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Fekete S, Guillarme D. Ultra-short columns for the chromatographic analysis of large molecules. J Chromatogr A 2023; 1706:464285. [PMID: 37562104 DOI: 10.1016/j.chroma.2023.464285] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Revised: 07/31/2023] [Accepted: 08/04/2023] [Indexed: 08/12/2023]
Abstract
Today, reverse phase liquid chromatography (RPLC) analysis of proteins is almost exclusively performed on conventional columns (100-150 mm) in gradient elution mode. However, it was shown many years ago that large molecules present an on/off retention mechanism, and that only a very short inlet segment of the chromatographic column retains effectively the large molecules. Much shorter columns - like only a few centimetres or even a few millimetres - can therefore be used to efficiently analyse such macromolecules. The aim of this review is to summarise the historical and more recent works related to the use of very short columns for the analysis of model and therapeutic proteins. To this end, we have outlined the theoretical concepts behind the use of short columns, as well as the instrumental limitations and potential applications. Finally, we have shown that these very short columns were also possibly interesting for other chromatographic modes, such as ion exchange chromatography (IEX), hydrophilic interaction chromatography (HILIC) or hydrophobic interaction chromatography (HIC), as analyses in these chromatographic modes are performed in gradient elution mode.
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Affiliation(s)
| | - Davy Guillarme
- Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva, CMU - Rue Michel Servet 1, 1211 Geneva 4, Switzerland; School of Pharmaceutical Sciences, University of Geneva, CMU - Rue Michel Servet 1, 1211 Geneva 4, Switzerland.
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Porfido C, Köpke K, Allegretta I, Bandte M, von Bargen S, Rybak M, Falkenberg G, Mimmo T, Cesco S, Büttner C, Terzano R. Combining micro- and portable-XRF as a tool for fast identification of virus infections in plants: The case study of ASa-Virus in Fraxinus ornus L. Talanta 2023; 262:124680. [PMID: 37235957 DOI: 10.1016/j.talanta.2023.124680] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2022] [Revised: 04/21/2023] [Accepted: 05/15/2023] [Indexed: 05/28/2023]
Abstract
Plant viruses can affect micro- and macro-nutrients homeostasis in woody plants, with fluctuation in the concentration of some elements at the leaf level due to the pathogen activity and/or the plant physiological response to the infection.Leaves of Fraxinus ornus L. (flowering ash) were sampled for three consecutive years in the city of Hamburg (Germany), from both trees showing the typical symptoms of the ash shoestring associated virus infection (ASaV+) and healthy trees (ASaV-). Such leaves were analyzed by μ-XRF, using both laboratory and synchrotron X-ray sources, and large differences between symptomatic and not symptomatic leaves were observed: ASaV+ samples showed uneven element distribution and regions of the lamina with severe depletions of P, S, and Ca. Differently, K appeared more concentrated. Thus, 139 leaflets sampled from various healthy and infected ash trees over the three-year period were analyzed for K and Ca concentration with a portable XRF instrument. We found that the K:Ca concentration ratio was always significantly higher in ASaV+ samples, and this trend was verified for all the samplings over the tree years. We conclude that the K:Ca ratio parameter has potential in the frame of trendsetting diagnostics and could be used, together with visual symptoms, for a rapid, non-destructive, on-site and cheap indirect ASaV detection.
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Affiliation(s)
- Carlo Porfido
- Department of Soil, Plant and Food Sciences, University of Bari "Aldo Moro", Via G. Amendola 165/A, 70126, Bari, Italy.
