Orthogonal Partial Least Squares Discriminant Analysis Research Articles

Neck and shoulder pain and inflammatory biomarkers in plasma among forklift truck operators - A case-control study.

The aim of this study was to investigate a panel of inflammatory biomarkers in plasma from forklift truck operators (FLTOs) and healthy controls, and their relation to neck pain characteristics. From employees in a warehouse, 26 FLTOs were recruited and 24 healthy age- and sex-matched controls (CONs) were recruited via advertisement. The inclusion criterion for FLTOs was that they should operate reach decker and/or counterbalanced tilting mast forklift trucks. All participants were asked to answer a questionnaire covering demographic data, pain intensity numeric rating scale (NRS), anatomical spread, psychological distress, and health aspects. Pain sensitivity was measured using a pressure algometer. Blood samples were collected and analyzed for inflammatory proteins in plasma using a panel of 71 cytokines and chemokines. Multivariate data analysis including orthogonal partial least square-discriminant analysis (OPLS-DA) was performed to identify significant biomarkers. Thirty percent of FLTOs reported NRS > 3 in the neck. Shoulder pain was common in 26% of the FLTOs. Pain and discomfort that most often prevented completion of activities were in the neck (20%), lower back (32%), and hips (27%). The FLTOs reported significantly (p = 0.04) higher levels of anxiety than the CON group and they had significantly lower pressure pain thresholds in the trapezius muscle on both right (p < 0.001) and left sides (p = 0.003). A significant OPLS-DA model could discriminate FLTOs from CON based on nine inflammatory proteins where the expression levels of four proteins were upregulated and five proteins were downregulated in FLTOs compared to CONs. Twenty-nine proteins correlated multivariately with pain intensity. The profile of self-reported health, pain intensity, sensitivity, and plasma biomarkers can discriminate FLTOs with pain from healthy subjects. A combination of both self-reported and objective biomarker measurements can be useful for better understanding the pathophysiological mechanisms underlying work-related neck and shoulder pain.

Characterization of Flavor Compounds in Chinese Indigenous Sheep Breeds Using Gas Chromatography-Ion Mobility Spectrometry and Chemometrics.

This study analyzed the flavor compounds in the meat of four indigenous breeds of Chinese sheep through the use of gas chromatography-ion mobility spectrometry (GC-IMS). GC-IMS provided information on the characteristics and strength of 71 volatile flavor compounds (monomers and dimers), with aldehydes, alcohols and ketones being the most abundant in all types of sheep meat. The compounds with higher intensity peaks in the sheep meat were aldehydes (n-nonanal, octanal, heptanal, 3-methylbutanal, and hexanal), alcohols (1-octen-3-ol, hexanol, and pentanol), ketones (3-hydroxy-2-butanon, 2-butanone, and 2-propanone), esters (methyl benzoate), and thiazole (trimethylthiazole). The volatile flavor components in the meat of the different breeds of sheep obtained via GC-IMS were further differentiated using principal component analysis. In addition, orthogonal partial least squares discriminant analysis (OPLS-DA) and variable importance on projection (VIP) were used to determine the characteristic flavor compounds in the meats of different breeds of sheep, and 21 differentially volatile components were screened out based on having a VIP above 1. These results indicate that GC-IMS combined with multivariate analysis is a convenient and powerful method for characterizing and discriminating sheep meat.

Metabolomic Profiling of Tumor Tissues Unveils Metabolic Shifts in Non-Small Cell Lung Cancer Patients with Concurrent Diabetes Mellitus.

