Multivariate Statistical Analysis Research Articles

Metabolomics distinguishes different grades of Scrophularia ningpoensis hemsl: Towards a biomarker discovery and quality evaluation

In managing unique complexities associated with Chinese medicinal quality assessment, metabolomics serves as an innovative tool. This study proposes an analytical approach to assess differing qualities of Scrophularia ningpoensis （S. ningpoensis）Hemsl by identifying potential biomarker metabolites and their activity with the corresponding secondary metabolites. The methodology includes four steps; first, a GC-MS based metabolomics exploration of the Scrophularia ningpoensis Hemsl. Second, a multivariate statistical analysis (PCA, PLS-DA, OPLS-DA) for quality assessment and biomarker identification. Third, the application of ROC analysis and pathway analysis based on identified biomarkers. Finally, validation of the associated active ingredients by HPLC. The analysis showed distinct metabolite profiles across varying grades of S. ningpoensis Hemsl, establishing a grading dependency relationship. Select biomarkers (gluconic Acid, d-xylulose, sucrose, etc.) demonstrated robust grading performances. Further, the Pentose Phosphate Pathway, deemed as most influential in grading, was tied to the synthesis of key constituents (iridoids, phenylpropanoids). HPLC validation tests affirm a decreasing trend in harpagoside and cinnamic acid levels between first and third-grade samples. In conclusion, this GC-MS based metabolomics combined HPLC method offers a sound approach to assess and distinguish quality variations in S. ningpoensis Hemsl samples.

Clinical features and risk factors of primary Sjögren's syndrome complicated with severe pneumonia: a case-control study.

To analyze clinical characteristics, risk factors, pathogen distribution, and prognostic markers in primary Sjögren's syndrome (pSS) patients with severe pneumonia (SP) compared to those without severe pneumonia (NSP). This case-control study included 24 hospitalized pSS patients with SP and 96 NSP at the first affiliated hospital of Soochow university from June 2014 to May 2023. Data encompassing demographics, comorbidities, treatments, and laboratory results were retrospectively collected. Univariate and multivariate regression analyses, ROC curves, and statistical analyses using SPSS 23.0 assessed risk factors. The study retrospectively analyzed clinical features and risk factors, highlighting distinct parameters between pSS patients with and without SP. Marked differences were observed in several parameters: pSS activity(P < 0.001), white blood cell (P = 0.043), lymphocyte (P < 0.001), neutrophils (P = 0.042), C-reactive protein (P = 0.042), and CD8+ T cell (P = 0.017). Notably, lymphocyte count and SS activity demonstrated robust discrimination ability (AUC > 0.85). C-reactive protein (CRP), procalcitonin, CD4+ T cell, and IgA showed significant associations with SP; higher CRP levels correlated with increased risk, while lower CD4+ T cell and IgA levels associated with increased risk. SS activity significantly impacted outcomes. Various biomarkers exhibited diverse discriminatory abilities but lacked strong predictive associations with outcomes. pSS patients with SP exhibited higher disease activity and altered immune profiles compared to those NSP. Lymphocyte count and SS activity emerged as robust discriminators. Higher CRP levels correlated with increased risk of SP, while lower CD4+T cell and IgA levels associated with increased risk. SS activity significantly impacted patient outcomes. Key Points • pSS patients with SP exhibited higher disease activity and altered immune profiles compared to those NSP. • Lymphocyte count and SS activity emerged as robust discriminators. • Higher CRP levels correlated with increased risk of SP, while lower CD4+ T cell and IgA levels associated with decreased risk. • SS activity significantly impacted patient outcomes.

