Heterogeneous treatment effects in stratified clinical trials with time‐to‐event endpoints

When analyzing clinical trials with a stratified population, homogeneity of treatment effects is a common assumption in survival analysis. However, in the context of recent developments in clinical trial design, which aim to test multiple targeted therapies in corresponding subpopulations simultaneously, the assumption that there is no treatment‐by‐stratum interaction seems inappropriate. It becomes an issue if the expected sample size of the strata makes it unfeasible to analyze the trial arms individually. Alternatively, one might choose as primary aim to prove efficacy of the overall (targeted) treatment strategy. When testing for the overall treatment effect, a violation of the no‐interaction assumption renders it necessary to deviate from standard methods that rely on this assumption. We investigate the performance of different methods for sample size calculation and data analysis under heterogeneous treatment effects. The commonly used sample size formula by Schoenfeld is compared to another formula by Lachin and Foulkes, and to an extension of Schoenfeld's formula allowing for stratification. Beyond the widely used (stratified) Cox model, we explore the lognormal shared frailty model, and a two‐step analysis approach as potential alternatives that attempt to adjust for interstrata heterogeneity. We carry out a simulation study for a trial with three strata and violations of the no‐interaction assumption. The extension of Schoenfeld's formula to heterogeneous strata effects provides the most reliable sample size with respect to desired versus actual power. The two‐step analysis and frailty model prove to be more robust against loss of power caused by heterogeneous treatment effects than the stratified Cox model and should be preferred in such situations.     

A comparison of abundance estimates from extended batch‐marking and Jolly–Seber‐type experiments

Little attention has been paid to the use of multi‐sample batch‐marking studies, as it is generally assumed that an individual's capture history is necessary for fully efficient estimates. However, recently, Huggins et al. ( 2010 ) present a pseudo‐likelihood for a multi‐sample batch‐marking study where they used estimating equations to solve for survival and capture probabilities and then derived abundance estimates using a Horvitz–Thompson‐type estimator. We have developed and maximized the likelihood for batch‐marking studies. We use data simulated from a Jolly–Seber‐type study and convert this to what would have been obtained from an extended batch‐marking study. We compare our abundance estimates obtained from the Crosbie–Manly–Arnason–Schwarz (CMAS) model with those of the extended batch‐marking model to determine the efficiency of collecting and analyzing batch‐marking data. We found that estimates of abundance were similar for all three estimators: CMAS, Huggins, and our likelihood. Gains are made when using unique identifiers and employing the CMAS model in terms of precision; however, the likelihood typically had lower mean square error than the pseudo‐likelihood method of Huggins et al. ( 2010 ). When faced with designing a batch‐marking study, researchers can be confident in obtaining unbiased abundance estimators. Furthermore, they can design studies in order to reduce mean square error by manipulating capture probabilities and sample size.     

Targeted On‐line SPE‐LC‐MS/MS Assay for the Quantitation of 12 Apolipoproteins from Human Blood

Laborious sample pretreatment of biological samples represents the most limiting factor for the translation of targeted proteomics assays from research to clinical routine. An optimized method for the simultaneous quantitation of 12 major apolipoproteins (apos) combining on‐line SPE and fast LC‐MS/MS analysis in 6.5 min total run time was developed, reducing the manual sample pretreatment time of 3 μL serum or plasma by 60%. Within‐run and between‐day imprecisions below 10 and 15% (n = 10) and high recovery rates (94–131%) were obtained applying the high‐throughput setup. High‐quality porcine trypsin was used, which outperformed cost‐effective bovine trypsin regarding digestion efficiency. Comparisons with immunoassays and another LC‐MS/MS assay demonstrated good correlation (Pearson's R: 0.81–0.98). Further, requirements on sample quality concerning sampling, processing, and long‐term storage up to 1 year were investigated revealing significant influences of the applied sampling material and coagulant on quantitation results. Apo profiles of 1339 subjects of the LIFE‐Adult‐Study were associated with lifestyle and physiological parameters as well as establish parameters of lipid metabolism (e.g., triglycerides, cholesterol). Besides gender effects, most significant impact was seen regarding lipid‐lowering medication. In conclusion, this novel highly standardized, high‐throughput targeted proteomics assay utilizes a fast, simultaneous analysis of 12 apos from least sample amounts.     

