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2021 Volume 49 Issue 10
2021, 49(10): 1597-1606
doi: 10.19756/j.issn.0253-3820.210427
Abstract:
Glycosylation is an important post-translational modification of proteins. Modification by glycans makes the functions of proteins diverse. As one of the main glycosylation types of proteins, N-glycosylation is closely involved in many life activities and plays a critical role in the occurrence and development of diseases. Therefore, it is of great significance to study the N-glycans on glycoproteins. Mass spectrometry technology is one of the most powerful tools for studying N-glycome. However, due to the complex structure, low abundance and low ionization efficiency of glycans in mass spectrometry, the research of N-glycome based on mass spectrometry still faces great challenges. The separation and enrichment of N-glycans is essential for the analysis of N-glycans by mass spectrometry. This article briefly introduces the process of N-glycan analysis based on mass spectrometry, focusing on the overview of N-glycan separation and enrichment methods, and summarizes the advantages and disadvantages of these methods and discusses the application and contribution of these various technologies in biomedical research.
Glycosylation is an important post-translational modification of proteins. Modification by glycans makes the functions of proteins diverse. As one of the main glycosylation types of proteins, N-glycosylation is closely involved in many life activities and plays a critical role in the occurrence and development of diseases. Therefore, it is of great significance to study the N-glycans on glycoproteins. Mass spectrometry technology is one of the most powerful tools for studying N-glycome. However, due to the complex structure, low abundance and low ionization efficiency of glycans in mass spectrometry, the research of N-glycome based on mass spectrometry still faces great challenges. The separation and enrichment of N-glycans is essential for the analysis of N-glycans by mass spectrometry. This article briefly introduces the process of N-glycan analysis based on mass spectrometry, focusing on the overview of N-glycan separation and enrichment methods, and summarizes the advantages and disadvantages of these methods and discusses the application and contribution of these various technologies in biomedical research.
2021, 49(10): 1607-1618
doi: 10.19756/j.issn.0253-3820.210485
Abstract:
Electrospray ionization (ESI) is one of the most commonly used mass spectrometry ionization techniques for biomolecules at present. Biological macromolecules such as proteins can carry multiple charges and form multiply charged ions during ESI. The formation of multiply charged protein ions can effectively reduce the mass-to-charge ratio (m/z) of the ions to be measured, expand the range of molecular weights detectable and improve the detection sensitivity, which brings more convenience to mass spectrometry analysis of biological macromolecules. Recently, several methods have been proposed to further increase the charge of protein ions during ESI, and these methods has been called supercharging of proteins. In this paper, several methods for supercharging of proteins developed recently are systematically classified and summarized, the ionization mechanism and influencing factors of these methods are reviewed, and their applications are also introduced.
Electrospray ionization (ESI) is one of the most commonly used mass spectrometry ionization techniques for biomolecules at present. Biological macromolecules such as proteins can carry multiple charges and form multiply charged ions during ESI. The formation of multiply charged protein ions can effectively reduce the mass-to-charge ratio (m/z) of the ions to be measured, expand the range of molecular weights detectable and improve the detection sensitivity, which brings more convenience to mass spectrometry analysis of biological macromolecules. Recently, several methods have been proposed to further increase the charge of protein ions during ESI, and these methods has been called supercharging of proteins. In this paper, several methods for supercharging of proteins developed recently are systematically classified and summarized, the ionization mechanism and influencing factors of these methods are reviewed, and their applications are also introduced.
2021, 49(10): 1619-1630
doi: 10.19756/j.issn.0253-3820.210450
Abstract:
With the increasing demand for water environmental quality, the development of simple, sensitive and accurate detection technologies for water quality monitoring have become one of research focuses. Metal-organic frameworks (MOFs) are a class of porous coordination polymers self-assembled by metal ions/clusters and organic ligands. Due to the reversible adsorption, high catalytic activity, large surface area, adjustable and diverse structure, MOFs show great potential as optical/electrochemical sensing materials in water environmental detection. In this review, recent progresses in MOFs-based optical/electrochemical sensors are introduced, which focuses on colorimetric, fluorescence, chemiluminescence, electrochemical, electrochemiluminescence and photoelectrochemical sensors. Finally, this review looks forward the future development of MOFs-based optical/electrochemical sensors in water environmental detection.
With the increasing demand for water environmental quality, the development of simple, sensitive and accurate detection technologies for water quality monitoring have become one of research focuses. Metal-organic frameworks (MOFs) are a class of porous coordination polymers self-assembled by metal ions/clusters and organic ligands. Due to the reversible adsorption, high catalytic activity, large surface area, adjustable and diverse structure, MOFs show great potential as optical/electrochemical sensing materials in water environmental detection. In this review, recent progresses in MOFs-based optical/electrochemical sensors are introduced, which focuses on colorimetric, fluorescence, chemiluminescence, electrochemical, electrochemiluminescence and photoelectrochemical sensors. Finally, this review looks forward the future development of MOFs-based optical/electrochemical sensors in water environmental detection.
2021, 49(10): 1631-1639
doi: 10.19756/j.issn.0253-3820.211024
Abstract:
Food safety is a global health issue. The food-borne pathogens, such as Escherichia coli, Salmonella, Staphylococcus aureus, etc., are the main causes of food-borne diseases and food poisoning. The contamination of different foods (Like fruits, vegetables, meat and seafood) by the food-borne pathogens has threatened the food safety so long. The rapid detection of food-borne pathogens is critical to public health and food safety. However, traditional detection methods are mostly cumbersome and time-consuming, and are difficult to meet the needs of quick diagnosis and quick examination. Point-of-care testing (POCT) technology, as an emerging on-site rapid detection and analysis technology, shows many advantages such as simple operation, fast, portable and automated. POCT technology, as a food-borne pathogen detection method that has developed rapidly in recent years, provides a new way for low-cost, high-sensitivity and high-specificity detection of food-borne pathogens. At present, the technologies used in POCT are mainly divided into optical technologies and biosensor technologies, which are mainly based on immunological and biochemical reactions. This review reports the current research status of the application of POCT technology based on colorimetry, paper-based, microfluidic, electromagnetic sensing, and commercially available portable reading platforms in the detection of food-borne pathogens in recent years.
