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Evaluation of portable atmospheric-pressure solids analysis probe–quadrupole mass spectrometry and UPLC−MS for the rapid screening of illicit substances in human urine 便携式常压固体分析探针-四极杆质谱法和UPLC - MS快速筛选人类尿液中违禁物质的评价
IF 4 2区 化学 Q1 BIOCHEMICAL RESEARCH METHODS Pub Date : 2026-01-20 DOI: 10.1016/j.chroma.2026.466720
Doreen N.B Chandra Siri , Si Ling Ng , Ngee Sing Chong , Philip J. Marriott , Yong Foo Wong
Atmospheric-pressure solids analysis probe (ASAP) is an ambient pressure ionisation mass spectrometry technique that allows the direct analysis of liquids and solids, with or without sample preparation, producing rapid, efficient, and real-time results. In this study, portable ASAP−quadrupole mass spectrometry (ASAP−QMS) method in positive ion mode was demonstrated for the rapid analysis of 9 drugs of abuse (amphetamine, methamphetamine, oxycodone, methadone, morphine, 3,4-methylenedioxymethamphetamine, ketamine, 6-monoacetylmorphine, and cocaine), fortified in water and urine samples, with analysis time of ∼30 s. Initially, a direct analysis approach without sample preparation was applied to fortified water and urine samples. However, significant urine matrix effects were observed, leading to ion suppression and detector saturation. A simple solid-phase extraction (SPE) procedure was then applied to reduce matrix effects arising from the urine samples. The influence of cone voltages on the fragmentation and abundance of molecular ions for the illicit compounds was evaluated. The analytes exhibited limits of detection in the range of 0.3 – 2 µg mL-1, which were considerably higher than the UPLC−ESIMS (0.05 – 0.1 µg mL-1) method. Drug compounds identification was performed via MS spectrum matching against an in-house database. Comparative assessment with UPLC−ESI linear ion trap MS using United Nations Office on Drugs and Crime International Collaborative Exercises urine samples showed detection accuracies of 43% for ASAP−QMS and 100% for the UPLC−MS method. The lower accuracy of ASAP−QMS was attributed to the poor spectral library matching (similarity scores < 850) in complex urine matrices, particularly for low-concentration drug compounds. Nevertheless, portable ASAP−QMS (with SPE) achieved a higher greenness assessment score (0.54) compared to UPLC−MS (0.37), highlighting its potential as a rapid and environmentally friendly drug screening approach.
大气压固体分析探针(ASAP)是一种环境压力电离质谱技术,允许直接分析液体和固体,有或没有样品制备,产生快速,高效和实时的结果。在这项研究中,便携式ASAP -四极杆质谱(ASAP - QMS)方法在正离子模式下用于快速分析9种滥用药物(安非他命,甲基苯丙胺,羟考酮,美沙酮,吗啡,3,4-亚甲基二氧基甲基苯丙胺,氯胺酮,6-单乙酰吗啡和可卡因),强化水和尿液样品,分析时间为~ 30 s。最初,没有样品制备的直接分析方法应用于强化水和尿液样本。然而,观察到明显的尿基质效应,导致离子抑制和检测器饱和。然后采用简单的固相萃取(SPE)程序来减少尿液样品中产生的基质效应。评估了锥体电压对非法化合物分子离子的碎片化和丰度的影响。分析物的检出限为0.3 ~ 2µg mL-1,显著高于UPLC - ESIMS(0.05 ~ 0.1µg mL-1)方法。通过MS谱与内部数据库匹配进行药物化合物鉴定。与UPLC - ESI线性离子阱质谱(使用联合国毒品和犯罪问题办公室国际合作训练尿液样本)的比较评估显示,ASAP - QMS的检测准确率为43%,UPLC - MS方法的检测准确率为100%。ASAP - QMS较低的准确性是由于在复杂的尿液基质中,特别是在低浓度的药物化合物中,谱库匹配差(相似分数<; 850)。尽管如此,与UPLC - MS(0.37)相比,便携式ASAP - QMS (with SPE)获得了更高的绿色评价分数(0.54),突出了其作为一种快速和环保的药物筛选方法的潜力。
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引用次数: 0
Rapid detection of perfluorinated compounds in tap water using confined methanol 使用密闭甲醇快速检测自来水中的全氟化合物
IF 4 2区 化学 Q1 BIOCHEMICAL RESEARCH METHODS Pub Date : 2026-01-19 DOI: 10.1016/j.chroma.2026.466718
Xinyang Zhang, Huilan Piao, Mengqing Cui, Xiangzi Jin, Meihui Tong, Donghao Li, Yilin Zou
