Conditional score approaches to errors-in-variables competing risks data in discrete time.

Analysis of competing risks data has been an important topic in survival analysis due to the need to account for the dependence among the competing events. Also, event times are often recorded on discrete time scales, rendering the models tailored for discrete-time nature useful in the practice of survival analysis. In this work, we focus on regression analysis with discrete-time competing risks data, and consider the errors-in-variables issue where the covariates are prone to measurement errors. Viewing the true covariate value as a parameter, we develop the conditional score methods for various discrete-time competing risks models, including the cause-specific and subdistribution hazards models that have been popular in competing risks data analysis. The proposed estimators can be implemented by efficient computation algorithms, and the associated large sample theories can be simply obtained. Simulation results show satisfactory finite sample performances, and the application with the competing risks data from the scleroderma lung study reveals the utility of the proposed methods.

The angiogenesis-modulating effects of coumarin-derivatives.

Coumarin is a natural compound that is rich in plants. Coumarin and its derivates were reported to have many biological activities, such as anti-bacterial, anti-tumor, and anti-coagulation. In this study, we examined the angiogenic modulating activities of six previously synthesized coumarin derivatives (Compound #1-#6) in zebrafish embryos and further confirmed them in a chick model. According to the survival rate in a zebrafish model, Compound #1 (100 %), #2 (82.5-100 %), and #4 (100 %) showed much less toxicity than Compound #3 (19.2-100 %), #5 (0-100 %), and #6 (0-100 %). Using a green blood vessel fluorescent transgenic fish Tg(fli1:egfp) to record the angiogenesis-modulating effects of Compound #1, #2, and #4, we found that Compound #2 had the highest effects in interfering intersegmental vessel growth, subintestinal vein growth, and caudal vein plexus remodeling. Chick chorioallantoic membrane (CAM) assay also showed that Compound #2 exposure led to a reduction of blood vessel growth. Real-time PCR experiments revealed that Compound #2 significantly changed the expression of vascular growth-related genes flt1, cdh5, and nrp1a in zebrafish. Based on our data from zebrafish and chick models, a new coumarin-derivative (Compound #2) possesses anti-angiogenic activity with low toxicity, but further investigation in mammal models is asked to confirm our findings.

Analyzing recurrent and nonrecurrent terminal events data in discrete time.

Joint analysis of recurrent and nonrecurrent terminal events has attracted substantial attention in literature. However, there lacks formal methodology for such analysis when the event time data are on discrete scales, even though some modeling and inference strategies have been developed for discrete-time survival analysis. We propose a discrete-time joint modeling approach for the analysis of recurrent and terminal events where the two types of events may be correlated with each other. The proposed joint modeling assumes a shared frailty to account for the dependence among recurrent events and between the recurrent and the terminal terminal events. Also, the joint modeling allows for time-dependent covariates and rich families of transformation models for the recurrent and terminal events. A major advantage of our approach is that it does not assume a distribution for the frailty, nor does it assume a Poisson process for the analysis of the recurrent event. The utility of the proposed analysis is illustrated by simulation studies and two real applications, where the application to the biochemists' rank promotion data jointly analyzes the biochemists' citation numbers and times to rank promotion, and the application to the scleroderma lung study data jointly analyzes the adverse events and off-drug time among patients with the symptomatic scleroderma-related interstitial lung disease.

Discrete-time survival data with longitudinal covariates.

Survival analysis has been conventionally performed on a continuous time scale. In practice, the survival time is often recorded or handled on a discrete scale; when this is the case, the discrete-time survival analysis would provide analysis results more relevant to the actual data scale. Besides, data on time-dependent covariates in the survival analysis are usually collected through intermittent follow-ups, resulting in the missing and mismeasured covariate data. In this work, we propose the sufficient discrete hazard (SDH) approach to discrete-time survival analysis with longitudinal covariates that are subject to missingness and mismeasurement. The SDH method employs the conditional score idea available for dealing with mismeasured covariates, and the penalized least squares for estimating the missing covariate value using the regression spline basis. The SDH method is developed for the single event analysis with the logistic discrete hazard model, and for the competing risks analysis with the multinomial logit model. Simulation results revel good finite-sample performances of the proposed estimator and the associated asymptotic theory. The proposed SDH method is applied to the scleroderma lung study data, where the time to medication withdrawal and time to death were recorded discretely in months, for illustration.

Joint analysis of panel count and interval-censored data using distribution-free frailty analysis.

