PubMed

Plant Physiol Biochem. 2025 Feb 24;222:109702. doi: 10.1016/j.plaphy.2025.109702. Online ahead of print.ABSTRACTBACKGROUND: Saffron (Crocus sativus L.) cultivation faces increasing challenges from climate change and declining yields. Optimal corm development occurs at 15/6 °C day/night temperatures. However, climate change is forcing cultivation under higher temperature regimes.This study investigated the effects of Trichoderma harzianum Bi, nano-TiO2, and magnetic field treatments on saffron cormlet production under high-temperature greenhouse conditions (25/15 °C day/night, exceeding optimal temperatures by 10 °C), representing increasingly common stress conditions in traditional growing regions. While controlled environment production offers potential solutions, the combined effects of biological and physical treatments for mitigating high-temperature stress remain unexplored.METHODS: A factorial experiment examined T. harzianum Bi-enriched medium (0, 100% v/v), nano-TiO2 (0, 250, 500 μl l-1), and magnetic field exposure (0, 60 militesla, 30-min constant exposure) effects on uniform-sized saffron corms (13 ± 0.5 g) grown in cocopeat-perlite medium (3:1 v/v). Analysis included cormlet production parameters and comprehensive metabolic profiling of key compounds including carbohydrates, amino acids, and organic acids.RESULTS: Combined T. harzianum and 250 μl l-1 nano-TiO2 treatment significantly enhanced cormlet production, increasing individual cormlet weight by 68.9% (from 9.0 ± 0.2 to 15.2 ± 0.3 g/cormlet, p < 0.05) and improving key metabolites: starch (37.6% increase to 255.2 ± 20.4 mg g-1 FW), GABA (159.6% increase to 1.35 ± 0.11 μmol g-1 FW), and myoinositol (111.1% increase to 0.95 ± 0.08 mg g-1 FW). Magnetic field exposure increased cormlet numbers but reduced individual weights by 20%. Metabolomic analysis revealed coordinated enhancement of carbohydrate metabolism and stress-response pathways.CONCLUSION: For commercial production, we recommend applying combined T. harzianum (100% v/v medium enrichment) with 250 μl l-1 nano-TiO2 treatment under controlled greenhouse conditions (25/15 °C Day/night). This protocol consistently produces larger, more vigorous cormlets with enhanced metabolic profiles, though magnetic field applications require further optimization. These findings provide immediate practical strategies for addressing cultivation challenges under increasing temperature stress conditions, particularly relevant for commercial greenhouse production systems.PMID:40020606 | DOI:10.1016/j.plaphy.2025.109702

Plant Physiol Biochem. 2025 Feb 21;222:109674. doi: 10.1016/j.plaphy.2025.109674. Online ahead of print.ABSTRACTThe accumulation of flavonoids facilitates plant resistance to biotic stress. However, few studies have explored the functions of flavonoids during the interaction between wheat and Puccinia striiformis Westendorp f. sp. tritici Eriksson (Pst). This study analyzed the expression profiles of flavonoids and their biosynthesis genes in the resistant accession Y0337 and the susceptible accession Y0402 infected with Pst. The results showed that flavonoid biosynthesis pathway (FBP) genes were induced during early Pst infection. Among these, 29 initial FBP DEGs exhibited higher expression during incompatible interaction. Further, the total levels of 12 identified flavonoids were higher during incompatible interaction; among these, apigenin, luteolin, cynaroside were accumulated and naringenin was decreased, they may play a crucial role in Pst resistance. Integrated analysis of the transcriptome and metabolome showed that 21 DEGs regulated four crucial flavonoids biosynthesis. The gene regulatory network suggested that the transcription factors EFRs, WRKYs, NACs, and bHLHs potentially regulated four flavonoids biosynthesis. Additionally, it was shown that luteolin inhibited spore germination and infection of Pstin vivo and in vitro. In summary, these results enhance our understanding of the flavonoids biosynthesis in wheat resistance to Pst and highlight the role of luteolin in this process.PMID:40020601 | DOI:10.1016/j.plaphy.2025.109674

