OPLS-DA Model Research Articles

Aroma Identification and Traceability of the Core Sub-Producing Area in the Helan Mountain Eastern Foothills Using Two-Dimensional Gas Chromatography and Time-of-Flight Mass Spectrometry and Chemometrics.

The combination of volatile compounds endows wines with unique aromatic characteristics and is closely related to their geographical origins. In the pursuit of origin identification and the subdivision of homogeneous production areas, clarifying the characteristics of production areas is of great significance for improving wine quality and commercial value. In this study, GC×GC-TOFMS technology was used to analyze the aroma characteristics of "Cabernet Sauvignon" wines from 26 wineries in the Helan (HL), Yinchuan (YC), Yongning (YN), Qingtongxia (QTX), and Hongsibu (HSP) sub-producing areas in the eastern foothills of Helan Mountain in Ningxia, China. The results indicate a gradual increase in relative humidity from the southern part of Ningxia, with the YN sub-region showing optimal fruit development and the QTX region having the highest maturity. A total of 184 volatile compounds were identified, with 36 compounds with an OAV > 1, crucial for the aroma profiles of primarily fermentation-derived alcohols and esters. An aromatic vector analysis revealed that "floral" and "fruity" notes are the primary characteristics of Cabernet Sauvignon wines from the Helan Mountain East region, with lower maturity aiding in the retention of these aromas. By constructing a reliable OPLS-DA model, it was determined that 15 substances (VIP > 1) played a crucial role in identifying production areas, among which phenylethyl alcohol and isoamyl alcohol were the main contributors. In addition, a Pearson correlation analysis showed a negative correlation between sunlight duration during the growing season and benzyl alcohol accumulation, while a significant positive correlation was observed during the ripening period. Due to the critical role of phenyl ethanol in identifying producing areas, this further demonstrates that sunshine conditions may be a key factor contributing to the differences in wine flavor across regions. This study offers a theoretical foundation for understanding the relationship between climatic factors and flavor characteristics, addressing the issue of wine homogenization in small production areas, clarifying typical style characteristics, and establishing a traceability technology system based on characteristic aroma.

The appearance, active components, antioxidant activities, and their markers in fibrous roots of Bletilla striata.

This study explores the potential medicinal properties of Bletilla striata fibrous roots by comparing their active ingredient contents and antioxidant activity with those in tubers. The study further examines the effects of growth age and origin on the distribution characteristics of medicinal properties in fibrous roots and identifies biomarkers that distinguish these characteristics. The Δ E value of fibrous roots significantly increases with age and is significantly influenced by origin; both the age and origin also significantly affect militarine content and antioxidant activity; a positive correlation exists between appearance quality, active ingredients, and antioxidant activity. The total phenolic content and antioxidant activity of fibrous roots significantly exceed those of tubers. The militarine content in both 1-year-old and 2-year-old fibrous roots complies with the 2020 edition of the Chinese Pharmacopoeia, suggesting that the fibrous roots possess medicinal potential. Additionally, this study demonstrates that the OPLS-DA model can differentiate 1-year-old and non-1-year-old fibrous roots of Bletilla striata and distinguish between their origin.

GC-MS and multivariate analysis reveal partial serum metabolome restoration by bevacizumab in a colon cancer rat model: An untargeted metabolomics investigation

Bevacizumab is an anti-angiogenic therapeutic agent that targets vascular endothelial growth factor (VEGF) and has been approved for the treatment of several types of cancer, including colon cancer. Herein, a GC-MS based metabolomics approach was employed to investigate the impact of bevacizumab on the serum metabolome of colon cancer rats. Multivariate chemometric analysis models such as PCA and PLS-DA showed a clear separation between the control, cancer and bevacizumab-treated groups, suggesting that bevacizumab administration induced significant metabolic alterations. Furthermore, pairwise comparisons between the studied groups using the OPLS-DA model in addition to univariate analysis identified several discriminatory metabolites belonged to various chemical classes including amino acids, organic acids and fatty acids that were perturbed between the studied groups. Interestingly, bevacizumab treatment was able to partially restore some of the cancer-induced metabolic disturbances, indicating its potential therapeutic efficacy via improving the tumor vasculature and nutrient delivery. Besides, pathway analysis of the differential metabolites identified key metabolic pathways affected by bevacizumab, which included valine, leucine and isoleucine metabolism, pyruvate metabolism and butanoate metabolism. However, little effects were observed on lipid metabolites such as palmitic acid and stearic acid and consequently their related metabolic pathways such as fatty acid biosynthesis metabolism suggesting that bevacizumab has more prominent effect on energy and amino acid metabolisms as compared to fatty acid metabolism in colon cancer rats. Overall, our study provided novel insights into the metabolic mechanisms underlying the therapeutic effects of bevacizumab in colon cancer rats via the use of a comprehensive GC-MS metabolomics approach.

