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2022 Volume 50 Issue 10
2022, 50(10): 1435-1443
doi: 10.19756/j.issn.0253-3820.221363
Abstract:
Hypercrosslinked polymers (HCPs) are a kind of porous organic polymers built from aromatic compounds via Friedel-Crafts acylation. Due to their excellent chemical stability, extremely high specific surface area, adjustable pore size, simple synthesis condition and easy functionalization, HCPs have shown great potential in sample pretreatment and chromatographic separation. In this article, the application and progress of HCPs in solid phase extraction (SPE), magnetic solid phase extraction (MSPE), solid phase microextraction (SPME), high performance liquid chromatography (HPLC) and gas chromatography (GC) are systematically reviewed. In the end, the outlook about the application of HCPs in separation science is prospected.
Hypercrosslinked polymers (HCPs) are a kind of porous organic polymers built from aromatic compounds via Friedel-Crafts acylation. Due to their excellent chemical stability, extremely high specific surface area, adjustable pore size, simple synthesis condition and easy functionalization, HCPs have shown great potential in sample pretreatment and chromatographic separation. In this article, the application and progress of HCPs in solid phase extraction (SPE), magnetic solid phase extraction (MSPE), solid phase microextraction (SPME), high performance liquid chromatography (HPLC) and gas chromatography (GC) are systematically reviewed. In the end, the outlook about the application of HCPs in separation science is prospected.
2022, 50(10): 1444-1455
doi: 10.19756/j.issn.0253-3820.221292
Abstract:
Quinolones, as a kind of broad-spectrum antibacterial antibiotics synthesized artificially, have been widely used in food production and processing. It is believed that quinolones, unscientific overuse or abuse can pose a major threat to human health and has long-term potential harm to food safety even the whole ecosystem through the food chain. In this review, the research advances of detection methods (including high performance liquid chromatography, high performance liquid chromatography-mass spectrometry, capillary electrophoresis and other non-chromatography detection technology) for quinolones residues in foods in recent years were introduced, and the broaden application scope in food detection, development and utilization of new pretreatment methods, selection and optimization of various purification fillers and how to reduce the interference of matrix effect were summarized. The challenges and prospect of the detection techniques for quinolones were also discussed.
Quinolones, as a kind of broad-spectrum antibacterial antibiotics synthesized artificially, have been widely used in food production and processing. It is believed that quinolones, unscientific overuse or abuse can pose a major threat to human health and has long-term potential harm to food safety even the whole ecosystem through the food chain. In this review, the research advances of detection methods (including high performance liquid chromatography, high performance liquid chromatography-mass spectrometry, capillary electrophoresis and other non-chromatography detection technology) for quinolones residues in foods in recent years were introduced, and the broaden application scope in food detection, development and utilization of new pretreatment methods, selection and optimization of various purification fillers and how to reduce the interference of matrix effect were summarized. The challenges and prospect of the detection techniques for quinolones were also discussed.
2022, 50(10): 1456-1464
doi: 10.19756/j.issn.0253-3820.221209
Abstract:
Atmospheric benzene series have high photochemical reactivity and biological toxicity, and have been one of the most important atmospheric volatile organic pollutants. However, their low concentration and rapid temporal and spatial changes make real-time and accurate quantitative monitoring extremely challenging. Vacuum ultraviolet photoionization (VUV-PI) mass spectrometry is a commonly used analytical method for online monitoring of benzene series, but the currently commonly used VUV-PI ionization source cannot effectively utilize the generated ions, which restricts the further improvement of sensitivity. In this study, a novel ion funnel focused photoionization time-of-flight mass spectrometer (IFPI-TOFMS) was developed. By introducing a radio frequency ion funnel into the photoionization source, the ion transmission efficiency in the source was increased by 26-37 times, and the limits of detection (LODs) of IFPI-TOFMS for isoprene, benzene, toluene, styrene, p-xylene, trimethylbenzene, and limonene reached 34.3×10-12, 7.9×10-12, 7.0×10-12, 9.4×10-12, 7.7×10-12, 10.6×10-12 and 13.7×10-12(V/V) within 5 s, respectively. Linear range of 2-3 orders of magnitude were achieved with the linear correlation coefficients (R2) greater than 0.99. The relative standard deviation (RSD) during 12 h monitoring was less than 3%, which exhibited good stability of IFPI-TOFMS. IFPI-TOFMS was utilized to carry out real-time online monitoring of atmospheric benzene series in Dalian urban area. The results showed that benzene series in the atmosphere down to 10-12 (V/V) could be quantitatively monitored in real-time and online by IFPI-TOFMS, which indicated that IFPI-TOFMS had potential application value and broad development prospects in the field of atmospheric environment monitoring.