Plant Physiol Biochem. 2025 Feb 20;222:109656. doi: 10.1016/j.plaphy.2025.109656. Online ahead of print.ABSTRACTBroussonetia papyrifera is an important source of unconventional feed. However, freezing injuries in winter are a considerable threat to the popularization and application of B. papyrifera. Notably, the use of anthocyanins is a promising approach for enhancing plant stress resistance. However, B. papyrifera contains low levels of anthocyanins, and the anthocyanin synthesis process in this plant remains unclear. In this study, the one-month-old cuttings of B. papyrifera were grown at low (4 °C) and average (25 °C) temperatures. After 3 weeks, petioles and veins from different growth environments were harvested for transcriptome and anthocyanin-targeted metabolome analyses. The targeted metabolome analysis revealed that following cold treatment, the levels of cyanidin-3-O-galactoside, cyanidin-3-O-rutinoside, cyanidin-3-O-(6-O-p-coumaroyl)-glucoside and cyanidin chloride increased by 756.22, 306.87, 222.28, and 776.67 times, respectively. Transcriptome analysis revealed 17 pivotal anthocyanin-related differentially expressing genes (DEGs), among which chalcone synthase 2 (BpCHS2) was significantly upregulated at low temperatures. The combined transcriptome and metabolome disclosed an apparent positive correlation between BpCHS2 and cyanidin derivatives (R2 ≥ 0.99). Transgenic experiments demonstrated that overexpression of BpCHS2 in tobacco markedly increased the expression of anthocyanin-related genes, promoted anthocyanin accumulation, and enhanced the activities of peroxidase, superoxide dismutase, and catalase. These results suggest that the expression of BpCHS2 is markedly increased in B. papyrifera under low-temperature stress, improving anthocyanin accumulation and cold tolerance.PMID:40020598 | DOI:10.1016/j.plaphy.2025.109656

Microbiol Res. 2025 Feb 26;295:128111. doi: 10.1016/j.micres.2025.128111. Online ahead of print.ABSTRACTRice direct-seeding technology is regarded as a promising alternative to traditional transplanting due to its labor- and water-saving benefits. However, poor seedling emergence and growth under low-temperature stress remain major obstacles to its widespread adoption in Heilongjiang Province, China. Here, we isolated an endophytic fungus Stagonosporopsis ajaci NEAU-BLH1 from the cold-resistant plant Adonis amurensis, which effectively enhanced rice seed germination and seedling growth under low-temperature stress. Two years of pot and field experiments demonstrated that soaking rice seeds in a spore suspension of NEAU-BLH1 significantly increased tillering, resulting in a 16.0-47.8 % improvement in yield for direct-seeded rice. Mechanistic investigations revealed that NEAU-BLH1 treatment elevated gibberellin levels and reduced abscisic acid, accelerating starch hydrolysis into soluble sugars, thus improving germination under low temperature. Comprehensive physiological, transcriptomic, and metabolomic analyses indicated that NEAU-BLH1 enhances seedling growth by boosting respiratory metabolism, mitigating oxidative damage, and modulating hormone pathways. These findings indicate that seed-soaking with NEAU-BLH1 has good potential to enhance seed germination under low-temperature stress and increases grain yield in direct-seeded rice.PMID:40020546 | DOI:10.1016/j.micres.2025.128111

Poult Sci. 2025 Feb 21;104(4):104941. doi: 10.1016/j.psj.2025.104941. Online ahead of print.ABSTRACTAs the age of laying increases, the metabolic capacity of the liver decreases, leading to excessive lipid accumulation, which seriously affects the laying performance of laying hens. Induced molting (IM) can rejuvenate the reproductive system of older laying hens, allowing them to enter a new laying cycle. However, it remains unclear whether induced molting can enhance lipid accumulation in the liver of aged laying hens and what the underlying mechanism might be. In this study, fasting-induced molting was performed on 70-week-old Hy-line brown laying hens, and the resulting metabolic changes were analyzed using non-targeted metabolomics. Serum lipid levels, liver oxidative stress, and inflammation were measured using kits, while autophagy and lipid metabolism-related factors were assessed through immunofluorescence and western blotting. The results showed that IM could promote hepatic lipid deposition in aged laying hens, reduce hepatic steatosis and injury, lower the blood lipid level, improve hepatic antioxidant capacity and increase egg production rate. During the fasting period, the hepatic autophagic system was activated in laying hens and the level of hepatic autophagy increased. Additionally, AMPK phosphorylation levels increased, while the expression of fatty acid synthesis genes SREBP-1C, ACC, and FASN decreased (P < 0.01). The expression of PPARα, PGC 1α and CPT1A, which are associated with fatty acid oxidation, was upregulated (P < 0.01). In conclusion, IM enhanced lipid metabolism, increased liver autophagy, and improved liver function in aged laying hens.PMID:40020412 | DOI:10.1016/j.psj.2025.104941

