Metabolites

32 pages, 8586 KB

Open AccessReview

Exercise and Sports Metabolomics: Analytical Platforms, Metabolite Annotation, Pathway-Level Interpretation, and Biomarker-Panel Readiness

by Donghai Lin, Yifen Chen and Caihua Huang

Metabolites 2026, 16(8), 530; https://doi.org/10.3390/metabo16080530 - 27 Jul 2026

Abstract

Exercise and sports metabolomics provide a systems-level approach to characterizing how acute exercise, training adaptation, nutrition, recovery, and environmental stress reshape human metabolism. By profiling metabolites related to substrate utilization, mitochondrial function, redox balance, inflammation, muscle stress, and recovery kinetics, these approaches can [...] Read more.

Exercise and sports metabolomics provide a systems-level approach to characterizing how acute exercise, training adaptation, nutrition, recovery, and environmental stress reshape human metabolism. By profiling metabolites related to substrate utilization, mitochondrial function, redox balance, inflammation, muscle stress, and recovery kinetics, these approaches can reveal pathway-level responses that conventional single biomarkers cannot capture. However, many exercise-responsive features remain difficult to interpret because of incomplete chemical identification, uncertain annotation confidence, limited quantitative reproducibility, variable pre-analytical control, inconsistent data processing, and insufficient biological validation. This narrative review examines recent advances in exercise and sports metabolomics, with emphasis on LC–MS, GC–MS, NMR spectroscopy, IMS–MS, and CE–MS workflows; platform selection; metabolite annotation and identification; pathway-level interpretation; and evidence requirements for candidate-panel development. Exercise-responsive metabolites should be interpreted as context-dependent pathway signals rather than isolated indicators of fatigue, recovery, adaptation, or performance. The review consolidates requirements for sampling, quality control, metadata capture, repeated-measures analysis, and external validation within an evidence-readiness roadmap. Wearable biochemical monitoring, AI-assisted analysis, and multi-omics integration may support future applications, but their value depends on analytical robustness, external validation, and physiological interpretability. Exercise and sports metabolomics should therefore progress from descriptive feature discovery toward reproducible, quantitatively reliable, and biologically validated pathway-level interpretation. Full article

(This article belongs to the Section Thematic Reviews)

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40 pages, 1132 KB

Open AccessReview

Metabolic Rewiring in MASLD: From Disease Mechanisms to Precision Medicine

by Amedeo Lonardo and Ralf Weiskirchen

Metabolites 2026, 16(8), 529; https://doi.org/10.3390/metabo16080529 - 27 Jul 2026

Abstract

Background/Objectives: Metabolic dysfunction-associated steatotic liver disease (MASLD), a leading cause of chronic liver disease, encompasses a continuum from steatosis to metabolic dysfunction-associated steatohepatitis (MASH), fibrosis, cirrhosis, and hepatocellular carcinoma. This review aimed to synthesize current evidence on how metabolomic, lipidomic, and spatial [...] Read more.

Background/Objectives: Metabolic dysfunction-associated steatotic liver disease (MASLD), a leading cause of chronic liver disease, encompasses a continuum from steatosis to metabolic dysfunction-associated steatohepatitis (MASH), fibrosis, cirrhosis, and hepatocellular carcinoma. This review aimed to synthesize current evidence on how metabolomic, lipidomic, and spatial multi-omic approaches illuminate MASLD pathogenesis and support precision hepatology. Methods: A structured narrative review was conducted through searches of PubMed, Scopus, and Web of Science, complemented by manual screening of key references. Studies were prioritized when they addressed MASLD biology, metabolic rewiring, lipid remodeling, mitochondrial dysfunction, inflammatory and fibrogenic pathways, gut–liver–adipose crosstalk, biomarker development, or therapeutic monitoring. Results: The reviewed evidence identifies MASLD as a systemic metabolic disorder shaped by excess lipid flux, enhanced de novo lipogenesis, impaired mitochondrial adaptation, oxidative and endoplasmic reticulum stress, sterile inflammation, and hepatic stellate-cell activation. Recurrent metabolomic signatures include altered amino acid, fatty acids, bile acid, and microbial co-metabolite pathways. Lipidomic studies consistently implicate depletion of protective polyunsaturated fatty acids, lysophosphatidylcholines, and phosphatidylcholines, in association with accumulation of diacylglycerols and ceramides, in the transition from steatosis to MASH and fibrosis. Emerging spatial and multi-omic analyses further resolve cell-specific metabolic niches involving hepatocytes, macrophages, endothelial cells, and stellate cells. Conclusions: Metabolomics provides a mechanistic and translational bridge between molecular injury, histological progression, and non-invasive risk stratification in MASLD. Future progress requires standardized analytical workflows, longitudinal validation, causal pathway interrogation, and integration with imaging, genetics, microbiome profiling, and treatment-response phenotyping. Clinical implementation will require standardized platforms, transparent metabolite identification, external validation across diverse populations, cost-effectiveness analyses, and regulatory-grade evidence of clinical utility. Full article

(This article belongs to the Special Issue Metabolomics and MASLD: Pathways, Biomarkers, and Clinical Insights)

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27 pages, 12128 KB

Open AccessSystematic Review

Acute Effects of Interrupting Prolonged Sitting on Glucose, Insulin and Lipid Metabolism in Healthy Populations: A Three-Level Meta-Analysis

by Mingnan Zhuang, Yufei Li, Zhengqi Qiu and Xueqin Zhang

Metabolites 2026, 16(8), 528; https://doi.org/10.3390/metabo16080528 - 27 Jul 2026

Abstract

Background/Objectives: Prolonged sedentary behavior is associated with adverse cardiometabolic risk, but the acute metabolic effects of interrupting sitting remain incompletely quantified in apparently healthy populations. The objective was to evaluate the acute effects of interrupting prolonged sitting on glucose, insulin and lipid metabolism [...] Read more.

