Research of 2D-COS with metabolomics modifications through deep learning for traceability of wine.

To tackle the difficulty of extracting features from one-dimensional spectral signals using traditional spectral analysis, a metabolomics analysis method is proposed to locate two-dimensional correlated spectral feature bands and combine it with deep learning classification for wine origin traceability. Metabolomics analysis was performed on 180 wine samples from 6 different wine regions using UPLC-Q-TOF-MS. Indole, Sulfacetamide, and caffeine were selected as the main differential components. By analyzing the molecular structure of these components and referring to the main functional groups on the infrared spectrum, characteristic band regions with wavelengths in the range of 1000-1400 nm and 1500-1800 nm were selected. Draw two-dimensional correlation spectra (2D-COS) separately, generate synchronous correlation spectra and asynchronous correlation spectra, establish convolutional neural network (CNN) classification models, and achieve the purpose of wine origin traceability. The experimental results demonstrate that combining two segments of two-dimensional characteristic spectra determined by metabolomics screening with convolutional neural networks yields optimal classification results. This validates the effectiveness of using metabolomics screening to determine spectral feature regions in tracing wine origin. This approach effectively removes irrelevant variables while retaining crucial chemical information, enhancing spectral resolution. This integrated approach strengthens the classification model's understanding of samples, significantly increasing accuracy.

Metabolomic analysis reveals Ligilactobacillus salivarius CCFM 1266 fermentation improves dairy product quality.

Previous studies have demonstrated that Ligilactobacillus salivarius CCFM 1266 exhibits anti-inflammatory properties and the capability to synthesize niacin. This study aimed to investigate the fermentative abilities of L. salivarius CCFM 1266 in fermented milk. Metabonomic analysis revealed that fermentation by L. salivarius CCFM 1266 altered volatile flavor compounds and metabolite profiles, including heptanal, nonanal, and increased niacin production. Genomic investigations confirmed that L. salivarius CCFM 1266 possess essential genes for the metabolism of fructose and mannose, affirming its proficiency in utilizing fructooligosaccharides and mannan oligosaccharides. The addition of fructooligosaccharides and mannan oligosaccharides during the fermentation process significantly facilitated the proliferation of L. salivarius CCFM 1266 in fermented milk, with growth exceeding 107 colony-forming units (CFU)/mL. This intervention not only augmented the microbial density but also modified the metabolite composition of fermented milk, resulting in an elevated presence of advantageous flavor compounds such as nonanal, 2,3-pentanedione, and 3-methyl-2-butanone. However, its influence on improving the texture of fermented milk was observed to be minimal. Co-fermentation of L. salivarius CCFM 1266 with commercial fermentation starters indicated that L. salivarius CCFM 1266 was compatible, similarly altering metabolite composition and increasing niacin content in fermented milk. In summary, the findings suggest that L. salivarius CCFM 1266 holds substantial promise as an adjunctive fermentation starter, capable of enhancing the nutritional diversity of fermented milk products.

Fluoride impairs vascular smooth muscle A7R5 cell lines via disrupting amino acids metabolism.

Given the insidious and high-fatality nature of cardiovascular diseases (CVDs), the emergence of fluoride as a newly identified risk factor demands serious consideration alongside traditional risk factors. While vascular smooth muscle cells (VSMCs) play a pivotal role in the progression of CVDs, the toxicological impact of fluoride on VSMCs remains largely uncharted. In this study, we constructed fluorosis model in SD rats and A7R5 aortic smooth muscle cell lines to confirm fluoride impaired VSMCs. Fluoride aggravated the pathological damage of rat aorta in vivo. Then A7R5 were exposed to fluoride with concentration ranging from 0 to 1200 µmol/L over a 24-h period, revealing a dose-dependent inhibition of cell proliferation and migration. The further metabolomic analysis showed alterations in metabolite profiles induced by fluoride exposure, notably decreasing organic acids and lipid molecules level. Additionally, gene network analysis underscored the frequency of fluoride's interference with amino acids metabolism, potentially impacting the tricarboxylic acid (TCA) cycle. Our results also highlighted the ATP-binding cassette (ABC) transporters pathway as a central element in VSMC impairment. Moreover, we observed a dose-dependent increase in osteopontin (OPN) and α-smooth muscle actin (α-SMA) mRNA level and a dose-dependent decrease in ABC subfamily C member 1 (ABCC1) and bestrophin 1 (BEST1) mRNA level. These findings advance our understanding of fluoride as a CVD risk factor and its influence on VSMCs and metabolic pathways, warranting further investigation into this emerging risk factor.

