Latent Structures Discriminant Analysis Research Articles

Feasibility of detecting non-small cell lung cancer using exhaled breath condensate metabolomics

Lung cancer is one of the most common malignancy in the world, and early detection of lung cancer remains a challenge. The exhaled breath condensate (EBC) from lung and trachea can be collected totally noninvasively. In this study, our aim is to identify differential metabolites between non-small cell lung cancer (NSCLC) and control EBC samples and discriminate NSCLC group from control group by orthogonal projections to latent structures-discriminant analysis (OPLS-DA) models. The EBC differential metabolites between NSCLC patients (n= 29) and controls (n= 24) (20 healthy and 4 benign individuals) were identified using ultra-performance liquid chromatography-high resolution mass spectrometry based untargeted metabolomics method. The upregulated metabolites in EBC of NSCLC included amino acids and derivatives (phenylalanine, tryptophan, 1-carboxyethylisoleucine/1-carboxyethylleucine, and 2-octenoylglycine), dipeptides (leucyl-phenylalanine, leucyl-leucine, leucyl-histidine/isoleucyl-histidine, and prolyl-valine), and fatty acids (tridecenoic acid, hexadecadienoic acid, tetradecadienoic acid, 9,12,13-trihydroxyoctadec-10-enoic acid/9,10,13-trihydroxyoctadec-11-enoic acid (9,12,13-TriHOME/9,10,13-TriHOME), 3-hydroxysebacic acid/2-hydroxydecanedioic acid, 9-oxooctadeca-10,12-dienoic acid/9,10-Epoxy-12,15-octadecadienoate (9-oxoODE/9(10)-EpODE), and suberic acid). The downregulated metabolites in EBC of NSCLC were 3,4-methylenesebacic acid, 2-isopropylmalic acid/3-isopropylmalic acid/2,3-dimethyl-3-hydroxyglutaric acid, and trimethylamine-N-oxide. The OPLS-DA model based on 5 EBC metabolites achieved 86.2% sensitivity, 83.3% specificity and 84.9% accuracy, showing a potential to distinguish NSCLC patients from controls.

OPLS-Based Multiclass Classification and Data-Driven Interclass Relationship Discovery.

Multiclass data sets and large-scale studies are increasingly common in omics sciences, drug discovery, and clinical research due to advancements in analytical platforms. Efficiently handling these data sets and discerning subtle differences across multiple classes remains a significant challenge. In metabolomics, two-class orthogonal projection to latent structures discriminant analysis (OPLS-DA) models are widely used due to their strong discrimination capabilities and ability to provide interpretable information on class differences. However, these models face challenges in multiclass settings. A common solution is to transform the multiclass comparison into multiple two-class comparisons, which, while more effective than a global multiclass OPLS-DA model, unfortunately results in a manual, time-consuming model-building process with complicated interpretation. Here, we introduce an extension of OPLS-DA for data-driven multiclass classification: orthogonal partial least squares-hierarchical discriminant analysis (OPLS-HDA). OPLS-HDA integrates hierarchical cluster analysis (HCA) with the OPLS-DA framework to create a decision tree, addressing multiclass classification challenges and providing intuitive visualization of interclass relationships. To avoid overfitting and ensure reliable predictions, we use cross-validation during model building. Benchmark results show that OPLS-HDA performs competitively across diverse data sets compared to eight established methods. This method represents a significant advancement, offering a powerful tool to dissect complex multiclass data sets. With its versatility, interpretability, and ease of use, OPLS-HDA is an efficient approach to multiclass data analysis applicable across various fields.

