PubMed

Clin Exp Rheumatol. 2025 Mar 28. doi: 10.55563/clinexprheumatol/9sdln5. Online ahead of print.ABSTRACTThe incidence of gout has increased steadily over the last decades and its management is still unsatisfactory. Growing evidence highlights the multifactorial etiology of this disease encompassing genetic predisposition, environmental stimuli and gut dysbiosis. Recent advances in biomolecular and computer sciences allowed to gain more and more genetic, epigenetic, transcriptomic, proteomics and metabolomics insights into hyperuricaemia and gout-related molecular mechanisms. Moreover, the interplay between gout and cardiovascular, metabolic and renal diseases may potentially offer novel targets for anti-inflammatory and urate-lowering therapies.This annual review aims to provide the latest updates on gout research, epidemiology, genetics, molecular mechanisms, diagnostic approach, and therapeutic advances.PMID:40153315 | DOI:10.55563/clinexprheumatol/9sdln5

Clin Rheumatol. 2025 Mar 28. doi: 10.1007/s10067-025-07402-2. Online ahead of print.ABSTRACTINTRODUCTION: Metabolic disorders represent a hallmark feature of gout. However, evidence on the causality of blood metabolites and gout remains lacking. We performed a Mendelian randomization (MR) analysis to systematically evaluate the causality from genetically proxied 1398 blood metabolites to gout.METHOD: Genome-wide association study (GWAS) data for 1398 blood metabolites were extracted from 8299 European subjects. The discovery stage was performed using gout data from FinnGen consortium R9 to initially explore causal associations between metabolites and gout. The significant associations identified in the discovery stage were validated in the replication stage employing gout GWAS data from the IEU database. Random-effect inverse variance weighted was chosen as the main method for causality analysis, with MR-Egger, weighted median, robust adjusted profile score, and maximum likelihood as complementary analysis methods. Then, a series of sensitivity analyses were performed.RESULTS: Results showed that there was a significant causal relationship between eight metabolites and gout, including 21-hydroxypregnenolone disulfate levels, carnitine levels, ethyl beta-glucopyranoside levels, gamma-glutamylglycine levels, glycine levels, glycine-to-alanine ratio, glycolithocholate sulfate levels, and propionylglycine levels. Colocalization analysis evidence strongly supported a causal relationship between 21-hydroxypregnenolone disulfate levels and carnitine levels and gout. In addition, four metabolic pathways were involved in the biological process of gout (carnitine synthesis, beta oxidation of very long-chain fatty acids, alanine metabolism, glutathione metabolism).CONCLUSIONS: The current study provides evidentiary support for the causal relationship between eight blood metabolites and gout and identifies four significant metabolic pathways. These findings hold the potential to inform future research, clinical interventions, and therapeutic strategies for gout.PMID:40153197 | DOI:10.1007/s10067-025-07402-2

J Chem Inf Model. 2025 Mar 28. doi: 10.1021/acs.jcim.5c00167. Online ahead of print.ABSTRACTAccurate retention time (RT) prediction in liquid chromatography remains a significant consideration in molecular analysis. In this study, we explore the use of a transformer-based language model to predict RTs by treating simplified molecular input line entry system (SMILES) sequences as textual input, an approach that has not been previously utilized in this field. Our architecture combines a pretrained RoBERTa (robustly optimized BERT approach, a variant of BERT) with bidirectional long short-term memory (BiLSTM) networks to predict retention times in reversed-phase high-performance liquid chromatography (RP-HPLC). The METLIN small molecule retention time (SMRT) data set comprising 77,980 small molecules after preprocessing, was encoded using SMILES notation and processed through a tokenizer to enable molecular representation as sequential data. The proposed transformer-LSTM architecture incorporates layer fusion from multiple transformer layers and bidirectional sequence processing, achieving superior performance compared to existing methods with a mean absolute error (MAE) of 26.23 s, a mean absolute percentage error (MAPE) of 3.25%, and R-squared (R2) value of 0.91. The model's explainability was demonstrated through attention visualization, revealing its focus on key molecular features that can influence RT. Furthermore, we evaluated the model's transfer learning capabilities across ten data sets from the PredRet database, demonstrating robust performance across different chromatographic conditions with consistent improvement over previous approaches. Our results suggest that the hybrid model presents a valuable approach for predicting RT in liquid chromatography, with potential applications in metabolomics and small molecule analysis.PMID:40152775 | DOI:10.1021/acs.jcim.5c00167