Optimizing geographical traceability models of Chinese Lycium barbarum: Investigating effects of region, cultivar, and harvest year on nutrients, bioactives, elements and stable isotope composition

Lycium barbarum is a type of “medicine-food homology” whose geographical origin has attracted strong interest from consumers due to different regional quality characteristics. A sophisticated OPLS-DA model to verify Lycium barbarum origin was developed using 266 samples gathered from five cultivars in two regions between 2020 and 2022, which was based on 67 indices, including nutrients, bioactives, elements and stable isotopes. Twelve variables (fructose, δ2H, glucose, tartaric acid, Mo, Na, Sr, His, Phe, Mn, Lys and Rb) were selected to refine models that could distinguish Lycium barbarum origin without being impacted by cultivar or year. The model of training set and testing set samples had discrimination rates of 100 % and 94.71 % to 98.28 %, suggesting an optimized multi-variate analysis strategy using OPLS-DA model could correctly predict the origin of blind Lycium barbarum samples. This study provides new evidence for constructing a reliable traceability model for the geographical origins of Lycium barbarum.

Characterisation of the volatile compounds in nine varieties and three breeding selections of celery using GC–IMS and GC–MS

Celery (Apium graveolens L.) is a popular vegetable crop planted worldwide. In this study, the volatile compound characteristics of three A. graveolens var. dulce varieties (type D), and six A. graveolens var. secalinum varieties (type S), and three breeding selections were analysed and 41 and 73 volatile compounds were identified using GC–MS and GC–IMS, respectively. The results showed that type S emitted more terpenes and phthalides than type D varieties. Both GC–MS and GC–IMS could discriminate between type S and type D. Six potential biomarkers, i.e., sabinene, (E)-caryophyllene, α-phellandrene, limonene, γ-terpinene, and hexanal, were identified using both models. Both GC–MS and GC–IMS could discriminate between parent and breeding selection. The relative contents of seven (GC–IMS OPLS–DA model) and ten (GC–MS OPLS–DA model) volatile compounds showed over-parent heterosis. This study provides a technical reference for distinguishing celery varieties in the same habitat and preliminarily reveals the aroma relationship between breeding selections and their parents.

Metabolome classification of Tongkat Ali (Eurycoma longifolia jack) and its commercial products via UHPLC-QTOF-MS-MS and its protective effect against 5-flurouracil-Induced testicular toxicity in male rats

