Calibration of the biotrainer pro activity monitor in children

The unique physical and movement characteristics of children necessitate the development of accelerometer equations and cut points that are population specific. The purpose of this study is to develop an ecologically valid cut point for the Biotrainer Pro monitor that reflects a threshold for moderate-intensity physical activity in elementary school children. A sample of 30 children (ages 8-12) wore a Biotrainer monitor while completing a series of 7 movement tasks (calibration phase) and while participating in an organized group activity (cross-validation phase). Videotapes from each session were processed using a computerized direct-observation technique to provide a criterion measure of physical activity. Analyses involved the use of mixed-model regression and receiver operator characteristic (ROC) curves. The results indicated that a cut point of 4 counts/min provides the optimal balance between the related needs for sensitivity (accurately detecting activity) and specificity (limiting misclassification of activity as inactivity). Results with the cross-validation data demonstrated that this value yielded the best overall kappa (.58) and a high classification agreement (84%) for activity determination. The specificity of 93% demonstrates that the proposed cut point can accurately detect activity; however, the lower sensitivity value of 61% suggests that some minutes of activity might be incorrectly classified as inactivity. The cut point of 4 counts/min provides an ecologically valid cut point to capture physical activity in children using the Biotrainer Pro activity monitor.

Physical activity correlates in adolescent girls who differ by weight status

Objective This study compared correlates of physical activity (PA) among African-American and white girls of different weight groups to guide future interventions. Research Methods and Procedures Participants were 1015 girls (mean age, 14.6 years; 45% African-American) from 12 high schools in South Carolina who served as control subjects for a school-based intervention. Post-intervention measures obtained at the end of ninth grade were used. PA was measured using the Three-Day PA Recall, and a questionnaire measured social-cognitive and environmental variables thought to mediate PA. Height and weight were measured, and BMI was calculated. Girls were stratified by race and categorized into three groups, based on BMI percentiles for girls from CDC growth charts: normal (BMI < 85th percentile), at risk (BMI, 85th to 94th percentile), and overweight (BMI ≥ 95th percentile). Girls were further divided into active and low-active groups, based on a vigorous PA standard (average of one or more 30-minute blocks per day per 3-day period). Mixed-model ANOVA was used to compare factors among groups, treating school as a random effect Results None of the social-cognitive or environmental variables differed by weight status for African-American or white girls. Perceived behavioral control and sports team participation were significantly higher in girls who were more active, regardless of weight or race group. In general, social-cognitive variables seem to be more related to activity in white girls, whereas environmental factors seem more related to activity in African-American girls. Discussion PA interventions should be tailored to the unique needs of girls based on PA levels and race, rather than on weight status alone.

Sequential monitoring of hospital adverse events when control charts fail : the example of fall injuries in hospitals

Objective To evaluate methods for monitoring monthly aggregated hospital adverse event data that display clustering, non-linear trends and possible autocorrelation. Design Retrospective audit. Setting The Northern Hospital, Melbourne, Australia. Participants 171,059 patients admitted between January 2001 and December 2006. Measurements The analysis is illustrated with 72 months of patient fall injury data using a modified Shewhart U control chart, and charts derived from a quasi-Poisson generalised linear model (GLM) and a generalised additive mixed model (GAMM) that included an approximate upper control limit. Results The data were overdispersed and displayed a downward trend and possible autocorrelation. The downward trend was followed by a predictable period after December 2003. The GLM-estimated incidence rate ratio was 0.98 (95% CI 0.98 to 0.99) per month. The GAMM-fitted count fell from 12.67 (95% CI 10.05 to 15.97) in January 2001 to 5.23 (95% CI 3.82 to 7.15) in December 2006 (p<0.001). The corresponding values for the GLM were 11.9 and 3.94. Residual plots suggested that the GLM underestimated the rate at the beginning and end of the series and overestimated it in the middle. The data suggested a more rapid rate fall before 2004 and a steady state thereafter, a pattern reflected in the GAMM chart. The approximate upper two-sigma equivalent control limit in the GLM and GAMM charts identified 2 months that showed possible special-cause variation. Conclusion Charts based on GAMM analysis are a suitable alternative to Shewhart U control charts with these data.

