Pub Date : 2025-02-09DOI: 10.1016/j.chroma.2025.465760
Ana Ballester-Caudet, Simón Mariño Perea, Diego García-Gómez, José Luis Pérez Pavón, Encarnación Rodríguez-Gonzalo
Therapeutic drug monitoring of paracetamol (acetaminophen, N-acetyl-p-aminophenol, APAP) metabolites in plasma and serum samples was conducted using two-dimensional liquid chromatography (2D-LC) by means of online heart-cutting passive modulation. The selective and efficient 2D-LC approach here developed was applied for the simultaneous determination of six paracetamol metabolites: its major metabolite, the glucuronide conjugate (APAP-GLUC), and its main transformation product p-aminophenol (PAP), along with the bioactive N-arachidonoylphenolamine (AM404), the reactive hepatotoxic N-Acetyl-p-benzoquinone imine (NAPQI), in addition to glutathione (APAP-GLUT) and protein-derived cysteine (APAP-CYS) conjugates. Online heart-cutting mode allowed the combination of C18 reversed-phase column in the first dimension and a Primesep SB analytical column (C18-anion exchange) in the second dimension promoting the effective separation of such different paracetamol metabolites, ranging from highly polar to extremely hydrophobic. The results suggest the promising potential of the proposed 2D-LC methodology for therapeutic drug analysis and pharmacokinetic studies.
{"title":"Pharmacokinetic profile of metabolites by heart-cutting two-dimensional liquid chromatography: A focus on paracetamol analysis","authors":"Ana Ballester-Caudet, Simón Mariño Perea, Diego García-Gómez, José Luis Pérez Pavón, Encarnación Rodríguez-Gonzalo","doi":"10.1016/j.chroma.2025.465760","DOIUrl":"10.1016/j.chroma.2025.465760","url":null,"abstract":"<div><div>Therapeutic drug monitoring of paracetamol (acetaminophen, <em>N</em>-acetyl-<em>p</em>-aminophenol, APAP) metabolites in plasma and serum samples was conducted using two-dimensional liquid chromatography (2D-LC) by means of online heart-cutting passive modulation. The selective and efficient 2D-LC approach here developed was applied for the simultaneous determination of six paracetamol metabolites: its major metabolite, the glucuronide conjugate (APAP-GLUC), and its main transformation product <em>p</em>-aminophenol (PAP), along with the bioactive <em>N</em>-arachidonoylphenolamine (AM404), the reactive hepatotoxic <em>N</em>-Acetyl-<em>p</em>-benzoquinone imine (NAPQI), in addition to glutathione (APAP-GLUT) and protein-derived cysteine (APAP-CYS) conjugates. Online heart-cutting mode allowed the combination of C18 reversed-phase column in the first dimension and a Primesep SB analytical column (C18-anion exchange) in the second dimension promoting the effective separation of such different paracetamol metabolites, ranging from highly polar to extremely hydrophobic. The results suggest the promising potential of the proposed 2D-LC methodology for therapeutic drug analysis and pharmacokinetic studies.</div></div>","PeriodicalId":347,"journal":{"name":"Journal of Chromatography A","volume":"1745 ","pages":"Article 465760"},"PeriodicalIF":3.8,"publicationDate":"2025-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143395658","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}
Pub Date : 2025-02-08DOI: 10.1016/j.chroma.2025.465723
Eric Denbaum , Mario A. Gutierrez Diaz , Scott H. Altern , Chris Belisle , Mark A. Snyder , Steven M. Cramer
This paper employs a previously developed high-throughput parallel batch adsorption screen with sequential salt step increases to rapidly investigate a set of prototype multimodal anion- (MMA) and cation-exchange (MMC) resins. Experiments were carried out using a model protein library with varying charge and hydrophobic characteristics at several pH conditions. Partition coefficients were calculated from the batch chromatograms and fed into a column (linear salt gradient) simulator to determine peak first moments (elution salt concentration). These results enabled the calculation of one-resin separability scores, quantifying each resin's ability, at a given pH, to separate all proteins in the library. Additionally, a clustering analysis grouped resins with similar chromatographic behavior, revealing correlations between resin chemistry (e.g., functional groups and geometric presentation) and protein elution patterns. Finally, the first moment data sets were used to calculate two-resin separability scores, the ability of two resins to synergistically separate the entire set of proteins from each other. These results indicated that MMC resins containing phthalimide-based moieties in concert with guanidine-containing MMA resins were particularly useful when used in concert. Overall, the presented approach is shown to be an enabling technology for rapidly screening large numbers of ligands and operating conditions for discovery of next-generation chromatographic resins.
