Time-dependent effects of lead on rat reproductive functions

The effects of exposure to lead on endocrine function and the reproductive parameters were studied in pubertal rats treated with 1.0 g l(-1) lead acetate in drinking water for 20 days (subacute group) or 9 months (chronic group) in addition to i.v. injections of lead acetate (0.1 mg 100 g(-1) body wt.) every 10 (subacute group) or 15 days (chronic group). Although basal levels of testosterone were higher both in plasma and in testes of acutely intoxicated animals, the circulating levels of luteinizing hormone (LH) were not affected in either group, nor was the LH-releasing hormone content of the median eminence. The density of [I-125]LH/human chorionic gonadotrophin (hCG) binding sites in testicular homogenates was reduced by saturnism in both groups, concomitant with a significantly increased apparent affinity constant of the hormone-receptor complex. These data can be viewed as the result of a mixture of specific lead toxicity (e.g. at the enzyme level) with other more general actions (e.g. at the level of the hypothalamus-pituitary-testicular axis).

Circadian time-dependent effects of fencamfamine on inhibition of dopamine uptake and release in rat striatal slices

Fencamfamine (FCF) is a central stimulant that facilitates central dopaminergic transmission through inhibition of dopamine uptake and enhanced release of the transmitter. We evaluated the changes in the inhibition of uptake and the release of striatal [ 3H]-dopamine at 9:00 and 21:00 h, times corresponding to maximal and minimal behavioral responses to FCF, respectively. Adult male Wistar rats (200-250 g) maintained on a 12-h light/12-h dark cycle (lights on at 7:00 h) were used. In the behavioral experiments the rats (N = 8 for each group) received FCF (3.5 mg/kg, ip) or saline at 9:00 or 21:00 h. Fifteen minutes after treatment the duration of activity (sniffing, rearing and locomotion) was recorded for 120 min. The basal motor activity was higher (28.6 ± 4.2 vs 8.4 ± 3.5 s) after saline administration at 21:00 h than at 9:00 h. FCF at a single dose significantly enhanced the basal motor activity (38.3 ± 4.5 vs 8.4 ± 3.5 s) and increased the duration of exploratory activity (38.3 ± 4.5 vs 32.1 ± 4.6 s) during the light, but not the dark phase. Two other groups of rats (N = 6 for each group) were decapitated at 9:00 and 21:00 h and striata were dissected for dopamine uptake and relase assays. The inhibition of uptake and release of [ 3H]-dopamine were higher at 9:00 than at 21:00 h, suggesting that uptake inhibition and the release properties of FCF undergo daily variation. These data suggest that the circadian time-dependent effects of FCF might be related to a higher susceptibility of dopamine presynaptic terminals to the action of FCF during the light phase which corresponds to the rats' resting period.

A Nonstationary Negative Binomial Time Series with Time-Dependent Covariates: Enterococcus Counts in Boston Harbor

Boston Harbor has had a history of poor water quality, including contamination by enteric pathogens. We conduct a statistical analysis of data collected by the Massachusetts Water Resources Authority (MWRA) between 1996 and 2002 to evaluate the effects of court-mandated improvements in sewage treatment. Motivated by the ineffectiveness of standard Poisson mixture models and their zero-inflated counterparts, we propose a new negative binomial model for time series of Enterococcus counts in Boston Harbor, where nonstationarity and autocorrelation are modeled using a nonparametric smooth function of time in the predictor. Without further restrictions, this function is not identifiable in the presence of time-dependent covariates; consequently we use a basis orthogonal to the space spanned by the covariates and use penalized quasi-likelihood (PQL) for estimation. We conclude that Enterococcus counts were greatly reduced near the Nut Island Treatment Plant (NITP) outfalls following the transfer of wastewaters from NITP to the Deer Island Treatment Plant (DITP) and that the transfer of wastewaters from Boston Harbor to the offshore diffusers in Massachusetts Bay reduced the Enterococcus counts near the DITP outfalls.