Unraveling varietal differences and nutraceutical potentials of Manjari Medika grape hybrid and its parents: An untargeted metabolomics study

The study presents a robust, reliable, and precise classification model that accurately compares the metabolite composition of an Indian grape hybrid named Manjari Medika (MM) to its parental lines, Pusa Navrang (PN) and Flame Seedless (FS). The objective was to evaluate the impact of PN and FS on the MM metabolome, and investigate the nutraceutical potential of these three grape varieties. By employing a liquid chromatography-high resolution mass spectrometry based untargeted approach, the methanolic extracts of these grapes were screened. The metabolites were identified by matching with globally available databases and were further subjected to multivariate statistical analysis. The study identified 427 metabolites, out of which 410 compounds were common across all three varieties. The MM cultivar revealed 73 distinct compounds. The chemoinformatics analysis identified 21 metabolites as distinguishing biomarkers. In MM, the elevated relative abundance of the potentially bioactive metabolites suggests its suitability as a potential functional food. From the statistical analysis, it is hypothesized that the anthocyanin profile and drought tolerance may be influenced by PN, while FS could potentially contribute to enhanced shelf life. This study could help grape breeders map inheritance pattern of bioactive compounds and identify the best parents and progenies to create robust varieties with rich metabolite profiles.

1H NMR spectroscopy as a tool to probe potential biomarkers of the drying-salting process: A proof-of-concept study with the Amazon fish pirarucu

Dry-salted pirarucu (Arapaima gigas) plays an important cultural role in the Amazon region – South America. In this study, we explored the changes in the chemical composition of pirarucu meat following the drying-salting process via 1H NMR spectroscopy. Combining multivariate and univariate statistical analyses yielded a robust differentiation of metabolites involved in the process. VIP score (>1), p-value (<0.05), and AUC (>0.7) were considered to selecting compounds that had significant fluctuations in their contents along the process. Our results pointed out acetate, lactate, succinate, and creatinine as metabolites undergoing significant changes during the drying-salting process. Creatinine was not detected in fresh samples. The investigation of multiple components delves deeper into the molecular nuances of the salting-drying process's impact on fish meat, providing a more comprehensive understanding of the possible chemical transformations and how the matrix's quality control and nutritional aspects should be addressed.

Rheological behaviour, fatty acid composition and pigment content of Moroccan Picholine virgin olive oil during three harvest periods

The physicochemical, rheological, and fatty acid composition of six virgin olive oils extracted from the Picholine variety in the Beni Mellal-Khénifra region (Morocco) were studied and compared over three harvest years: 2018-2019, 2019-2020, and 2020-2021. These results show that all samples are rich in oleic acid, with the lowest amount observed for samples harvested in 2018-2019, followed by samples from 2019-2020 and finally those from the 2020-2021 harvest. It was also shown that all virgin olive oil samples exhibited Newtonian behaviors at shear rates between 60 and 120 s-1 and that the average dynamic viscosity of the 2018-2019 samples was 0.045 ± 1.14.10-4 Pa.s, below that observed for the 2019-2020 period (0.063 ± 4.92.10-4 Pa.s). The latter was in turn lower than the viscosity recorded for the 2020-2021 harvest (0.071 ± 1.90.10-4 Pa.s). Analysis of fatty acid composition shows that olive oils with a high oleic acid content have a higher viscosity than those with a low content. Finally, multivariate statistical analyses (Principal Component Analysis and Hierarchical Cluster Analysis) showed good classification between samples according to their physicochemical properties and year of harvest. The olive oils produced in 2018 were significantly different from those harvested in 2020, probably due to their viscosities and fatty acid profiles.

Chemical Composition Variation in Essential Oil and Their Correlation with Climate Factors in Chinese Prickly Ash Peels (Zanthoxylum armatum DC.) from Different Habitats.

Essential oils are secondary metabolites in plants with a variety of biological activities. The flavor and quality of Zanthoxylum armatum DC. are mainly determined by the essential oil components in the Chinese prickly ash peels. In this study, the correlation between climate change in different regions and the content of essential oils of Z. armatum was investigated using gas chromatography-mass spectrometry (GC/MS) and multivariate statistical analysis. The Z1-24 refers to 24 batches of samples from different habitats. A total of 145 essential oils were detected in 24 batches of samples, with the highest number of terpene species and the highest content of alcohol. The relative odor activity (ROAV) values identified nine main flavor compounds affecting the odor of Z. armatum. Linalool, decanal, and d-limonene were the most critical main flavor compounds, giving Z. armatum a spicy, floral, oily, and fruity odor. The results of hierarchical cluster analysis (HCA) and principal component analysis (PCA) classified Z5 into a separate group, Z2 and Z7 were clustered into one group, and the rest of the samples were classified into another group. Correlation analysis and path analysis showed that temperature and precipitation were the main climatic factors affecting essential oils. Comparisons can be made with other plants in the genus Zanthoxylum to analyze differences in essential oil type and content. This study contributes to the identification of Z. armatum quality, promotes the accumulation of theories on the effects of climatic factors on essential oils, and enriches the site selection and breeding of Z. armatum under similar climatic conditions.