Ecotoxicol Environ Saf. 2025 Feb 27;292:117916. doi: 10.1016/j.ecoenv.2025.117916. Online ahead of print.ABSTRACTExcessive use of pesticides has raised great concern on food safety as well as crop quality in the form of pesticide residues. Plants have natural defense mechanisms against pesticides for its alleviation. This study investigated distribution of tolfenpyrad as well as physiological, metabolomic, transcriptomic and hormonal responses of tea plants to tolfenpyrad application. Results show that tolfenpyrad tends to accumulate in tea leaves, with limited translocation to stems and roots after foliar application. While no significant change in plant biomass or growth status was apparent following tolfenpyrad application, it triggered reactive oxygen species (ROS) and antioxidant system impacts. Metabolomic and transcriptomic analyses reveal disrupted purine metabolism and nitrogen metabolism, mainly in amino acid pathways, with a glutathione (GSH) detoxification response. Hormonal and targeted metabolic profiling confirms a significant elevation in melatonin biosynthesis, then exogenous application of melatonin is proved to efficiently reduce pesticide residue in tea plants. This study improved our understanding of the tea plants' defense mechanism to pesticide, and suggested an emerging plant-derived regulator for improving quality and safety of tea products.PMID:40020380 | DOI:10.1016/j.ecoenv.2025.117916

Water Res. 2025 Feb 18;277:123323. doi: 10.1016/j.watres.2025.123323. Online ahead of print.ABSTRACTSWATH-MS offers a robust data-independent acquisition method for complex proteomics and metabolomics. This study presents a detailed non-target screening workflow utilizing SWATH-MS to detect and analyze emerging contaminants (ECs) in aquatic environments. Our workflow, covering peak picking, alignment, prioritization, structure identification, and quantification, effectively identified all qualifying peaks from 298 standard compounds with different concentrations, discarding any that did not meet the criteria. In extracts of real water samples spiked at 100 and 10 ng/mL, our workflow prioritized 2083 and 1328 features, respectively. Following structure identification, these features were assigned confidence levels ranging from 1 to 5. Of these, 215 and 92 spiked standards achieved level 1. The remaining standards were not recognized as level 1 due to low intensities or poor peak shapes that failed to meet certain criteria. Additionally, using fragment ion peak areas for quantification significantly improved the linearity of standard curves, enhancing R2 values for ∼63 % of the standards. Incorporating fragment ion data improved quantification accuracy, increasing compounds within the 80 %-120 % range from 78 % to 90 % at 100 ng/mL and within the 50 %-150 % range from 36 % to 69 % at 10 ng/mL. These findings underscore SWATH-MS's potential to enhance monitoring of ECs and ecological risk assessments, providing critical insights for environmental management.PMID:40020354 | DOI:10.1016/j.watres.2025.123323

J Pharm Biomed Anal. 2025 Feb 20;259:116759. doi: 10.1016/j.jpba.2025.116759. Online ahead of print.ABSTRACTCisplatin (DDP) is widely used to fight lung cancer, but there is a risk of immune damage. Astragalus polysaccharides (APS) is the main active component of Astragalus membranaceus Bunge. It has demonstrated anticancer properties across a range of cancer types as well as to be effective against cisplatin induced immune damage. However, its therapeutic mechanism has not been fully explored. This study aimed to explore the antitumor mechanisms of APS and elucidate the relationship between APS and volatile organic compounds (VOCs) in exhaled breath of Lewis lung cancer (LLC) mice. Gas chromatography-mass spectrometry (GC-MS) was utilized to analyze the exhaled VOCs in LLC mice. A specific group of VOCs was identified as potential biomarkers for monitoring tumor progression. Furthermore, the effects of combined treatment with APS and DDP on the concentration of exhaled VOCs in LLC mice was evaluated. Stoichiometric analysis revealed that the levels of 12 VOCs exhibited substantial recovery following APS treatment. And a high concentration of APS (400 mg/kg), when combined with DDP, exhibited enhanced antitumor efficacy. The metabolic pathways involved in the action of APS include 12 pathways. Our methodology elucidated both the effects and mechanisms of APS on lung cancer, as well as the pharmacological enhancement of cisplatin by APS. These findings facilitate real-time monitoring of lung cancer treatments and contribute to the future development of anticancer therapies.PMID:40020348 | DOI:10.1016/j.jpba.2025.116759