Statistical evaluation of time-dependent metabolite concentrations: estimation of post-mortem intervals based on in situ 1H-MRS of the brain

Knowledge of the time interval from death (post-mortem interval, PMI) has an enormous legal, criminological and psychological impact. Aiming to find an objective method for the determination of PMIs in forensic medicine, 1H-MR spectroscopy (1H-MRS) was used in a sheep head model to follow changes in brain metabolite concentrations after death. Following the characterization of newly observed metabolites (Ith et al., Magn. Reson. Med. 2002; 5: 915-920), the full set of acquired spectra was analyzed statistically to provide a quantitative estimation of PMIs with their respective confidence limits. In a first step, analytical mathematical functions are proposed to describe the time courses of 10 metabolites in the decomposing brain up to 3 weeks post-mortem. Subsequently, the inverted functions are used to predict PMIs based on the measured metabolite concentrations. Individual PMIs calculated from five different metabolites are then pooled, being weighted by their inverse variances. The predicted PMIs from all individual examinations in the sheep model are compared with known true times. In addition, four human cases with forensically estimated PMIs are compared with predictions based on single in situ MRS measurements. Interpretation of the individual sheep examinations gave a good correlation up to 250 h post-mortem, demonstrating that the predicted PMIs are consistent with the data used to generate the model. Comparison of the estimated PMIs with the forensically determined PMIs in the four human cases shows an adequate correlation. Current PMI estimations based on forensic methods typically suffer from uncertainties in the order of days to weeks without mathematically defined confidence information. In turn, a single 1H-MRS measurement of brain tissue in situ results in PMIs with defined and favorable confidence intervals in the range of hours, thus offering a quantitative and objective method for the determination of PMIs.

Time-dependent interactions of the two porphyrinic compounds chlorin e6 and mono-L-aspartyl-chlorin e6 with phospholipid vesicles probed by NMR spectroscopy

The distribution processes of chlorin e6 (CE) and monoaspartyl-chlorin e6 (MACE) between the outer and inner phospholipid monolayers of 1,2-dioleoyl-phosphatidylcholine (DOPC) vesicles were monitored by 1H NMR spectroscopy through analysis of chemical shifts and line widths of the DOPC vesicle resonances. Chlorin adsorption to the outer vesicle monolayer induced changes in the DOPC 1H NMR spectrum. Most pronounced was a split of the N-methyl choline resonance, allowing for separate analysis of inner and outer vesicle layers. Transbilayer distribution of the chlorin compounds was indicated by time-dependent characteristic spectral changes of the DOPC resonances. Kinetic parameters for the flip-flop processes, that is, half-lives and rate constants, were obtained from the experimental data points. In comparison to CE, MACE transbilayer movement was significantly reduced, with MACE remaining more or less attached to the outer membrane layer. The distribution coefficients for CE and MACE between the vesicular and aqueous phase were determined. Both CE and MACE exhibited a high affinity for the vesicular phase. For CE, a positive correlation was found between transfer rate and increasing molar ratio CE/DOPC. Enhanced membrane rigidity induced by increasing amounts of cholesterol into the model membrane was accompanied by a decrease of CE flip-flop rates across the membrane. The present study shows that the movement of porphyrins across membranes can efficiently be investigated by 1H NMR spectroscopy and that small changes in porphyrin structure can have large effects on membrane kinetics.

Delay in diagnosis of eosinophilic esophagitis increases risk for stricture formation in a time-dependent manner

BACKGROUND & AIMS Development of strictures is a major concern for patients with eosinophilic esophagitis (EoE). At diagnosis, EoE can present with an inflammatory phenotype (characterized by whitish exudates, furrows, and edema), a stricturing phenotype (characterized by rings and stenosis), or a combination of these. Little is known about progression of stricture formation; we evaluated stricture development over time in the absence of treatment and investigated risk factors for stricture formation. METHODS We performed a retrospective study using the Swiss EoE Database, collecting data on 200 patients with symptomatic EoE (153 men; mean age at diagnosis, 39 ± 15 years old). Stricture severity was graded based on the degree of difficulty associated with passing of the standard adult endoscope. RESULTS The median delay in diagnosis of EoE was 6 years (interquartile range, 2-12 years). With increasing duration of delay in diagnosis, the prevalence of fibrotic features of EoE, based on endoscopy, increased from 46.5% (diagnostic delay, 0-2 years) to 87.5% (diagnostic delay, >20 years; P = .020). Similarly, the prevalence of esophageal strictures increased with duration of diagnostic delay, from 17.2% (diagnostic delay, 0-2 years) to 70.8% (diagnostic delay, >20 years; P < .001). Diagnostic delay was the only risk factor for strictures at the time of EoE diagnosis (odds ratio = 1.08; 95% confidence interval: 1.040-1.122; P < .001). CONCLUSIONS The prevalence of esophageal strictures correlates with the duration of untreated disease. These findings indicate the need to minimize delay in diagnosis of EoE.