A comprehensive understanding of the exact influence of type 2 diabetes mellitus (T2DM) on the metabolic status of non-small cell lung cancer (NSCLC) is still lacking. This study explores metabolic alterations in tumor tissues among patients with coexisting NSCLC and T2DM in comparison with NSCLC patients. A combined approach of clinical analysis and metabolomics was employed, including 20 NSCLC patients and 20 NSCLC+T2DM patients. Targeted metabolomics analysis was performed on tumor tissues using the liquid chromatography-mass spectrometry (LC-MS) approach. A clear segregation was observed between NSCLC+T2DM and matched NSCLC tissue samples in Orthogonal Partial Least Squares Discrimination Analysis (OPLS-DA). Furthermore, the levels of 7 metabolites are found to be significantly different between diabetes/nondiabetes tumor tissue samples. The related pathways included arginine biosynthesis, glutathione metabolism, arginine and proline metabolism, purine metabolism, biotin metabolism, and histidine metabolism. 3-Phenyllactic acid, carnitine-C5, carnitine-C12, and serotonin showed a positive linear correlation with fasting blood glucose levels in NSCLC patients. Uridine, pipecolic acid, cytosine, and fasting blood glucose levels were found to have a negative correlation. Our results suggest that NSCLC patients with concurrent T2DM exhibit distinct metabolic shifts in tumor tissues compared to those of solely NSCLC patients.

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

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

Traditional Processing Can Enhance the Medicinal Effects of Polygonatum cyrtonema by Inducing Significant Chemical Changes in the Functional Components in Its Rhizomes.

The aims of this study were to explore the significant chemical changes in functional components induced by the traditional processing method and evaluate whether this method based on nine cycles of steaming and drying can effectively enhance the medicinal effects of Polygonatum cyrtonema rhizome. A global analysis on dynamic changes in secondary metabolites during nine processing cycles was performed, and the significantly differentially accumulated secondary metabolites were initially identified based on the secondary metabolome. Unsupervised principal component analysis (PCA), hierarchical clustering analysis (HCA), and orthogonal partial least squares discriminant analysis (OPLA-DA) on secondary metabolites clearly showed that processing significantly increased the global accumulation of secondary metabolites in processed P. cyrtonema rhizomes compared to unprocessed crude rhizomes. The first six processing cycles induced drastic changes in the accumulation of functional components, while the last three did not induce further changes. The accumulations of most functional components were significantly enhanced after the first three cycles and stabilized after six cycles; meanwhile, the first three cycles also led to numerous new components. However, the enhancing effects were unavoidably reversed or weakened under continued processing lasting 6-9 cycles. Furthermore, continued processing also reduced the contents of a small number of original components to undetectable levels. Processing induced some significantly enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, among which the first three processing cycles enhanced the synthesis of various secondary metabolites and significantly affected the metabolisms of amino acids. In conclusion, this study not only reveals that processing can effectively enhance the medicinal effects, by two main mechanisms including enhancing chemical synthesis and inducing structural transformation of functional components, but also provides theoretical guidance for the optimization of the traditional processing method based on nine cycles of steaming and drying for achieving optimal effects on enhancing the medicinal effects of P. cyrtonema rhizome.

LC/MS-Based Untargeted Lipidomics Reveals Lipid Signatures of Sarcopenia.

Sarcopenia, a multifactorial systemic disorder, has attracted extensive attention, yet its pathogenesis is not fully understood, partly due to limited research on the relationship between lipid metabolism abnormalities and sarcopenia. Lipidomics offers the possibility to explore this relationship. Our research utilized LC/MS-based nontargeted lipidomics to investigate the lipid profile changes as-sociated with sarcopenia, aiming to enhance understanding of its underlying mechanisms. The study included 40 sarcopenia patients and 40 control subjects matched 1:1 by sex and age. Plasma lipids were detected and quantified, with differential lipids identified through univariate and mul-tivariate statistical analyses. A weighted correlation network analysis (WGCNA) and MetaboAna-lyst were used to identify lipid modules related to the clinical traits of sarcopenia patients and to conduct pathway analysis, respectively. A total of 34 lipid subclasses and 1446 lipid molecules were detected. Orthogonal partial least squares discriminant analysis (OPLS-DA) identified 80 differen-tial lipid molecules, including 38 phospholipids. Network analysis revealed that the brown module (encompassing phosphatidylglycerol (PG) lipids) and the yellow module (containing phosphati-dylcholine (PC), phosphatidylserine (PS), and sphingomyelin (SM) lipids) were closely associated with the clinical traits such as maximum grip strength and skeletal muscle mass (SMI). Pathway analysis highlighted the potential role of the glycerophospholipid metabolic pathway in lipid me-tabolism within the context of sarcopenia. These findings suggest a correlation between sarcopenia and lipid metabolism disturbances, providing valuable insights into the disease's underlying mechanisms and indicating potential avenues for further investigation.

