PubMed

Int J Mol Sci. 2025 May 7;26(9):4464. doi: 10.3390/ijms26094464.ABSTRACTMineral nutrition is of vital importance in plant growth and secondary metabolites accumulation, and thereby in the nutritional value of plants. In Lonicera japonica, a preference to nitrate (NO3--N) in comparison to ammonium (NH4+-N) was found in our previous study, which can be revealed from the rapid growth rate of L. japonica under NO3--N. This study assessed whether a preference for nitrogen sources could invoke metabolic reprogramming and interrelationships between factors. NO3--fed plants exhibited substantial enhancement of carbon stimulation, which was strongly and positively correlated with mesophyll conductance. As a result, the elevated carbon flux by NO3- supplement was shuttled to phenolic metabolites synthesis, including flavones and caffeoylquinic acids compounds. Notably, the stimulation was triggered by changes in the NO3- and C/N ratio and was mediated by the induction of several enzymes in the phenylpropanoid pathway. On the contrary, NH4+ plants showed an increment in the content of nitrogen, carbohydrates, and amino acids (mainly a strong increase in citrulline and theanine). Within secondary metabolism, NH4+ may involve active lignin metabolism, showing a dramatic increment in hydroxy-ferulic acid and lignin content. This work provides significant insights regarding the mechanisms of L. japonica in response to diverse nitrogen regimes and effective strategies of nitrogen fertilizer input for L. japonica.PMID:40362702 | DOI:10.3390/ijms26094464

Int J Mol Sci. 2025 May 7;26(9):4428. doi: 10.3390/ijms26094428.ABSTRACTSarcopenia, a condition characterised by the progressive decline in skeletal muscle mass and function, presents significant challenges in geriatric healthcare. Despite advances in its management, complex etiopathogenesis and the heterogeneity of diagnostic criteria underlie the limited precision of existing assessment methods. Therefore, efforts are needed to improve the knowledge and pave the way for more effective management and a more precise diagnosis. To this purpose, emerging technologies such as artificial intelligence (AI) can facilitate the identification of novel and accurate biomarkers by modelling complex data resulting from high-throughput technologies, fostering the setting up of a more precise approach. Based on such considerations, this review explores AI's transformative potential, illustrating studies that integrate AI, especially machine learning and deep learning, with heterogeneous data such as clinical, anthropometric and molecular data. Overall, the present review will highlight the relevance of large-scale, standardised studies to validate biomarker signatures using AI-driven approaches.PMID:40362666 | DOI:10.3390/ijms26094428

Int J Mol Sci. 2025 May 5;26(9):4389. doi: 10.3390/ijms26094389.ABSTRACTSenescence impacts plant growth and yields in tetraploid potatoes (Solanum tuberosum L.). Because of their homogenous tetraploid features, it is a major challenge to understand the genetic basis and molecular mechanisms of senescence. Here, we identified a novel central senescence regulator (Nicotinate-nucleotide pyrophosphorylase QPT/StNADC) through map-based cloning. Overexpression of StNADCZ3 accelerated senescence in the late-senescence variety, with NAD content declining by around 40%. CRISPR/Cas9-induced StNADC mutant cr2-11 exhibited extremely early senescence, and the NAD content was reduced by 87% along with reduced chlorophyll content and photosynthesis. Moreover, the downstream products of the NAD synthesis pathway, such as NaMN, NAD, or niacin, can refresh the cr2-11 mutant to grow normally. Further, the transcriptomics and metabolomics data unveiled that the disrupting of StNADC impairs NAD metabolism, accelerating plant senescence through multiple biological levels. Our results show that StNADC is indispensable for NAD synthesis, and targeting the StNADC-mediated NAD synthesis pathway could be a useful strategy to regulate senescence in potato breeding preprograms.PMID:40362626 | DOI:10.3390/ijms26094389

