PubMed

Cardiovasc Diabetol. 2025 Apr 2;24(1):152. doi: 10.1186/s12933-025-02701-z.ABSTRACTBACKGROUND: Disruption of lipid metabolism contributes to increased cardiovascular risk in diabetes.METHODS: We evaluated the associations between serum lipidomic profile and subclinical carotid atherosclerosis (SCA) in type 1 (T1D) and type 2 (T2D) diabetes, and in subjects without diabetes (controls) in a cross-sectional study. All subjects underwent a lipidomic analysis using ultra-high performance liquid chromatography-electrospray ionization tandem mass spectrometry, carotid ultrasound (mode B) to assess SCA, and clinical assessment. Multiple linear regression models were used to assess the association between features and the presence and burden of SCA in subjects with T1D, T2D, and controls separately. Additionally, multiple linear regression models with interaction terms were employed to determine features significantly associated with SCA within risk groups, including smoking habit, hypertension, dyslipidaemia, antiplatelet use and sex. Depending on the population under study, different confounding factors were considered and adjusted for, including sample origin, sex, age, hypertension, dyslipidaemia, body mass index, waist circumference, glycated haemoglobin, glucose levels, smoking habit, diabetes duration, antiplatelet use, and alanine aminotransferase levels.RESULTS: A total of 513 subjects (151 T1D, 155 T2D, and 207 non-diabetic control) were included, in whom the percentage with SCA was 48.3%, 49.7%, and 46.9%, respectively. A total of 27 unique lipid species were associated with SCA in subjects with T2D, in former/current smokers with T2D, and in individuals with T2D without dyslipidaemia. Phosphatidylcholines and diacylglycerols were the main SCA-associated lipidic classes. Ten different species of phosphatidylcholines were up-regulated, while 4 phosphatidylcholines containing polyunsaturated fatty acids were down-regulated. One diacylglycerol was down-regulated, while the other 3 were positively associated with SCA in individuals with T2D without dyslipidaemia. We discovered several features significantly associated with SCA in individuals with T1D, but only one sterol could be partially annotated.CONCLUSIONS: We revealed a significant disruption of lipid metabolism associated with SCA in subjects with T2D, and a larger SCA-associated disruption in former/current smokers with T2D and individuals with T2D who do not undergo lipid-lowering treatment.PMID:40176064 | DOI:10.1186/s12933-025-02701-z

Cardiovasc Diabetol. 2025 Apr 2;24(1):153. doi: 10.1186/s12933-025-02711-x.ABSTRACTBACKGROUND: Cardiovascular diseases (CVD) remain the leading cause of morbidity and mortality globally. Traditional risk models, primarily based on established risk factors, often lack the precision needed to accurately predict new-onset major adverse cardiovascular events (MACE). This study aimed to improve prediction and risk stratification by integrating traditional risk factors with biochemical and metabolomic biomarkers.METHODS: We analyzed data from 229,352 participants in the UK Biobank (median age 58.0 years; 45.4% male) who were free of baseline MACE. Biomarker selection was conducted using area under the curve (AUC), minimal joint mutual information maximization (JMIM), and correlation analyses, while Cox proportional hazards models were employed to evaluate the predictive performance of combined traditional risk factors and biomarkers. Optimal binary thresholds were determined utilizing CatBoost and SHAP, leading to the calculation of a Biomarker Risk Score (BRS) for each participant. Multivariable Cox models were conducted to assess the associations of each concerned biomarker and BRS with new-onset endpoints.RESULTS: The combination of PANEL + All Biochemistry + Cor0.95 of Nonov Met predictors demonstrated significantly improved discriminative performance compared to traditional models, such as Age + Sex and ASCVD, across all endpoints. Although the prediction for hemorrhagic stroke was suboptimal (C-index = 0.699), C-index values for other outcomes surpassed 0.75, with the highest value (0.822) recorded for CVD-related mortality. Key predictors of new-onset MACE included cystatin C, HbA1c, GlycA, and GGT, while IGF-1 and DHA exhibited potential protective effects. The BRS stratified individuals into low-, intermediate-, and high-risk groups, with the strongest effect observed for CVD death, where the high-risk group had a relative risk of 2.76 (95% CI 2.48-3.07) compared to the low-risk group.CONCLUSION: Integrating traditional risk factors and biomarkers improves prediction and risk stratification of new-onset MACE. The BRS shows promise as a tool for identifying high-risk individuals, with the potential to support personalized CVD prevention and management strategies.PMID:40176039 | DOI:10.1186/s12933-025-02711-x