We propose a joint analysis of recurrent and nonrecurrent event data subject to general types of interval censoring. The proposed analysis allows for general semiparametric models, including the Box-Cox transformation and inverse Box-Cox transformation models for the recurrent and nonrecurrent events, respectively. A frailty variable is used to account for the potential dependence between the recurrent and nonrecurrent event processes, while leaving the distribution of the frailty unspecified. We apply the pseudolikelihood for interval-censored recurrent event data, usually termed as panel count data, and the sufficient likelihood for interval-censored nonrecurrent event data by conditioning on the sufficient statistic for the frailty and using the working assumption of independence over examination times. Large sample theory and a computation procedure for the proposed analysis are established. We illustrate the proposed methodology by a joint analysis of the numbers of occurrences of basal cell carcinoma over time and time to the first recurrence of squamous cell carcinoma based on a skin cancer dataset, as well as a joint analysis of the numbers of adverse events and time to premature withdrawal from study medication based on a scleroderma lung disease dataset.

Sample size determination for semiparametric analysis of current status data.

Semiparametric transformation models, which include the Cox proportional hazards and proportional odds models as special cases, are popular in current practice of survival analysis owing to that, in contrast to parametric models, no assumption on the baseline distribution is required. Although sample size calculations for semiparametric survival analysis with right-censored data are available, no such calculation exits in literature for semiparametric analysis with current status data, where only an examination time and whether the event occurs prior to the examination are observable. We develop sample size calculation for semiparametric two-group comparison or regression analysis with current status data. The proposed formula can be readily implemented with given effect size, power level, covariate group proportions, covariate-specific examination (censoring) time distributions, and proportions of events observed in the control group at a few knot points in the study period. Simulation results show that the proposed sample size calculation is adequate in the sense that it leads to studies with empirical power very close to the planned power level. We illustrate practical applications of the proposal through examples from an animal tumorigenicity study and a cross-sectional survey on osteoporosis status in the elderly.

Embryonic exposure to 4-methylimidazole leads to zebrafish myofibril misalignment.

4-methylimidazole (4-MI) is an imidazole-derived organic chemical compound that can be used as a raw material in the manufacture of diverse chemicals and has been identified as an ingredient of caramel color in soybean sauce, beers, and other soft drinks. The aim of the present study was to investigate the teratogenic effects of 4-MI during zebrafish embryogenesis. Zebrafish embryos were treated with different dosages of 4-MI (0-120 mM) for different exposure durations (12-60 hours). The percentages of embryos with malformed phenotypes increased as the exposure dosages and duration time of 4-MI increased. We also used immunofluorescence and transmission microscopy to evaluate the subtle changes in the myofibril alignment and ultrastructure of muscle organization. Our data showed that 4-MI treatment disturbs muscle fiber alignment. Electron microscopy data indicated that Z-lines were undetectable in the 4-MI-treated embryos. Although the thick and thin filaments were visible, they were all disorganized. In addition, zebrafish embryos treated by 4-MI exhibited aberrant expression of 2 muscle-specific genes, myod and myogenin. Taken together, we concluded that early exposure to 4-MI affects zebrafish myogenesis, especially in myofibril alignment.

Pseudo and conditional score approach to joint analysis of current count and current status data.

We develop a joint analysis approach for recurrent and nonrecurrent event processes subject to case I interval censorship, which are also known in literature as current count and current status data, respectively. We use a shared frailty to link the recurrent and nonrecurrent event processes, while leaving the distribution of the frailty fully unspecified. Conditional on the frailty, the recurrent event is assumed to follow a nonhomogeneous Poisson process, and the mean function of the recurrent event and the survival function of the nonrecurrent event are assumed to follow some general form of semiparametric transformation models. Estimation of the models is based on the pseudo-likelihood and the conditional score techniques. The resulting estimators for the regression parameters and the unspecified baseline functions are shown to be consistent with rates of square and cubic roots of the sample size, respectively. Asymptotic normality with closed-form asymptotic variance is derived for the estimator of the regression parameters. We apply the proposed method to a fracture-osteoporosis survey data to identify risk factors jointly for fracture and osteoporosis in elders, while accounting for association between the two events within a subject.

Evaluation of the teratogenic effects of three traditional Chinese medicines, Si Jun Zi Tang, Liu Jun Zi Tang and Shenling Baizhu San, during zebrafish pronephros development.

