Direct-Breastfeeding in the Neonatal Intensive Care Unit and Breastfeeding Duration for Premature Infants

Aim To explore the relationship between direct-breastfeeding in the neonatal intensive care unit (NICU) and breastfeeding duration after discharge. Background Initiating and maintaining breastmilk feeding is an important goal that begins in the NICU. Little is known about direct-breastfeeding in the NICU and its relation to breastfeeding duration. Methods Chart review of 46 infants (\u3c 32 weeks gestational age or \u3c 1500 grams) whose mothers provided breastmilk. Results One month after discharge, mothers still providing breastmilk were more likely to have provided ≥ 1 direct-breastfeed per day in the NICU (21.16, CI: 3.13–143.25, p \u3c 0.01) and had prior breastfeeding experience (OR: 9.16, CI: 1.02–82.34, p \u3c 0.05). At 4 months, mothers still providing breastmilk were more likely to have provided ≥ 1 direct-breastfeed per day in the NICU (OR: 12.80, CI: 1.39–118.32, p \u3c 0.05). Conclusions Direct-breastfeeding in the NICU may play an essential role in preparing mothers for breastfeeding after discharge, thus potentially impacting breastfeeding duration

Topology, Vorticity and Limit Cycle in a Stabilized Kuramoto-Sivashinsky Equation

A noisy stabilized Kuramoto-Sivashinsky equation is analyzed by stochastic decomposition. For values of control parameter for which periodic stationary patterns exist, the dynamics can be decomposed into diffusive and transverse parts which act on a stochastic potential. The relative positions of stationary states in the stochastic global potential landscape can be obtained from the topology spanned by the low-lying eigenmodes which inter-connect them. Numerical simulations confirm the predicted landscape. The transverse component also predicts a universal class of vortex like circulations around fixed points. These drive nonlinear drifting and limit cycle motion of the underlying periodic structure in certain regions of parameter space. Our findings might be relevant in studies of other nonlinear systems such as deep learning neural networks.Comment: Main body: 16 pages, 3 figures; Supplementary: 14 pages, 6 figure

SPIDer: Saccharomyces protein-protein interaction database

BACKGROUND: Since proteins perform their functions by interacting with one another and with other biomolecules, reconstructing a map of the protein-protein interactions of a cell, experimentally or computationally, is an important first step toward understanding cellular function and machinery of a proteome. Solely derived from the Gene Ontology (GO), we have defined an effective method of reconstructing a yeast protein interaction network by measuring relative specificity similarity (RSS) between two GO terms. DESCRIPTION: Based on the RSS method, here, we introduce a predicted Saccharomyces protein-protein interaction database called SPIDer. It houses a gold standard positive dataset (GSP) with high confidence level that covered 79.2% of the high-quality interaction dataset. Our predicted protein-protein interaction network reconstructed from the GSPs consists of 92 257 interactions among 3600 proteins, and forms 23 connected components. It also provides general links to connect predicted protein-protein interactions with three other databases, DIP, BIND and MIPS. An Internet-based interface provides users with fast and convenient access to protein-protein interactions based on various search features (searching by protein information, GO term information or sequence similarity). In addition, the RSS value of two GO terms in the same ontology, and the inter-member interactions in a list of proteins of interest or in a protein complex could be retrieved. Furthermore, the database presents a user-friendly graphical interface which is created dynamically for visualizing an interaction sub-network. The database is accessible at . CONCLUSION: SPIDer is a public database server for protein-protein interactions based on the yeast genome. It provides a variety of search options and graphical visualization of an interaction network. In particular, it will be very useful for the study of inter-member interactions among a list of proteins, especially the protein complex. In addition, based on the predicted interaction dataset, researchers could analyze the whole interaction network and associate the network topology with gene/protein properties based on a global or local topology view

Experience of using a smartphone WeChat applet for dental anxiety assessment and preoperative evaluation: A nationwide multicenter study

IntroductionDental anxiety is a multivariate phenomenon that regularly occurs during a dental procedure. Although it may lead to patients' safety concerns and adverse events in routine treatment, it is often ignored. The purpose of this research is to develop a novel WeChat Applet for dental anxiety (WADA) with the following features and aims: (1) to help patients with dental anxiety management; (2) provide patient with a physical status self-evaluation; and(3) provide a platform for online assessment and tele-consultancy by dentists. We aimed to test and verify whether such an applet could play a beneficial role before and after a dental procedure and facilitate management of high-risk patients during the COVID-19 pandemic.Materials and methodsDuring the 12-month survey period (August 2020 to July 2021), a total of 180 patients aged 3–74 years from eight different cities (n = 180 at the end of treatment, n = 25 for the System Usability Scale (SUS) and follow-up interview) and 20 medical staff from eight different cities (n =20 for follow-up interview) were evaluated by WADA. At the end of the survey period, the results of the interviews were analyzed thematically.ResultsWADA assessment results from 180 patients and follow-up interview results from 45 participants were analyzed. In this study with a male to female ratio of 2:3, 75% were found to be suffering from dental anxiety, 86% were found with postoperative complications, and 11 cases were found to have contraindications to surgery. The total SUS score for WADA is 72.25 above the mean score, proving that WADA is a relevant and useful tool before and after dental treatment. Based on the results of the interviews, the following themes were identified: patient satisfaction; dentists' effectiveness; multi-center data integration; and increase its frequency of usage.ConclusionsThe WADA was developed for dental procedures and is effective for reducing treatment risks, improving patients' satisfaction and dentists' convenience, especially in terms of facilitating management of high-risk patient during the COVID-19 pandemic

