Variable Importance In Projection Research Articles

Unravelling the metabolomic diversity of pigmented and non-pigmented traditional rice from Tamil Nadu, India

Rice metabolomics is widely used for biomarker research in the fields of pharmacology. As a consequence, characterization of the variations of the pigmented and non-pigmented traditional rice varieties of Tamil Nadu is crucial. These varieties possess fatty acids, sugars, terpenoids, plant sterols, phenols, carotenoids and other compounds that plays a major role in achieving sustainable development goal 2 (SDG 2). Gas-chromatography coupled with mass spectrometry was used to profile complete untargeted metabolomics of Kullkar (red colour) and Milagu Samba (white colour) for the first time and a total of 168 metabolites were identified. The metabolite profiles were subjected to data mining processes, including principal component analysis (PCA), Orthogonal Partial Least Square Discrimination Analysis (OPLS-DA) and Heat map analysis. OPLS-DA identified 144 differential metabolites between the 2 rice groups, variable importance in projection (VIP) ≥ 1 and fold change (FC) ≥ 2 or FC ≤ 0.5. Volcano plot (64 down regulated, 80 up regulated) was used to illustrate the differential metabolites. OPLS-DA predictive model showed good fit (R2X = 0.687) and predictability (Q2 = 0.977). The pathway enrichment analysis revealed the presence of three distinct pathways that were enriched. These findings serve as a foundation for further investigation into the function and nutritional significance of both pigmented and non-pigmented rice grains thereby can achieve the SDG 2.

Key Aroma Differences in Volatile Compounds of Aged Feng-Flavored Baijiu Determined Using Sensory Descriptive Analysis and GC×GC-TOFMS.

Sensory descriptive analysis of aged feng-flavored Baijiu liquor indicated notable differences in samples of different ages. The samples of freshly distilled Baijiu and those with shorter storage times exhibit bran and fresh green flavors, whereas, with increasing storage time, honey, sweet, and floral fragrances are gradually enhanced. Samples of feng-flavored Baijiu were prepared using headspace solid-phase microextraction, followed by comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry. A total of 496 compounds were identified in all samples, mainly categorized as 14 groups of substances, including esters and aldehydes. Interestingly, 42 of these substances were found in Feng-flavored Baijiu for the first time. Chemometrics was used to analyze the key differential compounds. First, 143 differential compounds closely related to aging were preliminarily screened, and principal component analysis revealed that these compounds were separated by baijiu age. Then, 65 differential compounds were selected by partial least squares discriminant analysis. Furthermore, 43 key differential compounds were selected by combined analysis with variable importance in projection and Pearson correlation coefficients. Partial least squares regression was used to study the correlation between the sensory properties and key differential compounds, and the results indicated that most compounds were closely related to the aging period of the Baijiu. The results of this study provide a theoretical basis and reference for flavor research on feng-flavored Baijiu.

Advances in the individual authentication of cocoa beans: Vis/NIR spectroscopy as a tool to distinguish fermented from unfermented beans and classify genotypes in the eastern Amazonia

Reliable analytical methods to authenticate high-quality and economically valuable cocoa beans are highly desirable, and NIR spectroscopy stands out as a rapid and non-destructive alternative. This study employs NIR for the authentication and differentiation of 19 whole Forastero cocoa beans from Eastern Amazonia (Pará, Brazil), based on their fermentation status and genetic profiles. Partial Least Squares Discriminant Analysis (PLS-DA) models in wavelength ranges of 400–700 nm, 1400–1600 nm, and 1900–2500 nm, demonstrated high sensitivity and specificity in discriminating fermented from unfermented beans, regardless of genotype. Various compounds, including proteins, lipids, carbohydrates, anthocyanins, and theobromine, provide crucial insights into the spectral regions essential for distinction. The variable importance in projection (VIP) score value greater than 1 was used to select relevant variables, and Linear Discriminant Analysis (LDA) was performed in both the visible (472 nm and 636 nm) and infrared ranges (2096 nm and 2278 nm), demonstrating that absorbances at two specific wavelengths are sufficient for discrimination. The t-distributed stochastic neighbor embedding (t-SNE) indicated a segregation trend of the genotypes based on classification by major genetic groups in unfermented beans, suggesting that the biochemical characteristics shared by them are more prominent before fermentation. The PLS-DA models based on complete vis/NIR spectra showed comparable results in discriminating the 19 cocoa genotypes in both fermented (0.14% prediction error) and unfermented beans (0.16% prediction error). The model's classification errors can be attributed to shared genetic ancestry among the samples, primarily in unfermented beans. This research corroborates the effectiveness of vis/NIR spectroscopy as a straightforward tool for whole cocoa bean authentication, providing rapid insights into genetic diversity regardless of their fermentation state.