Ethnopharmacological relevanceTongkat Ali (Eurycoma longifolia Jack) is a chief herbal medicine that is well recognized for its aphrodisiac properties, available in various commercial products worldwide. Aim of the studyThe aim of this work is to identify the different classes of secondary metabolites present in Tongkat Ali commercial products versus authenticated root, and to assess its root extract mitigative effect against 5-flurouracil (5FU)-induced testicular toxicity. Materials and methodsHigh-resolution UHPLC-QTOF-MS/MS metabolites analysis was utilized on the ethanolic Tongkat Ali extract (TAE) parallel to three Mlayasian commercial products, followed by a multivariate data analysis to understand the variability among UHPLC-MS metabolites datasets. Adult male rats were treated with 5-Fluorouracil (5FU) ± Tongkat Ali extract. Semen parameters, serum testosterone, LH, and FSH, and testicular oxidative stress biomarkers like malondialdehyde (MDA) levels, Nuclear factor kappa B (NF-κB) and erythroid 2–related factor 2 (Nrf2) were analyzed. ResultsThe main categories of secondary metabolites identified through UHPLC-MS/MS profiling were quassinoids, alkaloids, fatty acids, lignans and coumarins. Long Jack Plus® ELP-2 clustered alongside authentic roots ELR on the negative side, while Naturelle® ELP-1 and Nu-Prep-LEAKI® ELP-3 were positioned on the opposite side. The OPLS-DA model was used to identify markers for preparations from authentic roots, with commercial products enriching in ailanthone epoxide. In vivo results showed that 5FU reduced sperm parameters by 42%, while TAE improved sperm quality by 35–43% and 58–74% at dose of 400 and 800 mg/kg, respectively. Testosterone, reduced by 74% with 5FU, increased 2.3- to 3.2-fold with TAE. TAE also reduced MDA by 31–62%, NF-κB by 32–55% and increased Nrf2 by 1–2 folds. ConclusionThe manuscript presents a comparative metabolomics study and in vivo investigation into the potential of Tongkat Ali root to improve testicular function in male rats intoxicated with 5FU, an area not previously explored. Further research is required to understand the mechanisms.

The high-resolution molecular portrait of coffee: A gateway to insights into its roasting chemistry and comprehensive authenticity profiles

The direct-infusion of 130 coffee samples into a Fourier-transform ion cyclotron mass spectrometer (FT-ICR-MS) provided an ultra-high resolution perspective on the molecular complexity of coffee: The exceptional resolving power and mass accuracy (± 0.2 ppm) facilitated the annotation of unambiguous molecular formulas to 11,500 mass signals.Utilizing this molecular diversity, we extracted hundreds of compound signals linked to the roasting process through guided Orthogonal Partial Least Squares (OPLS) analysis. Visualizations such as van Krevelen diagrams and Kendrick mass defect analysis provided deeper insights into the intrinsic compositional nature of these compounds and the complex chemistry underlying coffee roasting.Predictive OPLS-DA models established universal molecular profiles for rapid authentication of Coffea arabica versus Coffea canephora (Robusta) coffees. Compositional analysis revealed Robusta specific signals, indicative of tryptophan-conjugates of hydroxycinnamic acids. Complementary LC-ToF-MS2 confirmed their compound class, building blocks and structures. Their water-soluble nature allows for application across raw and roasted beans, as well as in ready-made coffee products.

Rapid and accurate identification of Gastrodia elata Blume species based on FTIR and NIR spectroscopy combined with chemometric methods

Different varieties of Gastrodia elata Blume (G. elata Bl.) have different qualities and different contents of active ingredients, such as polysaccharide and gastrodin, and it is generally believed that the higher the active ingredients, the better the quality of G. elata Bl. and the stronger the medicinal effects. Therefore, effective identification of G. elata Bl. species is crucial and has important theoretical and practical significance. In this study, first unsupervised PCA and t-SNE are established for data visualisation, follow by traditional machine learning (PLS-DA, OPLS-DA and SVM) models and deep learning (ResNet) models were established based on the fourier transform infrared (FTIR) and near infrared (NIR) spectra data of three G. elata Bl. species. The results show that PLS-DA, OPLS-DA and SVM models require complex preprocessing of spectral data to build stable and reliable models. Compared with traditional machine learning models, ResNet models do not require complex spectral preprocessing, and the training and test sets of ResNet models built based on raw NIR and low-level data fusion (FTIR + NIR) spectra reach 100 % accuracy, the external validation set based on low-level data fusion reaches 100 % accuracy, and the external validation set based on NIR has only one sample classification error and no overfitting.