{"title":"Evaluation of prototype multimodal resins using chromatographic separability","authors":"Eric Denbaum , Mario A. Gutierrez Diaz , Scott H. Altern , Chris Belisle , Mark A. Snyder , Steven M. Cramer","doi":"10.1016/j.chroma.2025.465723","DOIUrl":"10.1016/j.chroma.2025.465723","url":null,"abstract":"<div><div>This paper employs a previously developed high-throughput parallel batch adsorption screen with sequential salt step increases to rapidly investigate a set of prototype multimodal anion- (MMA) and cation-exchange (MMC) resins. Experiments were carried out using a model protein library with varying charge and hydrophobic characteristics at several pH conditions. Partition coefficients were calculated from the batch chromatograms and fed into a column (linear salt gradient) simulator to determine peak first moments (elution salt concentration). These results enabled the calculation of one-resin separability scores, quantifying each resin's ability, at a given pH, to separate all proteins in the library. Additionally, a clustering analysis grouped resins with similar chromatographic behavior, revealing correlations between resin chemistry (e.g., functional groups and geometric presentation) and protein elution patterns. Finally, the first moment data sets were used to calculate two-resin separability scores, the ability of two resins to synergistically separate the entire set of proteins from each other. These results indicated that MMC resins containing phthalimide-based moieties in concert with guanidine-containing MMA resins were particularly useful when used in concert. Overall, the presented approach is shown to be an enabling technology for rapidly screening large numbers of ligands and operating conditions for discovery of next-generation chromatographic resins.</div></div>","PeriodicalId":347,"journal":{"name":"Journal of Chromatography A","volume":"1745 ","pages":"Article 465723"},"PeriodicalIF":3.8,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143420540","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}
Pub Date : 2025-02-08DOI: 10.1016/j.chroma.2025.465759
Xu Zhang , Xiangbo Ji , Zifang Peng , Yanhao Zhang , Zongwei Cai , Shusheng Zhang
Due to the complicated sample matrix and low concentration, analysis of small-molecule emerging environmental pollutants generally required complex sample preparation and long instrumental detection. It guarantees the sensitivity but is not conducive to rapid screening. In this work, a p-aminoazobenzene (p-AAB) with excellent energy absorption capability was used to modify multilayer Ti3C2TX (MXene) to prepare novel material p-AAB/MXene. The modification significantly improved the laser absorption of original material, and made p-AAB/MXene could be employed as matrix for surface-assisted laser desorption/ionization-time of flight-mass spectrometry (SALDI-TOF MS) analysis of small-molecule emerging pollutants. More importantly, p-AAB/MXene could be used as adsorbent to enrich target compounds, then directly sent to SALDI-TOF MS detection without any other sample pre-treatment. Dual characteristics of enrichment material and matrix made p-AAB/MXene-based SALDI-TOF MS method successfully be applied to rapid and accurate detection of emerging environmental pollutants, p-phenylenediamine-quinones (PPDQs) and diamide insecticides (DAIs), in food (beverage) and environmental (PM2.5) samples. High sensitivity (LOD at ng mL-1 level) and satisfactory precision (RSD < 11%) indicated the qualified analytical performance of developed approach. The determined concentrations also elucidated the broad occurrence of PPDQs and DAIs in beverages and PM2.5. The results further confirmed the SALDI-TOF MS using p-AAB/MXene as both adsorbent and matrix had considerable potential for efficient and time-saving analysis of trace and ultra-trace small-molecule emerging environmental organic pollutants in complicated samples.