Background/Objectives: Prolonged sedentary behavior is associated with adverse cardiometabolic risk, but the acute metabolic effects of interrupting sitting remain incompletely quantified in apparently healthy populations. The objective was to evaluate the acute effects of interrupting prolonged sitting on glucose, insulin and lipid metabolism and to identify potential protocol-level moderators. Methods: We conducted a three-level meta-analysis of randomized crossover trials comparing structured sitting interruptions with uninterrupted sitting in apparently healthy participants, an approach used to account for the statistical dependency among multiple effect sizes reported within individual studies. PubMed, Embase, Web of Science, Scopus and Cochrane Library were searched from inception through March 2026. Standardized mean differences (Hedges’ g) were calculated using random-effects models with robust variance estimation. Subgroup analyses and meta-regression examined interruption modality, intensity, frequency and duration. Certainty of evidence was assessed using GRADE. Results: The evidence base comprised 25 publications representing 23 independent cohorts; primary outcome analyses included 23 cohorts (135 effect sizes). Sitting interruption produced small but significant reductions in glucose (g = −0.28, 95% CI −0.49 to −0.08; PI −1.15 to 0.59) and insulin (g = −0.22, 95% CI −0.36 to −0.07; PI −0.51 to 0.07). No significant effect was observed for triglycerides (g = −0.04, 95% CI −0.14 to 0.07), whereas the exploratory estimates for non-esterified fatty acids (NEFA) and C-peptide were inconclusive. Subgroup analyses did not identify any statistically significant moderators of glucose, insulin or triglyceride responses; all subgroup estimates drawn from fewer than five independent cohorts are exploratory and hypothesis-generating. Meta-regression identified no statistically significant linear moderators. Certainty of evidence was low for all three primary outcomes (glucose, insulin and triglycerides) and very low for the exploratory outcomes (NEFA and C-peptide). Conclusions: Interrupting prolonged sitting may produce modest acute improvements in glucose and insulin responses in apparently healthy participants but does not reliably affect triglyceride metabolism. Given the low certainty of the current evidence, sitting interruption may be considered a low-burden adjunctive behavior for reducing uninterrupted sitting time. However, the current evidence primarily supports the hypothesis that interrupting prolonged sitting is a promising behavioral strategy rather than an evidence-based clinical recommendation, and its metabolic effects require confirmation in adequately powered, higher-quality trials. Full article

(This article belongs to the Special Issue Effects of Exercise and Lifestyle on Cardiometabolic Health)

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18 pages, 983 KB

Open AccessReview

Metabolic Dysregulation in ADHD: Implications for Appetite, Sleep, Stress Reactivity, and Pharmacological Treatment

by Davoud Amiri, Swetang J. Shah, Lamberto Briziarelli, Sara Amiri and Barry Karlsson

Metabolites 2026, 16(8), 527; https://doi.org/10.3390/metabo16080527 - 27 Jul 2026

Abstract

Background: Attention-deficit/hyperactivity disorder (ADHD) has traditionally been understood through executive and frontostriatal models, but increasing evidence suggests that metabolic, inflammatory, circadian, and neuroendocrine mechanisms may also contribute to clinical heterogeneity. The hypothalamus is a central regulatory hub for appetite, sleep–wake organization, stress responsivity, [...] Read more.

Background: Attention-deficit/hyperactivity disorder (ADHD) has traditionally been understood through executive and frontostriatal models, but increasing evidence suggests that metabolic, inflammatory, circadian, and neuroendocrine mechanisms may also contribute to clinical heterogeneity. The hypothalamus is a central regulatory hub for appetite, sleep–wake organization, stress responsivity, autonomic function, and endocrine signalling. Objective: This review evaluated evidence linking ADHD with hypothalamic inflammation and related metabolic, inflammatory, circadian, and neuroendocrine dysregulation, with particular emphasis on appetite regulation, sleep and circadian function, stress reactivity, and pharmacological treatment response and tolerability. Methods: A systematic literature search was conducted in PubMed/MEDLINE, Embase, PsycINFO, Scopus, and Web of Science Core Collection from database inception to 31 May 2026. Human observational and intervention studies formed the primary evidence base. Evidence was synthesized narratively. Where available, quantitative findings from previously published meta-analyses were summarized to provide an overview of the strength and consistency of the evidence. Results: The reviewed evidence indicates that ADHD is associated with increased obesity risk, altered appetite-related hormones, immune-inflammatory changes, delayed circadian timing, atypical cortisol responsivity, and treatment-related effects on appetite, sleep, cardiovascular physiology, and tolerability. The strongest quantitative evidence concerned obesity, inflammatory markers, appetite hormones, and type 2 diabetes risk. Direct evidence for hypothalamic inflammation in ADHD remains limited, but converging indirect findings support hypothalamic and neuroendocrine mechanisms as biologically plausible contributors in a subgroup of individuals with ADHD. Conclusions: ADHD appears to be associated with broader metabolic, inflammatory, circadian, and neuroendocrine vulnerabilities beyond its core attentional and behavioural symptoms. Hypothalamic pathways should be interpreted as a mechanistic hypothesis rather than an established causal mechanism. Future longitudinal and multimodal studies are needed to clarify causality and identify biologically defined ADHD subgroups. Full article

(This article belongs to the Special Issue The Interaction Between Metabolic Dysfunction and Hypothalamic Inflammation)

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24 pages, 6844 KB

Open AccessArticle

LipidAnalyst: A Comprehensive Tool for Lipidomic Data Visualization and Analysis

by Xinyi Liu, Alla Karnovsky, Subramaniam Pennathur and Farsad Afshinnia

Metabolites 2026, 16(8), 526; https://doi.org/10.3390/metabo16080526 - 25 Jul 2026

Abstract

Introduction: Proper analysis of high-throughput lipidomic data requires specialized tools for data processing, normalization, visualization, and statistical and bioinformatic analysis. However, limitations in lipid parsing, data processing, and visualization capabilities in existing software packages create challenges for comprehensive lipidomic data analysis. To address [...] Read more.

