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. Moreover, we demonstrate that the propagation loss of the single-photon wavepackets in the QDs may be largely suppressed by means of a weak microwave field, by which the storage and routing of the single photons can be made to have high efficiency and fidelity. Our research opens a route for designs of advanced solid-state devices promising for applications in photonic quantum-information processing and transmission based on the QDs with SOC.

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 Λ-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-Λ-type level configuration.

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. Regular exercise has the potential to reduce the risk of developing gestational diabetes mellitus and can be used during pregnancy; however, its efficacy remain controversial. At present, most exercise training interventions are implemented on Caucasian women and in the second trimester, and there is a paucity of studies focusing on overweight/obese pregnant women. OBJECTIVE: We sought to test the efficacy of regular exercise in early pregnancy to prevent gestational diabetes mellitus in Chinese overweight/obese pregnant women. STUDY DESIGN: This was a prospective randomized clinical trial in which nonsmoking women age >18 years with a singleton pregnancy who met the criteria for overweight/obese status (body mass index 24≤28 kg/m2) and had an uncomplicated pregnancy at <12+6 weeks of gestation were randomly allocated to either exercise or a control group. Patients did not have contraindications to physical activity. Patients allocated to the exercise group were assigned to exercise 3 times per week (at least 30 min/session with a rating of perceived exertion between 12-14) via a cycling program begun within 3 days of randomization until 37 weeks of gestation. Those in the control group continued their usual daily activities. Both groups received standard prenatal care, albeit without special dietary recommendations. The primary outcome was incidence of gestational diabetes mellitus. RESULTS: From December 2014 through July 2016, 300 singleton women at 10 weeks' gestational age and with a mean prepregnancy body mass index of 26.78 ± 2.75 kg/m2 were recruited. They were randomized into an exercise group (n = 150) or a control group (n = 150). In all, 39 (26.0%) and 38 (25.3%) participants were obese in each group, respectively. Women randomized to the exercise group had a significantly lower incidence of gestational diabetes mellitus (22.0% vs 40.6%; P < .001). These women also had significantly less gestational weight gain by 25 gestational weeks (4.08 ± 3.02 vs 5.92 ± 2.58 kg; P < .001) and at the end of pregnancy (8.38 ± 3.65 vs 10.47 ± 3.33 kg; P < .001), and reduced insulin resistance levels (2.92 ± 1.27 vs 3.38 ± 2.00; P = .033) at 25 gestational weeks. Other secondary outcomes, including gestational weight gain between 25-36 gestational weeks (4.55 ± 2.06 vs 4.59 ± 2.31 kg; P = .9), insulin resistance levels at 36 gestational weeks (3.56 ± 1.89 vs 4.07 ± 2.33; P = .1), hypertensive disorders of pregnancy (17.0% vs 19.3%; odds ratio, 0.854; 95% confidence interval, 0.434-2.683; P = .6), cesarean delivery (except for scar uterus) (29.5% vs 32.5%; odds ratio, 0.869; 95% confidence interval, 0.494-1.529; P = .6), mean gestational age at birth (39.02 ± 1.29 vs 38.89 ± 1.37 weeks' gestation; P = .5); preterm birth (2.7% vs 4.4%, odds ratio, 0.600; 95% confidence interval, 0.140-2.573; P = .5), macrosomia (defined as birthweight >4000 g) (6.3% vs 9.6%; odds ratio, 0.624; 95% confidence interval, 0.233-1.673; P = .3), and large-for-gestational-age infants (14.3% vs 22.8%; odds ratio, 0.564; 95% confidence interval, 0.284-1.121; P = .1) were also lower in the exercise group compared to the control group, but without significant difference. However, infants born to women following the exercise intervention had a significantly lower birthweight compared with those born to women allocated to the control group (3345.27 ± 397.07 vs 3457.46 ± 446.00 g; P = .049). CONCLUSION: Cycling exercise initiated early in pregnancy and performed at least 30 minutes, 3 times per week, is associated with a significant reduction in the frequency of gestational diabetes mellitus in overweight/obese pregnant women. And this effect is very relevant to that exercise at the beginning of pregnancy decreases the gestational weight gain before the mid-second trimester. Furthermore, there was no evidence that the exercise prescribed in this study increased the risk of preterm birth or reduced the mean gestational age at birth.

