relating to influenza transmission and vaccination in the United States. We found that, for seasonal epidemics, the number of infections averted ranged from 9.6 million in the 2006-2007 season (95% credible interval (CI): 8.7, 10.9) to 37.2 million (95% CI: 34.1, 39.6) in the 2012-2013 season. Expressed in relative terms, the proportion averted ranged from 20.8% (95% CI: 16.8, 24.3) of potential infections in the 2011-2012 season to 47.5% (95% CI: 43.7, 50.8) in the 2008-2009 season. The percentage averted was only 1.04% (95% CI: 0.15, 3.2) for the 2009 H1N1 pandemic, owing to the late timing of the vaccination program in relation to the pandemic in the Northern hemisphere. In the future, further vaccination coverage, as well as improved influenza vaccines (especially those offering better protection in the elderly), could have an even stronger effect on annual influenza epidemics.

The case test-negative design for studies of the effectiveness of influenza vaccine in inpatient settings.

Background: The test-negative design (TND) to evaluate influenza vaccine effectiveness is based on patients seeking care for acute respiratory infection, with those who test positive for influenza as cases and the test-negatives serving as controls. This design has not been validated for the inpatient setting where selection bias might be different from an outpatient setting. Methods: We derived mathematical expressions for vaccine effectiveness (VE) against laboratory-confirmed influenza hospitalizations and used numerical simulations to verify theoretical results exploring expected biases under various scenarios. We explored meaningful interpretations of VE estimates from inpatient TND studies. Results: VE estimates from inpatient TND studies capture the vaccine-mediated protection of the source population against laboratory-confirmed influenza hospitalizations. If vaccination does not modify disease severity, these estimates are equivalent to VE against influenza virus infection. If chronic cardiopulmonary individuals are enrolled because of non-infectious exacerbation, biased VE estimates (too high) will result. If chronic cardiopulmonary disease status is adjusted for accurately, the VE estimates will be unbiased. If chronic cardiopulmonary illness cannot be adequately be characterized, excluding these individuals may provide unbiased VE estimates. Conclusions: The inpatient TND offers logistic advantages and can provide valid estimates of influenza VE. If highly vaccinated patients with respiratory exacerbation of chronic cardiopulmonary conditions are eligible for study inclusion, biased VE estimates will result unless this group is well characterized and the analysis can adequately adjust for it. Otherwise, such groups of subjects should be excluded from the analysis.

A simulation study of nonparametric total deviation index as a measure of agreement based on quantile regression.

Total deviation index (TDI) captures a prespecified quantile of the absolute deviation of paired observations from raters, observers, methods, assays, instruments, etc. We compare the performance of TDI using nonparametric quantile regression to the TDI assuming normality (Lin, 2000). This simulation study considers three distributions: normal, Poisson, and uniform at quantile levels of 0.8 and 0.9 for cases with and without contamination. Study endpoints include the bias of TDI estimates (compared with their respective theoretical values), standard error of TDI estimates (compared with their true simulated standard errors), and test size (compared with 0.05), and power. Nonparametric TDI using quantile regression, although it slightly underestimates and delivers slightly less power for data without contamination, works satisfactorily under all simulated cases even for moderate (say, ≥40) sample sizes. The performance of the TDI based on a quantile of 0.8 is in general superior to that of 0.9. The performances of nonparametric and parametric TDI methods are compared with a real data example. Nonparametric TDI can be very useful when the underlying distribution on the difference is not normal, especially when it has a heavy tail.

Intussusception after monovalent rotavirus vaccine-United States, Vaccine Adverse Event Reporting System (VAERS), 2008-2014.

BACKGROUND: In 2006 and 2008, two new rotavirus vaccines (RotaTeq [RV5] and Rotarix [RV1]) were introduced in the United States. US data on intussusception have been mostly related to RV5, with limited data on RV1. METHODS: We assessed intussusception events following RV1 reported to the Vaccine Adverse Event Reporting System (VAERS), a US national passive surveillance system, during February 2008-December 2014. We conducted a self-controlled risk interval analysis using Poisson regression to estimate the daily reporting ratio (DRR) of intussusception after the first 2 doses of RV1 comparing average daily reports 3-6 versus 0-2 days after vaccination. We calculated the excess risk of intussusception per 100,000 vaccinations based on DRRs and background rates of intussusception. Sensitivity analyses were conducted to assess effects of differential reporting completeness and inaccuracy of baseline rates. RESULTS: VAERS received 108 confirmed insusceptible reports after RV1. A significant clustering was observed on days 3-8 after does1 (p=0.001) and days 2-7 after dose 2 (p=0.001). The DRR comparing the 3-6 day and the 0-2 day periods after RV1 dose 1 was 7.5 (95% CI=2.3, 24.6), translating to an excess risk of 1.6 (95% CI=0.3, 5.8) per 100,000 vaccinations. The DRR was elevated but not significant after dose 2 (2.4 [95% CI=0.8,7.5]). The excess risk ranged from 1.2 to 2.8 per 100,000 in sensitivity analysis. CONCLUSIONS: We observed a significant increased risk of intussusception 3-6 days after dose 1 of RV1. The estimated small number of intussusception cases attributable to RV1 is outweighed by the benefits of rotavirus vaccination.