Integrated transcriptomics and metabolomics study of embryonic breast muscle of Jiaji ducks.

Because number of matured muscle fibers in poultry does not increase after birth, the meat yield is mainly determined during embryogenesis. We previously indicated breast muscle grew rapidly from 18th day after hatching (E18) to E27, and almost stopped from E27 to E34 of Jiaji ducks, while the mechanism is unclear. This study utilized RNA-seq to explore the related genes of muscle development and their relationship with small molecule metabolites at E18, E27 and E34 of Jiaji ducks. Several thousand differentially expressed genes (DEGs) were detected among E18, E27 and E34. DEGs expression profiles included 8 trend maps, among which trend 1 was opposite to and trend 6 was consistent with breast muscle development trend of Jiaji ducks. Through joint analysis between trend 1 of DEGs and trend 1 of differential metabolites (DEMs), protein digestion and absorption pathway stood out. The decrease of COL8A2 gene expression will lead to the decrease of arginine content, which will inhibit the development of breast muscle in embryonic Jiaji duck. Similarly, joint analysis between trend 6 of DEGs and trend 6 of DEMs indicated the increase of GAMT gene expression will cause the increase of proline content, and then promote the development of breast muscle of Jiaji duck in embryonic period. These results will be helpful for further understanding the mechanism of muscle yields of Jiaji ducks.

Effects of cold acclimation on serum biochemical parameters and metabolite profiles in Schizothorax prenanti.

BACKGROUND: Environmental temperature is critical in regulating biological functions in fish. S. prenanti is a kind of cold-water fish, but of which we have little knowledge about the metabolic adaptation and physiological responses to long-term cold acclimation. RESULTS: In this study, we determined the physiological responses of S. prenanti serum after 30 days of exposure to 6℃. Compared with the control group, the levels of TC, TG, and LDL-C in the serum were significantly (P < 0.05) increased, and the level of glucose was significantly (P < 0.05) decreased under cold acclimation. Cold acclimation had no effect on the gene expression of pro-inflammatory factors and anti-inflammatory factors of S. prenanti. Metabolomics analysis by LC-MS showed that a total of 60 differential expressed metabolites were identified after cold acclimation, which involved in biosynthesis of amino acids, biosynthesis of unsaturated fatty acids, steroid degradation, purine metabolism, and citrate cycle pathways. CONCLUSION: The results indicate that cold acclimation can alter serum metabolites and metabolic pathways to alter energy metabolism and provide insights for the physiological regulation of cold-water fish in response to cold acclimation.

Optimization and validation of metabolomics methods for feline urine and serum towards application in veterinary medicine.