Site‐specific and endothelial‐mediated dysfunction of the alveolar‐capillary barrier in response to lipopolysaccharides

Infectious agents such as lipopolysaccharides (LPS) challenge the functional properties of the alveolar‐capillary barrier (ACB) in the lung. In this study, we analyse the site‐specific effects of LPS on the ACB and reveal the effects on the individual cell types and the ACB as a functional unit. Monocultures of H441 epithelial cells and co‐cultures of H441 with endothelial cells cultured on Transwells^® were treated with LPS from the apical or basolateral compartment. Barrier properties were analysed by the transepithelial electrical resistance (TEER), by transport assays, and immunostaining and assessment of tight junctional molecules at protein level. Furthermore, pro‐inflammatory cytokines and immune‐modulatory molecules were evaluated by ELISA and semiquantitative real‐time PCR. Liquid chromatography–mass spectrometry‐based proteomics (LS‐MS) was used to identify proteins and effector molecules secreted by endothelial cells in response to LPS. In co‐cultures treated with LPS from the basolateral compartment, we noticed a significant reduction of TEER, increased permeability and induction of pro‐inflammatory cytokines. Conversely, apical treatment did not affect the barrier. No changes were noticed in H441 monoculture upon LPS treatment. However, LPS resulted in an increased expression of pro‐inflammatory cytokines such as IL‐6 in OEC and in turn induced the reduction of TEER and an increase in SP‐A expression in H441 monoculture, and H441/OEC co‐cultures after LPS treatment from basolateral compartment. LS‐MS‐based proteomics revealed factors associated with LPS‐mediated lung injury such as ICAM‐1, VCAM‐1, Angiopoietin 2, complement factors and cathepsin S, emphasizing the role of epithelial–endothelial crosstalk in the ACB in ALI/ARDS.     

Asymptotic Conditional Singular Value Decomposition for High‐Dimensional Genomic Data

Summary High‐dimensional data, such as those obtained from a gene expression microarray or second generation sequencing experiment, consist of a large number of dependent features measured on a small number of samples. One of the key problems in genomics is the identification and estimation of factors that associate with many features simultaneously. Identifying the number of factors is also important for unsupervised statistical analyses such as hierarchical clustering. A conditional factor model is the most common model for many types of genomic data, ranging from gene expression, to single nucleotide polymorphisms, to methylation. Here we show that under a conditional factor model for genomic data with a fixed sample size, the right singular vectors are asymptotically consistent for the unobserved latent factors as the number of features diverges. We also propose a consistent estimator of the dimension of the underlying conditional factor model for a finite fixed sample size and an infinite number of features based on a scaled eigen‐decomposition. We propose a practical approach for selection of the number of factors in real data sets, and we illustrate the utility of these results for capturing batch and other unmodeled effects in a microarray experiment using the dependence kernel approach of Leek and Storey (2008, Proceedings of the National Academy of Sciences of the United States of America 105 , 18718–18723) .     

HS‐SPME‐GC‐FID method for detection and quantification of Bacillus cereus ATCC 10702 mediated 2‐acetyl‐1‐pyrroline

A rapid micro‐scale solid‐phase micro‐extraction (SPME) procedure coupled with gas‐chromatography with flame ionized detector (GC‐FID) was used to extract parts per billion levels of a principle basmati aroma compound “2‐acetyl‐1‐pyrroline” (2‐AP) from bacterial samples. In present investigation, optimization parameters of bacterial incubation period, sample weight, pre‐incubation time, adsorption time, and temperature, precursors and their concentrations has been studied. In the optimized conditions, detection of 2‐AP produced by Bacillus cereus ATCC10702 using only 0.5 g of sample volume was 85 μg/kg. Along with 2‐AP, 15 other compounds produced by B. cereus were also reported out of which 14 were reported for the first time consisting mainly of (E)?2‐hexenal, pentadecanal, 4‐hydroxy‐2‐butanone, n‐hexanal, 2–6‐nonadienal, 3‐methoxy‐2(5H) furanone and 2‐acetyl‐1‐pyridine and octanal. High recovery of 2‐AP (87 %) from very less amount of B. cereus samples was observed. The method is reproducible fast and can be used for detection of 2‐AP production by B. cereus. © 2014 American Institute of Chemical Engineers Biotechnol. Prog., 30:1356–1363, 2014     

