Non-nutritive sucking scoring system for preterm newborns

Aim: To validate a non-nutritive sucking (NNS) scoring system for oral feeding in preterm newborns (PTNB). Methods: A cohort study was carried out in two phases. In phase one of the study, 22 mastered speech-language pathologists received the protocol and procedure for a NNS scoring system to evaluate the content and presentation of the form and to define the grading scale. In phase two, six speech-language pathologists evaluated 51 PTNBs weekly, using the defined scoring system. Setting: This study was carried out in the Nursery Annex to the Maternity at the Intensive and Neonatal Pediatrics Service, Instituto da Crianca, Hospital das Clinicas, School of Medicine, University of Sao Paulo (FMUSP) during the period from May 2004 to May 2006. Participants: A total of 28 speech-language pathologist experts and 51 PTNBs. Results: In the first phase of the study, 22 speech-language pathologists selected the criteria, utilized in the NNS evaluation with 80% agreement. In the second phase of the study, the NNS evaluation was carried out on 51 PTNB, and a scoring system of 50 points was proposed, which corresponds to the smallest number of false positive and negative results regarding oral feeding ability. Conclusion: An NNS evaluation system was validated that was able to indicate when oral feeding could safely begin in PTNBs with a high level of agreement among the speech-language pathologists who have participated.

A numerical investigation of the atmosphere-ocean thermal contrast over the coastal upwelling region of Cabo Frio, Brazil

An one-dimensional atmospheric second order closure model, coupled to an oceanic mixed layer model, is used to investigate the short term variation of the atmospheric and oceanic boundary layers in the coastal upwelling area of Cabo Frio, Brazil (23 degrees S, 42 degrees 08`W). The numerical simulations were carried out to evaluate the impact caused by the thermal contrast between atmosphere and ocean on the vertical extent and other properties of both atmospheric and oceanic boundary layers. The numerical simulations were designed taking as reference the observations carried out during the passage of a cold front that disrupted the upwelling regime in Cabo Frio in July of 1992. The simulations indicated that in 10 hours the mechanical mixing, sustained by a constant background flow of 10 in s(-1), increases the atmospheric boundary layer in 214 in when the atmosphere is initially 2 K warmer than the ocean (positive thermal contrast observed during upwelling regime). For an atmosphere initially -2 K colder than the ocean (negative thermal contrast observed during passage of the cold front), the incipient thermal convection intensifies the mechanical mixing increasing the vertical extent of the atmospheric boundary layer in 360 in. The vertical evolution of the atmospheric boundary layer is consistent with the observations carried out in Cabo Frio during upwelling condition. When the upwelling is disrupted, the discrepancy between the simulated and observed atmospheric boundary layer heights in Cabo Frio during July of 1992 increases considerably. During the period of 10 hours, the simulated oceanic mixed layer deepens 2 in and 5.4 in for positive and negative thermal contrasts of 2 K and -2 K, respectively. In the latter case, the larger vertical extent of the oceanic mixed layer is due to the presence of thermal convection in the atmospheric boundary layer, which in turn is associated to the absence of upwelling caused by the passage of cold fronts in Cabo Frio.

Next Generation Sequencing of Pooled Samples Reveals New SNRNP200 Mutations Associated with Retinitis Pigmentosa

The gene SNRNP200 is composed of 45 exons and encodes a protein essential for pre-mRNA splicing, the 200 kDa helicase hBrr2. Two mutations in SNRNP200 have recently been associated with autosomal dominant retinitis pigmentosa (adRP), a retinal degenerative disease, in two families from China. In this work we analyzed the entire 35-Kb SNRNP200 genomic region in a cohort of 96 unrelated North American patients with adRP. To complete this large-scale sequencing project, we performed ultra high-throughput sequencing of pooled, untagged PCR products. We then validated the detected DNA changes by Sanger sequencing of individual samples from this cohort and from an additional one of 95 patients. One of the two previously known mutations (p.S1087L) was identified in 3 patients, while 4 new missense changes (p.R681C, p.R681H, p.V683L, p.Y689C) affecting highly conserved codons were identified in 6 unrelated individuals, indicating that the prevalence of SNRNP200-associated adRP is relatively high. We also took advantage of this research to evaluate the pool-and-sequence method, especially with respect to the generation of false positive and negative results. We conclude that, although this strategy can be adopted for rapid discovery of new disease-associated variants, it still requires extensive validation to be used in routine DNA screenings. (C) 2011 Wiley-Liss, Inc.

