How young can children reliably and validly self-report their health-related quality of life?: An analysis of 8,591 children across age subgroups with the PedsQL™ 4.0 Generic Core Scales

BACKGROUND: The last decade has evidenced a dramatic increase in the development and utilization of pediatric health-related quality of life (HRQOL) measures in an effort to improve pediatric patient health and well-being and determine the value of healthcare services. The emerging paradigm shift toward patient-reported outcomes (PROs) in clinical trials has provided the opportunity to further emphasize the value and essential need for pediatric patient self-reported outcomes measurement. Data from the PedsQL™ Database(SM )were utilized to test the hypothesis that children as young as 5 years of age can reliably and validly report their HRQOL. METHODS: The sample analyzed represented child self-report age data on 8,591 children ages 5 to 16 years from the PedsQL™ 4.0 Generic Core Scales Database(SM). Participants were recruited from general pediatric clinics, subspecialty clinics, and hospitals in which children were being seen for well-child checks, mild acute illness, or chronic illness care (n = 2,603, 30.3%), and from a State Children's Health Insurance Program (SCHIP) in California (n = 5,988, 69.7%). RESULTS: Items on the PedsQL™ 4.0 Generic Core Scales had minimal missing responses for children as young as 5 years old, supporting feasibility. The majority of the child self-report scales across the age subgroups, including for children as young as 5 years, exceeded the minimum internal consistency reliability standard of 0.70 required for group comparisons, while the Total Scale Scores across the age subgroups approached or exceeded the reliability criterion of 0.90 recommended for analyzing individual patient scale scores. Construct validity was demonstrated utilizing the known groups approach. For each PedsQL™ scale and summary score, across age subgroups, including children as young as 5 years, healthy children demonstrated a statistically significant difference in HRQOL (better HRQOL) than children with a known chronic health condition, with most effect sizes in the medium to large effect size range. CONCLUSION: The results demonstrate that children as young as the 5 year old age subgroup can reliably and validly self-report their HRQOL when given the opportunity to do so with an age-appropriate instrument. These analyses are consistent with recent FDA guidelines which require instrument development and validation testing for children and adolescents within fairly narrow age groupings and which determine the lower age limit at which children can provide reliable and valid responses across age categories

Evaluating LINE-1 methylation in cleft lip tissues and its association with early pregnancy exposures

Aim: To pilot investigation of methylation of long interspersed nucleotide element-1 in lip tissues from infants with nonsyndromic cleft lip, and its association with maternal periconceptional exposures. Methods: The lateral and medial sides of the cleft lips of 23 affected infants were analyzed for long interspersed nucleotide element-1 methylation by bisulfite conversion and pyrosequencing. Results: The medial side showed 1.8% higher methylation compared with the lateral side; p = 0.031, particularly in male infants (2.7% difference; p = 0.011) or when the mothers did not take folic acid during periconceptional period (2.4% difference; p = 0.011). These results were not statistically significant when Bonferroni adjustment was used. Conclusion: The observed differences in DNA methylation, although nonsignificant after correction for multiple comparisons, suggest that differential regulation of the two sides may impact lip fusion and warrant larger-scale replication

Factors influencing agreement between child self-report and parent proxy-reports on the Pediatric Quality of Life Inventory™ 4.0 (PedsQL™) generic core scales

BACKGROUND: In situations where children are unable or unwilling to respond for themselves, measurement of quality of life (QOL) is often obtained by parent proxy-report. However the relationship between child self and parent proxy-reports has been shown to be poor in some circumstances. Additionally the most appropriate statistical method for comparing ratings between child and parent proxy-reports has not been clearly established. The objectives of this study were to assess the: 1) agreement between child and parent proxy-reports on an established child QOL measure (the PedsQL™) using two different statistical methods; 2) effect of chronological age and domain type on agreement between children's and parents' reports on the PedsQL™; 3) relationship between parents' own well-being and their ratings of their child's QOL. METHODS: One hundred and forty-nine healthy children (5.5 – 6.5, 6.5 – 7.5, and 7.5 – 8.5 years) completed the PedsQL™. One hundred and three of their parents completed these measures in relation to their child, and a measure of their own QOL (SF-36). RESULTS: Consistency between child and parent proxy-reports on the PedsQL™ was low, with Intra-Class correlation coefficients ranging from 0.02 to 0.23. Correlations were higher for the oldest age group for Total Score and Psychosocial Health domains, and for the Physical Health domain in the youngest age group. Statistically significant median differences were found between child and parent-reports on all subscales of the PedsQL™. The largest median differences were found for the two older age groups. Statistically significant correlations were found between parents' own QOL and their proxy-reports of child QOL across the total sample and within the middle age group. CONCLUSION: Intra-Class correlation coefficients and median difference testing can provide different information on the relationship between parent proxy-reports and child self-reports. Our findings suggest that differences in the levels of parent-child agreement previously reported may be an artefact of the statistical method used. In addition, levels of agreement can be affected by child age, domains investigated, and parents' own QOL. Further studies are needed to establish the optimal predictors of levels of parent-child agreement

