Joint Associations of Pregnancy Complications and Postpartum Maternal Renal Biomarkers With Severe Cardiovascular Morbidities: A US Racially and Ethnically Diverse Prospective Birth Cohort Study.

Background Pregnancy complications are risk factors for cardiovascular disease (CVD). Little is known about the role of renal biomarkers measured shortly after delivery, individually or in combination with pregnancy complications, in predicting subsequent severe maternal CVD. Methods and Results This study included 566 mothers of diverse races and ethnicities from the Boston Birth cohort, enrolled at delivery and followed prospectively. Plasma creatinine and CysC (cystatin C) were measured 1 to 3 days after delivery. CVD during follow-up was defined by physician diagnoses in electronic medical records. Associations of renal biomarkers and pregnancy complications with time-to-CVD events were assessed using Cox proportional hazards models. During an average of 10.3±3.2 years of follow-up, 30 mothers developed 1 or more CVDs. Only a modest association was observed between creatinine and risk of CVD. In comparison, we found that per 0.1 mg/L increase of CysC was associated with a hazard ratio (HR) of 1.2 (95% CI, 1.1-1.4) for CVD after adjusting for covariates. Compared with those without preeclampsia and with normal CysC level (≤75th percentile), mothers with preeclampsia and elevated CysC (>75th percentile) had the highest risk of CVD (HR, 4.6 [95% CI, 1.7-17.7]), whereas mothers with preeclampsia only or with elevated CysC only did not have significantly increased CVD risk. Similar synergistic effects for CVD were observed between CysC and preterm delivery. Conclusions In this sample of US, traditionally underrepresented multiracial and multiethnic high-risk mothers, elevated maternal plasma CysC, independently and jointly with pregnancy complications, increased risk of CVD later in life. These findings warrant further investigation. Registration URL: https://www.clinicaltrials.gov; Unique identifier: NCT03228875.

Joint associations of pregnancy complications and postpartum maternal renal biomarkers with severe cardiovascular morbidities: A US racially diverse prospective birth cohort study.

Rationale & Objective: Pregnancy complications are risk factors for cardiovascular diseases (CVD). Little is known about the role of renal biomarkers measured shortly after delivery, individually or in combination with pregnancy complications, in predicting subsequent severe maternal CVD. Methods: This study included 576 mothers of diverse ethnicities from the Boston Birth cohort, enrolled at delivery and followed prospectively. Plasma creatinine and cystatin C were measured 1-3 days after delivery. CVD during follow-up was defined by physician diagnoses in electronic medical records. Associations of renal biomarkers and pregnancy complications with time-to-CVD events were assessed using Cox proportional hazards models. Results: During an average of 10.3±3.2 years of follow-up, 34 mothers developed one or more CVD events. Although no significant associations were found between creatinine and risk of CVD, per unit increase of cystatin C (CysC) was associated with a hazard ratio (HR) of 5.21 (95%CI = 1.49-18.2) for CVD. A borderline significant interactive effect was observed between elevated CysC (≥75th percentile) and preeclampsia. Compared to those without preeclampsia and with normal CysC level (<75 th percentile), mothers with preeclampsia and elevated CysC had the highest risk of CVD (HR=3.8, 95%CI = 1.4-10.2), while mothers with preeclampsia only or with elevated CysC only did not have significantly increased CVD risk. Similar synergistic effects for CVD were observed between CysC and preterm delivery. Conclusions: In this sample of US, traditionally under-represented multi-ethnic high-risk mothers, elevated maternal plasma cystatin C and pregnancy complications synergistically increased risk of CVD later in life. These findings warrant further investigation. Clinical Perspectives: What is new?Maternal postpartum elevated levels of cystatin C are independently associated with higher risk of cardiovascular diseases (CVD) later in life.Maternal pregnancy complications coupled with postpartum elevated levels of cystatin C synergistically increased future risk of CVD.What are the clinical implications?These findings, if further confirmed, suggest that women with pregnancy complications and elevated postpartum cystatin C may be at particular high risk for CVD later in life compared to women without these risk factors.

