Advanced porous organic materials for sample preparation in pharmaceutical analysis

The development of novel sample preparation media plays a crucial role in pharmaceutical analysis. To facilitate the extraction and enrichment of pharmaceutical molecules in complex samples, various functionalized materials have been developed and prepared as adsorbents. Recently, some functionalized porous organic materials have become adsorbents for pharmaceutical analysis due to their unique properties of adsorption and recognition. These advanced porous organic materials, combined with consequent analytical techniques, have been successfully used for pharmaceutical analysis in complex samples such as environmental and biological samples. This review encapsulates the progress of advanced porous materials for pharmaceutical analysis including pesticides, antibiotics, chiral drugs, and other compounds in the past decade. In addition, we also address the limitations and future trends of these porous organic materials in pharmaceutical analysis.     

On-tissue chemical derivatization of volatile metabolites for matrix-assisted laser desorption/ionization mass spectrometry imaging

Mass spectrometry imaging (MSI) of volatile metabolites is challenging, especially in matrix-assisted laser desorption/ionization (MALDI). Most MALDI ion sources operate in vacuum, which leads to the vaporization of volatile metabolites during analysis. In addition, tissue samples are often dried during sample preparation, leading to the loss of volatile metabolites even for other MSI techniques. On-tissue chemical derivatization can dramatically reduce the volatility of analytes. Herein, a derivatization method is proposed utilizing N,N,N-trimethyl-2-(piperazin-1-yl)ethan-1-aminium iodide to chemically modify short-chain fatty acids in chicken cecum, ileum, and jejunum tissue sections before sample preparation for MSI visualization.     

Dispersive liquid-liquid microextraction followed by reversed phase-high performance liquid chromatography for the determination of polybrominated diphenyl ethers at trace levels in landfill leachate and environmental water samples

A simple, rapid and efficient method, dispersive liquid-liquid microextraction (DLLME), has been developed for the extraction and preconcentration of polybrominated diphenyl ethers (PBDEs) in water samples. The factors influencing microextraction efficiencies, such as the kind and volume of extraction and dispersive solvent, the extraction time and the salt effect, were optimized. Under the optimum conditions (sample volume: 5 mL; extraction solvent: tetrachloroethane, 20.0 μL; dispersive solvent: acetonitrile, 1.00 mL; extraction time: below 5 s and without salt addition), the enrichment factors and extraction recoveries were high and ranged from 268 to 305 and 87.0 to 119.1%, respectively. Linearity was observed in the range 0.05-50 ng mL⁻¹ for BDE-28 and BDE-99, and 0.1-100 ng mL⁻¹ for BDE-47 and BDE-209, respectively. Coefficients of correlation (r²) ranged from 0.9995 to 0.9999. The repeatability study was carried out by extracting the spiked water samples at concentration levels of 50 ng mL⁻¹ for BDE-28 and BDE-99, and 100 ng mL⁻¹ for BDE-47 and BDE-209, respectively. The relative standard deviations (R.S.D.s) varied between 3.8 and 6.3% (n = 5). The limits of detection (LODs), based on signal-to-noise ratio (S/N) of 3, ranged from 12.4 to 55.6 pg mL⁻¹ (the wavelength of detector at 226 nm). The relative recoveries of PBDEs from tap, lake water and landfill leachate samples at spiking levels of 5, 10 and 50 ng mL⁻¹ were in the range of 89.7-107.6%, 114.3-119.1% and 87.0-90.9%, respectively. As a result, this method can be successfully applied for the determination of PBDEs in landfill leachate and environmental water samples.     

Synthesis, crystal structure and theoretical investigation of two infinite two-dimensional supra-molecular compounds

Two supra-molecular compounds: (1,1′-biphenyl)-4,4′-diammonium bis(3,5-dinitrobenzoate) (1) and 4,4′-methylene bis(benzenammonium) bis(3,5-dinitrobenzoate) monohydrate (2) were synthesized and characterized by IR spectrum, UV spectrum and element analysis. The single crystal structure analysis indicates that these compositions in two compounds are linked through N–HO and O–HO hydrogen bonds into infinite two-dimensional structure. Moreover, theoretical investigation was performed by using RHF/6-31G(d) method, and their stabilities, frontier molecular orbital composition and Mulliken charge distribution were discussed.     