Introduction: Proper analysis of high-throughput lipidomic data requires specialized tools for data processing, normalization, visualization, and statistical and bioinformatic analysis. However, limitations in lipid parsing, data processing, and visualization capabilities in existing software packages create challenges for comprehensive lipidomic data analysis. To address these limitations, we developed LipidAnalyst (v 1.0.3), a user-friendly tool designed to facilitate efficient lipid parsing and processing, visualization, and analysis of lipidomic datasets. Methods: LipidAnalyst was developed using the R Shiny framework. It is hosted on MiServer for online work but can also be downloaded from GitHub. Results: LipidAnalyst provides functionalities in three major areas: data processing, visualization, and statistical analysis. Data processing features include quality control filtering, normalization, internal standard-based quantification, and unique capabilities for missing-value imputation, lipid parsing, and aggregation. Visualization tools include box and violin plots for data distribution assessment, principal component analysis (PCA) plots, hierarchical clustering and differential abundance heatmaps, volcano plots, correlation plots, and Debiased Sparse Partial Correlation (DSPC) clustering plots. Statistical analysis modules include t-test, analysis of variance (ANOVA), Partial Least Squares Differential Analysis (PLS-DA), Orthogonal Partial Least Squares Differential Analysis (OPLS-DA), and Random Forest (RF) modeling. Conclusions: LipidAnalyst is a comprehensive platform for optimal processing, visualization, and analysis of lipidomic data. By integrating advanced data processing workflows with extensive visualization and statistical analysis capabilities, LipidAnalyst enables researchers to explore lipidomic datasets more effectively and develop informed analytical strategies. Full article

(This article belongs to the Special Issue Open-Source Software in Metabolomics, 2nd Edition)

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19 pages, 958 KB

Open AccessArticle

Development of the Beta-Weighted Lacto-Glycemic Equation (β-LGE): A Dual-Application Machine Learning Framework for Non-Exhaustive Maximal Aerobic Capacity Estimation

by Ömer Özer, Ahmet Kurtoğlu, Musa Türkmen, Bekir Çar, Jarosław Muracki, Ali Tatlıcı and Safaa M. Elkholi

Metabolites 2026, 16(8), 525; https://doi.org/10.3390/metabo16080525 - 24 Jul 2026

Abstract

Background and Objective: Maximal oxygen uptake (VO₂max) is a fundamental indicator of cardiorespiratory fitness in sports medicine, essential for athletic profiling and training prescription. However, traditional direct measurements require exhaustive physical testing, which induces considerable physiological stress, limits testing frequency, and [...] Read more.

Background and Objective: Maximal oxygen uptake (VO₂max) is a fundamental indicator of cardiorespiratory fitness in sports medicine, essential for athletic profiling and training prescription. However, traditional direct measurements require exhaustive physical testing, which induces considerable physiological stress, limits testing frequency, and increases the risk of injury. To address this problem, this study aimed to eliminate the need for exhaustive protocols by developing a highly precise, non-invasive digital prediction model for VO₂max utilizing readily available anthropometric data and acute metabolic biomarkers (blood glucose and lactate kinetics). Methods: To overcome the limitations of a small initial empirical sample (n = 16) and prevent model overfitting, the original dataset was statistically augmented to create a robust synthetic cohort (n = 200) using Multivariate Normal Distribution and k-Nearest Neighbors (k-NN) algorithms. Three different machine learning models (Multiple Linear Regression [MLR], Random Forest [RF], and Support Vector Regression [SVR]) were trained using such parameters as sex, height, weight, baseline/pre-exercise, and net (Δ) glucose and lactate concentrations. Evaluation of the performance of the models included tenfold cross-validation and Bland–Altman analysis as a measure of clinical agreement. Results: Among the three algorithms used, the highest correlation coefficient (R² = 0.939) was observed for SVR, along with the lowest error metrics (RMSE = 1.442 mL/kg/min, MAPE = 2.78%). Moreover, SVR showed remarkable performance in predicting VO₂max of female (R² = 0.890) and male (R² = 0.702) athletes separately. Also, Bland–Altman analysis proved almost zero-bias estimation with 95% limits of agreement ranging between −4.40 and 4.43 mL/kg/min. In order to bypass the black-box problem of complex algorithms for practical application in the field, the MLR model was used for the development of the Beta-Weighted Lacto-Glycemic Equation (β-LGE). Conclusions: In this work, a unique dual-model approach was introduced, with the SVR algorithm serving as a high-performance backend of a digital tool for sport technologists and Beta-Weighted LGE providing a practical calculation formula for coaches. This innovative approach allowed for a completely non-exhaustive profiling of an athlete’s VO₂max using only minimally invasive metabolic measurements. Full article

(This article belongs to the Special Issue Metabolic Adaptations to Exercise: Mechanisms, Modulators, and Health Impacts)

14 pages, 6587 KB

Open AccessArticle

Association of M2BPGi with Subclinical Atherosclerosis in Metabolic Dysfunction-Associated Steatotic Liver Disease

by Yong Jun Choi, Kyunghoon Lee, Han-Ik Cho, Jooheon Park, Myung Geun Shin, Ye Seol Lee, Sun Cho and Eun-Hee Nah

Metabolites 2026, 16(8), 524; https://doi.org/10.3390/metabo16080524 - 24 Jul 2026

Abstract

Background/Objectives: Metabolic dysfunction-associated steatotic liver disease (MASLD) is increasingly recognized as a systemic metabolic disorder associated with an elevated risk of cardiovascular disease. Mac-2 binding protein glycosylation isomer (M2BPGi), a noninvasive serum biomarker of hepatic fibrosis, has also been linked to adverse [...] Read more.