Racial and ethnic disparities in mortality among breast cancer survivors after a second malignancy.

BACKGROUND: Racial and ethnic differences in survival after a first cancer are well established but have not been examined after a second primary cancer (SPC) despite the increasing incidence among survivors. METHODS: We examined 39 029 female breast cancer survivors who developed an SPC between 2000 and 2014 in the Surveillance, Epidemiology, and End Results 18 database. Multivariable Cox proportional hazards regression for competing risks data was used to estimate hazard ratios (HR) and 95% confidence intervals (CI) for cancer and cardiovascular disease mortality after SPCs comparing Hispanic, Non-Hispanic Asian, and Non-Hispanic Black survivors with Non-Hispanic White survivors. Models were adjusted for sociodemographics, tumor characteristics, and treatments of the first and second cancer. Analyses were stratified by SPC type. RESULTS: During 17 years of follow-up, there were 15 117 deaths after SPCs. The risk of cancer death was 12% higher among Non-Hispanic Black survivors (HR = 1.12, 95% CI = 1.05 to 1.19) and 8% higher among Hispanic survivors (HR = 1.08, 95% CI = 1.00 to 1.16) compared with Non-Hispanic White survivors. In subgroup analyses, the strongest associations were observed among Non-Hispanic Black survivors with a second breast or uterine cancer and among Hispanic survivors with a second breast cancer. Non-Hispanic Black survivors also experienced a 44% higher risk of cardiovascular disease death after SPC diagnosis than Non-Hispanic White survivors (HR = 1.44, 95% CI = 1.20 to 1.74). CONCLUSIONS: Higher cancer mortality among Non-Hispanic Black and Hispanic survivors and higher cardiovascular mortality among Non-Hispanic Black survivors exist among women who survive a first breast cancer to develop an SPC. Studies focused on identifying the contributors to these disparities are needed to enable implementation of effective mitigation strategies.

Mortality after second malignancy in breast cancer survivors compared to a first primary cancer: a nationwide longitudinal cohort study.

Limited information exists about survival outcomes after second primary cancers (SPCs) among breast cancer survivors. Studies suggest that mortality after certain SPCs may be higher than mortality after first primary cancers (FPCs) of the same type. A cohort study was conducted among 63,424 US women using the Surveillance, Epidemiology, and End Results 18 database (2000-2016) to compare mortality after a SPC among breast cancer survivors to mortality among women after a FPC using Cox proportional hazard regression. Propensity scores were used to match survivors with SPCs to women with FPCs 1:1 based on cancer type and prognostic factors. During a median follow-up of 42 months, 11,532 cancer deaths occurred after SPCs among survivors compared to 9305 deaths after FPCs. Cumulative cancer mortality was 44.7% for survivors with SPCs and 35.2% for women with FPCs. Survivors with SPCs had higher risk of cancer death (hazard ratio (HR): 1.27, 95% CI: 1.23-1.30) and death overall (HR: 1.18, 95% CI: 1.15-1.21) than women with FPCs. Increased risk of cancer death after SPCs compared to FPCs was observed for cancer in breast, lung, colon and/or rectum, uterus, lymphoma, melanoma, thyroid, and leukemia. Estrogen receptor status and treatment of the prior breast cancer as well as time between prior breast cancer and SPC significantly modified the mortality difference between women with SPC and FPC. A more tailored approach to early detection and treatment could improve outcomes from second cancer in breast cancer survivors.

Association Between Late-Life Neuropsychiatric Symptoms and Cognitive Decline in Relation to White Matter Hyperintensities and Amyloid Burden.