Genomic prediction of drought tolerance during seedling stage in maize using low-cost molecular markers

Drought tolerance in maize is a complex and polygenic trait, especially in the seedling stage. In plant breeding, complex genetic traits can be improved by genomic selection (GS), which has become a practical and effective breeding tool. In the present study, a natural maize population named Northeast China core population (NCCP) consisting of 379 inbred lines were genotyped with diversity arrays technology (DArT) and genotyping-by-sequencing (GBS) platforms. Target traits of seedling emergence rate (ER), seedling plant height (SPH), and grain yield (GY) were evaluated under two natural drought stress environments in northeast China. Adequate genetic variations were observed for all the target traits, but they were divergent across environments. Similarly, the heritability of the target trait also varied across years and environments, the heritabilities in 2019 (0.88, 0.82, 0.85 for ER, SPH, GY) were higher than those in 2020 (0.65, 0.53, 0.33) and cross-2-years (0.32, 0.26, 0.33). In total, three marker datasets, 11,865 SilicoDArT markers obtained from the DArT-seq platform, 7837 SNPs obtained from the DArT-seq platform, and 91,003 SNPs obtained from the GBS platform, were used for GS analysis after quality control. The results of phylogenetic trees showed that broad genetic diversity existed in the NCCP population. Genomic prediction results showed that the average prediction accuracies estimated using the DArT SNP dataset under the two-fold cross-validation scheme were 0.27, 0.19, and 0.33, for ER, SPH, and GY, respectively. The result of SilicoDArT is close to the SNPs from DArT-seq, those were 0.26, 0.22, and 0.33. For the trait with lower heritability, the prediction accuracy can be improved using the dataset filtered by linkage disequilibrium. For the same trait, the prediction accuracies estimated with two DArT marker datasets were consistently higher than that estimated with the GBS SNP dataset under the same genotyping cost. The prediction accuracy was improved by controlling population structure and marker quality, even though the marker density was reduced. The prediction accuracies were improved by more than 30% using the significant-associated SNPs. Due to the complexity of drought tolerance under the natural stress environments, multiple years of data need to be accumulated to improve prediction accuracy by reducing genotype-by-environment interaction. Modeling genotype-by-environment interaction into genomic prediction needs to be further developed for improving drought tolerance in maize. The results obtained from the present study provides valuable pathway for improving drought tolerance in maize using GS

Attitudes on the donation of human embryos for stem cell research among Chinese IVF patients and students

Bioethical debates on the use of human embryos and oocytes for stem cell research have often been criticized for the lack of empirical insights into the perceptions and experiences of the women and couples who are asked to donate these tissues in the IVF clinic. Empirical studies that have investigated the attitudes of IVF patients and citizens on the (potential) donation of their embryos and oocytes have been scarce and have focused predominantly on the situation in Europe and Australia. This article examines the viewpoints on the donation of embryos for stem cell research among IVF patients and students in China. Research into the perceptions of patients is based on in-depth interviews with IVF patients and IVF clinicians. Research into the attitudes of students is based on a quantitative survey study (n=427). The empirical findings in this paper indicate that perceptions of the donation of human embryos for stem cell research in China are far more diverse and complex than has commonly been suggested. Claims that ethical concerns regarding the donation and use of embryos and oocytes for stem cell research are typical for Western societies but absent in China cannot be upheld. The article shows that research into the situated perceptions and cultural specificities of human tissue donation can play a crucial role in the deconstruction of politicized bioethical argumentation and the (often ill-informed) assumptions about “others” that underlie socio-ethical debates on the moral dilemmas of technology developments in the life sciences

Potential of Core-Collapse Supernova Neutrino Detection at JUNO

JUNO is an underground neutrino observatory under construction in Jiangmen, China. It uses 20kton liquid scintillator as target, which enables it to detect supernova burst neutrinos of a large statistics for the next galactic core-collapse supernova (CCSN) and also pre-supernova neutrinos from the nearby CCSN progenitors. All flavors of supernova burst neutrinos can be detected by JUNO via several interaction channels, including inverse beta decay, elastic scattering on electron and proton, interactions on C12 nuclei, etc. This retains the possibility for JUNO to reconstruct the energy spectra of supernova burst neutrinos of all flavors. The real time monitoring systems based on FPGA and DAQ are under development in JUNO, which allow prompt alert and trigger-less data acquisition of CCSN events. The alert performances of both monitoring systems have been thoroughly studied using simulations. Moreover, once a CCSN is tagged, the system can give fast characterizations, such as directionality and light curve