Int J Mol Sci. 2025 May 5;26(9):4377. doi: 10.3390/ijms26094377.ABSTRACTThis study reports on the whole genome sequencing of the hazelnut endophytic Fusarium isolate Hzn5 from Poland. It was identified as a member of the Fusarium citricola species complex based on a phylogenetic analysis which also pointed out that other hazelnut isolates, previously identified as F. lateritium and F. tricinctum, actually belong to this species complex. Genome annotation allowed the mapping of 4491 different protein sequences to the genome assembly. A further in silico search for their potential biosynthetic activity showed that predicted genes are involved in 1110 metabolic pathways. Moreover, the analysis of the genome sequence carried out in comparison to another isolate, previously identified as an agent of hazelnut gray necrosis in Italy, revealed a homology to several regions containing biosynthetic gene clusters for bioactive secondary metabolites. The resulting indications for the biosynthetic aptitude concerning some emerging mycotoxins, such as the enniatins and culmorin, should be taken into consideration with reference to the possible contamination of hazelnuts and derived products.PMID:40362614 | DOI:10.3390/ijms26094377

Int J Mol Sci. 2025 May 2;26(9):4339. doi: 10.3390/ijms26094339.ABSTRACTGlioblastoma (GBM) is a fatal brain cancer known for its rapid and aggressive growth, with some studies indicating that females may have better survival outcomes compared to males. While sex differences in GBM have been observed, the underlying biological mechanisms remain poorly understood. Feature selection can lead to the identification of discriminative key biomarkers by reducing dimensionality from high-dimensional medical datasets to improve machine learning model performance, explainability, and interpretability. Feature selection can uncover unique sex-specific biomarkers, determinants, and molecular profiles in patients with GBM. We analyzed high-dimensional proteomic and metabolomic profiles from serum biospecimens obtained from 109 patients with pathology-proven glioblastoma (GBM) on NIH IRB-approved protocols with full clinical annotation (local dataset). Serum proteomic analysis was performed using Somalogic aptamer-based technology (measuring 7289 proteins) and serum metabolome analysis using the University of Florida's SECIM (Southeast Center for Integrated Metabolomics) platform (measuring 6015 metabolites). Machine learning-based feature selection was employed to identify proteins and metabolites associated with male and female labels in high-dimensional datasets. Results were compared to publicly available proteomic and metabolomic datasets (CPTAC and TCGA) using the same methodology and TCGA data previously structured for glioma grading. Employing a machine learning-based and hybrid feature selection approach, utilizing both LASSO and mRMR, in conjunction with a rank-based weighting method (i.e., GLIO-Select), we linked proteomic and metabolomic data to clinical data for the purposes of feature reduction to identify molecular biomarkers associated with biological sex in patients with GBM and used a separate TCGA set to explore possible linkages between biological sex and mutations associated with tumor grading. Serum proteomic and metabolomic data identified several hundred features that were associated with the male/female class label in the GBM datasets. Using the local serum-based dataset of 109 patients, 17 features (100% ACC) and 16 features (92% ACC) were identified for the proteomic and metabolomic datasets, respectively. Using the CPTAC tissue-based dataset (8828 proteomic and 59 metabolomic features), 5 features (99% ACC) and 13 features (80% ACC) were identified for the proteomic and metabolomic datasets, respectively. The proteomic data serum or tissue (CPTAC) achieved the highest accuracy rates (100% and 99%, respectively), followed by serum metabolome and tissue metabolome. The local serum data yielded several clinically known features (PSA, PZP, HCG, and FSH) which were distinct from CPTAC tissue data (RPS4Y1 and DDX3Y), both providing methodological validation, with PZP and defensins (DEFA3 and DEFB4A) representing shared proteomic features between serum and tissue. Metabolomic features shared between serum and tissue were homocysteine and pantothenic acid. Several signals emerged that are known to be associated with glioma or GBM but not previously known to be associated with biological sex, requiring further research, as well as several novel signals that were previously not linked to either biological sex or glioma. EGFR, FAT4, and BCOR were the three features associated with 64% ACC using the TCGA glioma grading set. GLIO-Select shows remarkable results in reducing feature dimensionality when different types of datasets (e.g., serum and tissue-based) were used for our analyses. The proposed approach successfully reduced relevant features to less than twenty biomarkers for each GBM dataset. Serum biospecimens appear to be highly effective for identifying biologically relevant sex differences in GBM. These findings suggest that serum-based noninvasive biospecimen-based analyses may provide more accurate and clinically detailed insights into sex as a biological variable (SABV) as compared to other biospecimens, with several signals linking sex differences and glioma pathology via immune response, amino acid metabolism, and cancer hallmark signals requiring further research. Our results underscore the importance of biospecimen choice and feature selection in enhancing the interpretation of omics data for understanding sex-based differences in GBM. This discovery holds significant potential for enhancing personalized treatment plans and patient outcomes.PMID:40362575 | DOI:10.3390/ijms26094339