BMC Microbiol. 2025 Apr 2;25(1):189. doi: 10.1186/s12866-025-03922-8.ABSTRACTBACKGROUND: In vitro studies have demonstrated the modulation of vaginal microbiota (VM) by cervical peptides which levels varied with the status of HPV infection and cervical intraepithelial neoplasia (CIN) grades. However, there is a deficiency in population-based studies investigating the modulation of VM compositions and metabolome by cervical differentially expressed genes (DEGs) across different grades of CIN.METHODS: This study included 43 HPV-positive women, classified into low-grade (CIN1, n = 23) and high-grade (CIN2 + , n = 20) groups. Vaginal swabs were collected for both microbiota and metabolome analysis. Cervical exfoliated cells were collected for RNA-Seq analysis.RESULTS: We identified 258 differentially expressed genes (DEGs), among which 176 CIN1-enriched genes were linked to immune responses, cell chemotaxis, negative regulation of cell migration, and B cell differentiation, activation, and proliferation. Eighty-two genes upregulated in CIN2 + cohorts were associated with epidermis development and keratinization. Then, we identified 5,686 paired correlations between DEGs, VM, and metabolome, with 2,320 involving Lactobacillus. Further analysis revealed Lactobacillus as the primary determinant of metabolic profiles, followed by Gardnerella, Faecalibacterium, Aerococcus and Streptococcus, such as the notable positive correlation between Lactobacillus with D-lactic acid and DL-indole-3-lactic acid. Applying mediation analysis, we found that Lactobacillus mediated the association of 14 CIN1-enriched DEGs, such as COL4A2, CCBE1 and SPON1, with the production of 57 metabolites, including D-lactic acid, oleic acid and various amino acids. Additional analysis indicated significant mediation effects of 79 metabolites on the association of DEGs with the growth of Lactobacillus, Gardnerella, Fannyhessea and Aerococcus.CONCLUSIONS: Our findings provide valuable population-based evidence for the inferred modulation of correlated VM and metabolome by cervical DEGs across different CIN stages.PMID:40175912 | DOI:10.1186/s12866-025-03922-8

BMC Genomics. 2025 Apr 2;26(1):333. doi: 10.1186/s12864-025-11483-3.ABSTRACTElaeagnus mollis Diels, is a rare and endangered woody plant endemic to China, which is listed on the IUCN Red List. In the natural state, the viability of its seeds declines very rapidly, which is the key to its endangered status, but the mechanism of E. mollis seed viability decline is still unclear. In order to explore the physiological and molecular mechanism of viability decline of E. mollis seeds, this study used fresh seeds as a control to compare and analyze the changes of seed vitality, antioxidant system, transcription and metabolomics, when seeds were stored for 1 and 3 months at room temperature. The viability of E. mollis seed decreased continuously after 1 month and 3 months of storage. The activities of superoxide dismutase (SOD), monodehydroascorbate reductase (MDHAR), ascorbate (AsA), and glutathione (GSH) decreased significantly, while catalase (CAT) activity increased gradually during the decline of seed viability. Transcriptomic results showed that a total of 801 differentially expressed genes (DEGs) were identified between fresh and 1-month-stored seeds, while 1,524 were identified between fresh and 3-month-stored seeds. Among them, the expression of CAT, MDHAR, GSH and GR were consistent with the results of physiological indicators. Moreover, WRKY, C3H, bZIP, B3, bHLH, NAC and AP2 / ERF-ERF transcription factors are important in regulating seed viability. Metabolomics results showed that the types of differential accumulated metabolites (DAMs) during viability decline were mainly flavonoids, amino acids and derivatives, and phenolic acids. The combined analysis results of transcriptomics and metabolomics further showed that DEGs and DAMs associated with viability were co-enriched in flavonoid biosynthesis and tryptophan metabolism pathways. Also identified were 22 key antioxidant genes, including CAT, ALDH, CHS and C4H, which were identified as participating in the changes of seed viability. This also illustrated that the metabolic pathways of flavonoid biosynthesis and tryptophan metabolism were involved in regulating the decline of seed viability by acting on the antioxidant system. These findings provide new insights into the mechanism of seed viability decline of E. mollis.PMID:40175887 | DOI:10.1186/s12864-025-11483-3