Morphometric stability of the corneal subbasal nerve plexus in healthy individuals a 3-year longitudinal study using corneal confocal microscopy

Purpose We examined the age-dependent alterations and longitudinal course of subbasal nerve plexus (SNP) morphology in healthy individuals. Methods Laser-scanning corneal confocal microscopy, ocular screening, and health and metabolic assessment were performed on 64 healthy participants at baseline and at 12-month intervals for 3 years. At each annual visit, eight central corneal images of the SNP were selected and analyzed using a fully-automated analysis system to quantify corneal nerve fiber length (CNFL). Two linear mixed model approaches were fitted to examine the relationship between age and CNFL, and the longitudinal changes of CNFL over three years. Results At baseline, mean age was 51.9 ± 14.7 years. The cohort was sex balanced (χ2 = 0.56, P = 0.45). Age (t = 1.6, P = 0.12) and CNFL (t = -0.50, P = 0.62) did not differ between sexes. A total of 52 participants completed the 36-month visit and 49 participants completed all visits. Age had a significant effect on CNFL (F1,33 = 5.67, P = 0.02) with a linear decrease of 0.05 mm/mm2 in CNFL per one year increase in age. No significant change in CNFL was observed over the 36-month period (F1,55 = 0.69, P = 0.41). Conclusions The CNFL showed a stable course over a 36-month period in healthy individuals, although there was a slight linear reduction in CNFL with age. The findings of this study have implications for understanding the time-course of the effect of pathology and surgical or therapeutic interventions on the morphology of the SNP, and serves to confirm the suitability of CNFL as a screening/monitoring marker for peripheral neuropathies.

Natural history of corneal nerve morphology in mild neuropathy associated with type 1 diabetes : Development of a potential measure of diabetic peripheral neuropathy

Purpose To investigate longitudinal changes of subbasal nerve plexus (SNP) morphology and its relationship with conventional measures of neuropathy in individuals with diabetes. Methods A cohort of 147 individuals with type 1 diabetes and 60 age-balanced controls underwent detailed assessment of clinical and metabolic factors, neurologic deficits, quantitative sensory testing, nerve conduction studies and corneal confocal microscopy at baseline and four subsequent annual visits. The SNP parameters included corneal nerve fiber density (CNFD), branch density (CNBD) and fiber length (CNFL) and were quantified using a fully-automated algorithm. Linear mixed models were fitted to examine the changes in corneal nerve parameters over time. Results At baseline, 27% of the participants had mild diabetic neuropathy. All SNP parameters were significantly lower in the neuropathy group compared to controls (P<0.05). Overall, 89% of participants examined at baseline also completed the final visit. There was no clinically significant change to health and metabolic parameters and neuropathy measures from baseline to the final visit. Linear mixed model revealed a significant linear decline of CNFD (annual change rate, -0.9 nerve/mm2, P=0.01) in the neuropathy group compared to controls, which was associated with age (β=-0.06, P=0.04) and duration of diabetes (β=-0.08, P=0.03). In the neuropathy group, absolute changes of CNBD and CNFL showed moderate correlations with peroneal conduction velocity and cold sensation threshold, respectively (rs, 0.38 and 0.40, P<0.05). Conclusion This study demonstrates dynamic small fiber damage at the SNP, thus providing justification for our ongoing efforts to establish corneal nerve morphology as an appropriate adjunct to conventional measures of DPN.

Pituitary volume and early treatment response in drug-naïve first-episode psychosis patients

BACKGROUND: An early response to antipsychotic treatment in patients with psychosis has been associated with a better course and outcome. However, factors that predict treatment response are not well understood. The onset of schizophrenia and related disorders has been associated with increased levels of stress and hyper-activation of the hypothalamic-pituitary-adrenal (HPA) axis. This study examined whether pituitary volume at the onset of psychosis may be a potential predictor of early treatment response in first-episode psychosis (FEP) patients. METHODS: We investigated the relationship between baseline pituitary volume and symptomatic treatment response over 12 weeks using mixed model analysis in a sample of 42 drug-naïve or early treated FEP patients who participated in a controlled dose-finding study of quetiapine fumarate. Logistic regression was used to examine predictors of treatment response. Pituitary volume was measured from magnetic resonance imaging scans that were obtained upon entry into the trial. RESULTS: Larger pituitary volume was associated with less improvement in overall psychotic symptoms (Brief Psychiatric Rating Scale (BPRS) P=0.031) and positive symptoms (BPRS positive symptom subscale P=0.010). Regardless of gender, patients with a pituitary volume at the 25th percentile (413 mm(3)) were approximately three times more likely to respond to treatment by week 12 than those at the 75th percentile (635 mm(3)) (odds ratio=3.07, CI: 0.90-10.48). CONCLUSION: The association of baseline pituitary volumes with early treatment response highlights the importance of the HPA axis in emerging psychosis. Potential implications for treatment strategies in early psychosis are discussed.

