三重四极杆电感耦合等离子体质谱(ICP-MS)法测定氧化铕中13种稀土杂质元素

稀土杂质元素直接影响高纯单金属稀土材料的整体性能,是高科技领域许多材料的重要组成部分。通过考察最佳的消解酸量、温度、时间、氧气反应气流量、稀释气流量,建立了基于三重四极杆电感耦合等离子体质谱仪(ICP-MS/MS)直接测定氧化铕中13种稀土杂质元素分析方法。该方法采用0.1%基体直接进样,可以很大程度提高前处理分析效率。利用碰撞模式测定氧化铕稀土中的Y、La、Pr、Nd、Sm、Gd、Tb、Dy、Ho、Er、Yb、Lu元素,氧气质量转移模式测定氧化铕中的Tm,两种模式结合可以有效去除多原子干扰,实现氧化铕的稳定测试分析。通过对氧化铕标准物质（GBW02902）直接测定分析,结果表明,在碰撞和氧气质量转移模式下,各元素线性相关系数（r）均大于 0.9999,方法检出限为0.001~0.023 mg/kg,测试精密度优于1.99%,13种元素的测试值都在认定值的不确定度范围之内。该分析方法操作简单,测试稳定,效率高,为实验室进行氧化铕材料中REE杂质的准确测试分析提供思路和借鉴。     

基于化学计量学结合ICP-MS的党参道地性的研究及安全评价

微量元素与中药的功效和安全性密切相关,也是药材道地性研究的一部分,为探讨党参中重金属元素的安全性、风险性及道地性的相关性。本文采用电感耦合等离子体质谱法（ICP-MS）及原子荧光光谱法(AFS)测定来源于甘肃、山西、湖北、四川等产区的39批党参药材中的20种元素的含量,结果结合化学计量学分析对党参产区进行差异判别。通过单因子污染指数法和内梅罗综合污染指数法对其进行安全性评价,通过健康风险基于暴露量、危害指数法和暴露限值法对其进行风险评估。结果表明,重金属在各自范围内线性关系良好,加样回收率,仪器精密度和重复性良好,其中 Ba、Sr、Mn的含量最高。主成分分析显示39批药材分为三类,同一产区的党参能较好的聚在一起,元素含量差异与产区分布有一定规律,其中Cs、Ga、As、Co、Li、Pb、Hg、Se、V、Mn为关键的差异标志物,为产地元素特征分析鉴别提供依据。安全评价结果为39批党参药材污染等级为安全,但风险评估后DS-31、DS-32、DS-34、DS-36及 DS-37在人体长期蓄积中具有健康风险。结论：本研究方法高效、准确、简便,结合化学计量学可以对党参进行有效的产地判别,评价党参中元素的安全性及风险性,为党参道地性及健康评价提供了科学依据。     

动能歧视(KED)-电感耦合等离子体质谱(ICP-MS)法测定贵州沉积型稀土矿中16种稀土元素

贵州沉积型稀土矿主要含有高岭土-锐钛矿石等矿物,存在高含量Si、Al、Fe、Ti、Zr等难溶基体元素,采用高压密闭微波消解法处理难以将其完全溶解,易使测定结果偏低,需再次消解或进一步电热板敞开酸溶处理,方法耗时长,不利于大批量样品检测需求。同时电感耦合等离子体质谱法(ICP-MS)在测定稀土元素时存在基体效应和质谱干扰,影响了检测数据的准确性。本文采用过氧化钠熔融分解样品,熔融物冷却后引入三乙醇胺溶液,在碱性溶液中,大量基体元素与三乙醇胺形成稳定配合物,并与大量溶剂钠盐存于溶液中,稀土元素与Ca、Mg、Sr、Ba等留存于沉淀,经过滤,实现稀土元素与大量基体元素分离,随后沉淀用(1+1)硝酸复溶,并以103Rh和185Re为在线注入内标协同降低基体干扰;启用动能歧视(KED)模式以降低测定过程中潜在的质谱干扰。实验结果表明:高压密闭微波消解法消解液浑浊有残渣,溶矿耗时长,测试结果偏低,碱溶法酸化后溶液清亮透明,稀土元素测定值准确性高;经条件试验,采用10%三乙醇胺溶液提取能较大降低基体干扰;启用KED模式可降低测定过程中的质谱干扰,且准确度优于STD模式;碱溶法方法检出限为0.008μg/g~0.049μg/g,测定下限为0.034μg/g~0.195μg/g,相对标准偏差RSD在0.78%～10.2%之间,相对误差RE在0.0225%~13.5%之间。经实际样品验证,碱熔法较适用于贵州沉积性稀土矿中16种稀土元素的测定。     