{"title":"p-AAB/MXene as a novel adsorbent and SALDI matrix for highly efficient enrichment and rapid MS detection of emerging environmental organic pollutants in beverages and PM2.5","authors":"Xu Zhang , Xiangbo Ji , Zifang Peng , Yanhao Zhang , Zongwei Cai , Shusheng Zhang","doi":"10.1016/j.chroma.2025.465759","DOIUrl":"10.1016/j.chroma.2025.465759","url":null,"abstract":"<div><div>Due to the complicated sample matrix and low concentration, analysis of small-molecule emerging environmental pollutants generally required complex sample preparation and long instrumental detection. It guarantees the sensitivity but is not conducive to rapid screening. In this work, a <em>p</em>-aminoazobenzene (<em>p</em>-AAB) with excellent energy absorption capability was used to modify multilayer Ti<sub>3</sub>C<sub>2</sub>T<sub>X</sub> (MXene) to prepare novel material <em>p</em>-AAB/MXene. The modification significantly improved the laser absorption of original material, and made <em>p</em>-AAB/MXene could be employed as matrix for surface-assisted laser desorption/ionization-time of flight-mass spectrometry (SALDI-TOF MS) analysis of small-molecule emerging pollutants. More importantly, <em>p</em>-AAB/MXene could be used as adsorbent to enrich target compounds, then directly sent to SALDI-TOF MS detection without any other sample pre-treatment. Dual characteristics of enrichment material and matrix made <em>p</em>-AAB/MXene-based SALDI-TOF MS method successfully be applied to rapid and accurate detection of emerging environmental pollutants, <em>p</em>-phenylenediamine-quinones (PPDQs) and diamide insecticides (DAIs), in food (beverage) and environmental (PM<sub>2.5</sub>) samples. High sensitivity (LOD at ng mL<sup>-1</sup> level) and satisfactory precision (RSD < 11%) indicated the qualified analytical performance of developed approach. The determined concentrations also elucidated the broad occurrence of PPDQs and DAIs in beverages and PM<sub>2.5</sub>. The results further confirmed the SALDI-TOF MS using <em>p</em>-AAB/MXene as both adsorbent and matrix had considerable potential for efficient and time-saving analysis of trace and ultra-trace small-molecule emerging environmental organic pollutants in complicated samples.</div></div>","PeriodicalId":347,"journal":{"name":"Journal of Chromatography A","volume":"1745 ","pages":"Article 465759"},"PeriodicalIF":3.8,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143395730","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}
Pub Date : 2025-02-05DOI: 10.1016/j.chroma.2025.465755
Felipe Coelho Vieira , Willian Kopp , Felipe Fernando Furlan , Thiago Faggion de Pádua , Marcelo Perencin de Arruda Ribeiro
The use of phenomenological models in preparative chromatography is often limited by the difficulty in accessing accurate model parameters. Although screening protocols are commonly used to select materials, the resulting data are not consistently used to estimate model parameters. A joint estimation procedure that integrates data from microplate screening with a single column experiment was proposed to estimate equilibrium and dispersion parameters for modeling gradient elution. Initial estimates of equilibrium isotherm parameters were derived from the screening data, which were then refined by incorporating column chromatogram data to estimate mass transport parameters and enhance isotherm predictions. The proposed method was validated using reverse-phase chromatography with a non-ionic surfactant and functionalized silica. The equilibrium parameters estimated with microplate data predicted a retention volume 8.9 % away from the experimental results, while the joint estimation prediction was 0.8 % in the best-case scenario. In this case, results show that the use of screening data combined with the l-curve method can effectively mitigate model overfitting, even when relying on a single gradient elution column assay. This approach has the potential to accelerate process development and reduce resource consumption.