mSystems. 2025 Mar 28:e0148724. doi: 10.1128/msystems.01487-24. Online ahead of print.ABSTRACTHoneybees (Apis mellifera), as social insects, exhibit complex social behaviors and cognitive functions. The short lifespan and stable gut microorganisms of honeybees provide certain availability as a rapid and high-flux animal model for aging research. This study explored the effect of D-galactose, a common aging inducer, on honeybees and investigated the associated effects and mechanisms, with particular focus on the potential protective role of sodium butyrate. Experimental cohorts were established as follows: conventional (CV) group, D-galactose-treated (DG) group, and sodium butyrate-treated (SB) group. The CV group was fed sucrose solution; the DG group was fed D-galactose solution; and the SB group was fed D-galactose and sodium butyrate solution. A comprehensive assessment was conducted on day 15 post-treatment, including survival analysis, starvation test, motor, learning and memory ability tests, malondialdehyde test, and Smurf test. Potential mechanisms through the microbiome and metabolome were investigated. Compared to the honeybees from the CV group, those in the DG group showed a shortened lifespan, a weaker energy storage ability, impaired motor, learning, and memory abilities, reduced weight, increased oxidation, and a disrupted gut barrier. These phenotypic changes were associated with microbial dysbiosis characterized by Lactobacillus enrichment and diminished butyrate levels. Notably, sodium butyrate supplementation extended the honeybees' lifespan and improved their learning and memory abilities damaged by D-galactose. Our findings establish honeybees as a valuable model system for aging research and highlight the crucial role of butyrate metabolism in senescence regulation.IMPORTANCEThis study presents a novel approach to investigating aging processes by establishing a D-galactose-induced aging model in honeybees. Our findings demonstrate that butyrate supplementation effectively attenuates D-galactose-induced senescence phenotypes, suggesting its potential as a therapeutic intervention for age-related decline. This research provides a unique model system for aging studies and highlights the significant role of butyrate in modulating senescence progression. The results contribute to our understanding of the molecular mechanisms underlying aging and offer new insights into potential anti-aging strategies.PMID:40152582 | DOI:10.1128/msystems.01487-24

J Gerontol A Biol Sci Med Sci. 2025 Mar 27:glaf057. doi: 10.1093/gerona/glaf057. Online ahead of print.ABSTRACTBACKGROUND: Metabolic-inflammatory states are central to multiorgan mechanisms of aging, but precise functional biomarkers of physiological aging remain less clear.METHODS: In the Health, Aging and Body Composition study, we defined metabolomic profiles of the Healthy Aging Index (HAI), a composite of cardiovascular, lung, cognitive, metabolic, and renal function (0-10, with higher scores indicating poorer health) in a split set design from 2015 older participants (mean age 73.6 years; 50% women; 35% Black). We used standard regression to identify metabolomic correlates of Year 1 and Year 10 HAI, change in HAI over time, and mortality. A metabolite score of HAI was developed using LASSO regression.RESULTS: We identified 42 metabolites consistently associated with Year 1 and Year 10 HAI, as well as change in HAI: 13 lipids, 4 amino acids, and 4 metabolites of other classes were associated with worse and worsening HAI while 20 lipids and 1 amino acid was associated with better and improving HAI. Most of these associations were no longer significant after additionally adjusting for inflammation biomarkers. A higher metabolite score of Year 1 HAI was associated with greater HAI deterioration over time (hold-out "test" set beta 0.40 [0.15-0.65]) and higher mortality (hold-out "test" set hazard ratio: 1.43 [1.23-1.67]).CONCLUSIONS: A multi-organ healthy aging phenotype was linked to lipid metabolites, suggesting potential pathways related to mitochondrial function, oxidative stress and inflammation. Metabolomics of HAI at older age were related to worsening health and mortality, suggesting potential links between metabolism and accelerated physiological aging.PMID:40152499 | DOI:10.1093/gerona/glaf057