| | - Kira Köpke
- Humboldt-Universität zu Berlin, Division Phytomedicine, Berlin, Germany, Lentzeallee 55/57, 14195, Berlin, Germany
| | - Ignazio Allegretta
- Department of Soil, Plant and Food Sciences, University of Bari "Aldo Moro", Via G. Amendola 165/A, 70126, Bari, Italy; Department of Biological and Environmental Sciences and Technologies, University of Salento, Via Monteroni 165, 73100, Lecce, Italy
| | - Martina Bandte
- Humboldt-Universität zu Berlin, Division Phytomedicine, Berlin, Germany, Lentzeallee 55/57, 14195, Berlin, Germany
| | - Susanne von Bargen
- Humboldt-Universität zu Berlin, Division Phytomedicine, Berlin, Germany, Lentzeallee 55/57, 14195, Berlin, Germany
| | - Malgorzata Rybak
- Plant Protection Service Hamburg, Ministry of Economy and Innovation, Free and Hanseatic City of Hamburg, Brennerhof 123, 22113, Hamburg, Germany
| | - Gerald Falkenberg
- Deutsches Elektronen-Synchrotron DESY, Notkestrasse 85, 22607, Hamburg, Germany
| | - Tanja Mimmo
- Faculty of Science and Technology, Free University of Bolzano, Piazza Universitá 5, 39100, Bolzano, Italy; Competence Centre for Plant Health, Free University of Bolzano, Piazza Universitá 1, 39100, Bolzano, Italy
| | - Stefano Cesco
- Faculty of Science and Technology, Free University of Bolzano, Piazza Universitá 5, 39100, Bolzano, Italy
| | - Carmen Büttner
- Humboldt-Universität zu Berlin, Division Phytomedicine, Berlin, Germany, Lentzeallee 55/57, 14195, Berlin, Germany
| | - Roberto Terzano
- Department of Soil, Plant and Food Sciences, University of Bari "Aldo Moro", Via G. Amendola 165/A, 70126, Bari, Italy
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Madurani KA, Suprapto, Yudha Syahputra M, Puspita I, Furqoni AH, Puspasari L, Rosyidah H, Hatta AM, Juniastuti, Lusida MI, Tominaga M, Kurniawan F. Fluorescence spectrophotometry for COVID-19 determination in clinical swab samples. ARAB J CHEM 2022; 15:104020. [PMID: 35664893 PMCID: PMC9150911 DOI: 10.1016/j.arabjc.2022.104020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Accepted: 05/25/2022] [Indexed: 11/29/2022] Open
Abstract
Considering the limitations of the assays currently available for the detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its emerging variants, a simple and rapid method using fluorescence spectrophotometry was developed to detect coronavirus disease 2019 (COVID-19). Forty clinical swab samples were collected from the nasopharyngeal and oropharyngeal cavities of COVID-19-positive and -negative. Each sample was divided into two parts. The first part of the samples was analyzed using reverse transcription-polymerase chain reaction (RT-qPCR) as the control method to identify COVID-19-positive and -negative samples. The second part of the samples was analyzed using fluorescence spectrophotometry. Fluorescence measurements were performed at excitation and emission wavelengths ranging from 200 to 800 nm. Twenty COVID-19-positive samples and twenty COVID-19-negative samples were detected based on RT-qPCR results. The fluorescence spectrum data indicated that the COVID-19-positive and -negative samples had significantly different characteristics. All positive samples could be distinguished from negative samples by fluorescence spectrophotometry. Principal component analysis showed that COVID-19-positive samples were clustered separately from COVID-19-negative samples. The specificity and accuracy of this experiment reached 100%. Limit of detection (LOD) obtained 42.20 copies/ml (Ct value of 33.65 cycles) for E gene and 63.60 copies/ml (Ct value of 31.36 cycles) for ORF1ab gene. This identification process only required 4 min. Thus, this technique offers an efficient and accurate method to identify an individual with active SARS-CoV-2 infection and can be easily adapted for the early investigation of COVID-19, in general.
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Affiliation(s)
- Kartika A Madurani
- Laboratory of Instrumentation and Analytical Science, Chemistry Department, Faculty of Science and Data Analytics, Institut Teknologi Sepuluh Nopember, Surabaya 60111, Indonesia
| | - Suprapto
- Laboratory of Instrumentation and Analytical Science, Chemistry Department, Faculty of Science and Data Analytics, Institut Teknologi Sepuluh Nopember, Surabaya 60111, Indonesia
| | - Muhammad Yudha Syahputra
- Laboratory of Instrumentation and Analytical Science, Chemistry Department, Faculty of Science and Data Analytics, Institut Teknologi Sepuluh Nopember, Surabaya 60111, Indonesia
| | - Ika Puspita
- Photonics Engineering Laboratory, Department of Engineering Physics, Faculty of Industrial Technology and Systems Engineering, Institut Teknologi Sepuluh Nopember, Surabaya 60111, Indonesia
| | - Abdul Hadi Furqoni
- Human Genetic Laboratory, Institute of Tropical Disease, Airlangga University, Surabaya 60115, Indonesia
| | - Listya Puspasari
- Laboratory of Instrumentation and Analytical Science, Chemistry Department, Faculty of Science and Data Analytics, Institut Teknologi Sepuluh Nopember, Surabaya 60111, Indonesia
| | - Hafildatur Rosyidah
- Laboratory of Instrumentation and Analytical Science, Chemistry Department, Faculty of Science and Data Analytics, Institut Teknologi Sepuluh Nopember, Surabaya 60111, Indonesia
| | - Agus Muhamad Hatta
- Photonics Engineering Laboratory, Department of Engineering Physics, Faculty of Industrial Technology and Systems Engineering, Institut Teknologi Sepuluh Nopember, Surabaya 60111, Indonesia
