JOURNAL OF DRUG DELIVERY SCIENCE AND TECHNOLOGY
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2022
·
IF 5.062
Fei Wang,Xuyang Li,Xialin Hu,Wenya Zhuang,Jiewei Lai,Wenchao Wang,Xuanrong Sun,Hong Wang,Qingyong Li
FLQY2 is a camptothecin derivative modified by FL118 and proved to be good antitumor activity in vitro . However, its poor solubility leads to the low therapeutic efficacy in vivo . Here, the injectable FLQY2 lyophilized powder was prepared with Kolliphor® HS 15 (HS 15), which was called HS 15-FLQY2. The preparation process of HS 15-FLQY2 was optimized by orthogonal design and the lyophilization process was investigated by single factor experiment. Moreover, the formulation was characterized, the pharmacokinetics study and the antitumor activity were carried out in vivo . As the results, HS 15-FLQY2 (1:1500, w/w) containing 5% mannitol as cryoprotectant showed good appearance and 70% entrapment efficiency. HS 15-FLQY2 revealed low particle size (<16 nm), better homogeneity (PDI <0.2) and remained stable for 24 h in water. In addition, the data of the DSC , XRD and FTIR demonstrated that FLQY2 was distributed within micelles . In vivo , the bioavailability of HS 15-FLQY2 (i.p.) was improved significantly compared with oral CD-FLQY2 (a cyclodextrin inclusion complex of FLQY2). In addition, HS 15-FLQY2 demonstrated higher tumor inhibition effect than capecitabine , confirming the possibility of treatment cancer by the delivery of FLQY2.
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Food Chemistry-X
·
2024
·
IF 6.5
Jianfeng Liang,Hailin Wu,Mingfei Lu,Ya Li
This study used headspace solid-phase microextraction-gas chromatography–mass spectrometry and multivariate statistical analysis to comprehensively analyze the volatile components in Liupao tea samples throughout fermentation. In total, 1009 volatile organic compounds were detected and identified, including terpenoids, heterocyclic compounds, esters, ketones, hydrocarbons, alcohols, aromatics, and acids. Principal component and hierarchical cluster analyses, characterize the volatile components of Liupao tea samples were characterized at various fermentation stages. Orthogonal partial least squares discriminant analysis identified 248 differentiating compounds (VIP ≥ 1, P < 0.05, and |Log 2 FC| ≥ 1.0) during fermentation. K-means clustering analysis showed that 11 metabolites increased significantly throughout the fermentation process, whereas 31 metabolites decreased continuously. Annotation of these differential compounds revealed significant changes in sensory flavor characteristics in “green, sweet, fruity, floral, and woody” flavors. The results demonstrated significant variations in the volatile components of Liupao tea fermentation, along with notable changes in flavor characteristics.
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PubMed
高影响因子
Journal of Food Measurement and Characterization
·
2024
·
IF 2.9
Chen Huajiang,Luo Yanran,Xing Guiqing,Shi Yongqing,Gu Shuang,Wang Xiangyang
Aspergillus spp. are common dominant fungi in the moldy agricultural products. Different Aspergillus species exhibit high morphological and genetic sequence similarity, making identification challenging. The measurement of mycelial growth in these Aspergillus species often requires a relatively long time. Therefore, there is a need to develop a new rapid method for identifying Aspergillus species and monitoring their growth. The volatile compounds released by five Aspergillus species on culture media were detected by gas chromatography-mass spectrometer (GC–MS), electronic nose and headspace-gas chromatography-ion migration spectrometry (HS-GC-IMS), their characteristic volatile signals were captured, the models for identifying Aspergillus species were established, and prediction models for mycelial growth of five Aspergillus species were developed. The results showed that the LDA classification training set model constructed using the fusion of GC-IMS and electronic nose data achieved a 100% accuracy rate for identifying Aspergillus species in the training set and an 83.3% accuracy rate in the test set, significantly outperforming models based on HS-GC-IMS or electronic nose data alone. When the result combined with morphological analysis, a 100% accuracy rate in identifying Aspergillus species could be achieved. The partial least squares regression (PLSR) prediction models for mycelial growth in Aspergillus species, constructed using both fusion electronic nose data and HS-GC-IMS data, demonstrated high accuracy with prediction accuracies greater than 0.972 for all five species. The prediction model based solely on electronic nose data had lower accuracy, while models using HS-GC-IMS data alone or its combined with electronic nose data achieved good results. This fusion approach of HS-GC-IMS and electronic nose might have the potential to serve as a preliminary screening tool for fungi identification.