Comparative study on the quality of wild and ecologically farmed large yellow croaker through on-site synchronous sampling from the Nanji Archipelago in the East China Sea

With consumers demanding higher quality in fish products, ecologically farmed fish are increasingly favored due to their quality being close to that of wild fish. However, the differences between the ecologically farmed and wild fish remain largely unclear. In the present study, the wild and ecologically farmed large yellow croakers of the same size were captured simultaneously from the same marine area around Nanji islands (27.479°E, 121.052°N). Then, synchronous tests were conducted to evaluate quality to clarify the key quality parameters that differentiate between the wild and farmed fish. We obtained 49 quality parameters after orthogonal partial least squares discriminant analysis (OPLS-DA) with variable importance in projection (VIP) scores >1 and p < 0.05 using 307 indicators related to 121 length ratios, 4 body color indicators, 5 muscle fiber characteristic indicators, 87 nutrition quality parameters, 40 taste parameters, and 50 volatile compounds. Compared to the farmed fish, the wild fish exhibited a more yellow skin color, higher levels of carotenoids, and a more streamlined conical shape. Changes in histology and ultrastructure of muscle fibers were noted, including increased muscle fiber density and the ratio of fiber area to gap, as well as reduced I band width, observed in the wild fish. The wild fish had high nutritional value of fatty acids and minerals and low nutritional value of amino acids, as reflected by higher levels of C22: 6n3 (DHA), Σn-3 PUFA (polyunsaturated fatty acids), Σn-3/Σn-6 PUFA, Na (sodium), K (potassium), Fe (iron), and Se (selenium), and lower values of ΣMUFA (monosaturated fatty acids), Σn-6 PUFA, TI (thrombogenic index), amino acid and chemistry scores of isoleucine, ΣEAA/ΣTAA (essential amino acid/ total amino acid), and ΣTAA/ΣNEAA (total amino acid/non-essential amino acid) in the muscles of the wild fish. The wild fish muscle showed high levels of hydrolyzed glycine and proline and free methionine, and low levels of free glycine and proline, indicating a propensity for collagen synthesis. Despite significant differences in the contents of fourteen flavor substances of free amino acids, 5′-nucleotides, and volatile compounds, their concentrations were notably below the corresponding threshold and contributed minimally to flavor, suggesting that the wild and farmed fish shared similar flavor characteristics. In summary, this study reveals the quality differences between ecologically farmed and wild large yellow croaker based on on-site synchronous sampling, providing a theoretical foundation for further enhancing the quality of this species.

An efficient method for rapid screening of triterpenoid saponins in three Glycyrrhiza species using rapid resolution liquid chromatography quadrupole time-of-flight mass spectrometry combined with mass defect filtering

Triterpenoid saponins, a major bioactive component of liquorice, possess high hydrophilicity and often co-occur with other impurities of similar polarity. Additionally, subtle structural differences of some triterpenoid saponins bring challenges to comprehensive characterisation. In this study, triterpenoid saponins of three Glycyrrhiza species were systematically analysed using rapid resolution liquid chromatography quadrupole time-of-flight mass spectrometry (RRLC-Q-TOF-MS) coupled with mass defect filtering (MDF). Firstly, comprehensive date acquisition was achieved using RRLC-Q-TOF-MS. Secondly, a polygonal MDF method was established by summarizing known and speculated substituents and modifications based on the core structure to rapidly screen potential triterpenoid saponins. Thirdly, based on the fragmentation patterns of reference compounds, an identification strategy for characterisation of triterpenoid saponins was proposed. The strategy divided triterpenoid saponins into three distinct classes. By this strategy, 98 triterpenoid saponins including 10 potential new ones were tentatively characterised. Finally, triterpenoid saponins of three Glycyrrhiza species were further analysed using principle component analysis (PCA) and orthogonality partial least squares discriminant analysis (OPLS-DA). Among these, 18 compounds with variable importance in projections (VIP) > 1.0 and P values < 0.05 were selected to distinguish three Glycyrrhiza species. Overall, our study provided a reference for quality control and rational use of the three species.