BACKGROUND: Metabolomics is an emerging and powerful technology that offers a comprehensive view of an organism's physiological status. Although widely applied in human medicine, it is only recently making its introduction in veterinary medicine. As a result, validated metabolomics protocols in feline medicine are lacking at the moment. Since biological interpretation of metabolomics data can be misled by the extraction method used, species and matrix-specific optimized and validated metabolomic protocols are sorely needed. RESULTS: Systematic optimization was performed using fractional factorial experiments for both serum (n = 57) and urine (n = 24), evaluating dilution for both matrices, and aliquot and solvent volume, protein precipitation time and temperature for serum. For the targeted (n = 76) and untargeted (n = 1949) validation of serum respectively, excellent instrumental, intra-assay and inter-day precision were observed (CV ≤ 15% or 30%, respectively). Linearity deemed sufficient both targeted and untargeted (R2 ≥ 0.99 or 0.90, respectively). An appropriate targeted recovery between 70 and 130% was achieved. For the targeted (n = 69) and untargeted (n = 2348) validation of the urinary protocol, excellent instrumental and intra-assay precision were obtained (CV ≤ 15% or 30%, respectively). Subsequently, the discriminative ability of our metabolomics methods was confirmed for feline chronic kidney disease (CKD) by univariate statistics (n = 41 significant metabolites for serum, and n = 55 for urine, p-value<0.05) and validated OPLS-DA models (R2(Y) > 0.95, Q2(Y) > 0.65, p-value<0.001 for both matrices). SIGNIFICANCE: This study is the first to present an optimized and validated wholistic metabolomics methods for feline serum and urine using ultra-high performance liquid chromatography coupled to quadrupole-Orbitrap high-resolution mass spectrometry. This robust methodology opens avenues for biomarker panel selection and a deeper understanding of feline CKD pathophysiology and other feline applications.

Predicting effect of anti-PD-1/PD-L1 inhibitors therapy for hepatocellular carcinoma by detecting plasma metabolite based on UHPLC-MS.

Introduction: Anti-PD-1/PD-L1 inhibitors therapy has become a promising treatment for hepatocellular carcinoma (HCC), while the therapeutic efficacy varies significantly among effects for individual patients are significant difference. Unfortunately, specific predictive biomarkers indicating the degree of benefit for patients and thus guiding the selection of suitable candidates for immune therapy remain elusive.no specific predictive biomarkers are available indicating the degree of benefit for patients and thus screening the preferred population suitable for the immune therapy. Methods: Ultra-high-pressure liquid chromatography-mass spectrometry (UHPLC-MS) considered is an important method for analyzing biological samples, since it has the advantages of high rapid, high sensitivity, and high specificity. Ultra-high-pressure liquid chromatography-mass spectrometry (UHPLC-MS) has emerged as a pivotal method for analyzing biological samples due to its inherent advantages of rapidity, sensitivity, and specificity. In this study, potential metabolite biomarkers that can predict the therapeutic effect of HCC patients receiving immune therapy were identified by UHPLC-MS. Results: A partial least-squares discriminant analysis (PLS-DA) model was established using 14 glycerophospholipid metabolites mentioned above, and good prediction parameters (R2 = 0.823, Q2 = 0.615, prediction accuracy = 0.880 and p < 0.001) were obtained. The relative abundance of glycerophospholipid metabolite ions is closely related to the survival benefit of HCC patients who received immune therapy. Discussion: This study reveals that glycerophospholipid metabolites play a crucial role in predicting the efficacy of immune therapy for HCC.

Metabolomic-derived endotypes of age-related macular degeneration (AMD): a step towards identification of disease subgroups.

Age-related macular degeneration (AMD) is a leading cause of blindness worldwide, with a complex pathophysiology and phenotypic diversity. Here, we apply Similarity Network Fusion (SNF) to cluster AMD patients into putative metabolomics-derived endotypes. Using a discovery cohort of 163 AMD patients from Boston, US, and a validation cohort of 214 patients from Coimbra, Portugal, we identified four distinct metabolomics-derived endotypes with varying retinal structural and functional characteristics, confirmed across both cohorts. Patients clustered into Endotype 1 exhibited a milder form of AMD and were characterized by low levels of amino acids in specific metabolic pathways. Meanwhile, patients clustered into both Endotype 3 and 4 were associated with more severe AMD and exhibited low levels of fatty acid metabolites and elevated levels of sphingomyelins and fatty acid metabolites, respectively. These preliminary findings indicate that metabolomics-derived endotyping may offer a refined strategy for categorizing AMD patients based on their specific pathophysiological underpinnings, rather than relying solely on traditional observational clinical indicators.