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LWT-FOOD SCIENCE AND TECHNOLOGY
·
2025
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IF 6.6
Yang-bo Xiao,Rongji Tian,Ying-ying Shen,Han Tang,Jian-an Huang,Wenliang Wu,Shu-guang Zhang,Xia Yin
Leaf grade is a critical factor influencing black tea aroma formation, yet the precise relationship between leaf grade and aroma characteristics, along with their key volatile compounds, remains unclear. This study employed sensory evaluation combined with headspace solid phase microextraction/gas chromatography-Mass spectrometry (HS-SPME/GC-MS), odor activity values (OAV), partial least squares (PLS) regression, and correlation analysis to investigate the association between leaf grades and aroma attributes, as well as their key volatile compounds. Sensory evaluation and quantitative analysis revealed that as fresh tea leaf grade decreased, the sweet aroma attribute gradually declined, while the floral aroma initially decreased before increasing. GC-MS and OAV analyses identified 22 and 23 differential aroma-active compounds in ‘Jinguanyin’ (JGY) and ‘Jinmudan’ (JMD) black teas of different grades, respectively. Furthermore, PLS modeling and correlation analysis determined that β-damascenone, β-myrcene, geraniol, linalool, and trans -β-ocimene were key compounds responsible for sweet aroma variations across leaf grades, whereas methyl jasmonate, β-ionone, and jasmine lactone were identified as critical compounds influencing floral aroma differences. This study deciphered the chemical basis of how leaf grades affect black tea aroma quality, providing theoretical guidance for precision processing of black tea.
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Horticulturae
·
2026
·Vol. 12
·期 9
·1165
·
IF 3.4
Genlin Mao,Diyang Qiu,Wanbing Chen,Jiwu Zeng
Citrus medica‘Guangdong Xiangshui’ is a commercially valuable specialty citrus cultivar whose leaf volatile organic compounds (VOCs) hold promise for applications in food flavor development. Although rootstock genotype is known to influence secondary metabolism in scions, its specific regulatory effects on leaf VOCs in this cultivar remain poorly understood. In this study, headspace gas chromatography–ion mobility spectrometry (HS-GC-IMS) combined with multivariate statistical analysis was employed to profile leaf VOCs from plants grafted onto four different rootstocks, alongside own-rooted controls. For comparative purposes, leaf and pericarp VOC profiles were also analyzed under identical conditions. A total of 43 valid ion signals were detected, of which 27 neutral parent volatile compounds—predominantly aldehydes, alcohols, ketones, esters, and sulfur-containing compounds—were tentatively identified via database matching (match score > 80%). Distinct volatile fingerprints were observed among rootstock genotypes and propagation modes, and nine candidate differential compounds with variable importance in projection (VIP) > 1 were screened, demonstrating that HS-GC-IMS coupled with exploratory chemometric analysis enables preliminary discrimination of leaf samples across rootstock treatments. Comparative tissue analysis revealed pronounced metabolic divergence: leaves accumulated abundant C6 aldehydes and alcohols, indicative of lipoxygenase (LOX) pathway activity, whereas pericarp exhibited a higher proportion of terpenoids, consistent with terpene synthase (TPS) pathway dominance. However, these metabolic profiling results alone do not conclusively establish pathway-mediated regulatory mechanisms, necessitating further molecular and biochemical investigations. Collectively, this study provides foundational data for rootstock selection and the utilization of leaf aroma resources inC. medica‘Guangdong Xiangshui’.
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POLYHEDRON
·
2019
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IF 2.284
Ning Tian,Yifang Dai,Qing Liu,Wei Dai
A general synthetic strategy for HS-Fe 3 O 4 @MIL-53(Al) adsorbent has been developed in this work. The composite material exhibits an efficient capture performance for rubidium ion due to sulfhydryl group and magnetic Fe 3 O 4 doped in its porous cavity. The results of X-ray diffraction, scanning electron microscopy, Fourier transform infrared spectroscopy, and N 2 adsorption–desorption proved that the HS-Fe 3 O 4 was immobilized in the composite material. High Rb + uptake capacity over the HS-Fe 3 O 4 @MIL-53(Al) is attributed to the exchange of acidic protons between the sulfhydryl group and the Rb + . The pseudo-second-order and Freundlich model could make a good description of the adsorption process. The Rb + sorption selectivity was moderately influenced by any co-ions effect (K + , Na + and Cs + ) due to HS-Fe 3 O 4 doped. These results reveal that our novel composite material might be a promising industrial adsorbent for Rb + capture.