Food safety is a global health issue. The food-borne pathogens, such as Escherichia coli, Salmonella, Staphylococcus aureus, etc., are the main causes of food-borne diseases and food poisoning. The contamination of different foods (Like fruits, vegetables, meat and seafood) by the food-borne pathogens has threatened the food safety so long. The rapid detection of food-borne pathogens is critical to public health and food safety. However, traditional detection methods are mostly cumbersome and time-consuming, and are difficult to meet the needs of quick diagnosis and quick examination. Point-of-care testing (POCT) technology, as an emerging on-site rapid detection and analysis technology, shows many advantages such as simple operation, fast, portable and automated. POCT technology, as a food-borne pathogen detection method that has developed rapidly in recent years, provides a new way for low-cost, high-sensitivity and high-specificity detection of food-borne pathogens. At present, the technologies used in POCT are mainly divided into optical technologies and biosensor technologies, which are mainly based on immunological and biochemical reactions. This review reports the current research status of the application of POCT technology based on colorimetry, paper-based, microfluidic, electromagnetic sensing, and commercially available portable reading platforms in the detection of food-borne pathogens in recent years.
2021, 49(10): 1640-1648
doi: 10.19756/j.issn.0253-3820.210601
Abstract:
Real-time monitoring of blood glucose levels is of great significance for the diagnosis and treatment of diabetic patients. However, traditional enzymatic minimally invasive determinations have problems such as low stability and poor experience. By using silver nanowires as a template, high-quality Ag-Au bimetallic nanotubes (Ag-Au BMNTs/GCE) could be successfully prepared by a one-step Galvanic replacement reaction to realize the non-enzymatic and non-invasive measurement of glucose. By optimizing the content of HAuCl4, the morphology and composition of Ag-Au bimetallic nanotubes could be controlled. The research results showed that the Ag-Au BMNTs/GCE had a wide detection range for glucose detection (1 μmol/L-3.79 mmol/L, 3.79 mmol/L-13.79 mmol/L), high sensitivity (154.09 μA/(mmol/L), 60.77 μA/(mmol/L)) and low detection limit (1 μmol/L). At the same time, the sensor showed good anti-interference performance and stability, and was successfully applied to the accurate determination of glucose content in human sweat, which indicated that the electrochemical sensor based on Ag-Au BMNTs had potential application value in the field of non-enzyme and non-invasive blood glucose detection.
Real-time monitoring of blood glucose levels is of great significance for the diagnosis and treatment of diabetic patients. However, traditional enzymatic minimally invasive determinations have problems such as low stability and poor experience. By using silver nanowires as a template, high-quality Ag-Au bimetallic nanotubes (Ag-Au BMNTs/GCE) could be successfully prepared by a one-step Galvanic replacement reaction to realize the non-enzymatic and non-invasive measurement of glucose. By optimizing the content of HAuCl4, the morphology and composition of Ag-Au bimetallic nanotubes could be controlled. The research results showed that the Ag-Au BMNTs/GCE had a wide detection range for glucose detection (1 μmol/L-3.79 mmol/L, 3.79 mmol/L-13.79 mmol/L), high sensitivity (154.09 μA/(mmol/L), 60.77 μA/(mmol/L)) and low detection limit (1 μmol/L). At the same time, the sensor showed good anti-interference performance and stability, and was successfully applied to the accurate determination of glucose content in human sweat, which indicated that the electrochemical sensor based on Ag-Au BMNTs had potential application value in the field of non-enzyme and non-invasive blood glucose detection.
2021, 49(10): 1649-1656
doi: 10.19756/j.issn.0253-3820.201572
Abstract:
Coronary heart disease with hypertension (CHD-HTN) is a serious threat to the life and health of patients. In this study, the plasma samples of 51 healthy controls, 21 patients with coronary heart disease (CHD) and 16 patients with CHD-HTN were used as samples, and the ultra-performance liquid chromatography-high resolution mass spectrometer was used to analyze the plasma metabolic characteristics of the two types of patients. Among them, 104 endogenous metabolites were analyzed qualitatively and quantitatively. On this basis, principal component analysis and partial least square-discriminant analysis models were established, and combined with the results of variable importance projection and one-way analysis of variance, 8, 41 and 26 characteristic metabolites were selected to distinguish between healthy controls and patients with CHD, healthy controls and patients with CHD-HTN, patients with CHD and CHD-HTN. The results of metabolic pathway analysis showed that in patients with CHD and CHD-HTN, significant changes took place in the metabolic pathways of fatty acids such as linoleic acid, as well as the biosynthesis of amino acids such as phenylalanine, tyrosine and tryptophan. Among them, amino acid metabolism showed more significant changes in patients with CHD-HTN.
Coronary heart disease with hypertension (CHD-HTN) is a serious threat to the life and health of patients. In this study, the plasma samples of 51 healthy controls, 21 patients with coronary heart disease (CHD) and 16 patients with CHD-HTN were used as samples, and the ultra-performance liquid chromatography-high resolution mass spectrometer was used to analyze the plasma metabolic characteristics of the two types of patients. Among them, 104 endogenous metabolites were analyzed qualitatively and quantitatively. On this basis, principal component analysis and partial least square-discriminant analysis models were established, and combined with the results of variable importance projection and one-way analysis of variance, 8, 41 and 26 characteristic metabolites were selected to distinguish between healthy controls and patients with CHD, healthy controls and patients with CHD-HTN, patients with CHD and CHD-HTN. The results of metabolic pathway analysis showed that in patients with CHD and CHD-HTN, significant changes took place in the metabolic pathways of fatty acids such as linoleic acid, as well as the biosynthesis of amino acids such as phenylalanine, tyrosine and tryptophan. Among them, amino acid metabolism showed more significant changes in patients with CHD-HTN.