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. Our analysis reveals that two particular miRNAs, miR-1 and miR-133, influence gene expression patterns in the zebrafish embryo where they account for >54% of the miRNA-mediated regulation in the muscle. We also found that muscle miRNA targets (1) tend to be expressed at low levels in wild-type muscle but are more highly expressed in dicer mutant muscle, and (2) are enriched for actin-related and actin-binding proteins. Loss of dicer function or down-regulation of miR-1 and miR-133 alters muscle gene expression and disrupts actin organization during sarcomere assembly. These results suggest that miR-1 and miR-133 actively shape gene expression patterns in muscle tissue, where they regulate sarcomeric actin organization.

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. elegans ncRNAs from coding sequences and other genomic elements with a high level of accuracy (97% AUC on an independent validation set), and find more than 7000 novel ncRNA candidates, among which more than 1000 are located in the intergenic regions of C. elegans genome. Based on the validation set, we estimate that 91% of the approximately 7000 novel ncRNA candidates are true positives. We then analyze 15 novel ncRNA candidates by RT-PCR, detecting the expression for 14. In addition, we characterize the properties of all the novel ncRNA candidates and find that they have distinct expression patterns across developmental stages and tend to use novel RNA structural families. We also find that they are often targeted by specific transcription factors (∼59% of intergenic novel ncRNA candidates). Overall, our study identifies many new potential ncRNAs in C. elegans and provides a method that can be adapted to other organisms.

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. It is therefore important to develop a framework to quantify the differences between networks in a unified fashion. We developed such a formalism based on analogy to simple models of sequence evolution, and used it to conduct a systematic study of network rewiring on all the currently available biological networks. We found that, similar to sequences, biological networks show a decreased rate of change at large time divergences, because of saturation in potential substitutions. However, different types of biological networks consistently rewire at different rates. Using comparative genomics and proteomics data, we found a consistent ordering of the rewiring rates: transcription regulatory, phosphorylation regulatory, genetic interaction, miRNA regulatory, protein interaction, and metabolic pathway network, from fast to slow. This ordering was found in all comparisons we did of matched networks between organisms. To gain further intuition on network rewiring, we compared our observed rewirings with those obtained from simulation. We also investigated how readily our formalism could be mapped to other network contexts; in particular, we showed how it could be applied to analyze changes in a range of "commonplace" networks such as family trees, co-authorships and linux-kernel function dependencies.

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 ≥5.1 mmol/L before 24th gestational week should be intervened or not. The aim of this study was to evaluate the value of FPG to screen GDM before 24th gestational week in women with different pre-pregnancy body mass index (BMI). METHODS: This was a multi-region retrospective cohort study in China. Women who had a singleton live birth between June 20, 2013 and November 30, 2014, resided in Beijing, Guangzhou and Chengdu, and received prenatal care in 21 selected hospitals, were included in this study. Pre-pregnancy BMI, FPG before the 24th gestational week, and one-step GDM screening with 75 g-OGTT at the 24th to 28th gestational weeks were extracted from medical charts and analyzed. The pregnant women were classified into four groups based on pre-pregnancy BMI: Group A (underweight, BMI < 18.5 kg/m), Group B (normal, BMI 18.5-23.9 kg/m), Group C (overweight, BMI 24.0-27.9 kg/m) and Group D (obesity, BMI ≥28.0 kg/m). The trend of FPG before 24th week of gestation was described, and the sensitivity and specificity of using FPG before the 24th gestational week to diagnose GDM among different pre-pregnancy BMI groups were reported. Differences in the means between groups were evaluated using independent sample t-test and analysis of variance. Pearson Chi-square test was used for categorical variables. RESULTS: The prevalence of GDM was 20.0% (6806/34,087) in the study population. FPG decreased gradually as the gestational age increased in all pre-pregnancy BMI groups until the 19th gestational week. FPG was higher in women with higher pre-pregnancy BMI. FPG before the 24th gestational week and pre-pregnancy BMI could be used to predict GDM. The incidence of GDM in women with FPG ≥5.10 mmol/L in the 19th to 24th gestational weeks and pre-pregnancy overweight or obesity was significantly higher than that in women with FPG ≥5.10 mmol/L and pre-pregnancy BMI <24.0 kg/m (78.5% [62/79] vs. 52.9% [64/121], χ = 13.425, P < 0.001). CONCLUSIONS: FPG decreased gradually as the gestational age increased in all pre-pregnancy BMI groups until the 19th gestational week. Pre-pregnancy overweight or obesity was associated with an increased FPG value before the 24th gestational week. FPG ≥5.10 mmol/L between 19 and 24 gestational weeks should be treated as GDM in women with pre-pregnancy overweight and obesity.

[Atomic emission spectrometry determination of Au, Pt and Pd after separation and enrichment by hyperbranched polymer].