Chemometric Analysis of Urinary Volatile Organic Compounds to Monitor the Efficacy of Pitavastatin Treatments on Mammary Tumor Progression over Time

Volatile organic compounds (VOCs) in urine are potential biomarkers of breast cancer. Previously, our group has investigated breast cancer through analysis of VOCs in mouse urine and identified a panel of VOCs with the ability to monitor tumor progression. However, an unanswered question is whether VOCs can be exploited similarly to monitor the efficacy of antitumor treatments over time. Herein, subsets of tumor-bearing mice were treated with pitavastatin at high (8 mg/kg) and low (4 mg/kg) concentrations, and urine was analyzed through solid-phase microextraction (SPME) coupled with gas chromatography-mass spectrometry (GC-MS). Previous investigations using X-ray and micro-CT analysis indicated pitavastatin administered at 8 mg/kg had a protective effect against mammary tumors, whereas 4 mg/kg treatments did not inhibit tumor-induced damage. VOCs from mice treated with pitavastatin were compared to the previously analyzed healthy controls and tumor-bearing mice using chemometric analyses, which revealed that mice treated with pitavastatin at high concentrations were significantly different than tumor-bearing untreated mice in the direction of healthy controls. Mice treated with low concentrations demonstrated significant differences relative to healthy controls and were reflective of tumor-bearing untreated mice. These results show that urinary VOCs can accurately and noninvasively predict the efficacy of pitavastatin treatments over time.     

Domain Adaptation with Data Uncertainty Measure Based on Evidence Theory

Domain adaptation aims to learn a classifier for a target domain task by using related labeled data from the source domain. Because source domain data and target domain task may be mismatched, there is an uncertainty of source domain data with respect to the target domain task. Ignoring the uncertainty may lead to models with unreliable and suboptimal classification results for the target domain task. However, most previous works focus on reducing the gap in data distribution between the source and target domains. They do not consider the uncertainty of source domain data about the target domain task and cannot apply the uncertainty to learn an adaptive classifier. Aimed at this problem, we revisit the domain adaptation from source domain data uncertainty based on evidence theory and thereby devise an adaptive classifier with the uncertainty measure. Based on evidence theory, we first design an evidence net to estimate the uncertainty of source domain data about the target domain task. Second, we design a general loss function with the uncertainty measure for the adaptive classifier and extend the loss function to support vector machine. Finally, numerical experiments on simulation datasets and real-world applications are given to comprehensively demonstrate the effectiveness of the adaptive classifier with the uncertainty measure.     

Sensing the ortho Positions in C6Cl6 and C6H4Cl2 from Cl2− Formation upon Molecular Reduction

The geometrical effect of chlorine atom positions in polyatomic molecules after capturing a low-energy electron is shown to be a prevalent mechanism yielding Cl₂⁻. In this work, we investigated hexachlorobenzene reduction in electron transfer experiments to determine the role of chlorine atom positions around the aromatic ring, and compared our results with those using ortho-, meta- and para-dichlorobenzene molecules. This was achieved by combining gas-phase experiments to determine the reaction threshold by means of mass spectrometry together with quantum chemical calculations. We also observed that Cl₂⁻ formation can only occur in 1,2-C₆H₄Cl₂, where the two closest C–Cl bonds are cleaved while the chlorine atoms are brought together within the ring framework due to excess energy dissipation. These results show that a strong coupling between electronic and C–Cl bending motion is responsible for a positional isomeric effect, where molecular recognition is a determining factor in chlorine anion formation.     