The YOU CALL-WE CALL randomized clinical trial: Impact of a multimodal support intervention after a mild stroke

Background Comparison of a multimodal intervention WE CALL (study initiated phone support/information provision) versus a passive intervention YOU CALL (participant can contact a resource person) in individuals with first mild stroke. Methods and Results This study is a single-blinded randomized clinical trial. Primary outcome includes unplanned use of health services (participant diaries) for adverse events and quality of life (Euroquol-5D, Quality of Life Index). Secondary outcomes include planned use of health services (diaries), mood (Beck Depression Inventory II), and participation (Assessment of Life Habits [LIFE-H]). Blind assessments were done at baseline, 6, and 12 months. A mixed model approach for statistical analysis on an intention-to-treat basis was used where the group factor was intervention type and occasion factor time, with a significance level of 0.01. We enrolled 186 patients (WE=92; YOU=94) with a mean age of 62.5±12.5 years, and 42.5% were women. No significant differences were seen between groups at 6 months for any outcomes with both groups improving from baseline on all measures (effect sizes ranged from 0.25 to 0.7). The only significant change for both groups from 6 months to 1 year (n=139) was in the social domains of the LIFE-H (increment in score, 0.4/9±1.3 [95% confidence interval, 0.1–0.7]; effect size, 0.3). Qualitatively, the WE CALL intervention was perceived as reassuring, increased insight, and problem solving while decreasing anxiety. Only 6 of 94 (6.4%) YOU CALL participants availed themselves of the intervention. Conclusions Although the 2 groups improved equally over time, WE CALL intervention was perceived as helpful, whereas YOU CALL intervention was not used.

Relationship of a variant in the NTRK1 gene to white matter microstructure in young adults

The NTRK1 gene (also known as TRKA) encodes a high-affinity receptor for NGF, a neurotrophin involved in nervous system development and myelination. NTRK1 has been implicated in neurological function via links between the T allele at rs6336 (NTRK1-T) and schizophrenia risk. A variant in the neurotrophin gene, BDNF, was previously associated with white matter integrity in young adults, highlighting the importantce of neurotrophins to white matter development. We hypothesized that NTRK1-T would relate to lower fractional anisotropy in healthy adults. We scanned 391 healthy adult human twins and their siblings (mean age: 23.6 ± 2.2 years; 31 NTRK1-T carriers, 360 non-carriers) using 105-gradient diffusion tensor imaging at 4 tesla. We evaluated in brain white matter how NTRK1-T and NTRK1 rs4661063 allele A (rs4661063-A, which is in moderate linkage disequilibrium with rs6336) related to voxelwise fractional anisotropy-acommondiffusion tensor imaging measure of white matter microstructure. We used mixed-model regression to control for family relatedness, age, and sex. The sample was split in half to test reproducibility of results. The false discovery rate method corrected for voxelwise multiple comparisons. NTRK1-T and rs4661063-A correlated with lower white matter fractional anisotropy, independent of age and sex (multiple-comparisons corrected: false discovery rate critical p=0.038 forNTRK1-Tand0.013 for rs4661063-A). In each half-sample, theNTRK1-T effectwasreplicated in the cingulum, corpus callosum, superior and inferior longitudinal fasciculi, inferior fronto-occipital fasciculus, superior corona radiata, and uncinate fasciculus. Our results suggest that NTRK1-T is important for developing white matter microstructure.

Common Alzheimer's disease risk variant within the CLU gene affects white matter microstructure in young adults

There is a strong genetic risk for late-onset Alzheimer's disease (AD), but so far few gene variants have been identified that reliably contribute to that risk. A newly confirmed genetic risk allele C of the clusterin (CLU) gene variant rs11136000 is carried by ~88% of Caucasians. The C allele confers a 1.16 greater odds of developing late-onset AD than the T allele. AD patients have reductions in regional white matter integrity. We evaluated whether the CLU risk variant was similarly associated with lower white matter integrity in healthy young humans. Evidence of early brain differences would offer a target for intervention decades before symptom onset. We scanned 398 healthy young adults (mean age, 23.6 ± 2.2 years) with diffusion tensor imaging, a variation of magnetic resonance imaging sensitive to white matter integrity in the living brain. We assessed genetic associations using mixed-model regression at each point in the brain to map the profile of these associations with white matter integrity. Each C allele copy of the CLUvariant was associated with lower fractional anisotropy-a widely accepted measure of white matter integrity-in multiple brain regions, including several known to degenerate in AD. These regions included the splenium of the corpus callosum, the fornix, cingulum, and superior and inferior longitudinal fasciculi in both brain hemispheres. Young healthy carriers of the CLU gene risk variant showed a distinct profile of lower white matter integrity that may increase vulnerability to developing AD later in life.