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SCIENTIA HORTICULTURAE
·
2024
·
IF 3.9
Yanhua Pan,Yini Ma,Jiadong He,Lu Zhang,Rong Huang,Ling Tang,Jiaxuan Ren,Weicheng Wang,Muriel Quinet,Yu Meng
This study addresses the identification and comparison of volatile organic compounds (VOCs) in different peony varieties to elucidate their distinct aroma profiles and the common VOCs that constitute the unique fragrance of peony flowers, laying a foundation for breeding high-quality peony varieties and developing related products. Headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS) combined with principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA) was employed to analyze and differentiate the VOCs of eight peony varieties: TAOXI, ZIHELIAN, BAITIANE, YAOHUANG, DAFUGUI, DAOJIN, HONGXIUQIU, and MANAOPAN. The study identified 87 VOCs, revealing significant differences in VOC compositions among the samples. Notably, BAITIANE displayed distinct differences in both color and VOC composition compared to the other seven varieties. It exhibited uniquely high levels of butanoic acid-M, butanoic acid-D, hexanal-D, ethanol-D, and ethyl acetate. Twelve key differential VOCs were identified as having significant impacts: ethanol-D, hexanal-D, (e)-2-hexenal-D, (e)-2-hexenal-M, hexanal-M, butanoic acid-M, acetic acid-D, acetic acid-M, butanoic acid-D, ethyl acetate, thiophene, and dimethyl sulfide. KEGG pathway analysis highlighted the roles of xenobiotics biodegradation, terpenoid metabolism, and amino acid metabolism in VOC biosynthesis. The findings are significant for the breeding of fragrant peony varieties and the development of floral-based products. The findings provide theoretical support for breeding new horticultural flower varieties and developing commercial peony products, enhancing the understanding of floral scent chemistry, and offering valuable information for the perfumery, floral food processing, and related industries.
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Frontiers in Chemistry
·
2025
·
IF 4.2
Pan-Pan Zhang,Xin-Jing Gui,Xue-Hua Fan,Han-Li,Hai-Yang Li,Xiao-Peng Li,Feng-Yu Dong,Yan-Li Wang,Jing-Yao,Jun-Han Shi,Rui-Xin Liu
Amomi fructus (AF) has been used for both medicinal and food purposes for centuries. However, issues such as source mixing, substandard quality, and product adulteration often affect its efficacy. This study used E-nose (EN) and headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) to determine and analyze the volatile organic compounds (VOCs) in AF and its counterfeit products. A total of 111 VOCs were detected by HS-GC-IMS, with 101 tentatively identified. Orthogonal Partial Least Squares-Discriminant Analysis (OPLS-DA) identified 47 VOCs as differential markers for distinguishing authentic AF from counterfeits (VIP value >1 and P < 0.05). Based on the E-nose sensor response value and the peak volumes of the 111 VOCs, the unguided Principal Component Analysis (PCA), guided Principal Component Analysis-Discriminant Analysis (PCA-DA), and Partial Least Squares-Discriminant Analysis (PLS-DA) models were established to differentiate AF by authenticity, origin, and provenance. The authenticity identification model achieved 100.00% accuracy after PCA analysis, while the origin identification model and the provenance identification model were 95.65% (HS-GC-IMS: PLS-DA) and 98.18% (HS-GC-IMS: PCA-DA/PLS-DA), respectively. Further data-level fusion of E-nose and HS-GC-IMS significantly improved the accuracy of the origin identification model to 97.96% (PLS-DA), outperforming single-source data modeling. In conclusion, the intelligent data fusion algorithm based on E-nose and HS-GC-IMS data effectively identifies the authenticity, origin, and provenance of AF, providing a rapid and accurate method for quality evaluation.
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Biomed Research International
·
2019
·
IF 2.197
Xiaohui Wang,Qian Li,Junkang Sui,Jiamiao Zhang,Zhaoyang Liu,Jianfeng Du,Ruiping Xu,Yanyan Zhou,Xunli Liu
Soilborne pathogens affect plant growth and food production worldwide. The application of chemical fertilizers and pesticides to control plant diseases has harmful effects; fortunately, plant growth-promoting rhizobacteria can be used as a potential alternative strategy. Here, Paenibacillus jamilae HS-26 was selected for its highly antagonistic activity against several soilborne pathogens. The bacterium synthesized hydrolytic enzymes and released extracellular antifungal metabolites and volatile organic compounds—primarily, N, N-diethyl-1, 4-phenylenediamine, which was detected by gas chromatography-mass spectrometry and shown to inhibit fungal mycelial growth. Furthermore, HS-26 was useful for nitrogen fixation, phosphate and potassium solubilization, and siderophore and indoleacetic acid production. In vitro tests and pot experiments revealed that HS-26 considerably increased plant biometric parameters. Illumina MiSeq sequencing data showed a significant reduction in soilborne pathogens and increase in beneficial bacteria in the wheat rhizosphere after treatment with strain HS-26.