Background/Objectives: Metabolic dysfunction-associated steatotic liver disease (MASLD) is increasingly recognized as a systemic metabolic disorder associated with an elevated risk of cardiovascular disease. Mac-2 binding protein glycosylation isomer (M2BPGi), a noninvasive serum biomarker of hepatic fibrosis, has also been linked to adverse metabolic and cardiovascular outcomes. However, the association between serum M2BPGi levels and subclinical coronary atherosclerosis in individuals with MASLD remains unclear. We investigated the association between serum M2BPGi levels and coronary artery calcium score (CACS), an established imaging marker of subclinical atherosclerosis, in individuals with MASLD. Methods: This retrospective cross-sectional study included 6514 adults with MASLD who underwent health screening examinations between 2020 and 2025. Participants were categorized into quartiles according to serum M2BPGi levels: Q1 (<0.48), Q2 (0.48–0.61), Q3 (0.62–0.80), and Q4 (≥0.81). Coronary artery calcification (CAC) was defined as CACS > 0. Multivariable logistic regression analysis was performed after adjustment for age, sex, smoking status, liver enzymes, adiposity, dysglycemia, blood pressure, and lipid profile. Multivariable ordinal logistic regression analysis was additionally performed to evaluate the association between M2BPGi levels and CAC severity. Results: The prevalence of CAC increased progressively across M2BPGi quartiles (39.4%, 45.3%, 48.5%, and 57.4% for Q1–Q4, respectively; p < 0.001). In multivariable logistic regression analysis, participants in the highest M2BPGi quartile had significantly higher odds of CAC presence than those in the lowest quartile (OR, 1.32; 95% CI, 1.10–1.58; p = 0.0035). Higher M2BPGi quartiles were also independently associated with greater CAC severity in multivariable ordinal logistic regression analysis (OR, 1.33; 95% CI, 1.13–1.57; p = 0.0007 for Q4 vs. Q1). Conclusions: Higher serum M2BPGi levels were independently associated with both the presence and severity of CAC in individuals with MASLD. These findings suggest that M2BPGi may serve as a potential biomarker for identifying individuals with MASLD at increased risk of subclinical atherosclerosis and may complement conventional cardiovascular risk assessment. Full article

(This article belongs to the Special Issue Biomarkers and Metabolites in Clinical Practice and Research)

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31 pages, 7199 KB

Open AccessArticle

Comprehensive Profiling of Antioxidant, Antidiabetic, and Cytotoxic Compounds from Morinda lucida Benth Using ¹H-NMR- and UHPLC-Q Exactive Orbitrap MS-Based Metabolomics Combined with Molecular Networking and Molecular Docking

by Dorcas Tlhapi, Ntsoaki Malebo, Idah Tichaidza Manduna, Monizi Mawunu, Chika Ifeanyi Chukwuma, Ramakwala Christinah Chokwe and Kolawole Olofinsan

Metabolites 2026, 16(8), 523; https://doi.org/10.3390/metabo16080523 - 24 Jul 2026

Abstract

Background/Objectives: Morinda lucida Benth is widely distributed throughout Central and West Africa. It has traditionally been used to treat and manage various diseases. However, scientific research on its phytochemical and pharmacological properties remains scarce. This study investigated the phytochemical profiles, antioxidant activities, [...] Read more.

Background/Objectives: Morinda lucida Benth is widely distributed throughout Central and West Africa. It has traditionally been used to treat and manage various diseases. However, scientific research on its phytochemical and pharmacological properties remains scarce. This study investigated the phytochemical profiles, antioxidant activities, α-glucosidase inhibitors, and cytotoxic effects of compounds derived from various parts of M. lucida. Methods: Seventy-seven natural compounds were putatively annotated using ¹H-NMR, UHPLC–Q Exactive Orbitrap MS, and molecular networking techniques. The antioxidant activities of the crude extracts were assessed in vitro using DPPH free radical scavenging and reducing power assays, whereas the in vitro α-glucosidase inhibition activity and toxicity of the crude extracts were evaluated using the α-glucosidase inhibition and MTT assays. Molecular docking was used to assess the interactions between the identified glycosides and the α-glucosidase protein. Results: The root extract exhibited the highest DPPH free radical scavenging (IC₅₀ = 7.7550 ± 6.9142 μg/mL) and reducing power capacity (IC_0.5 = 0.0052 ± 0.0025 μg/mL). In contrast, the stem bark extract demonstrated significant inhibition of alpha-glucosidase (IC₅₀ = 79.9 ± 16.1 µg/mL). Sophoricoside, formononetin 7-O-glucoside, and epicatechin identified in the stem bark extract showed notable in silico interactions with the α-glucosidase protein. The stem bark and leaf extracts were more toxic than the root extract at different concentrations. Conclusions: The results of this study demonstrate the therapeutic potential of M. lucida and provide information on its phytochemical composition and pharmacological properties. Full article

(This article belongs to the Section Metabolomic Profiling Technology)

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1 pages, 133 KB

Open AccessCorrection

Correction: Zupo et al. Dietary Intake of Polyphenols and All-Cause Mortality: A Systematic Review with Meta-Analysis. Metabolites 2024, 14, 404

by Roberta Zupo, Fabio Castellana, Giuseppe Lisco, Filomena Corbo, Pasquale Crupi, Rodolfo Sardone, Francesco Panza, Madia Lozupone, Mariangela Rondanelli and Maria Lisa Clodoveo

Metabolites 2026, 16(8), 522; https://doi.org/10.3390/metabo16080522 - 24 Jul 2026

Abstract

There was an error in the original publication [...] Full article

(This article belongs to the Special Issue Epidemiology, Nutrition and Metabolism, 2nd Edition)

