GDM treatment based on the WeChat platform effectively reduces FBG and 2-h PBG and may improve pregnancy outcomes. However, 1-h PBG was not affected by treatment. Obstetricians should consider the OGTT2h value to increase gestational age at delivery.

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Shale gas and oil is an increasingly important source of unconventional energy. Shale gas and oil reservoirs differ from their conventional counterparts mainly in the nanoporous structures of the former, which play a critical role not only for the resource estimation but also for the shale gas/oil extraction and development. However, the traditional methods for characterizing rock porosities, such as gas sorption (the Brunauer−Emmett−Teller technique, BET), mercury intrusion porosimetry (MIP), scanning electron microscopy (SEM), and transmission electron microscopy (TEM), cannot satisfactorily and adequately measure and characterize the nanoporous structures. Nuclear magnetic resonance (NMR) spectroscopy is known for its sensitivity to local environments at the atomic level and, therefore, can provide an alternative method for the investigation of nanoporous structures in gas shales. This study has refined the low field NMR cryoporometry (NMRC) method and applied it along with other methods such as NMR relaxometry (NMRR) to measure and characterize the nanoporous structures (i.e., the pore size distribution, PSD) of selected shale samples from the Sinian-Cambrian-Ordovician strata at the Low Yangzi Plateau, China. Our NMRC measurements of a controlled porous glass (CPG) and shale samples show that the organic compound octamethylcyclotetrasiloxane (OMCTS) is a superior NMR probe liquid in terms of improved spectral resolution and signal/ noise (S/N) ratio. Comparisons of the NMRC shale PSD results with those from NMRR and gas sorption show that NMRC is an independent and effective method for determining the distribution of nanosized pores in gas shales. Moreover, important parameters such as porosity can also be estimated from the low field NMR cryoporometry.

Low-field nuclear magnetic resonance (LF-NMR) and electronic nose combined with Gas chromatography mass spectrometry (GC-MS) were used to collect the data of moisture state and volatile substances to predict the flavor change of ginger during drying. An back propagation artificial neural network (BP-ANN) model was established with the input values of LF-NMR parameters and the output values of sensors for different flavor substances obtained from electronic nose. The results showed that fresh ginger contained three water components: bound water (T21), immobilized water (T22) and free water (T23), with the corresponding peak areas of A21, A22 and A23, respectively. During drying, the changes of A21 and A22 were not significant, while A23 and ATotal decreased significantly (p < 0.05). Linear discriminant analysis (LDA) of electronic nose data showed that samples with different drying time can be well distinguished. Hierarchical clustering analysis (HCA) confirmed that the electronic nose characteristic sensor data S4, S5, S8 and S13 corresponded with the data measured by GC-MS. The correlation analysis between LF-NMR parameters and characteristic sensors showed that A23 and ATotal were significantly correlated with the volatile components (p < 0.05). The results of the BP-ANN prediction showed that the model fitted well and had strong approximation ability (R>0.95 and error<3.65%) and stability, which indicated that the ANN model can accurately predict the flavor change during ginger drying based on LF-NMR parameters.

A rapid, sensitive, and robust CE-MS method has been developed for the determination of tetracycline, oxytetracycline, and chlortetracycline in milk. Field-amplified sample stacking with electromigration injection (FASS-EMI) was used for the online concentration of tetracyclines. The conditions of separation, MS detection, and stacking were systematically optimized. The optimum buffer composition was 35 mM Tris, 1.1% formic acid, 5% methanol, and 15% ACN. By using the online concentration method of field-enhanced sample stacking (FESI)-EMI stacking, the sensitivity was increased six- to seven-fold. The RSDs (n=6) of the relative migration time of tetracyclines were 1.1-1.4% for intraday and 2.4-2.9% for interday. The RSDs (n=6) of the relative peak area of tetracyclines were 3.2-4.6% for intraday and 4.7-6.1% for interday. The LODs (S/N=3) were 7.14 ng/mL for tetracycline, 11.4 ng/mL for oxytetracycline, and 14.9 ng/mL for chlortetracycline. The method has been successfully used to analyze tetracyclines residues in bovine milk.

One of the modern crop breeding techniques uses doubled haploid plants that contain an identical pair of chromosomes in order to accelerate the breeding process. Rapid haploid identification method is critical for large-scale selections of double haploids. The conventional methods based on the color of the endosperm and embryo seeds are slow, manual and prone to error. On the other hand, there exists a significant difference between diploid and haploid seeds generated by high oil inducer, which makes it possible to use oil content to identify the haploid. This paper describes a fully-automated high-throughput NMR screening system for maize haploid kernel identification. The system is comprised of a sampler unit to select a single kernel to feed for measurement of NMR and weight, and a kernel sorter to distribute the kernel according to the measurement result. Tests of the system show a consistent accuracy of 94% with an average screening time of 4 seconds per kernel. Field test result is described and the directions for future improvement are discussed.

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