The aim of this study was to evaluate the teratogenic effects of three common Chinese medical prescriptions, Si Jun Zi Tang (SJZT), Liu Jun Zi Tang (LJZT) and Shenling Baizhu San (SLBS), during zebrafish pronephros development. We used the transgenic zebrafish line Tg(wt1b:EGFP) to assess the teratogenic effects using 12 different protocols, which comprised combinations of 4 doses (0, 25, 250, 1,250 ng/mL) and 3 exposure methods [methods I, 12-36 hours post fertilization (hpf), II, 24-48 hpf, and III, 24-36 hpf]. As a result, few defects in the kidneys were observed in the embryos exposed to 25 ng/mL of each medical prescription. The percentage of kidney malformation phenotypes increased as the exposure concentrations increased (25 ng/mL, 0-10%; 250 ng/mL, 0-60%; 1,250 ng/mL, 80-100%). Immunohistochemistry for α6F, which is a basolateral and renal tubular differentiation marker, revealed no obvious defective phenotypes in either SJZT- or LJZT-treated embryos, indicating that these Chinese medical prescriptions had minimal adverse effects on the pronephric duct. However, SLBS-treated embryos displayed a defective phenotype in the pronephric duct. According to these findings, we suggest (1) that the Chinese medical prescriptions induced kidney malformation phenotypes that are dose dependent and (2) that the embryonic zebrafish kidney was more sensitive to SLBS than SJZT and LJZT.

Nephroprotective role of resveratrol and ursolic Acid in aristolochic Acid intoxicated zebrafish.

The nephrotoxicity of aristolochic acid (AA) is well known, but information regarding the attenuation of AA-induced toxicity is limited. The aim of the present study was to study the nephroprotective effects of resveratrol (Resv) and ursolic acid (UA) in a zebrafish model. We used two transgenic lines, Tg(wt1b:EGFP) and Tg(gata1:DsRed), to evaluate the nephroprotective effects of Resv and UA by recording subtle changes in the kidney and red blood cell circulation. Our results demonstrated that both Resv and UA treatment can attenuate AA-induced kidney malformations and improve blood circulation. Glomerular filtration rate assays revealed that both Resv and UA treatment can restore renal function (100% for Mock; 56.1% ± 17.3% for AA-treated; 80.2% ± 11.3% for Resv+AA; and 83.1% ± 8.1% for UA+AA, n = 15). Furthermore, real-time RT-PCR experiments showed that pre-treatment with either Resv or UA suppresses expression of pro-inflammatory genes. In conclusion, our findings reveal that AA-induced nephrotoxicities can be attenuated by pre-treatment with either Resv or UA. Therefore, we believe that zebrafish represent an efficient model for screening AA-protective natural compounds.

Perturbation of cytosolic calcium by 2-aminoethoxydiphenyl borate and caffeine affects zebrafish myofibril alignment.

The objective of the current study was to investigate the effects of Ca(2+) levels on myofibril alignment during zebrafish embryogenesis. To investigate how altered cytoplasmic Ca(2+) levels affect myofibril alignment, we exposed zebrafish embryos to 2-aminothoxyldiphenyl borate (2-APB; an inositol 1,4,5-trisphosphate receptor inhibitor that reduces cytosolic Ca(2+) levels) and caffeine (a ryanodine receptor activator that enhances cytosolic Ca(2+) levels). The results demonstrated that the most evident changes in zebrafish embryos treated with 2-APB were shorter body length, curved trunk and malformed somite boundary. In contrast, such malformed phenotypes were evident neither in untreated controls nor in caffeine-treated embryos. Subtle morphological changes, including changes in muscle fibers, F-actin and ultrastructures were easily observed by staining with specific monoclonal antibodies (F59 and α-laminin), fluorescent probes (phalloidin) and by transmission electron microscopy. Our data suggested that: (1) the exposure to 2-APB and/or caffeine led to myofibril misalignment; (2) 2-APB-treated embryos displayed split and short myofibril phenotypes, whereas muscle fibers from caffeine-treated embryos were twisted and wavy; and (3) zebrafish embryos co-exposed to 2-APB and caffeine resulted in normal myofibril alignment. In conclusion, we proposed that cytosolic Ca(2+) is important for myogenesis, particularly for myofibril alignment.

A functional inference for multivariate current status data with mismeasured covariate.

Covariate measurement error problems have been recently studied for current status failure time data but not yet for multivariate current status data. Motivated by the three-hypers dataset from a health survey study, where the failure times for three-hypers (hyperglycemia, hypertension, hyperlipidemia) are subject to current status censoring and the covariate self-reported body mass index may be subject to measurement error, we propose a functional inference method under the proportional odds model for multivariate current status data with mismeasured covariates. The new proposal utilizes the working independence strategy to handle correlated current status observations from the same subject, as well as the conditional score approach to handle mismeasured covariate without specifying the covariate distribution. The asymptotic theory, together with a stable computation procedure combining the Newton-Raphson and self-consistency algorithms, is established for the proposed estimation method. We evaluate the method through simulation studies and illustrate it with three-hypers data.