2021, 49(10): 1657-1665
doi: 10.19756/j.issn.0253-3820.210406
Abstract:
An in vitro blood-brain barrier (BBB) microfluidic chip was constructed to evaluate the transmittance of metal and metal nanoparticles. By combining with the "sandwich" blood-brain barrier model, the concentration gradient generation unit was integrated on the chip to realize permeability evaluation of metal-related components at different concentrations. bEnd.3 cells were employed as BBB model cells, and inductively coupled plasma-mass spectrometry (ICP-MS) was used to measure metal ions and metal nanoparticles trans-membrane and barrier absorption in the model in vitro. The mixing effect of the fluid in the chip channel was theoretically simulated by Comsol simulation software. The actual mixing effect was evaluated with samples including cadmium and Rhodamine B solution, and the reliability of the concentration gradient generation unit of the actual sample was evaluated by atomic absorption spectroscopy. In the barrier permeability evaluation experiment, the BBB permeability of sodium fluorescein was (5.45±0.48)×10-6 cm/s, which was basically consistent with the previous research. The chip could generate stable concentration generation, realize in vitro simulation of BBB organs and evaluation of metal permeability, which was expected to be used in the future in the central nervous system drug screening and metal, nanoparticle neurotoxicity assessment and other fields.
An in vitro blood-brain barrier (BBB) microfluidic chip was constructed to evaluate the transmittance of metal and metal nanoparticles. By combining with the "sandwich" blood-brain barrier model, the concentration gradient generation unit was integrated on the chip to realize permeability evaluation of metal-related components at different concentrations. bEnd.3 cells were employed as BBB model cells, and inductively coupled plasma-mass spectrometry (ICP-MS) was used to measure metal ions and metal nanoparticles trans-membrane and barrier absorption in the model in vitro. The mixing effect of the fluid in the chip channel was theoretically simulated by Comsol simulation software. The actual mixing effect was evaluated with samples including cadmium and Rhodamine B solution, and the reliability of the concentration gradient generation unit of the actual sample was evaluated by atomic absorption spectroscopy. In the barrier permeability evaluation experiment, the BBB permeability of sodium fluorescein was (5.45±0.48)×10-6 cm/s, which was basically consistent with the previous research. The chip could generate stable concentration generation, realize in vitro simulation of BBB organs and evaluation of metal permeability, which was expected to be used in the future in the central nervous system drug screening and metal, nanoparticle neurotoxicity assessment and other fields.
2021, 49(10): 1666-1677
doi: 10.19756/j.issn.0253-3820.210515
Abstract:
The micro-mixer is usually a pre-treatment device for laboratory chip (LOC). The study on the influence of mixing mechanism and structure on mixing can provide guides for design and processing of micromixers. In this work, the flow characteristics and mixing mechanism in the square wave micromixer were studied when the channel Re ynolds number was between 0.1 and 80, and the influence of channel structure on the flow and mixing performance of the fluid in the molecular diffusion dominant phase and the convection diffusion dominant phase was analyzed. The results showed that with the increase of Re in the channel, the fluid mixing transitions from molecular diffusion dominated to convection diffusion dominated stage. The factor that influenced the fluid mixing index during the dominant phase of molecular diffusion was the characteristic diffusion length. The channel width had a greater impact on the mixing index than the channel height. The reduction of the channel width could significantly increase the mixing index in the molecular diffusion phase. At Re=0.5, the mixing index was increased by 34.59% when the channel width was reduced from 400 μm to 200 μm. The factor affecting the mixing index in the dominant phase of convection diffusion was the magnitude and intensity of the vortex generated by the centrifugal force at the turn of the microchannel. The vortex of the square wave micromixer with square section had the most fully developed vortex and the best mixing performance. Reducing the size of the square section could increase the vortex strength. At Re=80, the mixing index of the micromixer with a channel section side length of 200 μm was 22.71% higher than the side length of 300 μm.
The micro-mixer is usually a pre-treatment device for laboratory chip (LOC). The study on the influence of mixing mechanism and structure on mixing can provide guides for design and processing of micromixers. In this work, the flow characteristics and mixing mechanism in the square wave micromixer were studied when the channel Re ynolds number was between 0.1 and 80, and the influence of channel structure on the flow and mixing performance of the fluid in the molecular diffusion dominant phase and the convection diffusion dominant phase was analyzed. The results showed that with the increase of Re in the channel, the fluid mixing transitions from molecular diffusion dominated to convection diffusion dominated stage. The factor that influenced the fluid mixing index during the dominant phase of molecular diffusion was the characteristic diffusion length. The channel width had a greater impact on the mixing index than the channel height. The reduction of the channel width could significantly increase the mixing index in the molecular diffusion phase. At Re=0.5, the mixing index was increased by 34.59% when the channel width was reduced from 400 μm to 200 μm. The factor affecting the mixing index in the dominant phase of convection diffusion was the magnitude and intensity of the vortex generated by the centrifugal force at the turn of the microchannel. The vortex of the square wave micromixer with square section had the most fully developed vortex and the best mixing performance. Reducing the size of the square section could increase the vortex strength. At Re=80, the mixing index of the micromixer with a channel section side length of 200 μm was 22.71% higher than the side length of 300 μm.