Perfluorinated compounds (PFCs), characterized by their persistence and bioaccumulative properties, have been extensively detected across diverse environmental compartments, including aquatic systems, sediments, and organisms. These contaminants enter human bodies via food chain transfer, subsequently undergoing internal transport and metabolic transformation. Meanwhile, the detection of samples is also difficult to achieve sensitivity analysis due to the low content of the analytes and the complex matrix. Based on this, we propose a novel approach for analyzing the derivatives of 9 PFCs (derivatization reaction conditions: 1 min, room temperature) in tap water using carbon nanofibers/carbon fibers (CNFs/CFs) nanoconfined solvent extraction method, termed nanoconfined liquid phase nanoextraction (NLPNE), coupled with gas chromatography-mass spectrometry (GC–MS). The effect of various experimental parameters on extraction efficiency was investigated using a Box-Behnken design (BBD), such as volume of nanoconfined solvent, extraction time and desorption time, which method requires a less solvent-consumption (20 μL) and time ≤ 1 min, meeting the requirements for green environmental and sustainable development. Under optimal conditions, the developed method shown good linearity within the studied concentration range. Accuracy was evaluated by analyzing the extraction recovery of spiked tap water sample, the satisfactory recoveries (71.31%-126.15%) with RSD ≤ 17.45%. In addition, the limits of detection (LODs) for the analytes were in the range of 0.2–3 μg L−1, which the sensitivity has been significantly improved. Considering the versatility of nanoconfined solvent extraction method, indicated that the NLPNE is a promising pretreatment technique for detecting PFCs in real samples.
全氟化合物(pfc)的特点是具有持久性和生物蓄积性,已在各种环境隔间(包括水生系统、沉积物和生物体)中广泛检测到。这些污染物通过食物链转移进入人体,然后进行内部运输和代谢转化。同时,由于分析物含量低、基质复杂,对样品的检测也难以实现灵敏度分析。基于此,我们提出了一种新的方法来分析自来水中9种PFCs的衍生物(衍生化反应条件:1 min,室温),使用纳米碳纤维/碳纤维(CNFs/CFs)纳米约束溶剂萃取法,称为纳米约束液相纳米萃取(NLPNE),结合气相色谱-质谱(GC-MS)。采用Box-Behnken设计(BBD)考察了纳米溶剂体积、萃取时间和解吸时间等实验参数对提取效率的影响,该方法溶剂用量少(20 μL),萃取时间≤1 min,满足绿色环保和可持续发展的要求。在最佳条件下,所建立的方法在研究的浓度范围内具有良好的线性关系。通过分析加标自来水样品的提取回收率来评价其准确性,满意回收率为71.31% ~ 126.15%,RSD≤17.45%。分析物的检出限(lod)在0.2 ~ 3 μg L−1范围内,灵敏度明显提高。考虑到纳米限制溶剂萃取方法的通用性,表明NLPNE是一种很有前途的检测实际样品中PFCs的前处理技术。
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引用次数: 0
Advances in desorption electrospray ionization mass spectrometry imaging: Research progress and applications 解吸电喷雾电离质谱成像的研究进展及应用
IF 4 2区 化学 Q1 BIOCHEMICAL RESEARCH METHODS Pub Date : 2026-01-19 DOI: 10.1016/j.chroma.2026.466719
Xujun Zhang , Shan Wang , Bo Sui , Yan Wang , Lingbo Ji , Jianxun Zhang , Ajuan Yu , Wu Fan , Wuduo Zhao
Desorption electrospray ionization mass spectrometry imaging (DESI-MSI) is regarded as a novel molecular imaging approach that integrates DESI source with conventional mass spectrometry to provide spatial information and molecular composition on the sample’s surface. In this review, the principle of DESI-MSI was elucidated, including its desorption process and ionization mechanism. Through the applications in biological tissues and organs, the advantages of DESI-MSI technology were demonstrated in exploring the tissue functional roles and disease mechanisms, including brain, liver, kidney, and lung. Building on these findings, we review DESI-MSI’s unique capability to map both exogenous and endogenous biomolecules, thereby providing insights into spatial distribution of exogenous organisms and endogenous metabolic of transformation pathways and pharmacokinetics. Finally, the recent applications of DESI-MSI in biomedicine, environmental monitoring, and food safety are also reviewed. With the continuous improvement of instruments and analysis methods, DESI-MSI is expected to bring meaningful changes across a growing number of fields, opening up exciting opportunities to support innovative technologies and applied research.
