The detection and utilization of volatile metabolomics in Klebsiella pneumoniae by gas chromatography-ion mobility spectrometry.

This research aimed to analyze the volatile compounds emitted during the proliferation of Klebsiella pneumoniae (K. pneumoniae) in the laboratory setting using gas chromatography-ion mobility spectrometry (GC-IMS) and to investigate the potential of volatile metabolomics for detecting carbapenemase-producing strains of K. pneumoniae. The volatile metabolomics of K. pneumoniae were comprehensively analyzed using GC-IMS in tryptic soy broth (TSB) as the culture medium. Afterward, the growth stabilization period (T2) served as the primary time point for analysis, with the introduction of imipenem and carbapenemase inhibitors (avibactam sodium or EDTA) during the exponential growth phase (T0) to further investigate alterations in volatile molecules associated with K. pneumoniae. Standard strains were utilized as references, while clinical strains were employed for validation purposes. At T2, a total of 22 volatile organic compounds (VOCs) associated with K. pneumoniae were identified (3 VOCs found in both monomer and dimer forms). Significant differences in VOCs were observed between carbapenemase-negative and carbapenemase-positive strains, both standard and clinical, following the introduction of imipenem. Furthermore, the addition of avibactam sodium led to distinct changes in the VOC content of strains producing class A carbapenemase, while the addition of EDTA resulted in specific alterations in the volatile metabolic profiles of strains producing class B carbapenemase. GC-IMS demonstrated significant promise for analyzing bacterial volatile metabolomics, and its application in evaluating the volatolomics of K. pneumoniae may facilitate the timely detection of carbapenemase-producing strains.

Early warning of Aspergillus contamination in maize by gas chromatography-ion mobility spectrometry.

Introduction: As one of the main grain crops in China, maize is highly susceptible to Aspergillus infection during processing, storage and transportation due to high moisture at harvest, which results in the loss of quality. The aim of this study is to explore the early warning marker molecules when Aspergillus infects maize kernels. Methods: Firstly, strains MA and MB were isolated from moldy maize and identified by morphological characterization and 18S rRNA gene sequence analysis to be Aspergillus flavus (A. flavus) and Aspergillus niger (A. niger). Next, fresh maize was moldy by contaminated with strains MA and MB. The volatile organic compounds (VOCs) during the contamination process of two fungal strains were analyzed by gas chromatography-ion mobility spectrometry (GC-IMS). A total of 31 VOCs were detected in maize contaminated with strain MA, a total of 32 VOCs were detected in maize contaminated with strain MB, including confirmed monomers and dimers. Finally, heat maps and principal component analysis (PCA) showed that VOCs produced in different growth stages of Aspergillus had great differences. Combined with the results of GC-IMS, total fungal colony counts and fungal spores, it was concluded that the Aspergillus-contaminated maize was in the early stage of mold at 18 h. Results: Therefore, the characteristic VOCs butan-2-one, ethyl acetate-D, Benzaldehyde, and pentan-2-one produced by maize at 18 h of storage can be used as early mildew biomarkers of Aspergillus infection in maize. Discussion: This study provided effective marker molecules for the development of an early warning and monitoring system for the degree of maize mildew in granaries.

Characterization and discrimination of volatile organic compounds and α-glucosidase inhibitory activity of soybeans (Glycine max L.) during solid-state fermentation with Eurotium cristatum YL-1.

In this study, the influence of solid-state fermentation (SSF) using probiotic Eurotium cristatum on the change of volatile organic compounds (VOCs) and α-glucosidase inhibition activity of soybeans was investigated. A total of 46 VOCs were characterized via headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS), the majority of which were aldehydes (17), alcohols (10), and ketones (7). SSF by E. cristatum drastically affected the flavor characteristics of soybeans, and the levels of unpleasant beany flavor components, such as hexanal-D, 1-octen-3-ol, 1-hexanol-D, 1-hexanol-M, heptanal-M, 1-pentanol, heptanal-D, and 2-pentyl furan were all substantially decreased by 50% after 15 days of SSF, while volatiles with floral, caramel, and desirable flavors such as pentanal-D, methylpropanal, 2-propanol, and propyl acetate drastically (p < 0.05) increased by 1.1-, 19.2-, 3.6-, and 2.6-fold, respectively. Key aroma-active compounds analysis revealed that 18 VOCs (ROAV, relative odor activity value ≥ 1) play a great role in shaping the flavor characteristics of the soybean samples. After 15 days of SSF, the ROAV values of methylpropanal, 2-propanol, and propyl acetate drastically (p < 0.05) increased to 8.48, 63.88, and 11.29, respectively, which greatly contributed to the desirable flavor characteristics of fermented soybeans. Furthermore, E. cristatum greatly improved the α-glucosidase inhibitory activity of soybean by 22.4% after 15 days fermentation, which was closely correlated with the accumulated phenolic compounds during SSF. Molecular docking showed that genistein and daidzein have high binding affinity for α-glucosidase active sites, primarily driven by hydrogen bonds and hydrophobic interactions. These results demonstrated that soybeans fermented with E. cristatum substantially improved the flavor characteristics and α-glucosidase inhibitory effect, and were greatly helpful to promote the application of soybeans in food products.

