Pub Date : 2026-03-08Epub Date: 2025-12-29DOI: 10.1016/j.aca.2025.345044
Lorenzo Sanjuan-Navarro, Juan Luís Benedé, Soledad Rubio, Carlos Moreno, Verónica Pino, Francisco Javier Pena-Pereira, Yolanda Moliner-Martínez
Background: The use of current metric tools for sample preparation has proven highly valuable in identifying the strengths and weaknesses of various analytical approaches. However, as Analytical Sciences increasingly move towards sustainability, it becomes evident that existing metrics may not fully cover all the dimensions required for a comprehensive assessment.
Results: An overview to encourage the evolution towards more advanced metric tools for sample preparation by reflecting on which parameters should be evaluated and on the principles that ought to guide their design. The tutorial highlights the need for new or improved metrics capable and identify the most relevant criteria and how they can be integrated. The discussion is particularly focused in the context of miniaturization and the development of new extractive materials. Through case studies, solvents and sorbents are examined using analytical performance, green, and market-related criteria, emphasizing the importance of integrating these perspectives into future tools. Solid-phase (SPME) and liquid-phase microextraction (LPME) are evaluated using the metric tools currently available, pointing out the challenges associated with the application. The results reveal the need to advance towards more advanced metric tools contextualizing the outcomes within the complexity of the analytical problem.
Significance and novelty: This manuscript highlight the need to advance metric tools towards models capable of integrating environmental, analytical, and practical dimensions within a coherent sustainability-oriented framework. The tutorial offers guidance for researchers and developers aiming to create more effective tools for the design and evaluation of sample preparation methods, tools that not only address greenness but also deliver greater robustness, relevance, and applicability in real analytical scenarios.
{"title":"A tutorial on developing metric tools for sample preparation: from green towards sustainable.","authors":"Lorenzo Sanjuan-Navarro, Juan Luís Benedé, Soledad Rubio, Carlos Moreno, Verónica Pino, Francisco Javier Pena-Pereira, Yolanda Moliner-Martínez","doi":"10.1016/j.aca.2025.345044","DOIUrl":"https://doi.org/10.1016/j.aca.2025.345044","url":null,"abstract":"<p><strong>Background: </strong>The use of current metric tools for sample preparation has proven highly valuable in identifying the strengths and weaknesses of various analytical approaches. However, as Analytical Sciences increasingly move towards sustainability, it becomes evident that existing metrics may not fully cover all the dimensions required for a comprehensive assessment.</p><p><strong>Results: </strong>An overview to encourage the evolution towards more advanced metric tools for sample preparation by reflecting on which parameters should be evaluated and on the principles that ought to guide their design. The tutorial highlights the need for new or improved metrics capable and identify the most relevant criteria and how they can be integrated. The discussion is particularly focused in the context of miniaturization and the development of new extractive materials. Through case studies, solvents and sorbents are examined using analytical performance, green, and market-related criteria, emphasizing the importance of integrating these perspectives into future tools. Solid-phase (SPME) and liquid-phase microextraction (LPME) are evaluated using the metric tools currently available, pointing out the challenges associated with the application. The results reveal the need to advance towards more advanced metric tools contextualizing the outcomes within the complexity of the analytical problem.</p><p><strong>Significance and novelty: </strong>This manuscript highlight the need to advance metric tools towards models capable of integrating environmental, analytical, and practical dimensions within a coherent sustainability-oriented framework. The tutorial offers guidance for researchers and developers aiming to create more effective tools for the design and evaluation of sample preparation methods, tools that not only address greenness but also deliver greater robustness, relevance, and applicability in real analytical scenarios.</p>","PeriodicalId":240,"journal":{"name":"Analytica Chimica Acta","volume":"1390 ","pages":"345044"},"PeriodicalIF":6.0,"publicationDate":"2026-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146123187","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 : 2026-02-07DOI: 10.1016/j.aca.2026.345214
Annika A.M. van der Zon, Bram Weijers, Danielle J. Vugts, Andrea F.G. Gargano
Background
Positron emission tomography (PET) using radiolabeled antibodies (radioimmunoconjugates) is a powerful imaging technique to track the distribution of therapeutic antibodies. Accurate determination of the average number of chelators per antibody (CAR) is essential for (radio)immunoconjugate characterization, which is important for maximizing tumor uptake and image quality. Determination of the CAR is considered a critical quality attribute. Radiometric titration, although widely used, is labor-intensive, material- and time-consuming, and requires approximately half a day per sample. To overcome this analytical bottleneck, we developed a microscale size exclusion chromatography – mass spectrometry (SEC-MS) analysis.
