Metabolites最新文献

Background: Cancer is a leading cause of mortality worldwide, characterized by metabolic reprogramming, including alterations in fatty acid (FA) metabolism. Plasma FA profiles hold promise as non-invasive biomarkers for the diagnosis and classification of cancer. Objectives: This study aimed to investigate the diagnostic potential of plasma FA profiles across four major cancers and to identify shared and cancer-type-specific metabolic alterations. Methods: We examine comprehensive FA profiling of plasma samples from 368 individuals, including patients with colorectal (CRC, n = 94), gastric (GC, n = 55), esophageal (EC, n = 53), and lung cancer (LC, n = 73), alongside 93 healthy controls (HCs) by gas chromatography-mass spectrometry. Data were analyzed using univariate statistics and multivariate modeling analysis. Results: Univariate analysis showed a shared set of altered FAs across the cancer types, demonstrating a shared pan-cancer metabolic shift. A comprehensive comparison revealed a remarkable shared pattern within the gastrointestinal (GI) cancers (GC, CRC, EC), while LC showed opposite trends for most FAs. Partial Least Squares Discriminant Analysis (PLS-DA) models on a 70% training set excellently discriminated each cancer type from HCs. The cross-validation of the model demonstrated robust internal performance with Q² = 0.675 (LC), 0.559 (GC), 0.774 (CRC), and 0.628 (EC). This is followed by assessing the diagnostic accuracy on a 30% hold-out test set, with area under the curve (AUC) values of 0.686 (LC), 0.926 (GC), 0.905 (CRC), and 0.843 (EC). Conclusions: Plasma FA profiles may provide a potential source of biomarkers, capturing both shared cancer markers and distinct tissue-specific metabolic alterations. These findings highlight the high diagnostic and classificatory potential of FAs alterations in oncology.

The authors would like to make the following correction to their published paper [...].

Background: Survivors with chronic sequelae of carbon monoxide (CO) poisoning after the 1963 Miike-Mikawa coal mine disaster can exhibit persistent higher brain dysfunction in late life. We examined whether serum metabolic alterations remained detectable ~60 years later and assessed serum brain-derived neurotrophic factor (BDNF).

Methods: In this cross-sectional case-control study, outpatients with chronic CO-poisoning sequelae (CO; n = 14) and former miners without CO exposure (CON; n = 16), all aged ≥ 75 years, underwent targeted serum metabolomics (1183 metabolites) and clinical assessments. Between-group differences were evaluated using Welch's t-test, and age-matched propensity-score matching (1:1) served as a sensitivity analysis. BDNF was additionally compared using a linear regression/ analysis of covariancemodel adjusting for age and Mini-Mental State Examination (MMSE).

Results: Relative to controls, the CO group showed higher valine, alanine, and betaine and lower 3-hydroxybutyric acid, inosine, and hypoxanthine; these contrasts persisted with concordant direction after matching. Serum BDNF was lower in the CO group (unadjusted trend) and was significantly reduced after age/MMSE adjustment (p = 0.0252). Exploratory correlations between clinical measures and selected metabolites/BDNF were attenuated after accounting for group.

Conclusions: Six decades after exposure, chronic CO sequelae were associated with a reproducible serum profile combining amino-acid elevations with relative suppression of ketone-body and purine-related metabolites, suggesting enduring alterations in systemic substrate handling and bioenergetics. If replicated in larger cohorts, such signatures-potentially alongside BDNF-should be regarded as hypothesis-generating; biomarker development would require external validation, longitudinal tracking, and assessment of intervention responsiveness before any clinical use is considered.

Background: Fatty acid oxidation disorders (FAOD) are rare inborn errors of metabolism that impair mitochondrial β-oxidation and energy production. Management includes fasting avoidance for all FAOD types. Patients with long-chain FAOD are advised to restrict long-chain triglycerides (LCTs) to 10% of total energy intake and supplement medium-chain triglycerides (MCTs). The impact of such dietary modification on fat-soluble vitamin status has not yet been studied. Methods: In this cross-sectional study, serum concentrations of vitamins A, 25(OH)D, E, and β-carotene were measured in 36 FAOD patients and 36 healthy controls matched for age and sex. Vitamins A, E, and β-carotene were quantified using high-performance liquid chromatography and vitamin 25(OH)D through an immunoassay. FAOD patients were further divided into fat-modified (LCT-restricted) and standard-fat diet subgroups based on dietary management. Results: FAOD patients had significantly higher vitamin A concentrations than controls (p < 0.05), while there was no difference in vitamins 25(OH)D, E, and β-carotene. Within the FAOD cohort, the fat-modified group had higher levels of vitamins A and 25(OH)D but lower levels of vitamin E and β-carotene than the standard-fat group (all p < 0.05). Vitamin 25(OH)D deficiency (<20 ng/mL) was more frequent in the standard-fat group (p = 0.03). Conclusions: Fat-modified diets influence fat-soluble vitamin status in FAOD, emphasising the importance of ongoing monitoring and tailored supplementation. Future work should focus on optimising nutritional management, including modifications to formula composition, and on addressing the currently limited evidence on nutritional status and vitamin deficiencies in patients with FAOD.