Front Biosci (Landmark Ed). 2025 Mar 21;30(3):27236. doi: 10.31083/FBL27236.ABSTRACTBACKGROUND: An appropriate animal model that can simulate the pathological process of atherosclerosis is urgently needed to improve treatment strategies. This study aimed to develop a new atherosclerosis model using ApoE-/- mice and to characterize lipidomics, gut microbiota profiles, and phenotypic alterations in adipose tissue using this model.METHODS: After a 14- or 18-week high-fat diet (HFD), male ApoE-/- mice were randomly divided into four groups and treated separately with or without short-term and strong co-stimulation, including ice water bath and intraperitoneal injection of lipopolysaccharide and phenylephrine. As a control group, C57BL/6 mice were fed with conventional chow. The serum lipid levels, aortic arch pathology, adipose tissue phenotypic changes, plasma lipidomics, and 16S rDNA gene sequencing of colon feces were investigated.RESULTS: The serum lipid levels were significantly lowered following extended HFD feeding for four weeks. However, co-stimulation increased serum interleukin (IL)-1β levels but did not affect serum lipid profiles. Co-stimulation revealed typical vulnerable atherosclerotic plaque characteristics and defective adipose hypertrophy associated with peroxisome proliferator-activated receptor γ (PPARγ) regulation in adipose tissue and a reduction in mitochondrial uncoupling protein 1 (UCP1) within brown adipose tissue. Plasma lipidomic analysis showed that sphingomyelin (SM), ceramide (Cer), and monohexosylceramide (HexCer) levels in plasma were significantly elevated by HFD feeding, whereas co-stimulation further elevated HexCer levels. Additionally, glycerophosphocholines (16:0/16:0, 18:2/20:4, 18:1/18:1) and HexCer (C12:1, C16:0), Cer (d18:1/16:0), and SM (C16:0) were the most sensitive to co-stimulation. Combined co-stimulation and HFD-fed increased the abundance of Firmicutes, the abundance of f_Erysipelotrichaceae, and the Firmicutes/Bacteroidota ratio but decreased the abundance of microflora promoting bile acid metabolism and short-chain fatty acids (SCFAs) in mouse feces. The results were consistent with the findings of epidemiologic atherosclerotic cardiovascular disease studies.CONCLUSIONS: This study established an ApoE-/- mouse atherosclerotic vulnerable plaque model using a multi-index evaluation method. Adipogenic disorders, dysregulation of lipid metabolism at the molecular level, and increasing harmful gut microbiota are significant risk factors for vulnerable plaques, with sphingolipid metabolism receiving the most attention.PMID:40152393 | DOI:10.31083/FBL27236

Front Biosci (Landmark Ed). 2025 Mar 21;30(3):31396. doi: 10.31083/FBL31396.ABSTRACTBACKGROUND: Bodyweight high-intensity interval training (BW-HIIT) is an effective, time-efficient exercise method that reduces cardiovascular risk factors and improves muscle endurance without requiring external equipment. High mobility group box 1 (HMGB1) is a proinflammatory protein involved in insulin resistance. Previous studies revealed that HMGB1 knockout mice show improved insulin sensitivity and hyperglycemia. This study investigates whether BW-HIIT exercise can reduce proinflammatory markers, such as HMGB1, in individuals with insulin resistance.METHODS: In total, 14 adults (2 male/12 female) aged 18 to 55 were subject to six weeks of BW-HIIT. Additionally, 10-week-old mice were subject to exercise conditioning (5 mice per group (all male)) for 4 weeks of treadmill exercise or sedentary. Human and mouse pre- and post-exercise serum/plasma samples were analyzed for lipidomics, hormonal, and cytokine multiplex assays. Cardiometabolic parameters were also performed on human subjects.RESULTS: Post-exercise decreased systolic blood pressure (SBP), cholesterol, triglycerides, high-density lipoprotein (HDL), and cholesterol/HDL ratio in human patients with insulin resistance. Meanwhile, hormones such as amylin, glucagon, and insulin all increased post-BW-HIIT or treadmill exercise in both human and mouse models. Moreover, circulating HMBG1 levels were reduced in insulin-resistant individuals and mice after exercise. Furthermore, treadmill exercise by the animal model increased anti-inflammatory cytokines, including interleukin (IL)-10, IL-12p40, and IL-12p70, and reduced proinflammatory cytokines: eotaxin, IL-2, and macrophage inflammatory protein (MIP)-2 or CXCL2.CONCLUSIONS: Six weeks of BW-HIIT exercise can improve cardiometabolic health, anti-inflammatory markers, hormones, and insulin sensitivity in human and mouse models undergoing exercise. Changes in circulating HMBG1 levels following BW-HIIT exercise make HMGB1 a suitable marker for cardiometabolic disease, potentiating its role beyond an alarmin. Further studies are needed to confirm these effects and to elucidate the underlying physiological mechanisms.PMID:40152388 | DOI:10.31083/FBL31396