Discriminative analysis of aroma profiles in diverse cigar products varieties through integrated sensory evaluation, GC-IMS and E-nose.

Cigars, treasured for their rich aromatic profiles, occupy a notable segment in the global consumer market. The objective of this study was to characterize the volatile aroma compounds that shape the flavor profiles of six distinct varieties of Great Wall cigars, contributing to the understanding of cigar aroma analysis. Utilizing HS-GC-IMS and sensory evaluation, the study discerned the aroma profiles of GJ No. 6 (GJ), Animal from the Chinese zodiac (SX), Range Rover No. 3 Classic (JD), Miracle 132 (QJ), Sheng Shi No. 5 (SS), and Red 132 (HS) cigars. The analysis uncovered a spectrum of characteristic aromas, including tobacco, creaminess, cocoa, leather, baking, herbaceous, leathery, woodsy, and fruity notes. A total of 88 compounds were identified, categorized into 11 chemical classes, with their quantities varying among the cigars in a descending order of QJ, JD, GJ, SS, HS, and SX. 24 compounds, such as 2-heptanone, n-butanol, 2,6-dimethylpyrazine and 2-furfuryl methyl sulfide were considered as key differential components. The volatile components were effectively differentiated using principal component analysis (PCA), orthogonal partial least squares-discriminant analysis (OPLS-DA), and cluster analysis, revealing correlations between sensory attributes, key components, and electronic nose (E-nose). This research introduces a novel method for analyzing volatile aroma components in cigars, offering insights to enhance cigar quality and to foster the development of new products with unique aroma profiles.

Chemometrics methods, sensory evaluation and intelligent sensory technologies combined with GAN-based integrated deep-learning framework to discriminate salted goose breeds.

The authenticity of salted goose products is concerning for consumers. This study describes an integrated deep-learning framework based on a generative adversarial network and combines it with data from headspace solid phase microextraction/gas chromatography-mass spectrometry, headspace gas chromatography-ion mobility spectrometry, E-nose, E-tongue, quantitative descriptive analysis, and free amino acid and 5'-nucleotide analyses to achieve reliable discrimination of four salted goose breeds. Volatile and non-volatile compounds and sensory characteristics and intelligent sensory characteristics were analyzed. A preliminary composite dataset was generated in InfoGAN and provided to several base classifiers for training. The prediction results were fused via dynamic weighting to produce an integrated model prediction. An ablation study demonstrated that ensemble learning was indispensable to improving the generalization capability of the model. The framework has an accuracy of 95%, a root mean square error (RMSE) of 0.080, a precision of 0.9450, a recall of 0.9470, and an F1-score of 0.9460.

Revealing alcoholization-related volatile compounds and determining alcoholization indices in tobacco using GC-IMS coupled with chemometrics.

Alcoholization is an integral part of tobacco processing and volatile compounds are key to assessing tobacco alcoholization. In this study, a total of 154 volatiles from nine categories were determined by gas chromatography-ion mobility spectrometry (GC-IMS) from four grades of tobacco, of which 114 were better identified. And then, the dynamic trends of volatile compounds with significant changes in tobacco alcoholization were analyzed. The relevant volatiles with the alcoholization indices (AIs) (R > 0.8) were screened as indicators of tobacco alcoholization. Cinnamyl isobutyrate, linolenic acid alcohol, propanoic acid-M and propanoic acid-D in all tobacco samples were highly correlated with the AIs and tended to increase during the alcoholization process. In addition, linear discriminant analysis (LDA), back-propagation neural network (BPNN) and random forest (RF) classifiers were constructed for discrimination of tobacco AIs. Three classifiers trained with a combination of 20 volatiles achieved satisfactory results with area under the curve (AUC) of 0.95 (LDA), 0.94 (BPNN) and 0.97 (RF), respectively. The RF classifier gained optimal accuracy of 100 % and 96.1 % for the training and test sets, respectively. The study confirmed that GC-IMS can be used to characterize the changes of volatile compounds in tobacco during alcoholization and combined with machine learning to achieve the determination of AIs. The results of the study may provide a new means for the tobacco industry to monitor the alcoholization process and determine the degree of alcoholization.

