Variable Importance For The Projection Research Articles

Application of preoperative advanced diffusion magnetic resonance imaging in evaluating the postoperative recurrence of lower grade gliomas

BackgroundRecurrence of lower grade glioma (LrGG) appeared to be unavoidable despite considerable research performed in last decades. Thus, we evaluated the postoperative recurrence within two years after the surgery in patients with LrGG by preoperative advanced diffusion magnetic resonance imaging (dMRI).Materials and methods48 patients with lower-grade gliomas (23 recurrence, 25 nonrecurrence) were recruited into this study. Different models of dMRI were reconstructed, including apparent fiber density (AFD), white matter tract integrity (WMTI), diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), neurite orientation dispersion and density imaging (NODDI), Bingham NODDI and standard model imaging (SMI). Orthogonal Partial Least Squares-Discriminant Analysis (OPLS-DA) was used to construct a multiparametric prediction model for the diagnosis of postoperative recurrence.ResultsThe parameters derived from each dMRI model, including AFD, axon water fraction (AWF), mean diffusivity (MD), mean kurtosis (MK), fractional anisotropy (FA), intracellular volume fraction (ICVF), extra-axonal perpendicular diffusivity (De⊥), extra-axonal parallel diffusivity (De∥) and free water fraction (fw), showed significant differences between nonrecurrence group and recurrence group. The extra-axonal perpendicular diffusivity (De⊥) had the highest area under curve (AUC = 0.885), which was significantly higher than others. The variable importance for the projection (VIP) value of De⊥ was also the highest. The AUC value of the multiparametric prediction model merging AFD, WMTI, DTI, DKI, NODDI, Bingham NODDI and SMI was up to 0.96.ConclusionPreoperative advanced dMRI showed great efficacy in evaluating postoperative recurrence of LrGG and De⊥ of SMI might be a valuable marker.

Identification of novel natural anti-browning agents based on phenotypic and metabolites differences in potato cultivars

This study aimed to elucidate the changes of browning-related metabolite in fresh-cut potato and to identify anti-browning agents. Metabolomics and weighted correlation network analysis (WGCNA) were used to identify metabolites and correlate them with potato browning traits. A total of 79 browning trait-positive-related metabolites and 19 browning trait-negative-related metabolites were obtained from four key modules via WGCNA. The accumulation of metabolites with rich reducing groups and acidic groups were found to enhance anti-browning activity in potatoes. Among these metabolites, only L-pyroglutamic acid (L-PA) and ascorbic acid had variable importance for the projection (VIP) values greater than 1.5. In addition, it was found that L-PA inhibited polyphenol oxidase (PPO) activity by lowering pH and interacting with amino acid residues of PPO. L-PA also inhibited the growth of microorganisms in fresh-cut potato. Our results show that L-AP is an effective novel anti-browning agent with antibacterial activity.

Dysregulation of cerebrospinal fluid metabolism profiles in spinal muscular atrophy patients: a case control study

BackgroundSpinal muscular atrophy (SMA) is a neurodegenerative disorder. Although prior studies have investigated the metabolomes of SMA in various contexts, there is a gap in research on cerebrospinal fluid (CSF) metabolomics compared to healthy controls. CSF metabolomics can provide insights into central nervous system function and patient outcomes. This study aims to investigate CSF metabolite profiles in untreated SMA patients to enhance our understanding of SMA metabolic dysregulation.MethodsThis case control study included 15 SMA patients and 14 control subjects. CSF samples were collected, and untargeted metabolomics was conducted to detect metabolites in SMA and control groups.ResultsA total of 118 metabolites abundance were significantly changed between the SMA and control groups. Of those, 27 metabolites with variable importance for the projection (VIP) ≥ 1.5 were identified. The top 5 differential metabolites were N-acetylneuraminic acid (VIP = 2.38, Fold change = 0.43, P = 5.49 × 10–5), 2,3-dihydroxyindole (VIP = 2.33, Fold change = 0.39, P = 1.81 × 10–4), lumichrome (VIP = 2.30, Fold change = 0.48, P = 7.90 × 10–5), arachidic acid (VIP = 2.23, Fold change = 10.79, P = 6.50 × 10–6), and 10-hydroxydecanoic acid (VIP = 2.23, Fold change = 0.60, P = 1.44 × 10–4). Cluster analysis demonstrated that the differentially metabolites predominantly clustered within two main categories: protein and amino acid metabolism, and lipid metabolism.ConclusionsThe findings highlight the complexity of SMA, with widespread effects on multiple metabolic pathways, particularly in amino acid and lipid metabolism. N-acetylneuraminic acid may be a potential treatment for functional improvement in SMA. The exact mechanisms and potential therapeutic targets associated with metabolic dysregulation in SMA require further investigation.

