Early predictive value of cord blood bilirubin and dynamic monitoring of transcutaneous bilirubin for hyperbilirubinemia of newborns

ObjectiveTo study the early predictive value of cord blood bilirubin and dynamic monitoring of transcutaneous bilirubin for hyperbilirubinemia of newborns.Methods389 newborns delivered from June 2014 to December 2015 were enrolled as the research subjects; detailed records were made about the general data of newborns and mothers, and after cord blood bilirubin being graded, the incidence of hyperbilirubinemia was counted, and the prediction efficiency of cord blood bilirubin was analyzed by receiver operator characteristic (ROC) curve. At the same time, the transcutaneous bilirubin was detected continuously when the neonate was born and 24 h, 48 h and 72 h after birth, and the relativity between transcutaneous bilirubin at 72 h and serum bilirubin was analyzed.ResultsNo significant difference was found in the hyperbilirubinemia group and the non-hyperbilirubinemia group concerning general data of the newborns and their mothers. With the concentration of cord blood bilirubin increased, the incidence of hyperbilirubinemia also increased; separate prediction of hyperbilirubinemia by cord blood bilirubin showed a sensitivity and specificity of 71.4% and 65.6% respectively, and they need further dynamic monitoring. The daily mean of transcutaneous bilirubin in hyperbilirubinemia group was significantly higher than that in non-hyperbilirubinemia group at 24 h, 48 h and 72 h, and the measurement value of transcutaneous bilirubin at 72 h had a high correlation with serum bilirubin. When transcutaneous bilirubin value is higher than 18, the incidence of hyperbilirubinemia should be considered.ConclusionsThe increase of cord blood bilirubin effectively predict the occurrence of neonatal hyperbilirubinemia. There is a good correlation between levels of transcutaneous bilirubin and serum bilirubin. Moreover, combined detection of transcutaneous bilirubin and cord blood bilirubin can significantly improve the prediction accuracy of hyperbilirubinemia.     

Potential for Powered Flight Neared by Most Close Avialan Relatives,but Few Crossed Its Thresholds

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Can transposable element copy number distribution parameters be estimated from natural populations of Drosophila melanogaster?

The copy frequency distribution of a transposable element family in a Drosophila melanogaster natural population is generally characterised by the values of the Charlesworths' model parameters α and β (Charlesworth & Charlesworth, 1983). The estimation of these parameters is made using the observed distribution of the occupied sites in a population sample. Several results have been interpreted as due either to the influence of stochastic factors or to deterministic factors (transposition, excision, selection…). The accuracy of this method was tested by estimations performed on samples from simulated populations. The results show that with the sample size usually used for natural population studies, the confidence intervals are too large to reasonably deduce either the element copy number distribution or the values of transposition and excision rate and selective coefficients.     

Influence of Methanogenic Populations in Holocene Lacustrine Sediments Revealed by Clone Libraries and Fatty Acid Biogeochemistry

Methanogenic populations were investigated in subsaline Laguna Potrok Aike sediments, southern Argentina. Microbial density and activity were assessed via cell count and in situ ATP detection for the last ～11K years. Methanogen phylogenetics highlighted species stratification throughout depth, whereas CO₂ reduction was the major pathway leading to methane production. Organic substrates, characterized using pore water analysis, bulk organic fractions and saturated fatty acids, showed a clear link between sediment colonization and initial organic sources. Concentrations and δ¹³C compositions of methane and fatty acids provided final evidence of a microbial imprint on Holocene organic proxies in the most colonized intervals.     

Sensory Neurons Contacting the Cerebrospinal Fluid Require the Reissner Fiber to Detect Spinal Curvature In Vivo

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Spatial metrics for detecting ecosystem degradation in the ridge-slough patterned landscape

Indicators of landscape condition should be selected based on their sensitivity to environmental changes and their capacity to provide early warning detection of those changes. We assessed the performance of a suite of spatial-pattern metrics selected to quantify the condition of the ridge-slough landscape in the Everglades (South Florida, USA). Spatial pattern metrics (n = 14) that describe landscape composition, geometry and hydrologic connectivity were enumerated from vegetation maps of twenty-five 2 × 2 km primary sampling units (PSUs) that span a gradient of hydrologic and ecological condition across the greater Everglades ecosystem. Metrics were assessed in comparison with field measurements from each PSU of landscape condition obtained from regional surveys of soil elevation, which have previously been shown to capture dramatic differences between conserved and degraded locations. Elevation-based measures of landscape condition included soil elevation bi-modality (BI_SE), a binary measure of landscape condition, and also the standard deviation of soil elevation (SD_SE), a continuous measure of condition. Metric performance was assessed based on the strength (sensitivity) and shape (leading vs. lagging) of the relationship between spatial pattern metrics and these elevation-based measures. We observed significant logistic regression slopes with BI_SE for only 4 metrics (slough width, ridge density, directional connectivity index – DCI, and least flow cost – LFC). More significant relationships (n = 8 metrics) were observed with SD_SE, with the strongest associations for slough density, mean ridge width, and the average length of straight flow, as well as for a suite of hydrologic connectivity metrics (DCI, LFC and landscape discharge competence – LDC). Leading vs. lagging performance, inferred from the curvature of the association obtained from the exponent of fitted power functions, suggest that only DCI was a leading metric of the loss of soil elevation variation; most metrics were indeterminate, though some were clearly lagging. Our findings support the contention that soil elevation changes from altered peat accretion dynamics precede changes in landscape pattern, and offer insights that will enable efficient monitoring of the ridge-slough landscape as part of the ongoing Everglades restoration effort.