Int J Mol Sci. 2025 May 1;26(9):4305. doi: 10.3390/ijms26094305.ABSTRACTPhytochemical investigation and bioactivity evaluation of terpenoids from the Croton species were conducted. The chemical composition of C. sylvaticus was explored using chemical phytochemical screening techniques and dereplication of 13C NMR data using MixONat software (v. 1.0.1). Natural products with diverse structural features were identified in the dichloromethane extract of trunk bark. These include monoterpenoids, sesquiterpenoids, diterpenoids, triterpenoids, along with other minor metabolites, such as steroids, saponins, and fatty acids. Further purification of this extract led to the isolation of three major secondary metabolites, acetyl aleuritolic acid, caryophyllene oxide, and phytol. These secondary metabolites were reported for the first time in C. sylvaticus. The isolated compounds were structurally compared to known anticancer terpenoids previously identified in two other Congolese Croton species. Through molecular docking studies, the predicted binding affinities of the identified compounds were assessed, and possible structure-activity relationships (SAR) were proposed. Two structurally characterized receptors-the human androgen receptor (HAR, PDB ID: 1E3G) and hypoxia-inducible factor 1-alpha (HIF-1α, PDB ID: 3KCX), known for their involvement in cancer-related pathways, were used for molecular docking investigations. Among the tested compounds, 1, 2, 3, and 12 were identified as having strong-to-moderate predicted binding affinities to both protein targets, along with favorable drug-like properties according to the ADMET analysis. This investigation could justify the use of Croton plants in traditional medicine. In addition, our study highlights the potential of the Congolese Croton species as sources of bioactive secondary metabolites.PMID:40362546 | DOI:10.3390/ijms26094305

Int J Mol Sci. 2025 Apr 30;26(9):4257. doi: 10.3390/ijms26094257.ABSTRACTMetabolomics is a commonly used method to study the responses of organisms to environmental changes. However, the relationships between metabolites and biological endpoints still need further discussion. In this study, we exposed wheat seeds to sulfamethoxazole (0, 1, 10, 100 mg/L) for 5 days. The results show that sulfamethoxazole (SMX) had an inhibitory effect on wheat growth. It reduced shoot length, root length, shoot fresh weight, root fresh weight, chlorophyll content, and carotenoid content. At the same time, it increased the concentration of reactive oxygen species, the activity of superoxide dismutase, the activity of peroxidase, and the activity of catalase in the root. An orthogonal partial least squares analysis and correlation analysis were performed. SMX transformed five key metabolic pathways. Notably, certain metabolic alterations exhibited negative correlations with reactive oxygen species (ROS) accumulation and antioxidant enzyme activities (including superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT)), while showing positive associations with root growth parameters (fresh weight and length). Conversely, other metabolic changes appeared to promote ROS generation and enhance antioxidant enzyme activities, consequently inhibiting root growth. These findings offer novel perspectives on the metabolic regulation of wheat's stress response to SMX exposure.PMID:40362497 | DOI:10.3390/ijms26094257