Using genome-Wwide complex trait analysis to quantify 'missing heritability' in Parkinson's disease

Genome-wide association studies (GWASs) have been successful at identifying single-nucleotide polymorphisms (SNPs) highly associated with common traits; however, a great deal of the heritable variation associated with common traits remains unaccounted for within the genome. Genome-wide complex trait analysis (GCTA) is a statistical method that applies a linear mixed model to estimate phenotypic variance of complex traits explained by genome-wide SNPs, including those not associated with the trait in a GWAS. We applied GCTA to 8 cohorts containing 7096 case and 19 455 control individuals of European ancestry in order to examine the missing heritability present in Parkinson's disease (PD). We meta-analyzed our initial results to produce robust heritability estimates for PD types across cohorts. Our results identify 27% (95% CI 17-38, P = 8.08E - 08) phenotypic variance associated with all types of PD, 15% (95% CI -0.2 to 33, P = 0.09) phenotypic variance associated with early-onset PD and 31% (95% CI 17-44, P = 1.34E - 05) phenotypic variance associated with late-onset PD. This is a substantial increase from the genetic variance identified by top GWAS hits alone (between 3 and 5%) and indicates there are substantially more risk loci to be identified. Our results suggest that although GWASs are a useful tool in identifying the most common variants associated with complex disease, a great deal of common variants of small effect remain to be discovered. © Published by Oxford University Press 2012.

Rank regression analysis of correlated water quality data from South East Queensland

With growing population and fast urbanization in Australia, it is a challenging task to maintain our water quality. It is essential to develop an appropriate statistical methodology in analyzing water quality data in order to draw valid conclusions and hence provide useful advices in water management. This paper is to develop robust rank-based procedures for analyzing nonnormally distributed data collected over time at different sites. To take account of temporal correlations of the observations within sites, we consider the optimally combined estimating functions proposed by Wang and Zhu (Biometrika, 93:459-464, 2006) which leads to more efficient parameter estimation. Furthermore, we apply the induced smoothing method to reduce the computational burden. Smoothing leads to easy calculation of the parameter estimates and their variance-covariance matrix. Analysis of water quality data from Total Iron and Total Cyanophytes shows the differences between the traditional generalized linear mixed models and rank regression models. Our analysis also demonstrates the advantages of the rank regression models for analyzing nonnormal data.

CIMMYT-selected derived synthetic bread wheats for rainfed environments: Yield evaluation in Mexico and Australia.

Synthetic backcrossed-derived bread wheats (SBWs) from CIMMYT were grown in the Northwest of Mexico at Centro de Investigaciones Agrícolas del Noroeste (CIANO) and sites across Australia during three seasons. During three consecutive years Australia received “shipments” of different SBWs from CIMMYT for evaluation. A different set of lines was evaluated each season, as new materials became available from the CIMMYT crop enhancement program. These consisted of approximately 100 advanced lines (F7) per year. SBWs had been top and backcrossed to CIMMYT cultivars in the first two shipments and to Australian wheat cultivars in the third one. At CIANO, the SBWs were trialled under receding soil moisture conditions. We evaluated both the performance of each line across all environments and the genotype-by-environment interaction using an analysis that fits a multiplicative mixed model, adjusted for spatial field trends. Data were organised in three groups of multienvironment trials (MET) containing germplasm from shipment 1 (METShip1), 2 (METShip2), and 3 (METShip3), respectively. Large components of variance for the genotype × environment interaction were found for each MET analysis, due to the diversity of environments included and the limited replication over years (only in METShip2, lines were tested over 2 years). The average percentage of genetic variance explained by the factor analytic models with two factors was 50.3% for METShip1, 46.7% for METShip2, and 48.7% for METShip3. Yield comparison focused only on lines that were present in all locations within a METShip, or “core” SBWs. A number of core SBWs, crossed to both Australian and CIMMYT backgrounds, outperformed the local benchmark checks at sites from the northern end of the Australian wheat belt, with reduced success at more southern locations. In general, lines that succeeded in the north were different from those in the south. The moderate positive genetic correlation between CIANO and locations in the northern wheat growing region likely reflects similarities in average temperature during flowering, high evaporative demand, and a short flowering interval. We are currently studying attributes of this germplasm that may contribute to adaptation, with the aim of improving the selection process in both Mexico and Australia.