Statistical Inference for a Two‐Stage Outcome‐Dependent Sampling Design with a Continuous Outcome

Summary The two‐stage case–control design has been widely used in epidemiology studies for its cost‐effectiveness and improvement of the study efficiency ( White, 1982 , American Journal of Epidemiology 115, 119–128; Breslow and Cain, 1988 , Biometrika 75, 11–20). The evolution of modern biomedical studies has called for cost‐effective designs with a continuous outcome and exposure variables. In this article, we propose a new two‐stage outcome‐dependent sampling (ODS) scheme with a continuous outcome variable, where both the first‐stage data and the second‐stage data are from ODS schemes. We develop a semiparametric empirical likelihood estimation for inference about the regression parameters in the proposed design. Simulation studies were conducted to investigate the small‐sample behavior of the proposed estimator. We demonstrate that, for a given statistical power, the proposed design will require a substantially smaller sample size than the alternative designs. The proposed method is illustrated with an environmental health study conducted at National Institutes of Health.     

Culture conditions and sample preparation methods affect spectrum quality and reproducibility during profiling of Staphylococcus aureus with matrix‐assisted laser desorption/ionization time‐of‐flight mass spectrometry

Matrix‐assisted laser desorption/ionization time‐of‐flight mass spectrometry (MALDI‐TOF MS) has emerged as a promising tool to rapidly characterize Staphylococcus aureus. Different protocols have been employed, but effects of experimental factors, such as culture condition and sample preparation, on spectrum quality and reproducibility have not been rigorously examined. We applied MALDI‐TOF MS to characterize a model system consisting of five methicillin‐sensitive (MSSA) and five methicillin‐resistant S. aureus isolates (MRSA) under two culture conditions (agar and broth) and using two sample preparation methods [intact cell method and protein extraction method (PEM)]. The effects of these treatments on spectrum quality and reproducibility were quantified. PEM facilitated increases in the number of peaks and mass range width. Broth cultures further improved spectrum quality in terms of increasing the number of peaks. In addition, PEM increased reproducibility in samples prepared using identical culture conditions. MALDI imaging data suggested that the improvement in reproducibility may result from a more homogeneous distribution of sample associated with the broth/PEM treatment. Broth/PEM treatment also yielded the highest rate (96%) of correct classification for MRSA. Taken together, these results suggest that broth/PEM maximizes the performance of MALDI‐TOF MS to characterize S. aureus.

Significance and Impact of the Study

Two culture conditions (agar or broth) and two sample preparation methods (intact cell or protein extraction) were evaluated for their effects on profiling of Staphylococcus aureus using matrix‐assisted laser desorption/ionization time‐of‐flight mass spectrometry (MALDI‐TOF MS). Results indicated that MALDI‐enabled profiling of S. aureus is most effective when cultures are grown in broth and processed using a protein extraction‐based approach. These findings should enhance future efforts to maximize the performance of this approach to characterize strains of S. aureus.     