Results
By applying microscale flow, high concentrations of volatile salts, up to 1000 mM ammonium acetate, could be used to minimize secondary interactions. Moreover, high isCID energy of 140 eV was applied to reduce adduct formation and enhance the MS sensitivity. The method was optimized using model radioimmunoconjugates based on intact trastuzumab, with a particular focus on the impact of buffer concentration on both chromatographic effects and CAR determination. A final buffer concentration of 600 mM ammonium acetate was selected. The method was compared with radionuclide titration for analysis of the same immunoconjugate model and yielded similar results. Finally, we demonstrated the broad applicability of the method by testing diverse immunoconjugates (e.g., ipilimumab, rituximab), including cysteine- and lysine-linked chelators (e.g., DFO, DOTA, RESCA), as well as other smaller protein models, such as nanobodies.
Significance
The optimized microflow native SEC-MS method, with a rapid 20-minute run time, provides comprehensive characterization, including determination of the average CAR, dispersity index, glycosylation profile, and mAb impurities. Crucially, this native approach is applicable to all tested immunoconjugates, including chemically sensitive species such as those with maleimide and thiourea linkages, which often challenge denaturing methods like RPLC-MS. This establishes SEC-MS as a broadly applicable alternative to radiometric titration for the comprehensive characterization of immunoconjugates
{"title":"Microscale Native Size Exclusion Chromatography High Resolution Mass Spectrometry for the Determination of the Chelator-To-Antibody Ratio of Immunoconjugates","authors":"Annika A.M. van der Zon, Bram Weijers, Danielle J. Vugts, Andrea F.G. Gargano","doi":"10.1016/j.aca.2026.345214","DOIUrl":"https://doi.org/10.1016/j.aca.2026.345214","url":null,"abstract":"<h3>Background</h3>Positron emission tomography (PET) using radiolabeled antibodies (radioimmunoconjugates) is a powerful imaging technique to track the distribution of therapeutic antibodies. Accurate determination of the average number of chelators per antibody (CAR) is essential for (radio)immunoconjugate characterization, which is important for maximizing tumor uptake and image quality. Determination of the CAR is considered a critical quality attribute. Radiometric titration, although widely used, is labor-intensive, material- and time-consuming, and requires approximately half a day per sample. To overcome this analytical bottleneck, we developed a microscale size exclusion chromatography – mass spectrometry (SEC-MS) analysis.<h3>Results</h3>By applying microscale flow, high concentrations of volatile salts, up to 1000 mM ammonium acetate, could be used to minimize secondary interactions. Moreover, high isCID energy of 140 eV was applied to reduce adduct formation and enhance the MS sensitivity. The method was optimized using model radioimmunoconjugates based on intact trastuzumab, with a particular focus on the impact of buffer concentration on both chromatographic effects and CAR determination. A final buffer concentration of 600 mM ammonium acetate was selected. The method was compared with radionuclide titration for analysis of the same immunoconjugate model and yielded similar results. Finally, we demonstrated the broad applicability of the method by testing diverse immunoconjugates (e.g., ipilimumab, rituximab), including cysteine- and lysine-linked chelators (e.g., DFO, DOTA, RESCA), as well as other smaller protein models, such as nanobodies.<h3>Significance</h3>The optimized microflow native SEC-MS method, with a rapid 20-minute run time, provides comprehensive characterization, including determination of the average CAR, dispersity index, glycosylation profile, and mAb impurities. Crucially, this native approach is applicable to all tested immunoconjugates, including chemically sensitive species such as those with maleimide and thiourea linkages, which often challenge denaturing methods like RPLC-MS. This establishes SEC-MS as a broadly applicable alternative to radiometric titration for the comprehensive characterization of immunoconjugates","PeriodicalId":240,"journal":{"name":"Analytica Chimica Acta","volume":"51 1","pages":""},"PeriodicalIF":6.2,"publicationDate":"2026-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146135286","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 : 2026-02-07DOI: 10.1016/j.aca.2026.345210
David Gleerup, Matthijs Vynck, Lien Gysens, Cindy De Baere, Wim Trypsteen, Jo Vandesompele, Olivier Thas, Ann Martens, Maarten Haspeslagh, Ward De Spiegelaere
Background
Digital PCR (dPCR) enables precise and absolute quantification of nucleic acids by partitioning samples into thousands of reactions, improving reproducibility and reducing reliance on standard curves compared to qPCR. However, rigorous assay validation remains essential to ensure reliability, particularly for parameters such as limit of detection, limit of quantification, trueness, and linearity. Existing guidelines (e.g., MIQE, dMIQE, ISO 20395:2019) highlight these requirements, but implementation is laborious and inconsistent across laboratories. To address this, we developed PCR-ValiPal, a user-friendly web application that standardizes and streamlines dPCR assay validation and reporting.