Atmospheric benzene series have high photochemical reactivity and biological toxicity, and have been one of the most important atmospheric volatile organic pollutants. However, their low concentration and rapid temporal and spatial changes make real-time and accurate quantitative monitoring extremely challenging. Vacuum ultraviolet photoionization (VUV-PI) mass spectrometry is a commonly used analytical method for online monitoring of benzene series, but the currently commonly used VUV-PI ionization source cannot effectively utilize the generated ions, which restricts the further improvement of sensitivity. In this study, a novel ion funnel focused photoionization time-of-flight mass spectrometer (IFPI-TOFMS) was developed. By introducing a radio frequency ion funnel into the photoionization source, the ion transmission efficiency in the source was increased by 26-37 times, and the limits of detection (LODs) of IFPI-TOFMS for isoprene, benzene, toluene, styrene, p-xylene, trimethylbenzene, and limonene reached 34.3×10-12, 7.9×10-12, 7.0×10-12, 9.4×10-12, 7.7×10-12, 10.6×10-12 and 13.7×10-12(V/V) within 5 s, respectively. Linear range of 2-3 orders of magnitude were achieved with the linear correlation coefficients (R2) greater than 0.99. The relative standard deviation (RSD) during 12 h monitoring was less than 3%, which exhibited good stability of IFPI-TOFMS. IFPI-TOFMS was utilized to carry out real-time online monitoring of atmospheric benzene series in Dalian urban area. The results showed that benzene series in the atmosphere down to 10-12 (V/V) could be quantitatively monitored in real-time and online by IFPI-TOFMS, which indicated that IFPI-TOFMS had potential application value and broad development prospects in the field of atmospheric environment monitoring.
2022, 50(10): 1465-1472
doi: 10.19756/j.issn.0253-3820.221414
Abstract:
Protein palmitoylation plays important roles in the occurrence, development and metastasis of colon cancer. In this study, acyl biotinyl exchange (ABE) method was improved and used to enrich palmitoylated proteins in colorectal cancer tissues. The enriched proteins were identified by proteomics approaches. A total of 213 highly reliable palmitoylated proteins(+HA/-HA>3) were identified, including enolase 1, peroxide oxidoreductase, vimentin, mitochondrial malate dehydrogenase, nuclear heterogeneous ribonucleoprotein K, and chaperone complex protein 1. The palmitoylation modification of enolase 1 was verified by Western blot analysis. The present study improved the classical ABE method to reduce its non-specific background. The detection results of palmitoylated proteins in colon cancer tissues could provide a new idea for further studying the molecular mechanism of palmitoylation of specific tumor related proteins and accurately discovering tumor markers or molecular targets of colon cancer.
Protein palmitoylation plays important roles in the occurrence, development and metastasis of colon cancer. In this study, acyl biotinyl exchange (ABE) method was improved and used to enrich palmitoylated proteins in colorectal cancer tissues. The enriched proteins were identified by proteomics approaches. A total of 213 highly reliable palmitoylated proteins(+HA/-HA>3) were identified, including enolase 1, peroxide oxidoreductase, vimentin, mitochondrial malate dehydrogenase, nuclear heterogeneous ribonucleoprotein K, and chaperone complex protein 1. The palmitoylation modification of enolase 1 was verified by Western blot analysis. The present study improved the classical ABE method to reduce its non-specific background. The detection results of palmitoylated proteins in colon cancer tissues could provide a new idea for further studying the molecular mechanism of palmitoylation of specific tumor related proteins and accurately discovering tumor markers or molecular targets of colon cancer.
2022, 50(10): 1473-1481
doi: 10.19756/j.issn.0253-3820.221180
Abstract:
A label-free visualized lead ion biosensor was constructed based on G-quadruplex-hemin DNAzyme-mediated etching of gold nanorods (AuNRs). Hemin could induce the transformation of the aptamer PS2.M into a G-quadruplex structure to generate a G-quadruplex-hemin DNAzyme with peroxidase-like activity. 3,3',5,5'-Tetramethylbenzidine (TMB) was oxidized to form a blue diimine derivative TMB+, and the enzymatic reaction was terminated after adding H2SO4, and TMB+ became TMB2+ (yellow). Under the action of hexadecyl trimethyl ammonium bromide (CTAB), TMB2+ could effectively oxidize Au(0) to Au(I), thereby realizing the etching of AuNRs, and the solution turned yellow. Due to the highly specific interaction between PS2.M and Pb2+, and the ability of Pb2+ to stabilize G-quadruplexes was significantly stronger than that of hemin, G-quadruplexes-hemin DNAzyme with enzyme-like activity could not be formed in the presence of Pb2+, thus unable to etch AuNRs. Therefore, different concentrations of Pb2+ made the solutions produce distinct color changes that could be easily identified with naked eyes. The ratiometric quantitative detection of Pb2+ was achieved by measuring the absorbance of the longitudinal surface plasmon absorption peak of AuNRs and the TMB+ absorption peak at 450 nm, with a linear range of 5-5000 nmol/L and a detection limit as low as 2.0 nmol/L. The method was successfully applied to detection of Pb2+ in Songhua River water and tap water samples, with spiked recoveries were 98.7%-102.5% and 94.8%-108.2%, respectively, and the results were consistent with the detection results of inductively coupled plasma-mass spectrometry (ICP-MS). The method ingeniously designed the nucleic acid sequence, and realized the rapid and high-sensitivity visual detection of Pb2+.