{"title":"Microplate approach to resin screening and parameter estimation applied to chromatography column modeling of gradient elution operation","authors":"Felipe Coelho Vieira , Willian Kopp , Felipe Fernando Furlan , Thiago Faggion de Pádua , Marcelo Perencin de Arruda Ribeiro","doi":"10.1016/j.chroma.2025.465755","DOIUrl":"10.1016/j.chroma.2025.465755","url":null,"abstract":"<div><div>The use of phenomenological models in preparative chromatography is often limited by the difficulty in accessing accurate model parameters. Although screening protocols are commonly used to select materials, the resulting data are not consistently used to estimate model parameters. A joint estimation procedure that integrates data from microplate screening with a single column experiment was proposed to estimate equilibrium and dispersion parameters for modeling gradient elution. Initial estimates of equilibrium isotherm parameters were derived from the screening data, which were then refined by incorporating column chromatogram data to estimate mass transport parameters and enhance isotherm predictions. The proposed method was validated using reverse-phase chromatography with a non-ionic surfactant and functionalized silica. The equilibrium parameters estimated with microplate data predicted a retention volume 8.9 % away from the experimental results, while the joint estimation prediction was 0.8 % in the best-case scenario. In this case, results show that the use of screening data combined with the l-curve method can effectively mitigate model overfitting, even when relying on a single gradient elution column assay. This approach has the potential to accelerate process development and reduce resource consumption.</div></div>","PeriodicalId":347,"journal":{"name":"Journal of Chromatography A","volume":"1746 ","pages":"Article 465755"},"PeriodicalIF":3.8,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143427812","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}
Dicyclopentadiene (DCPD) is a versatile compound used in various applications, including resins, polymers, and high-energy-density (HED) fuels, such as exo-tetrahydrodicyclopentadiene (exo-THDCPD). DCPD reaction mixtures are typically analyzed using gas chromatography (GC), but this process can be challenging due to its thermal instability. At temperatures above 150 °C, it can undergo a reverse Diels-Alder reaction (RDAR), decomposing into cyclopentadiene (CPD). This decomposition can lead to significant errors in quantitative measurements, including conversion and yield. To address this issue, we conducted GC analyses at temperatures exceeding the RDAR threshold to investigate DCPD dissociation under various conditions, including GC inlet temperatures, gas flow rates, and solvents. Our study reveals that at inlet temperatures above 200 °C, accurately determining DCPD conversion is extremely difficult. Additionally, we report that the flow rate of the carrier gas has a negligible impact on the DCPD dissociation, while the choice of solvent significantly affects the detection of the CPD formed. Among the three solvents examined, dichloromethane (DCM) was found to be the most effective for detecting dissociated CPD.
{"title":"Optimizing gas chromatography parameters for thermally unstable dicyclopentadiene mixtures analysis","authors":"Azeem Khan , Mahak Dhiman , Ankit Mishra , Anil Kumar Sinha","doi":"10.1016/j.chroma.2025.465754","DOIUrl":"10.1016/j.chroma.2025.465754","url":null,"abstract":"<div><div>Dicyclopentadiene (DCPD) is a versatile compound used in various applications, including resins, polymers, and high-energy-density (HED) fuels, such as exo-tetrahydrodicyclopentadiene (exo-THDCPD). DCPD reaction mixtures are typically analyzed using gas chromatography (GC), but this process can be challenging due to its thermal instability. At temperatures above 150 °C, it can undergo a reverse Diels-Alder reaction (RDAR), decomposing into cyclopentadiene (CPD). This decomposition can lead to significant errors in quantitative measurements, including conversion and yield. To address this issue, we conducted GC analyses at temperatures exceeding the RDAR threshold to investigate DCPD dissociation under various conditions, including GC inlet temperatures, gas flow rates, and solvents. Our study reveals that at inlet temperatures above 200 °C, accurately determining DCPD conversion is extremely difficult. Additionally, we report that the flow rate of the carrier gas has a negligible impact on the DCPD dissociation, while the choice of solvent significantly affects the detection of the CPD formed. Among the three solvents examined, dichloromethane (DCM) was found to be the most effective for detecting dissociated CPD.</div></div>","PeriodicalId":347,"journal":{"name":"Journal of Chromatography A","volume":"1745 ","pages":"Article 465754"},"PeriodicalIF":3.8,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143378862","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}
Pub Date : 2025-02-04DOI: 10.1016/j.chroma.2025.465752
Theodosia Vallianatou , Fotios Tsopelas , Anna Tsantili-Kakoulidou
Retention of molecules on immobilized artificial membrane (IAM) chromatography is a key physicochemical property for predictive models of permeability across biological barriers, with applications in drug design and ecotoxicology. Currently, IAM retention is solely experimentally determined, which limits its utility for screening virtual compound libraries or for predictions of yet not synthesized molecules. The present study focuses on developing predictive models of IAM retention factors (logkw(IAM)) for a structurally diverse set of drug compounds, scrutinizing the role of lipophilicity, experimental and calculated, as well as the contribution of additional molecular parameters, selected from a pool of physicochemical, constitutional, topological and 3D descriptors. After obtaining a data overview by principal component analysis, both multiple linear regression (MLR) and partial least squares (PLS) analyses were used to construct lipophilicity-based models and lipophilicity-independent models. Bulk, polarity and fraction of anionic species were common descriptors in all models. It was demonstrated that calculated lipophilicity values introduced additional uncertainty, depending on the software used. On the other hand, lipophilicity-independent MLR and PLS models, which relied solely on computational descriptors, showed comparable performance with lipophilicity-based models, while offering the advantage to more useful for screening large libraries in early drug discovery. The reliability of lipophilicity-independent MLR and PLS models was assessed by external validation as well as by using a blind test set. Error distribution between lipophilicity-based and lipophilicity-independent models was also investigated and found to be comparable, while it was better than the differences between experimental and calculated lipophilicity values.