An efficient method for tracing the geographic origin of Enshi Yulu fresh tea leaves based on near infrared spectroscopy combined with synergy interval PLS and genetic algorithm

This paper applies near-infrared spectroscopy (NIRS) and multiple chemometrics to efficiently distinguish the origins of fresh tea leaves. The key components were obtained using the partial least squares discriminant analysis (PLS-DA) method. PLS, synergy interval PLS (siPLS), principal component analysis (PCA), genetic algorithm (GA), and their combination methods were used to establish NIRS non-destructive discrimination models. Then, the practical application was examined using external samples. The study identified nine key components (variable importance for the projection (VIP) > 1): epigallocatechin, epicatechin, total sugar, water extracts, total catechins, gallocatechin gallate, tea polyphenols, gallocatechin, and epigallocatechin gallate. Of the six NIRS models, the siPLS-GA model that used 37 spectral data points produced the best results (Rp2 = 0.9706, RMSEP = 0.0772, RPD = 6.59). This model had a prediction accuracy of 96.67% for the prediction set samples and 93.33% for the external samples. It offers a rapid, precise, and non-invasive approach to monitor and regulate the illicit trade of fresh tea leaves, thereby guaranteeing the authenticity of Enshi Yulu products from the processing source and fostering the long-term prosperity and stability of the Enshi Yulu tea industry.

Мultivariate analysis for rapid screening and prediction of solid-state compatibility in pharmaceutical preformulation studies-paving the road for machine learning

Multivariate analysis models were developed to evaluate the results obtained from a compatibility study designed for ibuprofen with a large group of different types of excipients, as a possible approach for rapid screening of the incompatibility between the active pharmaceutical ingredient (API) and excipients. The solid-state characterization of the binary mixtures was performed by Fourier transform infrared spectroscopy (FTIR) and differential scanning calorimetry (DSC). Principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) using SIMCA® software were applied for evaluation of the experimentally obtained results. The optimal PCA model for the FTIR spectra explains 96.2 % of the variations in the dataset with good statistical indicators (R2X = 0.960, Q2 = 0.900), which was also the case for the PCA model for the DSC curves (R2X = 0.981, Q2 = 0.866). The applied PLS-DA models have shown similar behaviour to the PCA. Moreover, the main spectral variations in the FTIR spectra and the thermal events in the DSC data were attributed the highest variable importance for the projection (VIP) scores in the corresponding VIP plots, confirming the model capability for predicting ibuprofen interactions. Furthermore, the prediction power of the optimal models for FTIR and DSC experimental data was evaluated by the root mean square error of prediction (RMSEP) of 0.10 and 0.16, respectively. The obtained results demonstrated the potential of multivariate statistical analysis as a machine learning-based technique for screening and prediction of ibuprofen-excipients solid-state compatibility in the preformulation phase of the pharmaceutical development of dosage forms.

Expression and clinical significance of short-chain fatty acids in patients with intrahepatic cholestasis of pregnancy.