Int J Mol Sci. 2025 Apr 29;26(9):4231. doi: 10.3390/ijms26094231.ABSTRACTGrafting is a prevalent horticultural technique that enhances crop yields and stress resilience; nevertheless, compatibility issues frequently constrain its efficacy. This research examined the physiological, hormonal, and transcriptional factors regulating compatibility between the litchi (Litchi chinensis Sonn.) cultivars Feizixiao (FZX) and Ziniangxi (ZNX). The anatomical and growth investigations demonstrated significant disparities between compatible (FZX as scion and ZNX as rootstock) and incompatible (ZNX as scion and FZX as rootstock) grafts, with the latter showing reduced levels of indole acetic acid (IAA). Exogenous 1-naphthalene acetic acid (NAA) application markedly improved the graft survival, shoot development, and hormonal synergy, whereas the auxin inhibitor tri-iodobenzoic acid (TIBA) diminished these parameters. The incompatible grafts showed downregulation of auxin transporter genes, including ATP-binding cassette (ABC) transporter, AUXIN1/LIKE AUX1 (AUX/LAX), and PIN-FORMED (PIN) genes, suggesting impaired vascular tissue growth. Metabolomic profiling revealed dynamic interactions between auxin, salicylic acid, and jasmonic acid, with NAA-treated grafts exhibiting enhanced levels of stress-responsive metabolites. Transcriptome sequencing identified differentially expressed genes (DEGs) linked to auxin signaling (ARF, GH3), seven additional phytohormones, secondary metabolism (terpenoids, anthocyanins, and phenylpropanoids), and ABC transporters. Gene ontology and KEGG analyses highlighted the significance of hormone interactions and the biosynthesis of secondary metabolites in successful grafting. qRT-PCR validation substantiated the veracity of the transcriptome data, emphasizing the significance of auxin transport and signaling in effective graft development. This study provides an in-depth review of the molecular and physiological factors influencing litchi grafting. These findings provide critical insights for enhancing graft success rates in agricultural operations via targeted hormonal and genetic approaches.PMID:40362471 | DOI:10.3390/ijms26094231

Int J Mol Sci. 2025 Apr 29;26(9):4227. doi: 10.3390/ijms26094227.ABSTRACTThere is an escalating need to comprehend the long-term impacts of nuclear radiation exposure since the permeation of ionizing radiation has been frequent in our current societal framework. A system evaluation of the microbes that reside inside a host's colon could meet this knowledge gap since the microbes play major roles in a host's response to stress. Indeed, our past study suggested that these microbes might break their symbiotic association with moribund hosts to form a pro-survival condition exclusive to themselves. In this study, we undertook metagenomics and metabolomics assays regarding the descending colon content (DCC) of adult mice. DCCs were collected 1 month and 6 months after 7 Gy or 7.5 Gy total body irradiation (TBI). The assessment of the metagenomic diversity profile in DCC found a significant sex bias caused by TBI. Six months after 7.5 Gy TBI, decreased Bacteroidetes were replaced by increased Firmicutes in males, and these alterations were reflected in the functional analysis. For instance, a larger number of networks linked to small chain fatty acid (SCFA) synthesis and metabolism were inhibited in males than in females. Additionally, bioenergy networks showed regression dynamics in females at 6 months post-TBI. Increased accumulation of glucose and pyruvate, which are typical precursors of beneficial SCFAs coupled with the activated networks linked to the production of reactive oxygen species, suggest a cross-sex energy-deprived state. Overall, there was a major chronic adverse implication in male mice that supported the previous literature in suggesting females are more radioresistant than males. The sex-biased chronic effects of TBI should be taken into consideration in designing the pertinent therapeutics.PMID:40362462 | DOI:10.3390/ijms26094227