BACKGROUND: Neuropsychiatric symptoms (NPS) among cognitively normal older adults are increasingly recognized as risk factors for cognitive decline and impairment. However, the underlying mechanisms remain unclear. OBJECTIVE: To examine whether biomarkers of Alzheimer's disease (amyloid burden) and cerebrovascular disease (white matter hyperintensity (WMH) volume) modify the association between NPS and cognitive decline among cognitively unimpaired older adults. METHODS: Analyses included 193 cognitively unimpaired participants (M age = 70 years) from the BIOCARD study, including 148 with PET amyloid and WMH biomarker data. NPS were measured with Neuropsychiatric Inventory and Geriatric Depression Scale scores. Linear mixed effects models were used to examine the association between baseline NPS and longitudinal cognitive trajectories (M follow-up = 3.05 years), using separate models for global, episodic memory, and executive function cognitive composite scores. In a subset of individuals with biomarker data, we evaluated whether WMH or cortical amyloid burden modified the relationship between NPS and cognitive change (as indicated by the NPS×biomarker×time interactions). RESULTS: Higher baseline NPS were associated with lower executive function scores, but not a faster rate of decline in executive function. NPS symptoms were unrelated to the global or episodic memory composite scores, and there was little evidence of a relationship between NPS symptoms and cognitive change over time. The associations between NPS and cognitive decline did not differ by amyloid or WMH burden, and NPS were unrelated to amyloid and WMH burden. CONCLUSION: These results suggest that the effect of neuropsychiatric symptoms on executive dysfunction may occur through mechanisms outside of amyloid and cerebrovascular disease.

In Utero Exposure to Heavy Metals and Trace Elements and Childhood Blood Pressure in a U.S. Urban, Low-Income, Minority Birth Cohort.

BACKGROUND: In utero exposure to heavy metals lead (Pb), mercury (Hg), and cadmium (Cd) may be associated with higher childhood blood pressure (BP), whereas trace elements selenium (Se) and manganese (Mn) may have protective antioxidant effects that modify metal-BP associations. OBJECTIVES: We examined the individual and joint effects of in utero exposure to Pb, Hg, Cd, Se, and Mn on childhood BP. METHODS: We used data from the Boston Birth Cohort (enrolled 2002-2013). We measured heavy metals and trace elements in maternal red blood cells collected 24-72 h after delivery. We calculated child BP percentile per the 2017 American Academy of Pediatrics Clinical Practice Guideline. We used linear regression models to estimate the association of each metal, and Bayesian kernel machine regression (BKMR) to examine metal coexposures, with child BP between 3 to 15 years of age. RESULTS: Our analytic sample comprised 1,194 mother-infant pairs (61% non-Hispanic Black, 20% Hispanic). Hg and Pb were not associated with child systolic BP (SBP). Se and Mn were inversely associated with child SBP percentiles, which, on average, were 6.23 points lower with a doubling of Se (95% CI: -11.51, -0.96) and 2.62 points lower with a doubling of Mn (95% CI: -5.20, -0.04). BKMR models showed similar results. Although Cd was not associated with child SBP overall, the inverse association between Mn and child SBP was stronger at higher levels of Cd (p-interaction=0.04). Consistent with this finding, in utero exposure to cigarette smoke modified the Mn-child SBP association. Among children whose mothers smoked during pregnancy, a doubling of Mn was associated with a 10.09-point reduction in SBP percentile (95% CI: -18.03, -2.15), compared with a 1.49-point reduction (95% CI: -4.21, 1.24) in children whose mothers did not smoke during pregnancy (p-interaction=0.08). CONCLUSION: Se and Mn concentrations in maternal red blood cells collected 24-72 h after delivery were associated with lower child SBP at 3 to 15 years of age. There was an interaction between Mn and Cd on child SBP, whereby the protective association of Mn on child SBP was stronger among mothers who had higher Cd. The association of Mn and child SBP was also modified by maternal cigarette smoking-a source of Cd-during pregnancy. Optimizing in utero Se levels, as well as Mn levels in women who had high Cd or smoked during pregnancy, may protect offspring from developing high BP during childhood. https://doi.org/10.1289/EHP8325.

Comparison of Time to Clinical Improvement With vs Without Remdesivir Treatment in Hospitalized Patients With COVID-19.