2021, 49(10): 1678-1685
doi: 10.19756/j.issn.0253-3820.210443
Abstract:
Liquid crystal (LC) droplets are promising for biosensor applications. However, the nonuniform size of LC droplets has limited their sensing performance. In this work, the generation of monodispersed LC droplets using a flow-focusing microfluidic chip was systematically investigated. With the nematic liquid crystal as the dispersed phase and sodium dodecyl sulfate aqueous/polyvinyl alcohol solution as the continuous phase, different flow patterns for the generation of LC droplet were studied. The effects of flow rates of the two phases, the viscosity of the continuous phase and the width of the orifice on the size of the generated LC droplets were also investigated. Finally, the size effect of the LC droplets on the sensing performance for deoxycholic acid (DCA), a potential biomarker of liver and intestinal diseases, was preliminarily explored. The results showed that the detection limit of LC droplets for DCA decreased from (383 ±23.6) μmol/L to (140 ±14.1) μmol/L when the diameter of LC droplets increased from 38 μm to 77 μm.
Liquid crystal (LC) droplets are promising for biosensor applications. However, the nonuniform size of LC droplets has limited their sensing performance. In this work, the generation of monodispersed LC droplets using a flow-focusing microfluidic chip was systematically investigated. With the nematic liquid crystal as the dispersed phase and sodium dodecyl sulfate aqueous/polyvinyl alcohol solution as the continuous phase, different flow patterns for the generation of LC droplet were studied. The effects of flow rates of the two phases, the viscosity of the continuous phase and the width of the orifice on the size of the generated LC droplets were also investigated. Finally, the size effect of the LC droplets on the sensing performance for deoxycholic acid (DCA), a potential biomarker of liver and intestinal diseases, was preliminarily explored. The results showed that the detection limit of LC droplets for DCA decreased from (383 ±23.6) μmol/L to (140 ±14.1) μmol/L when the diameter of LC droplets increased from 38 μm to 77 μm.
2021, 49(10): 1686-1693
doi: 10.19756/j.issn.0253-3820.210490
Abstract:
A novel direct analysis technology for solid samples using an atomic emission spectrometer based on microwave plasma called plasma jet atomic emission spectrometer (PJ-AES) was developed for the first time. In the work, PJ-AES was used for the rapid detection of cadmium (Cd), zinc (Zn), copper (Cu), iron (Fe), phosphorus (P), silicon (Si) and other inorganic elements in rice. The linear range, sensitivity, stability and other properties of the PJ-AES were systematically investigated. As a result, the linear range of heavy metal element Cd (228.80 nm) was 0.03-1.72 mg/kg, and the linear correlation coefficient (R2) was 0.998, the detection limit was 0.009 mg/kg. A total of 8 groups of rice standard samples with a Cd concentration of 0.22 mg/kg were detected, and the relative standard deviation (RSD) of the signal intensity at 228.80 nm (Cd) was 2.8%. Finally, the method was used for quantitative detection of Cd in real samples and the obtained results were compared with that of inductively coupled plasma mass spectrometry (ICP-MS). The results showed that the PJ-AES was suitable for rapid, accurate, qualitative and quantitative detection of Cd in rice. The development of this technology provided a new direct analysis and detection method for solid samples for atomic spectroscopy. This method showed many advantages such as fast analysis speed, simple sample processing, small size, low cost, and accurate detection.
A novel direct analysis technology for solid samples using an atomic emission spectrometer based on microwave plasma called plasma jet atomic emission spectrometer (PJ-AES) was developed for the first time. In the work, PJ-AES was used for the rapid detection of cadmium (Cd), zinc (Zn), copper (Cu), iron (Fe), phosphorus (P), silicon (Si) and other inorganic elements in rice. The linear range, sensitivity, stability and other properties of the PJ-AES were systematically investigated. As a result, the linear range of heavy metal element Cd (228.80 nm) was 0.03-1.72 mg/kg, and the linear correlation coefficient (R2) was 0.998, the detection limit was 0.009 mg/kg. A total of 8 groups of rice standard samples with a Cd concentration of 0.22 mg/kg were detected, and the relative standard deviation (RSD) of the signal intensity at 228.80 nm (Cd) was 2.8%. Finally, the method was used for quantitative detection of Cd in real samples and the obtained results were compared with that of inductively coupled plasma mass spectrometry (ICP-MS). The results showed that the PJ-AES was suitable for rapid, accurate, qualitative and quantitative detection of Cd in rice. The development of this technology provided a new direct analysis and detection method for solid samples for atomic spectroscopy. This method showed many advantages such as fast analysis speed, simple sample processing, small size, low cost, and accurate detection.
2021, 49(10): 1694-1703
doi: 10.19756/j.issn.0253-3820.211117
Abstract:
An in vitro detection method for active ricin based on depurination of a novel RNA substrate was developed with no adenine interference in the negative control sample. The problem that the substrate was prone to self-hydrolysis and caused false positive results in the traditional depurination activity detection method was solved. The depurination activities of single-stranded DNA and RNA substrates with the same sequence were systematically compared. It was found that RNA was more suitable as the substrate for detection of ricin depurination activity. The optimization of reaction conditions showed that the pH values, temperature, and concentration of RNA substrate were the key factors for detection of ricin depurination activity. Under the optimal conditions, there was no adenine interference in the negative control sample. The influence of RNA stem-loop composition on substrate activity was validated by screening a series of RNA substrates. A novel RNA substrate was obtained with the optimal depurination activity, and its depurination activity was twice that of the reported substrate. By combining with the immunocapture purification, a quantitative detection method for the active ricin by isotope-labeled internal liquid chromatography-triple quadrupole mass spectrometry with multiple reaction monitoring using the novel RNA as the depurination substrate was established. This method had good specificity, the linear range of active ricin ranged from 5.0 to 300 ng/mL, and the limit of detection was 1.0 ng/mL (S/N=3). This method was applied to the quantitative detection of active ricin in tap water, milk, and plasma samples. The recoveries of spiked samples were between 91.0% and 116.5%, and the relative standard deviations (RSDs) were between 3.2% and 9.3%. This method was helpful for the screening and identification of active ricin in the fields of food safety and chemical weapons inspection.