1 pages, 121 KB

Open AccessCorrection

Correction: Zhao et al. Effects of Different Feed Additives on Intestinal Metabolite Composition of Weaned Piglets. Metabolites 2024, 14, 138

by Mingxuan Zhao, Jian Zhang, Fuzhou Liu, Lv Luo, Mingbang Wei, Yourong Ye, Chamba Yangzom and Peng Shang

Metabolites 2026, 16(8), 521; https://doi.org/10.3390/metabo16080521 - 24 Jul 2026

Abstract

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

1 pages, 168 KB

Open AccessCorrection

Correction: Santos et al. Salicylic Acid and Water Stress: Effects on Morphophysiology and Essential Oil Profile of Eryngium foetidum. Metabolites 2024, 14, 241

by Sabrina Kelly dos Santos, Daniel da Silva Gomes, Vanessa de Azevedo Soares, Estephanni Fernanda Oliveira Dantas, Ana Flávia Pellegrini de Oliveira, Moises Henrique Almeida Gusmão, Elyabe Monteiro de Matos, Tancredo Souza, Lyderson Facio Viccini, Richard Michael Grazul, Juliane Maciel Henschel and Diego Silva Batista

Metabolites 2026, 16(8), 520; https://doi.org/10.3390/metabo16080520 - 24 Jul 2026

Abstract

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

(This article belongs to the Special Issue Metabolic Responses of Plants to Abiotic Stress)

20 pages, 1270 KB

Open AccessReview

AI-Assisted Spatial Metabolic Engineering in Plants: Integrating Flux Design, Spatial Omics, and Synthetic Biology

by Huize Chen, Jia Yang and Meiting Du

Metabolites 2026, 16(8), 519; https://doi.org/10.3390/metabo16080519 - 23 Jul 2026

Abstract

Background: Plant synthetic biology reprograms metabolic networks for the sustainable production of high-value compounds. Recent computational advances incorporate machine learning to accelerate the design-build-test-learn (DBTL) cycle, enabling more predictable and scalable engineering in photoautotrophic chassis. However, the translation of AI-generated designs into stable [...] Read more.

Background: Plant synthetic biology reprograms metabolic networks for the sustainable production of high-value compounds. Recent computational advances incorporate machine learning to accelerate the design-build-test-learn (DBTL) cycle, enabling more predictable and scalable engineering in photoautotrophic chassis. However, the translation of AI-generated designs into stable plant phenotypes remains constrained by incomplete plant-specific training datasets, tissue heterogeneity, and limited in vivo validation. Scope: This review examines the convergence of machine learning methods with plant metabolic engineering across four spatial engineering levels: subcellular compartmentalization, cell/tissue/organ-specific control, developmental or inducible regulation, and genome-level organization. Spatial omics is considered a cross-cutting validation layer, and the evidence supporting each technology is classified as plant-demonstrated, non-plant proof-of-concept, or prospective. Conclusions: Integrating predictive machine learning with spatial engineering offers promising strategies to design complex biosynthetic pathways. Hybrid approaches, combining constraint-based metabolic models with generative algorithms, reduce trial-and-error in crop engineering. Future plant synthetic biology is likely to rely increasingly on automated and data-rich workflows to support more predictable plant bioproduction. Full article

(This article belongs to the Section Plant Metabolism)

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13 pages, 240 KB

Open AccessArticle

Partial Substitution of Soybean Meal with a Yeast-Fermented Vinasse Protein Source: Effects on Milk Yield, Composition, and Serum Biochemistry in Crossbred Dairy Cows

by Ahmet Akdag

Metabolites 2026, 16(8), 518; https://doi.org/10.3390/metabo16080518 - 23 Jul 2026

Abstract

Background/Objectives: This study aimed to compare the effects of two distinct dietary protein sources, soybean meal (SBM, 454 g CP/kg dry matter [DM]) and fermented protein source (FPS, 635 g CP/kg DM), on milk yield (MY), milk quality traits, and serum biochemistry in [...] Read more.

Background/Objectives: This study aimed to compare the effects of two distinct dietary protein sources, soybean meal (SBM, 454 g CP/kg dry matter [DM]) and fermented protein source (FPS, 635 g CP/kg DM), on milk yield (MY), milk quality traits, and serum biochemistry in crossbred dairy cows. Methods: This study employed a randomized complete block design with four groups (n = 6 per group): Control (120 g/kg SBM), FPS30 (30 g/kg FPS and 75 g/kg SBM), FPS40 (40 g/kg FPS and 60 g/kg SBM), and FPS50 (50 g/kg FPS and 45 g/kg SBM). Results: After 66 days (21-day adaptation period and 45-day feeding trial), DM intake, milk protein content, and milk density did not differ significantly across groups. However, MYs were significantly higher in the FPS50 group (p = 0.043). Additionally, milk fat (p = 0.021), DM (p = 0.013), solids-non-fat (SNF, p = 0.047), and lactose content (p = 0.007) were significantly higher in the FPS groups. Although serum biochemistry did not differ across groups on day 0, blood urea nitrogen (BUN, p = 0.044) and serum Ca (p = 0.041), P (p = 0.039), and Mg (p = 0.041) concentrations were significantly lower in the FPS groups on day 66. Moreover, FPS intake correlated positively with MY (R = 0.680), milk DM (R = 0.706), fat (R = 0.665), SNF (R = 0.566), lactose content (R = 0.653), and fat-to-protein ratio (R = 0.507) and negatively with milk density (R = −0.429) and mineral content (R = −0.271). Conclusions: These findings indicate that FPS is effective in increasing productivity and improving/maintaining milk quality traits in cows fed diets substituting specific amounts of SBM with FPS. The induced reduction in BUN can be interpreted as increased protein utilization. Full article

(This article belongs to the Special Issue Metabolic Responses to Feed and Nutrition in Livestock)

24 pages, 712 KB

Open AccessArticle

BMI-Stratified Physiological Responses to a 12-Week Mat Pilates Intervention on Body Composition, Cardiometabolic Risk Factors, and Autonomic Function in Middle-Aged Women: An Exploratory Secondary Analysis

by Won-Sang Jung, Won-Je Kim, Eunjoo Lee, Hana An and Hun-Young Park

Metabolites 2026, 16(8), 517; https://doi.org/10.3390/metabo16080517 - 23 Jul 2026

Abstract

Background/Objectives: Mat Pilates is widely recommended for middle-aged women, but whether baseline obesity modifies its effects remains unclear. This study compared responses to a 12-week mat Pilates programme between non-obese and obese middle-aged women across body-composition, cardiovascular, blood-metabolic, haemorheological and autonomic endpoints. [...] Read more.