Sci Rep. 2025 Apr 2;15(1):11310. doi: 10.1038/s41598-025-96004-8.ABSTRACTColorectal cancer (CRC) is the third most commonly diagnosed malignant tumour in worldwide populations. Although colon cancer (CC) and rectal cancer (RC) are often discussed together, there is a global trend towards considering them as two separate disease entities. It is necessary to choice the appropriate treatment for CC and RC based on their own characteristics. Hence, it is a great importance to find effective biomarkers to distinguish CC from RC. In the present study, a total of 343 participants were recruited, including 132 healthy individuals, 101 patients with CC, and 110 patients with RC. The concentrations of 93 metabolites were determined by using a combination of dried blood spot sampling and direct infusion mass spectrometry technology. Multiple algorithms were applied to characterize altered metabolic profiles in CC and RC. Significantly altered metabolites were screened for distinguishing RC from CC in training set. A biomarker panel including Glu, C0, C8, C20, Gly/Ala, and C10:1 was tested with tenfold cross-validation and an independent test set, and showed the potential to distinguish between RC and CC. The metabolomics analysis makes contribution to summarize the metabolic differences in RC and CC, which might provide further guidance on novel clinical designs for the two diseases.PMID:40175601 | DOI:10.1038/s41598-025-96004-8

Sci Rep. 2025 Apr 2;15(1):11309. doi: 10.1038/s41598-025-95816-y.ABSTRACTMetformin is an antidiabetic drug used in type 2 diabetes as well as indicators in polycystic ovary syndrome (PCOS) and cancer. Due to their increase in popularity, high amounts of metformin are being released into aquatic environments. However, the toxic effect of metformin on embryonic development in aquatic organisms remains limited. Therefore, this study aimed to elucidate the lethal embryotoxicity of metformin and determine the underlying molecular pathways influencing embryonic development using a zebrafish model through multi-omics analysis. Metformin was microinjected into zebrafish embryos at the 1-cell stage with varying concentrations (50 mM, 100 mM, 200 mM, 400 mM, and 800 mM). From the results, hatching rates decreased in a dose dependent manner. Fetal malformation and mortality (LC50 = 339.8 mM) increased in a dose dependent manner. In situ hybridization of whole-embryo assays demonstrated that metformin exerts a significant impact on the initial stages of embryonic development, leading to aberrant differentiation of the germ layers, perturbed organogenesis, and delayed development. Furthermore, transcriptomics, metabolomics, and lipidomics were used to study the molecular mechanisms of embryonic toxicity. The results showed that the cell cycle, dorsoventral axis formation, and collecting duct acid secretion pathways were significantly altered in treated embryos. In brief, these results provide useful information on the lethal toxicity mechanism of metformin overdose and provide clues for further studies in humans.PMID:40175592 | DOI:10.1038/s41598-025-95816-y

NPJ Precis Oncol. 2025 Apr 2;9(1):96. doi: 10.1038/s41698-025-00865-1.ABSTRACTMolecular Tumor Boards (MTBs) are pivotal in personalized cancer care. This systematic review and meta-analysis included 34 studies out of 576 articles (2020-January 2024) involving 12,176 patients across 26 major cancer entities. Of these, 20.8% (2,532 patients) received MTB-recommended therapies, with 178 outcome measures reported, achieving a median overall survival (OS) of 13.5 months, progression-free survival (PFS) of 4.5 months, and an objective response rate (ORR) of 5-57%. A pooled PFS2/PFS1 ratio ≥ 1.3 from 14 reports was observed in 38% (33-44%) of cases. Comparative data showed improved outcomes for MTB-treated patients, with hazard ratios of 0.46 (0.28-0.76, p < 0.001) for OS in 19 and 0.65 (0.52-0.80, p < 0.001) for PFS in 3 studies. These results highlight the benefits of MTB evaluations in improving outcomes for patients with solid tumors but also emphasize the need for standardized evaluation criteria to enable robust comparisons across studies.PMID:40175535 | DOI:10.1038/s41698-025-00865-1