解吸电喷雾电离质谱成像(DESI- msi)是一种新型的分子成像方法,它将DESI源与传统的质谱相结合,提供样品表面的空间信息和分子组成。本文综述了DESI-MSI的原理,包括其解吸过程和电离机理。通过在生物组织器官中的应用,展示了DESI-MSI技术在探索脑、肝、肾、肺等组织功能作用和疾病机制方面的优势。在这些发现的基础上,我们回顾了DESI-MSI绘制外源性和内源性生物分子的独特能力,从而提供了外源性生物的空间分布和内源性代谢转化途径和药代动力学的见解。最后,对DESI-MSI在生物医学、环境监测、食品安全等方面的应用进行了综述。随着仪器和分析方法的不断改进,DESI-MSI有望在越来越多的领域带来有意义的变化,为支持创新技术和应用研究开辟令人兴奋的机会。
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引用次数: 0
L-Cys-functionalized Zr-based MOF NU-1000: Fabrication and application as chiral stationary phase in open tubular capillary electrochromatography for chiral separation l - ys功能化zr基MOF NU-1000的制备及其在开管毛细管电色谱手性分离中的应用
IF 4 2区 化学 Q1 BIOCHEMICAL RESEARCH METHODS Pub Date : 2026-01-18 DOI: 10.1016/j.chroma.2026.466716
Gege Zhu , Li Qi , Bing Niu , Qi Zhang , Qin Chen , Dan Zhong , Xiaodong Sun
Metal-organic frameworks (MOFs) are promising chiral separation materials owing to their well-defined pore structures and tunable functionality. In this work, mesoporous/microporous NU-1000 was functionalized with L-Cysteine (L-Cys) via solvent-assisted ligand exchange to produce L-Cys-NU-1000, which was applied as a stationary phase in capillary electrochromatography (CEC). The resulting L-Cys-NU-1000@capillary system achieved baseline separation of five chiral amino acid enantiomers with excellent intra-day, inter-day, and batch reproducibility (RSDs < 5%). Notably, the system retained high enantioselectivity even after 100 consecutive injections. This study represents the first application of NU-1000 in chiral separation, opening new avenues for its use and laying a foundation for broader future applications. The system demonstrates distinct advantages for quality control of amino acids, offering high efficiency, robustness, and reproducible enantiomeric separation crucial for food and pharmaceutical analysis.
金属有机骨架(mof)具有良好的孔结构和可调的功能,是一种很有前途的手性分离材料。本研究通过溶剂辅助配体交换,将l -半胱氨酸(L-Cys)功能化得到L-Cys-NU-1000,并将其作为毛细管电色谱(CEC)的固定相。所建立的L-Cys-NU-1000@capillary系统实现了5种手性氨基酸对映体的基线分离,具有良好的日内、日内和批间重现性(rsd < 5%)。值得注意的是,即使在连续注射100次后,该体系仍保持高的对映体选择性。本研究代表了NU-1000在手性分离中的首次应用,为其使用开辟了新的途径,并为未来更广泛的应用奠定了基础。该系统在氨基酸的质量控制方面具有明显的优势,为食品和药物分析提供高效率、稳健性和可重复性的对映体分离。
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引用次数: 0
Integrating hybrid modeling and high throughput screening: A modular process development platform for flowthrough chromatography 集成混合建模和高通量筛选:流动色谱的模块化过程开发平台
IF 4 2区 化学 Q1 BIOCHEMICAL RESEARCH METHODS Pub Date : 2026-01-17 DOI: 10.1016/j.chroma.2026.466715
Llian Mabardi , Janani Ram , Chris Gerberich , André Dumetz , Lucas Kimerer , Kerri Mendola , Justin Godinho , Nicholas Vecchiarello
As the biopharmaceutical industry continues to advance towards intensified manufacturing and increasingly complex therapeutic pipelines, there is a growing demand for more efficient processes and process development strategies. Flowthrough and frontal loading operations are particularly attractive due to their high loading capacities, low buffer consumption, and operational simplicity. High throughput screening combined with mechanistic modeling provides a powerful framework for rapid development of these processes, but model calibration needed across the multitude of resins and conditions during screening remains resource intensive, and accurately capturing transport and kinetic effects is challenging. In this work, neural network and closed-form symbolic regression models were developed to predict protein loading and product yield, which can exclusively use high throughput plate-based data as inputs. To support training these models, a large database of general rate model (GRM) simulations spanning both high molecular weight (HMW) and low molecular weight (LMW) separations was created. This was accompanied by development of novel analytical expressions for loading and yield derived from fundamental principles under ideal chromatography