Effect of cooking methods on flavor profiles of Xuanwei Ham: Analytical insights into aromatic composition and sensory attributes

To examine flavor variations in Xuanwei ham due to different cooking methods, we selected one-year cured Xuanwei ham and applied four techniques: dry frying (DF), baking (BA), steaming (ST), and boiling (BO). Organoleptic evaluation revealed ST received the highest overall sensory score. High-performance liquid chromatography (HPLC) revealed that the total nucleotide content was significantly different (P < 0.05), lactic acid predominated the measured organic acids. Solid-phase microextraction-gas chromatography–mass spectrometry (SPME-GC–MS) and chromatography-electronic nose (GC-E-Nose) data indicated that ST resulting in significantly higher total volatile compounds than the other methods (P < 0.05). SPME-GC–MS detected 55 volatile compounds, and 12 characteristic flavor substances were identified using orthogonal partial least squares discriminant analysis (OPLS-DA) (VIP > 1). This study aimed to support comprehensive research on the flavor characteristics of cooked Xuanwei ham and guide the selection of appropriate processing methods.

Quality evaluation of Qiangli Tianma Duzhong (QLTMDZ) employing UHPLC-MS: A multivariate statistical analysis across multiple dosage forms and manufacturers

Traditional Chinese medicine (TCM) and its preparations have become increasingly popular in recent years. Nonetheless, due to the high complexity of the compounds in Traditional Chinese Patent Medicine (TCPM), the quality differences between different dosage forms and products from various manufacturers pose numerous challenges and difficulties in quality evaluation. The Qiangli Tianma Duzhong (QLTMDZ) prescription, comprising twelve TCM, is widely used in China. Despite its prevalence, current research on QLTMDZ is limited and lacks in-depth and systematic analysis of the chemical composition of the prescription. In this study, a comprehensive strategy was proposed for characterizing the chemical profile of QLTMDZ based on UHPLC-Q-TOF-MS. A total of 122 compounds were identified in QLTMDZ under both positive and negative ion modes. Subsequently, multivariate statistical methods such as principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) were conducted in the MS-DIAL software to further elucidate quality differences among 55 batches of QLTMDZ samples from seven manufacturers. Lastly, multiple reaction monitoring (MRM) mode was utilized in conjunction with UHPLC-QQQ-MS, for the precise quantification of the identified 24 compounds within the QLTMDZ preparation and providing supplementary information in quality evaluation. The established analytical method in this study is sensitive and efficient, enabling qualitative and quantitative analysis of the chemical constituents within QLTMDZ. The application of multivariate statistical analyses effectively discriminates samples based on different dosage forms and manufacturers, thereby providing new research directions and scientific support for further studies on the quality control of the prescription.

Geographic variation in secondary metabolites contents and their relationship with soil mineral elements in Pleuropterus multiflorum Thunb. from different regions

