A sequential Cox approach for estimating the causal effect of treatment in the presence of time-dependent confounding applied to data from the Swiss HIV Cohort Study

When estimating the effect of treatment on HIV using data from observational studies, standard methods may produce biased estimates due to the presence of time-dependent confounders. Such confounding can be present when a covariate, affected by past exposure, is both a predictor of the future exposure and the outcome. One example is the CD4 cell count, being a marker for disease progression for HIV patients, but also a marker for treatment initiation and influenced by treatment. Fitting a marginal structural model (MSM) using inverse probability weights is one way to give appropriate adjustment for this type of confounding. In this paper we study a simple and intuitive approach to estimate similar treatment effects, using observational data to mimic several randomized controlled trials. Each 'trial' is constructed based on individuals starting treatment in a certain time interval. An overall effect estimate for all such trials is found using composite likelihood inference. The method offers an alternative to the use of inverse probability of treatment weights, which is unstable in certain situations. The estimated parameter is not identical to the one of an MSM, it is conditioned on covariate values at the start of each mimicked trial. This allows the study of questions that are not that easily addressed fitting an MSM. The analysis can be performed as a stratified weighted Cox analysis on the joint data set of all the constructed trials, where each trial is one stratum. The model is applied to data from the Swiss HIV cohort study.

Blood component ratios in massively transfused, blunt trauma patients--a time-dependent covariate analysis

This study evaluated critical thresholds for fresh frozen plasma (FFP) and platelet (PLT) to packed red blood cell (PRBC) ratios and determined the impact of high FFP:PRBC and PLT:PRBC ratios on outcomes in patients requiring massive transfusion (MT).

THE RESONATE-AND-FIRE NEURON: TIME DEPENDENT AND FREQUENCY SELECTIVE NEURONS IN NEURAL NETWORKS

The means through which the nervous system perceives its environment is one of the most fascinating questions in contemporary science. Our endeavors to comprehend the principles of neural science provide an instance of how biological processes may inspire novel methods in mathematical modeling and engineering. The application ofmathematical models towards understanding neural signals and systems represents a vibrant field of research that has spanned over half a century. During this period, multiple approaches to neuronal modeling have been adopted, and each approach is adept at elucidating a specific aspect of nervous system function. Thus while bio-physical models have strived to comprehend the dynamics of actual physical processes occurring within a nerve cell, the phenomenological approach has conceived models that relate the ionic properties of nerve cells to transitions in neural activity. Further-more, the field of neural networks has endeavored to explore how distributed parallel processing systems may become capable of storing memory. Through this project, we strive to explore how some of the insights gained from biophysical neuronal modeling may be incorporated within the field of neural net-works. We specifically study the capabilities of a simple neural model, the Resonate-and-Fire (RAF) neuron, whose derivation is inspired by biophysical neural modeling. While reflecting further biological plausibility, the RAF neuron is also analytically tractable, and thus may be implemented within neural networks. In the following thesis, we provide a brief overview of the different approaches that have been adopted towards comprehending the properties of nerve cells, along with the framework under which our specific neuron model relates to the field of neuronal modeling. Subsequently, we explore some of the time-dependent neurocomputational capabilities of the RAF neuron, and we utilize the model to classify logic gates, and solve the classic XOR problem. Finally we explore how the resonate-and-fire neuron may be implemented within neural networks, and how such a network could be adapted through the temporal backpropagation algorithm.

Prognostic impact of lymph node ratio outperforms positive lymph nodes and lymph nodes harvested: a time-dependent analysis in mismatch repair-proficient and –deficient colrectal cancers

Objective: We compare the prognostic strength of the lymph node ratio (LNR), positive lymph nodes (+LNs) and collected lymph nodes (LNcoll) using a time-dependent analysis in colorectal cancer patients stratified by mismatch repair (MMR) status. Method: 580 stage III-IV patients were included. Multivariable Cox regression analysis and time-dependent receiver operating characteristic (tROC) curve analysis were performed. The Area under the Curve (AUC) over time was compared for the three features. Results were validated on a second cohort of 105 stage III-IV patients. Results: The AUC for the LNR was 0.71 and outperformed + LNs and LNcoll by 10–15 % in both MMR-proficient and deficient cancers. LNR and + LNs were both significant (p<0.0001) in multivariable analysis but the effect was considerably stronger for the LNR [LNR: HR=5.18 (95 % CI: 3.5–7.6); +LNs=1.06 (95 % CI: 1.04–1.08)]. Similar results were obtained for patients with >12 LNcoll. An optimal cut off score for LNR=0.231 was validated on the second cohort (p<0.001). Conclusion: The LNR outperforms the + LNs and LNcoll even in patients with >12 LNcoll. Its clinical value is not confounded by MMR status. A cut-of score of 0.231 may best stratify patients into prognostic subgroups and could be a basis for the future prospective analysis of the LNR.