Early Prediction of Fetal Macrosomia Through Maternal Lipid Profiles

The prevalence of fetal macrosomia is steadily increasing worldwide, reaching up to 20%. Fetal macrosomia complicates pregnancy and delivery. Current prediction strategies are inaccurate, and most patients with fetal macrosomia go into labor with an “unknown status.” The aim of this study was to develop a system for predicting fetal macrosomia based on the lipid profiles of pregnant women’s blood serum. In total, 110 patients were included in this study: 30 patients had gestational diabetes mellitus (GDM) and 80 did not. During the observation, blood samples were collected at three time points: in the first trimester (11–13 weeks of pregnancy), in the second trimester (24–26 weeks), and in the third trimester (30–32 weeks). Lipids were detected by flow injection analysis with mass spectrometry. Lipid profiles of pregnant women were discriminated by orthogonal projection on latent structure discriminant analysis (OPLS-DA) in all three trimesters. The developed OPLS-DA models allowed for the prediction of the occurrence of fetal macrosomia during pregnancy. Three sets of models were developed: models independent of GDM status with a sensitivity of 0.85 and specificity of 0.91, models for patients with positive GDM status with a sensitivity of 0.91 and specificity of 0.96, and models for patients with negative GDM status with a sensitivity of 0.93 and specificity of 0.92. Phosphatidylcholines and sphingomyelins were the most important discriminative features. These lipid groups probably play an important role in the pathogenesis of fetal macrosomia and may serve as laboratory markers of this pregnancy complication.

Niacin alters ruminal microbial composition and metabolites in sheep fed a high-concentrate diet

This study aimed to investigate the effects of niacin supplementation to a high-concentrate diet (ratio of concentrate supplement to forage = 70:30) on the growth performance, rumen fermentation, rumen microbiota, and metabolomics of sheep. Twelve sheep were randomly divided into two groups: (1) a control group (CON, n = 6) fed a basal diet and (2) a niacin group (NA, n = 6) fed a basal diet supplemented with 130 mg/day niacin for 35 days: days 1–14 were the adaptation period, days 15–35 were the experiment period. On days 15 and 35 of the experiment period, all trial sheep were weighed before the morning feed (07:30 am). Ruminal fluid samples were collected from all trial sheep on days 34 and 35. The results showed that (1) the dry matter feed intake of the NA group was higher than that of the CON group (p < 0.05). (2) The ruminal pH of the NA was significantly higher than that of the CON group at 3, 5, and 7 h after feeding (p < 0.01). The concentrations of NH3-N (p < 0.01), propionate (p < 0.01), and butyrate (p < 0.05) in the NA group were significantly higher than those in the CON group. (3) Compared to the CON group, the ruminal pyruvate content in the NA group was significantly increased at 0 h before feeding (p < 0.05), and lactic acid (p < 0.05) was significantly decreased at 1 and 3 h after feeding, lactate dehydrogenase activities was significantly decreased (p < 0.01) at 3 and 5 h after feeding. (4) The number of specific operational taxonomic units (OTUs) in the CON and NA groups were 26 and 37, respectively, for a total of 1,178 OTUs; principal coordinate analysis (R2 = 0.172, p-value = 0.007) and non-metric multidimensional scaling (stress = 0.1646) results showed that the two groups of samples were significantly separated. (5) The species distribution bar graph shows that at the phylum level, the relative abundances of Bacteroidetes, Firmicutes, and Proteobacteria were 43.70, 36.25, and 12.77%, respectively. (6) Orthogonal projection to latent structure-discriminant analysis results showed that the two groups of samples were clearly separated in the positive and negative ionization modes, with R2Y and Q2Y values of 0.705, 0.857, 0.695, and 0.28, respectively. There were 72 metabolic pathways, mainly citric acid cycle, pyruvate metabolism, and cysteine and methionine metabolism. (7) Correlation analysis showed that a number of microorganisms (such as Succinivibrio and Prevotella) and differential metabolites (such as L-malic acid, propionic acid, succinic acid, and pyruvic acid) participated in tricarboxylic acid cycle metabolism. In summary, supplementing niacin to high-concentrate diets can significantly improve the growth performance of sheep, improve rumen fermentation and the rumen microbial community structure, and affect rumen metabolites, thus alleviating the symptoms of rumen acidosis.

Alchemy in Nature: The Role of Lawsonia inermis Extract Choice in Crafting Potent Anticancer Metal Nanoparticles.