Results
PCR-ValiPal calculates the full range of analytical parameters required for ISO-compliant assay validation, including limit of blank, limit of detection, limit of quantification, precision, trueness, and linearity. While broadly applicable to any nucleic acid target, we demonstrate its use with a three-color PCR assay for bovine papillomavirus (BPV), a clinically relevant representative DNA assay, types 1 and 2, benchmarked across four platforms: Naica (droplet dPCR), QIAcuity (microwell dPCR), LOAA (real-time dPCR), and CFX96 (qPCR). Cross-platform comparisons revealed Naica and QIAcuity achieved low LOB and LOQ values with minimal bias, while LOAA exhibited stable but negative bias. qPCR performed best for BPV-2 sensitivity but was less reliable for BPV-1 at low concentrations. These results illustrate both the value of platform-specific optimization and the utility of PCR-ValiPal in providing transparent, standardized validation outputs.
Significance
PCR-ValiPal supports transparent, reproducible, and ISO-aligned validation of PCR-based assays, lowering barriers for both expert and non-expert users. By centralizing statistical analyses in a single tool, it enables reliable comparison across platforms and targets, facilitating adoption in research, diagnostics, and regulatory contexts. This work underscores the importance of standardized validation for ensuring confidence in nucleic acid quantification.
{"title":"Standardized digital PCR assay validation using PCR-ValiPal, demonstrated in cross-platform quantification of bovine papilloma virus","authors":"David Gleerup, Matthijs Vynck, Lien Gysens, Cindy De Baere, Wim Trypsteen, Jo Vandesompele, Olivier Thas, Ann Martens, Maarten Haspeslagh, Ward De Spiegelaere","doi":"10.1016/j.aca.2026.345210","DOIUrl":"https://doi.org/10.1016/j.aca.2026.345210","url":null,"abstract":"<h3>Background</h3>Digital PCR (dPCR) enables precise and absolute quantification of nucleic acids by partitioning samples into thousands of reactions, improving reproducibility and reducing reliance on standard curves compared to qPCR. However, rigorous assay validation remains essential to ensure reliability, particularly for parameters such as limit of detection, limit of quantification, trueness, and linearity. Existing guidelines (e.g., MIQE, dMIQE, ISO 20395:2019) highlight these requirements, but implementation is laborious and inconsistent across laboratories. To address this, we developed PCR-ValiPal, a user-friendly web application that standardizes and streamlines dPCR assay validation and reporting.<h3>Results</h3>PCR-ValiPal calculates the full range of analytical parameters required for ISO-compliant assay validation, including limit of blank, limit of detection, limit of quantification, precision, trueness, and linearity. While broadly applicable to any nucleic acid target, we demonstrate its use with a three-color PCR assay for bovine papillomavirus (BPV), a clinically relevant representative DNA assay, types 1 and 2, benchmarked across four platforms: Naica (droplet dPCR), QIAcuity (microwell dPCR), LOAA (real-time dPCR), and CFX96 (qPCR). Cross-platform comparisons revealed Naica and QIAcuity achieved low LOB and LOQ values with minimal bias, while LOAA exhibited stable but negative bias. qPCR performed best for BPV-2 sensitivity but was less reliable for BPV-1 at low concentrations. These results illustrate both the value of platform-specific optimization and the utility of PCR-ValiPal in providing transparent, standardized validation outputs.<h3>Significance</h3>PCR-ValiPal supports transparent, reproducible, and ISO-aligned validation of PCR-based assays, lowering barriers for both expert and non-expert users. By centralizing statistical analyses in a single tool, it enables reliable comparison across platforms and targets, facilitating adoption in research, diagnostics, and regulatory contexts. This work underscores the importance of standardized validation for ensuring confidence in nucleic acid quantification.","PeriodicalId":240,"journal":{"name":"Analytica Chimica Acta","volume":"88 1","pages":""},"PeriodicalIF":6.2,"publicationDate":"2026-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146135312","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 : 2026-02-07DOI: 10.1016/j.aca.2026.345216
Wuji Shuoti, Ruihan Peng, Xuemei Wang, Qiuxia Liu, Yixin Huang, Lishuo Liu, Yanyu Jiang, Jie Wen, Lian Zhong, Lujun Wang
Background
Bisphenols are widely used in thermal paper, inks, coatings, and other fields. Among them, abnormal concentrations of bisphenol A (BPA) can disrupt the human endocrine system, making it essential to closely monitor BPA levels in environmental and daily life samples. Owing to its strong separation and analytical capabilities, high performance liquid chromatography (HPLC) enables accurate analysis of compounds in complex real-world samples. Among various HPLC stationary phases, dendritic stationary phase materials have attracted significant attention due to their unique branched spatial structure. Therefore, it is of great research importance to continuously investigate dendritic HPLC stationary phases, expand their variety, and broaden their applications.