Proteome Analysis of Aflibercept Intervention in Experimental Central Retinal Vein Occlusion

Aflibercept is a frequently used inhibitor of vascular endothelial growth factor (VEGF) in the treatment of macular edema following central retinal vein occlusion (CRVO). Retinal proteome changes following aflibercept intervention in CRVO remain largely unstudied. Studying proteomic changes of aflibercept intervention may generate a better understanding of mechanisms of action and uncover aspects related to the safety profile. In 10 Danish Landrace pigs, CRVO was induced in both eyes with an argon laser. Right eyes were treated with intravitreal aflibercept while left control eyes received isotonic saline water. Retinal samples were collected 15 days after induced CRVO. Proteomic analysis by tandem mass tag-based mass spectrometry identified a total of 21 proteins that were changed in content following aflibercept intervention. In retinas treated with aflibercept, high levels of aflibercept components were reached, including the VEGF receptor-1 and VEGF receptor-2 domains. Fold changes in the additional proteins ranged between 0.70 and 1.19. Aflibercept intervention resulted in a downregulation of pigment epithelium-derived factor (PEDF) (fold change = 0.84) and endoplasmin (fold change = 0.91). The changes were slight and could thereby not be confirmed with less precise immunohistochemistry and Western blotting. Our data suggest that aflibercept had a narrow mechanism of action in the CRVO model. This may be an important observation in cases when macular edema secondary to CRVO is resistant to aflibercept intervention.     

Separation of Dihydro-Isocoumarins and Dihydro-Stilbenoids from Hydrangea macrophylla ssp. serrata by Use of Counter-Current Chromatography

Previously, different Hydrangea macrophylla ssp. serrata cultivars were investigated by untargeted LC-MS analysis. From this, a list of tentatively identified and unknown compounds that differ significantly between these cultivars was obtained. Due to the lack of reference compounds, especially for dihydro-isocoumarins, we aimed to isolate and structurally characterise these compounds from the cultivar ‘Yae-no-amacha’ using NMR and LC-MS methods. For purification and isolation, counter-current chromatography was used in combination with reversed-phase preparative HPLC as an orthogonal and enhanced purification workflow. Thirteen dihydro-isocoumarins in combination with other metabolites could be isolated and structurally identified. Particularly interesting was the clarification of dihydrostilbenoid glycosides, which were described for the first time in H. macrophylla ssp. serrata. These results will help us in further studies on the biological interpretation of our data.     

Precise Quantification of Molybdate In Vitro by the FRET-Based Nanosensor ‘MolyProbe’

Molybdenum (Mo) is an essential trace element in all kingdoms of life. Mo is bioavailable as the oxyanion molybdate and gains biological activity in eukaryotes when bound to molybdopterin, forming the molybdenum cofactor. The imbalance of molybdate homeostasis results in growth deficiencies or toxic symptoms within plants, fungi and animals. Recently, fluorescence resonance energy transfer (FRET) methods have emerged, monitoring cellular and subcellular molybdate distribution dynamics using a genetically encoded molybdate-specific FRET nanosensor, named MolyProbe. Here, we show that the MolyProbe system is a fast and reliable in vitro assay for quantitative molybdate determination. We added a Strep-TagII affinity tag to the MolyProbe protein for quick and easy purification. This MolyProbe is highly stable, resistant to freezing and can be stored for several weeks at 4 °C. Furthermore, the molybdate sensitivity of the assay peaked at low nM levels. Additionally, The MolyProbe was applied in vitro for quantitative molybdate determination in cell extracts of the plant Arabidopsis thaliana, the fungus Neurospora crassa and the yeast Saccharomyces cerevisiae. Our results show the functionality of the Arabidopsis thaliana molybdate transporter MOT1.1 and indicate that FRET-based molybdate detection is an excellent tool for measuring bioavailable Mo.     

Comparing Efficiency of Lysis Buffer Solutions and Sample Preparation Methods for Liquid Chromatography–Mass Spectrometry Analysis of Human Cells and Plasma

The use of a proper sample processing methodology for maximum proteome coverage and high-quality quantitative data is an important choice to make before initiating a liquid chromatography–mass spectrometry (LC–MS)-based proteomics study. Popular sample processing workflows for proteomics involve in-solution proteome digestion and single-pot, solid-phase-enhanced sample preparation (SP3). We tested them on both HeLa cells and human plasma samples, using lysis buffers containing SDS, or guanidinium hydrochloride. We also studied the effect of using commercially available depletion mini spin columns before SP3, to increase proteome coverage in human plasma samples. Our results show that the SP3 protocol, using either buffer, achieves the highest number of quantified proteins in both the HeLa cells and plasma samples. Moreover, the use of depletion mini spin columns before SP3 results in a two-fold increase of quantified plasma proteins. With additional fractionation, we quantified nearly 1400 proteins, and examined lower-abundance proteins involved in neurodegenerative pathways and mitochondrial metabolism. Therefore, we recommend the use of the SP3 methodology for biological sample processing, including those after depletion of high-abundance plasma proteins.