The accuracy of varietal selection using factor analytic models for multi-environment plant breeding trials

Modeling of cultivar x trial effects for multienvironment trials (METs) within a mixed model framework is now common practice in many plant breeding programs. The factor analytic (FA) model is a parsimonious form used to approximate the fully unstructured form of the genetic variance-covariance matrix in the model for MET data. In this study, we demonstrate that the FA model is generally the model of best fit across a range of data sets taken from early generation trials in a breeding program. In addition, we demonstrate the superiority of the FA model in achieving the most common aim of METs, namely the selection of superior genotypes. Selection is achieved using best linear unbiased predictions (BLUPs) of cultivar effects at each environment, considered either individually or as a weighted average across environments. In practice, empirical BLUPs (E-BLUPs) of cultivar effects must be used instead of BLUPs since variance parameters in the model must be estimated rather than assumed known. While the optimal properties of minimum mean squared error of prediction (MSEP) and maximum correlation between true and predicted effects possessed by BLUPs do not hold for E-BLUPs, a simulation study shows that E-BLUPs perform well in terms of MSEP.

The effect of interrogative function on intonation in spontaneous and read Finnish

Goals This study aims to map the effect of interrogative function on the intonation of spontaneous and read Finnish. Earlier research shows that the most prominent feature in Finnish question intonation is an appeal to the listener. Question word questions typically start with a high peak which is followed by falling intonation. In yes/no questions, F0 remains on a high level until the word carrying sentence stress and then falls. Final rises are mainly found in intonation clichés such as "Ai mitä?" ("What?") These earlier results are based on read speech and enacted dialogues. In this study, questions and statements found in spontaneous dialogues were compared. These utterances were also compared with read versions of the same utterances. Fundamental frequency values were compared using a mixed model. Contours were also grouped using auditory and visual inspection. Thus it was possible to compare frequencies of contour types according to utterance type and speech style. The position of questions in the F0 distribution of the whole material was also investigated in this study. Method The material consisted of four spontaneous dialogues and their read versions. The speakers were young adults from the Helsinki metropolitan area, four females and four males. The whole material was first divided into broad dialogue function categories arising from the material and F0 curves were calculated for each category. After this, 277 questions and 244 statements were selected for closer inspection. Values reflecting F0 distribution and contour shape were measured from the F0 contours of these utterances. A mixed model was used to analyse the differences. Utterance type, question type, speech style and speaker gender were used as fixed effects. The frequencies of F0 contour types were compared using a Chi square test. Additional material in this study came from eight young female speakers in central Finland. Results and conclusions In the mixed model analysis, significant differences were found both between questions and statements and between spontaneous and read speech. Generally, utterance type affected the variables reflecting contour type while speech style affected the variables reflecting F0 distribution. The effect of question type was not clearly visible. In read speech the contours resembled earlier results more closely. Speakers had different strategies in differentiating between questions and statements. In the whole material, F0 was slightly higher in questions than in statements. The effect of dialectal background could be seen in the contour types. The results show that interrogative function affects intonation in both spontaneous and read Finnish.

Detection and use of QTL for complex traits in multiple environments.

QTL mapping methods for complex traits are challenged by new developments in marker technology, phenotyping platforms, and breeding methods. In meeting these challenges, QTL mapping approaches will need to also acknowledge the central roles of QTL by environment interactions (QEI) and QTL by trait interactions in the expression of complex traits like yield. This paper presents an overview of mixed model QTL methodology that is suitable for many types of populations and that allows predictive modeling of QEI, both for environmental and developmental gradients. Attention is also given to multi-trait QTL models which are essential to interpret the genetic basis of trait correlations. Biophysical (crop growth) model simulations are proposed as a complement to statistical QTL mapping for the interpretation of the nature of QEI and to investigate better methods for the dissection of complex traits into component traits and their genetic controls.