Protective Role of Comfrey Leave Extracts on UV-induced Zebrafish Fin Damage.

In zebrafish, UV exposure leads to fin malformation phenotypes including fin reduction or absence. The present study evaluated UV-protective activities of comfrey leaves extracts in a zebrafish model by recording fin morphological changes. Chemopreventive effects of comfrey leave extracts were evaluated using Kaplan-Meier analysis and Cox proportional hazards regression. The results showed that (1) the mean times of return to normal fin in the UV+comfrey (50 and 100 ppm) groups were 3.43 and 2.86 days and were quicker compared with that in the UV only group (4.21 days); (2) zebrafish fins in the UV+comfrey (50 and 100 ppm) groups were 2.05 and 3.25 times more likely to return to normal than those in the UV only group; and (3) comfrey leave extracts had UV-absorbance abilities and significantly reduced ROS production in UV-exposed zebrafish embryos, which may attenuate UV-mediated apoptosis. In conclusion, comfrey leaves extracts may have the potential to be developed as UV-protective agents to protect zebrafish embryos from UV-induced damage.

Modeling pegylated liposomal doxorubicin-induced hand-foot syndrome and intestinal mucositis in zebrafish.

Pegylated liposomal doxorubicin (PLD) has been widely used to treat cancer. The adverse effects of PLD noted in clinical practice, especially hand-foot syndrome (HFS), are regarded as unique, and the management methods for them remain limited. This study was aimed at developing a feasible experimental model for translational medicine to solve this clinical issue by using skin fluorescent transgenic zebrafish. We established an optimal protocol for the administration of Lipo-Dox™, a PLD in current clinical use, to the Tg(k18:dsred) zebrafish line expressing red fluorescence in keratinocytes. We made use of bodyweight, survival rate, gross observation, flssuorescent microscopic assessment, and pathological examination of the zebrafish to assess this model. The consecutive administration protocol of PLD resulted in growth retardation of the zebrafish embryo and survival impairment, indicating establishment of a significant toxicity. We observed fin necrosis and keratinocyte dissociation phenotypes in the PLD-treated fish after consecutive administration. The skin toxicity induced by the Lipo-Dox injection was subsequently reversible, which might be compatible with a clinical course of skin recovery after discontinuation of Lipo-Dox administration. Furthermore, we found that the number of intestinal goblet cells, an important marker of intestinal inflammation, in the Lipo-Dox-injected zebrafish was markedly increased, accompanied by impaired mucosal integrity. The intestinal inflammation induced by Lipo-Dox resembled the intestinal mucositis the clinical patients suffered from after the administration of PLD. In conclusion, we established a zebrafish model for PLD-induced HFS. The intestinal mucositis simultaneously noted in the PLD-treated zebrafish validated the similarity of clinical courses after administration of PLD. This model is easily assessable, efficient, and worthy for use in developing a new therapeutic protocol for prevention or treatment of HFS as well as intestinal mucositis. Further clinical investigations to validate the correlation between human and zebrafish data are warranted.

Overdose of D-serine Induces Movement Disorder and Neuromuscular Changes of Zebrafish Larvae.

D-serine is a well-known activator of N-methyl-D-aspartate receptors; however, little is known about the teratogenic effects of D-serine overdose during early embryonic development. Here, we used zebrafish as a model to test toxicity and teratogenicity, since they have transparent eggs, making the organogenesis of zebrafish embryos easier to be observed. After D-serine injection (100-1000 ppm), the most evident defective phenotypes were bent trunk phenotypes, including malformed somite boundary, twisted body axis and shorter body length. As the injection dosages increased, the rates of embryos with bent trunk phenotypes decreased (0% for 0 ppm, n=573; 59.9~84.3% for 100-1000 ppm of D-serine, n=383-451). In addition, D-serine-injected embryos exhibited significantly reduced the frequencies of spontaneous in-chorion contraction (21.7 for 0 ppm vs. 18.3-0.9 for 100-1000 ppm D-serine, n=30) in comparison with mock-treated controls (0 ppm). Subtle changes are easily observed by staining with specific monoclonal antibodies F59, Znp1, Zn5 and α-bungarotoxin to detect morphological changes in muscle fibers, primary motor axons, secondary motor axon projections and neuromuscular junctions, respectively. Our data show that overdose of D-serine leads to misalignment of muscle fibers and motor neuron defects, especially secondary motor neuron axonal growth defects.

Semiparametric analysis of incomplete current status outcome data under transformation models.