The authors would like to make the following correction to their published paper [...].

Background: This study evaluated the effects of rumen-protected choline (RUPCHOL) supplementation in dairy cows from 21 days before calving to 28 days postpartum. The objective was to determine how RUPCHOL influences metabolic status, milk composition, and subsequent calf growth until weaning.

Methods: Twenty-seven pregnant Holstein cows were assigned to a Control group (n = 13) or an RUPCHOL group (n = 14), both receiving a total mixed ration (TMR), with the RUPCHOL group supplemented with 15 g/day of choline chloride. Cows were monitored during prepartum, calving, and postpartum periods for body weight, body condition score, dry matter intake, rectal temperature, milk yield and composition, and blood metabolites.

Results: RUPCHOL supplementation tended to reduce serum aspartate aminotransferase and lowered concentrations of non-esterified fatty acids and β-hydroxybutyrate, indicating improved metabolic status. Milk total solids, fat, and protein percentages were higher in RUPCHOL-fed cows, suggesting enhanced milk quality. Maternal supplementation did not affect colostrum immunoglobulin G (IgG) content or calf body weight and body measurements (heart girth, wither height, hip height, and body length) from birth to weaning.

Conclusions: In summary, RUPCHOL supplementation improved indicators of metabolic health and milk composition of dairy cows during the peripartum period without altering calf growth outcomes.

The tumor heterogeneity that is frequently observed in cancer tissues comprises not only cancer cells but also stromal cells in the tumor microenvironment. One of the major components of tumor stroma, i.e., cancer-associated fibroblasts (CAFs), play crucial roles in tumor progression and the tumor response to chemotherapy. The known subtypes of CAFs are antigen-presenting CAFs (apCAFs), myofibroblastic CAFs (myCAFs), and inflammatory CAFs (iCAFs). It has been speculated that (i) the heterogeneity of CAF subtypes might contribute to tumor progression; (ii) cell-to-cell interactions among CAF subtypes in tumors might be associated with the development of various types of carcinomas, and (iii) juxtracrine and/or paracrine signaling from CAFs may play important roles in this development. A clarification of the mechanisms that underlie the tumoral heterogeneity of CAFs could contribute to cancer treatment as precision medicine. This review explains the significance of CAF heterogeneity in tumor microenvironments, especially concerning the CAF subtypes.

Background: The Camellia genus is widely recognized for its remarkable diversity in floral morphology and coloration, with Camellia petelotii (Merr.) Sealy being particularly notable for its rare golden-yellow flowers, which possess exceptional ornamental value. Despite its horticultural significance, the molecular mechanisms governing its flowering process remain poorly elucidated, presenting a substantial barrier to effective conservation and breeding initiatives. Methods: To address this knowledge gap, we conducted a comprehensive transcriptomic analysis, focusing on three distinct developmental stages of C. petelotii floral organs: the alabastrum stage (S1), the half-opened flower stage (S2), and the full bloom stage (S3). These samples were subjected to high-throughput sequencing using the Illumina platform. Following rigorous quality control and alignment with the reference genome, we performed transcript assembly and integrated comprehensive gene annotation data with quantitative gene expression profiles. Results: Our analysis identified 18,732 differentially expressed genes (DEGs) showing significant expression changes across developmental stages. Notably, we identified 134 DEGs as potential flowering-related genes, which were functionally associated with key pathways involved in floral regulation, including plant hormone signal transduction (e.g., AUX/IAA, ARF, SAUR, GH3, JAR4, GID1 and SOC1), starch (SS, SUS, BAM) and sucrose metabolism (HK, FrK, and GH32), circadian rhythm regulation (e.g., PIF3, ELF3, LHY, and PRR), and the Autonomous pathway. Building upon these findings, we have proposed a comprehensive model illustrating the regulatory network underlying flowering transition in C. petelotii. The reliability of the transcriptomic data was demonstrated through the validation of 11 genes using quantitative real-time PCR (qRT-PCR). Conclusions: These insights not only enhance our understanding of the molecular basis of flowering in this species but also provide a valuable theoretical framework for future genetic improvement and breeding programs of C. petelotii.