Sci Rep. 2025 Apr 2;15(1):11243. doi: 10.1038/s41598-025-95671-x.ABSTRACTCirculating tumor cells (CTCs) are critical biomarkers for cancer diagnosis, prognosis, and therapy monitoring, but their rarity and reliance on surface markers limit detection and isolation. While conditionally replicative adenoviruses (crADs) enable tumor-selective targeting, their use has been limited to fluorescence-based detection without robust isolation of viable cells. To overcome this, we developed a crAD-based platform integrating SpyTag/SpyCatcher technology with SpyCatcher-decorated magnetic microbeads for marker-independent CTC detection and isolation. The engineered adenovirus (CR-Ad5-ST-GFP) selectively replicates in telomerase-positive tumor cells, expressing green fluorescent protein (GFP) and SpyTag under independent promoters. By leveraging the SpyTag/SpyCatcher interaction, our platform isolates CTCs without relying on surface markers, addressing epithelial-to-mesenchymal transition (EMT) and phenotype variations. In proof-of-concept experiments, A-549 and Ca Ski cells spiked into peripheral blood mononuclear cells (PBMCs) at 1:10,000 were detected and isolated with over 80% efficiency. The isolated cells remained viable and were successfully re-cultured, demonstrating their potential for downstream applications such as molecular profiling and drug sensitivity testing. This method advances crAD-based approaches by combining tumor-selective viral targeting with marker-independent, viable CTC isolation. Its compatibility with microfluidic systems makes it a promising tool for tumor monitoring and personalized cancer treatment.PMID:40175496 | DOI:10.1038/s41598-025-95671-x

Sci Rep. 2025 Apr 2;15(1):11347. doi: 10.1038/s41598-025-88807-6.ABSTRACTAmbient air pollution affects the respiratory system, but evidence of its impacts on asthma and lung function is lacking. We aimed to evaluate whether ambient air pollutants are associated with asthma prevalence, asthma outcomes, and lung function in adults. A cross-sectional study of 454,921 adults aged 37 to 73 years from the UK Biobank was performed with linear or logistic regression to assess the associations among air pollution and asthma prevalence, current wheezing, asthma hospitalizations and lung function. Each interquartile range (IQR) increase in of PM2.5 (odds ratio [OR]: 1.023, 95% confidence interval [CI]: 1.011-1.035), PM10 (OR: 1.013, 95% CI: 1.004-1.022), NO2 (OR: 1.025, 95% CI: 1.013-1.039), and NOx (OR: 1.019, 95% CI: 1.008-1.029) was significantly associated with asthma prevalence, respectively. Moreover, exposure to air pollution was related to increased odds of current wheezing and asthma-related hospitalization. Among asthmatic participants, each IQR increase in PMcoarse, PM10, NO2, and NOx was significantly associated with decreases of 5.143 ml, 7.614 ml, 13.266 ml, 9.440 ml, respectively, for the forced expiratory volume in one second and 11.744 ml, 15.637 ml, 13.041 ml, 9.063 ml, respectively, for the forced vital capacity. In a large sample size study of British adults, air pollution was related to increased odds of asthma prevalence. Among the asthmatic population, air pollution was associated with increased odds of current wheezing, hospitalization, and decreased lung function.PMID:40175422 | DOI:10.1038/s41598-025-88807-6