Comp Biochem Physiol Part D Genomics Proteomics. 2025 Feb 19;55:101448. doi: 10.1016/j.cbd.2025.101448. Online ahead of print.ABSTRACTUnderstanding metabolic adaptations to seasonal fluctuations in ectothermic organisms is challenging, especially in tropical species where physiological responses are more pronounced than in temperate or polar counterparts. Traditional analytical methods often fail to account for the complex metabolic adjustments that are present in these substantial responses, and the high-dimensional characteristics of metabolomic data complicate the interpretation process when using conventional statistical methods. We utilized Non-negative Matrix Factorization (NMF), an unsupervised machine learning algorithm, to analyze monthly serum metabolomics data from tilapia over a year in order to overcome these limits. A deeper analysis using NMF demonstrated that carbohydrates gained prominence during warmer months, as evidenced by consistently elevated weights of glycolysis intermediates in our quantitative analysis. Furthermore, fatty acids remained an important factor in both warm and cold seasons. Amino acids emerged as particularly versatile metabolites, exhibiting adaptability during seasonal transitions. This flexibility suggests their crucial role in coordinating energy-related adaptations and potentially facilitating epigenetic and reproductive responses to changing environments. Serum aspartate composition during the warm-cold transition indicated sex-specific metabolic strategies, as sexual dimorphism was observed in the seasonal utilization of fatty acids and aspartate. Collectively, NMF objectively assesses the metabolic tactics of tropical fish and reveals latent patterns in real-world metabolic dynamics. Consequently, it possesses the potential to facilitate metabolomics-driven species conservation in response to environmental changes.PMID:40020271 | DOI:10.1016/j.cbd.2025.101448

Medicine (Baltimore). 2025 Feb 28;104(9):e41651. doi: 10.1097/MD.0000000000041651.ABSTRACTHypertension continues to pose a huge burden to global public health. Abnormal metabolism not only serves as a risk factor for hypertension but also acts as a driving force in its aggravation. However, there remains a lack of large-scale causal demonstration based on extensive samples. Our study aims to investigate the causal relationship between metabolism and primary hypertension (PH) using Mendelian randomization analysis. We used genome-wide association studies instrumental variables for Mendelian randomization association analysis integrating the diagnosis results of PH in 3 populations from East Asia, the Middle East, and Africa with serum metabolites and metabolite ratios. This allowed us to identify predictive metabolites and metabolic pathways for diagnosing or treating PH. Inverse-variance weighting was the main model for establishing causal associations. In addition horizontal pleiotropy test, linkage disequilibrium test, and sensitivity analysis were employed to test the explanatory power of instrumental variables. A total of 10,922 cases of PH and 8299 cases of metabolomics detection cohorts were included in the study. In East Asian, Middle Eastern, and African populations, we found 36, 57, and 40 known metabolites respectively strongly associated with PH (P < .05). Cross-section and meta-analysis of these strongly correlated metabolites across the 3 ethnic groups revealed 7 common metabolites. Notably, elevated isoleucine (odds ratio = 0.74, 95% confidence interval: 0.56-0.96) was demonstrated as a potential protective factor against PH across 3 ethnic groups. The metabolites associated with PH have certain polymorphisms in different populations. Isoleucine may be a promising biomarker for PH diagnosis or treatment, but more clinical validation is needed.PMID:40020104 | DOI:10.1097/MD.0000000000041651

Curr Med Sci. 2025 Feb 28. doi: 10.1007/s11596-025-00023-5. Online ahead of print.ABSTRACTOBJECTIVE: This study aims to investigate the exosome-derived metabolomics profiles in systemic lupus erythematosus (SLE), identify differential metabolites, and analyze their potential as diagnostic markers for SLE and lupus nephritis (LN).METHODS: Totally, 91 participants were enrolled between February 2023 and January 2024 including 58 SLE patients [30 with nonrenal-SLE and 28 with Lupus nephritis (LN)] and 33 healthy controls (HC). Ultracentrifugation was used to isolate serum exosomes, which were analyzed for their metabolic profiles using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Endogenous metabolites were identified via public metabolite databases. Random Forest, Lasso regression and Support Vector Machine Recursive Feature Elimination (SVM-RFE) algorithms were employed to screen key metabolites, and a prediction model was constructed for SLE diagnosis and LN discrimination. ROC curves were constructed to determine the potential of these differential exosome-derived metabolites for the diagnosis of SLE. Furthermore, Spearman's correlation was employed to evaluate the potential links between exosome-derived metabolites and the clinical parameters which reflect disease progression.RESULTS: A total of 586 endogenous serum exosome-derived metabolites showed differential expression, with 225 exosome-derived metabolites significantly upregulated, 88 downregulated and 273 exhibiting no notable changes in the HC and SLE groups. Machine learning algorithms revealed three differential metabolites: Pro-Asn-Gln-Met-Ser, C24:1 sphingolipid, and protoporphyrin IX, which exhibited AUC values of 0.998, 0.992 and 0.969 respectively, for distinguishing between the SLE and HC groups, with a combined AUC of 1.0. In distinguishing between the LN and SLE groups, the AUC values for these metabolites were 0.920, 0.893 and 0.865, respectively, with a combined AUC of 0.931, demonstrating excellent diagnostic performance. Spearman correlation analysis revealed that Pro-Asn-Gln-Met-Ser and protoporphyrin IX were positively correlated with the SLE Disease Activity Index (SLEDAI) scores, urinary protein/creatinine ratio (ACR) and urinary protein levels, while C24:1 sphingolipid exhibited a negative correlation.CONCLUSIONS: This study provides the first comprehensive characterization of the exosome-derived metabolites in SLE and established a promising prediction model for SLE and LN discrimination. The correlation between exosome-derived metabolites and key clinical parameters strongly indicated their potential role in SLE pathological progression.PMID:40019633 | DOI:10.1007/s11596-025-00023-5