| | - Juniastuti
- Faculty of Medicine, Airlangga University, Surabaya 60131, Indonesia.,Institute of Tropical Disease, Airlangga University, Surabaya 60115, Indonesia
| | - Maria Inge Lusida
- Faculty of Medicine, Airlangga University, Surabaya 60131, Indonesia.,Institute of Tropical Disease, Airlangga University, Surabaya 60115, Indonesia
| | - Masato Tominaga
- Department of Chemistry and Applied Chemistry, Graduate School of Science and Engineering, Saga University, Saga 840-8502, Japan
| | - Fredy Kurniawan
- Laboratory of Instrumentation and Analytical Science, Chemistry Department, Faculty of Science and Data Analytics, Institut Teknologi Sepuluh Nopember, Surabaya 60111, Indonesia
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Kurniawan F, Nugroho A, Baskara RA, Candle L, Pradini D, Madurani KA, Sugiarso RD, Juwono H. Rapid analysis to distinguish porcine and bovine gelatin using PANI/NiO nanoparticles modified Quartz Crystal Microbalance (QCM) sensor. Heliyon 2022; 8:e09401. [PMID: 35600448 PMCID: PMC9118674 DOI: 10.1016/j.heliyon.2022.e09401] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2021] [Revised: 03/22/2022] [Accepted: 05/05/2022] [Indexed: 10/31/2022] Open
Abstract
Rapid analysis to distinguish porcine and bovine gelatin using a modified Quartz Crystal Microbalance (QCM) sensor has been studied. The PANI was deposited on the sensor surface using electropolymerization, and then nickel nanoparticles were deposited by layer by layer (LbL) technique. The modified QCM sensor's performance was compared to an unmodified sensor in porcine and bovine gelatin at neutral, acidic, and alkaline conditions. The result shows that the unmodified sensor cannot distinguish between porcine and bovine gelatin, whereas the modified QCM sensor produces a different response. Porcine gelatin shows an increasing frequency response, but in contrast, bovine gelatin decreases frequency response at the alkaline condition. The time response was 2 min with a detection limit of 51.2 ppm and 8.7 ppm for porcine and bovine gelatin, respectively. Further investigation shows that the modified sensor can analyze porcine gelatin contamination in the a mixed gelatin sample.
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Affiliation(s)
- Fredy Kurniawan
- Laboratory of Instrumentation and Analytical Sciences, Chemistry Department, Faculty of Science and Data Analytics, Institut Teknologi Sepuluh Nopember, Surabaya 60111, Indonesia.,ITS Halal Center, Institute of Research and Community Service, Institut Teknologi Sepuluh Nopember, Surabaya 60111, Indonesia
| | - Ari Nugroho
- Laboratory of Instrumentation and Analytical Sciences, Chemistry Department, Faculty of Science and Data Analytics, Institut Teknologi Sepuluh Nopember, Surabaya 60111, Indonesia
| | - Rangga Aji Baskara
- Laboratory of Instrumentation and Analytical Sciences, Chemistry Department, Faculty of Science and Data Analytics, Institut Teknologi Sepuluh Nopember, Surabaya 60111, Indonesia
| | - Lourentia Candle
- Laboratory of Instrumentation and Analytical Sciences, Chemistry Department, Faculty of Science and Data Analytics, Institut Teknologi Sepuluh Nopember, Surabaya 60111, Indonesia
| | - Diwasasri Pradini
- Laboratory of Instrumentation and Analytical Sciences, Chemistry Department, Faculty of Science and Data Analytics, Institut Teknologi Sepuluh Nopember, Surabaya 60111, Indonesia
| | - Kartika A Madurani
- Laboratory of Instrumentation and Analytical Sciences, Chemistry Department, Faculty of Science and Data Analytics, Institut Teknologi Sepuluh Nopember, Surabaya 60111, Indonesia
| | - Raden Djarot Sugiarso
- Laboratory of Instrumentation and Analytical Sciences, Chemistry Department, Faculty of Science and Data Analytics, Institut Teknologi Sepuluh Nopember, Surabaya 60111, Indonesia
| | - Hendro Juwono
- Laboratory of Instrumentation and Analytical Sciences, Chemistry Department, Faculty of Science and Data Analytics, Institut Teknologi Sepuluh Nopember, Surabaya 60111, Indonesia
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Spijkerman R, Hesselink L, Hellebrekers P, Vrisekoop N, Hietbrink F, Leenen LPH, Koenderman L. Automated flow cytometry enables high performance point-of-care analysis of leukocyte phenotypes. J Immunol Methods 2019; 474:112646. [PMID: 31419409 DOI: 10.1016/j.jim.2019.112646] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2019] [Revised: 08/09/2019] [Accepted: 08/12/2019] [Indexed: 01/23/2023]
Abstract
INTRODUCTION Phagocytes such as granulocytes and monocytes are fundamental players in the innate immune system. Activation of these cells can be quantified by the measurement of activation marker expression using flow cytometry. Analysis of receptor expression on inflammatory cells facilitates the diagnosis of inflammatory diseases and can be used to determine the extent of inflammation. However, several major limitations of this analysis precludes application of inflammation monitoring in clinical practice. Fast and automated analysis would minimalize ex vivo manipulation and allow reproducible processing. The aim of this study was to evaluate a fully automated "load & go" flow cytometer for analyzing activation of granulocytes and monocytes in a clinically applicable setting. METHODS Blood samples were obtained from 10 anonymous and healthy volunteers between the age of 18 and 65 