This work, motivated by an osteoporosis survey study, considers regression analysis with incompletely observed current status data. Here the current status data, including an examination time and an indicator for whether or not the event of interest has occurred by the examination time, is not observed for all subjects. Instead, a surrogate outcome subject to misclassification of the current status is available for all subjects. We focus on semiparametric regression under transformation models, including the proportional hazards and proportional odds models as special cases. Under the missing at random mechanism where the missingness of the current status outcome can depend only on the observed surrogate outcome and covariates, we propose an approach of validation likelihood based on the likelihood from the validation subsample where the data are fully observed, with adjustments of the probability of observing the current status outcome, as well as the distribution of the surrogate outcome in the validation subsample. We propose an efficient computation algorithm for implementation, and derive consistency and asymptotic normality for inference with the proposed estimator. The application to the osteoporosis survey data and simulations reveal that the validation likelihood performs well; it removes the bias from the "complete case" analysis discarding subjects with missing data, and achieves higher efficiency than the inverse probability weighting analysis.

Evaluation of the anti-inflammatory effect of chalcone and chalcone analogues in a zebrafish model.

The aim of this study was to investigate novel chalcones with potent anti-inflammatory activities in vivo. Chalcone and two chalcone analogues (compound 5 and 9) were evaluated using a caudal fin-wounded transgenic zebrafish line "Tg(mpx:gfp)" to visualize the effect of neutrophil recruitment dynamically. Results showed that treatment with compound 9 not only affected wound-induced neutrophil recruitment, but also affected Mpx enzymatic activity. Moreover, protein expression levels of pro-inflammatory factors (Mpx, NFκB, and TNFα) were also regulated by compound 9. Taken together, our results provide in vivo evidence of the anti-inflammatory effects of synthesized chalcone analogues on wound-induced inflammation.

Assessing age-at-onset risk factors with incomplete covariate current status data under proportional odds models.

Motivated by an epidemiological survey of fracture in elderly women, we develop a semiparametric regression analysis of current status data with incompletely observed covariate under the proportional odds model. To accommodate both the interval-censored nature of current status failure time data and the incompletely observed covariate data, we propose an analysis based on the validation likelihood (VL), which is derived from likelihood pertaining to the validation sample, namely the subset of the sample where the data are completely observed. The missing data mechanism is assumed to be missing at random and is explicitly modeled and estimated in the VL approach. We propose implementing the VL method by integrating self-consistency and Newton-Raphson algorithms. Asymptotic normality and standard error estimation for the proposed estimator of the regression parameter are guaranteed. Simulation results reveal good performance of the VL estimator. The VL method has some gain in efficiency compared with the naive complete case method. But the VL method leads to unbiased estimators, whereas the complete case method does not when missing covariates are not missing completely at random. Application of the VL approach to the fracture data confirms that osteoporosis (low bone density) is a strong risk factor for the age at onset of fracture in elderly women.

Evaluation of the structure-activity relationship of flavonoids as antioxidants and toxicants of zebrafish larvae.

The antioxidant ability of an array of commercially available flavonoids was evaluated on the larvae of the zebrafish model organism, in order to find flavonoids with lower toxicities and higher radical oxygen-scavenging properties than flavone. Among the flavonoids tested, chrysin and morin possessed higher reactive oxygen species (ROS)-scavenging rates (-99% and -101%, respectively) and lower toxicity (LD(50)>100 ppm). Zebrafish fins in the UVB+chrysin group were 6.30 times more likely to grow to normal fin size than those in the UVB-only control group, while zebrafish fins in the UVB+morin group were 11.9 times more likely to grow to normal fin size than those in the UVB-only control group. These results were analysed by the QSAR method and were in accordance with predicted values. A new 4'-fluoroflavone was synthesised. The ROS-scavenging rate of 4'-fluoroflavone was -54%, which corresponds well with the predicted value (-48%). We propose that a combination of QSAR prediction and the zebrafish model organism is efficient for evaluating new flavonoids.

Cox regression for mixed case interval-censored data with covariate errors.

Covariate measurement error problems have been extensively studied in the context of right-censored data but less so for interval-censored data. Motivated by the AIDS Clinical Trial Group 175 study, where the occurrence time of AIDS was examined only at intermittent clinic visits and the baseline covariate CD4 count was measured with error, we describe a semiparametric maximum likelihood method for analyzing mixed case interval-censored data with mismeasured covariates under the proportional hazards model. We show that the estimator of the regression coefficient is asymptotically normal and efficient and provide a very stable and efficient algorithm for computing the estimators. We evaluate the method through simulation studies and illustrate it with AIDS data.