Importance: Clinical effectiveness data on remdesivir are urgently needed, especially among diverse populations and in combination with other therapies. Objective: To examine whether remdesivir administered with or without corticosteroids for treatment of coronavirus disease 2019 (COVID-19) is associated with more rapid clinical improvement in a racially/ethnically diverse population. Design, Setting, and Participants: This retrospective comparative effectiveness research study was conducted from March 4 to August 29, 2020, in a 5-hospital health system in the Baltimore, Maryland, and Washington, DC, area. Of 2483 individuals with confirmed severe acute respiratory syndrome coronavirus 2 infection assessed by polymerase chain reaction, those who received remdesivir were matched to infected individuals who did not receive remdesivir using time-invariant covariates (age, sex, race/ethnicity, Charlson Comorbidity Index, body mass index, and do-not-resuscitate or do-not-intubate orders) and time-dependent covariates (ratio of peripheral blood oxygen saturation to fraction of inspired oxygen, blood pressure, pulse, temperature, respiratory rate, C-reactive protein level, complete white blood cell count, lymphocyte count, albumin level, alanine aminotransferase level, glomerular filtration rate, dimerized plasmin fragment D [D-dimer] level, and oxygen device). An individual in the remdesivir group with k days of treatment was matched to a control patient who stayed in the hospital at least k days (5 days maximum) beyond the matching day. Exposures: Remdesivir treatment with or without corticosteroid administration. Main Outcomes and Measures: The primary outcome was rate of clinical improvement (hospital discharge or decrease of 2 points on the World Health Organization severity score), and the secondary outcome, mortality at 28 days. An additional outcome was clinical improvement and time to death associated with combined remdesivir and corticosteroid treatment. Results: Of 2483 consecutive admissions, 342 individuals received remdesivir, 184 of whom also received corticosteroids and 158 of whom received remdesivir alone. For these 342 patients, the median age was 60 years (interquartile range, 46-69 years), 189 (55.3%) were men, and 276 (80.7%) self-identified as non-White race/ethnicity. Remdesivir recipients had a shorter time to clinical improvement than matched controls without remdesivir treatment (median, 5.0 days [interquartile range, 4.0-8.0 days] vs 7.0 days [interquartile range, 4.0-10.0 days]; adjusted hazard ratio, 1.47 [95% CI, 1.22-1.79]). Remdesivir recipients had a 28-day mortality rate of 7.7% (22 deaths) compared with 14.0% (40 deaths) among matched controls, but this difference was not statistically significant in the time-to-death analysis (adjusted hazard ratio, 0.70; 95% CI, 0.38-1.28). The addition of corticosteroids to remdesivir was not associated with a reduced hazard of death at 28 days (adjusted hazard ratio, 1.94; 95% CI, 0.67-5.57). Conclusions and Relevance: In this comparative effectiveness research study of adults hospitalized with COVID-19, receipt of remdesivir was associated with faster clinical improvement in a cohort of predominantly non-White patients. Remdesivir plus corticosteroid administration did not reduce the time to death compared with remdesivir administered alone.

Association of midlife vascular risk and AD biomarkers with subsequent cognitive decline.

OBJECTIVE: To determine whether vascular risk and Alzheimer disease (AD) biomarkers have independent or synergistic effects on cognitive decline and whether vascular risk is associated with the accumulation of AD pathology as measured by change in biomarkers over time. METHODS: At baseline, participants (n = 168) were cognitively normal and primarily middle-aged (mean 56.4 years, SD 10.9 years) and had both vascular risk factor status and proximal CSF biomarkers available. Baseline vascular risk was quantified with a composite vascular risk score reflecting the presence or absence of hypertension, hypercholesterolemia, diabetes, current smoking, and obesity. CSF biomarkers of ß-amyloid (Aß)1-42, total tau (t-tau), and phosphorylated tau (p-tau) were used to create dichotomous high and low AD biomarker groups (based on Aß1-42 and tau). Linear mixed-effects models were used to examine change in a cognitive composite score (mean follow-up 13.9 years) and change in CSF biomarkers (mean follow-up 4.2 years). RESULTS: There was no evidence of a synergistic relationship between the vascular risk score and CSF AD biomarkers and cognitive decline. Instead, the vascular risk score (estimate -0.022, 95% confidence interval [CI] -0.043 to -0.002, p = 0.03) and AD biomarkers (estimate -0.060, 95% CI -0.096 to -0.024, p = 0.001) were independently and additively associated with cognitive decline. In addition, the vascular risk score was unrelated to levels of or rate of change in CSF Aß1-42, t-tau, or p-tau. CONCLUSIONS: The results of this observational cohort study suggest that vascular risk and biomarkers of AD pathology, when measured in midlife, act along independent pathways and underscore the importance of accounting for multiple risk factors for identifying cognitively normal individuals at the greatest risk of cognitive decline.