Comparative Analysis of Commercially Available Flavor Oil Sausages and Smoked Sausages.

This study utilized gas chromatography-ion mobility spectrometry (GC-IMS) to analyze the volatile flavor compounds present in various commercially available sausages. Additionally, it conducted a comparative assessment of the distinctions among different samples by integrating sensory evaluation with textural and physicochemical parameters. The results of the GC-IMS analysis showed that a total of 65 volatile compounds were detected in the four samples, including 12 hydrocarbons, 11 alcohols, 10 ketones, 9 aldehydes, 12 esters, and 1 acids. Fingerprinting combined with principal component analysis (PCA) showed that the volatiles of different brands of sausages were significantly different (p < 0.05). The volatiles of S1 and S4 were more similar and significantly different from the other two samples (p < 0.05). Among them, there were 14 key volatile substances in the four samples, of which 3-hydroxy-2-butanone and diallyl sulfide were common to all four sausages. Combined textural and sensory evaluations revealed that smoked sausages exhibited superior characteristics in resilience, cohesiveness, springiness, gumminess, and chewiness. Additionally, smoked sausages were found to be more attractive in color, moderately spicy, and salty, while having a lower fat content. In conclusion, smoked sausages are preferred by consumers over flavored oil sausages.

Comparison of Different Deodorizing Treatments on the Flavor of Paddy Field Carp, Analyzed by the E-Nose, E-Tongue and Gas Chromatography-Ion Mobility Spectrometry.

Changes in the flavor and taste profiles of Paddy Field Carp after deodorization with perilla juice (PJ), cooking wine (CW) and a mixture of the two (PJ-CW) were analyzed using the E-nose, E-tongue, gas chromatography-ion mobility spectrometry (GC-IMS), free amino acid analysis and taste nucleotide analysis. The E-nose and E-tongue revealed that deodorization reduced the content of sulfur-containing compounds, enhanced umami, bitterness, sourness and astringency, and decreased saltiness. PCA and OPLS-DA analysis successfully distinguished between the effects of the treatments. Free amino acids increased from 8777.67 to 11,125.98 mg/100 g and umami amino acids increased from 128.24 to 150.37 mg/100 g after PJ-CW deodorization (p < 0.05). Equivalent umami concentration (EUC) comparisons showed that PJ-CW treatment produced the greatest synergistic umami enhancement (to 3.15 g MSG equiv./100 g). GC-IMS detected 52 aroma compounds; PJ treatment produced the greatest diversity of aldehydes, including heptanal, nonanal, hexanal, 3-methylbutanal, (E)-2-heptenal and (E,E)-2,4-heptadienal. The total content of volatile flavor compounds was the highest after PJ-CW treatment, and the content of many characteristic flavor substances (3-hydroxy-2-butanone, benzaldehyde, 5-methyl-2(3H)-furanone) increased. These findings provided a theoretical basis for the further development of deodorization methods for Paddy Field Carp.

Odor Fingerprinting of Chitosan and Source Identification of Commercial Chitosan: HS-GC-IMS, Multivariate Statistical Analysis, and Tracing Path Study.

Chitosan samples were prepared from the shells of marine animals (crab and shrimp) and the cell walls of fungi (agaricus bisporus and aspergillus niger). Fourier-transform infrared spectroscopy (FT-IR) was used to detect their molecular structures, while headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) was employed to analyze their odor composition. A total of 220 volatile organic compounds (VOCs), including esters, ketones, aldehydes, etc., were identified as the odor fingerprinting components of chitosan for the first time. A principal component analysis (PCA) revealed that chitosan could be effectively identified and classified based on its characteristic VOCs. The sum of the first three principal components explained 87% of the total variance in original information. An orthogonal partial least squares discrimination analysis (OPLS-DA) model was established for tracing and source identification purposes, demonstrating excellent performance with fitting indices R2X = 0.866, R2Y = 0.996, Q2 = 0.989 for independent variable fitting and model prediction accuracy, respectively. By utilizing OPLS-DA modeling along with a heatmap-based tracing path study, it was found that 29 VOCs significantly contributed to marine chitosan at a significance level of VIP > 1.00 (p < 0.05), whereas another set of 20 VOCs specifically associated with fungi chitosan exhibited notable contributions to its odor profile. These findings present a novel method for identifying commercial chitosan sources, which can be applied to ensure biological safety in practical applications.

