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Interval-censored data occur in a study where the exact event time of each participant is not observed but it is known to be within a certain time interval. Multiple tests were proposed for such data, including the logrank test by Sun, the proportional hazard test by Finkelstein, and the Wilcoxon-type test by Peto and Peto. We propose sample size calculations based on these tests for a parallel one-stage or two-stage design. When the proportional hazard assumption is met, the proportional hazard test and the logrank test need smaller sample sizes than the Wilcoxon-type test, and the sample size savings are substantial. But this trend is reversed when the proportional hazard assumption does not hold, and the sample size savings using the Wilcoxon-type test are sizable. An example from a lung cancer clinical trial is used to illustrate the application of the proposed sample size calculations. [ABSTRACT FROM AUTHOR]

The elastic network models (ENMs)are known as representative coarse-grained models to capture essential dynamics of proteins. Due to simple designs of the force constants as a decay with spatial distances of residue pairs in many previous studies, there is still much room for the improvement of ENMs. In this article, we directly computed the force constants with the inverse covariance estimation using a ridge-type operater for the precision matrix estimation (ROPE)on a large-scale set of NMR ensembles. Distance-dependent statistical analyses on the force constants were further comprehensively performed in terms of several paired types of sequence and structural information, including secondary structure, relative solvent accessibility, sequence distance and terminal. Various distinguished distributions of the mean force constants highlight the structural and sequential characteristics coupled with the inter-residue cooperativity beyond the spatial distances. We finally integrated these structural and sequential characteristics to build novel ENM variations using the particle swarm optimization for the parameter estimation. The considerable improvements on the correlation coefficient of the mean-square fluctuation and the mode overlap were achieved by the proposed variations when compared with traditional ENMs. This study opens a novel way to develop more accurate elastic network models for protein dynamics. [ABSTRACT FROM AUTHOR]

Objectives: Determine, through video reviews, how often concussions occur in combat sport matches, what influence they have on the outcome, and how well non-physician personnel can be trained to recognize concussions. Methods: This is a retrospective video analysis by an 8-person panel of 60 professional fights (30 boxing and 30 mixed martial arts). Through video review, physician and non-physician personnel recorded details about each probable concussion and determined if and when they would have stopped the fight compared to the official stoppage time. Results: A concussion was recorded in 47/60 fights. The mean number of concussions per minute of fight time was 0.061 (0.047 for boxers and 0.085 for MMA). When stratifying by outcome of the bout, the mean number of concussions per minute for the winner was 0.010 compared to the loser at 0.111 concussions per minute. The fighter that sustained the first concussion ultimately lost 98% of the time. The physician and non-physician raters had high agreement regarding the number of concussions that occurred to each fighter per match. The physician raters judged that 24 of the 60 fights (11 boxing [37%]; 13 MMA [43%]) should have been stopped sooner than what occurred. Conclusion: Recognizing that the concussions often occur in combat sport matches, that the losing fighter almost always is concussed first and tends to sustain more concussions during the fight, along with the demonstration that non-physician personnel can be taught to recognize concussion, may guide policy changes that improve brain health in combat sports. [ABSTRACT FROM AUTHOR]

Repeated data are increasingly collected in studies to investigate the trajectory of change in measurements over time. Determining a link between one repeated measurement with another that is considered as the biomarker for disease progression, may provide a new target for drug development. When a third variable is associated with one of the two measurements, partial correlation after eliminating the effect of that variable is able to provide reliable estimate for association as compared to the existing raw correlation for repeated data. We propose using linear regression models to compute residuals by modeling a relationship between each measurement and a third variable. The computed residuals are then used in a linear mixed model (implemented by SAS Proc Mixed) to compute partial correlation for repeated data. Alternatively, the partial correlation may be computed as the average of partial correlations at each visit. We provide two real examples to illustrate the application of the proposed partial correlation and conduct extensive numerical studies to evaluate the proposed partial correlation coefficients. [ABSTRACT FROM AUTHOR]