PSIV-24 Evaluation of different colostrum feeding volumes on serum immunoglobulin G concentration and metabolic profiles of calves in high altitude area

Abstract Qinghai-Tibet Plateau is the highest plateau in the world, reputed as “the roof of the world” and “the world’s third pole”. Its ecological environment is characterized by low atmospheric oxygen pressure, cold, and limited feed supplies. This study aimed to investigate the serum immunoglobulin G (IgG) concentration and metabolic profiles of calves in high altitude area (3,650 m) fed different volumes of colostrum [8, 12, or 15% of birth body weight (BW)] using untargeted metabolomics strategies. Neonatal Holstein hybrid heifer calves (n = 44) were randomly divided into 1 of the 3 colostrum feeding amounts: 8% of birth BW (Low volume, L), 12% of birth BW (Middle volume, M), and 15% of birth BW (High volume, H) in colostrum. To safeguard the efficiency of colostrum intake, the colostrum was fed to calves within 0.5 h and 6 h after birth. The serum samples at 24 h after birth were collected for IgG concentration determination by indirect enzyme-linked immunosorbent assay (ELISA) and for LC-MS/MS metabonomic analysis. As the volumes of colostrum increased, there was a linearly increased in the serum IgG concentration (P < 0.01). Differential metabolites were selected according to the following 3 conditions: minimum fold change (FC) > 2, P-value < 0.01 in single-dimensional statistical analysis, and variable importance in projection (VIP) > 1 in the OPLS-DA model. Multivariate statistical analyses were performed to visualize differences among groups. Based on the screening criteria, a total of 3 differential metabolites (22 alpha-Hydroxy-campesterol, N-Myristoyl Histidine, and Calcitetrol) were detected between L and M, of which all differential metabolites were down-regulated. Six differential metabolites were detected between M and H, of which PC[P-18:1(11Z)/18:1(12Z)-2OH(9,10)] was up-regulated and 5 differential metabolites including 1-arachidonoyl-2-hydroxy-sn-glycero-3-phosphate, propanoyl phosphate, ascorbic acid 6-palmitate, 20-hydroxyecdysone, and 6’’’-deamino-6’’’-hydroxyparomomycin II were down-regulated. There were 28 differed metabolites (including leucyl-tryptophan, calcitetrol, 3’’-Oxoribostamycin) between L and H, of which 9 differential metabolites were up-regulated and 19 differential metabolites were down-regulated (Figure 1). Based on KEGG metabolic enrichment pathway analysis and pathway topology analysis, porphyrin metabolism was identified as the most impacted pathway between L and H (Figure 2). In conclusion, increasing colostrum volumes significantly increased serum IgG concentrations at 24 h after birth, favoring the success of the transfer of passive immunity. Alterations in serum metabolome of calves in the Qinghai-Tibet Plateau fed different volumes of colostrum were successfully revealed by untargeted metabolomics. The role of the identified differential metabolites and enriched pathway in the transfer of passive immunity in calves at high altitude deserves further investigation. Keywords: calf, colostrum volumes, high altitude area

Chemometric study on the effect of cooking on bioactive compounds in tomato pomace enriched sauces

Tomato pomace (TP) is an underutilized source of bioactive compounds with potential application in the food sector. A factorial experiment was designed to compare three culinary techniques, Thermomix®, Roner®, and traditional pan-frying, for the preparation of tomato sauces, enriched or not with TP, applying two temperatures and two cooking times. A multivariate analysis was performed on all the results obtained for the metabolites. The addition of TP significantly increased the content of bioactive compounds, especially phenolic compounds. OPLS-DA models were generated using cooking technique, temperature, and time as discriminant factors. The cooking technique had a greater effect on the phenolic content than cooking temperature or time. Thermomix® released bioactive compounds from the tomato into the sauce to a similar extent as pan-frying. Roner® proved to be effective in preserving the volatile fraction of the sauce. The Thermomix® significantly increased the amount of bioactive compounds, while the Roner® increased the volatile compounds.

Effects of Different Fermentation Methods on Flavor Quality of Liupao Tea Using GC-Q-TOF-MS and Electronic Nose Analyses.