Quantitative analysis of four PAHs in oily sludge by surface-enhanced Raman spectroscopy (SERS) combined with partial least squares regression (PLS) based on a novel nano-silver-silicon coupling substrate

Polycyclic aromatic hydrocarbons (PAHs) present in oily sludge generated by the petroleum and petrochemical industries have emerged as a prominent concern within the realm of environmental conservation. The precise determination of PAHs holds immense significance in both petroleum geochemistry and environmental protection. In this study, a combination of surface-enhanced Raman spectroscopy (SERS) and solid–liquid extraction was employed for the screening of PAHs in oily sludge. Methanol was utilized as the extraction solvent for PAHs, while nanosilver-silicon coupling substrates were employed for their detection. The SERS spectrum was acquired using a portable Raman spectrometer. The nano silver-silicon coupling substrate exhibits excellent uniformity, with relative standard deviations (RSDs) of Phenanthrene, Fluoranthrene, Fluorene and Naphthalene (Phe, Flt, Flu and Nap) being 2.8 %, 1.08 %, 1.41 %, and 5.44 % respectively. Moreover, the limits of detection (LODs) achieved remarkable values of 0.542 μg/g, 0.342 μg/g, 0.541 μg/g, and 5.132 μg/g. The quantitative analysis of PAHs in oily sludge was investigated using SERS technology combined with partial least squares (PLS). The optimal PLS calibration model was optimized by combining spectral preprocessing methods and using the SiPLS (Synergy interval partial least squares)-VIP (Variable Importance in Projection) hybrid variable selection strategy. The prediction performance of the D1st (First derivative)-WT (Wavelet transform)-SiPLS-VIP-PLS model was deemed satisfactory, as evidenced by high R2P values of 0.9851, 0.9917, and 0.9925 for Phe, Flt, and Fluorene respectively; additionally, the corresponding MREP values were found to be 0.0580, 0.0668, and 0.0669 respectively. However, for Nap analysis, the D1st-WT-PLS model proved to be a better calibration model with an R2P value of 0.9864 and an MREP (Mean relative error of prediction) value of 0.0713. In summary, SERS technology combined with PLS based on different spectral pretreatment methods and mixed variable selection strategies is a promising method for quantitative analysis of PAHs in oily sludge, which will provide new ideas and methods for the quantitative analysis of PAHs in oily sludge.

Untargeted metabolomics using liquid chromatography-high resolution mass spectrometry and chemometrics for analysis of non-halal meats adulteration in beef meat.

The adulteration of raw beef (BMr) with dog meat (DMr) and pork (PMr) becomes a serious problem because it is associated with halal status, quality, and safety of meats. This research aimed to develop an effective authentication method to detect non-halal meats (dog meat and pork) in beef using metabolomics approach. Liquid chromatography-high resolution mass spectrometry (LC-HRMS) using untargeted approach combined with chemometrics was applied for analysis non-halal meats in BMr. The untargeted metabolomics approach successfully identified various metabolites in BMr DMr, PMr, and their mixtures. The discrimination and classification between authentic BMr and those adulterated with DMr and PMr were successfully determined using partial least square-discriminant analysis (PLS-DA) with high accuracy. All BMr samples containing non-halal meats could be differentiated from authentic BMr. A number of discriminating metabolites with potential as biomarkers to discriminate BMr in the mixtures with DMr and PMr could be identified from the analysis of variable importance for projection value. Partial least square (PLS) and orthogonal PLS (OPLS) regression using discriminating metabolites showed high accuracy (R2>0.990) and high precision (both RMSEC and RMSEE <5%) in predicting the concentration of DMr and PMr present in beef indicating that the discriminating metabolites were good predictors. The developed untargeted LC-HRMS metabolomics and chemometrics successfully identified non-halal meats adulteration (DMr and PMr) in beef with high sensitivity up to 0.1% (w/w). A combination of LC-HRMS untargeted metabolomic and chemometrics promises to be an effective analytical technique for halal authenticity testing of meats. This method could be further standardized and proposed as a method for halal authentication of meats.