A label-free visualized lead ion biosensor was constructed based on G-quadruplex-hemin DNAzyme-mediated etching of gold nanorods (AuNRs). Hemin could induce the transformation of the aptamer PS2.M into a G-quadruplex structure to generate a G-quadruplex-hemin DNAzyme with peroxidase-like activity. 3,3',5,5'-Tetramethylbenzidine (TMB) was oxidized to form a blue diimine derivative TMB+, and the enzymatic reaction was terminated after adding H2SO4, and TMB+ became TMB2+ (yellow). Under the action of hexadecyl trimethyl ammonium bromide (CTAB), TMB2+ could effectively oxidize Au(0) to Au(I), thereby realizing the etching of AuNRs, and the solution turned yellow. Due to the highly specific interaction between PS2.M and Pb2+, and the ability of Pb2+ to stabilize G-quadruplexes was significantly stronger than that of hemin, G-quadruplexes-hemin DNAzyme with enzyme-like activity could not be formed in the presence of Pb2+, thus unable to etch AuNRs. Therefore, different concentrations of Pb2+ made the solutions produce distinct color changes that could be easily identified with naked eyes. The ratiometric quantitative detection of Pb2+ was achieved by measuring the absorbance of the longitudinal surface plasmon absorption peak of AuNRs and the TMB+ absorption peak at 450 nm, with a linear range of 5-5000 nmol/L and a detection limit as low as 2.0 nmol/L. The method was successfully applied to detection of Pb2+ in Songhua River water and tap water samples, with spiked recoveries were 98.7%-102.5% and 94.8%-108.2%, respectively, and the results were consistent with the detection results of inductively coupled plasma-mass spectrometry (ICP-MS). The method ingeniously designed the nucleic acid sequence, and realized the rapid and high-sensitivity visual detection of Pb2+.
2022, 50(10): 1482-1490
doi: 10.19756/j.issn.0253-3820.221119
Abstract:
A rapid, simple and ultra-sensitive detection method for H1N1 influenza A virus (IAV) was developed based on aptamers and rolling circle amplification technique. Ten candidate aptamers of H1N1 IAV were screened by magnetic bead-systematic evolution of ligands by exponential enrichment (SELEX) technique, cloned, sequenced and combined repeat sequence. The binding force, specificity and affinity of aptamers were characterized by dot blot hybridization and enzyme linked immunosorbent assay (ELISA), and two linear aptamers Apt2 and Apt6 with good specificity and high affinity were obtained. H1N1 A influenza virus was captured and enriched by linear Apt2 modified on the surface of magnetic nanospheres. Then H1N1 IAV was combined with the circular aptamer CApt6, which was used as a template for rolling circle amplification (RCA). The detection results were displayed by gold nanoparticles visualization method. The results showed that the detection limit of H1N1 virus was 100.0 copies/μL. This work provided a new idea for development of ultra-sensitive and rapid method for detection of virus.
A rapid, simple and ultra-sensitive detection method for H1N1 influenza A virus (IAV) was developed based on aptamers and rolling circle amplification technique. Ten candidate aptamers of H1N1 IAV were screened by magnetic bead-systematic evolution of ligands by exponential enrichment (SELEX) technique, cloned, sequenced and combined repeat sequence. The binding force, specificity and affinity of aptamers were characterized by dot blot hybridization and enzyme linked immunosorbent assay (ELISA), and two linear aptamers Apt2 and Apt6 with good specificity and high affinity were obtained. H1N1 A influenza virus was captured and enriched by linear Apt2 modified on the surface of magnetic nanospheres. Then H1N1 IAV was combined with the circular aptamer CApt6, which was used as a template for rolling circle amplification (RCA). The detection results were displayed by gold nanoparticles visualization method. The results showed that the detection limit of H1N1 virus was 100.0 copies/μL. This work provided a new idea for development of ultra-sensitive and rapid method for detection of virus.
2022, 50(10): 1491-1501
doi: 10.19756/j.issn.0253-3820.221137
Abstract:
Molybdenum disulfide nanosheets (MoS2 NSs) were prepared by a simple one-step hydrothermal method, and their structure and morphology were characterized by X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS) and transmission electron microscope (TEM). In the presence of hydrogen peroxide (H2O2), the obtained MoS2 NSs could catalyze the oxidation of colorless 3,3',5,5'-tetramethylbenzidine (TMB) into blue oxidized products (oxTMB). On this basis, a colorimetric analysis method for determination of H2O2 concentration was established. The effects of color reaction conditions of MoS2 NSs-TMB-H2O2 on peroxidase-like activity of MoS2 NSs were investigated, and the steady-state kinetic analysis was carried out. The results showed that the enzymatic reaction of MoS2 NSs using TMB and H2O2 as reaction substrates followed the typical Michaelis-Menten kinetic model. The linear range for colorimetric determination of H2O2 was 10-50 μmol/L, with a limit of detection (LOD, S/N=3) of 1.0 μmol/L. The established method was used in detection of H2O2 in milk samples and the recoveries of H2O2 spiked in milk were 92.4%-106.9%, showing good practicability.
Molybdenum disulfide nanosheets (MoS2 NSs) were prepared by a simple one-step hydrothermal method, and their structure and morphology were characterized by X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS) and transmission electron microscope (TEM). In the presence of hydrogen peroxide (H2O2), the obtained MoS2 NSs could catalyze the oxidation of colorless 3,3',5,5'-tetramethylbenzidine (TMB) into blue oxidized products (oxTMB). On this basis, a colorimetric analysis method for determination of H2O2 concentration was established. The effects of color reaction conditions of MoS2 NSs-TMB-H2O2 on peroxidase-like activity of MoS2 NSs were investigated, and the steady-state kinetic analysis was carried out. The results showed that the enzymatic reaction of MoS2 NSs using TMB and H2O2 as reaction substrates followed the typical Michaelis-Menten kinetic model. The linear range for colorimetric determination of H2O2 was 10-50 μmol/L, with a limit of detection (LOD, S/N=3) of 1.0 μmol/L. The established method was used in detection of H2O2 in milk samples and the recoveries of H2O2 spiked in milk were 92.4%-106.9%, showing good practicability.