Results
The novel dendrimer based stationary phase named as Sil-G1-BDDE-TTCA was synthesized by modifying 1,4-butanediol diglycidyl ether and trithiocyanuric acid onto silica surfaces via thiol-epoxy click reaction. Through three repeated grafting, the third-generation stationary phase named as Sil-G3-BDDE-TTCA was prepared. The C18 modified dendrimer based stationary phase named as Sil-G3-BDDE-TTCA-C18 was finally prepared using 1-octadecene as a capping functional monomer. These dendritic stationary phases were characterized by Elemental analysis, Thermogravimetric analysis, Scanning electron microscope and X-ray photoelectron spectroscopy. To evaluate the hydrophobic, hydrophilic, and π-π interactions of the prepared dendritic stationary phases, test mixtures including alkylbenzenes, positional isomers, polycyclic aromatic hydrocarbons, nucleosides, and flavonoids were analyzed. The Tanaka test was employed to compare the chromatographic performance of different stationary phases. Thermodynamic parameters for the retention of alkylbenzenes and positional isomers on these stationary phases were calculated to investigate the effect of temperature on chromatographic behavior. The reproducibility of these prepared dendritic columns was investigated, yielding satisfactory results.
Significance
For the first time, a dendritic mixed-mode stationary phase was fabricated via thiol-epoxy click reaction for detecting bisphenols in actual samples. This strategy overcomes the time-consuming and inefficient synthesis of traditional dendritic phases, offering a novel route for dendritic materials and extending their environmental applications.
{"title":"Dendritic mixed-mode stationary phases prepared by thiol-epoxy click reaction for the determination of bisphenols in a variety of complex samples","authors":"Wuji Shuoti, Ruihan Peng, Xuemei Wang, Qiuxia Liu, Yixin Huang, Lishuo Liu, Yanyu Jiang, Jie Wen, Lian Zhong, Lujun Wang","doi":"10.1016/j.aca.2026.345216","DOIUrl":"https://doi.org/10.1016/j.aca.2026.345216","url":null,"abstract":"<h3>Background</h3>Bisphenols are widely used in thermal paper, inks, coatings, and other fields. Among them, abnormal concentrations of bisphenol A (BPA) can disrupt the human endocrine system, making it essential to closely monitor BPA levels in environmental and daily life samples. Owing to its strong separation and analytical capabilities, high performance liquid chromatography (HPLC) enables accurate analysis of compounds in complex real-world samples. Among various HPLC stationary phases, dendritic stationary phase materials have attracted significant attention due to their unique branched spatial structure. Therefore, it is of great research importance to continuously investigate dendritic HPLC stationary phases, expand their variety, and broaden their applications.<h3>Results</h3>The novel dendrimer based stationary phase named as Sil-G1-BDDE-TTCA was synthesized by modifying 1,4-butanediol diglycidyl ether and trithiocyanuric acid onto silica surfaces via thiol-epoxy click reaction. Through three repeated grafting, the third-generation stationary phase named as Sil-G3-BDDE-TTCA was prepared. The C18 modified dendrimer based stationary phase named as Sil-G3-BDDE-TTCA-C18 was finally prepared using 1-octadecene as a capping functional monomer. These dendritic stationary phases were characterized by Elemental analysis, Thermogravimetric analysis, Scanning electron microscope and X-ray photoelectron spectroscopy. To evaluate the hydrophobic, hydrophilic, and <em>π-π</em> interactions of the prepared dendritic stationary phases, test mixtures including alkylbenzenes, positional isomers, polycyclic aromatic hydrocarbons, nucleosides, and flavonoids were analyzed. The Tanaka test was employed to compare the chromatographic performance of different stationary phases. Thermodynamic parameters for the retention of alkylbenzenes and positional isomers on these stationary phases were calculated to investigate the effect of temperature on chromatographic behavior. The reproducibility of these prepared dendritic columns was investigated, yielding satisfactory results.<h3>Significance</h3>For the first time, a dendritic mixed-mode stationary phase was fabricated via thiol-epoxy click reaction for detecting bisphenols in actual samples. This strategy overcomes the time-consuming and inefficient synthesis of traditional dendritic phases, offering a novel route for dendritic materials and extending their environmental applications.","PeriodicalId":240,"journal":{"name":"Analytica Chimica Acta","volume":"1 1","pages":""},"PeriodicalIF":6.2,"publicationDate":"2026-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146135316","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}
β2−agonists, also known as β2−adrenoceptor agonists, are secreted by the adrenal medulla of the animal body and have a characteristic catecholamine structure. When inhaled, the drug rapidly relaxes the smooth muscles of the airways in asthma patients, improves ventilation, and temporarily increases alertness during exercise and helps relieve fatigue. However, the use of β2−agonists to improve physical performance in a short period of time can lead to extreme dependence and irritation, and there are still many unknown hazards. They are now on the World Anti−Doping Organization (WADA) prohibited list.
Results
Surface−enhanced Raman spectroscopy (SERS) can directly detect the characteristic peaks associated with β2−agonist compounds in a fast and sensitive manner. This study is the first to utilize a direct Raman detection technique, achieving successful acquisition of the fingerprint spectra of three target analytes (vilanterol, fenoterol, bambuterol) as well as the establishment of a corresponding fingerprint spectral analysis method. To further improve its performance, in this study, gold nanoparticles were synthesized via redox methods and integrated with covalent organic framework (COF) to construct a novel highly sensitive detection platform for β2−agonists. The Au−COF composite exhibits high adsorption performance and can significantly enhance the SERS signal of the target, thereby achieving low detection limits, including 9.25 × 10−6 g·mL−1 for bambuterol, 9.76 × 10−6 g·mL−1 for vilanterol, and 7.54 × 10−6 g·mL−1 for fenoterol, which makes it promising for improving the overall sensitivity of β2−agonist detection.