To further develop Liupao tea products and enhance their flavor, this study investigated the effects of different fermentation methods on the aroma quality of Liupao tea. The aroma quality of Liupao tea was comprehensively analyzed using HS-SPME in combination with GC-Q-TOF-MS, electronic nose, and sensory evaluations. Electronic nose detection showed that the aroma fingerprints of Liupao tea samples with different fermentation methods were different. Sulfides, alcohols, ketones, and methyls were the main aroma categories affecting the aroma of the four groups of Liupao tea samples. GC-Q-TOF-MS analysis revealed significant differences in the composition of aroma components among the four fermentation methods of Liupao tea (p < 0.05). Furthermore, the total amount of aroma compounds was found to be highest in the group subjected to hot fermentation combined with the inoculation of Monascus purpureus (DMl group). Based on the OPLS-DA model, candidate differential aroma components with VIP > 1 were identified, and characteristic aroma compounds were selected based on OAV > 10. The key characteristic aroma compounds shared by the four groups of samples were 1,2,3-Trimethoxybenzene with a stale aroma and nonanal with floral and fruity aromas. The best sensory evaluation results were obtained for the DMl group, and its key characteristic aroma compounds mainly included 1,2,3-Trimethoxybenzene, nonanal, and cedrol. The results of this study can guide the development of Liupao tea products and process optimization.

Dried Blood Spot Metabolome Features of Ischemic-Hypoxic Encephalopathy: A Neonatal Rat Model.

Hypoxic-ischemic encephalopathy (HIE) is a severe neurological disorder caused by perinatal asphyxia with significant consequences. Early recognition and intervention are crucial, with therapeutic hypothermia (TH) being the primary treatment, but its efficacy depends on early initiation of treatment. Accurately assessing the HIE severity in neonatal care poses challenges, but omics approaches have made significant contribution to understanding its complex pathophysiology. Our study further explores the impact of HIE on the blood metabolome over time and investigated changes associated with hypothermia's therapeutic effects. Using a rat model of hypoxic-ischemic brain injury, we comprehensively analyzed dried blood spot samples for fat-soluble compounds using HPLC-MS. Our research shows significant changes in the blood metabolome after HIE, with a particularly rapid recovery of lipid metabolism observed. Significant changes in lipid metabolites were observed after 3 h of HIE, including increases in ceramides, carnitines, certain fatty acids, phosphocholines, and phosphoethanolamines, while sphingomyelins and N-acylethanolamines (NAEs) decreased (p < 0.05). Furthermore, NAEs were found to be significant features in the OPLS-DA model for HIE diagnosis, with an area under the curve of 0.812. TH showed a notable association with decreased concentrations of ceramides. Enrichment analysis further corroborated these observations, showing modulation in several key metabolic pathways, including arachidonic acid oxylipin metabolism, eicosanoid metabolism via lipooxygenases, and leukotriene C4 synthesis deficiency. Our study reveals dynamic changes in the blood metabolome after HIE and the therapeutic effects of hypothermia, which improves our understanding of the pathophysiology of HIE and could lead to the development of new rapid diagnostic approaches for neonatal HIE.

Unraveling the formation mechanism of aroma compounds in pork during air frying using UHPLC-HRMS and Orbitrap Exploris GC–MS

Lipids are the key matrix for the presence of odorants in meat products. The formation mechanism of odorants of air-fried (AF) pork at 230 °C was elucidated from the perspectives of lipids and heat transfer using physicochemical analyses and multidimensional statistics. Twenty-nine key aroma compounds were identified, with pyrazines predominantly contributing to the roasty aroma of air-fried roasted pork. Untargeted lipidomics revealed 1184 lipids in pork during roasting, with phosphatidylcholine (PC), phosphatidylethanolamine (PE), and triglyceride (TG) being the major lipids accounting for about 60 % of the total lipids. TG with C18 acyl groups, such as TG 16:1_18:1_18:2 and TG 18:0_18:0_20:3, were particularly significant in forming the aroma of AF pork. The OPLS-DA model identified seven potential biomarkers that differentiate five roasting times, including PC 16:0_18:3 and 2-ethyl-3,5-dimethylpyrazine. Notably, a lower specific heat capacity and water activity accelerated heat transfer, promoting the formation and retention of odorants in AF pork.