Background/Objectives: Mat Pilates is widely recommended for middle-aged women, but whether baseline obesity modifies its effects remains unclear. This study compared responses to a 12-week mat Pilates programme between non-obese and obese middle-aged women across body-composition, cardiovascular, blood-metabolic, haemorheological and autonomic endpoints. Methods: In an exploratory secondary analysis of a completed, uncontrolled single-arm intervention cohort, de-identified pre- and post-intervention data from 32 premenopausal women (47.5 ± 7.6 years) were stratified by BMI into non-obese (NOG; <25 kg/m²; n = 14) and obese (OG; ≥25 kg/m²; n = 18) groups using WHO Asia-Pacific criteria. All completed identical 60 min sessions three times weekly for 12 weeks, with intensity progressed every four weeks. Outcomes were analysed with mixed-design ANOVA and Bonferroni-corrected paired t-tests. Results: Group × time interactions were significant for body weight, fat mass and percent body fat (p < 0.05). Flow-mediated dilation rose in both groups (NOG +15.6%, OG +29.7%; p < 0.05). Group × time interactions were non-significant for blood pressure, lipids and haemorheology; obesity-dependent claims are therefore restricted to the outcomes with significant interactions (body weight, fat mass, percent body fat). For the remaining outcomes, within-group changes reached significance only in the OG (total cholesterol, LDL-cholesterol, aggregation index, critical shear stress) or only in the NOG (diastolic and mean arterial pressure) but did not differ significantly between groups. Conclusions: Following the programme, endothelial function improved in both groups, whereas body-composition responses differed significantly by obesity status. Because this uncontrolled secondary analysis lacked a non-exercising control group, these associations cannot be attributed causally to mat Pilates. The apparent BMI dependence was not reproduced when adiposity was modelled continuously (baseline BMI, percent body fat or fat mass), so all between-group contrasts are hypothesis-generating. Adequately powered randomised controlled trials with a non-exercising comparator and objective monitoring of diet, non-exercise activity, sleep and menstrual-cycle phase are needed before BMI-dependent adaptations to mat Pilates can be considered established. Full article

(This article belongs to the Special Issue The Role of Lifestyle, Physical Activity, and Exercise on Cardiometabolic Health and Diseases)

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29 pages, 21085 KB

Open AccessArticle

Metabolomic Signatures of Biotrauma Associated with Mortality in ICU Patients Requiring Invasive Mechanical Ventilation and ECMO

by Tiago A. H. Fonseca, Cristiana P. Von Rekowski, Rúben Araújo, Gonçalo C. Justino, M. Conceição Oliveira, Luís Bento and Cecília R. C. Calado

Metabolites 2026, 16(7), 516; https://doi.org/10.3390/metabo16070516 - 22 Jul 2026

Abstract

Background: Biotrauma from invasive mechanical ventilation (IMV) and extracorporeal membrane oxygenation (ECMO) drives systemic inflammation, metabolic dysregulation, and organ dysfunction in critically ill patients. Therefore, this study aimed to identify clinical and metabolomic features associated with ICU mortality in patients receiving IMV [...] Read more.

Background: Biotrauma from invasive mechanical ventilation (IMV) and extracorporeal membrane oxygenation (ECMO) drives systemic inflammation, metabolic dysregulation, and organ dysfunction in critically ill patients. Therefore, this study aimed to identify clinical and metabolomic features associated with ICU mortality in patients receiving IMV or ECMO, as these remain incompletely characterized. Methods: The retrospective analysis included 30 ICU patients on IMV and 22 on ECMO. Metabolomic and proteomic profiling were performed using ultra-high-performance liquid chromatography coupled with high-resolution mass spectrometry (UHPLC-HRMS), and serum spectral analysis by Fourier-transform infrared spectroscopy (FTIRS). Significant variables were incorporated into multivariate logistic regression models, ranked by AIC, AUC, and statistical significance. Model performance was evaluated using stratified 5-fold cross-validation. Final models were adjusted for relevant demographic and clinical covariates. Results: The IMV cohort showed discriminatory FTIRS wavenumbers across all preprocessings, and 155 metabolites plus 14 proteins were significantly altered, with unadjusted models achieving mean AUCs above 0.9. The ECMO cohort showed discriminatory FTIRS wavenumbers in one preprocessing, and 15 metabolites plus 3 proteins were highlighted. FTIRS, metabolomic, and proteomic models reached mean AUCs of 0.967, 0.867, and 0.783, respectively, with lower stability during cross-validation. Adjustment for demographic and clinical covariates reduced model robustness. Conclusions: Stronger and more reproducible molecular signatures related to ICU mortality were observed in the IMV cohort, whereas the ECMO cohort showed reduced model stability, likely reflecting increased biological heterogeneity and small sample size. These findings support the utility of integrated omics for characterizing critical illness and outcome stratification, while reinforcing the need for validation in larger and independent cohorts. Full article

(This article belongs to the Special Issue Metabolomics for Clinical Biomarkers Discovery)

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17 pages, 8317 KB

Open AccessArticle

Effects of Dietary Metabolizable Energy and Crude Protein on Postprandial Metabolite Dynamics and Lactation Performance in Dairy Goats

by Xiuqing Li, Lingbo Wang, Zhiyong Hu, Qiuling Hou, Yun Wang, Yizhao Shen, Yingyu Mu, Xueyan Lin and Zhonghua Wang

Metabolites 2026, 16(7), 515; https://doi.org/10.3390/metabo16070515 - 22 Jul 2026

Abstract

Background: Dietary metabolizable energy (ME) and crude protein (CP) levels are important for lactation performance and metabolic responses in dairy ruminants. This study aimed to evaluate the effects of dietary ME and CP levels on lactation performance and postprandial metabolic responses in lactating [...] Read more.