Comparison of δ13C and δ18O from cellulose,whole wood,and resin-free whole wood from an old high elevation Pinus uncinata in the Spanish central Pyrenees*

δ¹³C and δ¹⁸O values from sapwood of a single Pinus uncinata tree, from a high elevation site in the Spanish Pyrenees, were determined to evaluate the differences between whole wood and resin-free whole wood. This issue is addressed for the first time with P. uncinata over a 38-year long period. Results are also compared with published isotope values of α-cellulose samples from the same tree. The differences in δ¹³C and δ¹⁸O between whole wood and resin-free whole wood vary within the analytical uncertainty of 0.3 and 0.5?‰, respectively, indicating that resin extraction is not necessary for sapwood of P. uncinata. Mean differences between cellulose and whole wood are 0.9?‰ (δ¹³C) and 5.0?‰ (δ¹⁸O), respectively. However, further analyses of different species and other sites are needed to evaluate whether the findings reported here are coherent more generally.     

基于模糊近似熵的抑郁症患者静息态功能磁共振成像信号复杂度分析

提出采用模糊近似熵的方法对功能磁共振成像(functional magnetic resonance imaging,fMRI)复杂度量化分析,并与样本熵进行比较.采用的22个成年抑郁症患者中,11位男性,年龄在18—65岁之间.我们期望测量的静息态fMRI信号复杂度与Goldberger/Lipsitz模型一致,越健康、越稳健其生理表现的复杂度越大,且复杂度随年龄的增大而降低.全脑平均模糊近似熵与年龄之间差异性显著(r=-0.512,p0.001).相比之下,样本熵与年龄之间差异性不显著(r=-0.102,p=0.482).模糊近似熵同样与年龄相关脑区(额叶、顶叶、边缘系统、颞叶、小脑顶叶)之间差异性显著(p0.05),样本熵与年龄相关脑区之间差异性不显著性.这些结果与Goldberger/Lipsitz模型一致,说明采用模糊近似熵分析fMRI数据复杂度是一个有效的新方法.     

职业女性总体幸福感及影响因素研究

用总体幸福感量表对淮安市职业女性进行抽样调查,得到结论,年龄、婚姻状况、教育程度、月收入、健康状况、工作满意度、心理健康自评及家庭地位自评等都对职业女性的心理健康产生影响.所以,建议在有条件的情况下,应对民企及事业单位女性职工、30-40岁及50岁以上职业女性、高学历职业女性、低收入职业女性、身体不健康、工作满意度不高及对家庭地位满意度低的职业女性等的心理健康给予关注.     

强混合样本下最近邻密度估计的渐近正态性

研究了α-混合样本下最近邻密度估计的渐近性质,证明了估计的渐近正态性并且给出了其渐近方差的显式表达式,由此构造了α-混合样本下概率密度的渐近置信区间.     

Reduced Graphene Oxide Non‐covalent Functionalized with Zinc Tetra Phenyl Porphyrin Nanocomposite for Electrochemical Detection of Dopamine in Human Serum and Rat Brain Samples

We described the use of a nanocomposite consisting of reduced graphene oxide and zinc tetraphenylporphyrin (RGO/Zn‐TPP) for electrochemical sensing of dopamine (DA). The surface of RGO was homogeneously functionalized with Zn‐TPP via non‐covalent π‐π interaction. The nanocomposite was characterized by scanning electron microscopy, UV‐Vis spectrometry, nuclear magnetic resonance spectroscopy and electrochemical impedance spectroscopy. The electroanalysis behavior of the nanocomposite was studied by cyclic voltammetry and amperometry. The excellent electrocatalytic activity is found for oxidation of DA, best at working voltage of 0.214 V (vs. Ag/AgCl) and linear response range of 0.04–238.8 μM. The sensitivity and detection limit were of 0.665 μA µM^?1 cm^?2 and 3 nM, respectrively. The electrode is well reproducible, stable, and represents a viable platform for the analysis of DA in DA injection, human serum and rat brain sample.     

High and low frequency unfolded partial least squares regression based on empirical mode decomposition for quantitative analysis of fuel oil samples

Accurate prediction of the model is fundamental to the successful analysis of complex samples. To utilize abundant information embedded over frequency and time domains, a novel regression model is presented for quantitative analysis of hydrocarbon contents in the fuel oil samples. The proposed method named as high and low frequency unfolded PLSR (HLUPLSR), which integrates empirical mode decomposition (EMD) and unfolded strategy with partial least squares regression (PLSR). In the proposed method, the original signals are firstly decomposed into a finite number of intrinsic mode functions (IMFs) and a residue by EMD. Secondly, the former high frequency IMFs are summed as a high frequency matrix and the latter IMFs and residue are summed as a low frequency matrix. Finally, the two matrices are unfolded to an extended matrix in variable dimension, and then the PLSR model is built between the extended matrix and the target values. Coupled with Ultraviolet (UV) spectroscopy, HLUPLSR has been applied to determine hydrocarbon contents of light gas oil and diesel fuels samples. Comparing with single PLSR and other signal processing techniques, the proposed method shows superiority in prediction ability and better model interpretation. Therefore, HLUPLSR method provides a promising tool for quantitative analysis of complex samples.