Intrahepatic cholestasis of pregnancy (ICP) is a pregnancy-specific liver condition that typically arises in the middle and late stages of pregnancy. Short-chain fatty acids (SCFAs), prominent metabolites of the gut microbiota, have significant connections with various pregnancy complications, and some SCFAs hold potential for treating such complications. However, the metabolic profile of SCFAs in patients with ICP remains unclear. To investigate the metabolic profiles and differences in SCFAs present in the maternal and cord blood of patients with ICP and determine the clinical significance of these findings. Maternal serum and cord blood samples were collected from both patients with ICP (ICP group) and normal pregnant women (NP group). Targeted metabolomics was used to assess the SCFA levels in these samples. Significant differences in maternal SCFAs were observed between the ICP and NP groups. Most SCFAs exhibited a consistent declining trend in cord blood samples from the ICP group, mirroring the pattern seen in maternal serum. Correlation analysis revealed a positive correlation between maternal serum SCFAs and cord blood SCFAs [r (Pearson) = 0.88, P = 7.93e-95]. In both maternal serum and cord blood, acetic and caproic acids were identified as key metabolites contributing to the differences in SCFAs between the two groups (variable importance for the projection > 1). Receiver operating characteristic analysis demonstrated that multiple SCFAs in maternal blood have excellent diagnostic capabilities for ICP, with caproic acid exhibiting the highest diagnostic efficacy (area under the curve = 0.97). Compared with the NP group, significant alterations were observed in the SCFAs of maternal serum and cord blood in the ICP group, although they displayed distinct patterns of change. Furthermore, the SCFA levels in maternal serum and cord blood were significantly positively correlated. Notably, certain maternal serum SCFAs, specifically caproic and acetic acids, demonstrated excellent diagnostic efficiency for ICP.

Integrated characterization of filler tobacco leaves: HS–SPME–GC–MS, E-nose, and microbiome analysis across different origins

This study delves into the aroma characteristics and microbial composition of filler tobacco leaves (FTLs) sourced from six distinct cigar-growing regions within Yunnan, China, following standardized fermentation. An integrated approach using gas chromatography-mass spectrometry (GC–MS), electronic nose (E-nose), and microbiome analysis was employed for comprehensive profiling. Results derived from Linear Discriminant Analysis (LDA) using E-nose data confirmed the presence of notable variability in flavor substance profiles among the FTLs from six regions. Additionally, GC–MS was used to discern disparities in volatile organic compound (VOC) distribution across FTLs from these regions, identifying 92, 81, 79, 58, 69, and 92 VOCs within each respective sample set. Significantly, 24 VOCs emerged as pivotal determinants contributing to the heterogeneity of flavor profiles among FTLs from diverse origins, as indicated by Variable Importance for the Projection (VIP) analysis. Furthermore, distinctions in free amino acid content and chemical constituents were observed across FTLs. Of noteworthy significance, solanone, isophorone, durene, (-)-alpha-terpineol, and 2,3'-bipyridine exhibited the strongest correlations with microbiome data, with fungal microorganisms exerting a more pronounced influence on metabolites, as elucidated through two-way orthogonal partial least-squares (O2PLS) modeling. These findings provide a theoretical and technical basis for accurately evaluating the synchronization of FTLs in aromas and fermentation processes, and they will enhance the quality of fermented FTLs and foster the growth of the domestic cigar tobacco industry ultimately.Graphical

Case study on the influence of serving temperature on the aroma release and perception of Huangjiu, a fermented alcoholic beverage

Serving temperature plays a crucial role in influencing the sensory experience of consumers. In this context, this study investigated the influence of serving temperature on the aroma release and perception of a typical fermented alcoholic beverage named Huangjiu. A quantitative sensory description analysis was conducted, determining serving temperature significantly influenced the 17 sensory attributes in both semi-dry and semi-sweet Huangjiu. The variation in the contents of 41 volatiles in the Huangjiu with temperature was investigated using gas chromatography-ion mobility spectrometry, resulting in volatile content significantly increasing above 30 ℃. The partial least squares discriminant analysis was conducted to predict the variable importance for the projection (VIP) of volatiles, and 22 volatiles (VIP > 1) were screened. These 22 volatiles were confirmed as key odorants influenced by serving temperature though aroma addition experiments. The findings would provide a reference for the effects of serving temperature on the flavor perception of fermented alcoholic beverages.