Int J Mol Sci. 2025 Apr 27;26(9):4164. doi: 10.3390/ijms26094164.ABSTRACTPrecision medicine stems from a new approach to the prevention, diagnosis and treatment of patients, due to the shift in focus away from pathology and towards the uniqueness of the individual, personalising the diagnostic-therapeutic pathway. This paradigm shift has been made possible by the emergence of new high-throughput technologies capable of generating large amounts of data on multiple levels of a biological system, identifying pathology-related genes, transcripts, proteins and metabolites. Metabolomics plays a primary role in this context, providing, through non-invasive sampling, a very close image of the phenotype of the organism being studied by detecting metabolites, end products downstream of gene transcription, present in cells, tissues, organs and biological fluids. The enormous amount of data that these modern technologies make available, together with the need to elucidate the complex interplay of the various biological levels by combining data from distinct omics, has led to the need to employ advanced informatics techniques, among which artificial intelligence has recently emerged. These innovations are of great interest in the field of perinatology, representing an attempt to optimise the diagnostic timeline for the most critical newborns. In addition, they may contribute to the improvement of prevention strategies available to date. All these contributions prove to be crucial at very vulnerable life stages, allowing crucial intervention opportunities. In this review, we have analysed studies that have integrated metabolomics with at least one other omics in the perinatal field, attempting to highlight the usefulness of multiomics integration and the different methods employed.PMID:40362403 | DOI:10.3390/ijms26094164

Int J Mol Sci. 2025 Apr 27;26(9):4156. doi: 10.3390/ijms26094156.ABSTRACTInsects are among the most diverse and abundant organisms on Earth, and their population dynamics are strongly influenced by entomopathogenic fungi. This study examines the role of carbon and nitrogen metabolism in the virulence of the entomopathogenic fungus Metarhizium rileyi against the migratory locust, Locusta migratoria. The findings demonstrate that the capacity of M. rileyi to utilize different carbon and nitrogen sources is a key factor in its virulence. Specifically, two strains of M. rileyi (PPDB201006 and SZCY201010) exhibited distinct metabolic abilities, with PPDB201006 displaying superior growth and enzyme activities on various carbon and nitrogen sources compared to SZCY201010. These metabolic differences were associated with significant variations in virulence, as PPDB201006 induced higher mortality rates in L. migratoria than SZCY201010. Metabolomics analysis revealed that infection by M. rileyi led to substantial alterations in the hemolymph metabolites of L. migratoria, particularly in organic acids, amino acids, sugars, and lipids. These results emphasize the significance of carbon and nitrogen metabolism in the pathogenicity of entomopathogenic fungi and offer new perspectives for optimizing their application as biological control agents. This study not only improves our understanding of fungal virulence mechanisms but also contributes to the development of more effective and sustainable pest management strategies.PMID:40362396 | DOI:10.3390/ijms26094156

Int J Mol Sci. 2025 Apr 27;26(9):4152. doi: 10.3390/ijms26094152.ABSTRACTInsulin overdose may cause hypoglycemic encephalopathy. In this study, Mendelian randomization was employed to analyze changes in the serum metabolites of patients with hypoglycemic encephalopathy, and metabolomics analysis was conducted to detect differential metabolites in the serum of a rat model of hypoglycemic encephalopathy induced by insulin overdose. The results indicated an overall upward trend in the tryptophan metabolism pathway in patients with hypoglycemic encephalopathy and rats with hypoglycemic encephalopathy caused by insulin overdose, while serum glutamate levels declined. The metabolic changes in the tryptophan pathway provide new insights into the impact of hypoglycemia on brain function. The related products of the tryptophan metabolism pathway have a certain diagnostic value for hypoglycemic encephalopathy and forensic identification of insulin overdose-induced hypoglycemic encephalopathy death.PMID:40362391 | DOI:10.3390/ijms26094152