Significance
This study develops a novel analytical method utilizing Au−COF composites for highly sensitive SERS detection. It pioneers the application of this strategy in the qualitative and quantitative analysis of trace β2-agonists. The research not only significantly expands the scope of Au−COF composites but also provides a technologically promising approach with substantial practical value for ensuring medical safety through clinical medication monitoring and for detecting banned substances in sports.
{"title":"SERS Fingerprinting of β2-Agonists for Anti-Doping Based on Au-COF Substrate","authors":"Siqing Liu, Liping Chen, Xingju Li, Ruxi Lin, Yunxin Zhang, Xiaojun Luo","doi":"10.1016/j.aca.2026.345206","DOIUrl":"https://doi.org/10.1016/j.aca.2026.345206","url":null,"abstract":"<h3>Background</h3>β<sub>2</sub>−agonists, also known as β<sub>2</sub>−adrenoceptor agonists, are secreted by the adrenal medulla of the animal body and have a characteristic catecholamine structure. When inhaled, the drug rapidly relaxes the smooth muscles of the airways in asthma patients, improves ventilation, and temporarily increases alertness during exercise and helps relieve fatigue. However, the use of β<sub>2</sub>−agonists to improve physical performance in a short period of time can lead to extreme dependence and irritation, and there are still many unknown hazards. They are now on the World Anti−Doping Organization (WADA) prohibited list.<h3>Results</h3>Surface−enhanced Raman spectroscopy (SERS) can directly detect the characteristic peaks associated with β<sub>2</sub>−agonist compounds in a fast and sensitive manner. This study is the first to utilize a direct Raman detection technique, achieving successful acquisition of the fingerprint spectra of three target analytes (vilanterol, fenoterol, bambuterol) as well as the establishment of a corresponding fingerprint spectral analysis method. To further improve its performance, in this study, gold nanoparticles were synthesized via redox methods and integrated with covalent organic framework (COF) to construct a novel highly sensitive detection platform for β<sub>2</sub>−agonists. The Au−COF composite exhibits high adsorption performance and can significantly enhance the SERS signal of the target, thereby achieving low detection limits, including 9.25 × 10<sup>−6</sup> g·mL<sup>−1</sup> for bambuterol, 9.76 × 10<sup>−6</sup> g·mL<sup>−1</sup> for vilanterol, and 7.54 × 10<sup>−6</sup> g·mL<sup>−1</sup> for fenoterol, which makes it promising for improving the overall sensitivity of β<sub>2</sub>−agonist detection.<h3>Significance</h3>This study develops a novel analytical method utilizing Au−COF composites for highly sensitive SERS detection. It pioneers the application of this strategy in the qualitative and quantitative analysis of trace β2-agonists. The research not only significantly expands the scope of Au−COF composites but also provides a technologically promising approach with substantial practical value for ensuring medical safety through clinical medication monitoring and for detecting banned substances in sports.","PeriodicalId":240,"journal":{"name":"Analytica Chimica Acta","volume":"9 1","pages":""},"PeriodicalIF":6.2,"publicationDate":"2026-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146129704","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 : 2026-02-06DOI: 10.1016/j.aca.2026.345205
Adel Ehab Ibrahim, Samy G. Alamir, Ghanem Al-Thani, Sami El Deeb, Ahmed Al-Harrasi
Background
Molecular chirality has a profound impact on pharmaceutical drugs’ efficacy and safety. Thus, chiral recognition plays a vital role in drug development throughout all process stages. LF is a globular glycoprotein composed of approximately 700 amino acids, that’s capable of providing multiple interactions through its amino acid residues.
Results
In the proposed research, lactoferrin (LF) was covalently immobilized for the first time using a monolithic epoxy stationary phase via a Schiff’s base formation as chiral selector (CS). LF-CS was evaluated for the enantioselective HPLC separation of 18 racemic pharmaceutical drugs. The chromatographic conditions were optimized for optimum enantio-separation. LF-CS proved its potential as a CS enabling the enantioseparation of 10 drug racemates: cetirizine, omeprazole, lansoprazole, dapoxetine, doxazosin, nebivolol, atenolol, bisoprolol, chlorthalidone and ofloxacin. Moreover, in-silico molecular docking studies were conducted to help understand the separation modes. LF as a CS reported hydrogen bonding, hydrophobic interactions, π bonding, Van der Waals forces, and electrostatic interactions. Finally, the novel LF-CS was applied to determine the enantiomeric purity of marketed single-enantiomer pharmaceutical products, demonstrating its ability to verify their composition and identify impurities.
Significance
HPLC remains the primary choice for all pharmaceutical research, as it offers higher sensitivity, reliability, and reproducibility. This work introduces LF as a novel, multifunctional CS for HPLC, covalently immobilized for the first time, expanding the toolbox of protein-based chiral stationary phases. Moreover, the study also offers a critical insight into the limitations of relying solely on computational predictions, empirically demonstrating that solvent effects can override binding affinities, a phenomenon not captured by standard docking simulations.
