Photon storage and routing in quantum dots with spin-orbit coupling.

As an essential element for quantum information processing and quantum communication, efficient quantum memory based on solid-state platforms is imperative for practical applications but remains a challenge. Here we propose a scheme to realize a highly efficient and controllable storage and routing of single photons based on quantum dots (QDs) with a Rashba spin-orbit coupling (SOC). We show that the SOC in the QDs can provide a flexible built-up of electromagnetically induced transparency (EIT) for single-photon propagation, and storage, retrieval, as well as routing of single-photon wavepackets can also be implemented through the EIT.

Storage and retrieval of slow-light dark solitons.

We show that stable slow-light dark solitons with finite continuous-wave background can be generated in a -type atomic system via electromagnetically induced transparency (EIT). We also show that such dark solitons can be stored and retrieved with high efficiency and fidelity. Moreover, an optical routing of them can be realized via EIT in the system with a double--type level configuration.

Value of fasting plasma glucose to screen gestational diabetes mellitus before the 24th gestational week in women with different pre-pregnancy body mass index.

Background: Gestational diabetes mellitus (GDM) is usually diagnosed between 24th and 28th gestational week using the 75-g oral glucose tolerance test (OGTT). It is difficult to predict GDM before 24th gestational week because fast plasma glucose (FPG) decreases as the gestational age increases. It is controversial that if FPG ≥5.

A randomized clinical trial of exercise during pregnancy to prevent gestational diabetes mellitus and improve pregnancy outcome in overweight and obese pregnant women.

Background: Obesity and being overweight are becoming epidemic, and indeed, the proportion of such women of reproductive age has increased in recent times. Being overweight or obese prior to pregnancy is a risk factor for gestational diabetes mellitus, and increases the risk of adverse pregnancy outcome for both mothers and their offspring. Furthermore, the combination of gestational diabetes mellitus with obesity/overweight status may increase the risk of adverse pregnancy outcome attributable to either factor alone.

Increased hepatic peroxisome proliferator-activated receptor coactivator-1α expression precedes the development of insulin resistance in offspring of rats from severe hyperglycemic mothers.

Background: Prenatal hyperglycaemia may increase metabolic syndrome susceptibility of the offspring. An underlying component of the development of these morbidities is hepatic gluconeogenic molecular dysfunction. We hypothesized that maternal hyperglycaemia will influence her offsprings hepatic peroxisome proliferator-activated receptor coactivator-1α (PGC-1α) expression, a key regulator of glucose production in hepatocytes.

Complementary and alternative medicine in the treatment of menopausal symptoms.

A large number of women will pass through menopause each year. Women in menopausal transition experience a variety of menopausal symptoms. Although hormonal therapy remains the most effective treatment, side effects have been reported by several large studies.

Genome-wide analysis of chromatin features identifies histone modification sensitive and insensitive yeast transcription factors.

We propose a method to predict yeast transcription factor targets by integrating histone modification profiles with transcription factor binding motif information. It shows improved predictive power compared to a binding motif-only method. We find that transcription factors cluster into histone-sensitive and -insensitive classes.

Non-thermal effects of terahertz radiation on gene expression in mouse stem cells.

In recent years, terahertz radiation sources are increasingly being exploited in military and civil applications. However, only a few studies have so far been conducted to examine the biological effects associated with terahertz radiation. In this study, we evaluated the cellular response of mesenchymal mouse stem cells exposed to THz radiation.

Integration of protein motions with molecular networks reveals different mechanisms for permanent and transient interactions.

The integration of molecular networks with other types of data, such as changing levels of gene expression or protein-structural features, can provide richer information about interactions than the simple node-and-edge representations commonly used in the network community. For example, the mapping of 3D-structural data onto networks enables classification of proteins into singlish- or multi-interface hubs (depending on whether they have >2 interfaces). Similarly, interactions can be classified as permanent or transient, depending on whether their interface is used by only one or by multiple partners.

A statistical framework for modeling gene expression using chromatin features and application to modENCODE datasets.

We develop a statistical framework to study the relationship between chromatin features and gene expression. This can be used to predict gene expression of protein coding genes, as well as microRNAs. We demonstrate the prediction in a variety of contexts, focusing particularly on the modENCODE worm datasets.

Measuring the evolutionary rewiring of biological networks.

We have accumulated a large amount of biological network data and expect even more to come. Soon, we anticipate being able to compare many different biological networks as we commonly do for molecular sequences. It has long been believed that many of these networks change, or "rewire", at different rates.

Integrative analysis of the Caenorhabditis elegans genome by the modENCODE project.

We systematically generated large-scale data sets to improve genome annotation for the nematode Caenorhabditis elegans, a key model organism. These data sets include transcriptome profiling across a developmental time course, genome-wide identification of transcription factor-binding sites, and maps of chromatin organization. From this, we created more complete and accurate gene models, including alternative splice forms and candidate noncoding RNAs.

Prediction and characterization of noncoding RNAs in C. elegans by integrating conservation, secondary structure, and high-throughput sequencing and array data.

We present an integrative machine learning method, incRNA, for whole-genome identification of noncoding RNAs (ncRNAs). It combines a large amount of expression data, RNA secondary-structure stability, and evolutionary conservation at the protein and nucleic-acid level. Using the incRNA model and data from the modENCODE consortium, we are able to separate known C.

Zebrafish miR-1 and miR-133 shape muscle gene expression and regulate sarcomeric actin organization.

microRNAs (miRNAs) represent approximately 4% of the genes in vertebrates, where they regulate deadenylation, translation, and decay of the target messenger RNAs (mRNAs). The integrated role of miRNAs to regulate gene expression and cell function remains largely unknown. Therefore, to identify the targets coordinately regulated by muscle miRNAs in vivo, we performed gene expression arrays on muscle cells sorted from wild type, dicer mutants, and single miRNA knockdown embryos.

The transcriptional landscape of the yeast genome defined by RNA sequencing.

The identification of untranslated regions, introns, and coding regions within an organism remains challenging. We developed a quantitative sequencing-based method called RNA-Seq for mapping transcribed regions, in which complementary DNA fragments are subjected to high-throughput sequencing and mapped to the genome. We applied RNA-Seq to generate a high-resolution transcriptome map of the yeast genome and demonstrated that most (74.