Parasitology. 2025 Mar 28:1-31. doi: 10.1017/S0031182025000162. Online ahead of print.NO ABSTRACTPMID:40152283 | DOI:10.1017/S0031182025000162

J Tradit Chin Med. 2025 Apr;45(2):225-233. doi: 10.19852/j.cnki.jtcm.2025.02.008.ABSTRACTOBJECTIVES: To systematically review the efficacy and safety of Jianpi formulas in reducing the recurrence of colorectal adenoma (CRA) after poly-pectomy.METHODS: Randomized controlled trials (RCTs) investigating Jianpi formulas for CRA post-polypectomy were systematically retrieved from eight electronic databases. The quality of the methodology was assessed using the Cochrane collaboration tool. The Grades of Recommendations Assessment Development and Evaluation (GRADE) approach was employed for evidence assessment. Statistical analyses were conducted using Statistics and Data Analysis (STATA) 17 (StataCorp (College Station, TX, USA) and Review Manager (RevMan) 5.4 (The Cochrane Collaboration (London, UK).RESULTS: The Meta-analysis, encompassing 18 RCTs with 1838 patients, revealed that Jianpi formulas significantly outperformed postoperative routine treatment. It demonstrated a reduction in the half-year recurrence rate [relative risk (RR) = 0.41, 95% confidence interval (CI) = 0.33-0.49, Z = 9.08, P < 0.000 01], the one-year recurrence rate [RR = 0.58, 95% CI= 0.49-0.69, Z= 6.12, P < 0.000 01], and an enhancement in the clinical effective rate [RR = 1.27, 95% CI = 1.19-1.36, Z= 7.06, P < 0.000 01]. The half-year recurrence rate and the clinical effective rate were medium-quality evidence. The one-year recurrence rate was low-quality evidence. Additionally, Jianpi formulas appear to be safe and do not increase adverse reactions compared to postoperative routine treatment alone.CONCLUSION: Jianpi formulas exhibit efficacy in reducing postoperative half-year and one-year recurrence rates while improving the clinical effective rate after polypectomy for CRA.PMID:40151110 | DOI:10.19852/j.cnki.jtcm.2025.02.008

Biomed Chromatogr. 2025 May;39(5):e70034. doi: 10.1002/bmc.70034.ABSTRACTBoth the flower of Citrus aurantium L. var. amara (CAVA) and rhizome of Zingiber officinale Roscoe (ginger) are food and medicinal homologous plants that have been used in China for aiding gastric digestion and preventing obesity. However, the combinatorial use of the two plants on obesity remains elusive. Our endeavor aimed to identify the optimal synergistic ratio between CAVA and ginger and to explore the underlying mechanism of their anti-obesity effects. Aqueous CAVA and ginger extracts were prepared separately and then combined into nine different ratios. The constituents of CAVA and ginger were unambiguously characterized by employing LC-MS. High-fat diet (HFD)-induced obese C57BL/6J mice were established and then administered with the nine combinations of CAVA-G extracts for 6 weeks. The trajectory of mice's body weights was analyzed. Besides, hematoxylin and eosin (HE) staining of the liver and oil red O staining of adipose tissue were performed. ELISA assay was employed to measure serum levels of total cholesterol (TC), triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C). Moreover, serum metabolic profiling was conducted through UPLC-Q-TOF/MS analysis. Gut microbiota analysis was performed via 16S rRNA gene sequencing. Pattern recognition and Pearson correlation analysis were used to pinpoint the key endogenous metabolites and microbiota. Two groups of CAVA-G combination treatment (C3 and A1) significantly prevented the increase of weight in mice. According to our analysis, the best anti-obesity effect was achieved when the ratio between CAVA and ginger was 37:63. The levels of TC and LDL-C were dramatically decreased in the C3 group, whereas the level of TG was significantly reduced in the A1 group. Interestingly, HDL-C level was increased dramatically in the C3 group. Compared with the model group, a total of 16 and 25 biomarkers were identified for groups C3 and A1, respectively. These biomarkers are mainly implicated in lipid metabolism and primary bile acid biosynthesis. Interestingly, the abnormal diversity of gut microbiota was induced by HFD feeding. Treatment with C3 or A1 significantly increased the relative abundance of Akkermansia and Novosphingobium, while reducing the relative abundance of Dorea, Bacteroides and Roseburia. Of note, this is the first report that Novosphingobium is involved in preventing obesity. These findings will layer a foundation for the usage of CAVA-G for preventing obesity.PMID:40150936 | DOI:10.1002/bmc.70034