Phyto-nanotechnology provides an eco-friendly approach for synthesizing biocompatible metal nanoparticles (NPs) with therapeutic potential. Lawsonia inermis (LI) has been historically valued for its diverse medicinal applications, especially its exceptional biological potency against various skin diseases, attributed to its rich abundance of bioactive compounds. Therefore, herein, plant-based iron and zinc NPs were biofabricated via sustainable and simple methods, using crude extracts of the aerial parts of LI as reducing, coating, and stabilizing agents. Since the extraction method affects the type of extracted phytocompounds, two extraction approaches─aqueous and hydro-alcoholic─were applied to determine the influence of the extraction route on the physicochemical and biological properties of the formed NPs. These properties were characterized via various analytical techniques and assays. The UV-Vis spectra revealed absorption bands ranging from 265 to 270 nm, while FT-IR confirmed the successful coating of the NPs with the extracts' phytochemicals, validating the biofabrication of the proposed NPs. The alcoholic-based NPs displayed higher total phenolic content, total flavonoid content, and antioxidant effect compared to their aqueous-based counterparts, reaching up to 55.13 μg of GAE/1 mg of dry weight (DW), 30.48 μg of QU/1 mg of DW, and IC50 of 46.02 μg/mL, respectively. All tested samples, except for Fe NPs, displayed significant cytotoxic effects against skin cancer, resulting in a cell viability as low as 1% at 1000 μg/mL. QTOF-LC/MS/MS analyses of LI extracts revealed tentative identification of more than 100 metabolites with phenolic compounds representing the largest share. Orthogonal Projections to Latent Structures Discriminant Analysis modeling revealed a clear separation between both extracts, with more than 40 marker compounds. The results indicated that both extracts were effective for the green synthesis of Fe and Zn NPs for biomedical applications, with the alcoholic extract of LI as a superior coating candidate and the aqueous extract as a stronger reducing agent. This work showcases the influence of extraction protocols on physicochemical and biological characteristics of the resulting nanoparticles.

Robust scaling strategies for outlier handling in orthogonal projection to latent structures discriminant analysis (OPLS-DA)

Orthogonal projection to latent structures discriminant analysis (OPLS-DA) is a widely used statistical method in multivariate data analysis, particularly in class pattern recognition. In addition, OPLS-DA is an extension of partial least square (PLS) that separately considers the variance of correlated and orthogonal predictors in the projection process to the response. PLS is a linear method that is very sensitive to outliers, making OPLS-DA susceptible to the influence of outliers. Investigations have shown that outliers commonly exist in datasets and can significantly affect statistical analysis. Therefore, this research aimed to propose a robust scaling method in the pre-processing step of OPLS-DA to address outliers. The proposed method was tested using both simulated and actual datasets, and the result showed effectiveness in handling outliers and improving classification accuracy. Consequently, Robust OPLS-DA could be designed to achieve optimal classification results by effectively separating classes and increasing robustness against outliers.

Identification of serum biomarkers for cystic echinococcosis in sheep through untargeted metabolomic analysis using LC–MS/MS technology

Abstract Background Echinococcosis is a zoonotic disease caused by an Echinococcus tapeworm infection. While diagnostic methods for humans often rely on ultrasound imaging and immunodiagnostic techniques, diagnosis in intermediate hosts typically has no widely used diagnostic markers, hampering disease control efforts. Methods The differences in serum metabolites of sheep infected with Echinococcus granulosus and a control group were analyzed using ultrahigh-performance liquid chromatography (UHPLC) separation with tandem mass spectrometry (MS/MS) detection. This provided a basis for the early diagnosis and pathogenetic study of cystic echinococcosis (CE) in intermediate hosts at the metabolomics level. Orthogonal projections to latent structures–discriminant analysis (OPLS-DA) were used to analyze different metabolites in the serum of the two groups. The differentially abundant metabolites were entered into the MetaboAnalyst 5.0 online analysis website for processing, and the top-15-ranked metabolic pathways were set to produce bubble plots and differential abundance score plots, with a significant difference of P < 0.05 and a false discovery rate (FDR) < 0.1 as the screening conditions. Results Data analyses of serum samples from both groups identified a total of 1905 significantly different metabolites, where 841 metabolites were upregulated and 1064 metabolites were downregulated. Twelve metabolites were significantly upregulated and 21 metabolites were significantly downregulated in the experimental group. Then, the 1,7-dihydroxyxanthone, 2-methylbutyrylglycine, 3,3-dimethylglutaric acid, 5,12-dihydroxy-6,8,10,14,17-eicosapentaenoic acid, 9-hydroperoxy-10E,12Z,15Z-octadecatrienoic acid, and trimethylamine N-oxide 6 metabolites were selected as diagnostically valuable candidate biomarkers (area under the curve [AUC] > 0.7). These differential metabolites are involved in various metabolic pathways, including amino acid metabolites (arginine, l-isoleucine, l-valine) and fatty acid metabolism (fenugreek, arachidonic acid, linolenic acid). Compared with the control group, sheep in the CE group had increased serum levels of fenugreek acid, while all other metabolites such as glycine showed significantly reduced serum levels (P < 0.01). Conclusions Through non-targeted metabolomic analysis of the serum of CE-infected sheep, differential metabolites closely related to amino acid metabolism and the fatty acid metabolism pathway were identified. These differentially abundant metabolites can serve as biomarkers for diagnosing CE infection in intermediate sheep hosts. Graphical abstract