Seminatural Grasslands: An Emblematic Challenge for Nature Conservation in Protected Areas

Seminatural grasslands are among the most threatened habitats in Europe and worldwide, mainly due to changes in/abandonment of their traditional extensive use by grazing animals. This study aimed to develop an innovative model that integrates plant biodiversity, animal husbandry, and geo-informatics to manage and preserve seminatural grasslands in protected areas. With this objective, an integrated study was conducted on the seminatural grasslands in the hilly, montane, and (to a minimum extent) subalpine belts of the Maiella National Park, one of Europe’s most biodiversity-rich protected sites. Plant biodiversity was investigated through 141 phytosociological relevés in homogeneous areas; the pastoral value was calculated, and grasslands’ productivity was measured together with the main nutritional parameters. Uni- and multivariate statistical analyses were performed to identify the main grassland vegetation types, their indicator species and ecological–environmental characteristics, and their pastoral and nutritional values’ variability and differences. A total of 17 grassland types, most of which correspond to habitat types listed in Annex I to the 92/43/EEC Directive, were identified and characterised in terms of their biodiversity and potential animal load. To allow for near-real-time analysis of grasslands, an NDVI-based web interface running on Google Earth Engine was implemented. This integrated approach can provide decision-making support for protected-area managers seeking to develop and implement sustainable grassland management practices that ensure the long-term maintenance of their biodiversity.

Effect of complex prebiotics on Lactobacillus gasseri JM1 fermented soymilk: Physicochemical, flavor characteristics, and metabolites

Fermented soymilk reduces its overall acceptability due to its unpleasant flavor, but synergistic fermentation of soymilk with prebiotics and probiotics may be an effective way to improve its flavor. In this study, soymilk was fermented by adding 3% complex prebiotics (fructose oligosaccharides (FOS): inulin: galactose oligosaccharides (GOS) = 2: 2: 1) in synergy with Lactobacillus gasseri JM1. The study found that by increasing the viscosity of soymilk (2528.80 ± 132.07 cP), which in turn increased its water holding capacity (52.07 ± 2.02%). Based on GC-MS, metabolomics, and multivariate statistical PCA analysis, 2,3-butanedione, 2,3-pentanedione, 2-butanone, and acetoin were found to be significant modifiers of soymilk flavor compared to the control group (P < 0.05). No odors such as 1-octen-3-ol, hexanal, etc. were detected. In addition, relatively high levels of isoflavonoids such as genistein and daidzein have also been found. This study provides ideas and baseline data for research related to soymilk product innovation, flavor extension, and quality improvement.

On the Estimation of the Interannual Variability of the Ocean Surface Temperature in the Area of the Peruvian Upwelling

The interannual variability of the ocean surface temperature in the area of the Peruvian upwelling for the period 1980–2022 is considered according to the satellite archive GODAS (Global Ocean Data Assimilation System) using the methods of multivariate statistical analysis. Local foci of significant trends, for average annual Sea Surface Temperature (SST) values, were identified near the Peruvian offshore. Four regions (clusters) were obtained, which describe the variability of SST in front off Peru, which could be used to pretend to develop a prognostic oceanographic model. Furthermore, coincidences of temperature fluctuations were found between the first cluster and the region N3+4

Effects of Elective Caesarean Sections in Healthy Near-Term Ewes on Subsequent Reproductive Performance.