Abstract Background Pleuropterus multiflorum Thunb cv. “Heshouwu” (HSW) has been used as a classical material for both medicine and food in China for millennia. Recently, the cultivation region of HSW has shifted from Guangdong to Sichuan, Guizhou, and other regions. The investigation of geographic variation in bioactive metabolite contents and their relationship with soil mineral elements holds academic significance. Objective This study aimed to investigate the variations in the distribution of active components in HSW across diverse planting regions and their relationship with soil mineral elements. Methods A reliable quantitative analysis based on ultrahigh-performance liquid chromatography with triple-quadrupole mass spectrometry (UPLC-QQQ-MS) was developed to assess the levels of 15 bioactive metabolites in 60 HSW samples collected from 4 distinct regions. A total of 43 soil mineral elements in corresponding 60 soil samples were quantified by inductively coupled plasma mass spectrometry (ICP-MS). Orthogonal partial least squares-discriminant analysis (OPLS-DA), heatmap analysis, Pearson correlation analysis, and random forest (RF) regression were conducted based on the above quantitative data. Results The content of stilbene glycosides displayed a wider range of variation compared with emodin and physcion among different regions. Eight compounds were screened as the differential metabolites in HSW samples from various sources using the supervised OPLS-DA analysis. Among these, 2 important functional compounds including physcion and 2,3,5,4′-tetrahydroxystilbene-2-O-(6″-O-acetyl)-glucoside (THSG-5) are the most abundant in HSW samples from Deqing, a geographical indicative production region. Pearson correlation analysis indicated that the impact of soil mineral elements on the levels of stilbene glycosides is greater compared to that on anthraquinones. A negative correlation was observed between the levels of elements Na, Zn, Ba, Ti, and 2,3,5,4′-tetrahydroxysilbene 2-O-glucoside (THSG-1). Conversely, a positive correlation was found between the contents of elements Na, Ce, Ti, and physcion and THSG-5, 2 components that exhibited higher levels in Deqing. Furthermore, an RF algorithm was employed to establish an interrelationship model, effectively forecasting the abundance of the majority of differential metabolites in HSW samples based on the content data of soil mineral elements. Conclusions The variation of stilbene glycosides is wider than emodin and physcion in HSW. The levels of metabolites in HSW samples are influenced by soil mineral elements, with stilbene glycosides being more susceptible to such influences compared to anthraquinones. Specifically, THSG-1 shows a negative association with most soil mineral elements, notably Na, Zn, Ba, and Ti, whereas the content of physcion displays a positive correlation.

Molecular signatures of normal pressure hydrocephalus: a large-scale proteomic analysis of cerebrospinal fluid

Given the persistent challenge of differentiating idiopathic Normal Pressure Hydrocephalus (iNPH) from similar clinical entities, we conducted an in-depth proteomic study of cerebrospinal fluid (CSF) in 28 shunt-responsive iNPH patients, 38 Mild Cognitive Impairment (MCI) due to Alzheimer’s disease, and 49 healthy controls. Utilizing the Olink Explore 3072 panel, we identified distinct proteomic profiles in iNPH that highlight significant downregulation of synaptic markers and cell-cell adhesion proteins. Alongside vimentin and inflammatory markers upregulation, these results suggest ependymal layer and transependymal flow dysfunction. Moreover, downregulation of multiple proteins associated with congenital hydrocephalus (e.g., L1CAM, PCDH9, ISLR2, ADAMTSL2, and B4GAT1) points to a possible shared molecular foundation between congenital hydrocephalus and iNPH. Through orthogonal partial least squares discriminant analysis (OPLS-DA), a panel comprising 13 proteins has been identified as potential diagnostic biomarkers of iNPH, pending external validation. These findings offer novel insights into the pathophysiology of iNPH, with implications for improved diagnosis.

Untargeted metabolomics using UHPLC-Q-Orbitrap HRMS for identifying cytotoxic compounds on MCF-7 breast cancer cells from Annona muricata Linn leaf extracts as potential anticancer agents.

The leaves of Annona muricata L., known as "soursop" or "sirsak" in Indonesia, are used traditionally for cancer treatment. However, the bioactive components remain largely unidentified. This study used untargeted liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based metabolomics to identify potential cytotoxic compounds in A. muricata leaf extracts on MCF-7 breast cancer cells in vitro. A. muricata leaves were macerated with water, 99% ethanol, and aqueous mixtures containing 30%, 50%, and 80% ethanol. Cytotoxic activity of the extracts against MCF-7 breast cancer cells was determined using the MTT assay. Ultra-high-performance liquid chromatography-Q-Orbitrap high-resolution mass spectroscopy (UHPLC-Q-Orbitrap-HRMS) was used to characterize the metabolite composition of each extract. The correlations between metabolite profile and cytotoxic activities were evaluated using orthogonal partial least square discriminant analysis (OPLS-DA). The binding of these bioactive compounds to the tumorigenic alpha-estrogen receptor (3ERT) was then evaluated by in silico docking simulations. Ninety-nine percent ethanol extracts demonstrated the greatest potency for reducing MCF-7 cell viability (IC50 = 22 μg/ml). We detected 35 metabolites in ethanol extracts, including alkaloids, flavonoids, and acetogenins. OPLS-DA predicted that annoreticuin, squadiolin C, and xylopine, and six unknown acetogenin metabolites, might reduce MCF-7 cell viability. In silico analysis predicted that annoreticuin, squadiolin C, and xylopine bind to 3ERT with an affinity comparable to doxorubicin. Untargeted metabolomics and in silico modeling identified cytotoxic compounds on MCF-7 cells and binding affinity to 3ERT in A. muricata leaf extracts. The findings need to be further verified to prove the screening results.