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HOLZFORSCHUNG
·
2018
·Vol. 72
·期 11
·973-978
·
IF 2.079
Hui-Chao Hu,Tong Zeng,Shaokai Zhang,Lihui Chen,Liulian Huang,Yonghao Ni
A solvent-assisted and pyrogallol (PG)-protected headspace gas chromatography (HS-GC) method was developed to determine the pinene (α- and β-pinene) content in the kraft pulping black liquor (BL). Ethanol (EtOH) addition eliminated pinene’s micelles in BL by complete dissolution in the EtOH/BL medium. PG was applied to protect pinene from oxidation during the sample storage and measurement. The results showed that, with a 25% (v/v) of EtOH content and a 0.1 g of PG in 5-ml of sample solution, a rapid and stable pinene HS extraction can be obtained in 20 min at 80°C. The method has high precision with relative standard deviations within 4.2%. The sensitivity [limits of quantification (LOQ) are ~140 μg l −1 ] was high, and a good accuracy (recovery=96.0–104%) was typical for the pinene detection. The presented method is simple, rapid, accurate and is suitable for pinene quantification in biorefinery related processes and it leads to the preparation of high-value chemicals.
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ANALYTICAL LETTERS
·
2024
·
IF 1.6
Yigong Geng,Shun Zhang,Jing Lin,Xuchu Zhu,Wenqing Gao,Junhui Li,Chenlu Wang,Yong Wu,Renlu Han,Keqi Tang,Jiancheng Yu
Ethanol abuse is increasingly becoming a global issue, adversely affecting both society and families. In blood alcohol concentration (BAC) detection, traditional techniques have long experimental cycles and harsh experimental conditions and often fail to produce timely results. Consequently, achieving swift and precise on-site detection of ethanol poisoning in humans poses a formidable challenge in analytical science. We designed a novel assay for swift on-site analysis of ethanol and BTEX (benzene, toluene, ethylbenzene, and xylene) poisoning in humans using a custom portable headspace injector (portable HS) and portable gas chromatography-mass spectrometry (portable GC-MS). This setup, known for its lightweight design and speed, allows on-site sampling and delivers rapid results. We established a calibration curve (R2 > 0.99) for ethanol in blood using portable gas chromatography-mass spectrometry (portable GC-MS). This on-site blood alcohol concentration (BAC) assay proves simpler than traditional methods, enabling rapid analysis of each sample within a short timeframe and requiring only a small blood volume (0.1 ml). In addition to our investigation on ethanol, we developed a portable method for detecting BTEX in blood. This method provides a favorable coefficient of determination (R2 > 0.99) for various substances, thereby broadening the utility of portable mass spectrometry in areas such as traffic inspection and forensic identification.
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JOURNAL OF CHROMATOGRAPHY A
·
2024
·
IF 3.8
Wenhui Lu,Chunli Ding,Mingshuo Zhu
The process of globalization and industrialization has resulted in a rise in the theft of coal and other related products, thereby becoming a focal point for forensic science. This situation has engendered an escalated demand for effective detection and monitoring technologies. The precise identification of coal trace evidence presents a challenge with current methods, owing to its minute quantity, fine texture, and intricate composition. In this study, we integrated machine learning with the identification of volatiles to accurately differentiate coal geographical origins through the application of headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS). The topographic distribution of volatiles in coals was visually depicted to elucidate the subtle distinctions through spectra and fingerprint analysis. Additionally, four supervised machine learning algorithms were developed to quantitatively predict the geographical origins of natural coals utilizing the HS-GC-IMS dataset, and these were subsequently compared with unsupervised models. Remarkable volatile compounds were identified through the quantitative analysis and optimal Random Forest model, which offered a rapid readout and achieved an average accuracy of 100 % in coal identification. Our findings indicate that the integration of HS-GC-IMS and machine learning is anticipated to enhance the efficiency and accuracy of coal geographical traceability, thereby providing a foundation for litigation and trials.
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