conditions, enabling transport limitations to be treated as perturbations from the ideal case. The resulting machine learning models trained with these data rely solely on easy-to-measure, experimentally accessible inputs from standard plate-based high throughput experiments and therefore provide accurate predictions without the full input parameter set required by the GRM. Neural networks achieved the highest accuracy, while symbolic regression models performed nearly as well with the added advantages of simplicity, interpretability, and ease of implementation. Further, Monte Carlo analysis demonstrated that predictive errors of the machine learning models were comparable to or smaller than those of mechanistic simulations when typical experimental uncertainty in difficult-to-measure input parameters was considered. Building on this, closed-form expressions for productivity were developed that use the machine learning models as inputs to identify resins and operating conditions that maximize performance as a function of residence time. Finally, a platform workflow is proposed that applies these models to translate high throughput data into practical guidance for resin and condition selection, with predicted purities, yields, and productivities aligning well with experimentally-measured column performances. Overall, this proposed platform provides a foundation for seamlessly integrating high throughput screening and hybrid modeling into process development.
随着生物制药行业不断向集约化制造和日益复杂的治疗管道迈进,对更有效的工艺和工艺开发策略的需求不断增长。由于其高装载能力、低缓冲消耗和操作简单,直通和正面装载操作尤其具有吸引力。高通量筛选与机械建模相结合,为这些过程的快速发展提供了强大的框架,但在筛选过程中,需要在多种树脂和条件下进行模型校准,这仍然是资源密集型的,并且准确捕捉运输和动力学效应具有挑战性。在这项工作中,开发了神经网络和封闭形式的符号回归模型来预测蛋白质负载和产品收率,这些模型可以专门使用高通量的基于平板的数据作为输入。为了支持这些模型的训练,创建了一个大型的通用速率模型(GRM)模拟数据库,涵盖高分子量(HMW)和低分子量(LMW)分离。与此同时,在理想色谱条件下,根据基本原理推导出了新的负载和产率分析表达式,使输运限制被视为来自理想情况的扰动。使用这些数据训练的机器学习模型仅依赖于易于测量的,实验上可访问的来自标准板的高通量实验的输入,因此可以提供准确的预测,而无需GRM所需的完整输入参数集。神经网络达到了最高的准确性,而符号回归模型具有简单、可解释性和易于实现的附加优势,表现得几乎一样好。此外,蒙特卡罗分析表明,当考虑到难以测量的输入参数的典型实验不确定性时,机器学习模型的预测误差与机械模拟的预测误差相当或更小。在此基础上,开发了封闭形式的生产力表达式,使用机器学习模型作为输入,以识别树脂和操作条件,使性能最大化,作为停留时间的函数。最后,提出了一个平台工作流,应用这些模型将高通量数据转化为树脂和条件选择的实际指导,预测的纯度、收率和生产率与实验测量的柱性能很好地一致。总的来说,这个提议的平台为无缝集成高通量筛选和混合建模到工艺开发中提供了基础。
{"title":"Integrating hybrid modeling and high throughput screening: A modular process development platform for flowthrough chromatography","authors":"Llian Mabardi ,&nbsp;Janani Ram ,&nbsp;Chris Gerberich ,&nbsp;André Dumetz ,&nbsp;Lucas Kimerer ,&nbsp;Kerri Mendola ,&nbsp;Justin Godinho ,&nbsp;Nicholas Vecchiarello","doi":"10.1016/j.chroma.2026.466715","DOIUrl":"10.1016/j.chroma.2026.466715","url":null,"abstract":"<div><div>As the biopharmaceutical industry continues to advance towards intensified manufacturing and increasingly complex therapeutic pipelines, there is a growing demand for more efficient processes and process development strategies. Flowthrough and frontal loading operations are particularly attractive due to their high loading capacities, low buffer consumption, and operational simplicity. High throughput screening combined with mechanistic modeling provides a powerful framework for rapid development of these processes, but model calibration needed across the multitude of resins and conditions during screening remains resource intensive, and accurately capturing transport and kinetic effects is challenging. In this work, neural network and closed-form symbolic regression models were developed to predict protein loading and product yield, which can exclusively use high throughput plate-based data as inputs. To support training these models, a large database of general rate model (GRM) simulations spanning both high molecular weight (HMW) and low molecular weight (LMW) separations was created. This was accompanied by development of novel analytical expressions for loading and yield derived from