Semiparametric modelling and estimation of covariate-adjusted dependence between bivariate recurrent events.

A time-dependent measure, termed the rate ratio, was proposed to assess the local dependence between two types of recurrent event processes in one-sample settings. However, the one-sample work does not consider modeling the dependence by covariates such as subject characteristics and treatments received. The focus of this paper is to understand how and in what magnitude the covariates influence the dependence strength for bivariate recurrent events. We propose the covariate-adjusted rate ratio, a measure of covariate-adjusted dependence. We propose a semiparametric regression model for jointly modeling the frequency and dependence of bivariate recurrent events: the first level is a proportional rates model for the marginal rates and the second level is a proportional rate ratio model for the dependence structure. We develop a pseudo-partial likelihood to estimate the parameters in the proportional rate ratio model. We establish the asymptotic properties of the estimators and evaluate the finite sample performance via simulation studies. We illustrate the proposed models and methods using a soft tissue sarcoma study that examines the effects of initial treatments on the marginal frequencies of local/distant sarcoma recurrence and the dependence structure between the two types of cancer recurrence.

Simultaneous removal of NH3-N and COD from shale gas distillate via an integration of adsorption and photo-catalysis: A hybrid approach.

In view of the circulation cooling water (CCW) quality for refining and petrochemical enterprises, distillates obtained from shale gas produced water after alkali precipitation, filtration and multi-effect evaporation required further purification to remove NH3-N and COD. Illumination, adsorption, photocatalysis after adsorption equilibrium (AP) and integration of adsorption and photocatalysis (IOAP) were carried out to optimize the distillates treatment. AP and IOAP treatments were feasible for the simultaneous removal of NH3-N and COD from the target distillate, while IOAP treatment had much better adaptability and practicability due to its economic cost and easy operation. In IOAP, the removal rate of COD and NH3-N was high up to 59.0% and 88.9%, respectively, under Xenon lamp illumination (25 A) for 60 min with 10 g/L zeolite. The residual concentration of COD and NH3-N were 73.9 mg/L and 23.0 mg/L, respectively, which could well meet the CCW quality. Furthermore, the results of zeolites characterization (SEM-EDX, BET and FTIR) and kinetics analysis showed that the removal of COD in IOAP process mainly depended on the effect of photocatalysis excited by zeolite, while the removal of NH3-N was in virtue of the synergistic effect of photocatalysis and adsorption.

Bioactive Terpenoids from Salvia plebeia: Structures, NO Inhibitory Activities, and Interactions with iNOS.

A phytochemical investigation to obtain new NO inhibitors resulted in the identification of six new (1-6) and four known (7-10) terpenoids from Salvia plebeia. Compounds 1 and 2 are new diterpenoids, 3-5 are new meroditerpenoids, 6-9 are sesquiterpenoids, and 10 is a known meroditerpenoid. The structures of these isolates were determined by routine NMR experiments and X-ray diffraction, as well as the electronic circular dichroism spectra. Compounds 1-4 are diterpenoids carrying an oxygen bridge, and 6 is a rare copane-type sesquiterpenoid with a bridged tricyclic framework. The isolates inhibited NO generation induced by lipopolysaccharide in BV-2 cells. The possible mechanism of NO inhibition of some bioactive compounds was also investigated using molecular docking, which revealed interactions of bioactive compounds with the iNOS protein.

Nonparametric analysis of bivariate gap time with competing risks.