Metabolic profiling of different parts of Physalis alkekengi L. var. franchetii (Mast.) Makino based on UPLC-Q-Orbitrap-HRMS coupled with bioactivity assays

Physalis alkekengi L.var. franchetii (Mast.) Makino (PAF) is an important edible and medicinal plant resource in China. Historically, phytochemical studies have primarily examined the calyx and fruit due to their long-standing use in traditional Chinese medicine for their ability to clear heat and detoxify. Metabolites and bioactivities of other parts such as the leaves, stems and roots, are rarely studied. The study involved conducting metabolic profiling of five plant parts of PAF using UPLC-Q-Orbitrap-HRMS analysis, in conjunction with two bioactivity assays. A total of 95 compounds were identified, including physalins, flavonoids, sucrose esters, phenylpropanoids, nitrogenous compounds and fatty acids. Notably, 14 aliphatic sucrose esters, which are potentially novel compounds, were initially identified. Furthermore, one new aliphatic sucrose ester was purified and its structure was elucidated by 1D and 2D NMR analysis. The hierarchical clustering analysis and principal component analysis showed the close clustering of the root and stem, suggesting similarities in their chemical composition, whereas the leaf, calyx and fruit clustered more distantly. Orthogonal partial least-squares discriminant analysis results showed that 41 compounds potentially serve as marker compounds for distinguishing among plant parts. Variations in activity were observed among the plant parts during the comparative evaluation with biological assays. The calyx, leaf and fruit extracts showed stronger antibacterial and anti-inflammatory activities than the stem and root extracts, and 19 potential biomarkers were identified by S-plot analysis for the observed activities, including chlorogenic acid, luteolin, cynaroside, physalin A, physalin F, physalin J, apigetrin, quercetin-3β-D-glucoside and five ASEs, which likely explain the observed potent bioactivity.

Impact of Bacillus subtilis on Chinese yellow rice wine (Huangjiu) fermentation: Method variations and flavor analysis

This investigation explores the impact of various fermentation techniques and the inoculation of Bacillus subtilis spores on the physicochemical properties and principal flavor profiles of Huangjiu. Employing sensory analysis, headspace solid-phase microextraction, gas chromatography-tandem mass spectrometry (HS-SPME-GC–MS), and orthogonal partial least squares discriminant analysis (OPLS-DA), we observed that these variables significantly alter the physicochemical attributes of Huangjiu. Our analysis, integrating volatile organic compounds (VOCs) with odor activity values (OAV), revealed that while B. subtilis inoculation modifies the concentrations of key flavor compounds, it does not affect their types. Notably, the inoculation enhances the concentrations of 13 primary flavor compounds, thereby enriching floral and fruity notes while reducing higher alcohol levels. These findings contribute valuable insights into the flavor formation mechanisms of Huangjiu and guide the optimization of fermentation processes.