Eur J Nucl Med Mol Imaging. 2025 Feb 28. doi: 10.1007/s00259-025-07157-7. Online ahead of print.ABSTRACTBACKGROUND: Cardiac amyloidosis (CA) is a severe condition characterized by amyloid fibril deposition in the myocardium, leading to restrictive cardiomyopathy and heart failure. Differentiating between amyloidosis subtypes is crucial due to distinct treatment strategies. The individual conventional diagnostic methods lack the accuracy needed for effective subtype identification. This study aimed to evaluate the efficacy of combining 11C-PiB PET/CT and 99mTc-DPD scintigraphy in detecting CA and distinguishing between its main subtypes, light chain (AL) and transthyretin (ATTR) amyloidosis while assessing the association of imaging findings with patient prognosis.METHODS: We retrospectively evaluated the diagnostic efficacy of combining 11C-PiB PET/CT and 99mTc-DPD scintigraphy in a cohort of 50 patients with clinical suspicion of CA. Semi-quantitative imaging markers were extracted from the images. Diagnostic performance was calculated against biopsy results or genetic testing. Both machine learning models and a rationale-based model were developed to detect CA and classify subtypes. Survival prediction over five years was assessed using a random survival forest model. Prognostic value was assessed using Kaplan-Meier estimators and Cox proportional hazards models.RESULTS: The combined imaging approach significantly improved diagnostic accuracy, with 11C-PiB PET and 99mTc-DPD scintigraphy showing complementary strengths in detecting AL and ATTR, respectively. The machine learning model achieved an AUC of 0.94 (95% CI 0.93-0.95) for CA subtype differentiation, while the rationale-based model demonstrated strong diagnostic ability with AUCs of 0.95 (95% CI 0.88-1.00) for ATTR and 0.88 (95% CI 0.770-0.961) for AL. Survival prediction models identified key prognostic markers, with significant stratification of overall mortality based on predicted survival (p value = 0.006; adj HR 2.43 [95% CI 1.03-5.71]).CONCLUSION: The integration of 11C-PiB PET/CT and 99mTc-DPD scintigraphy, supported by both machine learning and rationale-based models, enhances the diagnostic accuracy and prognostic assessment of cardiac amyloidosis, with significant implications for clinical practice.PMID:40019577 | DOI:10.1007/s00259-025-07157-7

Funct Integr Genomics. 2025 Feb 28;25(1):46. doi: 10.1007/s10142-025-01549-6.ABSTRACTSaussurea costus (Falc.) is an endangered medicinal plant possessing diverse phytochemical compounds with clinical significance and used to treat numerous human ailments. Despite the source of enriched phytochemicals, molecular insights into spatialized metabolism are poorly understood in S. costus. This study investigated the dynamics of organ-specific secondary metabolite biosynthesis using deep transcriptome sequencing and high-throughput UHPLC-QTOF based untargeted metabolomic profiling. A de novo assembly from quality reads fetched 59,725 transcripts with structural (53.02%) and functional (66.13%) annotations of non-redundant transcripts. Of the 7,683 predicted gene families, 3,211 were categorized as 'single gene families'. Interestingly, out of the 4,664 core gene families within the Asterids, 4,560 families were captured in S. costus. Organ-specific differential gene expression analysis revealed significant variations between leaves vs. stems (23,102 transcripts), leaves vs. roots (30,590 transcripts), and roots vs. stems (21,759 transcripts). Like-wise, putative metabolites (PMs) were recorded with significant differences in leaves vs. roots (250 PMs), leaves vs. stem (350 PMs), and roots vs. stem (107 PMs). The integrative transcriptomic and metabolomic analysis identified organ-specific differences in the accumulation of important metabolites, including secologanin, menthofuran, taraxerol, lupeol, acetyleugenol, scopoletin, costunolide, and dehydrocostus lactone. Furthermore, a global gene co-expression network (GCN) identified putative regulators controlling the expression of key target genes of secondary metabolite pathways including terpenoid, phenylpropanoid, and flavonoid. The comprehensive functionally relevant genomic resource created here provides beneficial insights for upscaling targeted metabolite biosynthesis through genetic engineering, and for expediting association mapping efforts to elucidate the casual genetic elements controlling specific bioactive metabolites.PMID:40019562 | DOI:10.1007/s10142-025-01549-6