ELF magnetic fields in electric and gasoline‐powered vehicles

We conducted a pilot study to assess magnetic field levels in electric compared to gasoline‐powered vehicles, and established a methodology that would provide valid data for further assessments. The sample consisted of 14 vehicles, all manufactured between January 2000 and April 2009; 6 were gasoline‐powered vehicles and 8 were electric vehicles of various types. Of the eight models available, three were represented by a gasoline‐powered vehicle and at least one electric vehicle, enabling intra‐model comparisons. Vehicles were driven over a 16.3 km test route. Each vehicle was equipped with six EMDEX Lite broadband meters with a 40–1,000 Hz bandwidth programmed to sample every 4 s. Standard statistical testing was based on the fact that the autocorrelation statistic damped quickly with time. For seven electric cars, the geometric mean (GM) of all measurements (N = 18,318) was 0.095 µT with a geometric standard deviation (GSD) of 2.66, compared to 0.051 µT (N = 9,301; GSD = 2.11) for four gasoline‐powered cars (P < 0.0001). Using the data from a previous exposure assessment of residential exposure in eight geographic regions in the United States as a basis for comparison (N = 218), the broadband magnetic fields in electric vehicles covered the same range as personal exposure levels recorded in that study. All fields measured in all vehicles were much less than the exposure limits published by the International Commission on Non‐Ionizing Radiation Protection (ICNIRP) and the Institute of Electrical and Electronics Engineers (IEEE). Future studies should include larger sample sizes representative of a greater cross‐section of electric‐type vehicles. Bioelectromagnetics 34:156–161, 2013. © 2012 Wiley Periodicals, Inc.     

iPSC‐derived mesenchymal stem cells exert SCF‐dependent recovery of cigarette smoke‐induced apoptosis/proliferation imbalance in airway cells

Mesenchymal stem cells (MSCs) have emerged as a potential cell‐based therapy for pulmonary emphysema in animal models. Our previous study demonstrated that human induced pluripotent stem cell–derived MSCs (iPSC‐MSCs) were superior over bone marrow–derived MSCs (BM‐MSCs) in attenuating cigarette smoke (CS)‐induced airspace enlargement possibly through mitochondrial transfer. This study further investigated the effects of iPSC‐MSCs on inflammation, apoptosis, and proliferation in a CS‐exposed rat model and examined the effects of the secreted paracrine factor from MSCs as another possible mechanism in an in vitro model of bronchial epithelial cells. Rats were exposed to 4% CS for 1 hr daily for 56 days. At days 29 and 43, human iPSC‐MSCs or BM‐MSCs were administered intravenously. We observed significant attenuation of CS‐induced elevation of circulating 8‐isoprostane and cytokine‐induced neutrophil chemoattractant‐1 after iPSC‐MSC treatment. In line, a superior capacity of iPSC‐MSCs was also observed in ameliorating CS‐induced infiltration of macrophages and neutrophils and apoptosis/proliferation imbalance in lung sections over BM‐MSCs. In support, the conditioned medium (CdM) from iPSC‐MSCs ameliorated CS medium‐induced apoptosis/proliferation imbalance of bronchial epithelial cells in vitro. Conditioned medium from iPSC‐MSCs contained higher level of stem cell factor (SCF) than that from BM‐MSCs. Deprivation of SCF from iPSC‐MSC‐derived CdM led to a reduction in anti‐apoptotic and pro‐proliferative capacity. Taken together, our data suggest that iPSC‐MSCs may possess anti‐apoptotic/pro‐proliferative capacity in the in vivo and in vitro models of CS‐induced airway cell injury partly through paracrine secretion of SCF.     

2‐methoxyestradiol inhibits atorvastatin‐induced rounding of human vascular smooth muscle cells