MALDI-TOF Mass Spectrometry Reveals the Effect of Acetyl-L-Carnitine on the Lipid Profile of Buffalo Oocytes and Cumulus Cells During InVitro Maturation.

Lipids in cumulus-oocyte complexes are important actors in molecular signalling pathways and are influenced by maturation conditions. Acetyl-L-carnitine (ALC) is a carrier involved in fatty acid transport and is a promoter of β-oxidation. Although the embryonic development potential of oocytes can be improved when ALC is added to the maturation medium, the effects of ALC on the lipid content and composition of oocytes and cumulus cells remain unknown. In this study, the effect of ALC supplementation on the lipid profiles of buffalo oocytes and cumulus cells after invitro maturation was evaluated using positive-ion matrix-assisted laser desorption ionisation time-of-flight mass spectrometry (MALDI-TOF MS). Orthogonal projections to latent structures discriminant analysis was used to analyse the data. The lipid profiles of oocytes and cumulus cells differed following ALC treatment. Four lipids were significantly different in oocytes and eight in granulosa cells. ALC treatment significantly reduced the cellular content of these lipids, with the exception of phosphatidylcholine [PC(36:3) + H] + in oocytes and triacylglycerol [TAG(58:8) + NH4] + in granulosa cells. Further staining experiments confirmed that ALC treatment reduced the total lipid content in oocytes. Therefore, ALC treatment alters lipid metabolism in oocytes and cumulus cells during their maturation and accelerates lipid metabolism in oocytes. The findings of this study demonstrate that ALC enhances the rate of oocyte maturation by altering lipid metabolism in oocytes, providing both a clear direction for further research into regulatory mechanisms as well as a foundation for further improving oocyte maturation rates.

Biochemometrics-Based Identification of Gallic Acid and Gallic Acid Galloylglucosides From Kalanchoe fedtschenkoi With Cytotoxic Effects on Cultured Melanoma Cells.

Kalanchoe Adans. (Crassulaceae) is a genus of widespread succulent plants extensively studied for their biological activities. Plants of the genus are considered a potential source of antitumor agents. This study aimed to investigate the effect of an aqueous extract and fractions of leaves of Kalanchoe fedtschenkoi R. Hamet & H. Perrier on the proliferation of melanoma cell lines employing an NMR-based biochemometric approach complemented with HPLC-DAD and UHPLC-MS/MS analyses. The n-butanol fraction (KFBuOH) from K. fedtschenkoi aqueous leaf extract, which decreased B16F10 murine melanoma cells viability by 65% at 100 μg/mL, was fractionated with RP-18 SPE and Sephadex LH-20 column chromatography. The fractions were analyzed by 1H-NMR spectroscopy and submitted to MTT cytotoxicity assays against cultured melanoma cells. Orthogonal projection to latent structures discriminant analysis (OPLS-DA) was used to correlate their 1H-NMR profile and cytotoxic activity. This strategy enabled the identification of gallic acid (1) and two gallic acid glucosides-gallic acid 4-O-(6'-O-galloyl)-glucopyranoside) (2) and gallic acid 3-O-(6'-O-galloyl)-glucopyranoside) (3)-as putative bioactive substances, which was further corroborated by subsequent assays with enriched fractions and a gallic acid standard. The fractions enriched in gallic acid (KFA) and gallic acid galloylglucosides (KFB) evidenced selective cytotoxicity towards B16F10 cells (IC50 43.0 and 56.6 μg/mL, respectively) and MV3 human melanoma cells (IC50 93.6 and 66.1 μg/mL, respectively). These results suggest a potential therapeutic use for K. fedtschenkoi in melanoma treatment. This is the first study to evidence a potential antitumor activity for gallic acid galloylglucosides.