Sci Rep. 2025 Apr 2;15(1):11215. doi: 10.1038/s41598-025-95165-w.ABSTRACTSelenium is an indispensable nutrient for plants, and optimizing selenium levels can enhance plant growth and metabolism, leading to improved yield and quality. In comparison to conventional inorganic or organic selenium fertilizers, nano-selenium demonstrates superior safety and enhanced biological activity, making it more suitable for crop production. Although nano-selenium fertilizer is extensively used in various crops, its application in pak choi remains limited. As a vital source of selenium, previous research on pak choi (Brassica chinensis var. pekinensis cv. 'Suzhouqing') has primarily focused on investigating physiological effects with limited exploration of the molecular mechanism. Therefore, this study aims to investigate the impact of nano-selenium on pak choi through an integrated analysis of transcriptome and metabolome. Specifically, we examined the effects of different concentrations of nano-selenium (0, 5, 10 and 20 mg L-1) on the growth and nutritional quality of Suzhouqing. The findings revealed that a low concentration (5 mg L-1) of nano-selenium significantly increased leaf weight and total selenium content, while modulating primary metabolites such as soluble amino acids, proteins, sugars and ascorbic acid. Additionally, it influenced secondary metabolites including glucosinolates, phenolic acids and flavonoids. Consequently, this enhancement in growth performance and nutritional quality was attributed to the regulation of pathways involved in selenocompound metabolism, phenylpropanoid biosynthesis, and flavonoid biosynthesis by key enzymes such as methionine S-methyltransferase, 5-methyltetrahydrofolate-homocysteine methyltransferase, kynurenine-oxoglutarate transaminase, thioredoxin reductase, phenylalanine ammonian-lyase, 4-coumarate-CoA ligase, flavonoid 3', 5'-hydroxylase, naringenin 3-dioxygenase, flavonol synthase and bifunctional dihydroflavonol 4-reductase. These results provide comprehensive insights into the physiological and molecular mechanisms underlying the influence of nano-selenium on plant growth and nutritional quality. Therefore, they offer a solid theoretical basis and technical support for breeding and cultivation strategies aimed at producing selenium-rich pak choi.PMID:40175406 | DOI:10.1038/s41598-025-95165-w

Nat Commun. 2025 Apr 2;16(1):2539. doi: 10.1038/s41467-025-57273-z.ABSTRACTWe evaluated associations among exposure to prenatal phthalate metabolites, perturbations of the newborn metabolome, and infant neurobehavioral functioning in mother-newborn pairs enrolled in the Atlanta African American Maternal-Child Cohort during 2016-2018. We quantified eight phthalate metabolites in prenatal urine samples collected between 8- and 14-weeks' (visit 1; n = 216) and 24- and 30-weeks' gestation (visit 2; n = 145) and metabolite features in newborn dried-blood spot samples collected at delivery. Associations between phthalate metabolite concentrations and metabolic feature intensities at both visits were examined using adjusted generalized linear models (MWAS). Then, an exploratory meet-in-the-middle (MITM) analysis was conducted in a subset with NICU Neonatal Neurobehavioral Scale (NNNS) scores (visit 1 n = 81; visit 2 n = 71). In both the MWAS and MITM, many of the confirmed metabolites are involved in tyrosine and tryptophan metabolism, including tryptophan, tyrosine, thyroxine, and serine. This analysis elucidates how prenatal phthalate exposure disrupts the newborn metabolome and infant neurobehavioral outcomes.PMID:40175358 | DOI:10.1038/s41467-025-57273-z