This article considers nonparametric methods for studying recurrent disease and death with competing risks. We first point out that comparisons based on the well-known cumulative incidence function can be confounded by different prevalence rates of the competing events, and that comparisons of the conditional distribution of the survival time given the failure event type are more relevant for investigating the prognosis of different patterns of recurrence disease. We then propose nonparametric estimators for the conditional cumulative incidence function as well as the conditional bivariate cumulative incidence function for the bivariate gap times, that is, the time to disease recurrence and the residual lifetime after recurrence. To quantify the association between the two gap times in the competing risks setting, a modified Kendall's tau statistic is proposed. The proposed estimators for the conditional bivariate cumulative incidence distribution and the association measure account for the induced dependent censoring for the second gap time. Uniform consistency and weak convergence of the proposed estimators are established. Hypothesis testing procedures for two-sample comparisons are discussed. Numerical simulation studies with practical sample sizes are conducted to evaluate the performance of the proposed nonparametric estimators and tests. An application to data from a pancreatic cancer study is presented to illustrate the methods developed in this article.

Isolation, Characterization, and Antiproliferative Activities of Eudesmanolide Derivatives from the Flowers of Inula japonica.

Inula japonica belongs to the family Asteraceae, and its flowers have been used as dietary supplements and health tea in China. The study aimed to identify the bioactive components with the antiproliferative property. Ten 1,10-seco-eudesmanolide derivatives, including four new compounds (1-4), were isolated from the flowers of I. japonica. Their structures were established on the basis of the interpretation of spectroscopic data and electronic circular dichroism (ECD) calculations. All of these isolates were evaluated for their antiproliferative activities against MCF-7 and MDA-MB-231 human breast cancer cells. Compound 4 possessed the most potent effects, with the IC50 values of 0.20 ± 0.04 and 6.22 ± 1.30 µM against MCF-7 and MDA-MB-231 cells, respectively. The present investigation indicated that eudesmanolide derivatives from the flowers of I. japonica, especially compound 4, might be used as potential antitumor chemotherapy agent candidates.

Analysis of longitudinal multivariate outcome data from couples cohort studies: application to HPV transmission dynamics.

We consider a specific situation of correlated data where multiple outcomes are repeatedly measured on each member of a couple. Such multivariate longitudinal data from couples may exhibit multi-faceted correlations which can be further complicated if there are polygamous partnerships. An example is data from cohort studies on human papillomavirus (HPV) transmission dynamics in heterosexual couples. HPV is a common sexually transmitted disease with 14 known oncogenic types causing anogenital cancers. The binary outcomes on the multiple types measured in couples over time may introduce inter-type, intra-couple, and temporal correlations. Simple analysis using generalized estimating equations or random effects models lacks interpretability and cannot fully utilize the available information. We developed a hybrid modeling strategy using Markov transition models together with pairwise composite likelihood for analyzing such data. The method can be used to identify risk factors associated with HPV transmission and persistence, estimate difference in risks between male-to-female and female-to-male HPV transmission, compare type-specific transmission risks within couples, and characterize the inter-type and intra-couple associations. Applying the method to HPV couple data collected in a Ugandan male circumcision (MC) trial, we assessed the effect of MC and the role of gender on risks of HPV transmission and persistence.

Bioactive Diterpenoids from the Leaves of Callicarpa macrophylla.

A phytochemical investigation of the leaves of Callicarpa macrophylla led to the isolation of five new diterpenoids (1-5), macrophypenes A-E, and nine known analogues (6-14). The structures of 1-5 were established on the basis of extensive analysis of NMR spectroscopic data, X-ray diffraction data, and experimental and calculated electronic circular dichroism spectra. Compound 1 is a spiroditerpenoid with a novel skeleton, and compound 5 is a rare ent-abietane diterpenoid possessing a peroxide bridge. Compounds 1, 5-7, and 11-14 stimulate nerve growth factor mediated neurite outgrowth from PC12 cells.

Causal estimation using semiparametric transformation models under prevalent sampling.