Effects of defatting and cooking methods on pig large intestines volatile compounds by flavor omics and fatty acids

Pig large intestines (PLIs) are a food with a selective preference globally because of characteristic odors. To investigate the effect of defatting and different cooking methods on the volatile compounds of PLIs, defatted and nondefatted samples were cooked using steaming, water boiling, and frying. A total of 63 volatiles were identified, including 22 compounds detected in all samples. Using odor activity value (OAV) and sensory evaluation, 3-methyl indole and p-cresol, with animal and fecal odors, respectively, were identified as the key off-odors of PLIs. The three cooking methods increased the concentration of aldehydes and endowed samples with fatty and green odors derived from lipid oxidation, especially C18:1n9c and C18:2n6c. Frying significantly increased the content of (E)-2-heptenal and (E,E)-2,4-decadienal (P < 0.05) due to higher contents of C18:2n6c. Compared with steaming and frying, water boiling could significantly reduce the occurrence of off-odors and had the best result combined with defatting. Using orthogonal partial least squares-discriminant analysis (OPLS-DA) and variable importance for the projection (VIP), p-cresol could act as a marker to discriminate samples with different treatments.

Metabolomic study on urine of chronic inflammation rats treated with Buyang Huanwu Decoction based on UPLC-Q-TOF-MS

The study investigated the effect of Buyang Huanwu Decoction(BYHWD) on endogenous biomarkers in the urine of rats with chronic inflammation induced by lipopolysaccharide(LPS) using ultra-high performance liquid chromatography-quadrupole-time-of-flight-mass spectrometry(UPLC-Q-TOF-MS), aiming to elucidate the molecular mechanism underlying the therapeutic effect of BYHWD on chronic inflammation from a metabolomics perspective. Male SD rats were randomly divided into a normal group, a model group, and low-, medium-, and high-dose BYHWD groups(7.5, 15, and 30 g·kg~(-1)). The model group and BYHWD groups received tail intravenous injection of LPS(200 μg·kg~(-1)) on the first day of each week, followed by oral administration of BYHWD once a day for four consecutive weeks. Urine samples were collected at the end of the administration period, and UPLC-Q-TOF-MS was used to analyze the metabolic profiles of the rat urine in each group. Multivariate statistical analysis methods such as principal component analysis(PCA), partial least squares-discriminant analysis(PLS-DA), and orthogonal partial least squares-discriminant analysis(OPLS-DA) were used to analyze the effect of BYHWD on endogenous metabolites. One-way ANOVA and variable importance for the projection(VIP) were used to screen for potential biomarkers related to chronic inflammation. The identified biomarkers were subjected to pathway and enrichment analysis using MetaboAnalyst 5.0. A total of 25 potential biomarkers were screened and identified in the rat urine in this experiment. Compared with the normal group, the model group showed significant increases in the levels of 14 substances(P&lt;0.05) and significant decreases in the levels of 11 substances(P&lt;0.05). BYHWD was able to effectively reverse the trend of most endogenous biomarkers. Compared with the model group, BYHWD significantly down-regulated 13 biomarkers(P&lt;0.05) and up-regulated 10 biomarkers(P&lt;0.05). The metabolic products were mainly related to the biosynthesis of pantothenic acid and coenzyme A, tryptophan metabolism, retinol metabolism, and propionate metabolism. BYHWD has therapeutic effect on chronic inflammation induced by LPS, which may be related to its ability to improve the levels of endogenous metabolites, enhance the body's anti-inflammatory and antioxidant capabilities, and restore normal metabolic activity.