J Agric Food Chem. 2025 Mar 27. doi: 10.1021/acs.jafc.4c12022. Online ahead of print.ABSTRACTTo elucidate the cryoprotective mechanism of wheat bran antifreeze arabinoxylan (AX) on yeast cells, this study investigated its effects on the physiological, metabolic, and genetic stability of yeast subjected to cyclic freeze-thaw cycles. Antifreeze AX inhibited ice crystal growth and interacted with cells to form an external barrier, which preserved cell membrane integrity, inhibited reactive oxygen species accumulation, and reduced oxidative damage. Metabolome analysis revealed that AX regulated key metabolic pathways, enhancing cell activity and maintaining homeostasis. Transcriptome analysis demonstrated that AX promoted DNA repair and maintained genetic stability. By synergistically inhibiting ice crystal growth, forming physical barriers and regulating metabolic and genetic pathways, antifreeze AX improved yeast cell viability and activity during freeze-thaw cycles, thereby maintaining cellular homeostasis under freezing stress. This study could provide a theoretical basis for the practical application of antifreeze AX as an efficient cryoprotectant in yeast cell cryopreservation.PMID:40150904 | DOI:10.1021/acs.jafc.4c12022

Mol Nutr Food Res. 2025 Mar 27:e70029. doi: 10.1002/mnfr.70029. Online ahead of print.ABSTRACTGalangin (GAL), a flavonol found in Alpinia officinarum and propolis, is a promising functional food. This study investigated the therapeutic effects and mechanisms of GAL in mice with hyperuricemic nephropathy (HN) by focusing on renal metabolomics and network pharmacology. In this study, we conducted untargeted metabolomic analysis and network pharmacology prediction. Subsequently, a compound-reaction-enzyme-gene network was constructed based on the results of metabolomics and network pharmacology to elucidate potential connections. The results demonstrated that GAL can improve renal interstitial fibrosis and inflammatory infiltration and reduce serum levels of uric acid (UA), urea nitrogen (UREA), and creatinine (CREA). Metabolome analysis indicated that GAL affected thiamine, pyrimidine, nicotinate, nicotinamide, pyruvate, glyoxylate, and dicarboxylate metabolism. Network pharmacology and experimental results showed that GAL reduced the key target expression of the tumor protein P53 (TP53), tumor necrosis factor (TNF), signal transducer and activator of transcription 3 (STAT3), heat shock protein 90 alpha family class A member 1 (HSP90aa1), albumin (ALB), and caspase-3 (CASP3). GAL also downregulated the expression of Janus kinase 2 (JAK2), phospho-JAK2 (P-JAK2), and phospho-STAT3 (P-STAT3). Furthermore, a joint analysis of the metabolome and network pharmacology showed that GAL can reverse HN through amino acid metabolism, nucleotide metabolism, energy metabolism, and endocrine system pathways. GAL can alleviate HN effectively and might play synergistic therapeutic roles through regulating metabolic profiles and the JAK2/STAT3 signaling pathway.PMID:40150835 | DOI:10.1002/mnfr.70029