{"title":"Exploring Lactoferrin as an Innovative Covalently Immobilized Chiral Selector for the Selective Separation of Pharmaceutical Enantiomers Using HPLC","authors":"Adel Ehab Ibrahim, Samy G. Alamir, Ghanem Al-Thani, Sami El Deeb, Ahmed Al-Harrasi","doi":"10.1016/j.aca.2026.345205","DOIUrl":"https://doi.org/10.1016/j.aca.2026.345205","url":null,"abstract":"<h3>Background</h3>Molecular chirality has a profound impact on pharmaceutical drugs’ efficacy and safety. Thus, chiral recognition plays a vital role in drug development throughout all process stages. LF is a globular glycoprotein composed of approximately 700 amino acids, that’s capable of providing multiple interactions through its amino acid residues.<h3>Results</h3>In the proposed research, lactoferrin (LF) was covalently immobilized for the first time using a monolithic epoxy stationary phase via a Schiff’s base formation as chiral selector (CS). LF-CS was evaluated for the enantioselective HPLC separation of 18 racemic pharmaceutical drugs. The chromatographic conditions were optimized for optimum enantio-separation. LF-CS proved its potential as a CS enabling the enantioseparation of 10 drug racemates: cetirizine, omeprazole, lansoprazole, dapoxetine, doxazosin, nebivolol, atenolol, bisoprolol, chlorthalidone and ofloxacin. Moreover, <em>in-silico</em> molecular docking studies were conducted to help understand the separation modes. LF as a CS reported hydrogen bonding, hydrophobic interactions, π bonding, Van der Waals forces, and electrostatic interactions. Finally, the novel LF-CS was applied to determine the enantiomeric purity of marketed single-enantiomer pharmaceutical products, demonstrating its ability to verify their composition and identify impurities.<h3>Significance</h3>HPLC remains the primary choice for all pharmaceutical research, as it offers higher sensitivity, reliability, and reproducibility. This work introduces LF as a novel, multifunctional CS for HPLC, covalently immobilized for the first time, expanding the toolbox of protein-based chiral stationary phases. Moreover, the study also offers a critical insight into the limitations of relying solely on computational predictions, empirically demonstrating that solvent effects can override binding affinities, a phenomenon not captured by standard docking simulations.","PeriodicalId":240,"journal":{"name":"Analytica Chimica Acta","volume":"182 1","pages":""},"PeriodicalIF":6.2,"publicationDate":"2026-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146135331","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}
As the land-based mineral deposits are depleting fast, deep-sea metal mineral resources have been proven to have a great mining value. Traditional deep-sea mineral detection techniques require ore samples to be brought back to the laboratory by geological sampling methods for chemical analysis. This approach suffers from substantial time delays and cannot provide real-time, large-scale and rapid feedback during the mining process. Therefore, there is a critical demand for the rapid and in-situ technique of underwater ores identification without requiring the ore samples to be brought back to the laboratory.
Results
We combined LIBS and time-gated Raman spectroscopy for the rapid identification of underwater ores. An integrated LIBS-Raman setup was built based on a same laser and a same spectrometer, to acquire both the elemental and molecular information of ore samples immersed in deionized water. PLS-DA was used to establish the classification model based on the LIBS and Raman spectra. Two data fusion strategies including data-level fusion and feature-level fusion were used for the combination of LIBS and Raman data. The data fusion strategies offer a significant improvement in ores classification compared to using the individual LIBS or Raman data. The data-level fusion model provides the best classification accuracy of 99.11%, while the feature-level fusion model has a slightly lower accuracy of 98.44% but with a much reduced computation time. The feature selection by successive projections algorithm (SPA) involved in the feature-level fusion improves the computing efficiency and the interpretability of the model.