Striatum-enriched protein, arginase 2 localizes to medium spiny neurons and controls striatal metabolic profile

Arginase 2 (Arg2) is the predominant arginase isoenzyme in the brain, however its distribution appears to be limited to selected, region-specific subpopulations of cells. Although striatum is highly enriched with Arg2, precise localization and function of striatal Arg2 have never been studied. Here, we confirm that Arg2 is the only arginase isoenzyme in the striatum, and, using genetic model of total Arg2 loss, we show that Arg2 in this region is fully responsible for arginase catalytic activity, and its loss doesn't induce compensatory activation of Arg1. We exhibit that Arg2 is present in medium spiny neurons (MSNs), striatum-specific projecting neurons, where it localizes in soma and neuronal processes, and is absent in astrocytes or microglia. Finally, analysis of NMR spectroscopy-measured metabolic profiles of striata of Arg2-null mice enabled to recognize two metabolites (NADH and malonic acid) to be significantly altered compared to control animals. Multivariate comparison of the data using orthogonal projections to latent structures discriminant analysis, allowed for discrimination between control and Arg2-null mice and identified metabolites that contributed the most to this between-group dissimilarity. Our study reveals for the first time the localization of Arg2 in MSNs and demonstrates significant role of this enzyme in regulating striatal metabolism. These findings may be especially interesting in the context of Huntington's disease (HD), a disorder that specifically affects MSNs and in which, with the use of mouse models, the onset of pathological phenotypes was recently shown to be preceded by progressive impairment of striatal Arg2, a phenomenon of an unknown significance for disease pathogenesis.

Camellia oil grading adulteration detection using characteristic volatile components GC-MS fingerprints combined with chemometrics

The volatile compounds combined with chemometrics, were used for different grade camellia oil adulterated detection. Using unsupervised models with fatty acids or triglycerides as input variables, the first-grade camellia oils (CAO Ⅰ) and second-grade camellia oils (CAO Ⅱ) occurred severely overlay in principle component analysis (PCA), for their almost quite identical compositions. While based on volatile components, hierarchical clustering analysis (HCA) presented a clear boundary between CAO Ⅰ and CAO Ⅱ samples. Subsequently, using our selected 15 volatile components by the variable importance in projection (VIP), both orthogonal projections to latent structure-discriminant analysis (OPLS-DA) and support vector machines (SVM), could be utilized as complementary models for camellia oil grade authentication with good classification rate (≥91.67%). In addition, according to those above characteristic variables with auto-scaling pretreatment, the optimized OPLS model could be recommended for adulterated level prediction (5%–100%, w/w).

Metabolite profiling in ten bread wheat (Triticum aestivum L.) genotypes in response to drought stress

Wheat is frequently constrained by extreme environmental conditions such as drought. Improving drought tolerance in wheat genotypes is crucial for ensuring food security, especially considering the challenges posed by climate change. To reveal the involvement of metabolites in drought response, ten diverse wheat genotypes were investigated under control and water scarcity conditions. The field experiments were set-up, using a 5 × 2 alpha lattice design, with two replicates per treatment, in the 2022 and 2023 growing seasons. Metabolites associated with drought tolerance were analysed using ultra-high performance liquid chromatography, coupled with a quadruple time of flight mass spectrometry (UHPLC-qTOF-MS). Multivariate statistical analysis (MVDA) tools, viz. principal component analysis (PCA) and the orthogonal projection to latent structures-discriminant analysis (OPLS-DA) loading scatter plot were used to identify the metabolites that are positively and negatively correlated to drought stress. Significant variation (p < 0.05) among genotypes was observed, with 58 metabolites annotated, including phenolic acids, carbohydrates, and fatty acids. The annotated compounds were linked to thirteen most significant pathways, with one carbon metabolism, cutin, suberin and wax synthesis and starch and sucrose metabolism being significantly affected by water stress, based on the KEGG pathway analysis. The two high-yielding wheat genotypes (LM48 and BW140) under drought stress displayed significant upregulation of key metabolites such as sinapoyl hydroxyagmatine, 7-oxostigmasterol, 1-O-caffeoyl-3-O-p-coumaroylglycerol, and 3-beta-3-lupanol, when compared to the non-stressed conditions. This study demonstrates the prospects of applied metabolomics for chemotaxonomic classification, phenotyping and selection in plant breeding, as well as potential use in crop improvement.