Adv Pharmacol. 2025;103:185-207. doi: 10.1016/bs.apha.2025.01.001. Epub 2025 Feb 6.ABSTRACTHigh-throughput computational screening (HTCS) has revolutionized the drug discovery process by enabling the rapid identification and optimization of potential lead compounds. Leveraging the power of advanced algorithms, machine learning, and molecular simulations, HTCS facilitates the efficient exploration of vast chemical spaces, significantly accelerating early-stage drug discovery. The time, cost, and labor in the case of traditional experimental approaches are reduced by the ability to virtually screen millions of compounds for biological activity. This paradigm shift is also facilitated by the combination of omics data, genomics, proteomics, and metabolomics in computational pipelines, allowing detailed understanding of complex biological systems and paving the way toward personalized medicine. Core methods such as molecular docking, QSAR models, and pharmacophore modeling are the foundation of HTCS, providing predictive information on molecular interactions and binding affinities. Machine learning and artificial intelligence are augmenting these tools with more precise prediction accuracy and revealing rich patterns embedded in molecular data. With the development of HTCS, more and more, computational methods are used as a powerful tool in de novo drug design, in which computational tools produce a novel chemical entity that shows optimal fit to the target. Despite its transformative potential, HTCS faces challenges related to data quality, model validation, and the need for robust regulatory frameworks. Nevertheless, as AI-driven approaches, quantum computing, and big data analytics continue to evolve, HTCS is set to become a cornerstone of modern drug discovery, reshaping the field with smarter, more personalized therapeutic strategies that address complex diseases with precision and efficiency.PMID:40175041 | DOI:10.1016/bs.apha.2025.01.001

Adv Pharmacol. 2025;103:1-22. doi: 10.1016/bs.apha.2025.01.006. Epub 2025 Feb 13.ABSTRACTIn the current scenario of pandemics, drug discovery and design have undergone a significant transformation due to the integration of advanced computational methodologies. These methodologies utilize sophisticated algorithms, machine learning, artificial intelligence, and high-performance computing to expedite the drug development process, enhances accuracy, and reduces costs. Machine learning and AI have revolutionized predictive modeling, virtual screening, and de novo drug design, allowing for the identification and optimization of novel compounds with desirable properties. Molecular dynamics simulations provide a detailed insight into protein-ligand interactions and conformational changes, facilitating an understanding of drug efficacy at the atomic level. Quantum mechanics/molecular mechanics methods offer precise predictions of binding energies and reaction mechanisms, while structure-based drug design employs docking studies and fragment-based design to improve drug-receptor binding affinities. Network pharmacology and systems biology approaches analyze polypharmacology and biological networks to identify novel drug targets and understand complex interactions. Cheminformatics explores vast chemical spaces and employs data mining to find patterns in large datasets. Computational toxicology predicts adverse effects early in development, reducing reliance on animal testing. Bioinformatics integrates genomic, proteomic, and metabolomics data to discover biomarkers and understand genetic variations affecting drug response. Lastly, cloud computing and big data technologies facilitate high-throughput screening and comprehensive data analysis. Collectively, these computational innovations are driving a paradigm shift in drug discovery and design, making it more efficient, accurate, and cost-effective.PMID:40175036 | DOI:10.1016/bs.apha.2025.01.006

Water Res. 2025 Mar 24;281:123548. doi: 10.1016/j.watres.2025.123548. Online ahead of print.ABSTRACTFoaming during anaerobic digestion (AD) of sewage sludge is poorly understood and remains an uncontrollable operational obstacle for sewage treatment systems globally, causing mechanical damage, increased hazards and reduced biogas recovery. Foams during AD commonly occur after process disturbances, such as organic loading shocks. However, it is still unclear whether these foam events are biologically driven and linked to the abundance of organisms like filamentous or hydrophobic bacteria. A time-series study was conducted, comparing digestion performance, microbial community succession, metagenomes, and metabolomes in six anaerobic continuous stirred-tank reactors (CSTRs): a control group fed normally (n = 3), and one treated group inhibited through organic shock loading of more than twice the steady state loading rate with glycerol (treatment, n = 3). As soon as microbial activity and methanogenesis recovered after inhibition, significant volumes of foam accumulated simultaneously in the reactor headspace of the three treated CSTRs. Microbial abundance profiles (16S rRNA, V3-V4) from 165 days of operation showed that filamentous or mycolic acid-producing organisms were not associated with this foam event. Shock loading led to acidification, biomass decline and microbial imbalance, contributing indirectly to the foam event. During that period, metabolomes and functional pathway abundances indicated that the stressed microbial biomass was enriched in long-chain fatty acids prior to foaming. This biomass, combined with pH changes, may have modified the physicochemical properties of sludge, leading to the fractionation of organic mass once gas production resumed. More research is needed to understand how abiotic and biotic interactions contribute to foam formation.PMID:40174565 | DOI:10.1016/j.watres.2025.123548