Mechanisms of cordycepin in the treatment of pulmonary arterial hypertension in rats based on metabonomics and transcriptomics.

Pulmonary arterial hypertension (PAH) is a fatal disease featured by high morbidity and mortality. Although Cordycepin is known for its anti-inflammatory, antioxidant and immune-enhancing effects, its role in PAH treatment and the underlying mechanisms remain unclear. The therapeutic effects of Cordycepin on rats with PAH were investigated using a monocrotaline (MCT)-induced rat model. The metabolic effects of Cordycepin were assessed based on the plasma metabolome. The potential mechanisms of Cordycepin in PAH treatment were investigated through transcriptome sequencing and validated in pulmonary artery smooth muscle cells (PASMC). Evaluations included hematoxylin and eosin staining for pulmonary vascular remodeling, CCK-8 assay, EDU, and TUNEL kits for cell viability, proliferation, and apoptosis, respectively, and western blot for protein expression. Cordycepin significantly reduced right ventricular systolic pressure (RVSP) and right ventricular hypertrophy index (RVHI) in PAH rats, and mitigated pulmonary vascular remodeling. Plasma metabolomics showed that Cordycepin could reverse the metabolic disorders in the lungs of MCT-induced PAH rats, particularly impacting linoleic acid and alpha-linolenic acid metabolism pathways. Transcriptomics revealed that the P53 pathway might be the primary pathway involved, and western blot results showed that Cordycepin significantly increased P53 and P21 protein levels in lung tissues. Integrated analysis of transcriptomics and metabolomics suggested that these pathways were mainly enriched in linoleic acid metabolism and alpha-linolenic acid metabolism pathway. In vitro experiments demonstrated that Cordycepin significantly inhibited the PDGFBB (PD)-induced abnormal proliferation and migration of PASMC and promoted PD-induced apoptosis. Meanwhile, Cordycepin enhanced the expression levels of P53 and P21 proteins in PD-insulted PASMC. However, inhibitors of P53 and P21 eliminated these effects of Cordycepin. Cordycepin may activate the P53-P21 pathway to inhibit abnormal proliferation and migration of PASMC and promote apoptosis, offering a potential approach for PAH treatment.

ProMENDA: an updated resource for proteomic and metabolomic characterization in depression.

Depression is a prevalent mental disorder with a complex biological mechanism. Following the rapid development of systems biology technology, a growing number of studies have applied proteomics and metabolomics to explore the molecular profiles of depression. However, a standardized resource facilitating the identification and annotation of the available knowledge from these scattered studies associated with depression is currently lacking. This study presents ProMENDA, an upgraded resource that provides a platform for manual annotation of candidate proteins and metabolites linked to depression. Following the establishment of the protein dataset and the update of the metabolite dataset, the ProMENDA database was developed as a major extension of its initial release. A multi-faceted annotation scheme was employed to provide comprehensive knowledge of the molecules and studies. A new web interface was also developed to improve the user experience. The ProMENDA database now contains 43,366 molecular entries, comprising 20,847 protein entries and 22,519 metabolite entries, which were manually curated from 1370 human, rat, mouse, and non-human primate studies. This represents a significant increase (more than 7-fold) in molecular entries compared to the initial release. To demonstrate the usage of ProMENDA, a case study identifying consistently reported proteins and metabolites in the brains of animal models of depression was presented. Overall, ProMENDA is a comprehensive resource that offers a panoramic view of proteomic and metabolomic knowledge in depression. ProMENDA is freely available at https://menda.cqmu.edu.cn .

Unveiling the metabolic landscape of pulmonary hypertension: insights from metabolomics.