fundamental principles under ideal chromatography conditions, enabling transport limitations to be treated as perturbations from the ideal case. The resulting machine learning models trained with these data rely solely on easy-to-measure, experimentally accessible inputs from standard plate-based high throughput experiments and therefore provide accurate predictions without the full input parameter set required by the GRM. Neural networks achieved the highest accuracy, while symbolic regression models performed nearly as well with the added advantages of simplicity, interpretability, and ease of implementation. Further, Monte Carlo analysis demonstrated that predictive errors of the machine learning models were comparable to or smaller than those of mechanistic simulations when typical experimental uncertainty in difficult-to-measure input parameters was considered. Building on this, closed-form expressions for productivity were developed that use the machine learning models as inputs to identify resins and operating conditions that maximize performance as a function of residence time. Finally, a platform workflow is proposed that applies these models to translate high throughput data into practical guidance for resin and condition selection, with predicted purities, yields, and productivities aligning well with experimentally-measured column performances. Overall, this proposed platform provides a foundation for seamlessly integrating high throughput screening and hybrid modeling into process development.</div></div>","PeriodicalId":347,"journal":{"name":"Journal of Chromatography A","volume":"1768 ","pages":"Article 466715"},"PeriodicalIF":4.0,"publicationDate":"2026-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146034304","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Development and validation of an analytical method for determining triflumezopyrim residues in multiple paddy field matrices (Paddy Water, Paddy Soil, Brown Rice, Rice Husk, and Rice Straw) using GC-ECD and GC-MS 用气相色谱- ecd和气相色谱-质谱联用测定多种水田基质(水稻水、水稻土、糙米、稻壳和稻草)中三氟嘧啶残留量的方法的建立和验证
IF 4 2区 化学 Q1 BIOCHEMICAL RESEARCH METHODS Pub Date : 2026-01-16 DOI: 10.1016/j.chroma.2026.466714
Xinhong Deng , Wenxing Wang , Bin Yang , Xuguo Zhou , Lihua Yang
Triflumezopyrim (TFM), a neonicotinoid insecticide for rice planthopper control, poses potential risks to rice safety and paddy ecosystems via residues. Herein, gas chromatography-electron capture detector (GC-ECD) and GC-mass spectrometry (GC-MS, selected ion monitoring: m/z 206.0, 116.0, 131.0) methods were developed and validated for TFM residue analysis in paddy matrices. Samples were extracted with dichloromethane and purified by dispersive solid-phase extraction. For five matrices, calibration curves showed good linearity (0.01–1 mg L−1, R2 ≥ 0.9912). At 0.01, 0.1, 1 mg kg−1 spiking levels, mean recoveries were 81.04%-109.66% (GC-MS) and 89.45%-106.41% (GC-ECD), with relative standard deviations (RSDs) of 3.55%-13.08% and 0.59%-9.30%, respectively. Limits of quantitation (LOQ) were 0.01 mg kg−1 for both techniques; limits of detection (LOD) were 0.001 mg L−1 (GC-ECD) and 0.0005 mg L−1 (GC-MS). These parameters met current residue limits and analytical criteria. Robustness tests revealed minimal impacts of pretreatment and most chromatographic parameters, except carrier gas flow rate (critical, RSD > 10% when varied). The validated method was applied to real paddy field samples from Hunan Province, China, and 20 batches of five types of substrates were screened, with trace TFM in soil (below LOQ). This is the first validated GC-ECD/GC-MS method for TFM trace analysis covering the entire paddy ecosystem (paddy water, paddy soil, brown rice, rice husk, and rice straw), suitable for routine monitoring and supporting TFM environmental/food safety evaluation.