J Gastroenterol. 2025 Feb 28. doi: 10.1007/s00535-025-02226-y. Online ahead of print.ABSTRACTBACKGROUND: Hepatocellular carcinoma (HCC), the most common form of liver cancer, presents a challenging malignancy with scarce treatment options. Liver progenitor cells (LPCs) play a pivotal role in both liver regeneration and the progression of liver cancer, yet the specific functions of LPCs from different origins in liver cancer remain to be fully elucidated.METHODS: We explored the liver progenitor-like cells derived from human hepatocytes (HepLPCs) on the proliferation of HCC both in vitro and in vivo. The mitochondrial function was assessed through electron microscopy and functional experiments. Transcriptomic sequencing and western blot unveiled the fundamental mechanisms at play, whereas metabolomic sequencing pinpointed crucial effector molecules involved in the paracrine secretion of HepLPCs.RESULTS: By employing a co-culture system of HepLPCs and HCC cells, we found that HepLPCs markedly inhibited HCC growth by prompting mitochondrial dysfunction, which further led to the co-inhibition of the Notch1 and JAK1/STAT3 signaling pathways through paracrine actions involving S-adenosylmethionine (SAM) and Nicotinic acid (NA).CONCLUSIONS: This study has uncovered that HepLPCs have a suppressive influence on the proliferation of HCC cells. This is achieved through the impairment of mitochondrial function and the inhibition of key signaling pathways, namely, Notch1 and JAK1/STAT3, which are critical drivers of cancer progression. The secretion of the metabolites SAM and NA by HepLPCs appears to be instrumental in mediating these effects. These findings provide a solid foundation for identifying new therapeutic targets and clarifying the mechanisms through which HepLPCs can be harnessed to effectively treat HCC.PMID:40019515 | DOI:10.1007/s00535-025-02226-y

Ther Deliv. 2025 Feb 28:1-15. doi: 10.1080/20415990.2025.2470614. Online ahead of print.ABSTRACTAIMS: This study aimed to evaluate the potential of Eryngium maritimum L. (EM) callus media filtrate (ECMF) for enhanced skin delivery through multilayered liposomes (MLs).MATERIALS & METHODS: ECMF was applied to human skin cells to assess its antioxidant, anti-inflammatory, and skin barrier-enhancing properties. ECMF was encapsulated in MLs to enhance delivery efficiency, creating a formulation called Cellbiome. Clinical trials involving human participants were conducted to compare its effects with traditional formulations, assessing parameters such as skin density, hydration, elasticity, and wrinkle reduction.RESULTS: Cellbiome significantly improved skin density and moisturization, outperforming conventional formulations. ML encapsulation facilitated deeper penetration of active ingredients beyond the stratum corneum, leading to synchronized improvements in multiple skin parameters, including elasticity, wrinkle reduction, and overall skin health. Transcriptomic and metabolomic analyses further confirmed ECMF's bioactivity and its role in skin improvement.CONCLUSIONS: ML-based formulations, such as Cellbiome, offer superior efficacy in skincare applications compared to conventional methods. This study underscores the importance of advanced delivery technologies in cosmetics and highlights the need for further research to optimize the benefits of natural extracts like EM for human skin, potentially advancing dermatological and cosmeceutical applications.PMID:40019355 | DOI:10.1080/20415990.2025.2470614

Anal Chem. 2025 Feb 28. doi: 10.1021/acs.analchem.4c06375. Online ahead of print.ABSTRACTAccurate identification and quantification of fatty acids are critical for investigating their biological function in disease models. Although several derivatization methods have been proposed for identifying the positions of C═C bonds in unsaturated fatty acids, poor ionization efficiency of the carboxyl group leads to lower intensity of molecular ion peaks, making their identification difficult and interfering with the accuracy of quantification based on peak areas of characteristic ion pairs. In this study, a strategy of stable isotope-labeled carboxyl derivatization combined with C═C derivatization was employed for simultaneously the identification and quantification of fatty acids using d0/d9-5-amino-N,N,N-trimethylpentane-1-ammonium iodide (d0/d9-ATPAI) to label the carboxyl group and m-chloroperoxybenzoic acid to label C═C bonds. The stable isotope-labeled quaternary amine groups in the novel carboxyl derivatization reagent d0/d9-ATPAI can enhance the accuracy of the recognition of characteristic ion pairs to facilitate the structural elucidation of various fatty acids. The heavy isotope-labeled fatty acids can be served as internal standards to achieve accurate relative quantification of the C═C position isomers of individual unsaturated fatty acids among samples based on the peak area ratio of the characteristic ion pairs. Unsaturated fatty acid C═C positional isomers were quantified using aldehyde or alkenyl diagnostic ions. In addition, saturated fatty acids were quantified using the m/z 86.09679 cyclamine characteristic ion. This approach enhanced the detection sensitivity of fatty acids by 60,000 times, allowing for the characterization of 70 fatty acids in rat serum, including 26 unsaturated fatty acid C═C positional isomers. Pseudotargeted metabolomics analysis of serum fatty acids revealed alterations in the fatty acid metabolic pathway during diabetic cognitive dysfunction. Overall, the proposed method, with high sensitivity and wide coverage, could provide accurate identification and relative quantification of various fatty acids in complex matrices.PMID:40019293 | DOI:10.1021/acs.analchem.4c06375