Pulmonary hypertension (PH) is regarded as cardiovascular disease with an extremely poor prognosis, primarily due to irreversible vascular remodeling. Despite decades of research progress, the absence of definitive curative therapies remains a critical challenge, leading to high mortality rates. Recent studies have shown that serious metabolic disorders generally exist in PH animal models and patients of PH, which may be the cause or results of the disease. It is imperative for future research to identify critical biomarkers of metabolic dysfunction in PH pathophysiology and to uncover metabolic targets that could enhance diagnostic and therapeutic strategies. Metabolomics offers a powerful tool for the comprehensive qualitative and quantitative analysis of metabolites within specific organisms or cells. On the basis of the findings of the metabolomics research on PH, this review summarizes the latest research progress on metabolic pathways involved in processes such as amino acid metabolism, carbohydrate metabolism, lipid metabolism, and nucleotide metabolism in the context of PH.

Altered gut microbiota and metabolite profiles provide clues in understanding resistant hypertension.

BACKGROUND: Resistant hypertension is a severe phenotype in hypertension that may be driven by interactions between genetic and environmental factors. Specific changes in gut microbiota and metabolites have been shown to influence cardiovascular disease progression. However, microbial and metabolomic changes associated with resistant hypertension remain elusive. METHODS: In this study, the gut microbiome of 30 participants with resistant hypertension, 30 with controlled hypertension, and 30 nonhypertension was characterized using 16S rRNA amplicon sequencing. In addition, the serum metabolome of the same population was assessed by untargeted metabolomics. RESULTS: The alpha diversity of microbiome in the resistant hypertension decreased, and changes were also observed in the composition of the gut microbiota. The resistant hypertension group was characterized by elevated levels of Actinobacteitia and Proteobacteria. Twenty-three genera were found to have significantly different abundances between resistant hypertension and controlled hypertension, as well as 55 genera with significantly different abundances between resistant hypertension and nonhypertension. Compared with the controlled hypertension group, the genera Rothia and Sharpea in resistant hypertension were more abundant. Compared with the nonhypertension group, the genera Escherichia-Shigella , Lactobacillus , Enterococcus were more abundant. Untargeted metabolomics provided distinctly different serum metabolic profiles for the three groups and identified a range of differential metabolites. These metabolites were mainly associated with the pathway of glycerophospholipid metabolism. Furthermore, correlation analysis provided evidence of new interactions between gut microbiota and metabolites in the resistant hypertension. CONCLUSION: In conclusion, our study provides a comprehensive understanding of the resistant hypertension gut microbiota and metabolites, suggesting that treatment resistance in resistant hypertension patients may be related to the gut microbiota and serum metabolites.

NMR-based comparative metabolomics of quiescent muscle cells.

Adult muscle tissue largely comprised of differentiated myofibers also harbors quiescent muscle-resident stem cells (MuSCs) that are responsible for its maintenance, repair and regeneration. Emerging evidence suggests that quiescent MuSCs exhibit a specific metabolic state, which is regulated during physiological and pathological alterations. However, a detailed understanding of the metabolic state of quiescent MuSCs and its alteration during activation and repair is lacking. Direct profiling of MuSCs in vivo is challenging because the cells are rare and dispersed, while isolation and enrichment leads to their activation and loss of quiescence. In this study, we employed 1H-nuclear magnetic resonance (NMR) spectroscopy to profile metabolites in an established culture model of quiescent MuSC-derived myoblasts and compared with activated, proliferative and differentiated muscle cells to determine the state-specific metabolome. We report that the proliferating and differentiated cells are highly enriched in metabolites involved in energy generation, the quiescent state is enriched in metabolites related to phospholipid catabolism (glycerophosphocholine and choline) and depleted for phosphocholine which is enriched in proliferating cells. We propose that the ratio of these metabolites may be useful as a biomarker of MuSC quiescence.

A circular network of adenosine-mediated mitochondrial dysfunction as coregulators of acute myocardial infarction.