This article presents methods and inference for causal estimation in semiparametric transformation models for the prevalent survival data. Through the estimation of the transformation models and covariate distribution, we propose a few analytical procedures to estimate the causal survival function. As the data are observational, the unobserved potential outcome (survival time) may be associated with the treatment assignment, and therefore there may exist a systematic imbalance between the data observed from each treatment arm. Further, due to prevalent sampling, subjects are observed only if they have not experienced the failure event when data collection began, causing the prevalent sampling bias. We propose a unified approach, which simultaneously corrects the bias from the prevalent sampling and balances the systematic differences from the observational data. We illustrate in the simulation study that standard analysis without proper adjustment would result in biased causal inference. Large sample properties of the proposed estimation procedures are established by techniques of empirical processes and examined by simulation studies. The proposed methods are applied to the Surveillance, Epidemiology, and End Results (SEER) and Medicare-linked data for women diagnosed with breast cancer.

Bioactive clerodane diterpenoids from the twigs of Casearia balansae.

Eight new clerodane diterpenes, balanspenes A-H (1-8), along with two known analogues (9 and 10), were isolated from the twigs of Casearia balansae. The structures of 1-8 were elucidated on the basis of extensive 1D and 2D NMR spectroscopic data analysis, and the absolute configurations of compounds 1, 4, and 7 were confirmed by comparing their experimental CD spectra with those calculated by the time-dependent density functional theory method. Compounds 4-7, 9, and 10 were found to possess the property of being able to stimulate NGF-mediated neurite outgrowth from PC12 cells.

Two novel clerodane diterpenenes with NGF-potentiating activities from the twigs of Croton yanhuii.

Nerve growth factor (NGF) and analog reagents to promote the neurite outgrowth of nerve cells against the neuron degeneration are expected to be potentially useful for the medical treatment of Alzheimer's disease. In our focus on the discovery of bioactive diterpenes, we investigated the chemical constituents of the plant Croton yanhuii. This investigation led to the isolation and identification of two novel clerodane diterpenes (1 and 2). Their structures were elucidated on the basis of extensive 1D and 2D NMR (COSY, HMQC, HMBC, and NOESY) and mass (ESIMS and HR-ESIMS) spectroscopic data analyses. Further biological screenings showed that both of the compounds enhanced NGF-mediated neurite outgrowth from PC12 cells.

Estimating propensity scores and causal survival functions using prevalent survival data.

This article develops semiparametric approaches for estimation of propensity scores and causal survival functions from prevalent survival data. The analytical problem arises when the prevalent sampling is adopted for collecting failure times and, as a result, the covariates are incompletely observed due to their association with failure time. The proposed procedure for estimating propensity scores shares interesting features similar to the likelihood formulation in case-control study, but in our case it requires additional consideration in the intercept term. The result shows that the corrected propensity scores in logistic regression setting can be obtained through standard estimation procedure with specific adjustments on the intercept term. For causal estimation, two different types of missing sources are encountered in our model: one can be explained by potential outcome framework; the other is caused by the prevalent sampling scheme. Statistical analysis without adjusting bias from both sources of missingness will lead to biased results in causal inference. The proposed methods were partly motivated by and applied to the Surveillance, Epidemiology, and End Results (SEER)-Medicare linked data for women diagnosed with breast cancer.

Estimating incident population distribution from prevalent data.

A prevalent sample consists of individuals who have experienced disease incidence but not failure event at the sampling time. We discuss methods for estimating the distribution function of a random vector defined at baseline for an incident disease population when data are collected by prevalent sampling. Prevalent sampling design is often more focused and economical than incident study design for studying the survival distribution of a diseased population, but prevalent samples are biased by design. Subjects with longer survival time are more likely to be included in a prevalent cohort, and other baseline variables of interests that are correlated with survival time are also subject to sampling bias induced by the prevalent sampling scheme. Without recognition of the bias, applying empirical distribution function to estimate the population distribution of baseline variables can lead to serious bias. In this article, nonparametric and semiparametric methods are developed for distribution estimation of baseline variables using prevalent data.