A strategy to distinguish similar traditional Chinese medicines by liquid chromatography-mass spectrometry, electronic senses, and gas chromatography-ion mobility spectrometry: Marsdeniae tenacissimae Caulis and Paederiae scandens Caulis as examples.

INTRODUCTION: Marsdeniae tenacissimae Caulis (MTC), a popular traditional Chinese medicine, has been widely used in the treatment of tumor diseases. Paederiae scandens Caulis (PSC), which is similar in appearance to MTC, is a common counterfeit product. It is difficult for traditional methods to effectively distinguish between MTC and PSC. Therefore, there is an urgent need for a rapid and accurate method to identify MTC and PSC. OBJECTIVES: The aim is to distinguish between MTC and PSC by analyzing the differences in nonvolatile organic compounds (NVOCs), taste, odor, and volatile organic compounds (VOCs). METHODS: Liquid chromatography-mass spectrometry (LC-MS) was utilized to analyze the NVOCs of MTC and PSC. Electronic tongue (E-tongue) and electronic nose (E-nose) were used to analyze their taste and odor respectively. Gas chromatography-ion mobility spectrometry (GC-IMS) was applied to analyze VOCs. Finally, multivariate statistical analyses were conducted to further investigate the differences between MTC and PSC, including principal component analysis, orthogonal partial least squares discriminant analysis, discriminant factor analysis, and soft independent modeling of class analysis. RESULTS: The results of this study indicate that the integrated strategy of LC-MS, E-tongue, E-nose, GC-IMS, and multivariate statistical analysis can be effectively applied to distinguish between MTC and PSC. Using LC-MS, 25 NVOCs were identified in MTC, while 18 NVOCs were identified in PSC. The major compounds in MTC are steroids, while the major compounds in PSC are iridoid glycosides. Similarly, the distinct taste difference between MTC and PSC was precisely revealed by the E-tongue. Specifically, the pronounced bitterness in PSC was proven to stem from iridoid glycosides, whereas the bitterness evident in MTC was intimately tied to steroids. The E-nose detected eight odor components in MTC and six in PSC, respectively. The subsequent statistical analysis uncovered notable differences in their odor profiles. GC-IMS provided a visual representation of the differences in VOCs between MTC and PSC. The results indicated a relatively high relative content of 82 VOCs in MTC, contrasted with 32 VOCs exhibiting a similarly high relative content in PSC. CONCLUSION: In this study, for the first time, the combined use of LC-MS, E-tongue, E-nose, GC-IMS, and multivariate statistical analysis has proven to be an effective method for distinguishing between MTC and PSC from multiple perspectives. This approach provides a valuable reference for the identification of other visually similar traditional Chinese medicines.

Traditional method of rhubarb processing optimized by combining flavor analysis with anthraquinone content determination.

Introduction: Rhubarb is a popular food that relieves constipation and aids with weight loss. The traditional method of preparation, includes steaming and sun-drying rhubarb nine times (SDR-9) to reduce its toxicity and increase efficacy. Methods: Flavor analysis includes odor analysis by gas chromatography-ion mobility spectrometry and taste characterization using an electronic tongue. Results: Odor analysis of the samples prepared through SDR-9 identified 61 volatile compounds, including aldehydes, esters, alcohols, ketones, acids, alkenes, and furans. Of these, 13 volatile components were the key substances associated with odor. This enabled the process to be divided into two stages: 1-5 times of steaming and sun-drying and 6-9 times. In the second stage, SDR-6 and SDR-9 were grouped together in terms of odor. Analysis using electronic tongue revealed that the most prominent taste was bitterness. A radar map indicated that the bitterness response was the highest for raw rhubarb, whereas that for processed (steamed and sun-dried) rhubarb decreased. Orthogonal partial least squares discriminant analysis (OPLS-DA) clustering results for SDR-6 and SDR-9 samples indicated that their tastes were similar. Anthraquinones were analyzed via high-performance liquid chromatography; moreover, analysis of the taste and components of the SDR samples revealed a significant correlation. Discussion: These results indicate that there are similarities between SDR-6 and SDR-9 in terms of smell, taste, and composition, indicating that the steaming and sun-drying cycles can be conducted six times instead of nine.