This study aims to explore the molecular mechanisms and associated pathways of myocardial infarction (MI). We employed a variety of analytical methods, including Mendelian Randomization (MR) analysis, transcriptome microarray data analysis, gene function and pathway enrichment analysis, untargeted metabolomic mass spectrometry analysis, and gene-metabolite interaction network analysis. The MR analysis results revealed a significant impact of mitochondrial DNA copy number on MI and coronary artery bypass grafting. Transcriptome analysis unveiled numerous differentially expressed genes associated with myocardial ischemia, with enrichment observed in cardiac function and energy metabolism pathways. Metabolomic analysis indicated a significant downregulation of mitochondrial regulation pathways in ischemic myocardium. T500 metabolite quantification analysis identified 90 differential metabolites between MI and Sham groups, emphasizing changes in metabolites associated with energy metabolism. Gene-metabolite interaction network analysis revealed the significant roles of key regulatory molecules such as HIF1A, adenosine, TBK1, ATP, NRAS, and EIF2AK3, in the pathogenesis of myocardial ischemia. In summary, this study provides important insights into the molecular mechanisms of MI and highlights interactions at multiple molecular levels, contributing to the establishment of new theoretical foundations for the diagnosis and treatment of MI.

Untargeted metabolomics in gastric and colorectal cancer patients - preliminary results.

Introduction: Recent years, microbiota-associated aspects have been analysed in multiple disorders regarding cancers. Existing evidence pints that gut microorganisms might take part in tumour origin and therapy efficacy. Nevertheless, to date, data on faecal metabolomics in cancer patients is still strongly limited. Therefore, we aimed to analyse gut untargeted metabolome in gastrointestinal cancer patients (i.e., gastric and colorectal cancer). Patients and methods: There were 12 patients with either gastric (n=4) or colorectal cancer (n=8) enrolled and 8 analysed (n=4 each). Stool samples were collected prior to anti-cancer treatments. Untargeted metabolomics analyses were conducted by means of mass spectrometry. Results: A plethora of metabolites in cancer patients we analysed were noted, with higher homogenity in case of gastric cancer patients. We found that the level of Deoxyguanosine,m/z 266.091,[M-H]-, Uridine,m/z 245.075,[M+H]+, Deoxyguanosine,m/z 268.104,[M]+, 3-Indoleacetic acid,m/z 176.07,[M+H]+, Indoxyl,m/z 132.031,[M-H]-, L-Phenylalanine,m/z 164.073,[M-H]-, L-Methionine,m/z 150.058,[M+NH4]+, was significantly higher in colorectal cancer patients and Ethyl hydrogen malonate,m/z 133.031,[M+H]+ in gastric cancer. Conclusion: The overall insights into untargeted metabolomics showed that most often higher levels of analysed metabolites were detected in colorectal cancer patients compared to gastric cancer patients. The link between gut metabolome and both local and distal metastasis might exist, however it requires confirmation in further multi-centre studies regarding larger sample size.

Metabolomic analysis of retinopathy stages and amputation in type 2 diabetes.

BACKGROUND: Diabetic retinopathy (DR) and limb amputation are frequent complications of diabetes that cannot always be explained by blood glucose control. Metabolomics is a science that is currently being explored in the search for biomarkers or profiles that identify clinical conditions of interest. OBJECTIVE: This study aimed to analyze, using a metabolomic approach, peripheral blood samples from type 2 diabetes mellitus (DM2) individuals, compared with those with diabetic retinopathy and limb amputation. METHODS: The sample consisted of 128 participants, divided into groups: control, DM2 without DR (DM2), non-proliferative DR (DRNP), proliferative DR (DRP), and DM2 amputated (AMP). Metabolites from blood plasma were classified by spectra using nuclear magnetic resonance (NMR), and the metabolic routes of each group using metaboanalyst. RESULTS: We identified that the metabolism of phenylalanine, tyrosine, and tryptophan was discriminant for the DRP group. Histidine biosynthesis, on the other hand, was statistically associated with the AMP group. The results of this work consolidate metabolites such as glutamine and citrulline as discriminating for DRP, and the branched-chain amino acids as important for DR. CONCLUSIONS: The results demonstrate the relationship between the metabolism of ketone bodies, with acetoacetate metabolite being discriminating for the DRP group and histidine being a significant metabolite in the AMP group, when compared to the DM2 group.