Post-surgical reproductive performance following ovine caesarean section has not been well studied. To assess any direct effects of surgical delivery in the absence of confounders such as dystocia or underlying diseases, we studied elective surgery performed in healthy animals for teaching purposes. Four hundred and eleven paired breeding records following vaginal delivery (n = 233), elective caesarean section (n = 122), and subsequent further vaginal deliveries in animals with a history of one prior elective caesarean operation (n = 56) were evaluated retrospectively. The overall subsequent pregnancy rate was 95%. Multivariable statistical analyses did not reveal any significant influence of planned caesarean surgery on subsequent conception, stillbirth, perinatal lamb mortality, lamb birth weights, or the incidence of premature foetal death (mummification and abortion). A significantly higher number of mating attempts was, however, necessary. Also, a significant reduction in litter size was seen in the first pregnancy immediately following a surgical delivery in comparison to animals which had previously only delivered vaginally (p = 0.001), but litter size returned to pre-caesarean levels in further follow-up pregnancies in animals with a history of one elective caesarean section (p = 0.436). Subsequent long-term reproductive performance of sheep following elective caesarean section is thus excellent, and the results encourage retention for breeding.

Pollution status and health risk assessment of heavy metals in the soil of Sahibzada Ajit Singh (SAS) Nagar district of Punjab, India and its source apportionment

The threat of heavy metals in soil due to rapid urbanization, intensive agricultural practices, vehicular emission, and industry-related activities is increasing day by day, causing high risk to environmental health. The present study assessed the heavy metal pollution (Cr, Co, Ni, Co, Zn, As, Cd, and Pb) in the soil of Sahibzada Ajit Singh Nagar District, Punjab, India, through the index of geoaccumulation (Igeo), contamination factors (CF), degree of contamination (DC), pollution load index (PLI), ecological risk factor (Er) and potential ecological risk indices (PRI). The results showed the concentration of heavy metals in the soil in the order of Pb > Zn > Ni > Cr > Cu > As > Co > Cd. The pollution risk assessment indices: Igeo, CF, and Er indicated that most soil samples were moderately contaminated with Pb. The village Majra showed considerable contamination as evidenced by the Cd. The multivariate statistical analysis revealed the anthropogenic sources (agricultural practices and discharges from micro, small and medium enterprises (MSME) industries) to be the possible sources of Cr, Co, Ni, Cu, Zn, and Pb. The health risk assessment studies indicated that carcinogenic risks were higher for children than the adults. The cancer risk (CR) for all heavy metals in decreasing order is As > Cr > Pb > Ni > Cd. Likewise, the non-carcinogenic risks calculated as HQ followed the order of Pb > As > Cr > Cd > Ni > Cu > Co > Zn. The significant disparities in heavy metal concentrations underscore the necessity of establishing appropriate baseline levels for toxic trace metals in soils.

Comprehensive profiling of amino acids and derivatives in biological samples: A robust UHPLC-MS/MS method for investigating acute lung injury

The severe respiratory dysfunctions associated with acute lung injury (ALI) and its sequelae have a high morbidity and mortality rate, are multifactorial, and lack a viable treatment. Considering the critical function that amino acids and derivatives play in the genesis of illnesses and the regulation of metabolic processes, monitoring the levels of metabolites associated with amino acids in biological matrices is necessary and interesting to study their pathological mechanisms. Exploring the dynamics of amino acids and derivatives level and searching for biomarkers provides improved clinical ideas for the diagnosis and treatment of ALI. Therefore, we developed an ultra-high-performance liquid chromatography-electrospray tandem mass spectrometry (UHPLC-MS/MS) method that can simultaneously determine the amino acid and derivatives metabolic levels to study amino acid profiles in different biological samples to facilitate clinical research of ALI. In this study, 48 amino acids and derivatives, including neurotransmitters, polyamines, purines, and other types, were quantified simultaneously in a fast, high-throughput, sensitive, and reliable manner within a 15-minute run time without derivatization. No relevant studies have been reported to quantify these 48 amino acid metabolites in three biological samples simultaneously. Satisfactory linearity (R > 0.995), inter-day and intra-day accuracy (85.17–112.67 % and 85.29–111.60 %, respectively), inter-day and intra-day precision (RSD < 13.80 % and RSD < 12.01 %, respectively), matrix effects (81.00 %–118.00 %), recovery (85.09 %–114.65 %) and stability (RSD < 14.72 %) were all demonstrated by the optimized method's successful validation for all analytes. In addition, the suggested method was effectively implemented in plasma, urine, and lung tissue from normal mice and mice with ALI, with the aim of finding potential biomarkers associated with ALI. Potential biomarkers were screened through multivariate statistical analysis and volcanic map analysis, and the changes of markers in ALI were again identified through heat map analysis and correlation analysis with biochemical indicators, which provided ideas and references for subsequent mechanism studies. Here, the technique created in this work offers a quick and dependable way to perform an integrated analysis of amino acids in a variety of biological materials, which can provide research ideas for understanding the physiopathological state of various diseases.