Chemometric assessment of electronic cigarettes based on the ICP-MS determination of multiple heavy metal concentrations

To elucidate the concentrations of heavy metal elements in commercially available electronic cigarettes and improve quality assessment. Inductively coupled plasma-mass spectrometry (ICP-MS) coupled to chemometrics was used to determine the concentrations of Cr, Ni, As, Cd, Sn, Sb, Hg, and Pb in the e-liquids and aerosols derived from 32 electronic cigarettes sold commercially under six brand names. The e-liquids contained: 4.858 to 274.658 (Cr), 17.292 to 3068.375 (Ni), 3.217 to 29.867 (As), 0.225 to 24.717 (Cd), 0.783 to 17.042 (Sn), 0.658 to 36.033 (Sb), 0.658 to 187.592 (Hg), and 2.458 to 17.417 (Pb) ng·g−1. The aerosol samples contained: 276.075 to 3333.175 (Cr), 72.908 to 1150.183 (Ni), 4.567 to 86.958 (As), 0.400 to 12.842 (Cd), 1.092 to 32.142 (Sn), 0.976 to 10.633 (Sb), 3.483 to 234.708 (Hg), 27.833 to 849.100 (Pb) ng·100 puffs−1. The recovery of heavy metals ranged from 99.1% to 112.4% in the e-liquids and from 87.3% to 116.6% in the aerosols, with RSD values below 10%. Hierarchical cluster analysis grouped the e-liquids into eight clusters, and the aerosols into five, indicating differences between products within brands and between different brands. Orthogonal partial least squares discriminant analysis coupled with variable importance in projection (VIP > 1) identified As and Sb as the primary heavy metals causing differences between the e-liquids, while differences between the aerosols were caused by Hg, As, Pb, Cd, and Cr. The use of chemometric methods yields a greater depth of information that will support improvements to the quality control of e-cigarette products and the assessment of their potential risk to human health.

Widely Targeted Metabolomic Analysis Revealed the Diversity in Milk from Goats, Sheep, Cows, and Buffaloes and Its Association with Flavor Profiles.

The milk flavor can be attributed to the presence of numerous flavor molecules and precursors. In this study, we employed widely targeted metabolomic analysis techniques to analyze the metabolic profiles of various milk samples obtained from goats, sheep, dairy cows, and buffaloes. A total of 631 metabolites were identified in the milk samples, which were further categorized into 16 distinct classes. Principal component analysis (PCA) suggested that the metabolite profiles of samples from the same species exhibit clustering, while separated patterns of metabolite profiles are observed across goat, sheep, cow, and buffalo species. The differential metabolites between the groups of each species were screened based on fold change and variable importance in projection (VIP) values. Five core differential metabolites were subsequently identified, including 3-(3-hydroxyphenyl)-3-hydroxypropanoic acid, inosine 5'-triphosphate, methylcysteine, N-cinnamylglycine, and small peptide (L-tyrosine-L-aspartate). Through multiple comparisons, we also screened biomarkers of each type of milk. Our metabolomic data showed significant inter-species differences in the composition and concentration of some compounds, such as organic acids, amino acids, sugars, nucleotides, and their derivatives, which may affect the overall flavor properties of the milk sample. These findings provided insights into the molecular basis underlying inter-species variations in milk flavor.

Characteristics and diagnostic value of serum bile acids profile in pregnant women with intrahepatic cholestasis of pregnancy and asymptomatic hypercholanemia of pregnancy

Objective: To analyze serum bile acid profiles in pregnant women with normal pregnancy, intrahepatic cholestasis of pregnancy (ICP) and asymptomatic hypercholanemia of pregnancy (AHP), and to evaluate the application value of serum bile acid profiles in the diagnosis of ICP and AHP. Methods: The clinical data of 122 pregnant women who underwent prenatal examination in Xuzhou Maternal and Child Health Care Hospital from June 2022 to May 2023 were collected, including 54 cases of normal pregnancy group, 28 cases of ICP group and 40 cases of AHP group. Ultraperformance liquid chromatography-tandem mass spectrometry was used to measure the levels of 15 serum bile acids in each group, including cholic acid (CA), chenodeoxycholic acid (CDCA), deoxycholic acid (DCA), lithocholic acid (LCA), ursodeoxycholic acid (UDCA), glycolcholic acid (GCA), glycochenodeoxycholic acid (GCDCA), glycodeoxycholic acid (GDCA), glycolithocholic acid (GLCA), glycoursodeoxycholic acid (GUDCA), taurocholic acid (TCA), taurochenodeoxycholic acid (TCDCA), taurodeoxycholic acid (TDCA), taurolithocholic acid (TLCA) and tauroursodeoxycholic acid (TUDCA). Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were used to screen differential bile acids. The receiver operating characteristic (ROC) curve was used to analyze the diagnostic efficacy of differential bile acids and combined indicators between groups. Results: (1) Compared with normal pregnancy group, the serum levels of LCA, GCA, GCDCA, GDCA, GLCA, UDCA, TCA, TCDCA, TDCA, TLCA, GUDCA and TUDCA in ICP group were significantly different (all P<0.05), while the levels of LCA, DCA, GCA, GCDCA, GDCA, GLCA, TCA, TCDCA, TDCA, TLCA, GUDCA and TUDCA in AHP group were significantly different (all P<0.05). Compared with ICP group, the serum levels of CDCA, DCA, UDCA, TDCA, GUDCA and TUDCA in AHP group were significantly different (all P<0.05). (2) In the OPLS-DA model, the differential bile acids between ICP group and AHP group were TUDCA, TCA, UDCA, GUDCA and GCA, and their variable importance in projection (VIP) were 1.489, 1.345, 1.344, 1.184 and 1.111, respectively. TCA, GCDCA, GCA, TDCA, GDCA and TCDCA were the differentially expressed bile acids between AHP group and normal pregnancy group, and their VIP values were 1.236, 1.229, 1.197, 1.145, 1.139 and 1.138, respectively. (3) ROC analysis showed that the area under the curve (AUC) of TUDCA, TCA, UDCA, GUDCA and GCA in the differential diagnosis of ICP and AHP was 0.860, and the sensitivity and specificity were 67.9% and 95.0%, respectively. The AUC of TCA, GCDCA, GCA, TDCA, GDCA and TCDCA in the diagnosis of AHP was 0.964, and the sensitivity and specificity were 95.0% and 93.1%, respectively. Conclusions: There are differences in serum bile acid profiles among normal pregnant women, ICP and AHP. The serum bile acid profiles of pregnant women have potential application value in the differential diagnosis of ICP and AHP and the diagnosis of AHP.