GC × GC-ToF-MS combined with multivariate statistical methods to explore the effects of L. paracasei fermentation on bread flavor characteristics

GC × GC-ToF-MS is increasingly used to analyze complex food flavors due to its high resolution and sensitivity, but few studies have used the method to identify aroma components of bread. For the first time, this study combines GC × GC-ToF-MS and multivariate statistical methods to explore the effects of L. paracasei fermentation on bread flavor characteristics. A total of 1534 volatile organic compounds were identified, of which 447 were obtained by metabolome normalization. Based on the variable importance for the projection and p values, 82 different compounds were screened in L. paracasei bread compared with yeast bread, and the total relative content was 1.52 times higher than that of yeast bread. 2-Furancarboxaldehyde, 5-methyl-, pentanoic acid, 2-hydroxy-4-methyl-, ethyl ester, pyrazine, 2,5-dimethyl- and γ-terpinene are aroma-presenting substances specific to L. paracasei bread that could be potential identification compounds. This study provides a new techno-theoretical approach for the characterization and discrimination of LAB bread flavors.

Plasma metabolic profiling reveals that chromium yeast alleviates the negative effects of heat stress in mid-lactation dairy cows.

Chromium yeast (CY) supplementation has the potential to alleviate the negative effects of heat stress in dairy cows, but the mechanism remains elusive. We aimed to identify the metabolic mechanisms whereby CY supplementation alleviates the negative effects of heat stress in mid-lactation dairy cows. Twelve Holstein dairy cows with similar milk yield (24.6±1.5kg/d), parity (2 or 3) and days in milk (125±8d) were fed the same basal diet containing 0.09mg of Cr/kg DM. They were allocated randomly to 2 groups: a control group (CON, without CY supplementation) and a CY group (CY, administered 0.36mg Cr/kg DM). The experiment was performed over 8 weeks during a hot summer, in which the mean temperature-humidity index was 79.0±3.13 (>72), indicating that the dairy cows were exposed to heat stress. Chromium yeast supplementation reduced rectal temperature (P=0.032), and increased the lactation performance by increasing the yield of milk (+2.6kg/d), protein, lactose and total solid, and protein and lactose percentages in the milk of the heat-stressed dairy cows (P<0.05). Supplementation with CY increased the serum glucose and thyroxine concentrations, but reduced the urea nitrogen, insulin, and triiodothyronine concentrations on d 56 (P<0.05). Furthermore, plasma metabolomic analysis was performed using liquid chromatography tandem-mass spectrometry, which identified 385 metabolites in the two groups. Subsequently, 16 significantly different metabolites in the plasma, were significantly higher in the CY group (variable importance for the projection >1.0, P<0.05), and found to be involved in 6 Kyoto Encyclopedia of Genes and Genomes pathways, including those involved in nicotinate and nicotinamide metabolism. Specifically, plasma concentration of nicotinamide was higher after CY supplementation, which might also contribute to the reduction of rectal temperature, the regulation of glucose homeostasis, and an improvement in the lactation performance of heat-stressed dairy cows. In conclusion, CY supplementation reduces rectal temperature, influences metabolism by reducing serum insulin concentration and increasing serum glucose and plasma nicotinamide concentrations, and finally increases lactation performance of heat-stressed dairy cows.