Clinical prediction of wound re-epithelisation outcomes in non-severe burn injury using the plasma lipidome

Whilst wound repair in severe burns has received substantial research attention, non-severe burns (<20 % total body surface area) remain relatively understudied, despite causing considerable physiological impact and constituting most of the hospital admissions for burns. Early prediction of healing outcomes would decrease financial and patient burden, and aid in preventing long-term complications from poor wound healing. Lipids have been implicated in inflammation and tissue repair and may play essential roles in burn wound healing. In this study, plasma samples were collected from 20 non-severe burn patients over six weeks from admission, including surgery, and analysed by liquid chromatography-tandem mass spectrometry and nuclear magnetic resonance spectroscopy to identify 850 lipids and 112 lipoproteins. Orthogonal projections to latent structures-discriminant analysis was performed to identify changes associated with re-epithelialisation and delayed re-epithelisation. We demonstrated that the lipid and lipoprotein profiles at admission could predict re-epithelisation outcomes at two weeks post-surgery, and that these discriminatory profiles were maintained up to six weeks post-surgery. Inflammatory markers GlycB and C-reactive protein indicated divergent systemic responses to the burn injury at admission. Triacylglycerols, diacylglycerols and low-density lipoprotein subfractions were associated with re-epithelisation (p-value <0.02, Cliff’s delta >0.7), whilst high-density lipoprotein subfractions, phosphatidylinositols, phosphatidylcholines, and phosphatidylserines were associated with delayed wound closure at two weeks post-surgery (p-value <0.01, Cliff’s delta <−0.7). Further model validation will potentially lead to personalised intervention strategies to reduce the risk of chronic complications post-burn injury.

Soil-Mulching Treatment Enhances the Content of Stilbene in Grape Berries: A Transcriptomic and Metabolomic Analysis

Soil mulching is a useful agronomic practice that promotes early fruit maturation and affects fruit quality. However, the regulatory mechanism of fruit metabolites under soil-mulching treatments remains unknown. In this study, variations in the gene sets and metabolites of grape berries after mulching (rice straw + felt + plastic film) using transcriptome and metagenomic sequencing were investigated. The results of the cluster analysis and orthogonal projection to latent structures discriminant analysis of the metabolites showed a difference between the mulching and control groups, as did the principal component analysis results for the transcriptome. In total, 36 differentially expressed metabolites were identified, of which 10 (resveratrol, ampelopsin F, piceid, 3,4′-dihydroxy-5-methoxystilbene, ε-viniferin, trans resveratrol, epsilon-viniferin, 3′-hydroxypterostilbene, 1-methyl-resveratrol, and pterostil-bene) were stilbenes. Their content increased after mulching, indicating that stilbene synthase activity increased after mulching. The weighted gene co-expression network analysis revealed that the turquoise and blue modules were positively and negatively related to stilbene compounds. The network analysis identified two seed genes (VIT_09s0054g00610, VIT_13s0156g00260) and two transcription factors (VIT_13s0156g00260, VIT_02s0025g04590). Overall, soil mulching promoted the accumulation of stilbene compounds in grapes, and the results provided key genetic information for further studies.

Metabolic profiling of blood plasma in depression in pregnant women during early pregnancy.

The study aimed to perform metabolic profiling of serum samples using liquid chromatography with mass spectroscopy (LC-MS) and to explore potential biomarkers of early trimester depression. Using the Edinburgh Postnatal Depression Scale (EPDS), participants were randomly divided into study and control groups. Serum metabolic profiles of the two groups were analysed by using LC-MS. Differential metabolite and pathway analysis were identified by using orthogonal projections to latent structure-discriminant analysis (OPLS-DA) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Additionally, least absolute shrinkage and selection operator (LASSO) logistic and receiver operating characteristic (ROC) curve analyses were also conducted to explore potential biomarkers of antenatal depression (AD). The study included 41 participants, consisting of 16 subjects with AD and 25 controls. A total of 22 different metabolites were identified (p < .005), mainly affecting glycerophospholipid metabolism, linoleic acid metabolism, synthesis and degradation of ketone bodies, phenylalanine metabolism, and butanoate metabolism. The area under the ROC curve (AUC) for the LysoPC (24:0) was 0.858. This suggests that LysoPC (24:0) may be a potentially effective predictor of risk factors for AD. The study suggests that LysoPC (24:0) may be an effective and specific lipid biomarker for early trimester depression.