Repeated measures designs are widely used in practice to increase power, reduce sample size, and increase efficiency in data collection. Correlation between repeated measurements is one of the first research questions that needs to be addressed in a repeated-measure study. In addition to an estimate for correlation, confidence interval should be computed and reported for statistical inference. The asymptotic interval based on the delta method is traditionally calculated due to its simplicity. However, this interval is often criticized for its unsatisfactory performance with regards to coverage and interval width. Bootstrap could be utilized to reduce the interval width, and the widely used bootstrap intervals include the percentile interval, the bias-corrected interval, and the bias-corrected with acceleration interval. Wilcox (Comput Stat Data Anal 22:89–98,1996) suggested a modified percentile interval with the interval levels adjusted by sample size to have the coverage probability close to the nominal level. For a study with repeated measures, more parameters in addition to sample size would affect the coverage probability. For these reasons, we propose modifying the percentiles in the percentile interval to guarantee the coverage probability based on simulation studies. We analyze the correlation between imaging volumes and memory scores from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study to illustrate the application of the considered intervals. The proposed interval is exact with the coverage probability guaranteed, and is recommended for use in practice. [ABSTRACT FROM AUTHOR]

Cognitive decline and mood symptoms are common in Parkinson's disease (PD). Reductions in striatal dopaminergic binding have been associated with worse cognition and mood. We investigated whether this association persists throughout the disease progression in newly diagnosed PD. Four-year data from Parkinson's Progression Markers Initiative (PPMI) were used. Groups consisted of left and right limb dominantly affected PD patients, and controls. Longitudinal relationships between cognition, mood and striatal binding ratios were assessed by repeated measures correlations. Reduced binding was associated with general cognitive decline in controls, reduced processing speed and increased mood symptoms in PD. Anxiety was associated with striatum only in left limb dominantly affected PD. Dominantly affected limb side did not impact striatum and cognition association. There are longitudinal associations between striatum, processing speed and anxiety. Dopamine transporter availability imaging may have some prognostic value for cognition and mood in PD. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the sex differences in cognitive course over 4 years in Parkinson's disease (PD) patients with and without mild cognitive impairment (MCI) compared to controls. Methods: Four-year longitudinal cognitive scores of 257 cognitively intact PD, 167 PD-MCI, and 140 controls from the Parkinson's Progression Markers Initiative were included. Longitudinal scores of men and women, and PD with and without MCI were compared. Results: Women had better verbal memory, men had better visuospatial function. There was no interaction between sex, diagnostic group, and/or time (4-year follow-up period). Conclusions: Sex differences in cognitive course in de novo PD are similar to healthy aging. Cognitive decline rates in PD with and without MCI are similar for the first 4 years of PD. [ABSTRACT FROM AUTHOR]

It has long been established that fighting sports such as boxing and mixed martial arts can lead to head injury. Prior work from this group on the Professional Fighters Brain Health Study found that exposure to repetitive head impacts is associated with lower brain volumes and decreased processing speed in fighters. Current and previously licensed professional fighters were recruited, divided into active and retired cohorts, and matched with a control group that had no prior experience in sports with likely head trauma. This study examined the relationship between age of first exposure (AFE) to fighting sports and brain structure (MRI regional volume), cognitive performance (CNS Vital Signs, iComet C3), and clinical neuropsychiatric symptoms (PHQ-9, Barratt Impulsiveness Scale). Brain MRI data showed significant correlations between earlier AFE and smaller bilateral hippocampal and posterior corpus callosum volumes for both retired and active fighters. Earlier AFE in active fighters was correlated with decreased processing speed and decreased psychomotor speed. Retired fighters showed a correlation between earlier AFE and higher measures of depression and impulsivity. Overall, the results help to inform clinicians, governing bodies, parents, and athletes of the risks associated with beginning to compete in fighting sports at a young age. [ABSTRACT FROM AUTHOR]