Asian J Androl. 2025 Feb 28. doi: 10.4103/aja2024110. Online ahead of print.ABSTRACTIn contrast to the conventional spermiogram, metabolomics approaches give insights into the molecular composition of semen and may provide more detailed information on the fertility status of the respective donor. Given the intra-individual variability of spermiogram parameters between two donations, this study sought to elucidate the biological variability of the seminal plasma metabolome over an average period of 8 weeks. Two time-shifted semen samples from 15 healthy donors were compared by a targeted metabolomics approach utilizing the Biocrates AbsoluteIDQ p180 kit. Next to intraclass correlation coefficients (ICC), which represent a measure of reliability, coefficients of variation within individuals (CVW) and coefficients of variation between individuals (CVB) were calculated for each metabolite to demonstrate its stability. Furthermore, men were divided into two cohorts, a similar sperm concentration (SSC) and a differing sperm concentration (DSC) cohort, based on the observed variance in sperm concentration between the two semen donations. The ICC was higher in the SSC compared to the DSC cohort. The levels of 18 metabolites, primarily acylcarnitines, varied between the initial and subsequent donations. After subdivision into subgroups, only ornithine and phosphatidylcholine 40:5 exhibited differential levels between the two donations in the SSC group, compared to 14 metabolites in the DSC group. CVB was higher than CVW but both differed between the metabolite subclasses. Biogenic amines were identified as the least reliable analytes over time, exhibiting the highest CVW, compared to sphingomyelins, which demonstrated the highest reliability with the lowest variation. CVB was the highest for ether-bound glycerophosphatidylcholines and the lowest for amino acids.PMID:40019275 | DOI:10.4103/aja2024110

Appl Environ Microbiol. 2025 Feb 28:e0018025. doi: 10.1128/aem.00180-25. Online ahead of print.ABSTRACTSince cheese is one of the most commonly and globally consumed fermented foods, scientific investigations in recent decades have focused on determining the impact of this dairy product on human health and well-being. However, the modulatory effect exerted by the autochthonous cheese microbial community on the taxonomic composition and associated functional potential of the gut microbiota of human is still far from being fully dissected or understood. Here, through the use of an in vitro human gut-simulating cultivation model in combination with multi-omics approaches, we have shown that minor rather than dominant bacterial players of the cheese microbiota are responsible for gut microbiota modulation of cheese consumers. These include taxa from the genera Enterococcus, Bacillus, Clostridium, and Hafnia. Indeed, they contribute to expand the functional potential of the intestinal microbial ecosystem by introducing genes responsible for the production of metabolites with relevant biological activity, including genes involved in the synthesis of vitamins, short-chain fatty acids, and amino acids. Furthermore, tracing of cheese microbiota-associated bacterial strains in fecal samples from cheese consumers provided evidence of horizontal transmission events, enabling the detection of particular bacterial strains transferred from cheese to humans. Moreover, transcriptomic and metabolomic analyses of a horizontally transmitted (cheese-to-consumer) bacterial strain, i.e., Hafnia paralvei T10, cultivated in a human gut environment-simulating medium, confirmed the concept that cheese-derived bacteria may expand the functional arsenal of the consumer's gut microbiota. This highlights the functional and biologically relevant contributions of food microbes acquired through cheese consumption on the human health.IMPORTANCEDiet is universally recognized as the primary factor influencing and modulating the human intestinal microbiota both taxonomically and functionally. In this context, cheese, being a fermented food with its own microbiota, serves not only as a source of nourishment for humans, but also as a source of nutrients for the consumer's gut microbiota. Additionally, it may act as a vehicle for autochthonous food-associated microorganisms which undergo transfer from cheese to the consumer, potentially influencing host gut health. The current study highlights not only that cheese microbiota-associated bacteria can be traced in the human gut microbiota, but also that they may expand the functional repertoire of the human gut microbiota, with potentially significant implications for human health.PMID:40019271 | DOI:10.1128/aem.00180-25