Background: Dietary metabolizable energy (ME) and crude protein (CP) levels are important for lactation performance and metabolic responses in dairy ruminants. This study aimed to evaluate the effects of dietary ME and CP levels on lactation performance and postprandial metabolic responses in lactating dairy goats. Methods: Goats were randomly assigned to a 4 × 4 two-factor Latin square experiment consisting of four 14 d periods. The dietary treatments were high energy, high protein (HEHCP); high energy, low protein (HELCP); low energy, high protein (LEHCP); and low energy, low protein (LELCP). Serial postprandial arterial blood samples were collected at 17 daytime time points to characterize temporal changes in plasma amino acids, biochemical parameters and hormones. Results: Increasing CP supply elevated milk yield (+6%) and lactose yield (+5%) but decreased milk fat yield (−8%; p ≤ 0.04). Increasing ME supply tended to enhance milk yield and milk fat yield and increased milk lactose content only under the high CP condition (ME × CP interaction: p = 0.04), suggesting that the response to ME supply depended partly on dietary CP level. High CP increased plasma branched chain amino acid concentrations, whereas high ME reduced Leu and Val under the high CP condition. Most plasma amino acids exhibited marked postprandial dynamics, decreasing initially and then stabilizing, with CP × time interactions observed for Leu, Met, and Phe (p ≤ 0.05). High ME decreased plasma AST activity and tended to reduce urea N concentration and also reduced ALT activity and increased glucose concentration under the high CP diet. Following morning feeding, plasma urea N showed a progressive postprandial decline (p = 0.02), with glucagon decreasing and both prolactin and growth hormone increasing, despite no dietary effects on mean plasma hormone concentrations. Conclusions: Overall, dietary ME and CP levels affected lactation performance and selected plasma metabolic indicators in lactating dairy goats. Coordinated energy and protein supply should be considered when formulating diets for lactating dairy goats. Serial postprandial sampling further revealed temporal changes in plasma metabolites and hormones, providing useful information for refining precision nutrition strategies during lactation. Full article

(This article belongs to the Special Issue Metabolic Responses to Feed and Nutrition in Livestock)

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28 pages, 5883 KB

Open AccessSystematic Review

Effects of High-Intensity Interval Training on Body Composition and Cardiometabolic Health in Physically Inactive Individuals: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

by Cunyu Lan, Beibei Lei, Juerui Li, Wenjie Huang, Kun Yang and Bo Gou

Metabolites 2026, 16(7), 514; https://doi.org/10.3390/metabo16070514 - 22 Jul 2026

Abstract

Background/Objectives: Increasing physical activity is important for reducing cardiometabolic risk. However, evidence on the effects of high-intensity interval training (HIIT) in physically inactive individuals, including those with extremely sedentary behavior, remains inconsistent. We evaluated the effects of HIIT on body composition and cardiometabolic [...] Read more.

Background/Objectives: Increasing physical activity is important for reducing cardiometabolic risk. However, evidence on the effects of high-intensity interval training (HIIT) in physically inactive individuals, including those with extremely sedentary behavior, remains inconsistent. We evaluated the effects of HIIT on body composition and cardiometabolic outcomes compared with a non-exercise control (CON) and moderate-intensity continuous training (MICT). Methods: PubMed, Web of Science, Embase, the Cochrane Library, Ovid-hosted resources, and ClinicalTrials.gov were searched through 8 July 2026. The protocol was registered (PROSPERO CRD420251230848). Random-effects models were used. Risk of bias, evidence certainty, and robustness were assessed using the Cochrane Risk of Bias 2 (RoB 2) tool, Grading of Recommendations Assessment, Development and Evaluation (GRADE), and leave-one-out analyses, respectively. Results: Twenty-four randomized trials involving 877 participants were analyzed. A conservative study-level summary classified all studies as having at least some concerns, including five at high risk of bias. Compared with CON, HIIT reduced body weight (weighted mean difference [WMD] = −1.60 kg), systolic blood pressure (WMD = −2.85 mmHg), diastolic blood pressure (WMD = −6.57 mmHg), low-density lipoprotein cholesterol (WMD = −0.29 mmol/L), and total cholesterol (WMD = −0.42 mmol/L), and increased maximal oxygen uptake (VO₂max; WMD = 7.72 mL/kg/min). Compared with MICT, most outcomes showed no statistically significant differences, but HIIT produced a greater VO₂max increase (WMD = 3.72 mL/kg/min). Several findings were sensitive to individual-study removal, and certainty of evidence was low or very low. No serious adverse events were reported in 11 studies; attendance or adherence was generally high in 15 studies, despite incomplete reporting and supervised interventions. Conclusions: HIIT may improve selected body composition and cardiometabolic outcomes, with VO₂max showing a relatively consistent direction of effect. However, the certainty of evidence for most outcomes was low or very low; therefore, these findings should be interpreted with caution. Current evidence is insufficient to establish equivalence to MICT or identify an optimal HIIT protocol. Larger, longer-term, high-quality trials using objective measures of sedentary behavior are needed, particularly in extremely sedentary populations. Full article