Interrelation between factors controlling sediment yield in the largest catchment of Peninsular India

The catchment area of the Godavari in Peninsular India shows complex heterogeneous morphologic, climatic, and geological settings. Although the sub-basins of the Godavari indicate a great spatial variation in sediment yield, the role of such morpho-climatic heterogeneity in the sediment yield variation is poorly understood. This study aims to analyze the role of geomorphology, lithology, precipitation, and land use on spatial sediment yield variation in the Godavari basin. Using digital topography data, with the aid of a Geographical Information System (GIS), we delineated 25 sub-basins based on gauging station locations and showed a wide variation of sediment yield, ranging from 28 to 3404 t km−2 yr−1. Several geomorphic attributes were found to be co-dependent; then, we utilized the partial least-square regression (PLSR) technique to recognize the relationship between controlling factors with sediment yield and established a predictive model. Furthermore, we quantitatively determined the most important first-order controlling factors using variable importance for the projection (VIP) method. The results of PLSR and VIP revealed that among 20 geomorphic variables, plan curvature (VIP = 1.61), profile curvature (1.61), LS factor (VIP = 1.51), topographic ruggedness index (VIP = 1.51), slope (VIP = 1.51), topographic wetness index (VIP = 1.29), and steepness index (VIP = 1.06) exert first-order control in sediment yield variation. Moreover, Mesozoic and Precambrian rocks in agricultural, forested, and bare-ground environments collectively play a crucial role under the influence of differential rainfall patterns in the spatial variation of sediment yield as indicated by VIP values higher than 1. Our optimal PLSR model explained 62% of the total variance in average sediment yield with a moderate predictive ability value (Q2 = 0.46). The insights obtained from the results of this study can be utilized for basin-specific erosion and hydrological modeling in a similar environment. Moreover, this study can be helpful to planners and policymakers for better erosion management and soil–water conservation measures in the Godavari basin.

Characterization of key sweet taste compounds in Camellia nanchuanica black tea

Camellia nanchuanica gained attention for having original tea tree characteristics and producing black tea with appealing sweetness. To better study the sweet taste of Camellia nanchuanica black tea, 30 kinds of Camellia nanchuanica black tea (NCBT) samples were classified into three types (high, middle and low sweetness) according to the differences in sweetness. A total of 844 metabolites were detected in NCBT; among them, there were 155 differential metabolites. Four differential metabolites (phloridzin, dulcitol, l-alanine, and sucrose) positively correlated with sweetness and showed higher VIP (variable importance for the projection) values (>1), which made main contributions to the sweetness of NCBT. Phloridzin and l-alanine might be the key sweet compounds of NCBT due to higher DoT (dose-over-threshold) values. Addition experiments further verified that phloridzin was the key sweet taste compound because phloridzin significantly increased the sweet taste of low sweetness samples. Notably, although NCBT24, 26, and 28 belonged to high sweetness samples, phloridzin content was lower. Based on the interactions of binary mixture, hyper-addition effects of phloridzin, dulcitol, l-alanine, and sucrose existed in NCBT24, 26 and 28.

Fluoride induced metabolic disorder of endothelial cells

Endemic fluorosis is a global public health problem. Cardiovascular diseases caused by fluoride are closely related to endothelial cell injury. Metabolism disorder of endothelial cells (ECs) are recognized as the key factor of endothelial dysfunction which has been a hot topic in recent years. However, the toxic effect of fluoride on vascular endothelium has not been elucidated. The aim of this study was to explore the alteration of endothelial cell metabolites in Human Umbilical Vein Endothelial Cells (HUVECs) exposed to NaF using LC-MS/MS technique. The screening conditions were Variable Importance for the Projection (VIP) > 1 and P < 0.05. It was found that the expression of the metabolites Lumichrome and S-Methyl-5′-thioadenosine was upregulated and of the other metabolites, such as Creatine, L-Glutamate, Stearic acid was downregulated. Differential metabolites were found to be primarily related to FoxO、PI3K/Akt and apoptosis signaling pathways by Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. From the perspective of metabolism, this study explored the possible mechanism of fluoride induced endothelial cell injury which providing theories and clues for subsequent studies.

Effects of Magnesium on Transcriptome and Physicochemical Index of Tea Leaves.

