Identification of metabolic markers in patients with type 2 Diabetes by Ultrafast gas chromatography coupled to electronic nose. A pilot study

Metabolomics is a potential tool for the discovery of new biomarkers in the early diagnosis of diseases. An ultra-fast gas chromatography system equipped to an electronic nose detector (FGC eNose) was used to identify the metabolomic profile of Volatile Organic Compounds (VOCs) in type 2 diabetes (T2D) urine from Mexican population. A cross-sectional, comparative, and clinical study with translational approach was performed. We recruited twenty T2D patients and twenty-one healthy subjects. Urine samples were taken and analyzed by FGC eNose. Eighty-eight compounds were identified through Kovats's indexes. A natural variation of 30% between the metabolites, expressed by study groups, was observed in Principal Component 1 and 2 with a significant difference (p < 0.001). The model, performed through a Canonical Analysis of Principal coordinated (CAP), allowed a correct classification of 84.6% between healthy and T2D patients, with a 15.4% error. The metabolites 2-propenal, 2-propanol, butane- 2,3-dione and 2-methylpropanal, were increased in patients with T2D, and they were strongly correlated with discrimination between clinically healthy people and T2D patients. This study identified metabolites in urine through FGC eNose that can be used as biomarkers in the identification of T2D patients. However, more studies are needed for its implementation in clinical practice.     

Purity determination of a new antifungal drug candidate using quantitative 1H NMR spectroscopy: Method validation and comparison of calibration approaches

Quantitative nuclear magnetic resonance (qNMR) is an analytical technique that offers numerous advantages in pharmaceutical applications including minimum sample preparation and rapid data collection times with no need for response factor corrections, being a powerful tool for assaying drug content in both drug discovery and early drug development. In the present work, we have applied qNMR, using both the internal standard and the electronic reference to access in vivo concentrations 2 calibration methods, to assess the purity of RI76, a novel antifungal drug candidate. NMR acquisition and processing parameters were optimized in order to obtain spectra with intense, well-resolved signals of completely relaxed nuclei. The analytical method was validated following current guidelines, demonstrating selectivity, linearity, accuracy, precision, and robustness. The calibration approaches were statistically compared, and no significant difference was observed when comparing the obtained results and their dispersion in terms of relative standard deviation. The proposed qNMR method may, therefore, be used for both qualitative and quantitative assessments of RI76 in early drug development and for characterization of this compound.     

Computational and dynamic NMR investigation of 2,2-dimesityl-1,1,1,3,3,3-hexamethyltrisilane

The structure and rotational barrier for the mesityl-silicon bond of 2,2-dimesityl-1,1,1,3,3,3-hexamethyltrisilane have been investigated by ¹H- and ¹³C-variable temperature nuclear magnetic resonance (NMR) as well as by density functional theory structural calculations. The calculations show that the lowest energy structure has C₂ symmetry with nonequivalent ortho methyl groups, consistent with the crystal structure and solution NMR. The nonequivalent ortho methyl groups exchange through a C_s transition state with a calculated relative free energy of 11.0 kcal mol⁻¹. The barrier for this rotation found by dynamic NMR is 13.4 ± 0.2 kcal mol⁻¹ at 298 K.     

Gas-phase 21Ne NMR studies and the nuclear magnetic dipole moment of neon-21

Gas-phase ²¹Ne nuclear magnetic resonance spectra were measured at the natural abundance of ²¹Ne isotope for samples consisting of pressurized neon up to 60 bar at room temperature and applying the magnetic field of the strength B₀ = 11.7574 T. It showed that the nuclear magnetic resonance frequency is linearly dependent on the density of gaseous neon. The resonance frequency was extrapolated to the zero-density point, and it permitted the determination of the ²¹Ne nuclear magnetic moment, μ(²¹Ne) = 0.6617774(10) μ_N. The present value of μ(²¹Ne) is not influenced by the bulk magnetic susceptibility of neon and interactions between neon atoms; therefore, it is more precise and reliable than the previous result obtained for μ(²¹Ne).     