Impact of storage time on microbial communities and flavor profiles in highland barley grains

Microbial activity and the resulting flavor changes in stored highland barley grains may reduce the product quality and pose potential risks to food safety with economic losses. This study aims to elucidate the association between microbial load and flavor compounds during the preservation of highland barley. High-throughput sequencing (HTS) was used to investigate the microbial composition in stored highland barley. The volatile flavor components of the latter were identified via the headspace solid-phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS). Moreover, the study examined the correlation between the types of microorganisms and volatile flavor molecules. The results indicated that the dominant phyla in highland barley were Ascomycota and Basidiomycota, with the dominant genera being Cladosporium, Vishniacozyma, Filobasidium, Udeniomyces, Cystofilobasidium, Aspergillus, Alternaria, Monographella, Didymella, and Neoascochyta. Inside，Cystofilobasidium, Itersonilia, Sarocladium, Ustilago, Penicillium and Pyrenophora served as effective biomarkers to distinguish highland barley grains stored at different times. Further, the highland barley samples contained 192 volatile organic compounds (VOCs), such as alcohols, ketones, esters, alkanes, aldehydes, etc. The top 20 volatile flavor compounds with differences were selected based on the variable importance of projection (VIP) > 1. Based on the correlation analysis findings, it was found that the genera Cystofilobasidium, Aspergillus, and Cladosporium hold promise in contributing volatile flavor compounds to highland barley. This study examined a pattern of changes in safety and quality across varying storage durations, providing crucial insights to enhance the flavor profile and texture of highland barley products.

Based on HPLC and HS-GC-IMS Techniques, the Changes in the Internal Chemical Components of Schisandra chinensis (Turcz.) Baill. Fruit at Different Harvesting Periods Were Analyzed.

Schisandra chinensis, as a traditional Chinese herbal medicine, has clear pharmacological effects such as treating asthma, protecting nerves and blood vessels, and having anti-inflammatory properties. Although the Schisandra chinensis fruit contain multiple active components, the lignans have been widely studied as the primary pharmacologically active compound. The volatile chemical components of Schisandra chinensis include a large amount of terpenes, which have been proven to have broad pharmacological activities. However, when to harvest to ensure the highest accumulation of pharmacologically active components in Schisandra chinensis fruits is a critical issue. The Schisandra chinensis fruit trees in the resource nursery were all planted in 2019 and began bearing fruit in 2021. Their nutritional status and tree vigor remain consistently good. The content of lignans and organic acids in the fruits of Schisandra chinensis over seven different harvest periods was tested, and the results of high-performance liquid chromatography (HPLC) indicated that the lignan content was higher, at 35 mg/g, in late July, and the organic acid content was higher, at 72.34 mg/g, in early September. If lignans and organic acids are to be selected as raw materials for pharmacological development, the harvest can be carried out at this stage. Using HS-GC-IMS technology, a total of 67 volatile flavor substances were detected, and the fingerprint of the volatile flavor substances in the different picking periods was established. It was shown by the results that the content of volatile flavor substances was the highest in early August, and 16 flavor substances were selected by odor activity value (OAV). The variable importance in projection (VIP) values of 16 substances were further screened, and terpinolene was identified as the key volatile flavor substance that caused the aroma characteristics of Schisandra chinensis fruit at different harvesting periods. If the aroma component content of Schisandra chinensis fruit is planned to be used as raw material for development and utilization, then early August, when the aroma component content is higher, should be chosen as the time for harvest. This study provides a theoretical basis for the suitable harvesting time of Schisandra chinensis for different uses, and promotes the high-quality development of the Schisandra chinensis industry.