Seasonal and isotopic precipitation patterns in the semi-arid and high mountain areas

Precipitation plays a crucial role in the natural hydrological cycle. Understanding the spatial and temporal variations of precipitation isotopes is essential for identifying hydrological, meteorological, and ecological processes. In high mountain areas with arid and semi-arid conditions, especially in regions with endorheic basins, the portion of precipitation that infiltrates the groundwater as the primary source of water recharge. However, estimating this recharge is challenging and prone to high uncertainty.The main objective of this study was to implement a robust and detailed methodology to analyze the influence of meteorological variables and the origin of moisture sources on the stable isotopic composition (δ18O and δ2H) of precipitation. As an illustrative case, we focused on the Los Pozuelos Basin, an endorheic basin in the Altiplano-Puna region of the Andes. The analysis incorporated precipitation samples collected over a 3-year period (January 2020 to April 2023) along with comprehensive monitoring of local atmospheric variables, satellite imagery, and HYSPLIT backward trajectory models.The examination involved a multivariate analysis of meteorological and stable isotope data and atmospheric transport pattern. Precipitation characteristics exhibited seasonal variability, with summer precipitation being depleted in heavy isotopes due to its extended continental journey and the recycling it undergoes while crossing the Amazon basin with convective activity. Another moisture path from the Atlantic Ocean, via the Río de la Plata or Gran Chaco basin, represented an intermediate isotopic stage. La Niña events intensified westerly winds, drawing moist air masses from the Pacific Ocean and causing rainfall in the study area. In winter, precipitation comes from the Pacific Ocean and isotopically enriched due to the low amount of precipitation and lower convective activity.By employing a meticulous methodology and multivariate statistical analysis, the study contributes positively to the broader discourse on water resource management and conservation in arid and semi-arid environments.

A LC-MS-based serum pharmacochemistry approach to reveal the compatibility features of mutual promotion/assistance herb pairs in Xijiao Dihuang decoction

Xijiao Dihuang decoction (XDT), a famous formula, was usually used to improve the prognosis of patients with blood-heat and blood-stasis syndrome-related diseases. There were some mutual promotion and mutual assistance herb pairs in XDT. However, the exact functions of these herb pairs in the compatibility of XDT were not elucidated due to the lack of appropriate methodologies. Based on the theory of serum pharmacochemistry, a systematic method was established for the qualitative and quantitative analysis of characteristic components in the extracts and drug-containing plasma samples of XDT and its relational mutual promotion/assistance herb pairs. For qualitative analysis, 85 characteristic components were identified using the liquid chromatography with triple time-of-flight mass/mass spectrometry (LC-Triple QTOF-MS/MS) based on the mass defect filtering, product ion filtering, neutral loss filtering and isotope pattern filtering techniques. For quantitative detection, a relative quantitation assay using an extract ion chromatogram (EIC) of the full scan MS experiment was validated and employed to assess the quantity of the 85 identified compounds in the test samples of single herb, herb pairs and XDT. The results of multivariate statistical analyses indicated that both the assistant and guide herbs could improve the solubilization of active compounds from the sovereign and minister herbs in XDT in vitro, might change the trans-membrane transportation, and regulate metabolism in vivo. The methods used in present study might be also valuable for the investigation of multiple components from other classic TCM formulas for the purpose of compatibility feature study.

A novel strategy for the quality control of carbonized Typhae pollen using colorimeter, liquid chromatography-mass spectrometry, and efficacy evaluation coupled with multivariate statistical analysis.