Discriminating Craft and Industrial Beers by Untargeted Gas Chromatography-Mass Spectrometry (GC-MS) Metabolomics Combined with Multivariate Statistical Analysis

Developing robust analytical methodologies for the discrimination of craft and industrial beer presents a significant yet formidable challenge. The identification and differentiation of products necessitate the utilization of reliable analytical methods, which are indispensable for ensuring market stability and safeguarding consumer interests. In this study, representative samples with a significant market share were selected for headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry (HS-SPME-GC-MS) analysis to compare the volatile substance characteristics of craft and industrial beers. The findings suggested that alcohols and esters constituted the primary volatiles. Craft beer exhibited a higher abundance of both types and concentrations compared to industrial beer. Subsequently, unsupervised and supervised chemometric techniques were employed for further analysis of the data matrix. An orthogonal partial least squares discriminant analysis (OPLS-DA) method was established to effectively discriminate between industrial and craft beers, enabling the identification of characteristic volatile markers. The untargeted GC-MS metabolomics coupled with multivariate statistical analysis holds promise for the authentication of craft and industrial beers.

Comparative analysis of the differences in volatile organic components of three lavender essential oils in Ili region using sensory evaluation, GC-IMS and GC-MS techniques

Lavender (Lavandula angustifolia Mill.) is a widely utilized aromatic plant, with the economic value of its essential oil (EO) largely dependent on its aroma. This study investigated the differences in volatile organic compounds (VOCs) within the EOs of three species of lavender (H70-1, French blue, Taikong blue) in Ili region from 2019 to 2023 with the combination of sensory evaluation, gas chromatography-ion mobility spectrometry (GC-IMS), and gas chromatography-mass spectrometry (GC-MS). The EO from Taikong blue lavender exhibited greater stability in VOC composition compared to the other two varieties. Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) effectively distinguished the aromas of the three EOs aroma. Combining odor activity value (OAV) and variable importance in projection (VIP) values identified five VOCs crucial for discriminating among the three lavender EO types. This study provides theoretical support for the cultivation and commercialization of lavender as an industrial crop, as well as for quality control of EO production in the Ili region.

Exploring accurate mass measurements in pixel-based chemometrics: Advancing coffee classification with GC-HRMS—A proof of concept study

This paper presents a study that assesses the application of chemometrics for classifying coffee samples in a quality control context. High-resolution and accurate mass measurements were utilized as input for pixel-based orthogonal partial least squares discriminant analysis (OPLS-DA) models. The compositional data were acquired through a fully automated workflow combining headspace solid-phase microextraction and gas chromatography-high-resolution mass spectrometry (GC-HRMS) using an FT-Orbitrap® mass analyzer. A workflow centered on accurate mass measurements was successfully utilized for group-type analysis, offering an alternative to methods relying solely on MS similarity searches. The predictive models underwent thorough evaluation, demonstrating robust multivariate classification performance. Five key coffee attributes, bitterness, acidity, body, intensity, and roasting level were successfully predicted using GC-HRMS data. The results revealed strong predictive accuracy across all models, ranging from 88.9 % (bitterness) to 94.4 % (roasting level). This study represents a significant advancement in automating methods for coffee quality control, notably increasing the predictive ability of the models compared to existing literature.

Alkaloid profiling of the new species Corydalis huangshanensis and other 13 medicinal plants in genus Corydalis.

Corydalis DC., the largest genus of Papaveraceae, comprises numerous species known for their abundant alkaloid content and historical use in clinical medicine. Recently, a new species of genus Corydalis named Corydalis huangshanensis Lu Q. Huang & H. S. Peng was discovered in the Huangshan Mountains of Anhui Province, China. To compare the chemical characteristics of C. huangshanensis and other 13 Corydalis species, aiming to elucidate the potential medicinal value of this new species. The chemical constituents of C. huangshanensis and other 13 medicinal plants of genus Corydalis were analyzed using ultra-high-performance liquid chromatography Q-Exactive Plus hybrid quadrupole-Orbitrap mass spectrometer (Q-Orbitrap) mass technology. The differences in the alkaloids in the 14 species were distinguished by chemometrics. The mass spectrometry fragmentation information and relative content of 72 alkaloids were obtained. Orthogonal partial least squares discriminant analysis (OPLS-DA) and cluster heat mapping analysis showed that these 14 species were divided into two groups. The clustering relationship between C. huangshanensis and C. decumbens (Thunb.) Pers. was similar, exhibiting similar chemical compositions and characteristics. These results indicate the potential pharmacological effects of C. huangshanensis. This study enhances our understanding of the chemical classification of Corydalis and provides a basis for speculations on the medicinal value of C. huangshanensis.