Metabolomic profiling of the aqueous humor in patients with pediatric cataract

Pediatric cataract, including congenital and developmental cataract, is a kind of pediatric vision-threatening disease with extensive phenotypic heterogeneity and multiple mechanisms. We aimed to investigate the metabolite profile of aqueous humor (AH) in patients with pediatric cataracts, and identify underlying mutual correlations between differential metabolites. Metabolomic profiles of AH were analyzed and compared between pediatric cataract patients (n = 33) and age-related cataract patients without metabolic diseases (n = 29), using global untargeted metabolomics with ultra-high-performance liquid chromatography tandem mass spectrometry. Principal component analysis, partial least squares discriminant analysis and heat map were applied. Enriched pathway analysis was conducted using Kyoto Encyclopedia of Genes and Genomes. Receiver-operating characteristic (ROC) analyses were employed to select potential biomarkers. A total of 318 metabolites were identified, of which 54 differential metabolites (25 upregulated and 29 downregulated) were detected in pediatric cataract group compared with controls (variable importance of projection >1.0, fold change ≥1.5 or ≤ 0.667 and P < 0.05). A significant accumulation of N-Acetyl-Dl-glutamic acid was observed in pediatric cataract group. The differential metabolites were mainly enriched in histidine metabolism (increased L-Histidine and decreased 1-Methylhistamine) and the tryptophan metabolism (increased N-Formylkynurenine and L-Kynurenine). 5-Aminosalicylic acid showed strong positive mutual inter-correlation with L-Tyrosinemethylester and N,N-Diethylethanolamine, both of which were down-regulated in pediatric cataract group. The ROC analysis implied 11 metabolites served as potential biomarkers for pediatric cataract patients (all area under the ROC curve ≥0.900). These results illustrated novel potential metabolites and metabolic pathways in pediatric cataract, which provides new insights into the pathophysiology of pediatric cataract.

Discrimination and screening of volatile metabolites in atractylodis rhizoma from different varieties using headspace solid-phase microextraction-gas chromatography-mass spectrometry and headspace gas chromatography-ion mobility spectrometry, and ultra-fast gas chromatography electronic nose

Atractylodis rhizoma is a common bulk medicinal material with multiple species. Although different varieties of atractylodis rhizoma exhibit variations in their chemical constituents and pharmacological activities, they have not been adequately distinguished due to their similar morphological features. Hence, the purpose of this research is to analyze and characterize the volatile organic compounds (VOCs) in samples of atractylodis rhizoma using multiple techniques and to identify the key differential VOCs among different varieties of atractylodis rhizoma for effective discrimination. The identification of VOCs was carried out using headspace solid-phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC–MS) and headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS), resulting in the identification of 60 and 53 VOCs, respectively. The orthogonal partial least squares discriminant analysis (OPLS-DA) model was employed to screen potential biomarkers and based on the variable importance in projection (VIP ≥ 1.2), 24 VOCs were identified as critical differential compounds. Random forest (RF), K-nearest neighbor (KNN) and back propagation neural network based on genetic algorithm (GA-BPNN) models based on potential volatile markers realized the greater than 90 % discriminant accuracies, which indicates that the obtained key differential VOCs are reliable. At the same time, the aroma characteristics of atractylodis rhizoma were also analyzed by ultra-fast gas chromatography electronic nose (Ultra-fast GC E-nose). This study indicated that the integration of HS-SPME-GC–MS, HS-GC-IMS and ultra-fast GC E-nose with chemometrics can comprehensively reflect the differences of VOCs in atractylodis rhizoma samples from different varieties, which will be a prospective tool for variety discrimination of atractylodis rhizoma.