In this study, a novel quality control strategy was proposed, aiming to establish a multivariate specification for the processing step by exploring the correlation between colors, chemical components, and hemostatic effects of the carbonized Typhae pollen (CTP) using multivariate statistical analysis. The CTP samples were stir-fried at different durations. Afterward, the colorimeter and LC-MS techniques were applied to characterize the CTP samples, followed by the determination of bleeding time and clotting time using mice to evaluate their hemostatic effect. Then, principal component analysis, hierarchical cluster analysis, and multi-block partial least squares were used for data analysis on colors, chemical components, and their correlation with the hemostatic effect. Consequently, 13 critical quality attributes (CQAs) of CTP were identified via multivariate statistical analysis-L*, a*, b*, 3,4-dihydroxybenzoic acid, 4-hydroxybenzoic acid, 3-hydroxybenzoic acid, quercetin-3-O-glucoside, azelaic acid, kaempferol-3-O-glucoside, quercetin, naringenin, kaempferol, and isorhamnetin. The multivariate specification method involving the 13 CQAs was developed and visualized in the latent variable space of the partial least squares model, indicating that the proposed method was successfully applied to assess the quality of CTP and the degree of carbonization. Most importantly, this study offers a novel insight into the control of processing for carbonized Chinese herbal medicines.

Quantitative and qualitative assessment of groundwater resources for drinking water supply in the peri-urban area of Dhaka, Bangladesh

Groundwater is the primary source of freshwater for drinking, industrial, and agricultural water in many nations worldwide. This vital resource is deteriorating due to rapidly growing urbanization, pollution, overexploitation, and climate change. However, it is unclear how much this specific resource deteriorates over time. Therefore, this study aimed to investigate groundwater resources qualitatively and quantitatively in the peri-urban area of Dhaka, Bangladesh. The study used the modified Mann-Kendall trend test, hotspot analysis, groundwater recharge estimation, multivariate statistical analysis, and the water quality index (WQI) mapping. The trend analysis of groundwater levels indicates that in the most recent year, groundwater levels close to industrial areas have declined at a maximum rate of 1.18 m/year. The estimated groundwater recharge reveals that it is highest (480 mm/year) on rural agricultural land and lowest (220 mm/year) in urban areas. With a 99% confidence level, the groundwater water trend cluster analysis indicates the hotspots of groundwater level depletion near the industrial area. The results showed that Mn, Fe, and As exceeded the World Health Organization's (WHO) recommended limit for drinking water by 76.92%, 61.53%, and 23.07%, respectively. The principal component analysis and hierarchical clustering results indicate that groundwater quality is influenced by rock-water interaction and human interventions. The WQI results suggest that 47.05% of the samples were excellent, 7.69% were good, 9.96% were poor, 17.65% were very poor, and the remaining 17.65% were unfit for drinking purposes. The depletion of groundwater hotspots was identified in northeast region of the study area. Overall, an integrated framework was proposed that offers a holistic approach to sustainable groundwater resource management amid urbanization and industrialization. These findings will provide an essential guideline for groundwater resource management in the peri-urban area of Dhaka city.

Targeted metabolomic analysis of serum amino acids in heart failure patients

Heart failure (HF) has been recognized as a global epidemic with high rates of morbidity, hospitalization, and mortality. The role of amino acids, which provide the body with energy, in the development of HF is still unclear. The aim of this study was to explore changes in serum amino acids in patients with HF and identify potential biomarkers. First, the serum amino acid metabolism profiles of 44 patients with HF and 30 healthy controls (Con) were quantitatively measured. Then, candidate markers were identified through the utilization of T test, multivariate statistical analysis, and receiver operating characteristic (ROC) curve analysis. The results found that there were 11 amino acid levels that were significantly different between patients with HF and Con. Based on ROC curve analysis, the biomarkers of eight amino acids (Glutamic acid, Taurine, l-aspartic acid, l-ornithine, Ethanolamine, l-Serine, l-Sarcosine, and Cysteine) showed high sensitivity and specificity (AUC > 0.90), and binary logistic regression analysis was used in MetaboAnalyst 5.0. Among the amino acids examined, six exhibited notable alterations in accordance with the severity of HF. In conclusion, this study cannot only provide clinicians with an objective diagnostic approach for the early identification of HF, but also enhances comprehension of the underlying mechanisms involved in the pathogenesis of HF.

Spatiotemporal variations, sources, pollution status and health risk assessment of dissolved trace elements in a major Arabian Sea draining river: insights from multivariate statistical and machine learning approaches.