Revealing the comprehensive effect of mechanization on sauce-flavor Daqu through high-throughput sequencing and multi-dimensional metabolite profiling

Mechanization has emerged as a focal point in the modernization of traditional enterprises, offering standardized production and labor reduction benefits. However, little is known about how mechanization affects the microbiota and metabolite profiles of Daqu. To address this gap, we conducted a comprehensive comparison between traditional and mechanical sauce-flavor Daqu using a multi-omics approach. Results showed that mechanical Daqu exhibited higher acidity, amino acid nitrogen and enzyme activity, alongside lower fat and moisture levels. Following mechanization, lactic acid bacteria (LAB), Staphylococcus, Aspergillus and Saccharomycopsis were enriched and identified as biomarkers, whereas Oceanobacillus, Monascus and Scopulariopsis were notably decreased. Furthermore, significant disparities in metabolic profiles were observed between the two types of Daqu based on GC–MS, GC-IMS, and LC-MS/MS analyses. The content of volatile compounds was significantly higher in mechanical Daqu (332.82 ± 22.69 mg/kg), while that of non-volatile compounds was higher in traditional Daqu (753.44 ± 41.82 mg/kg). Moreover, OPLS-DA models identified 44 volatile and 31 non-volatile compounds as differential metabolites. Multivariate statistical analysis indicated that bacteria and fungi primarily contributed to protease and saccharification activities, respectively. Additionally, the co-occurrence network revealed that Oceanobacillus and Scopulariopsis were closely associated with non-volatile compound formation, while LAB and Rhizopus significantly influenced volatile compound production. These findings elucidate the multi-dimensional relationship between mechanization and Daqu quality, offering insights to advance the modernization of traditional industries.

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

BackgroundMetabolomics 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. ResultsSystematic 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). SignificanceThis 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.

Authentication of oats and discrimination from their gluten-containing adulterants using NIR diffuse reflectance spectroscopy and multivariate analysis

Oat (Avena sativa L.) is recognized for its nutritional value and gluten-free status, however, ensuring its authenticity and purity is crucial, given the potential for contamination with gluten-containing grains. In this study, near-infrared spectroscopy coupled with chemometrics were employed to authenticate oat flour (from different forms of oat; oat groats, steel-cut and rolled oats) and distinguish it from common gluten-containing adulterants including wheat, farro, triticale, barley, rye, and ryegrass. Both unsupervised and supervised chemometric methodologies, encompassing PCA, SIMCA, and OPLS-DA, were applied. Both SIMCA and OPLS-DA models displayed 100% sensitivity, enabling reliable identification of oat flour and detection of potential adulteration with these gluten-containing grains with specificity of 97.78% and 100%, respectively. In the SIMCA model for oat groats and adulterated mixtures, samples with 1% and 2% adulteration were incorrectly classified as oat groats, yet successful discrimination from deliberately-adulterated mixtures was accomplished through the OPLS-DA model with 100% specificity. Moreover, PLS regression analysis was employed to precisely quantify the levels of adulterants in oat groats flour. The models exhibited reliable performance, as reflected in Root Mean Square Error of Calibration (RMSEC) values. Validation of these models using test samples provided further confirmation of their efficacy in detecting sample adulteration and ensuring product authenticity, all while maintaining a high sample throughput rate.

NMR Metabolite Profiling for the Characterization of Vessalico Garlic Ecotype and Bioactivity against Xanthomonas campestris pv. campestris.

The Italian garlic ecotype "Vessalico" possesses distinct characteristics compared to its French parent cultivars Messidor and Messidrôme, used for sowing, as well as other ecotypes in neighboring regions. However, due to the lack of a standardized seed supply method and cultivation protocol among farmers in the Vessalico area, a need to identify garlic products that align with the Vessalico ecotype arises. In this study, an NMR-based approach followed by multivariate analysis to analyze the chemical composition of Vessalico garlic sourced from 17 different farms, along with its two French parent cultivars, was employed. Self-organizing maps allowed to identify a homogeneous subset of representative samples of the Vessalico ecotype. Through the OPLS-DA model, the most discriminant metabolites based on values of VIP (Variable Influence on Projections) were selected. Among them, S-allylcysteine emerged as a potential marker for distinguishing the Vessalico garlic from the French parent cultivars by NMR screening. Additionally, to promote sustainable agricultural practices, the potential of Vessalico garlic extracts and its main components as agrochemicals against Xanthomonas campestris pv. campestris, responsible for black rot disease, was explored. The crude extract exhibited a MIC of 125 μg/mL, and allicin demonstrated the highest activity among the tested compounds (MIC value of 31.25 μg/mL).