Environmental temperature variations drive the changes of microbial communities to affect Baijiu flavor quality: Case study of Qingxiangxing Baijiu

Environmental temperature is a crucial factor that affects the fermentation quality of Baijiu. In this study, Illumina Miseq sequencingd, Two-dimensional gas chromatography coupled to mass spectrometry (GC × GC-MS), and physicochemical analyses were employed to investigate the microbial communities, flavor compounds, and physicochemical properties during fermentation at different ambient temperatures (10 ± 2 °C in the lower environmental temperature (LT) group and 22 ± 2 °C in the higher environmental temperature (HT) group). The findings demonstrated an augmentation in microbial diversity, ecological network complexity, and utilization of raw materials by microorganisms in HT group. Sensory analysis showed that sensory properties of Baijiu produced by the HT group had a better overall performance. The Baijiu in the HT group exhibited higher quality in terms of sweetness, fruity and floral, whereas the Baijiu in the LT group displayed a greater degree of unpleasant pungency and acidity. 24 flavor compounds were identified with the Variable Importance in Projection (VIP) > 1, and they were the main factors contributing to the differences in Baijiu flavors at two environmental temperatures. Correlation analysis showed that ambient temperature influenced microbial interactions and their correlation with metabolites. This difference showed the quality change of Baijiu driven by different temperatures. These results provide solid data support for optimizing the Baijiu fermentation process under different seasonal temperatures.

Best performances of visible–near-infrared models in soils with little carbonate – a field study in Switzerland

Abstract. Conventional laboratory analysis of soil properties is often expensive and requires much time if various soil properties are to be measured. Visual and near-infrared (vis–NIR) spectroscopy offers a complementary and cost-efficient way to gain a wide variety of soil information at high spatial and temporal resolutions. Yet, applying vis–NIR spectroscopy requires confidence in the prediction accuracy of the infrared models. In this study, we used soil data from six agricultural fields in eastern Switzerland and calibrated (i) field-specific (local) models and (ii) general models (combining all fields) for soil organic carbon (SOC), permanganate oxidizable carbon (POXC), total nitrogen (N), total carbon (C) and pH using partial least-squares regression. The 30 local models showed a ratio of performance to deviation (RPD) between 1.14 and 5.27, and the root mean square errors (RMSE) were between 1.07 and 2.43 g kg−1 for SOC, between 0.03 and 0.07 g kg−1 for POXC, between 0.09 and 0.14 g kg−1 for total N, between 1.29 and 2.63 g kg−1 for total C, and between 0.04 and 0.19 for pH. Two fields with high carbonate content and poor correlation between the target properties were responsible for six local models with a low performance (RPD &lt; 2). Analysis of variable importance in projection, as well as of correlations between spectral variables and target soil properties, confirmed that high carbonate content masked absorption features for SOC. Field sites with low carbonate content can be combined with general models with only a limited loss in prediction accuracy compared to the field-specific models. On the other hand, for fields with high carbonate contents, the prediction accuracy substantially decreased in general models. Whether the combination of soils with high carbonate contents in one prediction model leads to satisfying prediction accuracies needs further investigation.

Untargeted LC–MS metabolomics reveals the metabolic responses in the Eriocheir sinensis gills exposed to salinity and alkalinity stress

In recent years, saline–alkaline aquaculture development has become an important measure for China to expand its fishery development space to ensure food safety. Previous studies have verified that salinity and alkalinity positively influence the quality of Chinese mitten crabs (Eriocheir sinensis). However, the regulatory mechanism of E. sinensis endures saline–alkaline stress which remains obscure. This study investigated the metabolic changes in puberty-molting E. sinensis gills exposed to freshwater (FW), sodium chloride salinity of 5 ppt (SW), and carbonate alkalinity 10.00 mmol/L (AW) for 50 days using untargeted liquid chromatography-mass spectrometry metabolomics (LC–MS). A total of 5802 (positive-ion mode) and 6520 (negative-ion mode) peaks were extracted by LC–MS, respectively. A total of 188 (50 upregulated and 138 downregulated), 141 (94 upregulated and 47 downregulated), and 130 (87 upregulated and 43 downregulated) significantly regulated metabolites (SRMs) were observed in the FW–SW, FW–AW, and SW–AW treatments, respectively, wherein 42 generic SRMs were also found by Venn diagram analysis. Seven of the top 10 SRMs with the highest (variable importance in projection) VIP values were similarly identified in FW–SW and SW–AW. Integrated analysis of key metabolic pathways revealed glycerophospholipid, choline in cancer, phenylalanine, and butanoate metabolism. Overall, significant differences were observed in the metabolites and key metabolic pathways of E. sinensis gill exposed to salinity and alkalinity stress. These results will be helpful in understanding the environmental adaptability of aquatic crustaceans to saline–alkaline water.