An in vitro detection method for active ricin based on depurination of a novel RNA substrate was developed with no adenine interference in the negative control sample. The problem that the substrate was prone to self-hydrolysis and caused false positive results in the traditional depurination activity detection method was solved. The depurination activities of single-stranded DNA and RNA substrates with the same sequence were systematically compared. It was found that RNA was more suitable as the substrate for detection of ricin depurination activity. The optimization of reaction conditions showed that the pH values, temperature, and concentration of RNA substrate were the key factors for detection of ricin depurination activity. Under the optimal conditions, there was no adenine interference in the negative control sample. The influence of RNA stem-loop composition on substrate activity was validated by screening a series of RNA substrates. A novel RNA substrate was obtained with the optimal depurination activity, and its depurination activity was twice that of the reported substrate. By combining with the immunocapture purification, a quantitative detection method for the active ricin by isotope-labeled internal liquid chromatography-triple quadrupole mass spectrometry with multiple reaction monitoring using the novel RNA as the depurination substrate was established. This method had good specificity, the linear range of active ricin ranged from 5.0 to 300 ng/mL, and the limit of detection was 1.0 ng/mL (S/N=3). This method was applied to the quantitative detection of active ricin in tap water, milk, and plasma samples. The recoveries of spiked samples were between 91.0% and 116.5%, and the relative standard deviations (RSDs) were between 3.2% and 9.3%. This method was helpful for the screening and identification of active ricin in the fields of food safety and chemical weapons inspection.
2021, 49(10): 1704-1712
doi: 10.19756/j.issn.0253-3820.211233
Abstract:
By using NO-recognizable o-diaminophenyl-substituted terpyridine derivative ligand 4-(4-[(2,2':6',2″-terpyridin)-4'-yl]phenoxy)benzene-1,2-diamine (TPBD) as the ligand, and β-diketone 6-(1',1″-diphenyl-4'-yl)-1,1,1,2,2,3,3-heptafluoro-4,6-hexanedione (DHH) as the coligand, a new β-diketonate-Eu3+ complex-based fluorescent probe,[Eu(DHH)3(TPBD)], was designed and synthesized for detection of NO, and its structure was characterized by mass spectrum and elemental analysis methods. The spectral results indicated that the probe[Eu(DHH)3(TPBD)] had only weak fluorescence, and its fluorescence intensity was increased by nearly 10 times after reacting with NO. The probe could be used to quantitatively detect NO at concentrations ranging from 0.017-0.83 μmol/L with a detection limit of 7.4 nmol/L. Meanwhile,[Eu(DHH)3(TPBD)] showed approximately no response to other common reactive oxygen/nitrogen species, which demonstrated the good NO sensitivity of the probe. The fluorescence imaging experiments proved that the probe[Eu(DHH)3(TPBD)] had low cytotoxicity and mitochondria targetability, and was successfully applied to the time-gated fluorescence imaging of NO in living cells and zebrafish.
By using NO-recognizable o-diaminophenyl-substituted terpyridine derivative ligand 4-(4-[(2,2':6',2″-terpyridin)-4'-yl]phenoxy)benzene-1,2-diamine (TPBD) as the ligand, and β-diketone 6-(1',1″-diphenyl-4'-yl)-1,1,1,2,2,3,3-heptafluoro-4,6-hexanedione (DHH) as the coligand, a new β-diketonate-Eu3+ complex-based fluorescent probe,[Eu(DHH)3(TPBD)], was designed and synthesized for detection of NO, and its structure was characterized by mass spectrum and elemental analysis methods. The spectral results indicated that the probe[Eu(DHH)3(TPBD)] had only weak fluorescence, and its fluorescence intensity was increased by nearly 10 times after reacting with NO. The probe could be used to quantitatively detect NO at concentrations ranging from 0.017-0.83 μmol/L with a detection limit of 7.4 nmol/L. Meanwhile,[Eu(DHH)3(TPBD)] showed approximately no response to other common reactive oxygen/nitrogen species, which demonstrated the good NO sensitivity of the probe. The fluorescence imaging experiments proved that the probe[Eu(DHH)3(TPBD)] had low cytotoxicity and mitochondria targetability, and was successfully applied to the time-gated fluorescence imaging of NO in living cells and zebrafish.
2021, 49(10): 1713-1721
doi: 10.19756/j.issn.0253-3820.211162
Abstract:
Matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) has become a promising analytical technology for large molecular weight molecules compounds, however, the interference of matrix-related ion peaks from the conventional matrix restricts the application of MALDI-MS in low molecular weight (LMW) organs (<500 Da). Although multiple exploration has been conducted in this region, it is still difficult to directly detect some molecules, such as low-molecular carbohydrate, which is a challenge to direct analysis without any enrichment because of its neutral property and difficulty in ionization. Herein, the in-situ Au nanoparticles (AuNPs) covalently embedded covalent organic frameworks (COFs) with sulfide cantilever (TTB-COF) were applied as a novel kind of matrix for direct analysis of various small organic molecules by MALDI-MS. The advantages of COFs such as abundant π-π periodic structure, suitable pore distribution, and increasing strong adsorption in the near UV region enable COFs be employed for various LMW organic analytes in cimprison with conventional matrix α-cyano-4-hydroxycinnamic acid (CHCA). Secondly, the addition of AuNPs not only facilitated the energy adsorption and desorption/ionization efficiency, but also provided an enrichment detection of sulfide molecules (LODs of thiabendazole as 5.0 nmol/L). Additionally, the synergistic effect between spatial confined COFs with sulfide cantilever and in-situ homogeneously distributed AuNPs solved the aggregation problem of inorganic nanoparticles during the evaporation preparation, which guaranteed the low background signals and improved the desorption/ionization efficiency. Therefore, after optimization of the synthetic conditions, Au-TTB-COF as a new matrix had an extremely low detection limit for small saccharides molecules as 11.0 nmol/L. Furthermore, Au-TTB-COF with strong salt tolerance and good reproducibility was applied to direct analysis of LMW molecules in the complex samples, such as glucose in serum samples, lactose in milk and thiabendazole in soft drinks. These results indicated that this metal-organic composites as MALDI-MS matrix had great potential in sensitive and specific detection of LMW organic chemicals in complex samples.
Matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) has become a promising analytical technology for large molecular weight molecules compounds, however, the interference of matrix-related ion peaks from the conventional matrix restricts the application of MALDI-MS in low molecular weight (LMW) organs (<500 Da). Although multiple exploration has been conducted in this region, it is still difficult to directly detect some molecules, such as low-molecular carbohydrate, which is a challenge to direct analysis without any enrichment because of its neutral property and difficulty in ionization. Herein, the in-situ Au nanoparticles (AuNPs) covalently embedded covalent organic frameworks (COFs) with sulfide cantilever (TTB-COF) were applied as a novel kind of matrix for direct analysis of various small organic molecules by MALDI-MS. The advantages of COFs such as abundant π-π periodic structure, suitable pore distribution, and increasing strong adsorption in the near UV region enable COFs be employed for various LMW organic analytes in cimprison with conventional matrix α-cyano-4-hydroxycinnamic acid (CHCA). Secondly, the addition of AuNPs not only facilitated the energy adsorption and desorption/ionization efficiency, but also provided an enrichment detection of sulfide molecules (LODs of thiabendazole as 5.0 nmol/L). Additionally, the synergistic effect between spatial confined COFs with sulfide cantilever and in-situ homogeneously distributed AuNPs solved the aggregation problem of inorganic nanoparticles during the evaporation preparation, which guaranteed the low background signals and improved the desorption/ionization efficiency. Therefore, after optimization of the synthetic conditions, Au-TTB-COF as a new matrix had an extremely low detection limit for small saccharides molecules as 11.0 nmol/L. Furthermore, Au-TTB-COF with strong salt tolerance and good reproducibility was applied to direct analysis of LMW molecules in the complex samples, such as glucose in serum samples, lactose in milk and thiabendazole in soft drinks. These results indicated that this metal-organic composites as MALDI-MS matrix had great potential in sensitive and specific detection of LMW organic chemicals in complex samples.
2021, 49(10): 1722-1732
doi: 10.19756/j.issn.0253-3820.210565
Abstract:
Ni-CuO/ITO electrode was prepared by sequential electrodeposition of Ni and CuO onto indium tin oxide (ITO) substrate. Scanning electron microscopy (SEM) demonstrated uniform distribution of Ni-CuO nanoflowers on the ITO substrate. X-ray diffraction (XRD) characterization showed that the Ni-CuO was mainly composed of Ni, NiSO4 and CuO. The electrochemical catalysis of different electrodes for ethanol (100 mmol/L) oxidation was studied in alkaline solution (1 mol/L KOH). ITO and CuO/ITO electrodes had negligible electrochemical activity, while the Ni-CuO electrode had high electrochemical activity, exhibiting oxidative peak current density of 20.90 mA/cm2, 1.7 times as high as that of the Ni/ITO. Furthermore, the electrochemical responses of the Ni-CuO electrode at different scan rates (20-100 mV/s) and toward different concentrations (10-500 mmol/L) of ethanol were inspected. By investigating the relationship between the amount of Ni and CuO deposition and the electrochemical catalysis of ethanol, the highest catalytic activity was achieved with potentiostatic Ni deposition for 300 s and CuO deposition for two cyclic voltammetry (CV) cycles. The Ni-CuO/ITO electrode retained 54.39% of its initial oxidative peak current density over a 10000-s stability test by chronoamperometry, exhibiting high long-term stability. A linear relationship was obtained between the oxidative peak current densities of the Ni-CuO/ITO electrode and the ethanol concentrations ranging from 0.1 mmol/L to 15 mmol/L, with an ethanol detection sensitivity of 150 μA/(cm2 (mmol/L)), a detection limit of 0.047 μmol/L (S/N=3) and recoveries of 95.2%-104.1%. In addition, excellent anti-interference was found when NaCl, KCl, disodium hydrogen phosphate, sorbic acid, and citric acid were added as interference species during the ethanol detection. These results suggested that the Ni-CuO/ITO electrode had potential practical applications in detection of ethanol.
Ni-CuO/ITO electrode was prepared by sequential electrodeposition of Ni and CuO onto indium tin oxide (ITO) substrate. Scanning electron microscopy (SEM) demonstrated uniform distribution of Ni-CuO nanoflowers on the ITO substrate. X-ray diffraction (XRD) characterization showed that the Ni-CuO was mainly composed of Ni, NiSO4 and CuO. The electrochemical catalysis of different electrodes for ethanol (100 mmol/L) oxidation was studied in alkaline solution (1 mol/L KOH). ITO and CuO/ITO electrodes had negligible electrochemical activity, while the Ni-CuO electrode had high electrochemical activity, exhibiting oxidative peak current density of 20.90 mA/cm2, 1.7 times as high as that of the Ni/ITO. Furthermore, the electrochemical responses of the Ni-CuO electrode at different scan rates (20-100 mV/s) and toward different concentrations (10-500 mmol/L) of ethanol were inspected. By investigating the relationship between the amount of Ni and CuO deposition and the electrochemical catalysis of ethanol, the highest catalytic activity was achieved with potentiostatic Ni deposition for 300 s and CuO deposition for two cyclic voltammetry (CV) cycles. The Ni-CuO/ITO electrode retained 54.39% of its initial oxidative peak current density over a 10000-s stability test by chronoamperometry, exhibiting high long-term stability. A linear relationship was obtained between the oxidative peak current densities of the Ni-CuO/ITO electrode and the ethanol concentrations ranging from 0.1 mmol/L to 15 mmol/L, with an ethanol detection sensitivity of 150 μA/(cm2 (mmol/L)), a detection limit of 0.047 μmol/L (S/N=3) and recoveries of 95.2%-104.1%. In addition, excellent anti-interference was found when NaCl, KCl, disodium hydrogen phosphate, sorbic acid, and citric acid were added as interference species during the ethanol detection. These results suggested that the Ni-CuO/ITO electrode had potential practical applications in detection of ethanol.