Int J Mol Sci. 2025 Apr 27;26(9):4151. doi: 10.3390/ijms26094151.ABSTRACTThe success of assisted reproductive technology is contingent upon the growth potential of embryos post-vitrification process. When compared to in vivo embryos, it has been found that the high intracellular lipid accumulation inside the in vitro-derived embryos results in poor survival during vitrification. Based on this finding, the present study assessed the impact of incorporating forskolin and linoleic acid (FL) entering in vitro culture (IVC) on the embryos' cryo-survival, lipid content, and viability throughout vitrification. Lipid metabolomics and single-cell RNA sequencing (scRNA-seq) techniques were used to determine the underlying mechanism that the therapies were mimicking. It was observed that out of 726 identified lipids, 26 were expressed differentially between the control and FL groups, with 12 lipids upregulated and 14 lipids downregulated. These lipids were classified as Triacylglycerol (TG), Diacylglycerol (DG), Phosphatidylcholine (PC), and so on. A total of 1079 DEGs were detected between the FL and control groups, consisting of 644 upregulated genes and 435 downregulated genes. These DEGs were significantly enhanced in the arachidonic acid metabolism, lipolysis, fatty acid metabolism, cAMP signaling pathway, and other critical developmental pathways. Based on the observation, it was concluded that forskolin and linoleic acid decreased the droplet content of embryos by modulating lipid metabolism, thus enhancing the vitrified bovine embryos' cryo-survival.PMID:40362390 | DOI:10.3390/ijms26094151

Int J Mol Sci. 2025 Apr 23;26(9):3995. doi: 10.3390/ijms26093995.ABSTRACTDuring the breeding process of Macrobrachium rosenbergii, a male-to-female ratio of 1:3 or higher is typically adopted, so as a result, the quality of the male broodstock significantly influences the quality of the offspring. We observed that overused males exhibited notable changes in body color, particularly in the tail fan region, which turned orange or red due to the excessive accumulation of astaxanthin in the muscles and exoskeleton. Frequent mating also led to a significant decrease in male body weight, with histological analysis revealing disorganized muscle fiber patterns and increased tissue damage. To investigate the molecular mechanisms underlying these physiological changes, we performed transcriptomic and metabolomic analyses of muscle tissues. A total of 1069 differentially expressed genes (DEGs), 540 differentially expressed proteins (DEPs), and 385 differentially expressed metabolites (DEMs) were identified. Pathway analysis revealed that the DEGs were significantly enriched in pathways related to energy metabolism and degenerative diseases, while the DEMs were notably associated with cancer metabolism, signal transduction, substance transport, energy metabolism, nucleic acid metabolism, neurotransmission, immune response, and metabolic diseases. Proteome analysis showed that proteins and lipids were involved in muscle energy supply. These findings suggest that male M. rosenbergii upregulate energy metabolism in muscles to cope with frequent mating stress, but this adaptation leads to physiological damage. This study provides valuable insights for optimizing male broodstock selection and mating frequency in M. rosenbergii breeding practices.PMID:40362236 | DOI:10.3390/ijms26093995

Int J Mol Sci. 2025 Apr 23;26(9):3973. doi: 10.3390/ijms26093973.ABSTRACTA well-regulated metabolism is crucial for optimal oocyte development and embryonic health. However, the metabolic framework governing oocyte maturation remains poorly understood. Using bovine oocytes as a model, we examined metabolomic and transcriptomic alterations during the transition from the germinal vesicle (GV) to the metaphase II (MII) stage. Our findings reveal distinct metabolic shifts, including suppressed β-oxidation combined with the accumulation of long-chain fatty acids (LCFAs). Notably, progesterone emerged as a key regulator of meiotic resumption through its influence on cAMP levels. We also observed enhanced glycolysis, moderate activation of the citric acid cycle (TCA cycle), and suppression of oxidative phosphorylation (OXPHOS), alongside reduced urea cycle flux and shifts in amino acid metabolism favoring glutamate synthesis. Intriguingly, discrepancies between metabolic and transcriptional activities in pathways such as the TCA cycle and nucleotide metabolism suggest asynchronous regulation. These findings provide a comprehensive multi-omics resource, advancing our understanding of the dynamic metabolic and transcriptional landscape during bovine oocyte maturation.PMID:40362214 | DOI:10.3390/ijms26093973