The E3 ubiquitin ligase parkin is recruited to the 26 S proteasome via the proteasomal ubiquitin receptor Rpn13.

Mutations in the Park2 gene, encoding the RING-HECT hybrid E3 ubiquitin ligase parkin, are responsible for a common familial form of Parkinson disease. By mono- and polyubiquitinating target proteins, parkin regulates various cellular processes, including degradation of proteins within the 26 S proteasome, a large multimeric degradation machine. In our attempt to further elucidate the function of parkin, we have identified the proteasomal ubiquitin receptor Rpn13/ADRM1 as a parkin-interacting protein. We show that the N-terminal ubiquitin-like (Ubl) domain of parkin binds directly to the pleckstrin-like receptor for ubiquitin (Pru) domain within Rpn13. Using mutational analysis and NMR, we find that Pru binding involves the hydrophobic patch surrounding Ile-44 in the parkin Ubl, a region that is highly conserved between ubiquitin and Ubl domains. However, compared with ubiquitin, the parkin Ubl exhibits greater than 10-fold higher affinity for the Pru domain. Moreover, knockdown of Rpn13 in cells increases parkin levels and abrogates parkin recruitment to the 26 S proteasome, establishing Rpn13 as the major proteasomal receptor for parkin. In contrast, silencing Rpn13 did not impair parkin recruitment to mitochondria or parkin-mediated mitophagy upon carbonyl cyanide m-chlorophenyl hydrazone-induced mitochondrial depolarization. However, it did delay the clearance of mitochondrial proteins (TIM23, TIM44, and TOM20) and enhance parkin autoubiquitination. Taken together, these findings implicate Rpn13 in linking parkin to the 26 S proteasome and regulating the clearance of mitochondrial proteins during mitophagy.

Effect of 13-valent pneumococcal conjugate vaccine on admissions to hospital 2 years after its introduction in the USA: a time series analysis.

BACKGROUND: In March 2010, 13-valent pneumococcal conjugate vaccine (PCV13) replaced the seven-valent vaccine in the USA. We assessed the effect of PCV13 use on pneumococcus-related admissions to hospital 2 years after the vaccine was introduced, when coverage in children younger than age 5 years had reached 54%. METHODS: We used data from a private inpatient discharge record database. We extracted age-specific data for admissions to hospital per month (July 1-June 30) for all-cause pneumonia, invasive pneumococcal disease, non-invasive pneumococcal pneumonia, and empyema (all coded by International Classification of Diseases 9) for 2005-12. We also extracted data for urinary tract infection and hospital admission for any reason as control outcomes. We assessed incidences of hospital admission before and after the introduction of PCV13 and used a negative binomial multiple regression model to estimate how much of the change in hospital admissions could be attributed to the vaccine. FINDINGS: Our model results showed that PCV13 was associated with significant reductions in hospital admissions for all-cause pneumonia for some children (21% [95% CI 14-28] in children aged <2 years, 17% [7-27] in those aged 2-4 years) and for empyema (50% [95% CI 22-68] for children age <2 years, 46% [21-64] for 2-4 years, and 37% [13-54] for 5-17 years). All-cause pneumonia was significantly reduced in adults aged 18-39 years (12% (6-17) but not for other adult age groups. The vaccine also reduced admissions for invasive pneumococcal pneumonia and non-invasive pneumococcal or lobar pneumonia in children and adults, indicating herd protection, although the reduction was only significant in some age groups. INTERPRETATION: Only 2 years into the US programme, PCV13 significantly reduced residual invasive and non-invasive pneumococcal hospital admissions in children younger than 5 years, as well as in some adult age groups. Our study design captured the total prevented hospital burden (directly and indirectly by herd protection) and also showed a reversal of the PCV7 era increase in paediatric empyema related to strain replacement. FUNDING: Pfizer.

Accounting for unintended binding events in the analysis of quartz crystal microbalance kinetic data.

Previous methods for analyzing protein-ligand binding events using the quartz crystal microbalance with dissipation monitoring (QCM-D) fail to account for unintended binding that inevitably occurs during surface measurements and obscure kinetic information. In this article, we present a system of differential equations that accounts for both reversible and irreversible unintended interactions. This model is tested on three protein-ligand systems, each of which has different features, to establish the feasibility of using the QCM-D for protein binding analysis. Based on this analysis, we were able to obtain kinetic information for the intended interaction that is consistent with those obtained in literature via bulk-phase methods. In the appendix, we include a method for decoupling these from the intended binding events and extracting relevant affinity information.