Endocr Connect. 2025 Feb 1:EC-24-0681. doi: 10.1530/EC-24-0681. Online ahead of print.ABSTRACTOBJECTIVE: Women with gestational diabetes mellitus (GDM) often develop a metabolic memory that increases the risk of future metabolic disorders, even after blood glucose levels normalize following clinical intervention. However, the impact of this metabolic memory on susceptibility to SARS-CoV-2 remains unclear. Therefore, we aim to investigate the potential association between metabolic memory in GDM and susceptibility to SARS-CoV-2 infection.METHODS: We conducted a prospective cohort study with 1,675 pregnant women, including 197 (11.8%) with GDM. Postpartum SARS-CoV-2 infections were tracked via telephone follow-up and categorized into negative and positive groups. Logistic regression was used to explore risk factors for SARS-CoV-2 infection. Peripheral blood samples were collected from 30 GDM and 30 normal glucose-tolerant (NGT) pregnant women in three trimesters (T1, T2, T3) for longitudinal untargeted metabolomics to identify GDM and SARS-CoV-2-associated metabolites. Limma package was applied to find differential metabolites (DEMs) associated with SARS-CoV-2 infection and GDM.RESULTS: Among 1,675 women, 1,348 (80.5%) tested positive for SARS-CoV-2. GDM post-partum women had higher SARS-CoV-2 infection rates (88.3% vs. 79.4%, P = 0.003) than NGT women. GDM was associated with SARS-CoV-2 infection (T2: OR [95% CI]: 2.17 [1.26-3.54], P = 0.005; T3: OR [95% CI]: 1.70 [1.03-2.82], P = 0.040). Compared to the SARS-CoV-2 negative group, the positive group exhibited elevated levels of allantoic acid, LPE (0:0/22:6), LPC (15:0/0:0), 1-linoleoyl-sn-glycero-3-phosphorylcholine in T1 and T2, before clinical intervention. In T3, allantoic acid remained elevated post-intervention. A similar increase as described above was observed in the GDM compared to the NGT group.CONCLUSION: Compared to NGT, women with GDM are at a higher risk of postnatal SARS-CoV-2 infection. Metabolic memory from GDM may heighten susceptibility to SARS-CoV-2.PMID:40019194 | DOI:10.1530/EC-24-0681

J Agric Food Chem. 2025 Feb 28. doi: 10.1021/acs.jafc.4c04734. Online ahead of print.ABSTRACTThe amount of nitrogen (N) fertilization influences the content and composition of phytochemicals in plants. However, the influence of different chemical forms of N fertilizers on the phytochemical profiles of fruits remains less known. We investigated the effect of nitrate [NO3-; supplied as CaNO3], ammoniacal [NH4+; supplied as (NH4)2SO4], and organic-N (supplied as meat and bone meal [MBM]) fertilization on the profile of volatile compounds, primary, and secondary metabolites in the fruits of Alpine strawberries (Fragaria vesca "Reine des Vallées") using global metabolomic approaches. The form of plant-available soil N varied as a function of fertilization, with (NH4)2SO4 and MBM fertilization retaining a higher proportion of N as ammoniacal-N throughout the growing period. Leaf nitrate reductase activity was 5 times higher in CaNO3 treatments, suggesting NO3- as the major N form taken up by plants in this treatment. Although ammoniacal-N fertilization resulted in lower plant biomass, the fruit yield and tissue nutrient content were similar to those of nitrate-N treatments. The plant biomass of organic-N treatment was similar to that of nitrate-N fertilization, but the fruit yield was 30% lower. Compared to nitrate-N treatment, aroma-related volatile compounds increased under organic- and ammoniacal-N fertilization, including up to a 5-fold increase in esters, a 6-fold increase in alcohols, a 3-fold increase in volatile fatty acids, and a 60% increase in organic acids. The content of primary metabolites, especially sugar, sugar alcohol, and amino acids, exhibited an opposite trend and increased in nitrate-N than under ammoniacal- and organic-N fertilization. Compared to nitrate-N, the secondary metabolites generally were higher under ammoniacal- and organic-N fertilization, with an 80% increase in the activity of phenylalanine ammonia lyase, resulting in up to 38% increase in flavones, 28% increase in flavanols, and 33% increase in anthocyanins, except for dihydroflavonols and proanthocyanidins, which decreased by 6 and 13%, respectively. The hydrolyzable tannins, including galloyl glucosides, ellagitannins, and ellagic acids, were 25% abundant under organic-N fertilization. Our results indicate that while nitrate-N generally increased the primary metabolites, organic-N and ammoniacal-N fertilization enhanced the aroma-related volatiles and secondary metabolites in strawberry fruits. Thus, precise management of the chemical form of N fertilization can be a valuable tool to improve the phytonutrient content of strawberries.PMID:40019181 | DOI:10.1021/acs.jafc.4c04734