Significance
The present results demonstrated the capability of LIBS and Raman techniques for the rapid identification of underwater ores. The integrated setup that combining LIBS with time-gated Raman spectroscopy based on a same laser source and a same spectrometer could be beneficial for developing down-sizing and low-power consumed underwater devices for the future deep-sea mining applications.
{"title":"Combining laser-induced breakdown spectroscopy (LIBS) and time-gated Raman spectroscopy for underwater ores identification","authors":"Jiaojian Song, Ye Tian, Yuanyuan Xue, Qingxi Liu, Pingsai Chu, Jinjia Guo, Yuan Lu, Ronger Zheng","doi":"10.1016/j.aca.2026.345204","DOIUrl":"https://doi.org/10.1016/j.aca.2026.345204","url":null,"abstract":"<h3>Background</h3>As the land-based mineral deposits are depleting fast, deep-sea metal mineral resources have been proven to have a great mining value. Traditional deep-sea mineral detection techniques require ore samples to be brought back to the laboratory by geological sampling methods for chemical analysis. This approach suffers from substantial time delays and cannot provide real-time, large-scale and rapid feedback during the mining process. Therefore, there is a critical demand for the rapid and in-situ technique of underwater ores identification without requiring the ore samples to be brought back to the laboratory.<h3>Results</h3>We combined LIBS and time-gated Raman spectroscopy for the rapid identification of underwater ores. An integrated LIBS-Raman setup was built based on a same laser and a same spectrometer, to acquire both the elemental and molecular information of ore samples immersed in deionized water. PLS-DA was used to establish the classification model based on the LIBS and Raman spectra. Two data fusion strategies including data-level fusion and feature-level fusion were used for the combination of LIBS and Raman data. The data fusion strategies offer a significant improvement in ores classification compared to using the individual LIBS or Raman data. The data-level fusion model provides the best classification accuracy of 99.11%, while the feature-level fusion model has a slightly lower accuracy of 98.44% but with a much reduced computation time. The feature selection by successive projections algorithm (SPA) involved in the feature-level fusion improves the computing efficiency and the interpretability of the model.<h3>Significance</h3>The present results demonstrated the capability of LIBS and Raman techniques for the rapid identification of underwater ores. The integrated setup that combining LIBS with time-gated Raman spectroscopy based on a same laser source and a same spectrometer could be beneficial for developing down-sizing and low-power consumed underwater devices for the future deep-sea mining applications.","PeriodicalId":240,"journal":{"name":"Analytica Chimica Acta","volume":"293 1","pages":""},"PeriodicalIF":6.2,"publicationDate":"2026-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146129703","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}
The identification of structural features is an essential prerequisite for the determination of DNA secondary structures and investigating structural formation mechanisms. Circular dichroism (CD) spectroscopy, fluorescence (FL) spectroscopy, and thermal difference spectra (TDS) have already been used to monitor the DNA secondary structures due to their advantages in operation simplicity, detection speed and lower cost. However, each individual spectroscopic method has limitations in providing comprehensive structural information. Therefore, we propose that integrating these three spectroscopic techniques could improve the classification accuracy of DNA secondary structures—though to date, no related studies have been reported.