Benchmarking breath analysis using peppermint approach with gas chromatography ion mobility spectrometer coupled to micro thermal desorber.

The Peppermint Initiative, established within the International Association of Breath Research, introduced the peppermint protocol, a breath analysis benchmarking effort designed to address the lack of inter-comparability of outcomes across different breath sampling techniques and analytical platforms. Benchmarking with gas chromatography-ion mobility spectrometry (GC-IMS) using peppermint has been previously reported however, coupling micro-thermal desorption (µTD) to GC-IMS has not yet, been benchmarked for breath analysis. To benchmarkµTD-GC-IMS for breath analysis using the peppermint protocol. Ten healthy participants (4 males and 6 females, aged 20-73 years), were enrolled to give six breath samples into Nalophan bags via a modified peppermint protocol. Breath sampling after peppermint ingestion occurred over 6 h att= 60, 120, 200, 280, and 360 min. The breath samples (120 cm3) were pre-concentrated in theµTD before being transferred into the GC-IMS for detection. Data was processed using VOCal, including background subtractions, peak volume measurements, and room air assessment. During peppermint washout, eucalyptol showed the highest change in concentration levels, followed byα-pinene andß-pinene. The reproducibility of the technique for breath analysis was demonstrated by constructing logarithmic washout curves, with the average linearity coefficient ofR2= 0.99. The time to baseline (benchmark) value for the eucalyptol washout was 1111 min (95% CI: 529-1693 min), obtained by extrapolating the average logarithmic washout curve. The study demonstrated thatµTD-GC-IMS is reproducible and suitable technique for breath analysis, with benchmark values for eucalyptol comparable to the gold standard GC-MS.

Analysis of unique volatile organic compounds in "Mianhua" made from wheat planted in arid alkaline land.

Hebei Province's Huanghua "Mianhua" is a province intangible cultural property made from arid alkaline wheat (AAW). This study aims to assess how different soil conditions affect the volatile organic compounds (VOCs) of "Mianhua" and identify distinct VOCs for land type discrimination. These findings will guide future research on AAW products, enhancing their processing and utilization. 51 VOCs in "Mianhua" from wheat samples grown in arid alkaline land and general land in Huanghua were analyzed by Gas Chromatography-Ion Mobility Spectrometry (GC-IMS). The result of ANOVA, VOC fingerprint, T test, and OPLS-DA revealed VOCs differences based on planting environments. According to multivariate variance contribution rate analysis, most VOCs were more affected by the variety. Land type significantly influenced (E)-2-heptenal (75.3%), Butanol (60.6%), Propyl acetate (60.0%), ethyl pentanoate (45.5%), and ethyl acetate (44.4%). LDA progressively identified Butanol as the characteristic VOC to distinguish "Mianhua" between it made from AAW and general wheat (GW), with a classification accuracy of 75%.

Characterization of the key flavor compounds in cream cheese by GC-MS, GC-IMS, sensory analysis and multivariable statistics.

The aroma types of cream cheese affect its commercial value and consumer acceptability. However, the types of volatile substances and sensory characteristics of cream cheese at different fermentation stages are still unclear. Therefore, in this study, headspace solid-phase microextraction gas chromatography-mass spectrometry (HS-SPME-GC-MS) and headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS) were used to analyze the volatile substances in cream cheese fermentation. Orthogonal partial least squares discriminant analysis (OPLS-DA), odor activity value (OAV), relative odor activity value (ROAV) and variable projection importance (VIP) were used to identify the characteristic flavor substances in cream cheese fermentation. Finally, the relationship between key flavor substances and sensory characteristics was determined by partial least squares (PLS) analysis. A total of 34 and 36 volatile organic compounds were identified by HS-SPME-GC-MS and HS-GC-MS, respectively, and 14 characteristic flavor substances were found, based on VIP, ROAV and OAV models. Combined with sensory analysis and flavor substance changes, it was found that the cream cheese fermented for 15 d had the best flavor and taste. This study reveals the characteristics and contribution of volatile substances in cream cheese at different fermentation stages, which provides new insights into improving flavor and quality control.