Micro/Nanoengineered α-Fe2O3 Nanoaggregate Conformably Enclosed by Ultrathin N-Doped Carbon Shell for Ultrastable Lithium Storage and Insight into Phase Evolution Mechanism

The Fe-based transition metal oxides are promising anode candidates for lithium storage considering their high specific capacity, low cost, and environmental compatibility. However, the poor electron/ion conductivity and significant volume stress limit their cycle and rate performances. Furthermore, the phenomena of capacity rise and sudden decay for α-Fe₂O₃ have appeared in most reports. Here, a uniform micro/nano α-Fe₂O₃ nanoaggregate conformably enclosed in an ultrathin N-doped carbon network (denoted as M/N-α-Fe₂O₃@NC) is designed. The M/N porous balls combine the merits of secondary nanoparticles to shorten the Li⁺ transportation pathways as well as alleviating volume expansion, and primary microballs to stabilize the electrode/electrolyte interface. Furthermore, the ultrathin carbon shell favors fast electron transfer and protects the electrode from electrolyte corrosion. Therefore, the M/N-α-Fe₂O₃@NC electrode delivers an excellent reversible capacity of 901 mA h g⁻¹ with capacity retention up to 94.0 % after 200 cycles at 0.2 A g⁻¹. Notably, the capacity rise does not happen during cycling. Moreover, the lithium storage mechanism is elucidated by ex situ XRD and HRTEM experiments. It is verified that the reversible phase transformation of α↔γ occurs during the first cycle, whereas only the α-Fe₂O₃ phase is reversibly transformed during subsequent cycles. This study offers a simple and scalable strategy for the practical application of high-performance Fe₂O₃ electrodes.     

单层n型MoS2/p型c-Si异质结太阳电池数值模拟

单层二硫化钼(MoS₂)是一种具有优异光电性能的半导体材料,在太阳能能量转换中表现出很大的应用潜力。本文基于AMPS模拟软件,对单层n型MoS₂/p型c-Si异质结太阳电池进行了数值模拟与分析。通过模拟优化,n型MoS₂的电子亲和能为3.75 eV、掺杂浓度为10¹⁸ cm^-3,p型c-Si的掺杂浓度为10¹⁷ cm^-3时,太阳电池能够取得最高22.1%的转换效率。最后模拟了n型MoS₂/p型c-Si异质结界面处的界面态对太阳电池性能的影响,发现界面态密度超过10¹¹ cm^-2·eV^-1时会严重影响太阳电池的光伏性能。     

基于Nie-Tan算法的区间二型模糊集质心计算:改变主变量采样个数

计算区间二型模糊集的质心(也称降型)是区间二型模糊逻辑系统中的一个重要模块。Karnik-Mendel(KM)迭代算法通常被认为是计算区间二型模糊集质心的标准算法。尽管如此,KM算法涉及复杂的计算过程,不利于实时应用。在各种改进类算法中,非迭代的Nie-Tan(NT)算法可节省计算消耗。此外,连续版本NT(CNT,continuous version of NT)算法被证明是计算质心的准确算法。本文比较了离散版本NT算法中求和运算和连续版本NT算法中求积分运算,通过四个计算机仿真例子证实了当适度增加区间二型模糊集主变量采样个数时,NT算法的计算结果可以精确地逼近CNT算法。     

铅基堆超临界CO2复合循环发电系统热力学分析

本文对比了再压缩超临界CO2 (S-CO2)循环、蒸汽朗肯循环、He布雷顿循环分别应用于铅基堆的最优热学性能,明确了S-CO2循环与铅基堆结合较传统循环的热力学优势。为进一步提高再压缩S-CO2循环的效率,以跨临界CO2 (T-CO2)循环为底循环构建了再压缩S-CO2/T-CO2复合循环,探讨了不同顶循环透平入口温度、压力和压缩机入口温度条件下系统性能的变化规律,对比了S-CO2/T-CO2复合循环和S-CO2循环的热学性能。结果表明:铅基堆再压缩S-CO2循环发电系统较传统循环形式具有更高的热效率;构建的S-CO2/T-CO2复合循环能够有效提高S-CO2循环的效率,在所研究参数范围内,S-CO2/T-CO2复合循环的热效率和效率比S-CO2循环分别最大可提高约4.8%和8.3%;再压缩S-CO2循环和S-CO2/T-CO2复合循环热学性能随顶循环关键参数变化规律具有一致性。     

基于深度学习的ELM实时识别研究

基于深度学习的方法，在HL-2A装置上开发出了一套边缘局域模(ELM)实时识别算法。算法使用5200次放电数据(约24.19万数据切片)进行学习，得到一个深度为22层的卷积神经网络。为衡量算法的识别能力，识别了HL-2A装置自2009年实现稳定ELMy H模放电以来所有历史数据(约26000次放电数据)，共识别出1665次H模放电，其中误识别35次，误报率为2.10%。在实际的1634次H模放电中，漏识别4次，漏识别率为0.24%。该误报率和漏报率可以满足ELM实时识别的精度要求。识别算法在实时控制环境下，对单个时间点的平均计算时间为0.46ms，可以满足实时控制的计算速度要求。