2022, 50(10): 1502-1510
doi: 10.19756/j.issn.0253-3820.221270
Abstract:
Fluorescent probes have attracted a lot of attention because of their high accuracy and rapid visualization of heavy metals. Carbon nitride dots show potential applications in ion detection, due to their metal-free, water solubility, low toxicity, ease of preparation and high quantum yield. In this work, a carbon nitride dot fluorescent probe was prepared using ethanediamine and CCl4, and Cu2+ could burst the fluorescence of the probe, based on which a Cu2+ fluorescence detection method was established. The linear detection range was 2.0-10.0 μmol/L, and the detection limit (S/N=3) was as low as 0.058 μmol/L. When this probe was used for the determination of Cu2+ in tap water, lake and wastewater, the recoveries were in the range of 91.5%-105.3%, indicating the practicality of this method. The fluorescence test paper constructed based on carbon nitride dots with a detection limit as low as 0.5 μmol/L provided an alternative solution for the real-time detection of Cu2+ in the field.
Fluorescent probes have attracted a lot of attention because of their high accuracy and rapid visualization of heavy metals. Carbon nitride dots show potential applications in ion detection, due to their metal-free, water solubility, low toxicity, ease of preparation and high quantum yield. In this work, a carbon nitride dot fluorescent probe was prepared using ethanediamine and CCl4, and Cu2+ could burst the fluorescence of the probe, based on which a Cu2+ fluorescence detection method was established. The linear detection range was 2.0-10.0 μmol/L, and the detection limit (S/N=3) was as low as 0.058 μmol/L. When this probe was used for the determination of Cu2+ in tap water, lake and wastewater, the recoveries were in the range of 91.5%-105.3%, indicating the practicality of this method. The fluorescence test paper constructed based on carbon nitride dots with a detection limit as low as 0.5 μmol/L provided an alternative solution for the real-time detection of Cu2+ in the field.
2022, 50(10): 1511-1519
doi: 10.19756/j.issn.0253-3820.221303
Abstract:
The release of silver nanoparticles (AgNPs) in four kinds of polyethylene antibacterial food packaging materials were evaluated via single particle-inductively coupled plasma-mass spectrometry (SP-ICP-MS). The iterative algorithm was used to distinguish the signals produced by nano-silver signal and ionic silver (Ag+) in samples, and the effects of food simulants (ultrapure water, ethanol (10%) and acetic acid (3%)), temperature and storage time on the migration of AgNPs and Ag+were investigated. The results showed that the contents of total silver in the four kinds of antibacterial food packaging materials were 1.53-125 μg/g, the release of Ag+ and AgNPs was found in the four polyethylene food packaging materials, and low temperature conditions could reduce the migration of silver. Acidic media and media with high organic solvent were conducive to the release of Ag+ but had no significant effect on AgNPs, and the release of AgNPs accounted for 0.3%-6.1% of total silver, mainly distributed below 50 nm. This approach provided a method for accurately evaluating the migration of nanoparticles in food packaging materials.
The release of silver nanoparticles (AgNPs) in four kinds of polyethylene antibacterial food packaging materials were evaluated via single particle-inductively coupled plasma-mass spectrometry (SP-ICP-MS). The iterative algorithm was used to distinguish the signals produced by nano-silver signal and ionic silver (Ag+) in samples, and the effects of food simulants (ultrapure water, ethanol (10%) and acetic acid (3%)), temperature and storage time on the migration of AgNPs and Ag+were investigated. The results showed that the contents of total silver in the four kinds of antibacterial food packaging materials were 1.53-125 μg/g, the release of Ag+ and AgNPs was found in the four polyethylene food packaging materials, and low temperature conditions could reduce the migration of silver. Acidic media and media with high organic solvent were conducive to the release of Ag+ but had no significant effect on AgNPs, and the release of AgNPs accounted for 0.3%-6.1% of total silver, mainly distributed below 50 nm. This approach provided a method for accurately evaluating the migration of nanoparticles in food packaging materials.
2022, 50(10): 1520-1532
doi: 10.19756/j.issn.0253-3820.221286
Abstract:
Biomimetic chitosan hydrogels (CS-GNPs) with controllable physical and chemical properties for inducing periodontal tissue regeneration were prepared by performing a nucleophilic substitution reaction on the ester group of the natural protein crosslinker genipine (GNP) with polyglucine (1-4)-2-amino-β-D glucose (chitosan, CS) as the matrix under acidic conditions. The structure and morphology of the materials were characterized, and the mechanical properties, porosity, swelling rate, and degradation rate of the material were detected. The cytotoxicities of the materials were evaluated by the viability detection of mice fibroblasts (L-929) in vitro. The effects of the materials on the biological behavior of pluripotent stem cells were analyzed by observing the proliferation rate of periodontal ligament stem cells (hPDLSCs) and detecting mRNA expression levels of periodontal ligament-related genes PLAP-1, COL1, SCX and POSTN by qPCR. The experimental results showed that CS-GNP with different physicochemical characteristics could be obtained by changing the ratio of GNP. The mechanical signals of the materials affected the biological behaviors of pluripotent stem cells and changing the elastic modulus of the materials could regulate the extension area and proliferation rates of stem cells. When the material's modulus of elasticity was (46.02±15.7) kPa, which was close to the normal periodontal ligament extracellular matrix, the differentiation of hPDLSCs could be induced to the direction of the periodontal ligament. The results verified that the physical signals of the stem cell microenvironment could regulate the fate and differentiation of cells, and the simulation of natural extracellular matrix hardness could greatly regulate the directional differentiation of pluripotent stem cells, providing feasible model materials and systems for analyzing and characterizing the influence of the cell microenvironment on stem cell behavior.