{"title":"Predicting retention on immobilized artificial membrane chromatography: Lipophilicity-based versus lipophilicity-independent models","authors":"Theodosia Vallianatou , Fotios Tsopelas , Anna Tsantili-Kakoulidou","doi":"10.1016/j.chroma.2025.465752","DOIUrl":"10.1016/j.chroma.2025.465752","url":null,"abstract":"<div><div>Retention of molecules on immobilized artificial membrane (IAM) chromatography is a key physicochemical property for predictive models of permeability across biological barriers, with applications in drug design and ecotoxicology. Currently, IAM retention is solely experimentally determined, which limits its utility for screening virtual compound libraries or for predictions of yet not synthesized molecules. The present study focuses on developing predictive models of IAM retention factors (logk<sub>w(IAM)</sub>) for a structurally diverse set of drug compounds, scrutinizing the role of lipophilicity, experimental and calculated, as well as the contribution of additional molecular parameters, selected from a pool of physicochemical, constitutional, topological and 3D descriptors. After obtaining a data overview by principal component analysis, both multiple linear regression (MLR) and partial least squares (PLS) analyses were used to construct lipophilicity-based models and lipophilicity-independent models. Bulk, polarity and fraction of anionic species were common descriptors in all models. It was demonstrated that calculated lipophilicity values introduced additional uncertainty, depending on the software used. On the other hand, lipophilicity-independent MLR and PLS models, which relied solely on computational descriptors, showed comparable performance with lipophilicity-based models, while offering the advantage to more useful for screening large libraries in early drug discovery. The reliability of lipophilicity-independent MLR and PLS models was assessed by external validation as well as by using a blind test set. Error distribution between lipophilicity-based and lipophilicity-independent models was also investigated and found to be comparable, while it was better than the differences between experimental and calculated lipophilicity values.</div></div>","PeriodicalId":347,"journal":{"name":"Journal of Chromatography A","volume":"1745 ","pages":"Article 465752"},"PeriodicalIF":3.8,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143420592","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-03DOI: 10.1016/j.chroma.2025.465751
Dejene Kifle
Heavy rare earth elements (HREEs) are used in strategically important niche applications such as laser crystals, optical amplifiers, and high-tech alloys, thus regarded as essential resources that play an irreplaceable role in advanced technology and national defense. However, the huge demand and the lack of efficient separation technologies cause severe concerns about their supply. The environmental impact of their production is also a significant concern. Current industrial HREE separation is dominated by solvent extraction, which is technically inefficient and environmentally hostile. This work presents a continuous extraction chromatography method for separating HREEs as an efficient and greener alternative to solvent extraction. The proposed method uses ligand-coated C18-silica as a stationary phase and mineral acid as eluent, eliminating toxic and highly flammable organic solvents required for solvent extraction with significant environmental and safety advantages. Moreover, the method can be optimized easily to target the specific HREEs of value within the mix, namely Terbium, Dysprosium, Holmium, and Yttrium, which account for all the basket's value. This avoids the requirement to separate a full spectrum of REEs and simplifies the overall separation process. The technical feasibility of the method has been verified on a bench-scale pilot using mining-originated HREE concentrate and recycled neodymium magnet leachate with a purity of ≥ 99.9 % of individual REEs. The method showed high stability and consistent separation efficiency. In summary, the proposed extraction chromatography method has proven to be a promising green technology; hence, it might contribute to more efficient and sustainable HREE separation processes.