A comprehensive analysis of aroma quality and perception mechanism in ginger-infused stewed beef using instrumental analysis, sensory evaluation and molecular docking

The ginger-infused stewed beef exhibited a satisfactory odor in Chinese cooking meat. This study aimed to reveal its aroma quality and perception mechanism through electronic nose, sensory evaluation and gas chromatography–mass spectrometry (GC–MS), gas chromatography-ion mobility spectrometry (GC-IMS) coupled with chemometric methods and molecular docking. Sensory evaluation and electronic nose analysis indicated ginger could greatly modify aroma profile of beef. Most C6-C10 aldehydes significantly decreased and terpenes increased in ginger-infused stewed beef. Orthogonal partial least squares-discriminant analysis (OPLS-DA) found 7 key markers for distinguishing stewed beef with or without ginger. Ginger additions could reduce fatty acids consumption. Moreover, the key contributors of fatty, bloody, meaty, ginger and mint aroma attributes, namely (E)-2-octenal, 1-octen-3-ol, 2-acetylthiazole, zingiberene and γ-elemene, respectively, selected by partial least squares regression (PLSR) analysis were docked with the olfactory receptor. Hydrogen bonds and hydrophobic interactions were the main interaction forces between olfactory receptor and the five compounds.

Evolution of Aroma Profiles in Vitis vinifera L. Marselan and Merlot from Grapes to Wines and Difference between Varieties.

The fermentation process has a significant impact on the aromatic profile of wines, particularly in relation to the difference in fermentation matrix caused by grape varieties. This study investigates the leaching and evolution patterns of aroma compounds in Vitis vinifera L. Marselan and Merlot during an industrial-scale vinification process, including the stages of cold soak, alcohol fermentation, malolactic fermentation, and one-year bottle storage. The emphasis is on the differences between the two varieties. The results indicated that most alcohols were rapidly leached during the cold soak stage. Certain C6 alcohols, terpenes, and norisoprenoids showed faster leaching rates in 'Marselan', compared to 'Merlot'. Some branched chain fatty-acid esters, such as ethyl 3-methylbutyrate, ethyl 2-methylbutyrate, and ethyl lactate, consistently increased during the fermentation and bottling stages, with faster accumulation observed in 'Marselan'. The study combines the Orthogonal Partial Least Squares-Discriminant Analysis (OPLS-DA) model based on odor activity values to elucidate the accumulation of these ethyl esters during bottle storage, compensating for the reduction in fruity aroma resulting from decreased levels of (E)-β-damascenone. The 'Marselan' wine exhibited a more pronounced floral aroma due to its higher level of linalool, compared to the 'Merlot' wine. The study unveils the distinctive variation patterns of aroma compounds from grapes to wine across grape varieties. This provides a theoretical framework for the precise regulation of wine aroma and flavor, and holds significant production value.

Metabolic profiling of Citrus maxima L. seedlings in response to cadmium stress using UPLC-QTOF-MS

Cadmium (Cd) pollution significantly reduces agricultural crop yields. In our research, metabolomic changes in Citrus maxima L. subjected to Cd stress were investigated using ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS) in tandem with multivariate analytical techniques. This integrative method, coupled with physiological evaluations, aimed to elucidate the core adaptive mechanisms to Cd stress. We found that under Cd stress, C. maxima seedlings exhibited elevated levels of reactive oxygen species, malondialdehyde, and electrolyte leakage. Furthermore, principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) demonstrated distinct a separation of the metabolome among the different treatment groups under Cd stress, indicating dynamic metabolic changes. Metabolic analysis suggested that genes involved are initially induced by Cd treatment, followed by the activation of the flavonoid biosynthesis pathway. This investigation provides new insights into the complex metabolic responses of C. maxima seedlings to Cd exposure.