Biomimetic chitosan hydrogels (CS-GNPs) with controllable physical and chemical properties for inducing periodontal tissue regeneration were prepared by performing a nucleophilic substitution reaction on the ester group of the natural protein crosslinker genipine (GNP) with polyglucine (1-4)-2-amino-β-D glucose (chitosan, CS) as the matrix under acidic conditions. The structure and morphology of the materials were characterized, and the mechanical properties, porosity, swelling rate, and degradation rate of the material were detected. The cytotoxicities of the materials were evaluated by the viability detection of mice fibroblasts (L-929) in vitro. The effects of the materials on the biological behavior of pluripotent stem cells were analyzed by observing the proliferation rate of periodontal ligament stem cells (hPDLSCs) and detecting mRNA expression levels of periodontal ligament-related genes PLAP-1, COL1, SCX and POSTN by qPCR. The experimental results showed that CS-GNP with different physicochemical characteristics could be obtained by changing the ratio of GNP. The mechanical signals of the materials affected the biological behaviors of pluripotent stem cells and changing the elastic modulus of the materials could regulate the extension area and proliferation rates of stem cells. When the material's modulus of elasticity was (46.02±15.7) kPa, which was close to the normal periodontal ligament extracellular matrix, the differentiation of hPDLSCs could be induced to the direction of the periodontal ligament. The results verified that the physical signals of the stem cell microenvironment could regulate the fate and differentiation of cells, and the simulation of natural extracellular matrix hardness could greatly regulate the directional differentiation of pluripotent stem cells, providing feasible model materials and systems for analyzing and characterizing the influence of the cell microenvironment on stem cell behavior.
2022, 50(10): 1533-1541
doi: 10.19756/j.issn.0253-3820.221073
Abstract:
The distribution of small molecular neurochemicals and their metabolites in rat brain was analyzed by desorption electrospray ionization time-of-flight mass spectrometry imaging (DESI-TOF-MSI) technique. The whole brain frozen horizontal sections of rats were prepared and scanned by DESI-TOF-MSI imaging. The influences of composition and proportion of spray solvents on the signal intensity of neurochemicals under positive and negative ion modes were also investigated. By comparison of high resolution mass spectrometry information in positive and negative ion mode and HMDB database searching, 25 kinds of neurochemicals and their metabolites were detected in rat brain. Under the condition of 0.1% formic acid-methanol spray, the molecular ion intensity of neurochemicals was increased mostly. HDImaging v1.5 was used for fine imaging analysis. Addition of 0.1% formic acid to the spray solvent could improve the imaging effect similar to the increasing trend of mass signal intensity. The method presented high repeatability. γ-Aminobutyric acid and aspartic acid were mainly distributed in cerebral cortex. Serine was detected throughout the brain. Glutamine was distributed around the hippocampus. The same spatial distribution of neurochemicals and their precursors and major metabolites in the brain was detected. The DESI-TOF-MSI technique developed here could be used to analyze the distribution of small molecular neurochemicals in rat brain. This work provided a fast and effective visualization method for the study of spatial distribution and metabolism of small molecule neurochemicals in brain.
The distribution of small molecular neurochemicals and their metabolites in rat brain was analyzed by desorption electrospray ionization time-of-flight mass spectrometry imaging (DESI-TOF-MSI) technique. The whole brain frozen horizontal sections of rats were prepared and scanned by DESI-TOF-MSI imaging. The influences of composition and proportion of spray solvents on the signal intensity of neurochemicals under positive and negative ion modes were also investigated. By comparison of high resolution mass spectrometry information in positive and negative ion mode and HMDB database searching, 25 kinds of neurochemicals and their metabolites were detected in rat brain. Under the condition of 0.1% formic acid-methanol spray, the molecular ion intensity of neurochemicals was increased mostly. HDImaging v1.5 was used for fine imaging analysis. Addition of 0.1% formic acid to the spray solvent could improve the imaging effect similar to the increasing trend of mass signal intensity. The method presented high repeatability. γ-Aminobutyric acid and aspartic acid were mainly distributed in cerebral cortex. Serine was detected throughout the brain. Glutamine was distributed around the hippocampus. The same spatial distribution of neurochemicals and their precursors and major metabolites in the brain was detected. The DESI-TOF-MSI technique developed here could be used to analyze the distribution of small molecular neurochemicals in rat brain. This work provided a fast and effective visualization method for the study of spatial distribution and metabolism of small molecule neurochemicals in brain.
2022, 50(10): 1542-1550
doi: 10.19756/j.issn.0253-3820.221246
Abstract:
As an important trace evidence, fingerprints are widely used in personal identification and disclosure of criminal acts at the crime scene. Traditional fingerprint studies mainly focus on morphological analysis, while the in-depth exploration of its chemical constituents has always been neglected. In comparison, the chemical analysis of fingerprint substances can better improve the sensitivity and scientificity of fingerprint inspection technique. In this work, by taking the fatty acid in the fingerprint substance as the target, a new method was explored to measure the fatty acid by gas chromatography-mass spectrometry and applied to the analysis of real fingerprint samples. Experiment results showed that when the concentration of hydrochloric acid/methanol solution was 5% (V/V), the derivative temperature was 50℃, the derivative time was 20 min, and the derivative reagent amount was 400 μL, the fatty acid components in fingerprint residues could be detected more accurately. On this basis, the method was applied to the detection of lipid composition in real fingerprint samples, which identified the standard detection process for fingerprint samples and proved a quite obvious individual difference in lipid composition in fingerprint residues. The lipid composition of four fingerprints left by 2 volunteers on the same day was analyzed and the main components with 99.7% of the cumulative variance contribution rate by employing the principal component analysis method was retained, which demonstrated a strong correlation between the lipid composition of these fingerprints, further proving the stability and reproducibility of the fingerprint lipid composition detection method. This work might lay a research foundation for further exploration of employing fingerprint substances to identify individuals.