The long-term stability of self-esteem: Its time-dependent decay and nonzero asymptote

How stable are individual differences in self-esteem? We examined the time-dependent decay of rank-order stability of self-esteem and tested whether stability asymptotically approaches zero or a nonzero value across long test–retest intervals. Analyses were based on 6 assessments across a 29-year period of a sample of 3,180 individuals aged 14 to 102 years. The results indicated that, as test–retest intervals increased, stability exponentially decayed and asymptotically approached a nonzero value (estimated as .43). The exponential decay function explained a large proportion of variance in observed stability coefficients, provided a better fit than alternative functions, and held across gender and for all age groups from adolescence to old age. Moreover, structural equation modeling of the individual-level data suggested that a perfectly stable trait component underlies stability of self-esteem. The findings suggest that the stability of self-esteem is relatively large, even across very long periods, and that self-esteem is a trait-like characteristic.

TIME DEPENDENT ALTERATIONS IN CENTRAL NERVOUS SYSTEM DOPAMINE RECEPTORS INDUCED BY DOPAMINE AGONIST TREATMENT

Levodopa, the precursor of dopamine, is currently the drug of choice in the treatment of Parkinson's disease. Recently, two direct dopamine agonists, bromocriptine and pergolide, have been tested for the treatment of Parkinson's disease because of reduced side effects compared to levodopa. Few studies have evaluated the effects of long-term treatment of dopamine agonists on dopamine receptor regulation in the central nervous system. Thus, the purpose of this study was to determine whether chronic dopamine agonist treatment produces a down-regulation of striatal dopamine receptor function and to compare the results of the two classes of dopaminergic drugs.^ Levodopa with carbidopa, a peripheral decarboxylase inhibitor, was administered orally to rats whereas bromocriptine and pergolide were injected intraperitoneally once daily. Several neurochemical parameters were examined from 1 to 28 days.^ Levodopa minimally decreased striatal D-1 receptor activity but increased the number of striatal D-2 binding sites. Levodopa increased the V(,max) of tyrosine hydroxylase (TH) in all brain regions tested. Protein blot analysis of striatal TH indicated a significant increase in the amount of TH present. Dopamine-beta-hydroxylase (DBH) activity was markedly decreased in all brain regions studied and mixing experiments of control and drug-treated cortices did not show the presence of an increased level of endogenous inhibitors.^ Bromocriptine treatment decreased the number of D-2 binding sites. Striatal TH activity was decreased and protein blot analysis indicated no change in TH quantity. The specificity of bromocriptine for striatal TH suggested that bromocriptine preferentially interacts with dopamine autoreceptors.^ Combination levodopa-bromocriptine was administered for 12 days. There was a decrease in both D-1 receptor activity and D-2 binding sites, and a decrease in brain HVA levels suggesting a postsynaptic receptor action. Pergolide produced identical results to the combination levodopa-bromocriptine studies.^ In conclusion, combination levodopa-bromocriptine and pergolide treatments exhibited the expected down-regulation of dopamine receptor activity. In contrast, levodopa appeared to up-regulate dopamine receptor activity. Thus, these data may help to explain, on a biochemical basis, the decrease in the levodopa-induced side effects noted with combination levodopa-bromocriptine or pergolide therapies in the treatment of Parkinson's disease. ^