2021, 49(10): 1733-1742
doi: 10.19756/j.issn.0253-3820.211256
Abstract:
Sulfur mustard (SM) is a typically representative alkylating agent with high reactivity. SM can produce a variety of hydrolytic and oxidative metabolites including various proteins and nucleic acid adducts. Among them, divinyl sulfone (DVS) is an important oxidative metabolite that should be paid more attention, which has high reactivity and toxicity close to SM. In this study, the human serum albumin (HSA) and human plasma were exposed to DVS and its two-phase metabolite DVS-GSH, respectively. After digestion with proteinase K and purification by solid phase extraction (SPE), UPLC-Q-extractive orbitrap high rosolution mass spectrometry (HRMS) was used to identify some albumin adducts. According to the analysis results, three novel biomarkers, DVS-Cys-Pro-Phe, Phe-Pro-Cys-DVS-Cys-Pro-Phe and GSH-DVS-Cys-Pro-Phe, were successfully identified by UPLC-Q-exactive orbitrap/HRMS. The results showed that both DVS and DVS-GSH could react with Cys-34 of albumin due to their highly reactive alkene bonds. These novel damage biomarkers not only provided new clues for SM exposure and diagnosis, but also provided evidence for elucidating the damage mechanism of SM from a new perspective.
Sulfur mustard (SM) is a typically representative alkylating agent with high reactivity. SM can produce a variety of hydrolytic and oxidative metabolites including various proteins and nucleic acid adducts. Among them, divinyl sulfone (DVS) is an important oxidative metabolite that should be paid more attention, which has high reactivity and toxicity close to SM. In this study, the human serum albumin (HSA) and human plasma were exposed to DVS and its two-phase metabolite DVS-GSH, respectively. After digestion with proteinase K and purification by solid phase extraction (SPE), UPLC-Q-extractive orbitrap high rosolution mass spectrometry (HRMS) was used to identify some albumin adducts. According to the analysis results, three novel biomarkers, DVS-Cys-Pro-Phe, Phe-Pro-Cys-DVS-Cys-Pro-Phe and GSH-DVS-Cys-Pro-Phe, were successfully identified by UPLC-Q-exactive orbitrap/HRMS. The results showed that both DVS and DVS-GSH could react with Cys-34 of albumin due to their highly reactive alkene bonds. These novel damage biomarkers not only provided new clues for SM exposure and diagnosis, but also provided evidence for elucidating the damage mechanism of SM from a new perspective.
2021, 49(10): 1743-1749
doi: 10.19756/j.issn.0253-3820.210456
Abstract:
Near-infrared spectroscopy (NIRS) has been widely used in various fields such as food detection and quantitative analysis. As a key step in NIRS modeling and analysis, variable selection plays an important role in improving the stability and predictive performance of model. A new variable selection method for NIRS, variable frequency weighted bootstrap sampling (FWBS), was proposed in this work. Different variable subsets were generated by random combination of binary matrix sampling (BMS), and sub-models of different variable subsets were established by partial least squares (PLS). The frequency of each variable in the sub-model was counted and normalized to get the initial weight of the variable. Finally, the best characteristic variables were selected by weighted bootstrap sampling (WBS). Taking the public data base of NIRS spectroscopy of corn and milk as examples, the prediction models of starch content in corn and protein content in milk were established. The results showed that, comparing with uninformative variable elimination by PLS (UVE-PLS), competitive adapative reweighted sampling by PLS (CARS-PLS) and bootstrapping soft shrinkage by PLS (BOSS-PLS), the root mean square error of prediction (RMSEP) of the FWBS-PLS on the corn dataset decreased from 0.2523, 0.1162 and 0.0831 to 0.0740, respectively. The prediction accuracy increased by 70.7%, 36.3% and 11.0%, respectively. The relative percent deviation (RPD) of FWBS-PLS was 11.1328. The RMSEP on the milk dataset decreased from 0.1743, 0.1437 and 0.1432 to 0.0887, respectively. The prediction accuracy increased by 49.1%, 38.3% and 38.1%, respectively. The RPD of FWBS-PLS was 12.2701. The variable selection of NIRS based on FWBS could simplify model and improve the prediction accuracy of model greatly.
Near-infrared spectroscopy (NIRS) has been widely used in various fields such as food detection and quantitative analysis. As a key step in NIRS modeling and analysis, variable selection plays an important role in improving the stability and predictive performance of model. A new variable selection method for NIRS, variable frequency weighted bootstrap sampling (FWBS), was proposed in this work. Different variable subsets were generated by random combination of binary matrix sampling (BMS), and sub-models of different variable subsets were established by partial least squares (PLS). The frequency of each variable in the sub-model was counted and normalized to get the initial weight of the variable. Finally, the best characteristic variables were selected by weighted bootstrap sampling (WBS). Taking the public data base of NIRS spectroscopy of corn and milk as examples, the prediction models of starch content in corn and protein content in milk were established. The results showed that, comparing with uninformative variable elimination by PLS (UVE-PLS), competitive adapative reweighted sampling by PLS (CARS-PLS) and bootstrapping soft shrinkage by PLS (BOSS-PLS), the root mean square error of prediction (RMSEP) of the FWBS-PLS on the corn dataset decreased from 0.2523, 0.1162 and 0.0831 to 0.0740, respectively. The prediction accuracy increased by 70.7%, 36.3% and 11.0%, respectively. The relative percent deviation (RPD) of FWBS-PLS was 11.1328. The RMSEP on the milk dataset decreased from 0.1743, 0.1437 and 0.1432 to 0.0887, respectively. The prediction accuracy increased by 49.1%, 38.3% and 38.1%, respectively. The RPD of FWBS-PLS was 12.2701. The variable selection of NIRS based on FWBS could simplify model and improve the prediction accuracy of model greatly.