{"title":"Efficient extraction chromatography method for the separation of heavy rare earth elements from various sources","authors":"Dejene Kifle","doi":"10.1016/j.chroma.2025.465751","DOIUrl":"10.1016/j.chroma.2025.465751","url":null,"abstract":"<div><div>Heavy rare earth elements (HREEs) are used in strategically important niche applications such as laser crystals, optical amplifiers, and high-tech alloys, thus regarded as essential resources that play an irreplaceable role in advanced technology and national defense. However, the huge demand and the lack of efficient separation technologies cause severe concerns about their supply. The environmental impact of their production is also a significant concern. Current industrial HREE separation is dominated by solvent extraction, which is technically inefficient and environmentally hostile. This work presents a continuous extraction chromatography method for separating HREEs as an efficient and greener alternative to solvent extraction. The proposed method uses ligand-coated C18-silica as a stationary phase and mineral acid as eluent, eliminating toxic and highly flammable organic solvents required for solvent extraction with significant environmental and safety advantages. Moreover, the method can be optimized easily to target the specific HREEs of value within the mix, namely Terbium, Dysprosium, Holmium, and Yttrium, which account for all the basket's value. This avoids the requirement to separate a full spectrum of REEs and simplifies the overall separation process. The technical feasibility of the method has been verified on a bench-scale pilot using mining-originated HREE concentrate and recycled neodymium magnet leachate with a purity of ≥ 99.9 % of individual REEs. The method showed high stability and consistent separation efficiency. In summary, the proposed extraction chromatography method has proven to be a promising green technology; hence, it might contribute to more efficient and sustainable HREE separation processes.</div></div>","PeriodicalId":347,"journal":{"name":"Journal of Chromatography A","volume":"1745 ","pages":"Article 465751"},"PeriodicalIF":3.8,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143350452","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}
Pub Date : 2025-02-03DOI: 10.1016/j.chroma.2025.465750
Joan Noguerol Arias, August Bonmatí, Francesc X. Prenafeta-Boldú, Míriam Cerrillo
This study reports the development of a novel analytical method for the determination of carbon dioxide (CO2) along with the other main greenhouse gases (GHG)‒methane (CH4) and nitrous oxide (N2O)‒ from environmental samples by gas chromatography (GC) using an electron capture detector (ECD). This new method was compared and validated with the standard GC method for the determination of CO2 using a thermal conductivity detector (TCD). The main performance parameters considered for the validation of an analytical method were evaluated: selectivity/specificity, linearity/working range, precision, trueness, limit of detection (LOD) and limit of quantitation (LOQ). This comparison was carried out using gas standards, reference materials and environmental samples containing GHG. Both the ECD- and TCD-based chromatographic analytical methods displayed a similar precision (3.1–3.4 %) and accuracy (101–106 %) for CO2 analysis. Although the LOQ for the ECD detector is higher than that of the TCD detector (300 vs. 99 µmol mol⁻¹), it is still sufficient for the analysis of most GHG samples. Once validated, the new analytical method was used for the simultaneous determination of CO2, CH4 and N2O in gaseous samples obtained from a wide range of conditions and agricultural environments. To this end, a GC instrument was equipped with a flame ionization detector (FID) for the determination of CH4 and an ECD for CO2 and N2O, connected in series by a system of valves. In this way, it was possible to accurately measure the main GHG present in the atmosphere and in gaseous samples, simplifying the required laboratory equipment and reducing the associated labor and costs.