Magnesium (Mg) is one of the essential elements for the growth of tea tree and is extremely important for its development. In this study, we investigated the effect of Mg on the transcriptome and physicochemical indexes of tea leaves, and the results showed that Mg could significantly affect the gene expression of tea leaves. The results of Orthogonal Partial Least-Squares Discriminant Analysis (OPLS-DA) model analysis showed that a total of 300 key genes (Variable Importance for the Projection, VIP > 1) were screened under different concentrations of Mg treatment, among which 140 genes were up-regulated and 160 genes were down-regulated. The bubble map was used to screen the characteristic genes from the above key genes, and a total of 121 representative characteristic genes were obtained, mainly involving 9 metabolic pathways. Among them, gene expression of three metabolic pathways, including porphyrin metabolism, alpha-linolenic acid metabolism and photosynthesis, showed an increasing trend with the increase of Mg concentration, while gene expression of four metabolic pathways, including biosynthesis of secondary metabolites, anthocyanin biosynthesis, ABC transporters, pentose and glucuronate interconversions, showed a decreasing trend. The results of physiological index analysis showed that with the increase of Mg concentration, the photosynthetic physiological index, theanine and soluble sugar content of tea leaves showed an increasing trend, while the content of tea polyphenol, flavone and caffeine showed a decreasing trend. The results of TOPSIS analysis showed that the physiological indexes of tea trees most affected by Mg were chlorophyll, tea polyphenols and flavonoids, while the metabolic pathways most affected by Mg on gene expression were the metabolic pathways and biosynthesis of secondary metabolites. It can be seen that the effects of Mg on tea tree were mainly related to photosynthesis and synthesis of secondary metabolites, and Mg was beneficial for improving the photosynthetic capacity of tea tree, enhancing the accumulation of primary metabolites, and thus increasing tea yield. However, Mg was not conducive to the synthesis of secondary metabolites of tea tree and the accumulation of main quality indexes of tea leaves.

Microbiota structure of traditional starters from around the Tai-hang mountains and their influence on the fermentation properties, aroma profile and quality of Chinese steamed bread.

Steamed bread is a popular staple food in China, and the significant regional differences of the microbiota in traditional starters make the flavor and quality of steamed bread highly variable along with long preparation times. Therefore, analyzing the microbial flora of traditional starters and their influences on the flavor and quality may help to solve the problems mentioned earlier, and it may also be conducive to potentially meet consumer needs and permit industrialization of this traditional fermented food. One hundred and thirty-two fungal and 50 bacterial species were identified in five traditional starters, each with a different dominant genus. The fermentation properties of dough showed that total titratable acid, dough volume and gas production increased and the pH decreased with fermentation time. The traditional starters improved the quality of Chinese steamed bread (CSB) including the crumb structure, specific volume and sensory attributes. Thirty-three aroma compounds with a VIP (variable importance for the projection) > 1 were identified as characteristic aroma compounds. The correlations among the microbiota, aroma and qualities of CSB showed a greater contribution from the bacteria, which was consistent with the predictions of metabolic pathways in the sequenced genomes. The quality of CSB fermented with traditional starters was improved induced by their different microbial profiles, and bacteria made a greater contribution than fungus to the aroma and qualities of CSB. © 2023 Society of Chemical Industry.

Signatory metabolomics biomarkers of stress, anxiety, and depression: a proof of concept for precision health among university students: A cross-sectional study