Asian J Psychiatr. 2025 Apr 1;107:104478. doi: 10.1016/j.ajp.2025.104478. Online ahead of print.NO ABSTRACTPMID:40174517 | DOI:10.1016/j.ajp.2025.104478

Redox Biol. 2025 Mar 27;82:103613. doi: 10.1016/j.redox.2025.103613. Online ahead of print.ABSTRACTLifestyle factors such as a Western diet or metabolic diseases like diabetes disrupt glucose homeostasis and induce stress responses, yet their impact on skin metabolism and structural integrity remains poorly understood. Here, we performed multiomic and bioenergetic analyses of human dermal fibroblasts (HDFs), human equivalent dermis (HED), human reconstructed skin (HRS), and skin explants from diabetic patients. We found that 12 mM glucose stress represses oxidative phosphorylation (OXPHOS) through a dual mechanism: the glucose-dependent nuclear receptor NR2F2 activates mitochondrial transcription termination factor 3 (MTERF3) while inhibiting growth-differentiation factor 15 (GDF15). Promoter assays revealed that MTERF3 is regulated by NR2F2 and MYCN, whereas GDF15 is modulated by NR2F2 and FOS. Consequently, OXPHOS proteins and mitochondrial respiration were suppressed, and MTERF3 overexpression additionally interfered with collagen biosynthesis. In contrast, GDF15 supplementation fully rescued hyperglycemia-induced bioenergetic and metabolomic alterations, suggesting a pharmacological strategy to mitigate hyperglycemic damage in the skin. Finally, silencing GDF15 or TFAM impaired fibroblast haptotaxis and skin reconstruction, underscoring the crucial role of mitochondrial energetics in dermal structure and function. Collectively, these findings identify the NR2F2-MTERF3-GDF15 axis as a key mediator of OXPHOS suppression and highlight a potential therapeutic target to preserve skin integrity under hyperglycemic stress.PMID:40174478 | DOI:10.1016/j.redox.2025.103613

Plant Physiol Biochem. 2025 Mar 18;223:109802. doi: 10.1016/j.plaphy.2025.109802. Online ahead of print.ABSTRACTDrought stress (DS) significantly hampers the growth and productivity of tea plants, necessitating effective strategies to enhance their resilience. This study comprehensively investigated the mechanisms of carbonyl volatiles-methyl jasmonate (MeJA) and cis-3-hexenyl acetate (cis-3-HAC) and signal peptide CLAVATA3/EMBRYO-SURROUNDING REGION-RELATED 25 (CLE25) promotion DS resistance using integrative metabolomics and proteomics strategy. Total pigment content decreased, while soluble sugar and proteins increased significantly under DS and further increased after foliar inducement of CLE25, MeJA, and cis-3-HAC. Gallated catechins and amino acids exhibited apparent decreased under DS, especially EGCG (24.6-13.4 mg g-1) and theanine (10.66-3.78 mg g-1), but significantly mitigated by CLE25 inducement. Antioxidant enzymes activity, such as catalase (CAT), jumped from 23.1 to 48.2 and further boosted to 118.8 Ug-1min-1 FW with CLE25. Proteomic analysis revealed massive increased in stress tolerance proteins, particularly dehydrins and heat shock proteins, rising by >50.0 % with CLE25 inducement and the expression levels of peroxidase (POX), superoxide dismutase (SOD), α-galactosidase (α-GAL), carboxypeptidases (CPs), and transaldolase (TAL) exhibited higher after inducement. Furthermore, stress signaling-related proteins were in-depth explored, especially thioredoxin proteins; sucrose non-fermenting 1-related protein kinase 2 (SnRK2) was novelly verified in activating abscisic acid (ABA) responding. Differences among drought resistance mechanisms after carbonyl volatile and CLE25 treatments were comprehensively studied. The integration of metabolite and protein levels provided a comprehensive illustration of tea DS tolerance mechanisms and offered promising promotion strategies through foliar application of MeJA, cis-3-HAC, and CLE25.PMID:40174298 | DOI:10.1016/j.plaphy.2025.109802