Untargeted Metabolomics Approach for the Discovery of Salinity-Related Alkaloids in a Stony Coral-Derived Fungus Aspergillus terreus

As a part of the important species that form coral reef ecosystems, stony corals have become a potential source of pharmacologically active lead compounds for an increasing number of compounds with novel chemical structures and strong biological activity. In this study, the secondary metabolites and biological activities are reported for Aspergillus terreus C21-1, an epiphytic fungus acquired from Porites pukoensis collected from Xuwen Coral Reef Nature Reserve, China. This strain was cultured in potato dextrose broth (PDB) media and rice media with different salinities based on the OSMAC strategy. The mycelial morphology and high-performance thin layer chromatographic (HPTLC) fingerprints of the fermentation extracts together with bioautography were recorded. Furthermore, an untargeted metabolomics study was performed using principal component analysis (PCA), orthogonal projection to latent structure discriminant analysis (O-PLSDA), and feature-based molecular networking (FBMN) to analyze their secondary metabolite variations. The comprehensive results revealed that the metabolite expression in A. terreus C21-1 differed significantly between liquid and solid media. The metabolites produced in liquid medium were more diverse but less numerous compared to those in solid medium. Meanwhile, the mycelial morphology underwent significant changes with increasing salinity under PDB cultivation conditions, especially in PDB with 10% salinity. Untargeted metabolomics revealed significant differences between PDB with 10% salinity and other media, as well as between liquid and solid media. FBMN analysis indicated that alkaloids, which might be produced under high salt stress, contributed largely to the differences. The biological activities results showed that six groups of crude extracts exhibited acetylcholinesterase (AChE) inhibitory activities, along with 1,1-diphenyl-2-picrylhydrazyl (DPPH) free radical scavenging and antibacterial activities. The results of this study showed that the increase in salinity favored the production of unique alkaloid compounds by A. terreus C21-1.

Metabolomic profiling of Greyia radlkoferi on water stress, phenological growth stages, and leaf age using 1H NMR

Greyia radlkoferi Szyszyl (Melianthaceae) is a native plant to southern Africa identified as a viable commercial crop. The leaf extract is rich in flavonoid compounds with the ethanolic leaf extract found to treat skin hyper-pigmentation of humans without adverse effects (anti-tyrosinase activity value IC50 17.86 μg/ml). Anti-tyrosinase activity is found to be variable between plants, even when planted at the same site, which raises concerns regarding commercial production, necessitating the need for cultivation interventions that will not compromise the activity of the extract. Interventions to limit the variation were thus explored by imposing targeted water stress (different durations) before harvesting and determining the effect on the different phenological growth stages and activity of different leaf ages. The inhibitory tyrosinase activity was evaluated using mushroom tyrosinase and kojic acid as a control and data was presented as IC50 values. The metabolomics investigation was conducted through the use of nuclear magnetic resonance (1H NMR) analysis coupled with the multivariate statistical data set. Pattern recognition methods such as principal component analysis (PCA) and orthogonal projection on latent structure-discriminant analysis (OPLS-DA) were employed to obtain the metabolic discrimination between the treatments. No clear pattern was observed in the grouping of samples exposed to targeted water stress on both plant age and leaf position, except for younger leaves of one month and four months old which had a strong clustering of high activity samples as compared to older leaves of six months old. However, plant materials harvested during the flowering growth stage had a strong grouping of samples producing high anti-tyrosinase activity as compared to the budding and vegetative growth stages. The study determined the changes in the concentration of various compounds, although quantification of compounds should be determined in the future.