Purpose: The highly competitive nature of tertiary education and the pressure to perform academically have increased psychological morbidity like emotional distress. Untargeted metabolomics was used to analyze serum samples of university students for biomarkers and perturbated metabolism due to stress, anxiety, and depression (SAD).Methods: Depression, Anxiety, Stress Scale 21 (DASS-21) was used to assess the severity of SAD in university students. The metabolite fingerprint of each subject was obtained using liquid chromatography-mass spectrometry quadrupole time-of-flight (LC/MS QTOF). The signature metabolites for each trait were determined by projections to latent structures discriminant analysis (PLS-DA) with variable importance for the projection (VIP) score &gt; 1.0 (P&lt;0.05) and subjected to analysis using the area under the receiver operating characteristic curve (AUROC). Potential biomarkers with an area under the curve (AUC) value exceeding 0.65 were identified.Results: Various groups of glycerophospholipids were upregulated in the studied traits. On the other hand, metabolites such as glycocholic acid was upregulated in depression, while hypoxanthine was upregulated in anxiety, and PE-Cer(d14:1(4E)/22:1(13Z)) was upregulated in stress.Conclusion: To our knowledge, this is the first study to assess the relationship of the differentially expressed metabolites in university students of different categories of SAD using the DASS-21 screening tool in Malaysia as we move forward with precision health.

Effects of warming and fertilization on paddy N2O emissions and ammonia volatilization

Several studies have proved the influence of warming to N2O emissions and NH3 volatilization in paddies. However, it is not clear whether the performance is affected by fertilization. Here, we performed a field trial to evaluate the impacts of warming and fertilization on N2O emissions and NH3 volatilization from paddies. A free air temperature increase system was used for the experimental warming treatment (ET), while the control treatment used ambient temperature (AC). Both ET and AC treatments were combined with nitrogen (N) fertilizer (CF) or without fertilizer input (CK). The results showed insignificant interaction effects of warming and fertilization on seasonal cumulative N2O emissions and NH3 volatilization. Compared with AC, seasonal cumulative N2O emissions and ammonia volatilization in the ET treatment increased by 118.44% and 38.41%, respectively. Moreover, fertilization surprisingly stimulated seasonal cumulative N2O emissions and ammonia volatilization; values were 15.91 and 2.35 times higher than those in the CK treatment. These results imply that fertilization could intensify the increasing effect of warming on N2O emissions and ammonia volatilization. The variable importance for the projection (VIP) analysis revealed that soil N transformation (the rates of N mineralization, nitrification, and denitrification) was the key to affecting reactive N loss rather than soil fertility. Additionally, the ammonia volatilization rate increased with ambient temperature and NH4+-N solution concentration in the microsystem. Importantly, there was a "surge" inflection point of the ammonia volatilization rate under both high ambient temperature (30 °C) and NH4+-N concentration (15 mg/L) conditions. Our findings indicate that warming did promote N2O emissions and ammonia volatilization in paddies by accelerating soil N transformation, which might be aggravated by fertilization. Furthermore, the "surge" effect of high ambient temperature and NH4+-N concentration on ammonia volatilization deserves further attention.

Biomarkers for isolated congenital heart disease based on maternal amniotic fluid metabolomics analysis

IntroductionCongenital heart disease (CHD) is one of the most prevalent birth defects in the world. The pathogenesis of CHD is complex and unclear. With the development of metabolomics technology, variations in metabolites may provide new clues about the causes of CHD and may serve as a biomarker during pregnancy.MethodsSixty-five amniotic fluid samples (28 cases and 37 controls) during the second and third trimesters were utilized in this study. The metabolomics of CHD and normal fetuses were analyzed by untargeted metabolomics technology. Differential comparison and randomForest were used to screen metabolic biomarkers.ResultsA total of 2472 metabolites were detected, and they were distributed differentially between the cases and controls. Setting the selection criteria of fold change (FC) ≥ 2, P value < 0.01 and variable importance for the projection (VIP) ≥ 1.5, we screened 118 differential metabolites. Within the prediction model by random forest, PE(MonoMe(11,5)/MonoMe(13,5)), N-feruloylserotonin and 2,6-di-tert-butylbenzoquinone showed good prediction effects. Differential metabolites were mainly concentrated in aldosterone synthesis and secretion, drug metabolism, nicotinate and nicotinamide metabolism pathways, which may be related to the occurrence and development of CHD.ConclusionThis study provides a new database of CHD metabolic biomarkers and mechanistic research. These results need to be further verified in larger samples.