{"title":"Determination of carbon dioxide by gas chromatography using an electron capture detector for the analysis of greenhouse gases: A comparison and validation with the standard method","authors":"Joan Noguerol Arias, August Bonmatí, Francesc X. Prenafeta-Boldú, Míriam Cerrillo","doi":"10.1016/j.chroma.2025.465750","DOIUrl":"10.1016/j.chroma.2025.465750","url":null,"abstract":"<div><div>This study reports the development of a novel analytical method for the determination of carbon dioxide (CO<sub>2</sub>) along with the other main greenhouse gases (GHG)‒methane (CH<sub>4</sub>) and nitrous oxide (N<sub>2</sub>O)‒ from environmental samples by gas chromatography (GC) using an electron capture detector (ECD). This new method was compared and validated with the standard GC method for the determination of CO<sub>2</sub> using a thermal conductivity detector (TCD). The main performance parameters considered for the validation of an analytical method were evaluated: selectivity/specificity, linearity/working range, precision, trueness, limit of detection (LOD) and limit of quantitation (LOQ). This comparison was carried out using gas standards, reference materials and environmental samples containing GHG. Both the ECD- and TCD-based chromatographic analytical methods displayed a similar precision (3.1–3.4 %) and accuracy (101–106 %) for CO<sub>2</sub> analysis. Although the LOQ for the ECD detector is higher than that of the TCD detector (300 vs. 99 µmol mol⁻¹), it is still sufficient for the analysis of most GHG samples. Once validated, the new analytical method was used for the simultaneous determination of CO<sub>2</sub>, CH<sub>4</sub> and N<sub>2</sub>O in gaseous samples obtained from a wide range of conditions and agricultural environments. To this end, a GC instrument was equipped with a flame ionization detector (FID) for the determination of CH<sub>4</sub> and an ECD for CO<sub>2</sub> and N<sub>2</sub>O, connected in series by a system of valves. In this way, it was possible to accurately measure the main GHG present in the atmosphere and in gaseous samples, simplifying the required laboratory equipment and reducing the associated labor and costs.</div></div>","PeriodicalId":347,"journal":{"name":"Journal of Chromatography A","volume":"1745 ","pages":"Article 465750"},"PeriodicalIF":3.8,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143343086","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}
Pub Date : 2025-02-01DOI: 10.1016/j.chroma.2025.465747
Yu-shi Huang , Ya-ling An , Yue-yuan Zheng , Wen-jie Zhao , Chun-qian Song , Li-jie Zhang , Jie-ting Chen , Zi-jun Tang , Lin Feng , Zhen-wei Li , Xiao-kang Liu , Dai-di Zhang , De-an Guo
Citrus-derived raw medicinal materials are frequently used for health care, flavoring, and therapeutic purposes. However, Due to similarities in origin or appearance, citrus herbs are often misused in the market, necessitating effective differentiation methods. For the first time, this study constructed automated discrimination models for 16 citrus species (239 batches) while previous studies focused on a limited number of species. Seven machine learning models —Tree, Discriminant, Support Vector Machine, K-Nearest Neighbor, Ensemble, Neural Network, and Partial least squares discriminant analysis—were compared, with the Ensemble model achieving 100% accuracy in the test set. 16 Orthogonal partial least squares discriminant analysis models were constructed to screen and identify 53 differential markers. These markers were successfully utilized to determine the absence or presence of specified components in the 20 citrus products. This study provides a comprehensive solution for the quality control of citrus herbs, enabling the differentiation of raw herbs and processed slices, as well as the identification of complex systems such as Chinese patent medicines.
{"title":"A holistic strategy for the in-depth discrimination and authentication of 16 citrus herbs and associated commercial products based on machine learning techniques and non-targeted metabolomics","authors":"Yu-shi Huang , Ya-ling An , Yue-yuan Zheng , Wen-jie Zhao , Chun-qian Song , Li-jie Zhang , Jie-ting Chen , Zi-jun Tang , Lin Feng , Zhen-wei Li , Xiao-kang Liu , Dai-di Zhang , De-an Guo","doi":"10.1016/j.chroma.2025.465747","DOIUrl":"10.1016/j.chroma.2025.465747","url":null,"abstract":"<div><div>Citrus-derived raw medicinal materials are frequently used for health care, flavoring, and therapeutic purposes. However, Due to similarities in origin or appearance, citrus herbs are often misused in the market, necessitating effective differentiation methods. For the first time, this study constructed automated discrimination models for 16 citrus species (239 batches) while previous studies focused on a limited number of species. Seven machine learning models —Tree, Discriminant, Support Vector Machine, K-Nearest Neighbor, Ensemble, Neural Network, and Partial least squares discriminant analysis—were compared, with the Ensemble model achieving 100% accuracy in the test set. 16 Orthogonal partial least squares discriminant analysis models were constructed to screen and identify 53 differential markers. These markers were successfully utilized to determine the absence or presence of specified components in the 20 citrus products. This study provides a comprehensive solution for the quality control of citrus herbs, enabling the differentiation of raw herbs and processed slices, as well as the identification of complex systems such as Chinese patent medicines.</div></div>","PeriodicalId":347,"journal":{"name":"Journal of Chromatography A","volume":"1745 ","pages":"Article 465747"},"PeriodicalIF":3.8,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143173273","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}
Pub Date : 2025-02-01DOI: 10.1016/j.chroma.2025.465746
Jörgen Samuelsson , Martin Enmark , Gergely Szabados , Manal Rahal , Bestoun S. Ahmed , Jakob Häggström , Patrik Forssén , Torgny Fornstedt
This study presents an improved workflow to support the development of machine learning models to predict oligonucleotide retention times, peak widths and thus peak resolutions, from larger datasets where manual processing is not feasible. We explored diverse oligonucleotide forms, ranging from native to fully phosphorothioated, using three different gradient slopes. Both native and phosphorothioated oligonucleotides were separated, using a chromatographic C18 system with tributylaminium ion as the ion–pair reagent in the eluent, resulting in retention time data for approximately 900 sequences per gradient.