Impact of breath sample collection method and length of storage of breath samples in Tedlar bags on the level of selected volatiles assessed using gas chromatography-ion mobility spectrometry (GC-IMS).

The analysis of volatile organic compounds (VOCs) in exhaled air has attracted the interest of the scientific community because it provides the possibility of monitoring physiological and metabolic processes and non-invasive diagnostics of various diseases. However, this method remains underused in clinical practice as well as in research because of the lack of standardized procedures for the collection, storage and transport of breath samples, which would guarantee good reproducibility and comparability of results. The method of sampling, as well as the storage time of the breath samples in the polymer bags used for sample storage and transport, affect the composition and concentration of VOCs present in the breath samples. The aim of our study was to compare breath samples obtained using two methods with fully disposable equipment: a Haldane sampling tube intended for direct breath collection and breath samples exhaled into a transparent Tedlar bag. The second task was to monitor the stability of selected compounds of real breath samples stored in a Tedlar bag for 6 h. Gas chromatography coupled with ion mobility spectrometry (GC-IMS) implemented in the BreathSpec®device was used to analyse exhaled breath. Our results showed a significant difference in the signal intensity of some volatiles when taking a breath sample with a Haldane tube and a Tedlar bag. Due to its endogenous origin, acetone levels were significantly higher when the Haldane tube sampler was used while elevated levels of 2-propanol and unidentified VOC (designated as VOC 3) in the Tedlar bag samples likely originated from contamination of the Tedlar bags. The VOC stability study revealed compound-specific signal intensity changes of the selected VOCs with storage time in the Tedlar bags, with some volatiles showing increasing signal intensity during storage in Tedlar bags. This limits the use of Tedlar bags only for very limited time and carefully selected purpose. Our results highlight the importance of careful design and implementation of experiments and clinical protocols to obtain relevant and reliable results.

Insights into "wheat aroma": Analysis of volatile components in wheat grains cultivated in saline-alkali soil.

The wheat grains that are cultivated in saline-alkali soil exhibit a richer "wheat aroma" compared to their counterparts. This study characterized the composition and content of volatiles in five wheat kernel varieties, harvested from two fields with varying pH levels and total salt content in the soil. The wheat grown in soil with high pH and total salt content had significantly lower levels (p < 0.05) of ethyl 3-methylbutanoate and 1-octen-3-one and significantly higher levels (p < 0.05) of 1-butanol and 1-octen-3-ol. Among all factors, plant site contributed the highest F-value contribution rate (more than 77 %) for these four volatile compounds. Six e-nose sensors responsive to these four compounds exhibited consistent trends. Therefore, the lower of ethyl 3-methylbutanoate and 1-octen-3-one, the higher of 1-butanol and 1-octen-3-ol in wheat, grown on saline-alkali soil, served as characteristic markers for "wheat aroma".

Faecal Volatile Organic Compound Analysis in De Novo Paediatric Inflammatory Bowel Disease by Gas Chromatography-Ion Mobility Spectrometry: A Case-Control Study.

The gut microbiota and its related metabolites differ between inflammatory bowel disease (IBD) patients and healthy controls. In this study, we compared faecal volatile organic compound (VOC) patterns of paediatric IBD patients and controls with gastrointestinal symptoms (CGIs). Additionally, we aimed to assess if baseline VOC profiles could predict treatment response in paediatric IBD patients. We collected faecal samples from a cohort of de novo therapy-naïve paediatric IBD patients and CGIs. VOCs were analysed using gas chromatography-ion mobility spectrometry (GC-IMS). Response was defined as a combination of clinical response based on disease activity scores, without requiring treatment escalation. We included 109 paediatric IBD patients and 75 CGIs, aged 4 to 17 years. Faecal VOC profiles of paediatric IBD patients were distinguishable from those of CGIs (AUC ± 95% CI, p-values: 0.71 (0.64-0.79), <0.001). This discrimination was observed in both Crohn's disease (CD) (0.75 (0.67-0.84), <0.001) and ulcerative colitis (UC) (0.67 (0.56-0.78), 0.01) patients. VOC profiles between CD and UC patients were not distinguishable (0.57 (0.45-0.69), 0.87). Baseline VOC profiles of responders did not differ from non-responders (0.70 (0.58-0.83), 0.1). In conclusion, faecal VOC profiles of paediatric IBD patients differ significantly from those of CGIs.