The cardiovascular benefits of statins, including atorvastatin (ATV), have been reported to be gender‐dependent, but the underlying mechanism is unclear. In this study we examine whether estrogen and its metabolite, 2‐methoxyestradiol (2ME), affect the rounding response of human vascular smooth muscle cells (SMCs) induced by ATV. Twenty‐four hour treatment with ATV (10–100 µM) induced rounding of cultured human SMCs. Addition of 2ME (1–20 µM), but not 17β‐estradiol, for 2 h induced re‐spreading of rounded cells. Our further studies showed that the effects of 2ME were mimicked by microtubule‐disrupting drugs and inhibited by taxol. Inhibition of RhoA and ROCK (Rho‐kinase) by C3‐toxin and H‐1152, respectively, blocked 2ME effects. 2ME effects were also blocked by treatment with either actin‐interfering drugs, such as cytochalasin D and jasplakinolide, or myosin inhibitor blebbistatin. ML‐7 and ‐9, the inhibitors for myosin light chain kinase, inhibited 2ME effect as well. ATV treatment induced a decrease of F‐actin content and Thr18/Ser19 dual phosphorylation of myosin regulatory light chain (MRLC), which was rescued by 2ME or mevalonate. The rescue effects of 2ME on F‐actin content and MRLC dual phosphorylation were abolished by taxol or H‐1152. In addition, kinesin Eg5 inhibitor monastrol and dynein inhibitor erythro‐9‐3‐(2‐hydroxynonyl) adenine (EHNA) significantly blocked 2ME effects. Finally, our results revealed that 2ME inhibited the migration of SMCs induced by ATV (0.1 µM) in wound healing assay and Boyden chamber assay. In summary, our data show that 2ME, but not estrogen, inhibits ATV‐induced rounding of human SMCs through induction of microtubule disassembly and activation of the Rho‐ROCK‐actinomyosin pathway. J. Cell. Physiol. 222: 556–564, 2010. © 2009 Wiley‐Liss, Inc.     

SIMLR: A Tool for Large‐Scale Genomic Analyses by Multi‐Kernel Learning

SIMLR (S ingle‐cell I nterpretation via M ulti‐kernel L eaR ning), an open‐source tool that implements a novel framework to learn a sample‐to‐sample similarity measure from expression data observed for heterogenous samples, is presented here. SIMLR can be effectively used to perform tasks such as dimension reduction, clustering, and visualization of heterogeneous populations of samples. SIMLR was benchmarked against state‐of‐the‐art methods for these three tasks on several public datasets, showing it to be scalable and capable of greatly improving clustering performance, as well as providing valuable insights by making the data more interpretable via better a visualization. SIMLR is available on https://github.com/BatzoglouLabSU/SIMLR GitHub in both R and MATLAB implementations. Furthermore, it is also available as an R package on http://bioconductor.org     

Non‐additive effects of density‐dependent and density‐independent factors on brown trout vital rates

Interactions between density‐dependent and density‐independent processes can lead to variation in both growth and survival rates. Detecting such effects, however, will often require sampling on an individual level and at the appropriate spatial and temporal scale. This study documents substantial variation in survival and growth of stream‐dwelling brown trout Salmo trutta from a small Norwegian stream. The data is based on seasonal capture–recaptures of individually marked trout on fixed stations during eight years. The fish were small‐sized, rarely reaching sizes larger than 20 cm and ages older than seven years. Density varied between 0.2–0.8 fish m^?2. Variation in survival and recapture probabilities was analysed using program MARK. Apparent survival (the probability of being alive and present within the study area) generally decreased with increasing trout density and increasing drought level (measured as lowest observed water flow) during both winter and summer. Further, there was a significant interaction effect between density and water flow, indicating that density‐dependent effects on survival predominated when environmental conditions were benign (no drought), while density‐independent processes were most important under harsh environmental conditions (drought). Observed length‐at‐age during autumn indicated a more or less linear growth trajectory throughout life, and no effect of density, water flow or temperature was found. However, using the individual‐based capture–recapture data to estimated specific growth rate, significant positive effects of water flow and temperature and a negative effect of density were identified. Thus, the capture–recapture data suggest a strong potential for population regulation at the rather low densities found in this stream, and regulation may occur both through effects on survival and growth.     