River Mahi drains through semi-arid regions (Western India) and is a major Arabian Sea draining river. As the principal surface water source, its water quality is important to the regional population. Therefore, the river water was sampled extensively (n = 64, 16 locations, 4 seasons and 2years) and analyzed for 11 trace elements (TEs; Sr, V, Cu, Ni, Zn, Cd, Ba, Cr, Mn, Fe, and Co). Machine learning (ML) and multivariate statistical analysis (MVSA) were applied to investigate their possible sources, spatial-temporal-annual variations, evaluate multiple water quality parameters [heavy metal pollution index (HPI), heavy metal evaluation index (HEI)], and health indices [hazard quotient (HQ), and hazard index (THI)] associated with TEs. TE levels were higher than their corresponding world average values in 100% (Sr, V and Zn), 78%(Cu), 41%(Ni), 27%(Cr), 9%(Cd), 8%(Ba), 8%(Co), 6%(Fe), and 0%(Mn), of the samples. Three principal components (PCs) accounted for 74.5% of the TE variance: PC-1 (Fe, Co, Mn and Cu) and PC-2 (Sr and Ba) are contributed from geogenic sources, while PC-3 (Cr, Ni and Zn) are derived from geogenic and anthropogenic sources. HPI, HEI, HQ and THI all indicate that water quality is good for domestic purposes and poses little hazard. ML identified Random forest as the most suitable model for predicting HEI class (accuracy: 92%, recall: 92% and precision: 94%). Even with a limited dataset, the study underscores the potential application of ML to predictive classification modeling.

Insight into the dynamic change of flavor profiles and their correlation with microbial community succession and lipid oxidation during the processing of dry-cured duck

Microbial community and lipid oxidation play an important role in flavor development of dry-cured duck. To explore the dynamic changes in microbial community succession, oxidative properties and flavor profiles during the processing of dry-cured duck and the relationships between them, the samples were analyzed by high-throughput sequencing, peroxide values, electronic nose and gas chromatography-mass spectrometry, and their relationships were established by multivariate statistical analysis. The results showed that the changes in lipid oxidation were related to the processing technology, especially the air-drying time. Thirty-five volatiles were identified, of which nonanal, 1-octen-3-ol, hexanal, benzaldehyde, and 2-pentylfuran were the characteristic aroma compounds. Staphylococcus, Vibrio, and Lactococcus were the dominant genera during the processing. Staphylococcus and Lactococcus were positively correlated with the characteristic flavor compounds and lipid oxidation products. These findings offer novel insights into the flavor formation of dry-cured ducks and offer deeper theoretical guidance for their preparation and production.

Metabolomic Comparison of Guava (Psidium guajava L.) Leaf Extracts Fermented by Limosilactobacillus fermentum and Lactiplantibacillus plantarum and Their Antioxidant and Antiglycation Activities.

Probiotic fermentation of plant-based materials can lead to the generation of various bioactive substances via bacterial metabolites and the biotransformation of phenolic compounds. We compared the metabolic differences between fermentation by Limosilactobacillus fermentum KCTC15072BP (LFG) and fermentation by Lactiplantibacillus plantarum KGMB00831 (LPG) in guava leaf extract (0%, 0.5%, and 2% (w/v))-supplemented medium via non-targeted metabolite profiling. By performing multivariate statistical analysis and comparing the different guava leaf extract groups, 21 guava-derived and 30 bacterial metabolites were identified. The contents of guava-derived glucogallin, gallic acid, and sugar alcohols were significantly higher in LFG than they were in LPG. Similarly, significantly higher contents of guava-derived pyrogallol, vanillic acid, naringenin, phloretin, and aromatic amino acid catabolites were obtained with LPG than with LFG. LFG led to significantly higher antioxidant activities than LPG, while LPG led to significantly higher antiglycation activity than LFG. Interestingly, the fermentation-induced increase in the guava-leaf-extract-supplemented group was significantly higher than that in the control group. Thus, the increased bioactivity induced by guava fermentation with the Lactobacillaceae strain may be influenced by the synergistic effects between microbial metabolites and plant-derived compounds. Overall, examining the metabolic changes in plant-based food fermentation by differentiating the origin of metabolites provides a better understanding of food fermentation.