Analysis of recurrent failure times: A time-dependent Yule process approach

Analysis of recurrent events has been widely discussed in medical, health services, insurance, and engineering areas in recent years. This research proposes to use a nonhomogeneous Yule process with the proportional intensity assumption to model the hazard function on recurrent events data and the associated risk factors. This method assumes that repeated events occur for each individual, with given covariates, according to a nonhomogeneous Yule process with intensity function λx(t) = λ 0(t) · exp( x′β). One of the advantages of using a non-homogeneous Yule process for recurrent events is that it assumes that the recurrent rate is proportional to the number of events that occur up to time t. Maximum likelihood estimation is used to provide estimates of the parameters in the model, and a generalized scoring iterative procedure is applied in numerical computation. ^ Model comparisons between the proposed method and other existing recurrent models are addressed by simulation. One example concerning recurrent myocardial infarction events compared between two distinct populations, Mexican-American and Non-Hispanic Whites in the Corpus Christi Heart Project is examined. ^

AN ILLNESS-DEATH PROCESS WITH TIME-DEPENDENT COVARIATES

A general model for the illness-death stochastic process with covariates has been developed for the analysis of survival data. This model incorporates important baseline and time-dependent covariates to make proper adjustment for the transition probabilities and survival probabilities. The follow-up period is subdivided into small intervals and a constant hazard is assumed for each interval. An approximation formula is derived to estimate the transition parameters when the exact transition time is unknown.^ The method developed is illustrated by using data from a study on the prevention of the recurrence of a myocardial infarction and subsequent mortality, the Beta-Blocker Heart Attack Trial (BHAT). This method provides an analytical approach which simultaneously includes provision for both fatal and nonfatal events in the model. According to this analysis, the effectiveness of the treatment can be compared between the Placebo and Propranolol treatment groups with respect to fatal and nonfatal events. ^

Age -period -cohort analysis: An extension of Cox's lifetable regression with time -dependent covariates

It is well known that an identification problem exists in the analysis of age-period-cohort data because of the relationship among the three factors (date of birth + age at death = date of death). There are numerous suggestions about how to analyze the data. No one solution has been satisfactory. The purpose of this study is to provide another analytic method by extending the Cox's lifetable regression model with time-dependent covariates. The new approach contains the following features: (1) It is based on the conditional maximum likelihood procedure using a proportional hazard function described by Cox (1972), treating the age factor as the underlying hazard to estimate the parameters for the cohort and period factors. (2) The model is flexible so that both the cohort and period factors can be treated as dummy or continuous variables, and the parameter estimations can be obtained for numerous combinations of variables as in a regression analysis. (3) The model is applicable even when the time period is unequally spaced.^ Two specific models are considered to illustrate the new approach and applied to the U.S. prostate cancer data. We find that there are significant differences between all cohorts and there is a significant period effect for both whites and nonwhites. The underlying hazard increases exponentially with age indicating that old people have much higher risk than young people. A log transformation of relative risk shows that the prostate cancer risk declined in recent cohorts for both models. However, prostate cancer risk declined 5 cohorts (25 years) earlier for whites than for nonwhites under the period factor model (0 0 0 1 1 1 1). These latter results are similar to the previous study by Holford (1983).^ The new approach offers a general method to analyze the age-period-cohort data without using any arbitrary constraint in the model. ^

The number and timing of time -dependent covariate measurements for the Cox regression model