Neural Regen Res. 2025 Feb 24. doi: 10.4103/NRR.NRR-D-24-00975. Online ahead of print.ABSTRACTAlzheimer's disease is the most common cause of dementia. Although increasing evidence suggests that disruptions in lipid metabolism are closely associated with the disease, the overall profile of lipid and sterol changes that occur in the brain during Alzheimer's disease remains unclear. In this study, we compared brain tissues extracted from 32-week-old male wild-type mice and 5×FAD transgenic Alzheimer's disease model mice, which carry mutations in the amyloid precursor protein (APP) and presenilin 1 (PS1) genes. Using untargeted lipidomics and sterolomics techniques, we investigated the metabolic profiles of lipids, with a focus on sterols specifically, in three brain regions: cerebellum, hippocampus, and olfactory bulb. Our results revealed significant alterations in various lipids, particularly in the hippocampus and olfactory bulb, suggesting changes in energy levels in these regions. Further pathway analysis indicated notable disruptions in key metabolic processes, particularly those related to fatty acids and cell membrane components. Additionally, we observed decreased expression of 15 genes involved in lipid and sterol regulation. Collectively, these findings provide new insights into how imbalances in lipid and sterol metabolism may contribute to the progression of Alzheimer's disease, highlighting potential metabolic pathways involved in the development of this debilitating disease.PMID:40150820 | DOI:10.4103/NRR.NRR-D-24-00975

Mult Scler. 2025 Mar 27:13524585251325468. doi: 10.1177/13524585251325468. Online ahead of print.ABSTRACTBACKGROUND: The circulating metabolome incorporates multiple levels of biological interactions and is an emerging field for biomarker discovery. However, few studies have linked metabolite levels with quantitative neurologic function assessments in people with multiple sclerosis (pwMS).OBJECTIVES: We quantified metabolomic differences between pwMS and healthy controls (HCs) and assessed the association of metabolites with disease severity.METHODS: We profiled 517 metabolites using liquid chromatography-mass spectrometry (Biocrates Inc.) for participants from the MS Partners Advancing Technology and Health Solutions (MS PATHS). We conducted a multicenter cross-sectional study and applied linear regression to assess the association between metabolites and neurological function measures in multiple sclerosis (MS), including walking speed, manual dexterity, and processing speed.RESULTS: Among 1010 participants (837 MS; 71.2% relapsing-remitting MS; 173 HC; mean age: 44.5 (standard deviation (SD): 11.4); 73.9% female; 12.7% non-white), pwMS showed decreased levels of phosphatidylcholines (PCs) and different amino acids (AAs) but increased triglycerides (TGs). Metabolites showed an association with worse neurologic function; for instance, a 1-SD decrease in PC aa C36:6 was associated with 21.36% (95% confidence interval (CI): 11.07-30.46; p = 1.35E-04) slower walking speed.CONCLUSIONS: This large study identified lipid alterations linked to MS severity. Future longitudinal studies will evaluate if these metabolite levels predict MS outcomes.PMID:40150792 | DOI:10.1177/13524585251325468

Animals (Basel). 2025 Mar 17;15(6):860. doi: 10.3390/ani15060860.ABSTRACTGeoduck aquaculture is becoming a key component in meeting international market demand, given the natural and regulatory restrictions on wild geoduck supply. Geoduck clams are not sexually dimorphic, making it practically unfeasible to distinguish between males and females prior to a spawning event. To facilitate increased production of geoduck, a better understanding of reproductive biology and associated targeted bio-markers is required. In this study, metabolomics was utilised as a research tool to distinguish between metabolites related to male and female New Zealand geoduck (Panopea zelandica), gill and muscle samples collected from broodstock individuals housed in an experimental hatchery. A total of 17 metabolites were detected, showing significant differences between sexes. The findings indicate that metabolites associated with lipid biosynthesis were increased in female clams to support reproductive functions. An increase in carbohydrate-linked metabolic pathways was detected in male geoduck, arguably to sustain sperm production. Taurine has been reported as a biomarker to distinguish between male and female bivalves in other studies and is confirmed within this study, with significant elevation in male adductor muscle tissue. Moreover, male geoduck had increased purine and pyrimidine biosynthesis, supporting energy needs. This study provides useful sex biomarkers for future breeding strategies of P. zelandica.PMID:40150389 | DOI:10.3390/ani15060860