Hazard ratio estimation for two‐sample case under interval‐censored failure time data

This paper discusses two‐sample comparison in the case of interval‐censored failure time data. For the problem, one common approach is to employ some nonparametric test procedures, which usually give some p‐values but not a direct or exact quantitative measure of the survival or treatment difference of interest. In particular, these procedures cannot provide a hazard ratio estimate, which is commonly used to measure the difference between the two treatments or samples. For interval‐censored data, a few nonparametric test procedures have been developed, but it does not seem to exist as a procedure for hazard ratio estimation. Corresponding to this, we present two procedures for nonparametric estimation of the hazard ratio of the two samples for interval‐censored data situations. They are generalizations of the corresponding procedures for right‐censored failure time data. An extensive simulation study is conducted to evaluate the performance of the two procedures and indicates that they work reasonably well in practice. For illustration, they are applied to a set of interval‐censored data arising from a breast cancer study.     

Direct negative density‐dependence in a pond‐breeding frog population

Understanding population dynamics is critical for the management of animal populations. Comparatively little is known about the relative importance of endogenous (i.e. density‐dependent) and exogenous (i.e. density‐independent) factors on the population dynamics of amphibians with complex life cycles. We examined the potential effects of density‐dependent and ‐independent (i.e. climatic) factors on population dynamics by analyzing a 15‐yr time series data of the agile frog Rana dalmatina population from Târnava Mare Valley, Romania. We used two statistical models: 1) the partial rate correlation function to identify the feedback structure and the potential time lags in the time series data and 2) a Gompertz state‐space model to simultaneously investigate direct and delayed density dependence as well as climatic effects on population growth rate. We found evidence for direct negative density dependence, whereas delayed density dependence and climate did not show a strong influence on population growth rate. Here we demonstrated that direct density dependence rather than delayed density dependence or climate determined the dynamics of our study population. Our results confirm the findings of many experimental studies and suggest that density dependence may buffer amphibian populations against environmental stress. Consequently, it may not be easy to scale up from individual‐level effects to population‐level effects.     

Zero‐inflated spatio‐temporal models for disease mapping

In this paper, our aim is to analyze geographical and temporal variability of disease incidence when spatio‐temporal count data have excess zeros. To that end, we consider random effects in zero‐inflated Poisson models to investigate geographical and temporal patterns of disease incidence. Spatio‐temporal models that employ conditionally autoregressive smoothing across the spatial dimension and B‐spline smoothing over the temporal dimension are proposed. The analysis of these complex models is computationally difficult from the frequentist perspective. On the other hand, the advent of the Markov chain Monte Carlo algorithm has made the Bayesian analysis of complex models computationally convenient. Recently developed data cloning method provides a frequentist approach to mixed models that is also computationally convenient. We propose to use data cloning, which yields to maximum likelihood estimation, to conduct frequentist analysis of zero‐inflated spatio‐temporal modeling of disease incidence. One of the advantages of the data cloning approach is that the prediction and corresponding standard errors (or prediction intervals) of smoothing disease incidence over space and time is easily obtained. We illustrate our approach using a real dataset of monthly children asthma visits to hospital in the province of Manitoba, Canada, during the period April 2006 to March 2010. Performance of our approach is also evaluated through a simulation study.     

Effects of extremely low‐frequency magnetic field exposure on cognitive functions: results of a meta‐analysis

There is extensive literature on possible effects of extremely low‐frequency magnetic fields (ELF‐MFs) on human cognitive functions. However, due to methodological deficits (e.g., low statistical power, small sample sizes) findings have been inconsistent. In the current study we try to overcome these problems by carrying out a meta‐analysis. Literature research revealed 17 studies. Nine of these were included in the meta‐analysis because they fulfilled minimum requirements (e.g., at least single‐blind experimental study design and documentation of means and standard deviation of the dependent variables). All of the studies used a 50 Hz magnetic field exposure. Small but significant effect sizes could be detected in two cognitive dimensions: in the hard level of visual duration discrimination, task‐exposed subjects performed better than controls; at the intermediate level however, exposed subjects performed worse. Additionally, a significant improvement of correct responses was observed in the dimension of “flexibility” under exposure. However, due to the small number of studies per performance dimensions and the resulting instability of estimates, these findings have to be treated with extreme caution. Taken together, the results of the meta‐analysis provide little evidence that ELF‐MFs have any effects on cognitive functions. Bioelectromagnetics 31:173–179, 2010. © 2009 Wiley‐Liss, Inc.     