UPLC-MS/MS-based metabolomics and chemometrics unveil metabolic patterns and their regulatory pathways over the course of pumpkin seeds (Cucurbita maxima) germination

While pumpkin seeds (Cucurbita maxima) are regarded as agro-industrial waste, they serve as powerhouses packed with a plethora of valuable compounds with potential nutraceutical significance. The present work offers an integrated view of metabolites dynamics and their regulatory pathways over the course of pumpkin seeds germination and their potential entanglements on Alzheimerʼs disease (AD) mitigation through Ultra Performance Liquid Chromatography-mass spectrometry (UPLC-MS/MS) analysis and chemometrics. A total of 76 compounds spanning amino acids, phenolic acid, flavonoids, lignans, vitamins, fatty acids, phospholipids and phytosterols were annotated revealing changing trends during germination process. Coincidentally, orthogonal projection to latent structures-discriminant analysis (OPLS-DA) demonstrated a clear separation trend among the five pumpkin samples assuring their chemical heterogeneity. Complementarily, OPLS-DA models were constructed in different timepoint comparisons to pick out the significant metabolic features which were subsequently imported into MetaboAnalyst 5.0 (https://www.metaboanalyst.ca/) software for metabolic pathway enrichment analysis. Enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed biosynthesis of unsaturated fatty acids, phenylpropanoid biosynthesis, glycerophospholipid metabolism and phenylalanine, tyrosine and tryptophan biosynthesis as the top predictive metabolic pathways associated with significant phytochemical shifts during germination process. Importantly, our efficacy experimental results dissected that 5 d and 7 d sprouted samples exerted noteworthy inhibitory potentials against acetylcholine esterase (AChE) and monoamine oxidase (MAO-B) enzymes. OPLS-derived coefficients plots portrayed that docosahexaenoic acid, oleic acid, lirioresinol A and tocotrienols dramatically augmented during germination were probably ascribed to promising AChE and MAO-B inhibitory activities. These findings offer a turning point for using pumpkin sprouts with an appreciable biochemical content to pursue the concept of nutritional therapy and accelerate perpetual influx of novel bioproducts to rectify AD.

Ten years of detecting Neoehrlichia mikurensis infections in Sweden: demographic, clinical and inflammatory parameters.

To increase knowledge about the varied clinical manifestations of human infection with the emerging tick-borne pathogen Neoehrlichia mikurensis. All patients diagnosed in Sweden with N. mikurensis infection during a 10-year period (2013-2023) were investigated regarding their demographic factors, risk factors, comorbidities, clinical signs and symptoms, and laboratory results. Multivariate models were generated using "Orthogonal Projections to Latent Structures-Discriminant Analysis" to identify clinical and immune parameters associated with N. mikurensis infection. During the 10-year period, 134 patients were diagnosed with N. mikurensis infection, 102 of whom were included in this study. Most of the patients (79%) were immunosuppressed. The main comorbidities were malignant B-cell lymphomas, multiple sclerosis, and rheumatoid arthritis. Rituximab therapy (59%) and splenectomy (14%) featured prominently. All patients resided in the southern tick-endemic part of Sweden, yet one-third of them were diagnosed in wintertime when ticks are inactive. Two asymptomatically infected blood donors were identified but transfusion-transmitted infection was not confirmed. Increased levels of C-reactive protein, orosomucoid, and total IgM in serum were associated with neoehrlichiosis. Previously unreported symptoms such as ankle edema, neck pain, numbness, and sudden deafness were detected in some patients. One case of aplastic anemia partially improved after eradication of the infection. Neoehrlichiosis is a multi-faceted emerging infectious disease.

Effects of Loquat Juice Addition on Sensory Characteristics and Volatile Organic Compounds of Loquat Beer.

Beer, as an ancient and widely consumed alcoholic beverage, holds a rich cultural heritage and history. In recent years, fruit beer has gained significant attention as a distinct beer type produced by incorporating fruit juice into traditional beer ingredients. This study employed headspace solid-phase microextraction-gas chromatography-mass spectrometry techniques, redundancy analysis, and orthogonal projections to latent structures discriminant analysis to analyze the sensory evaluation, physicochemical properties, organic acids, and volatile organic compounds (VOCs) of loquat beer with different proportions of loquat juice. The results shown that the addition of an appropriate amount of loquat juice (40%) enhanced the overall sensory quality of the beer; as the proportion of loquat juice increased, the contents of malic acid and tartaric acid significantly increased (p < 0.05). A total of 100 VOCs were identified, among which 23 key VOCs (VIP > 1, p < 0.05) represented the most important characteristic flavor components in loquat beer based on their odor activity value (OAV). This study holds significant importance for the value-added processing and economic development of loquat.