years. Granulocyte and monocyte activation was determined by the use of the markers CD35, CD11b and CD10 measured in the automated AQUIOS CL® "load & go" flow cytometer. This machine is able to pierce the tube caps, add antibodies, lyse and measure the sample within 20 min after vena puncture. Reproducibility tests were performed to test the stability of activation marker expression on phagocytes. The expression of activation markers was measured at different time points after blood drawing to analyze the effect of bench time on granulocyte and monocyte activation. RESULTS The duplicate experiments demonstrate a high reproducibility of the measurements of the activation state of phagocytes. Healthy controls showed a very homogenous expression of activation markers at T = 0 (immediately after vena puncture). Activation markers on neutrophils were already significantly increased after 1 h (T = 1) depicted as means (95%Cl) CD35: 2.2× (1.5×-2.5×) p = .028, CD11b: 2.5× (1.7×-3.1×) p = .023, CD10: 2.5× (2.1×-2.7×) p = .009) and a further increase in activation markers was observed after 2 and 3 h. Monocytes also showed a increase in activation markers in 1 h (mean (95%Cl) CD35: 1.8× (1.3×-2.2×) p = .058, CD11b: 2.13× (1.6×-2.4×) p = .025) and also a further significant increase in 2 and 3 h was observed. CONCLUSION This study showed that bench time of one hour already leads to a significant upregulation and bigger variance in activation markers of granulocytes and monocytes. In addition, it is likely that automated flow cytometry reduces intra-assay variability in the analysis of activation markers on inflammatory cells. Therefore, we found that it is of utmost importance to perform immune activation analysis as fast as possible to prevent drawing wrong conclusions. Automated flow cytometry is able to reduce this analysis from 2 h to only 15-20 min without the need of dedicated personnel and in a point-of-care context. This now allows fast and automated inflammation monitoring in blood samples obtained from a variety of patient groups. FUND: This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
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Affiliation(s)
- Roy Spijkerman
- Department of Trauma Surgery, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, the Netherlands; Laboratory of Translational Immunology (LTI) and Department of Respiratory Medicine, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, the Netherlands
| | - Lillian Hesselink
- Department of Trauma Surgery, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, the Netherlands; Laboratory of Translational Immunology (LTI) and Department of Respiratory Medicine, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, the Netherlands.
| | - Pien Hellebrekers
- Department of Trauma Surgery, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, the Netherlands; Laboratory of Translational Immunology (LTI) and Department of Respiratory Medicine, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, the Netherlands.
| | - Nienke Vrisekoop
- Laboratory of Translational Immunology (LTI) and Department of Respiratory Medicine, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, the Netherlands.
| | - Falco Hietbrink
- Department of Trauma Surgery, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, the Netherlands.
| | - Luke P H Leenen
- Department of Trauma Surgery, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, the Netherlands.
| | - Leo Koenderman
- Laboratory of Translational Immunology (LTI) and Department of Respiratory Medicine, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, the Netherlands.
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Ma J, Zhang B, Wang Y, Hou X, He L. Determination of flavor enhancers in milk powder by one-step sample preparation and two-dimensional liquid chromatography. J Sep Sci 2014; 37:920-6. [PMID: 24677676 DOI: 10.1002/jssc.201301367] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2013] [Revised: 02/05/2014] [Accepted: 02/05/2014] [Indexed: 11/06/2022]
Abstract
Maltol, ethyl maltol, vanillin, and ethyl vanillin are important food additives as flavor enhancers. To quantify the four additives in milk powder, a novel 2D liquid chromatographic (2DLC) method was developed in this article. In such a 2DLC system, the target fractions eluted from the first dimensional column (C4) are stored onto the trapping column (C8) for subsequent analysis; after that, they were switched into the second dimensional column (C18) by a two-position six-port switching valve. A one-step sample preparation method was used prior to 2DLC chromatographic analysis, which was easy and convenient. After optimization of all experimental parameters, the new method was validated in terms of linearity, LODs, and LOQs, intra- and interday precision, and accuracy. A conventional single-dimensional liquid chromatographic method was also proposed in this work for comparison. In order to evaluate the applicability of the new 2DLC method, five brands of commercial milk powder samples (n = 8) were analyzed. Vanillin and ethyl vanillin were detected in two samples, respectively. It is showed that the 2DLC method is effective in quality control programs of milk powder products.
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Affiliation(s)
- Jing Ma
- School of Medicine, Xi'an Jiaotong University, Xi'an, China
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