Double Inverse‐Weighted Estimation of Cumulative Treatment Effects Under Nonproportional Hazards and Dependent Censoring

Summary In medical studies of time‐to‐event data, nonproportional hazards and dependent censoring are very common issues when estimating the treatment effect. A traditional method for dealing with time‐dependent treatment effects is to model the time‐dependence parametrically. Limitations of this approach include the difficulty to verify the correctness of the specified functional form and the fact that, in the presence of a treatment effect that varies over time, investigators are usually interested in the cumulative as opposed to instantaneous treatment effect. In many applications, censoring time is not independent of event time. Therefore, we propose methods for estimating the cumulative treatment effect in the presence of nonproportional hazards and dependent censoring. Three measures are proposed, including the ratio of cumulative hazards, relative risk, and difference in restricted mean lifetime. For each measure, we propose a double inverse‐weighted estimator, constructed by first using inverse probability of treatment weighting (IPTW) to balance the treatment‐specific covariate distributions, then using inverse probability of censoring weighting (IPCW) to overcome the dependent censoring. The proposed estimators are shown to be consistent and asymptotically normal. We study their finite‐sample properties through simulation. The proposed methods are used to compare kidney wait‐list mortality by race.     

A novel endo‐β‐N‐acetylglucosaminidase releases specific N‐glycans depending on different reaction conditions

Milk glycoproteins are involved in different functions and contribute to different cellular processes, including adhesion and signaling, and shape the development of the infant microbiome. Methods have been developed to study the complexities of milk protein glycosylation and understand the role of N‐glycans in protein functionality. Endo‐β‐N‐acetylglucosaminidase (EndoBI‐1) isolated from Bifidobacterium longum subsp. infantis ATCC 15697 is a recently isolated heat‐stable enzyme that cleaves the N‐N′‐diacetyl chitobiose moiety found in the N‐glycan core. The effects of different processing conditions (pH, temperature, reaction time, and enzyme/protein ratio) were evaluated for their ability to change EndoBI‐1 activity on bovine colostrum whey glycoproteins using advanced mass spectrometry. This study shows that EndoBI‐1 is able to cleave a high diversity of N‐glycan structures. Nano‐LC‐Chip–Q‐TOF MS data also revealed that different reaction conditions resulted in different N‐glycan compositions released, thus modifying the relative abundance of N‐glycan types. In general, more sialylated N‐glycans were released at lower temperatures and pH values. These results demonstrated that EndoBI‐1 is able to release a wide variety of N‐glycans, whose compositions can be selectively manipulated using different processing conditions. © 2015 American Institute of Chemical Engineers Biotechnol. Prog., 31:1323–1330, 2015     

On Estimating the Relationship between Longitudinal Measurements and Time‐to‐Event Data Using a Simple Two‐Stage Procedure

Summary Ye, Lin, and Taylor (2008, Biometrics 64 , 1238–1246) proposed a joint model for longitudinal measurements and time‐to‐event data in which the longitudinal measurements are modeled with a semiparametric mixed model to allow for the complex patterns in longitudinal biomarker data. They proposed a two‐stage regression calibration approach that is simpler to implement than a joint modeling approach. In the first stage of their approach, the mixed model is fit without regard to the time‐to‐event data. In the second stage, the posterior expectation of an individual's random effects from the mixed‐model are included as covariates in a Cox model. Although Ye et al. (2008) acknowledged that their regression calibration approach may cause a bias due to the problem of informative dropout and measurement error, they argued that the bias is small relative to alternative methods. In this article, we show that this bias may be substantial. We show how to alleviate much of this bias with an alternative regression calibration approach that can be applied for both discrete and continuous time‐to‐event data. Through simulations, the proposed approach is shown to have substantially less bias than the regression calibration approach proposed by Ye et al. (2008) . In agreement with the methodology proposed by Ye et al. (2008) , an advantage of our proposed approach over joint modeling is that it can be implemented with standard statistical software and does not require complex estimation techniques.