[Multi-omics research progress in early-onset colorectal cancer].

Globally, the incidence of early-onset colorectal cancer (EOCRC) among individuals younger than 50 is escalating. Compared to late-onset colorectal cancer, EOCRC exhibits distinct clinical, pathological, and molecular features, with a higher prevalence in the left colon and rectum. However, the occurrence and development of EOCRC is a multi-factor and multi-stage evolution process, which is the result of the mutual effect of environmental, genetic and biological factors, and involves the multi-level regulation mechanism of other organisms. With the development and improvement of high-throughput sequencing technology, the application of multi-omics analysis has become an important development direction to resolve the pathogenesis of complex diseases and individualized treatment plans. This article aims to review the research progress of EOCRC at the multi-omics level, providing a theoretical foundation for earlier diagnosis and more precise treatment of this diseases.

Intercropping with maize and sorghum-induced saikosaponin accumulation in Bupleurum chinense DC. by liquid chromatography-mass spectrometry-based metabolomics.

Bupleuri Radix is an important medicinal plant, which has been used in China and other Asian countries for thousands of years. Cultivated Bupleurum chinense DC. (B. chinense) is the main commodity of Bupleuri Radix. The benefits of intercropping with various crops for B. chinense have been recognized; however, the influence of intercropping on the chemical composition of B. chinense is still unclear yet. In this study, intercropping with sorghum and maize exhibited little effect on the root length, root diameter, and single root mass of B. chinense. Only the intercropping with sorghum increased the root length of B. chinense slightly compared to the monocropping. In addition, 200 compounds were identified by UHPLC-Q-TOF-MS, and metabolomic combined with the Venn diagram and heatmap analysis showed apparent separation between the intercropped and monocropped B. chinense samples. Intercropping with sorghum and maize could both increase the saikosaponins, fatty acyls, and organic acids in B. chinense while decreasing the phospholipids. The influence of intercropping on the saikosaponin biosynthesis was probably related with the light intensity and hormone levels in B. chinense. Moreover, we found intercropping increased the anti-inflammatory activity of B. chinense. This study provides a scientific reference for the beneficial effect of intercropping mode of B. chinense.

Metabolomic pathways in food allergy.

Food allergy (FA) is a widespread issue, affecting as many as 10% of the population. Over the past two to three decades, the prevalence of FA has been on the rise, particularly in industrialized and westernized countries. FA is a complex, multifactorial disease mediated by type 2 immune responses and involving environmental and genetic factors. However, the precise mechanisms remain inadequately understood. Metabolomics has the potential to identify disease endotypes, which could beneficially promote personalized prevention and treatment. A metabolome approach would facilitate the identification of surrogate metabolite markers reflecting the disease activity and prognosis. Here, we present a literature overview of recent metabolomic studies conducted on children with FA.

Differential metabolite analysis of the pharmacodynamic differences between different ratios of Dahuang ()-Taoren () herb pair.

OBJECTIVE: To explore the material basis of the difference of efficacy of Dahuang (Radix Et Rhizoma Rhei Palmati)-Taoren (Semen Persicae) (DT) drugs with different proportions. METHODS: Samples of different ratios of Dahuang (Radix et Rhizoma Rhei Palnati, DH) to Taoren (Semen Persicae, TR) (Group A 1:1, B 2:3, C 3:2) were analyzed based on gas chromatography time-of-flight mass spectrometry untargeted metabolomics technique. RESULTS: A total of 240 primary metabolites were detected. Forty-one differential metabolites involved nine differential metabolic pathways, of which four were closely related to the efficacy of DT in the treatment of heat and blood stasis syndrome. These pathways included the biosynthesis of amino acid (phenylalanine tyrosine and tryptophan), flavonoids, unsaturated fatty acids, and the glycolysis/glycogenesis pathway. CONCLUSION: There are significant differences in the efficacy of different ratios of DT drugs, and their optimal ratio for the treatment of heat and blood stasis syndrome should be 1:1.