As an important trace evidence, fingerprints are widely used in personal identification and disclosure of criminal acts at the crime scene. Traditional fingerprint studies mainly focus on morphological analysis, while the in-depth exploration of its chemical constituents has always been neglected. In comparison, the chemical analysis of fingerprint substances can better improve the sensitivity and scientificity of fingerprint inspection technique. In this work, by taking the fatty acid in the fingerprint substance as the target, a new method was explored to measure the fatty acid by gas chromatography-mass spectrometry and applied to the analysis of real fingerprint samples. Experiment results showed that when the concentration of hydrochloric acid/methanol solution was 5% (V/V), the derivative temperature was 50℃, the derivative time was 20 min, and the derivative reagent amount was 400 μL, the fatty acid components in fingerprint residues could be detected more accurately. On this basis, the method was applied to the detection of lipid composition in real fingerprint samples, which identified the standard detection process for fingerprint samples and proved a quite obvious individual difference in lipid composition in fingerprint residues. The lipid composition of four fingerprints left by 2 volunteers on the same day was analyzed and the main components with 99.7% of the cumulative variance contribution rate by employing the principal component analysis method was retained, which demonstrated a strong correlation between the lipid composition of these fingerprints, further proving the stability and reproducibility of the fingerprint lipid composition detection method. This work might lay a research foundation for further exploration of employing fingerprint substances to identify individuals.
2022, 50(10): 1551-1559
doi: 10.19756/j.issn.0253-3820.221049
Abstract:
Postmortem interval (PMI) estimation is the key issue to be solved in forensic practice. The current technologies and methods lack accuracy, specificity and reproducibility, so reliable and stable molecular markers are needed to provide scientific evidence. In this study, proton nuclear magnetic resonance spectrum (1H NMR)-based metabolomics technology was used to explore the changes of small molecular compounds in rat skeletal muscles at different PMI, and the PMI was predicted combined with machine learning model. Ten Sprague-Dawley rats were sacrificed. Then the skeletal muscle tissues were collected at 0, 6, 12, 18, 24, 48 and 72 h (n=10) post-death. The metabolite profiles were obtained by 1H NMR. Twenty molecular markers including hydroxybutyric acid, lactic acid, tyrosine and hypoxanthine were filtered from the metabolite spectrum by orthogonal partial least squares (OPLS) method combined with Mann Whitney U test, database comparison and random forest (RF) feature selection. On this basis, a stacking ensemble model based on RF, gradient boosting decision tree (GBDT), linear discriminant analysis (LDA) as the base classifier and logistic regression (LR) classifier as meta-classifier was established to predict PMI. The prediction performance of the stacking ensemble learning model was better than those of RF, GBDT and LDA. The accuracy of this model for PMI estimation was 85.71% and the AUC value was 0.85. The results showed that 1H NMR technique combined with stacking ensemble model could effectively predict PMI by detecting metabolites changes in skeletal muscle of rats at different PMI, providing a new technique and analytical strategy for PMI inference.
Postmortem interval (PMI) estimation is the key issue to be solved in forensic practice. The current technologies and methods lack accuracy, specificity and reproducibility, so reliable and stable molecular markers are needed to provide scientific evidence. In this study, proton nuclear magnetic resonance spectrum (1H NMR)-based metabolomics technology was used to explore the changes of small molecular compounds in rat skeletal muscles at different PMI, and the PMI was predicted combined with machine learning model. Ten Sprague-Dawley rats were sacrificed. Then the skeletal muscle tissues were collected at 0, 6, 12, 18, 24, 48 and 72 h (n=10) post-death. The metabolite profiles were obtained by 1H NMR. Twenty molecular markers including hydroxybutyric acid, lactic acid, tyrosine and hypoxanthine were filtered from the metabolite spectrum by orthogonal partial least squares (OPLS) method combined with Mann Whitney U test, database comparison and random forest (RF) feature selection. On this basis, a stacking ensemble model based on RF, gradient boosting decision tree (GBDT), linear discriminant analysis (LDA) as the base classifier and logistic regression (LR) classifier as meta-classifier was established to predict PMI. The prediction performance of the stacking ensemble learning model was better than those of RF, GBDT and LDA. The accuracy of this model for PMI estimation was 85.71% and the AUC value was 0.85. The results showed that 1H NMR technique combined with stacking ensemble model could effectively predict PMI by detecting metabolites changes in skeletal muscle of rats at different PMI, providing a new technique and analytical strategy for PMI inference.