三氟嘧啶(TFM)是一种防治稻飞虱的新烟碱类杀虫剂,其残留对水稻安全和水稻生态系统构成潜在风险。本文建立了气相色谱-电子捕获检测器(GC-ECD)和气相色谱-质谱法(GC-MS,选择离子监测:m/z 206.0, 116.0, 131.0)分析水稻基质中TFM残留的方法,并进行了验证。样品用二氯甲烷萃取,分散固相萃取纯化。5种基质的线性关系良好(0.01 ~ 1 mg L−1,R2≥0.9912)。在0.01、0.1、1 mg kg−1添加水平下,平均加样回收率分别为81.04% ~ 109.66% (GC-MS)和89.45% ~ 106.41% (GC-ECD),相对标准偏差(rsd)分别为3.55% ~ 13.08%和0.59% ~ 9.30%。两种方法的定量限(LOQ)均为0.01 mg kg−1;检出限(LOD)分别为0.001 mg L−1 (GC-ECD)和0.0005 mg L−1 (GC-MS)。这些参数符合当前的残留限值和分析标准。鲁棒性测试显示,除载气流速(临界RSD >; 10%)外,预处理和大多数色谱参数的影响最小。将验证的方法应用于中国湖南省的实际水田样品,筛选了5种基质的20批次,土壤中痕量TFM(低于LOQ)。这是首次验证的覆盖整个水稻生态系统(水稻水、水稻土、糙米、稻壳、秸秆)的TFM痕量分析的GC-ECD/GC-MS方法,适用于TFM的日常监测和支持TFM环境/食品安全评价。
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引用次数: 0
Screening terpene-based eutectic solvents for bisphenol A extraction from plastic-packed dairy products and water storage tanks: COSMO-RS and quantum chemistry calculations 从塑料包装乳制品和储水罐中提取双酚A的萜烯基共晶溶剂的筛选:cosmos - rs和量子化学计算
IF 4 2区 化学 Q1 BIOCHEMICAL RESEARCH METHODS Pub Date : 2026-01-15 DOI: 10.1016/j.chroma.2026.466709
Nazir Fattahi , Parvin Zohrabi , Pouya Karimi , Filipe Hobi Bordón Sosa , Beshare Hashemi , Fereshteh Shiri
Bisphenol A (BPA) is globally used in the plastic and polymer industries. Regarding its toxicity, it raises health and environmental concerns due to its potential leaching into water, soil, and food chains. This work aims to screen the most efficient terpene-based hydrophobic eutectic solvents (HESs) for the extraction of BPA using COSMO-RS, an in-silico predictive approach, thereby minimizing the need for extensive trial-and-error experimentation. We also evaluated the extraction efficiency of HESs by assessing the stability of hydrogen bonding using quantum chemistry calculations. A HES composed of menthol: octanoic acid (2:1) was found to be the most efficient solvent after experimental validations. Experimental design showed the optimal extraction conditions to be 95 µL of menthol: octanoic acid (2:1), 100 µL of KOH 4.5 M, and 100 µL of HCl 5.0 M. A maximum extraction recovery of 75% with a limit of detection of 0.05 µg/L was achieved under the optimal extraction conditions in a pH-switchable extraction process. The environmental impact and applicability of the method were subsequently evaluated using AGREE, AGREEprep, and the blue applicability grade index, scoring 0.61, 0.66, and 65.0, respectively.
双酚A (BPA)在全球塑料和聚合物工业中得到广泛应用。关于其毒性,由于其可能渗入水、土壤和食物链,引起了健康和环境问题。这项工作旨在筛选最有效的萜烯基疏水共晶溶剂(HESs),用于提取BPA,使用cosmos - rs,一种硅预测方法,从而最大限度地减少了广泛的试错实验的需要。我们还通过量子化学计算氢键的稳定性来评估HESs的提取效率。经实验验证,薄荷醇与辛酸(2:1)组成的HES是最有效的溶剂。实验设计表明,最佳提取条件为95µL薄荷醇:辛酸(2:1),100µL KOH (4.5 M), 100µL HCl (5.0 M),在ph可调提取工艺下,最大提取回收率为75%,检出限为0.05µg/L。随后采用AGREE、AGREEprep和蓝色适用性等级指数对该方法的环境影响和适用性进行评价,得分分别为0.61、0.66和65.0。
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引用次数: 0
Alkyl glucamine-based mixed-mode stationary phase for reversed-phase and hydrophilic interaction liquid chromatography 以烷基氨基葡萄糖为基础的混合模式固定相用于反相和亲水相互作用液相色谱
IF 4 2区 化学 Q1 BIOCHEMICAL RESEARCH METHODS Pub Date : 2026-01-15 DOI: 10.1016/j.chroma.2026.466712
Shuo Wang , Yiming Gu , Jin Zhou , Shudong Wang
In modern liquid chromatography, versatile mixed-mode stationary phases have emerged as a practical choice for complex separations. Glucamine is promising in this field due to its distinctive amino-substituted glucose structure. This work presents a novel alkyl glucamine-based stationary phase (SIL–GNOGA) prepared via an epoxide-amine ring-opening reaction and immobilized onto silica surfaces. The morphology and composition of the stationary phase were characterized by multiple analytical techniques. Its retention mechanism was systematically investigated using analytes with diverse properties under varied chromatographic conditions. Furthermore, the separation performance of SIL–GNOGA was assessed and compared against its alkylamine- and glucamine-based counterparts. The stationary phase demonstrated excellent versatility, enabling efficient separation of hydrophilic, hydrophobic, as well as amphiphilic analytes in hydrophilic interaction or reversed-phase mode, depending on their molecular characteristics. Notably, complex mixtures were successfully resolved in both modes through the synergistic effects of hydrophilic, hydrophobic, hydrogen-bonding, and electrostatic interactions. This mixed-mode capability highlights SIL–GNOGA’s broad selectivity and potential across diverse chromatographic applications.