Int J Mol Sci. 2025 Apr 22;26(9):3935. doi: 10.3390/ijms26093935.ABSTRACTType 1 diabetes (T1D) is an autoimmune condition characterized by the destruction of insulin-producing pancreatic beta cells, leading to lifelong insulin dependence and significant complications. Early detection of T1D is essential to delay disease onset and improve outcomes. Recent advancements in artificial intelligence (AI) and machine learning (ML) have provided powerful tools for predicting and diagnosing T1D. This systematic review evaluates the current landscape of AI/ML-based approaches for early T1D detection. A comprehensive search across PubMed, EMBASE, Science Direct, and Scopus identified 1447 studies, of which 10 met the inclusion criteria for narrative synthesis after screening and full-text review. The studies utilized diverse ML models, including logistic regression, support vector machines, random forests, and artificial neural networks. The datasets encompassed clinical parameters, genetic risk markers, continuous glucose monitoring (CGM) data, and proteomic and metabolomic biomarkers. The included studies involved a total of 49,172 participants and employed case-control, retrospective cohort, and prospective cohort designs. Models integrating multimodal data achieved the highest predictive accuracy, with area under the curve (AUC) values reaching up to 0.993 in sex-specific models. CGM data and plasma biomarkers, such as CXCL10 and IL-1RA, also emerged as valuable tools for identifying at-risk individuals. While the results highlight the potential of AI/ML in revolutionizing T1D risk stratification and diagnosis, challenges remain. Data heterogeneity and limited model generalizability present barriers to widespread implementation. Future research should prioritize the development of universal frameworks and real-world validation to enhance the reliability and clinical integration of these tools. Ultimately, AI/ML technologies hold transformative potential for clinical practice by enabling earlier diagnosis, guiding targeted interventions, and improving long-term patient outcomes. These advancements could support clinicians in making more informed, timely decisions, thus reducing diagnostic delays and paving the way for personalized prevention strategies in both pediatric and adult populations.PMID:40362176 | DOI:10.3390/ijms26093935

Animals (Basel). 2025 May 7;15(9):1350. doi: 10.3390/ani15091350.ABSTRACTThe traditional horse industry has undergone a remarkable evolution, with horse racing emerging as a prominent and pivotal economic driver within the sector. Among the various breeds, Mongolian horses, renowned for their exceptional endurance and speed, occupy a significant position in the horse industry. To investigate their homeostasis mechanisms during and after a 20 km endurance exercise and identify novel oxidative-imbalance markers, we selected 12 two-year-old horses and collected blood samples at various time points before, during (at 5, 10, 15, and 20 km), and after the exercise (at 1, 2, 4, and 6 h post-exercise). These samples were analyzed for haematology, blood biochemistry, antioxidant enzyme activities, and liquid chromatography-mass spectrometry (LC-MS) metabolomics. Our results revealed significant changes in heart rate, speed, blood cells, and biochemical markers throughout the exercise. Antioxidant indicators decreased, while malondialdehyde increased, indicating oxidative imbalance post-exercise. Metabolomics analysis identified 122 differential metabolites, including uric acid and L-tyrosine, which were enriched in pathways related to energy metabolism. Uric acid and tyrosine correlated positively with serum creatine kinase, suggesting their potential as markers of oxidative-imbalance injury. These findings elucidate the mechanisms of endurance adaptability in Mongolian horses and provide a theoretical basis for mitigating oxidative imbalance, enhancing horse performance, and promoting the sustainable development of the equine industry.PMID:40362165 | DOI:10.3390/ani15091350