2022, 50(10): 1560-1566
doi: 10.19756/j.issn.0253-3820.221176
Abstract:
Surface plasmon coupled emission (SPCE), a novel surface enhanced fluorescence technique, can generate directional and amplified radiation by the intense interaction between fluorophores and surface plasmon of metallic nanofilm. Strong interaction between localized and propagating surface plasmon and "hot spot" structure is important to enhance electromagnetic field while providing special optical phenomena. This unique plasmonic effect has the potential to optimize the performance of SPCE based system. Herein, gold nanorods (AuNRs) were introduced through electrostatic adsorption to achieve an enhanced fluorescence system. After introduction of AuNRs, the fluorescence signal enhancement was realized by factors over 40 and 150 compared with the normal SPCE and free space emission, respectively. The unique enhancement of SPCE by the AuNRs effectively overcame the signal quenching and this enhancement was proven to be triggered by the enhanced electromagnetic field induced by the AuNRs assembly, which provided an opportunity to increase the detection sensitivity and established an optimal plasmonic enhancement system. The amplified SPCE system was employed for multi-wavelength detection through different emission angles, which could broaden the application of SPCE in multi-wavelength simultaneous enhancement and detection.
Surface plasmon coupled emission (SPCE), a novel surface enhanced fluorescence technique, can generate directional and amplified radiation by the intense interaction between fluorophores and surface plasmon of metallic nanofilm. Strong interaction between localized and propagating surface plasmon and "hot spot" structure is important to enhance electromagnetic field while providing special optical phenomena. This unique plasmonic effect has the potential to optimize the performance of SPCE based system. Herein, gold nanorods (AuNRs) were introduced through electrostatic adsorption to achieve an enhanced fluorescence system. After introduction of AuNRs, the fluorescence signal enhancement was realized by factors over 40 and 150 compared with the normal SPCE and free space emission, respectively. The unique enhancement of SPCE by the AuNRs effectively overcame the signal quenching and this enhancement was proven to be triggered by the enhanced electromagnetic field induced by the AuNRs assembly, which provided an opportunity to increase the detection sensitivity and established an optimal plasmonic enhancement system. The amplified SPCE system was employed for multi-wavelength detection through different emission angles, which could broaden the application of SPCE in multi-wavelength simultaneous enhancement and detection.
2022, 50(10): 1567-1577
doi: 10.19756/j.issn.0253-3820.221029
Abstract:
Carbon-based transition metal oxide nanosheets metal-organic framework material(Pd NPs-Cu(Ⅱ)Co(Ⅱ)@C) were prepared by one-step room temperature process, pyrolysis in air, and in-situ reduction method. Then the Au-Ag NCs-TAEA-Pd NPs-Cu(Ⅱ)Co(Ⅱ)@C ternary luminescent composite nanomaterials were synthesized for the first time with gold-silver bimetallic nanoclusters (Au-Ag NCs) as luminophor, tri-(3-aminoethyl) amine (TAEA) as coreactant and Pd NPs-Cu(Ⅱ)Co(Ⅱ)@C as coreaction accelerator. A sandwich electrochemiluminescence (ECL) immunosensor was thus constructed by combining the ternary luminescent composite with alpha fetoprotein (AFP) secondary antibody as capture probe for ultra-sensitive detection of AFP. The ternary Au-Ag NCs-TAEA-Pd NPs-Cu(Ⅱ)Co(Ⅱ)@C luminescent nanocomposites had excellent ECL properties due to the dual catalytic synergy of intramolecular coreaction promoters and intramolecular coreactants, and the "silver effect" of bimetallic nanoclusters. Without any additional signal amplification strategy, the detection range of the ECL biosensor for AFP was 0.001-100 ng/mL, and the detection limit was as low as 0.3 pg/mL. Moreover, the proposed ECL immunosensor was expected to be applied to the diagnosis and bioanalysis of other biomolecules.
Carbon-based transition metal oxide nanosheets metal-organic framework material(Pd NPs-Cu(Ⅱ)Co(Ⅱ)@C) were prepared by one-step room temperature process, pyrolysis in air, and in-situ reduction method. Then the Au-Ag NCs-TAEA-Pd NPs-Cu(Ⅱ)Co(Ⅱ)@C ternary luminescent composite nanomaterials were synthesized for the first time with gold-silver bimetallic nanoclusters (Au-Ag NCs) as luminophor, tri-(3-aminoethyl) amine (TAEA) as coreactant and Pd NPs-Cu(Ⅱ)Co(Ⅱ)@C as coreaction accelerator. A sandwich electrochemiluminescence (ECL) immunosensor was thus constructed by combining the ternary luminescent composite with alpha fetoprotein (AFP) secondary antibody as capture probe for ultra-sensitive detection of AFP. The ternary Au-Ag NCs-TAEA-Pd NPs-Cu(Ⅱ)Co(Ⅱ)@C luminescent nanocomposites had excellent ECL properties due to the dual catalytic synergy of intramolecular coreaction promoters and intramolecular coreactants, and the "silver effect" of bimetallic nanoclusters. Without any additional signal amplification strategy, the detection range of the ECL biosensor for AFP was 0.001-100 ng/mL, and the detection limit was as low as 0.3 pg/mL. Moreover, the proposed ECL immunosensor was expected to be applied to the diagnosis and bioanalysis of other biomolecules.