The combination of Fourier-transform infrared spectroscopy with pattern recognition techniques for classification and discrimination of red snapper fish oils

The combination of Fourier-transform infrared spectroscopy with pattern recognition techniques for classification and discrimination of red snapper fish oils

Distinct Changes in Metabolic Profile and Sensory Quality with Different Varieties of Chrysanthemum (Juhua) Tea Measured by LC-MS-Based Untargeted Metabolomics and Electronic Tongue.

Chrysanthemum tea, a typical health tea with the same origin as medicine and food, is famous for its unique health benefits and flavor. The taste and sensory quality of chrysanthemum (Juhua) tea are mainly determined by secondary metabolites. Therefore, the present research adopted untargeted metabolomics combined with an electronic tongue system to analyze the correlation between the metabolite profiles and taste characteristics of different varieties of chrysanthemum tea. The results of sensory evaluation showed that there were significant differences in the sensory qualities of five different varieties of chrysanthemum tea, especially bitterness and astringency. The results of principal component analysis (PCA) indicated that there were significant metabolic differences among the five chrysanthemum teas. A total of 1775 metabolites were identified by using untargeted metabolomics based on UPLC-Q-TOF/MS analysis. According to the variable importance in projection (VIP) values of the orthogonal projections to latent structures discriminant analysis (OPLS-DA), 143 VIP metabolites were found to be responsible for metabolic changes between Huangju and Jinsi Huangju tea; among them, 13 metabolites were identified as the key metabolites of the differences in sensory quality between them. Kaempferol, luteolin, genistein, and some quinic acid derivatives were correlated with the "astringency" attributes. In contrast, l-(-)-3 phenyllactic acid and L-malic acid were found to be responsible for the "bitterness" and "umami" attributes in chrysanthemum tea. Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis showed that the flavonoid and flavonol biosynthesis pathways had important effects on the sensory quality of chrysanthemum tea. These findings provide the theoretical basis for understanding the characteristic metabolites that contribute to the distinctive sensory qualities of chrysanthemum tea.

Relevance of plasma lipoproteins and small metabolites in assessment of nutritional status among patients with severe injuries

BackgroundThis study aimed to identify plasma lipoproteins and small metabolites associated with high risk of malnutrition during intensive care unit (ICU) stay in patients with severe injuries. MethodsThis observational prospective exploratory study was conducted at two level-1 trauma centers in the Netherlands. Adult patients (aged ≥18 years) who were admitted to the ICU for more than 48 h between July 2018 and April 2022 owing to severe injuries (polytrauma, as defined by Injury Severity Scores of ≥16) caused by blunt trauma were eligible for inclusion. Overall, 51 patients were included; partial least squares discriminant analysis was used to analyze the relationship of 112 lipoprotein-related components and 23 small metabolites with the risk of malnutrition (modified Nutrition Risk in Critically Ill score). Malnutrition was diagnosed based on Subjective Global Assessment scores. The relationship of lipoprotein properties and small metabolite concentrations with malnutrition (during ICU admission) was evaluated using mixed effects logistic regression. ResultsLower (very) low-density lipoprotein ([V]LDL) (free) cholesterol and phospholipid levels, low particle number, and higher levels of LDL triglycerides were associated with a higher risk of malnutrition (variable importance in projection [VIP] value >1.5). Low levels of most (V)LDL and intermediate-density lipoprotein subfractions and high levels of high-density lipoprotein Apo-A1 were associated with the diagnosis of malnutrition (VIP value >1.5). Increased levels of dimethyl sulfone, trimethylamine N-oxide, creatinine, N, N-dimethylglycine, and pyruvic acid and decreased levels of creatine, methionine, and acetoacetic acid were also indicative of malnutrition (VIP value >1.5). Overall, 14 lipoproteins and 1 small metabolite were significantly associated with a high risk of malnutrition during ICU admission (P <0.05); however, the association did not persist after correcting the false discovery rate (P=0.35 for all). ConclusionIncreased triglyceride in several lipoprotein subfractions and decreased levels of other lipoprotein subfraction lipids and several small metabolites (involved in the homocysteine cycle, ketone body formation, and muscle metabolism) may be indicative of malnutrition risk. Following validation in larger cohorts, these indicators may guide institution of preventive nutritional measures in patients admitted to the ICU with severe injuries.