Intrinsic gain modulation and adaptive neural coding

In many cases, the computation of a neural system can be reduced to a receptive field, or a set of linear filters, and a thresholding function, or gain curve, which determines the firing probability; this is known as a linear/nonlinear model. In some forms of sensory adaptation, these linear filters and gain curve adjust very rapidly to changes in the variance of a randomly varying driving input. An apparently similar but previously unrelated issue is the observation of gain control by background noise in cortical neurons: the slope of the firing rate vs current (f-I) curve changes with the variance of background random input. Here, we show a direct correspondence between these two observations by relating variance-dependent changes in the gain of f-I curves to characteristics of the changing empirical linear/nonlinear model obtained by sampling. In the case that the underlying system is fixed, we derive relationships relating the change of the gain with respect to both mean and variance with the receptive fields derived from reverse correlation on a white noise stimulus. Using two conductance-based model neurons that display distinct gain modulation properties through a simple change in parameters, we show that coding properties of both these models quantitatively satisfy the predicted relationships. Our results describe how both variance-dependent gain modulation and adaptive neural computation result from intrinsic nonlinearity.Comment: 24 pages, 4 figures, 1 supporting informatio

Changes in catastrophizing and kinesiophobia are predictive of changes in disability and pain after treatment in patients with anterior knee pain

Purpose. The purpose of the study was to investigate if changes in psychological variables are related to the outcome in pain and disability in patients with chronic anterior knee pain. Methods. A longitudinal observational study on 47 patients with chronic anterior knee pain was performed in a secondary healthcare setting. Pain was measured with the visual analogue scale and disability with the Lysholm scale. The psychological variables, such as anxiety, depression, pain coping strategies, catastrophizing and fear to movement beliefs, were studied by using self-administered questionnaires. Results. Among the pain coping strategies, only the catastrophizing subscale showed a significant reduction. Similarly, anxiety, depression and kinesiophobia were significantly reduced after treatment. Those patients who decreased the catastrophizing, kinesiophobia, anxiety and depression showed a greater improvement in pain and disability after a purely biomedical treatment. A multiple regression analysis revealed that changes in catastrophizing predicted the amount of improvement in pain severity and that changes in both catastrophizing and anxiety predicted changes in disability after treatment. Conclusion. What has been found suggests that clinical improvement in pain and disability is associated with a reduction in catastrophizing and kinesiophobia. Therefore, co-interventions to reduce catastrophizing thinking and kinesiophobia may enhance the results. Level of evidence. Prospective Cohort Study, Level I for prognosis

A Generalized Linear Model for Estimating Spectrotemporal Receptive Fields from Responses to Natural Sounds

In the auditory system, the stimulus-response properties of single neurons are often described in terms of the spectrotemporal receptive field (STRF), a linear kernel relating the spectrogram of the sound stimulus to the instantaneous firing rate of the neuron. Several algorithms have been used to estimate STRFs from responses to natural stimuli; these algorithms differ in their functional models, cost functions, and regularization methods. Here, we characterize the stimulus-response function of auditory neurons using a generalized linear model (GLM). In this model, each cell's input is described by: 1) a stimulus filter (STRF); and 2) a post-spike filter, which captures dependencies on the neuron's spiking history. The output of the model is given by a series of spike trains rather than instantaneous firing rate, allowing the prediction of spike train responses to novel stimuli. We fit the model by maximum penalized likelihood to the spiking activity of zebra finch auditory midbrain neurons in response to conspecific vocalizations (songs) and modulation limited (ml) noise. We compare this model to normalized reverse correlation (NRC), the traditional method for STRF estimation, in terms of predictive power and the basic tuning properties of the estimated STRFs. We find that a GLM with a sparse prior predicts novel responses to both stimulus classes significantly better than NRC. Importantly, we find that STRFs from the two models derived from the same responses can differ substantially and that GLM STRFs are more consistent between stimulus classes than NRC STRFs. These results suggest that a GLM with a sparse prior provides a more accurate characterization of spectrotemporal tuning than does the NRC method when responses to complex sounds are studied in these neurons