Nat Prod Res. 2025 Apr 2:1-10. doi: 10.1080/14786419.2025.2487692. Online ahead of print.ABSTRACTDuchesnea indica is a traditional medicinal plant known for its antioxidant, anticancer and antibacterial properties. This study is the first to investigate endophytic fungi in D. indica, isolating PS4 (Aspergillus sp.) and employing the innovative OSMAC strategy to enhance its metabolomic profile, analysing the metabolites of both D. indica and its endophytic fungus for the first time using UPLC-Orbitrap HRMS. Specifically, in potato dextrose broth (PDB), PS4's metabolites showed remarkable potential for antioxidant, antibacterial and anticancer effects. The potential targets for the anticancer effects of D. indica and its endophytic fungus were innovatively predicted using network pharmacology and molecular docking, identifying 17 key compounds and six core target genes for the first time in this context. Strong binding between these components and target genes underscores the value of integrating metabolomics and network pharmacology in natural product research, laying a foundation for future drug development.PMID:40174222 | DOI:10.1080/14786419.2025.2487692

Plant Physiol. 2025 Apr 2:kiaf126. doi: 10.1093/plphys/kiaf126. Online ahead of print.ABSTRACTPotato (Solanum tuberosum) is highly water and space efficient but susceptible to abiotic stresses such as heat, drought, and flooding, which are severely exacerbated by climate change. Our understanding of crop acclimation to abiotic stress, however, remains limited. Here, we present a comprehensive molecular and physiological high-throughput profiling of potato (Solanum tuberosum, cv. Désirée) under heat, drought, and waterlogging applied as single stresses or in combinations designed to mimic realistic future scenarios. Stress responses were monitored via daily phenotyping and multi-omics analyses of leaf samples comprising proteomics, targeted transcriptomics, metabolomics, and hormonomics at several timepoints during and after stress treatments. Additionally, critical metabolites of tuber samples were analyzed at the end of the stress period. We performed integrative multi-omics data analysis using a bioinformatic pipeline that we established based on machine learning and knowledge networks. Waterlogging produced the most immediate and dramatic effects on potato plants, interestingly activating ABA responses similar to drought stress. In addition, we observed distinct stress signatures at multiple molecular levels in response to heat or drought and to a combination of both. In response to all treatments, we found a downregulation of photosynthesis at different molecular levels, an accumulation of minor amino acids, and diverse stress-induced hormones. Our integrative multi-omics analysis provides global insights into plant stress responses, facilitating improved breeding strategies toward climate-adapted potato varieties.PMID:40173380 | DOI:10.1093/plphys/kiaf126

Curr Opin Organ Transplant. 2025 Apr 3. doi: 10.1097/MOT.0000000000001217. Online ahead of print.ABSTRACTPURPOSE OF REVIEW: Despite the introduction of many new immunosuppressive medications, allograft rejection remains a significant complication in transplantation. The use of "liquid biopsy" to evaluate allograft function and detect early rejection has recently become a prominent focus of investigation as it holds promise in providing noninvasive and immediate insights into the cellular and molecular makeup of the graft.RECENT FINDINGS: In recent years, the introduction of molecular medicine along with the use of new technologies, including high-throughput techniques, has not only accelerated biomarker discovery but has also contributed to improving our understanding of the mechanisms underlying immune rejection. Genomics, transcriptomics, and metabolomics approaches, along with the increasing use of machine learning techniques, have paved the way for the discovery and development of novel biomarkers.SUMMARY: Each year, there are hundreds of new biomarker discoveries in the publications. However, only a small fraction can be practically used as clinical tests or surrogate endpoints, receive FDA approval, and reach clinical application. Well designed and reproducible discovery and validation studies are rare and crucial. A contributing factor could be poor study design or quality of biospecimen repositories. In this review, we discuss urinary biomarkers of kidney allograft rejection that have shown promising findings but have yet to be successfully transitioned from bench to bedside.PMID:40173008 | DOI:10.1097/MOT.0000000000001217