Self-reporting and screening: Data with right-censored, left-censored, and complete observations.

We consider survival data that combine three types of observations: uncensored, right-censored, and left-censored. Such data arises from screening a medical condition, in situations where self-detection arises naturally. Our goal is to estimate the failure-time distribution, based on these three observation types. We propose a novel methodology for distribution estimation using both semiparametric and nonparametric techniques. We then evaluate the performance of these estimators via simulated data. Finally, as a case study, we estimate the patience of patients who arrive at an emergency department and wait for treatment. Three categories of patients are observed: those who leave the system and announce it, and thus their patience time is observed; those who get service and thus their patience time is right-censored by the waiting time; and those who leave the system without announcing it. For this third category, the patients' absence is revealed only when they are called to service, which is after they have already left; formally, their patience time is left-censored. Other applications of our proposed methodology are discussed.

A quantile regression model for failure-time data with time-dependent covariates.

Since survival data occur over time, often important covariates that we wish to consider also change over time. Such covariates are referred as time-dependent covariates. Quantile regression offers flexible modeling of survival data by allowing the covariates to vary with quantiles. This article provides a novel quantile regression model accommodating time-dependent covariates, for analyzing survival data subject to right censoring. Our simple estimation technique assumes the existence of instrumental variables. In addition, we present a doubly-robust estimator in the sense of Robins and Rotnitzky (1992, Recovery of information and adjustment for dependent censoring using surrogate markers. In: Jewell, N. P., Dietz, K. and Farewell, V. T. (editors), AIDS Epidemiology. Boston: Birkhaäuser, pp. 297-331.). The asymptotic properties of the estimators are rigorously studied. Finite-sample properties are demonstrated by a simulation study. The utility of the proposed methodology is demonstrated using the Stanford heart transplant dataset.

Fear and C-reactive protein cosynergize annual pulse increases in healthy adults.

Recent international terror outbreaks notably involve long-term mental health risks to the exposed population, but whether physical health risks are also anticipated has remained unknown. Here, we report fear of terror-induced annual increases in resting heart rate (pulse), a notable risk factor of all-cause mortality. Partial least squares analysis based on 325 measured parameters successfully predicted annual pulse increases, inverse to the expected age-related pulse decline, in approximately 4.1% of a cohort of 17,380 apparently healthy active Israeli adults. Nonbiased hierarchical regression analysis among 27 of those parameters identified pertinent fear of terror combined with the inflammatory biomarker C-reactive protein as prominent coregulators of the observed annual pulse increases. In comparison, basal pulse primarily depended on general physiological parameters and reduced cholinergic control over anxiety and inflammation, together indicating that consistent exposure to terror threats ignites fear-induced exacerbation of preexisting neuro-immune risks of all-cause mortality.

Longitudinal Position and Cancer Risk in the United States Revisited.

The debate over daylight saving time (DST) has surged, with interests in the effects of sunlight exposure on health. Prior studies simulated DST and standard time conditions by analyzing different locations within time zones and neighboring areas across time zone borders. We analyzed cancer incidence rates from various longitudinal positions within time zones and at time zone borders in the contiguous United States. Using data from State Cancer Profiles (2016-2020), we analyzed total cancer of 19 types and specific rates for eight cancers, adjusted for age and includes all demographics. log-linear regression is used to replicate a previous study, and spatial regression models are employed to explore discontinuities at borders. Cancer rate differences lack statistical significance within time zones and near borders for total cancer and most individual cancers. Exceptions included breast, prostate, and liver and bile duct cancers, which exhibited significant relationships with relative position at the 95% significance level. Breast and liver and bile duct cancers saw decreases, while prostate cancer incidence increased from west to east within time zones. Relative position does not have a significant impact on cancer incidence, hence cancer development in general. Isolated exceptions may warrant further investigation as more data become available. Our findings challenge prior research, revealing numerous inconsistencies. These disparities urge a reconsideration of the potential disparities in human health associated with DST and standard time. They offer insights contribute to the ongoing discussion surrounding the retention or abandonment of DST. SIGNIFICANCE: In this article, we investigate the relation between the epidemiology of cancer incidence in the United States and time zone-related longitudinal positions. Our results differ from previous research, which were based on a subset of our data, and show that the time zone effect on cancer incidence rate is not significant. Our research provides implications on the implementation of DST by suggesting that there is no cancer-risk associated reason to prefer one time over the other. Our study also uses regression discontinuity design using natural splines, a more advanced statistical method, to increase robustness of our result. Our findings challenge prior research, revealing numerous inconsistencies. These disparities urge a reconsideration of the potential disparities in human health associated with DST and standard time. They offer insights contribute to the ongoing discussion surrounding the retention or abandonment of DST.

Levodopa and subthalamic deep brain stimulation responses are not congruent.

There is a consensus that in Parkinson's disease, the extent of preoperative levodopa responsiveness predicts the efficacy of subthalamic nucleus deep brain stimulation (STN DBS). However, this may be the result of statistical methods and primary assumptions. We were able to reproduce previously published correlation results on our data (N = 49 patients). Yet, these same results were demonstrated even after random shuffling of our data. Notably, we did not observe a correlation between STN DBS efficacy and preoperative levodopa responsiveness when using their respective baselines and fractional scores of motor improvement. Furthermore, postoperative responses were not limited by preoperative scores, with tremor demonstrating the greatest discrepancy. We conclude that preoperative levodopa responsiveness does not predict or limit the outcome of STN DBS. These results imply different therapeutic mechanisms for levodopa and STN DBS and therefore question the validity of using substantial preoperative levodopa responsiveness as a selection criterion for STN DBS.

Functional correlations between neighboring neurons in the primate globus pallidus are weak or nonexistent.