DNp73 improves generation efficiency of human induced pluripotent stem cells

<p>Abstract</p> <p>Background</p> <p>Recent studies have found that p53 and its' associated cell cycle pathways are major inhibitors of human induced pluripotent stem (iPS) cell generation. In the same family as p53 is p73, which shares sequence similarities with p53. However, p73 also has distinct properties of its own, such as two alternative promoters to express transactivation of p73 (TAp73) and N terminal deleted p73 (DNp73). Functionally, TAp73 acts similarly to p53 in tumor suppression. However, DNp73, on the other hand acts as an oncogene to suppress p53 and p73 induced apoptosis. Therefore, how can p73 have opposing roles in human iPS cell generation?</p> <p>Results</p> <p>Transcription factors, Oct4, Sox2, Klf4 and cMyc (4TF, Yamanaka factors) are used as basal conditions to generate iPS cells. In addition, the factor of DNp73(actually alpha splicing DNp73, DNp73α) is used to generate iPS cells. The experiment found that the addition of DNp73 gene increases human iPS cell generation efficiency by 12.6 folds in comparison to human fibroblast cells transduced with only the basal conditions. Also, iPS cells generated with DNp73 expression are more resistant to <it>in vitro </it>and <it>in vivo </it>differentiation.</p> <p>Conclusions</p> <p>This study found DNp73, a family member of p53, is also involved in the human iPS cell generation. Specifically, that the involvement of DNp73 generates iPS cells that are more resistant to <it>in vitro </it>and <it>in vivo </it>differentiation. Therefore, this data may prove to be useful in future developmental studies and cancer researches.</p

Estimating Receptive Fields from Responses to Natural Stimuli with Asymmetric Intensity Distributions

The reasons for using natural stimuli to study sensory function are quickly mounting, as recent studies have revealed important differences in neural responses to natural and artificial stimuli. However, natural stimuli typically contain strong correlations and are spherically asymmetric (i.e. stimulus intensities are not symmetrically distributed around the mean), and these statistical complexities can bias receptive field (RF) estimates when standard techniques such as spike-triggered averaging or reverse correlation are used. While a number of approaches have been developed to explicitly correct the bias due to stimulus correlations, there is no complementary technique to correct the bias due to stimulus asymmetries. Here, we develop a method for RF estimation that corrects reverse correlation RF estimates for the spherical asymmetries present in natural stimuli. Using simulated neural responses, we demonstrate how stimulus asymmetries can bias reverse-correlation RF estimates (even for uncorrelated stimuli) and illustrate how this bias can be removed by explicit correction. We demonstrate the utility of the asymmetry correction method under experimental conditions by estimating RFs from the responses of retinal ganglion cells to natural stimuli and using these RFs to predict responses to novel stimuli

Receptive Field Inference with Localized Priors

The linear receptive field describes a mapping from sensory stimuli to a one-dimensional variable governing a neuron's spike response. However, traditional receptive field estimators such as the spike-triggered average converge slowly and often require large amounts of data. Bayesian methods seek to overcome this problem by biasing estimates towards solutions that are more likely a priori, typically those with small, smooth, or sparse coefficients. Here we introduce a novel Bayesian receptive field estimator designed to incorporate locality, a powerful form of prior information about receptive field structure. The key to our approach is a hierarchical receptive field model that flexibly adapts to localized structure in both spacetime and spatiotemporal frequency, using an inference method known as empirical Bayes. We refer to our method as automatic locality determination (ALD), and show that it can accurately recover various types of smooth, sparse, and localized receptive fields. We apply ALD to neural data from retinal ganglion cells and V1 simple cells, and find it achieves error rates several times lower than standard estimators. Thus, estimates of comparable accuracy can be achieved with substantially less data. Finally, we introduce a computationally efficient Markov Chain Monte Carlo (MCMC) algorithm for fully Bayesian inference under the ALD prior, yielding accurate Bayesian confidence intervals for small or noisy datasets