Background: Traditional machine-learning approaches face challenges when attempting to integrate diverse biological information for predicting metabolite-disease relationships. The intricate connections linking metabolites, diseases, proteins, and Gene Ontology (GO) annotations present substantial obstacles for conventional pairwise graph representations, which prove inadequate for modeling such complex multi-way interactions. Methods: An innovative hypergraph-based framework (DHG-LGB) was developed to exploit this complexity through conceptualizing diseases as hyperedges. Within this architecture, individual hyperedges link multiple vertices including metabolites, proteins, and GO annotations, thereby enabling richer representation of the biological networks underlying metabolite-disease relationships. Metabolite-disease relationships were encoded as low-dimensional vectors through hypergraph neural network (HGNN) operations incorporating Laplacian smoothing and message propagation mechanisms. LightGBM (LGB) was used to construct a model for identifying the potential metabolite-disease associations. Results: Under 5-fold cross-validation, DHG-LGB achieved 98.87% accuracy, 91.77% sensitivity, 99.58% specificity, 95.60% precision, Matthews correlation coefficient (MCC) of 0.9305, receiver operating characteristic area under curve (AUC) of 0.9983, and precision-recall area under curve (AUPRC) of 0.9860. The framework maintained strong performance when tested with varying positive-to-negative ratios (spanning 1:1 through 1:10), consistently achieving AUC values exceeding 0.9954 and AUPRC values above 0.9820, thereby confirming excellent robustness and generalization capability. Comparative evaluations against existing methodologies verified the superiority of DHG-LGB. Conclusions: The DHG-LGB framework delivers more comprehensive modeling of biological interactions relative to conventional approaches and substantially enhances predictive accuracy for metabolite-disease relationships. It is foreseeable that it will be a valuable computational tool for biomarker identification and precision medicine initiatives.

Background/objectives: Exercise calorimetry provides a means to quantify the relative contributions of lipid and carbohydrate (CHO) oxidation across a range of exercise intensities. Although lipid oxidation capacity has been widely studied-particularly in relation to exercise prescription for individuals with obesity-the factors governing CHO oxidation during exercise are less clearly defined. This study therefore aimed to investigate, within a large single-center cohort, not only the established determinants of maximal lipid oxidation (LIPOXmax) but also those influencing CHO oxidation.

Methods: Exercise calorimetry was performed in a cohort of 6465 individuals (4561 women and 1904 men; mean age 46.5 years; mean BMI 33.6 kg/m²). Two principal physiological indices were derived: LIPOXmax, defined as the exercise intensity eliciting maximal rates of fat oxidation, and the carbohydrate cost of the watt (CCW), defined as the slope characterizing the relationship between CHO oxidation and power output.

Results: LIPOXmax showed positive associations with lean and muscle mass, and negative associations with fat mass and age, supporting the notion that greater muscle mass enhances the capacity for fat oxidation. Although men demonstrated higher absolute maximal fat oxidation rates, adjustment for body composition revealed that women exhibited relatively higher lipid oxidation (+30%, p < 0.001), occurring at a greater percentage of V˙O_2max (+9.2%, p < 0.001). Furthermore, the carbohydrate cost of the watt was significantly elevated in women (+17.8% compared with men). CCW was positively correlated with BMI, fat mass, and age, and negatively correlated with muscle mass, LIPOXmax, and the crossover point-that is, the exercise intensity at which CHO becomes the predominant substrate.

Discussion and conclusions: Individuals with higher adiposity exhibited a greater reliance on carbohydrate oxidation, whereas leaner individuals preferentially oxidized lipids at comparable exercise intensities. These observations reinforce the reciprocal interplay between lipid and carbohydrate metabolism during exercise and highlight the substantial influence of body composition, age, and sex. Notably, this study provides the first comprehensive characterization of the determinants of CHO oxidation during exercise, identifying sex, age, and adiposity as major contributing factors. This underexplored facet of metabolic flexibility may hold practical relevance in clinical contexts such as obesity or susceptibility to exercise-induced hypoglycemia.