The present paper shows that the trace amount of gold, platinum and palladium in hydrochloric acid solution can be concentrated by hyperbranched polymer. The new reagent has a rapid adsorption rate and big concentrating capacity. The determination of trace Au, Pt and Pd in sample using carbon powder and strontium carbonate as buffer was carried out by atomic emission spectrometry(AES). Zirconium was selected as internal standard line. The sample was directly loaded into ordinary electrode. The method is simple, rapid and accurate. The condition of determination, and factors of influence were studied. The analysis line of Au, Pt and Pd is 312.3, 306.5 and 311.4 nm respectively. The internal standard line of Zr is 310.7 nm. The linear range of the determination of Au, Pt and Pd is 0-0. 20%, 0-0. 40% and 0-0. 20% respectively. The detection limit of Au, Pt and Pd is 0.010%, 0.0030% and 0.0030% respectively. The method has been applied to the determination of Au, Pt and Pd with satisfactory results.

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. METHOD: We established maternal hyperglycaemia by streptozotocin injection to induce the maternal hyperglycaemic Wistar rat model. Offspring from the severe hyperglycemia group (SDO) and control group (CO) were monitored until 180 days after birth. Blood pressure, lipid metabolism indicators and insulin resistance (IR) were measured. Hepatic PGC-1α expression was analyzed by reverse transcription polymerase chain reaction and Western blotting. mRNA expression of two key enzymes in gluconeogenesis, glucose-6-phosphatase (G-6-Pase) and phosphoenolpyruvate carboxykinase (PEPCK), were analyzed and compared. RESULTS: In the SDO group, PGC-1α expression at protein and mRNA levels were increased, so were expression of G-6-Pase and PEPCK (P < 0.05). The above effects were seen prior to the onset of IR. CONCLUSION: The hepatic gluconeogenic molecular dysfunction may contribute to the metabolic morbidities experienced by this population.

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. An increased number of women seek the use of complementary and alternative medicine (CAM) for treating menopausal symptoms. This review analyzes the evidence from systematic reviews, randomized controlled trials and epidemiological studies of using herbal medicine (Black cohosh, Dong quai, St John's wart, Hops, Wild yam, Ginseng, and evening primrose oil) and acupuncture for the treatment of menopausal symptoms. Evidence supporting the efficacy and safety of most CAM for relief of menopausal symptoms are limited. Future larger and better controlled studies testing the effectiveness of these treatments are needed.

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. Here, we incorporate an additional dimension into molecular networks: dynamic conformational changes. We parse the entire PDB structural databank for alternate conformations of proteins and map these onto the protein interaction network, to compile a first version of the Dynamic Structural Interaction Network (DynaSIN). We make this network available as a readily downloadable resource file, and we then use it to address a variety of downstream questions. In particular, we show that multi-interface hubs display a greater degree of conformational change than do singlish-interface ones; thus, they show more plasticity which perhaps enables them to utilize more interfaces for interactions. We also find that transient associations involve smaller conformational changes than permanent ones. Although this may appear counterintuitive, it is understandable in the following framework: as proteins involved in transient interactions shuttle between interchangeable associations, they interact with domains that are similar to each other and so do not require drastic structural changes for their activity. We provide evidence for this hypothesis through showing that interfaces involved in transient interactions bind fewer classes of domains than those in a control set.

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. The target genes of histone-sensitive transcription factors have stronger histone modification signals than those of histone-insensitive ones. The two classes also differ in tendency to interact with histone modifiers, degree of connectivity in protein-protein interaction networks, position in the transcriptional regulation hierarchy, and in a number of additional features, indicating possible differences in their transcriptional regulation mechanisms.

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. Moreover, our framework reveals the positional contribution around genes (upstream or downstream) of distinct chromatin features to the overall prediction of expression levels.

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 (74.5%) of the nonrepetitive sequence of the yeast genome is transcribed. We confirmed many known and predicted introns and demonstrated that others are not actively used. Alternative initiation codons and upstream open reading frames also were identified for many yeast genes. We also found unexpected 3'-end heterogeneity and the presence of many overlapping genes. These results indicate that the yeast transcriptome is more complex than previously appreciated.

Preparation and evaluation of non-bonded hyperbranched polymer-coated columns for capillary electrophoresis.

A series of hyperbranched poly(amine-ester)s based on 1,1,1-trimethylolpropane, methyl acrylate and diethanolamine were synthesized and coated on the inner surface of the fused-silica capillaries by physical adsorption. The most effective coating was the seventh generation hyperbranched poly(amine-ester) coating, which reduced the electroosmotic flow (EOF) greatly and suppressed protein adsorption effectively. The high separation efficiencies for basic proteins were obtained and the coating had a good stability.