在现代液相色谱中,多功能混合模式固定相已成为复杂分离的实用选择。由于其独特的氨基取代葡萄糖结构,葡萄糖胺在这一领域具有广阔的应用前景。本研究提出了一种新型的烷基氨基葡萄糖固定相(SIL-GNOGA),通过环氧化物-胺开环反应制备并固定在二氧化硅表面。采用多种分析技术对固定相的形貌和组成进行了表征。采用不同性质的分析物,在不同的色谱条件下,系统地研究了其保留机理。此外,对SIL-GNOGA的分离性能进行了评估,并与基于烷基胺和氨基葡萄糖的同类产品进行了比较。固定相表现出优异的通用性,根据其分子特性,可以在亲水性相互作用或反相模式下有效分离亲水性,疏水性以及两亲性分析物。值得注意的是,通过亲水性、疏水性、氢键和静电相互作用的协同作用,在两种模式下都成功地解决了复杂的混合物。这种混合模式能力突出了SIL-GNOGA在不同色谱应用中的广泛选择性和潜力。
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引用次数: 0
Trends of microextraction methods for opioids in complex samples 复杂样品中阿片类药物微提取方法的发展趋势。
IF 4 2区 化学 Q1 BIOCHEMICAL RESEARCH METHODS Pub Date : 2026-01-15 DOI: 10.1016/j.chroma.2026.466713
Mei-di Wang , Yuan Zhang , Ping-yuan Zhang , Yun-yang Zhang , Li Yu , Xue-song Feng , Xiao-dan Liu
The growing global opioid crisis, evidenced by a 90% surge in overdose deaths between 2013 and 2017 and >130 fatalities reported daily in the U.S., underscores the pressing need for advanced detection methods. Opioids, including natural alkaloids (e.g., morphine), semi-synthetic derivatives (e.g., oxycodone), and synthetic analogs (e.g., fentanyl), pose significant public health risks due to their rampant misuse. This review highlights cutting-edge microextraction technologies, specifically liquid-phase microextraction (LPME) and solid-phase microextraction (SPME), which aim to effectively address these limitations. Recent innovations in LPME include surfactant-assisted single-drop microextraction and hollow fiber LPME with amine-functionalized mesoporous foam. These techniques achieve high recovery rates while significantly minimizing solvent use. Furthermore, deep eutectic solvents and ionic liquids (e.g., [C₈MIM][PF₆]) have emerged as environmentally friendly alternatives, enhancing selectivity and enrichment factors. For SPME, advancements such as molecularly imprinted polymers and graphene oxide nanosheets offer exceptional specificity and reusability, with high recoveries. Novel materials, such as electrochemically co-deposited sol-gel/Cu nanocomposite fibers and magnetic materials, further enhance operational efficiency and reduce processing time. These developments enhance analytical precision and adhere to the principles of green chemistry, facilitating scalable and high-throughput detection of opioids in complex matrices. Future research should focus on integrating these technologies with portable analytical platforms for practical applications. Thin-film microextraction devices can be directly coupled with handheld mass spectrometers or miniaturized GC–MS systems. This integration enables rapid, on-site detection of opioids in forensic or clinical settings. Moreover, microextraction sorbents could be incorporated into paper-based lateral flow assay devices, allowing simple, cost-effective, and disposable field testing for opioid residues.