The anatomical structure of the basal ganglia displays topographical organization and massive funneling of neuronal projections toward the globus pallidus as well as an axonal collateral system within this nucleus. This structure suggests the formation of correlations between the spiking activities of pallidal cells. Nevertheless, previous studies of remote neurons in the pallidum have reported uncorrelated spiking activity. These correlation results may be challenged, because remote pallidal neurons may be located in different pallidal territories. To further test the independence of pallidal activity, we studied the spiking activity of neighboring pairs recorded by the same electrodes. A narrow peak dominated the correlations of all pairs of neurons recorded on the same electrode. This type of peak is classically interpreted as a sign of strong common input. However, recent mathematical analysis shows that such peaks may derive from a technical inability to detect overlapping spikes by spike-sorting techniques. A long-term shallow trough in the correlation of neighboring neurons may also result from the same effect, which we have termed the "shadowing effect." A comparison of the expected shadowing effect with the actual correlations suggests that no real correlations exist between 93.9% of neighboring pallidal pairs. The remaining 6.1% of the pairs display symmetric long-term positive correlations centered on time 0. Thus, functional interactions between neighboring pallidal neurons do not display any significant differences from the interactions between physically remote neurons in this brain area. Moreover, the combination of anatomical data and current physiological results suggests an active decorrelating process performed in the basal ganglia.

Balance of increases and decreases in firing rate of the spontaneous activity of basal ganglia high-frequency discharge neurons.

Most neurons in the external and internal segments of the globus pallidus and the substantia nigra pars reticulata (GPe, GPi, and SNr) are characterized by a high-frequency discharge (HFD) rate (50-80 Hz) that, in most GPe neurons, is also interrupted by pauses. Almost all (approximately 90%) of the synaptic inputs to these HFD neurons are GABAergic and inhibitory. Nevertheless, their responses to behavioral events are usually dominated by increases in discharge rate. Additionally, there are no reports of prolonged bursts in the spontaneous activity of these cells that could reflect their disinhibition by GPe pauses. We recorded the spontaneous activity of 385 GPe, GPi, and SNr HFD neurons during a quiet-wakeful state from two monkeys. We developed three complementary methods to quantify the balance of increases and decreases in the spontaneous discharge of HFD neurons and validated them by simulations. Unlike the behavioral evoked responses, the spontaneous activity of pallidal and SNr neurons is not dominated by increases. Moreover, the activity of basal ganglia neurons does not include bursts that could reflect disinhibition by the spontaneous pauses of GPe neurons. These findings suggest that the discharge increase/decrease balance during a quiet-wakeful state better reflects the inhibitory input of the HFD basal ganglia neurons than during responses to behavioral events; however, the GPe pauses are not echoed by comparable bursts either in the GPe or in the output nuclei. Changes in the excitatory drive of these structures (e.g., during behavioral activity) thus may lead to a remarkable change in this balance.

Local shuffling of spike trains boosts the accuracy of spike train spectral analysis.

Spectral analysis of neuronal spike trains is an important tool in understanding the characteristics of neuronal activity by providing insights into normal and pathological periodic oscillatory phenomena. However, the refractory period creates high-frequency modulations in spike-train firing rate because any rise in the discharge rate causes a descent in subsequent time bins, leading to multifaceted modifications in the structure of the spectrum. Thus the power spectrum of the spiking activity (autospectrum) displays elevated energy in high frequencies relative to the lower frequencies. The spectral distortion is more dominant in neurons with high firing rates and long refractory periods and can lead to reduced identification of low-frequency oscillations (such as the 5- to 10-Hz burst oscillations typical of Parkinsonian basal ganglia and thalamus). We propose a compensation process that uses shuffling of interspike intervals (ISIs) for reliable identification of oscillations in the entire frequency range. This compensation is further improved by local shuffling, which preserves the slow changes in the discharge rate that may be lost in global shuffling. Cross-spectra of pairs of neurons are similarly distorted regardless of their correlation level. Consequently, identification of low-frequency synchronous oscillations, even for two neurons recorded by a single electrode, is improved by ISI shuffling. The ISI local shuffling is computed with confidence limits that are based on the first-order statistics of the spike trains, thus providing a reliable estimation of auto- and cross-spectra of spike trains and making it an optimal tool for physiological studies of oscillatory neuronal phenomena.

Acetylcholinesterase/paraoxonase genotype and expression predict anxiety scores in Health, Risk Factors, Exercise Training, and Genetics study.

Anxiety involves complex, incompletely understood interactions of genomic, environmental, and experience-derived factors, and is currently being measured by psychological criteria. Here, we report previously nonperceived interrelationships between expression variations and nucleotide polymorphisms of the chromosome 7q21-22 acetylcholinesterase-paraoxonase 1 (ACHE-PON1) locus with the trait- and state-anxiety measures of 461 healthy subjects from the Health, Risk Factors, Exercise Training, and Genetics Family Study. The AChE protein controls the termination of the stress-enhanced acetylcholine signaling, whereas the PON protein displays peroxidase-like activity, thus protecting blood proteins from oxidative stress damages. Serum AChE and PON enzyme activities were both found to be affected by demographic parameters, and showed inverse, reciprocal associations with anxiety measures. Moreover, the transient scores of state anxiety and the susceptibility score of trait anxiety both appeared to be linked to enzyme activities. This finding supported the notion of corresponding gene expression relationships. Parallel polymorphisms in the ACHE and PON1 genes displayed apparent associations with both trait- and state-anxiety scores. Our findings indicate that a significant source of anxiety feelings involves inherited and acquired parameters of acetylcholine regulation that can be readily quantified, which can help explaining part of the human variance for state and trait anxiety.