The Impact of Maternal Characteristics on the Moderately Premature Infant: An Antenatal Maternal Transport Clinical Prediction Rule

Background: Moderately premature infants, defined here as those born between 30 $\frac{0}{7}$ and 34 $\frac{6}{7}$ weeks gestation, comprise 3.9% of all births in the United States and 32% of all preterm births. While long-term outcomes for these infants are better than for less mature infants, morbidity and mortality are still substantially increased in comparison to infants born at term. There is an added survival benefit resulting from birth at a tertiary neonatal care center, and although many of these infants require tertiary level care, delivery at lower level hospitals and subsequent neonatal transfer are still common. Objective: Our primary aim was to determine the impact of maternal characteristics and antenatal medical management on the early neonatal course of the moderately premature infant. The secondary aim was to create a clinical prediction rule to determine which infants require intubation and mechanical ventilation in the first 24 hours of life. Such a prediction rule could inform the decision to transfer maternal-fetal patients prior to delivery to a facility with a Level III Neonatal Intensive Care Unit (NICU), where optimal care could be provided without the requirement for a neonatal transfer. Methods: Data for this analysis came from the cohort of infants in the Moderately Premature Infant Project (MPIP) database, a multi-center cohort study of 850 infants born at gestational age 30 $\frac{0}{7}$ to 34 $\frac{6}{7}$ weeks, who were discharged home alive. We built a logistic regression model to identify maternal characteristics associated with need for tertiary care, as measured by administration of surfactant. Using statistically significant covariates from this model, we then created a numerical decision rule to predict need for tertiary care. Results: In multivariate modeling, 4 factors were associated with reduction in the need for tertiary care, including, surfactant administration, including non-White race (OR=0.5, [0.3, 0.7], older gestational age, female gender (OR=0.6 [0.4, 0.8]) and use of antenatal corticosteroids (OR=0.5, [0.3, 0.8]). The clinical prediction rule to discriminate between infants who received surfactant, versus those who did not, had an area under the curve of 0.77 [0.73, 0.8]. Conclusions: Four antenatal risk factors are associated with a requirement for Level III NICU care as defined by the need for surfactant administration. Future analyses will examine a broader spectrum of antenatal characteristics and revalidate the prediction rule in an independent cohort

Mixture modeling of microarray gene expression data

About 28% of genes appear to have an expression pattern that follows a mixture distribution. We use first- and second-order partial correlation coefficients to identify trios and quartets of non-sex-linked genes that are highly associated and that are also mixtures. We identified 18 trio and 35 quartet mixtures and evaluated their mixture distribution concordance. Concordance was defined as the proportion of observations that simultaneously fall in the component with the higher mean or simultaneously in the component with the lower mean based on their Bayesian posterior probabilities. These trios and quartets have a concordance rate greater than 80%. There are 33 genes involved in these trios and quartets. A factor analysis with varimax rotation identifies three gene groups based on their factor loadings. One group of 18 genes has a concordance rate of 56.7%, another group of 8 genes has a concordance rate of 60.8%, and a third group of 7 genes has a concordance rate of 69.6%. Each of these rates is highly significant, suggesting that there may be strong biological underpinnings for the mixture mechanisms of these genes. Bayesian factor screening confirms this hypothesis by identifying six single-nucleotide polymorphisms that are significantly associated with the expression phenotypes of the five most concordant genes in the first group

Fuzzy Clustering Method Based on Improved Weighted Distance

As an essential data processing technology, cluster analysis has been widely used in various fields. In clustering, it is necessary to select appropriate measures to evaluate the similarity in the data. In this paper, firstly, a cluster center selection method based on the grey relational degree is proposed to solve the problem of sensitivity in initial cluster center selection. Secondly, combining the advantages of Euclidean distance, DTW distance, and SPDTW distance, a weighted distance measurement based on three kinds of reach is proposed. Then, it is applied to Fuzzy C-MeDOIDS and Fuzzy C-means hybrid clustering technology. Numerical experiments are carried out with the UCI datasets. The experimental results show that the accuracy of the clustering results is significantly improved by using the clustering method proposed in this paper. Besides, the method proposed in this paper is applied to the MUSIC INTO EMOTIONS and YEAST datasets. The clustering results show that the algorithm proposed in this paper can also achieve a better clustering effect when dealing with practical problems

Parental Satisfaction and Objective Test Measurements Associated with Post-Partum versus Nursery Newborn Hearing Screening

Beth Israel Deaconess Medical Center (BIDMC; Boston, MA) initiated a change to the newborn hearing screening program in 2013 to encourage increased parental presence at the time of screening and support a more family centered hospital environment. Newborn hearing screening program technicians were encouraged to conduct all hearing screens in the parent’s post-partum rooms instead of in the nursery. To measure the effect of this change on the families and screening measures, satisfaction surveys and retrospective data was collected over a 2 year period and compared. Newborn hearing screening program technicians and mother-baby nursing staff were surveyed to determine influence of this new process on their work flow. Results suggest post-partum room testing leads to an increase in family satisfaction without a resulting change in pass rates or decrease in efficiency of screen or staff work flow

Genome-Wide Identification and Expression Analysis of Dof Transcription Factors in Lotus (Nelumbo nucifera Gaertn.)

Lotus (Nelumbo nucifera Gaertn.) is a traditional Chinese aquatic flower with high ornamental and economic value, but water salinity seriously affects lotus cultivation and distribution. The Dof transcription factors (TFs) play a crucial function in the regulatory network of growth and defense in plants. However, no systematic investigations of the Dof TFs in lotus have been performed. In this study, comprehensive searches of the lotus genome yielded 29 potential NnDofs. We carried out a series of standardized analyses, which include physical properties, multiple sequence alignment, phylogenetic analysis, gene structure, motif composition, cis-acting element prediction, chromosome distribution, and synteny analysis. The results showed that segment duplication probably caused the NnDofs gene family expansion. The potential functions of NnDofs in lotus development and stress conditions are speculated by promoter analysis. Furthermore, a complete expression investigation of NnDofs utilizing an RNA-seq atlas and quantitative real-time polymerase chain reaction (qRT-PCR) was performed. The majority of the NnDofs exhibit tissue-specific expression patterns, and many genes have been identified as being extremely sensitive to salt stressors. Overall, this study is the first to report a genome-wide assessment of the Dof family in lotus, and the findings offer vital insights for prospective functional studies on lotus salinity stress

Crashworthiness analysis of novel cactus-inspired multi-cell structures under axial crushing

This study introduces an innovative cactus-inspired bionic tube (CBT) designed for enhanced energy absorption, drawing inspiration from the ribbed structure of cacti. Validation is achieved through quasi-static crushing experiments, confirming the numerical model's accuracy. Numerical simulations investigate critical factors, including structural mass, wall thickness, loading velocity, and cross-sectional configuration, revealing that proper cross-section design can boost the specific energy absorption (SEA) of the original CBT by 15.84 %. Additionally, a theoretical model is developed to forecast the mean crushing force of CBTs. Comparative analysis demonstrates the superior crashworthiness of CBTs over contemporary bionic and widely adopted multicell structures with the same mass, achieving a remarkable SEA of 11.44 J/g—exceeding maximum and minimum SEA values of these structures by 28.3 % and 127.9 %, respectively. This research significantly contributes to advancing the development of high-performance bionic energy-absorbing structures for crash applications

Economic evaluation of caffeine for apnea of prematurity

In comparison with placebo, caffeine therapy for apnea of prematurity in infants weighing less than 1250 g is economically appealing for infants up to 18 to 21 months' corrected age