Results
In this assay, a combination method of CD, FL, and TDS was proposed through machine learning (ML). Principal component analysis (PCA) was firstly used to reduce the dimensionality and facilitate data analysis, and then, three machine learning methods, including linear discriminant analysis (LDA), K-nearest neighbor (KNN), and support vector machine (SVM), are employed to deeply excavate more structure-related information of CD, FL, and TDS spectra. Combined with a two-step ML strategy, 79 out of 85 DNA sequences, that fall into G4, iM and DS category respectively, were correctly classified (classification accuracy of 0.95). Thus, we achieved the goal of predicting unknown DNA secondary structures by combining CD, FL, and TDS spectra, and demonstrated the superiority of the combination of three spectra in DNA structure identification.
Significance
The method is significantly superior to the single spectroscopic technique. Thus, a simple, fast and cost-efficient spectroscopic platform for direct and comprehensive identification of DNA secondary structures has been established. By building a multispectral database and using ML methods, the accurate and comprehensive identification of unknown DNA secondary structures will finally be realized.
{"title":"Classification of DNA secondary structures by combining multiple spectral techniques with machine learning","authors":"Hong Luo, Guantong Xu, Yujing Zhang, Xiaoxuan Xiang, Hao Wang, Xinhua Guo","doi":"10.1016/j.aca.2026.345195","DOIUrl":"https://doi.org/10.1016/j.aca.2026.345195","url":null,"abstract":"<h3>Background</h3>The identification of structural features is an essential prerequisite for the determination of DNA secondary structures and investigating structural formation mechanisms. Circular dichroism (CD) spectroscopy, fluorescence (FL) spectroscopy, and thermal difference spectra (TDS) have already been used to monitor the DNA secondary structures due to their advantages in operation simplicity, detection speed and lower cost. However, each individual spectroscopic method has limitations in providing comprehensive structural information. Therefore, we propose that integrating these three spectroscopic techniques could improve the classification accuracy of DNA secondary structures—though to date, no related studies have been reported.<h3>Results</h3>In this assay, a combination method of CD, FL, and TDS was proposed through machine learning (ML). Principal component analysis (PCA) was firstly used to reduce the dimensionality and facilitate data analysis, and then, three machine learning methods, including linear discriminant analysis (LDA), K-nearest neighbor (KNN), and support vector machine (SVM), are employed to deeply excavate more structure-related information of CD, FL, and TDS spectra. Combined with a two-step ML strategy, 79 out of 85 DNA sequences, that fall into G4, iM and DS category respectively, were correctly classified (classification accuracy of 0.95). Thus, we achieved the goal of predicting unknown DNA secondary structures by combining CD, FL, and TDS spectra, and demonstrated the superiority of the combination of three spectra in DNA structure identification.<h3>Significance</h3>The method is significantly superior to the single spectroscopic technique. Thus, a simple, fast and cost-efficient spectroscopic platform for direct and comprehensive identification of DNA secondary structures has been established. By building a multispectral database and using ML methods, the accurate and comprehensive identification of unknown DNA secondary structures will finally be realized.","PeriodicalId":240,"journal":{"name":"Analytica Chimica Acta","volume":"48 1","pages":""},"PeriodicalIF":6.2,"publicationDate":"2026-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146129535","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}
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