(This article belongs to the Special Issue Metabolic Adaptations to Exercise: Mechanisms, Modulators, and Health Impacts)

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15 pages, 1914 KB

Open AccessArticle

Untargeted Metabolomics Reveals Distinct Metabolic Signatures of Lactic Acid Bacteria in Food Fermentation and the Same Pipeline Applied to Foodborne Pathogen Detection

by Hao Li and Yuchen Tao

Metabolites 2026, 16(7), 513; https://doi.org/10.3390/metabo16070513 - 22 Jul 2026

Abstract

Background/Objectives: Lactic acid bacteria (LAB) are essential drivers of food fermentation, yet systematic metabolic comparisons across different LAB strains remain underexplored. This study characterized and contrasted the metabolic fingerprints of Lactiplantibacillus plantarum and Lacticaseibacillus rhamnosus in vegetable fermentation and subsequently evaluated whether [...] Read more.

Background/Objectives: Lactic acid bacteria (LAB) are essential drivers of food fermentation, yet systematic metabolic comparisons across different LAB strains remain underexplored. This study characterized and contrasted the metabolic fingerprints of Lactiplantibacillus plantarum and Lacticaseibacillus rhamnosus in vegetable fermentation and subsequently evaluated whether the same untargeted metabolomics pipeline could be applied to rapid foodborne pathogen detection. Methods: A multi-platform untargeted metabolomics strategy integrating GC-MS and UPLC-Q-TOF-MS was applied to profile four experimental conditions: non-fermented control, L. plantarum monoculture, L. rhamnosus monoculture, and mixed-culture fermentation. Multivariate statistical tools (PCA and PLS-DA) were used to identify differential metabolites and perturbed pathways. The identical analytical workflow was then applied to beef samples artificially contaminated with Escherichia coli O157:H7, Salmonella enterica, or Listeria monocytogenes. Results: Across all samples, 847 metabolites were annotated, of which 312 showed significant abundance changes upon fermentation. PLS-DA delivered robust group discrimination (R²X = 0.89, R²Y = 0.95, Q² = 0.91). Organic acids (32.0%) and amino acids (24.0%) dominated the metabolic landscape, with lactic acid, acetic acid, diacetyl, and acetoin as the most elevated compounds. KEGG analysis highlighted glycolysis/gluconeogenesis, pyruvate metabolism, and branched-chain amino acid degradation as the most heavily rewired pathways. When the same pipeline was applied to pathogen detection, it yielded AUC values of 0.89, 0.87, and 0.88 for E. coli O157:H7, S. enterica, and L. monocytogenes, respectively, with detection times of 18 h, 24 h, and 30 h. Conclusions: This work delivers a side-by-side metabolic atlas of two prominent LAB species and demonstrates the technical portability of an untargeted metabolomics pipeline from a fermentation model system to a pathogen detection scenario. The identified biomarker panels warrant further validation in diverse food matrices, and translation to routine monitoring will require matrix-specific model training and validation. Full article

(This article belongs to the Section Food Metabolomics)

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18 pages, 8417 KB

Open AccessArticle

Comprehensive Evaluation of Fruit Traits and Altitudinal Adaptability of 189 Wild Camellia oleifera Germplasms in East Guizhou, China

by Tanming Ye, Bingqian Wu and Chengjiang Ruan

Metabolites 2026, 16(7), 512; https://doi.org/10.3390/metabo16070512 - 22 Jul 2026

Abstract

Background: Eastern Tongren City, Guizhou Province, China, possesses abundant wild germplasm resources of Camellia oleifera Abel.; however, there is a lack of systematic evaluation, and the promotion of superior varieties is insufficient. This study aimed to evaluate 21 trait indices of 189 wild [...] Read more.

Background: Eastern Tongren City, Guizhou Province, China, possesses abundant wild germplasm resources of Camellia oleifera Abel.; however, there is a lack of systematic evaluation, and the promotion of superior varieties is insufficient. This study aimed to evaluate 21 trait indices of 189 wild C. oleifera accessions from four regions in the Tongren area to clarify their variation characteristics, assess the effects of altitude on trait expression, and identify candidate germplasms with outstanding comprehensive performance. Methods: A total of 21 traits spanning fruit morphology, oil content, fatty acid composition, and bioactive components (tocopherols, squalene, and polyphenols) were measured. Principal Component Analysis (PCA) was employed to construct a comprehensive evaluation score (Z_n) for quantitative ranking and screening. Trait differences between a low-altitude group (400–800 m, n = 139) and a high-altitude group (800–1200 m, n = 50) were compared using Welch’s t-test. Results: The germplasms exhibited abundant phenotypic variation, with coefficients of variation (CV) ranging from 5.29% (total unsaturated fatty acids) to 124.42% (beta + gamma-tocopherol). Bioactive components showed the highest variability, while fatty acid composition was relatively stable. Altitude had a significant effect on six of the 21 traits. Seed oil content and kernel oil content were significantly higher in the high-altitude group, with mean differences of 5.92 and 5.74 percentage points, respectively (both p < 0.001). However, oleic acid, total unsaturated fatty acids, fruit morphological traits, and most bioactive components showed no significant altitudinal differences (p > 0.05). The first five principal components explained 65.0% of the total variance. CL40 achieved the highest comprehensive score (Z_n = 4.15), followed by MJX2 (Z_n = 2.56). Among the top 10 individuals, eight were from the low-altitude group. Conclusions: This study revealed rich phenotypic variations and distinct altitudinal effects among wild C. oleifera germplasms in eastern Guizhou. The superior germplasms identified (such as CL40 and MJX2) can serve as candidate materials for locally adapted variety improvement. This study was primarily based on single-season phenotypic data, and the genetic stability of the selected germplasms should be validated through clonal trials and molecular marker analysis in future research. Full article

(This article belongs to the Section Plant Metabolism)

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