2022, 50(10): 1578-1586
doi: 10.19756/j.issn.0253-3820.221042
Abstract:
The issue of antibiotic abuse and residues has attracted more and more attention. Combined with surface-enhanced Raman spectroscopy (SERS), QuEChERS (Quick, easy, cheap, effective, rugged, rafe) rapid sample preparation and chemometric methods, a simple, sensitive and rapid method was established to detect quinolone antibiotic residues in chicken eggs. The effectiveness of 0.2% formic acid-acetonitrile solution for extracting quinolone antibiotic residues in egg white was determined, and the detection limit of enrofloxacin was 0.1783 mg/kg. Univariate regression models based on Raman characteristic peaks and a partial least squares regression (PLSR) model based on full spectrum were established, and the effectiveness and performance of competitive adaptive weighted sampling, random frog, and successive projections algorithms for enrofloxacin SERS characteristic spectral variable screening were studied. The PLSR model established by 11 variables selected by random frog algorithm obtained the lowest root mean square error of cross validation set (RMSECV=0.1346 mg/kg) and root mean square error of prediction set (RMSEP=0.1380 mg/kg), indicating that the multispectral variables were closely related to enrofloxacin concentration in eggs. The results showed that SERS technique based on rapid sample pretreatment and chemometrics could achieve rapid quantitative prediction of quinolone antibiotic residues in eggs, so as to monitor the quality and safety of eggs.
The issue of antibiotic abuse and residues has attracted more and more attention. Combined with surface-enhanced Raman spectroscopy (SERS), QuEChERS (Quick, easy, cheap, effective, rugged, rafe) rapid sample preparation and chemometric methods, a simple, sensitive and rapid method was established to detect quinolone antibiotic residues in chicken eggs. The effectiveness of 0.2% formic acid-acetonitrile solution for extracting quinolone antibiotic residues in egg white was determined, and the detection limit of enrofloxacin was 0.1783 mg/kg. Univariate regression models based on Raman characteristic peaks and a partial least squares regression (PLSR) model based on full spectrum were established, and the effectiveness and performance of competitive adaptive weighted sampling, random frog, and successive projections algorithms for enrofloxacin SERS characteristic spectral variable screening were studied. The PLSR model established by 11 variables selected by random frog algorithm obtained the lowest root mean square error of cross validation set (RMSECV=0.1346 mg/kg) and root mean square error of prediction set (RMSEP=0.1380 mg/kg), indicating that the multispectral variables were closely related to enrofloxacin concentration in eggs. The results showed that SERS technique based on rapid sample pretreatment and chemometrics could achieve rapid quantitative prediction of quinolone antibiotic residues in eggs, so as to monitor the quality and safety of eggs.
2022, 50(10): 1587-1596
doi: 10.19756/j.issn.0253-3820.221239
Abstract:
The contents of lignocellulosic components (including cellulose, hemicellulose and lignin) have an important influence on the methane yield of anaerobic digestion (AD) with corn stover (CS) as feedstocks in biogas industry. Aiming at the time-consuming and high-cost issues of traditional chemical analytical techniques, the feasibility of near infrared spectroscopy (NIRS) combined with chemometrics methods to measure the contents of lignocellulose in corn stover was analyzed in this work. To improve the detection accuracy and efficiency of NIRS regressive model, the genetic simulated annealing interval support vector machine (GSA-iSVM) was constructed using genetic simulated annealing algorithm (GSA) combined with interval partial least squares (iPLS) and support vector machine (SVM), which was used for synchronous optimization of the NIRS characteristic intervals and SVM parameters. By comparison with the modeling performance of the characteristic spectral intervals selected by backward interval partial least squares and genetic simulated annealing interval partial least squares (GSA-iPLS), it was found that the calibration model for cellulose and lignin established by GSA-iSVM had the best predicted accuracy, and that of hemicellulose established by GSA-iPLS performed best. For the validation set, the determination coefficients of prediction, root mean squared error of prediction and residual predictive deviation of the best calibration models were 0.910, 0.881% and 3.283 for cellulose; 0.990, 0.707% and 10.235 for hemicellulose; and 0.939, 0.249% and 4.270 for lignin, respectively. The results indicated that NIRS coupled with characteristic intervals intelligent selection of GSA could be used as a reliable alternative strategy to measure contents of lignocellulosic components in the pretreated CS in AD process.
The contents of lignocellulosic components (including cellulose, hemicellulose and lignin) have an important influence on the methane yield of anaerobic digestion (AD) with corn stover (CS) as feedstocks in biogas industry. Aiming at the time-consuming and high-cost issues of traditional chemical analytical techniques, the feasibility of near infrared spectroscopy (NIRS) combined with chemometrics methods to measure the contents of lignocellulose in corn stover was analyzed in this work. To improve the detection accuracy and efficiency of NIRS regressive model, the genetic simulated annealing interval support vector machine (GSA-iSVM) was constructed using genetic simulated annealing algorithm (GSA) combined with interval partial least squares (iPLS) and support vector machine (SVM), which was used for synchronous optimization of the NIRS characteristic intervals and SVM parameters. By comparison with the modeling performance of the characteristic spectral intervals selected by backward interval partial least squares and genetic simulated annealing interval partial least squares (GSA-iPLS), it was found that the calibration model for cellulose and lignin established by GSA-iSVM had the best predicted accuracy, and that of hemicellulose established by GSA-iPLS performed best. For the validation set, the determination coefficients of prediction, root mean squared error of prediction and residual predictive deviation of the best calibration models were 0.910, 0.881% and 3.283 for cellulose; 0.990, 0.707% and 10.235 for hemicellulose; and 0.939, 0.249% and 4.270 for lignin, respectively. The results indicated that NIRS coupled with characteristic intervals intelligent selection of GSA could be used as a reliable alternative strategy to measure contents of lignocellulosic components in the pretreated CS in AD process.