A Bayesian model for estimating the malaria transition probabilities considering individuals lost to follow-up

It is known that patients may cease participating in a longitudinal study and become lost to follow-up. The objective of this article is to present a Bayesian model to estimate the malaria transition probabilities considering individuals lost to follow-up. We consider a homogeneous population, and it is assumed that the considered period of time is small enough to avoid two or more transitions from one state of health to another. The proposed model is based on a Gibbs sampling algorithm that uses information of lost to follow-up at the end of the longitudinal study. To simulate the unknown number of individuals with positive and negative states of malaria at the end of the study and lost to follow-up, two latent variables were introduced in the model. We used a real data set and a simulated data to illustrate the application of the methodology. The proposed model showed a good fit to these data sets, and the algorithm did not show problems of convergence or lack of identifiability. We conclude that the proposed model is a good alternative to estimate probabilities of transitions from one state of health to the other in studies with low adherence to follow-up.

Anomalous dependence on the diffusion coefficients of the ionic relaxation time in electrolytes

We show, by using a numerical analysis, that the dynamic toward equilibrium for an electrolytic cell subject to a step-like external electric field is a multirelaxation process when the diffusion coefficients of positive and negative ions are different. By assuming that the diffusion coefficient of positive ions is constant, we observe that the number of involved relaxation processes increases when the diffusion coefficient of the negative ions diminishes. Furthermore, two of the relaxation times depend nonmonotonically on the ratio of the diffusion coefficients. This result is unexpected, because the ionic drift velocity, by means of which the ions move to reach the equilibrium distribution, increases with increasing ionic mobility.

Comparing diagnostic tests with missing data

When missing data occur in studies designed to compare the accuracy of diagnostic tests, a common, though naive, practice is to base the comparison of sensitivity, specificity, as well as of positive and negative predictive values on some subset of the data that fits into methods implemented in standard statistical packages. Such methods are usually valid only under the strong missing completely at random (MCAR) assumption and may generate biased and less precise estimates. We review some models that use the dependence structure of the completely observed cases to incorporate the information of the partially categorized observations into the analysis and show how they may be fitted via a two-stage hybrid process involving maximum likelihood in the first stage and weighted least squares in the second. We indicate how computational subroutines written in R may be used to fit the proposed models and illustrate the different analysis strategies with observational data collected to compare the accuracy of three distinct non-invasive diagnostic methods for endometriosis. The results indicate that even when the MCAR assumption is plausible, the naive partial analyses should be avoided.

Generalized Birnbaum-Saunders distributions applied to air pollutant concentration

The generalized Birnbaum-Saunders (GBS) distribution is a new class of positively skewed models with lighter and heavier tails than the traditional Birnbaum-Saunders (BS) distribution, which is largely applied to study lifetimes. However, the theoretical argument and the interesting properties of the GBS model have made its application possible beyond the lifetime analysis. The aim of this paper is to present the GBS distribution as a useful model for describing pollution data and deriving its positive and negative moments. Based on these moments, we develop estimation and goodness-of-fit methods. Also, some properties of the proposed estimators useful for developing asymptotic inference are presented. Finally, an application with real data from Environmental Sciences is given to illustrate the methodology developed. This example shows that the empirical fit of the GBS distribution to the data is very good. Thus, the GBS model is appropriate for describing air pollutant concentration data, which produces better results than the lognormal model when the administrative target is determined for abating air pollution. Copyright (c) 2007 John Wiley & Sons, Ltd.