Increased sensitivity in mapping task demand in visuospatial processing using reaction-time-dependent hemodynamic response predictors in rapid event-related fMRI

Searching for the neural correlates of visuospatial processing using functional magnetic resonance imaging (fMRI) is usually done in an event-related framework of cognitive subtraction, applying a paradigm comprising visuospatial cognitive components and a corresponding control task. Besides methodological caveats of the cognitive subtraction approach, the standard general linear model with fixed hemodynamic response predictors bears the risk of being underspecified. It does not take into account the variability of the blood oxygen level-dependent signal response due to variable task demand and performance on the level of each single trial. This underspecification may result in reduced sensitivity regarding the identification of task-related brain regions. In a rapid event-related fMRI study, we used an extended general linear model including single-trial reaction-time-dependent hemodynamic response predictors for the analysis of an angle discrimination task. In addition to the already known regions in superior and inferior parietal lobule, mapping the reaction-time-dependent hemodynamic response predictor revealed a more specific network including task demand-dependent regions not being detectable using the cognitive subtraction method, such as bilateral caudate nucleus and insula, right inferior frontal gyrus and left precentral gyrus.

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.

Concentration- and time-dependent effects of the synthetic estrogen, 17alpha-ethinylestradiol, on reproductive capabilities of the zebrafish, Danio rerio

Partial or full life-cycle tests are needed to assess the potential of endocrine-disrupting compounds (EDCs) to adversely affect development and reproduction of fish. Small fish species such as zebrafish, Danio rerio, are under consideration as model organisms for appropriate test protocols. The present study examines how reproductive effects resulting from exposure of zebrafish to the synthetic estrogen 17alpha-ethinylestradiol (EE2) vary with concentration (0.05 to 10 ng EE2 L(-1), nominal), and with timing/duration of exposure (partial life-cycle, full life-cycle, and two-generation exposure). Partial life-cycle exposure of the parental (F1) generation until completion of gonad differentiation (0-75 d postfertilization, dpf) impaired juvenile growth, time to sexual maturity, adult fecundity (egg production/female/day), and adult fertilization success at 1.1 ng EE2 L(-1) and higher. Lifelong exposure of the F1 generation until 177 dpf resulted in lowest observed effect concentrations (LOECs) for time to sexual maturity, fecundity, and fertilization success identical to those of the developmental test (0-75 dpf), but the slope of the concentration-response curve was steeper. Reproduction of zebrafish was completely inhibited at 9.3 ng EE2 L(-1), and this was essentially irreversible as a 3-mo depuration restored fertilization success to only a very low rate. Accordingly, elevated endogenous vitellogenin (VTG) synthesis and degenerative changes in gonad morphology persisted in depurated zebrafish. Full life-cycle exposure of the filial (F2) generation until 162 dpf impaired growth, delayed onset of spawning and reduced fecundity and fertilization success at 2.0 ng EE2 L(-1). In conclusion, results show that the impact of estrogenic agents on zebrafish sexual development and reproductive functions as well as the reversibility of effects, varies with exposure concentration (reversibility at < or = 1.1 ng EE2 L(-1) and irreversibility at 9.3 ng EE2 L(-1)), and between partial and full life-cycle exposure (exposure to 10 ng EE2 L(-1) during critical period exerted no permanent effect on sexual differentiation, but life-cycle exposure did).

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 hierarchical organization of spatial working memory: a transcranial magnetic stimulation study

The performance of memory-guided saccades with two different delays (3 and 30 s of memorization) was studied in seven healthy subjects. Double-pulse transcranial magnetic stimulation (dTMS) with an interstimulus interval of 100 ms was applied over the right dorsolateral prefrontal cortex (DLPFC) early (1 s after target presentation) and late (28 s after target presentation). Early stimulation significantly increased in both delays the percentage of error in amplitude (PEA) of contralateral memory-guided saccades compared to the control experiment without stimulation. dTMS applied late in the delay had no significant effect on PEA. Furthermore, we found a significantly smaller effect of early stimulation in the long-delay paradigm. These results suggest a time-dependent hierarchical organization of the spatial working memory with a functional dominance of DLPFC during the early memorization, independent from the memorization delay. For a long memorization delay, however, working memory seems to have an additional, DLPFC-independent component.

Radiation metabolomics. 2. Dose- and time-dependent urinary excretion of deaminated purines and pyrimidines after sublethal gamma-radiation exposure in mice

Gamma-radiation exposure of humans is a major public health concern as the threat of terrorism and potential hostile use of radiological devices increases worldwide. We report here the effects of sublethal gamma-radiation exposure on the mouse urinary metabolome determined using ultra-performance liquid chromatography-coupled time-of-flight mass spectrometry-based metabolomics. Five urinary biomarkers of sublethal radiation exposure that were statistically significantly elevated during the first 24 h after exposure to doses ranging from 1 to 3 Gy were unequivocally identified by tandem mass spectrometry. These are deaminated purine and pyrimidine derivatives, namely, thymidine, 2'-deoxyuridine, 2'-deoxyxanthosine, xanthine and xanthosine. Furthermore, the aminopyrimidine 2'-deoxycytidine appeared to display reduced urinary excretion at 2 and 3 Gy. The elevated biomarkers displayed a time-dependent excretion, peaking in urine at 8-12 h but returning to baseline by 36 h after exposure. It is proposed that 2'-deoxyuridine and 2'-deoxyxanthosine arise as a result of gamma irradiation by nitrosative deamination of 2'-deoxycytidine and 2'-deoxyguanosine, respectively, and that this further leads to increased synthesis of thymidine, xanthine and xanthosine. The urinary excretion of deaminated purines and pyrimidines, at the expense of aminopurines and aminopyrimidines, appears to form the core of the urinary radiation metabolomic signature of mice exposed to sublethal doses of ionizing radiation.

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.