For managing the large and extensive datasets, we developed a semi-automatic rule-based approach for retention time determination, peak decomposition, peak width assessment, signal-to-noise ratio, and skewness analysis. Probability density functions (PDFs) were fitted to elution profiles, with PDF selection based on an F-test. Co-eluting peaks were addressed using a multiple Gaussian PDF.
The encoded sequence data underwent modeling using support vector regression (SVR), gradient boosting (GB), random forest (RF), and decision tree (DT) models. GB and SVR showed promise for retention predictions, while RT and DT were faster but demonstrated limited generalization capabilities.
The machine learning models exhibited larger errors for the shallowest gradient and lower predictability for P=O sequences, potentially due to signal intensity and sequence heterogeneity. Improvements in signal-to-noise ratios were considered, including mass spectrometry in selected ion monitoring mode. The best model for this data sets were GB, closely followed by the SVR model.
With established models for retention and peak width, chromatograms can now be predicted for various gradient slopes, offering prediction of impurity peak resolution for arbitrary sequences and gradient slopes.
{"title":"Improved workflow for constructing machine learning models: Predicting retention times and peak widths in oligonucleotide separation","authors":"Jörgen Samuelsson , Martin Enmark , Gergely Szabados , Manal Rahal , Bestoun S. Ahmed , Jakob Häggström , Patrik Forssén , Torgny Fornstedt","doi":"10.1016/j.chroma.2025.465746","DOIUrl":"10.1016/j.chroma.2025.465746","url":null,"abstract":"<div><div>This study presents an improved workflow to support the development of machine learning models to predict oligonucleotide retention times, peak widths and thus peak resolutions, from larger datasets where manual processing is not feasible. We explored diverse oligonucleotide forms, ranging from native to fully phosphorothioated, using three different gradient slopes. Both native and phosphorothioated oligonucleotides were separated, using a chromatographic C18 system with tributylaminium ion as the ion–pair reagent in the eluent, resulting in retention time data for approximately 900 sequences per gradient.</div><div>For managing the large and extensive datasets, we developed a semi-automatic rule-based approach for retention time determination, peak decomposition, peak width assessment, signal-to-noise ratio, and skewness analysis. Probability density functions (PDFs) were fitted to elution profiles, with PDF selection based on an <em>F</em>-test. Co-eluting peaks were addressed using a multiple Gaussian PDF.</div><div>The encoded sequence data underwent modeling using support vector regression (SVR), gradient boosting (GB), random forest (RF), and decision tree (DT) models. GB and SVR showed promise for retention predictions, while RT and DT were faster but demonstrated limited generalization capabilities.</div><div>The machine learning models exhibited larger errors for the shallowest gradient and lower predictability for P=O sequences, potentially due to signal intensity and sequence heterogeneity. Improvements in signal-to-noise ratios were considered, including mass spectrometry in selected ion monitoring mode. The best model for this data sets were GB, closely followed by the SVR model.</div><div>With established models for retention and peak width, chromatograms can now be predicted for various gradient slopes, offering prediction of impurity peak resolution for arbitrary sequences and gradient slopes.</div></div>","PeriodicalId":347,"journal":{"name":"Journal of Chromatography A","volume":"1747 ","pages":"Article 465746"},"PeriodicalIF":3.8,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143510650","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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