Critical Review of Selected Analytical Platforms for GC-MS Metabolomics Profiling-Case Study: HS-SPME/GC-MS Analysis of Blackberry's Aroma.

Data processing and data extraction are the first, and most often crucial, steps in metabolomics and multivariate data analysis in general. There are several software solutions for these purposes in GC-MS metabolomics. It becomes unclear which platform offers what kind of data and how that information influences the analysis's conclusions. In this study, selected analytical platforms for GC-MS metabolomics profiling, SpectConnect and XCMS as well as MestReNova software, were used to process the results of the HS-SPME/GC-MS aroma analyses of several blackberry varieties. In addition, a detailed analysis of the identification of the individual components of the blackberry aroma club varieties was performed. In total, 72 components were detected in the XCMS platform, 119 in SpectConnect, and 87 and 167 in MestReNova, with automatic integral and manual correction, respectively, as well as 219 aroma components after manual analysis of GC-MS chromatograms. The obtained datasets were fed, for multivariate data analysis, to SIMCA software, and underwent the creation of PCA, OPLS, and OPLS-DA models. The results of the validation tests and VIP-pred. scores were analyzed in detail.

Physicochemical, Quality and Flavor Characteristics of Starch Noodles with Auricularia cornea var. Li. Powder.

Auricularia cornea var. Li., as an edible mushroom rich in various nutrients, could be widely used in noodle food. This study aimed to investigate the effect of Auricularia cornea var. Li. (AU) powder on the gel properties, structure and quality of starch noodles. Taking the sample without adding AU powder as a control, the addition of AU powder enhanced the peak viscosity, trough viscosity, final viscosity, breakdown, setback, peak time, gelatinization temperature, G' (storage modulus) and G'' (loss modulus). Meanwhile, the incorporation of AU powder significantly enhanced the stability of the starch gel structure and contributed to a more ordered microstructure also promoting the short-term aging of starch paste. In vitro digestion results displayed lower rapid digestibility (21.68%) but higher resistant starch content (26.58%) with the addition of AU powder and increased breaking rate, cooking loss, swelling index and a* and b* values. However, it decreased dry matter content and L*, particularly the reducing sugar content significantly increased to 4.01% (p < 0.05), and the total amino acid content rose to 349.91 mg/g. The GC-IMS library identified 51 VOCs, and the OPLS-DA model classified 18 VOCs (VIP > 1). Overall, the findings indicate that starch noodles with the addition of AU powder may provide greater nutritional quality, gel stability and starch antidigestibility.

Serum metabolism alteration behind different etiology, diagnosis, and prognosis of disorders of consciousness

BackgroundPatients with disorders of consciousness (DoC) exhibit varied revival outcomes based on different etiologies and diagnoses, the mechanisms of which remain largely unknown. The fluctuating clinical presentations in DoC pose challenges in accurately assessing consciousness levels and prognoses, often leading to misdiagnoses. There is an urgent need for a deeper understanding of the physiological changes in DoC and the development of objective diagnostic and prognostic biomarkers to improve treatment guidance.MethodsTo explore biomarkers and understand the biological processes, we conducted a comprehensive untargeted metabolomic analysis on serum samples from 48 patients with DoC. Patients were categorized based on etiology (TBI vs. non-TBI), CRS-R scores, and prognosis. Advanced analytical techniques, including PCA and OPLS-DA models, were employed to identify differential metabolites.ResultsOur analysis revealed a distinct separation in metabolomic profiles among the different groups. The primary differential metabolites distinguishing patients with varying etiologies were predominantly phospholipids, with a notable decrease in glycerophospholipids observed in the TBI group. Patients with higher CRS-R scores exhibited a pattern of impaired carbohydrate metabolism coupled with enhanced lipid metabolism. Notably, serum concentrations of both LysoPE and PE were reduced in patients with improved outcomes, suggesting their potential as prognostic biomarkers.ConclusionsOur study underscores the critical role of phospholipid metabolism in the brain’s metabolic alterations in patients with DoC. It identifies key biomarkers for diagnosis and prognosis, offering insights that could lead to novel therapeutic targets. These findings highlight the value of metabolomic profiling in understanding and potentially treating DoC.