2021, 49(10): 1750-1757
doi: 10.19756/j.issn.0253-3820.211248
Abstract:
Thiol resin was used as an adsorbent to remove metal ions in organic photoresists. The thermodynamics and kinetics of the adsorption of Pd in photoresists were investigated extensively by inductively coupled plasma-mass spectrometry (ICP-MS). The adsorption data of Pd ion under different temperatures followed pseudo-second-order kinetic model, indicating that the adsorption process was controlled by chemical interactions of Pd and thiol groups. The results of isothermal adsorption were fitted well with Langmuir isothermal adsorption model, indicating that Pd in photoresist tended to adsorb monolayer on the surface of thiol resin. With the temperature increased, the maximum adsorption capacity of thiol resin for Pd increased from 12.68 mg/g to 17.49 mg/g, suggesting that appropriately increasing the adsorption temperature was helpful to improve the adsorption efficiency. The comprehensive purification results showed that thiol resin could be considered as a promising adsorbent for removal of Li, Na, Mg, Al, K, Ca, Cr, Mn, Fe, Ni, Cu, Zn, Pd and Sn ions in the photoresist. Most of the metal ions could be removed, with residual concentration down to 1.0 μg/L level. Compared with the Pall purification system, thiol resin was more effective for Pd purification, decreasing the content of Pd from 5.9 mg/L to 0.4 μg/L. However, for abundant metal ions such as Na and Ca with reducing limitation to 11.8 μg/L and 13.0 μg/L, respectively, the purification needs to be further optimized.
Thiol resin was used as an adsorbent to remove metal ions in organic photoresists. The thermodynamics and kinetics of the adsorption of Pd in photoresists were investigated extensively by inductively coupled plasma-mass spectrometry (ICP-MS). The adsorption data of Pd ion under different temperatures followed pseudo-second-order kinetic model, indicating that the adsorption process was controlled by chemical interactions of Pd and thiol groups. The results of isothermal adsorption were fitted well with Langmuir isothermal adsorption model, indicating that Pd in photoresist tended to adsorb monolayer on the surface of thiol resin. With the temperature increased, the maximum adsorption capacity of thiol resin for Pd increased from 12.68 mg/g to 17.49 mg/g, suggesting that appropriately increasing the adsorption temperature was helpful to improve the adsorption efficiency. The comprehensive purification results showed that thiol resin could be considered as a promising adsorbent for removal of Li, Na, Mg, Al, K, Ca, Cr, Mn, Fe, Ni, Cu, Zn, Pd and Sn ions in the photoresist. Most of the metal ions could be removed, with residual concentration down to 1.0 μg/L level. Compared with the Pall purification system, thiol resin was more effective for Pd purification, decreasing the content of Pd from 5.9 mg/L to 0.4 μg/L. However, for abundant metal ions such as Na and Ca with reducing limitation to 11.8 μg/L and 13.0 μg/L, respectively, the purification needs to be further optimized.
2021, 49(10): 1758-1765
doi: 10.19756/j.issn.0253-3820.211033
Abstract:
The transfer performance of near infrared (NIR) spectrometry quantitative analysis model for methanol gasoline was studied based on piecewise direct standardization (PDS) algorithm. First, in the experimental environment, 20 methanol gasoline samples were prepared and their NIR spectra were collected. Secondly, the influence of different NIR wave ranges as input variables on the prediction performance of the model was explored. Thirdly, the effects of different spectral pretreatment methods on the NIR spectra were investigated. Based on the spectral data preprocessed by normalization (Nor) and multiple scattering correction (MSC), the initial PLS calibration model and PDS-PLS transfer model were constructed. Finally, to further verify the prediction performance of PDS-PLS model, PLS model based on original spectrum, domain adaptive (DA) and kernel domain adaptive (KDA) were constructed. The results showed that, compared with other PLS models, the model constructed by PDS-PLS calibration model had a significant improvement on the prediction performance. The coefficient of determination of prediction set (RP2) was 0.9984, the root mean square error of prediction set (RMSEP) was 0.0056, and the mean relative error (MREP) was 4.36%. The results showed that PDS-PLS was a simple and efficient model transfer method for NIR quantitative analysis of methanol gasoline.
The transfer performance of near infrared (NIR) spectrometry quantitative analysis model for methanol gasoline was studied based on piecewise direct standardization (PDS) algorithm. First, in the experimental environment, 20 methanol gasoline samples were prepared and their NIR spectra were collected. Secondly, the influence of different NIR wave ranges as input variables on the prediction performance of the model was explored. Thirdly, the effects of different spectral pretreatment methods on the NIR spectra were investigated. Based on the spectral data preprocessed by normalization (Nor) and multiple scattering correction (MSC), the initial PLS calibration model and PDS-PLS transfer model were constructed. Finally, to further verify the prediction performance of PDS-PLS model, PLS model based on original spectrum, domain adaptive (DA) and kernel domain adaptive (KDA) were constructed. The results showed that, compared with other PLS models, the model constructed by PDS-PLS calibration model had a significant improvement on the prediction performance. The coefficient of determination of prediction set (RP2) was 0.9984, the root mean square error of prediction set (RMSEP) was 0.0056, and the mean relative error (MREP) was 4.36%. The results showed that PDS-PLS was a simple and efficient model transfer method for NIR quantitative analysis of methanol gasoline.