The problem of analyzing data with updated measurements in the time-dependent proportional hazards model arises frequently in practice. One available option is to reduce the number of intervals (or updated measurements) to be included in the Cox regression model. We empirically investigated the bias of the estimator of the time-dependent covariate while varying the effect of failure rate, sample size, true values of the parameters and the number of intervals. We also evaluated how often a time-dependent covariate needs to be collected and assessed the effect of sample size and failure rate on the power of testing a time-dependent effect.^ A time-dependent proportional hazards model with two binary covariates was considered. The time axis was partitioned into k intervals. The baseline hazard was assumed to be 1 so that the failure times were exponentially distributed in the ith interval. A type II censoring model was adopted to characterize the failure rate. The factors of interest were sample size (500, 1000), type II censoring with failure rates of 0.05, 0.10, and 0.20, and three values for each of the non-time-dependent and time-dependent covariates (1/4,1/2,3/4).^ The mean of the bias of the estimator of the coefficient of the time-dependent covariate decreased as sample size and number of intervals increased whereas the mean of the bias increased as failure rate and true values of the covariates increased. The mean of the bias of the estimator of the coefficient was smallest when all of the updated measurements were used in the model compared with two models that used selected measurements of the time-dependent covariate. For the model that included all the measurements, the coverage rates of the estimator of the coefficient of the time-dependent covariate was in most cases 90% or more except when the failure rate was high (0.20). The power associated with testing a time-dependent effect was highest when all of the measurements of the time-dependent covariate were used. An example from the Systolic Hypertension in the Elderly Program Cooperative Research Group is presented. ^

A method for revealing phase space structures of general time dependent dynamical systems

In this paper we develop new techniques for revealing geometrical structures in phase space that are valid for aperiodically time dependent dynamical systems, which we refer to as Lagrangian descriptors. These quantities are based on the integration, for a finite time, along trajectories of an intrinsic bounded, positive geometrical and/or physical property of the trajectory itself. We discuss a general methodology for constructing Lagrangian descriptors, and we discuss a “heuristic argument” that explains why this method is successful for revealing geometrical structures in the phase space of a dynamical system. We support this argument by explicit calculations on a benchmark problem having a hyperbolic fixed point with stable and unstable manifolds that are known analytically. Several other benchmark examples are considered that allow us the assess the performance of Lagrangian descriptors in revealing invariant tori and regions of shear. Throughout the paper “side-by-side” comparisons of the performance of Lagrangian descriptors with both finite time Lyapunov exponents (FTLEs) and finite time averages of certain components of the vector field (“time averages”) are carried out and discussed. In all cases Lagrangian descriptors are shown to be both more accurate and computationally efficient than these methods. We also perform computations for an explicitly three dimensional, aperiodically time-dependent vector field and an aperiodically time dependent vector field defined as a data set. Comparisons with FTLEs and time averages for these examples are also carried out, with similar conclusions as for the benchmark examples.

Remarks on blow up time for solutions of a nonlinear diffusion system with time dependent coefficients

2000 Mathematics Subject Classification: 35K55, 35K60.

Monitoring time-dependent deformation patterns through geodetic techniques

In this thesis we focus on the analysis and interpretation of time dependent deformations recorded through different geodetic methods. Firstly, we apply a variational Bayesian Independent Component Analysis (vbICA) technique to GPS daily displacement solutions, to separate the postseismic deformation that followed the mainshocks of the 2016-2017 Central Italy seismic sequence from the other, hydrological, deformation sources. By interpreting the signal associated with the postseismic relaxation, we model an afterslip distribution on the faults involved by the mainshocks consistent with the co-seismic models available in literature. We find evidences of aseismic slip on the Paganica fault, responsible for the Mw 6.1 2009 L’Aquila earthquake, highlighting the importance of aseismic slip and static stress transfer to properly model the recurrence of earthquakes on nearby fault segments. We infer a possible viscoelastic relaxation of the lower crust as a contributing mechanism to the postseismic displacements. We highlight the importance of a proper separation of the hydrological signals for an accurate assessment of the tectonic processes, especially in cases of mm-scale deformations. Contextually, we provide a physical explanation to the ICs associated with the observed hydrological processes. In the second part of the thesis, we focus on strain data from Gladwin Tensor Strainmeters, working on the instruments deployed in Taiwan. We develop a novel approach, completely data driven, to calibrate these strainmeters. We carry out a joint analysis of geodetic (strainmeters, GPS and GRACE products) and hydrological (rain gauges and piezometers) data sets, to characterize the hydrological signals in Southern Taiwan. Lastly, we apply the calibration approach here proposed to the strainmeters recently installed in Central Italy. We provide, as an example, the detection of a storm that hit the Umbria-Marche regions (Italy), demonstrating the potential of strainmeters in following the dynamics of deformation processes with limited spatio-temporal signature