GC-IMS facilitates identification of carbapenem-resistant Klebsiella pneumoniae in simulated blood cultures.

This study aimed to identify carbapenem-resistant Klebsiella pneumoniae (CRKP) based on changes in levels of its volatile organic compounds (VOCs) in simulated blood cultures (BCs) using the gas chromatography-ion mobility spectrometry (GC-IMS) technique. A comprehensive analysis of volatile metabolites produced by Klebsiella pneumoniae (K. pneumoniae) in BC bottles was conducted using GC-IMS. Subsequently, the released VOCs were analyzed to examine differences in VOC release between CRKP and carbapenem-susceptible Klebsiella pneumoniae (CSKP). A total of 54 VOCs were detected, of which 18 (6 VOCs found in both monomer and dimer forms) were successfully identified. The VOCs produced by K. pneumoniae in BC bottles (BacT/ALERT® SA) were primarily composed of organic acids, alcohols, esters, and ketones. The content of certain VOCs was significantly different between CRKP and CSKP after the addition of imipenem (IPM). Moreover, the inclusion of carbapenemase inhibitors facilitated the identification of carbapenemase-producing K. pneumoniae based on the variations in VOCs. This study demonstrates the utility of GC-IMS technology in identifying CRKP, and reveals that changes in VOCs are closely related to the growth and metabolism of K. pneumoniae, indicating that they can be leveraged to promote early identification of CRKP bacteremia. However, further in-depth studies and experiments are needed to validate our findings.

An Evaluation of the Impact of 60Co Irradiation on Volatile Organic Compounds of Olibanum Using Gas Chromatography Ion Mobility Spectrometry.

Olibanum is a resinous traditional Chinese medicine that is directly used as a powder. It is widely used in China and is often combined with other traditional Chinese medicine powders to promote blood circulation and relieve pain, as well as to treat rheumatism, rheumatoid arthritis, and osteoarthritis. Powdered traditional Chinese medicine is often easily contaminated by microorganisms and 60Co irradiation is one of the good sterilization methods. Volatile organic compounds (VOCs) are the main active ingredient of olibanum. The aim of this study was to validate the optimum doses of 60Co irradiation and its effect on VOCs. 60Co irradiation was applied in different doses of 0 kGy, 1.5 kGy, 3.0 kGy, and 6.0 kGy. Changes in VOCs were detected using gas chromatography ion mobility spectrometry. A total of 81 VOCs were identified. The odor fingerprint results showed that, with an increase in irradiation dose, most of the VOCs of olibanum changed. Through principal component analysis, cluster analysis, and partial least squares discriminant analysis, it was demonstrated that, at 1.5 kGy, the impact of radiation on the VOCs of olibanum was minimal, indicating this is a relatively good irradiation dose. This study provides a theoretical basis for the irradiation processing and quality control of resinous medicinal materials such as olibanum and it also provides a good reference for irradiation technology development and its application to functional foods, thus making it both significant from a research perspective and useful from an application perspective.

Multifaceted analysis of the effects of roasting conditions on the flavor of fragrant Camellia oleifera Abel. seed oil.

Fragrant Camellia oleifera Abel. seed oil (FCSO), produced by a roasting process, is popular for its characteristic aroma. This study investigated the effects of various roasting temperatures (90℃, 120℃, 150℃, 180℃) and durations (20 min, 40 min, 60 min) on the flavor of FCSO by physicochemical properties, hazardous substances, sensory evaluation, and flavor analyses. The results showed that FCSO roasted at 120℃/20 min had a reasonable fatty acid composition with a lower acid value (0.16 mg/g), peroxide value (0.13 g/100 g), p-anisidine value (2.27), dibutyl phthalate content (0.04 mg/kg), and higher 1,1-diphenyl-2-picrylhydrazyl free radical scavenging activity (224.51 µmol TE/kg) than other samples. A multivariate analysis of FCSO flavor revealed that the 120℃/20 min group had a higher grassy flavor score (5.3 score) from nonanoic acid and a lower off-flavor score (2.2 score) from 2-methylbutyric acid. The principal component analysis showed that 120℃/20 min could guarantee the best flavor and quality of FCSO. Therefore, this information can guide the preparation of FCSO.