Environ Int. 2025 May 2;199:109503. doi: 10.1016/j.envint.2025.109503. Online ahead of print.ABSTRACTSuccinate dehydrogenase inhibitors (SDHi) are fungicides used worldwide to control the proliferation of fungi in crops. They act by blocking the activity of succinate dehydrogenase (SDH), a universal enzyme involved in mitochondrial functions and metabolism. While SDH-encoding genes are tumour suppressors, which loss-of-function mutations predispose to different types of rare tumors in humans, the consequences of chemical inactivation of SDH by SDHi remain largely unknown, particularly regarding their carcinogenic potential. Here, we investigated the metabolic and cellular impact of SDHi on human non-cancer and transformed colon cells. We show that SDHi inhibit SDH activity and increase the level of succinate, known to act as an oncometabolite in SDH-deficient cancers. SDHi exposure also induces a Warburg-like metabolic reprogramming typical of cancer cells, associated with transcriptomic and morphological changes promoting cell migration and invasion. These effects are enhanced in transformed colon cells carrying mutations in colorectal cancer (CRC) driver genes. These findings provide the first evidence that SDHi-mediated chemical inactivation of SDH mimics some metabolic and phenotypic features previously described in human tumors with SDH genetic deficiencies. Given that loss of SDH expression in CRC patients correlates with a poor prognosis, these patients could represent a population sensitive to SDHi exposure. Therefore, it would be wise to include them in biomonitoring programs. Finally, our work highlights the need to improve regulatory assessment procedures to take better account of SDHi mode of action, by developing relevant tests to cover the multiple key events linked to SDH inactivation and assess the resulting mitochondrial toxicity.PMID:40359599 | DOI:10.1016/j.envint.2025.109503

PLoS One. 2025 May 13;20(5):e0321896. doi: 10.1371/journal.pone.0321896. eCollection 2025.ABSTRACTThe Dothideomycete pathogen Coniothyrium glycines causes red leaf blotch of soybean, a major disease in Africa. It is one of two fungal plant pathogens on the USDA PPQ Select Agents and Toxins list of pathogens important to the biosecurity of the United States, reflective of its potential to be highly destructive if introduced. Despite its importance, there are no published reports regarding the molecular basis of host infection. Examination of the C. glycines genome revealed a secondary metabolite gene cluster that is similar in gene content and organization to clusters that synthesize light-activated perylenequinone toxins, such as cercosporin. Perylenequinones are non-host specific toxins that, upon exposure to light, generate reactive oxygen species, which have near-universal toxicity to plant hosts. Coniothyrium glycines isolates from eastern and southern Africa were cultured axenically under light and dark conditions. Light-grown cultures produced red-pink pigmentation typical of perylenequinones. Differential gene expression analysis showed that six of the eight genes in the biosynthetic gene cluster, including the polyketide synthase gene, were significantly upregulated in light. Liquid chromatography-mass spectrometry confirmed production of the perylenequinone elsinochrome A, a known virulence factor in other fungal pathogens. On leaves incubated in the dark, significantly fewer lesions formed and symptoms were delayed, compared to leaves incubated in the light. In addition, we identified orthologous gene clusters in more distantly related Dothideomycete plant pathogens where their presence was previously unknown, indicating a broader importance of these toxins to agriculture and fungal ecology. This work provides the first evidence that elsinochrome A may contribute to the virulence of C. glycines.PMID:40359450 | DOI:10.1371/journal.pone.0321896

J Agric Food Chem. 2025 May 13. doi: 10.1021/acs.jafc.5c02588. Online ahead of print.ABSTRACTHuangjiu is a traditional Chinese fermented alcoholic beverage made from glutinous rice. The quality and flavor profile of Huangjiu are intricately linked to the intrinsic properties of the rice used. While research on rice for Huangjiu emphasizes macronutrients such as starch and protein, little is known about the characteristics of small molecular metabolites. Here, we characterized the macromolecular profiles of three glutinous rice varieties suitable for Huangjiu brewing, and matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) was applied to map the distribution and relative abundance of small molecular metabolites within the rice grains, providing insights for the development of specialized rice varieties for brewing.PMID:40359257 | DOI:10.1021/acs.jafc.5c02588