2013年至2017年期间,过量死亡人数激增90%,美国每天报告的死亡人数为100万130人,这证明了日益严重的全球阿片类药物危机,这凸显了对先进检测方法的迫切需求。类阿片,包括天然生物碱(如吗啡)、半合成衍生物(如羟考酮)和合成类似物(如芬太尼),由于滥用泛滥,构成重大公共健康风险。本文综述了旨在有效解决这些局限性的前沿微萃取技术,特别是液相微萃取(LPME)和固相微萃取(SPME)。LPME最近的创新包括表面活性剂辅助单滴微萃取和中空纤维LPME与胺功能化介孔泡沫。这些技术实现了高回收率,同时显著减少了溶剂的使用。此外,深共晶溶剂和离子液体(如[C₈MIM][PF₆])已成为环境友好的替代品,提高了选择性和富集系数。对于SPME,分子印迹聚合物和氧化石墨烯纳米片等技术的进步提供了卓越的特异性和可重用性,具有高回收率。新型材料,如电化学共沉积溶胶-凝胶/Cu纳米复合纤维和磁性材料,进一步提高了操作效率,缩短了加工时间。这些发展提高了分析精度,坚持绿色化学原则,促进了复杂矩阵中阿片类药物的可扩展和高通量检测。未来的研究应侧重于将这些技术与便携式分析平台相结合,以实现实际应用。薄膜微萃取装置可以直接与手持式质谱仪或小型化的GC-MS系统耦合。这种整合能够在法医或临床环境中快速、现场检测阿片类药物。此外,微萃取吸附剂可以结合到基于纸张的横向流动检测装置中,允许对阿片类药物残留进行简单,具有成本效益和一次性的现场测试。
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引用次数: 0
Sustainable downstream processing of ganoderma lucidum triterpenoids: Integrated chromatographic strategies and techno-economic evaluation 灵芝三萜的可持续下游加工:综合色谱策略和技术经济评价
IF 4 2区 化学 Q1 BIOCHEMICAL RESEARCH METHODS Pub Date : 2026-01-14 DOI: 10.1016/j.chroma.2026.466710
Hui Wang , Nengqi Zhang , Houle Xiang , Jingwei Kou , Yuqing Zhang , Hanjie Ying , Pengpeng Yang , Hao Qiao , Jinglan Wu
Ganoderma lucidum triterpenoids (GLTs) are high-value bioactive metabolites with increasing demand in pharmaceutical and nutraceutical sectors. However, their structural diversity, characterized by numerous analogs and structural isomers, coupled with the complexity of sources such as spores, fruiting bodies, and mycelia, presents significant challenges for high-resolution separation and high-purity isolation. This review critically evaluates the evolution of chromatographic and preparative isolation technologies tailored for GLTs. We systematically analyze three integrated separation workflows, designated as Route I, II, and III, from a chromatographic perspective, focusing on how different stationary phase behaviors and mobile phase configurations address specific sample complexities. Key emerging technologies, including high-speed counter-current chromatography (HSCCC), and preparative supercritical fluid chromatography (Prep-SFC), are assessed for their efficacy in resolving isomeric pairs and reducing irreversible adsorption. Furthermore, a technical-economic and environmental evaluation using the environmental factor (E-factor) is provided to link separation efficiency with industrial purity requirements ranging from 30 % to 90 %. By comparing the resolution, throughput, and sustainability of these chromatographic modes, this review provides a strategic roadmap for selecting optimal purification platforms to ensure the quality standardization of Ganoderma lucidum products.
灵芝三萜(GLTs)是一种高价值的生物活性代谢物,在制药和营养保健领域的需求日益增加。然而,它们的结构多样性,具有众多的类似物和结构异构体的特征,加上孢子、子实体和菌丝等来源的复杂性,为高分辨率分离和高纯度分离提出了重大挑战。这篇综述批判性地评价了针对glt的色谱和制备分离技术的发展。我们从色谱的角度系统地分析了三种集成的分离工作流程,即路线I、路线II和路线III,重点关注不同的固定相行为和流动相配置如何解决特定的样品复杂性。对高速逆流色谱法(HSCCC)和制备超临界流体色谱法(Prep-SFC)等新兴关键技术在分辨异构体对和减少不可逆吸附方面的效果进行了评估。此外,利用环境因子(e因子)进行技术经济和环境评价,将分离效率与30%至90%的工业纯度要求联系起来。通过比较这些色谱模式的分辨率、通量和可持续性,本文为选择最佳纯化平台以确保灵芝产品的质量标准化提供了战略路线图。
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Journal of Chromatography A
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