Animals (Basel). 2025 Mar 14;15(6):842. doi: 10.3390/ani15060842.ABSTRACTThe main objective of this research was to observe the effects of feed restriction on caecum microbiota and metabolites in rabbits. Forty-eight male 8-week-old rabbits with similar body weights (1872.11 ± 180.85 g) were randomly assigned to two treatments according to completely randomized design: (1) the control group received ad libitum access to feed (AL), and (2) the treatment received 80% of the feed consumed by the control (FR). The results showed that FR did not differ (p > 0.05) for average daily weight gain or feed conversion ratio between the two groups. FR treatment led to a significant increase (p < 0.05) in acid detergent fibre apparent faecal digestibility, nitrogen digestibility and retention, and gross energy digestibility and retention. The FR treatment showed significantly (p < 0.05) lower blood triglycerides, creatinine, high-density lipoprotein cholesterol, malondialdehyde, and hydroxyl free radicals but significantly (p < 0.05) greater total antioxidant capacity and superoxide dismutase. The FR group presented greater (p < 0.05) Firmicutes and Ruminococcus abundances but a lower (p < 0.05) Akkermansiaceae abundance in the caecal content. Moreover, 222 differentiated metabolites were identified, and beta-alanine metabolism was the top enriched pathway. Collectively, FR can improve nutrient utilisation, lipid metabolism, antioxidant activity, caecum microbiota, and metabolites in rabbits.PMID:40150371 | DOI:10.3390/ani15060842

Animals (Basel). 2025 Mar 13;15(6):816. doi: 10.3390/ani15060816.ABSTRACTReproductive efficiency is crucial for dairy farm productivity, but achieving consistent fertility remains challenging. TAI improves pregnancy rates by synchronizing ovulation and enabling precision breeding. Despite the advancements in hormone synchronization protocols, outcomes vary due to genetic, physiological, and metabolic differences among cows. This review examines current TAI protocols, including gonadotropin-releasing hormone (GnRH)-based and estradiol/progesterone (P4)-based synchronization methods, emphasizing their effectiveness and practical limitations. We also examined how to integrate emerging omics technologies, such as genomics, transcriptomics, proteomics, and metabolomics, into TAI protocols, marking a significant shift in reproductive management. These tools unveil molecular biomarkers that enable the precise tailoring of TAI protocols to the genetic, metabolic, and physiological profiles of individual animals, addressing challenges in variable fertility responses. Key factors influencing TAI success, such as animal health, environment, and insemination timing, are explored. This review identifies gaps in the existing literature, such as the integrated omics methodologies and data integration across platforms, and proposes a framework for future research to refine TAI protocols to address genetic variability and apply omics technologies to identify validated biomarkers for early pregnancy detection, which will significantly enhance the practical impact of TAI. Future directions highlight the need for interdisciplinary approaches combining molecular insights with robust on-farm applications to improve fertility outcomes and reduce reliance on blanket synchronization methods. By combining traditional synchronization methods with cutting-edge molecular tools, TAI offers promising opportunities for improving reproductive efficiency and sustainability in dairy farming.PMID:40150345 | DOI:10.3390/ani15060816

Biomolecules. 2025 Mar 20;15(3):443. doi: 10.3390/biom15030443.ABSTRACT(1) Background: The follicular fluid (FF) comprises a large portion of ovarian follicles, and serves as both a communication and growth medium for oocytes, and thus should be representative of the metabolomic status of the follicle. This review aims to explore FF biomarkers as well as their effects on fertilization, oocyte, and embryo development, and later on implantation and maintenance of pregnancy. (2) Methods: This review was registered in the PROSPERO database with the ID: CRD42025633101. We parsed PubMed, Scopus, and Google Scholar for research on the effects of different FF biomarkers on IVF/ICSI outcomes in normo-ovulatory women. Included studies were assessed for risk of bias using the NOS scale. Data were extracted and tabulated by two independent researchers. (3) Results: 22 included articles, with a sample size range of 31 to 414 and a median of 60 participants, contained 61 biomarkers, including proteins, growth factors, steroid and polypeptide hormones, inflammation and oxidative stress markers, amino acids, vitamins, lipids of different types, and miRNAs. Most of the biomarkers studied had significant effects on IVF/ICSI outcomes, and seem to have roles in various cellular pathways responsible for oocyte and embryo growth, implantation, placental formation, and maintenance of pregnancy. The FF metabolome also seems to be interconnected, with its various components influencing the levels and activities of each other through feedback loops. (4) Conclusions: FF biomarkers can be utilized for diagnostic and therapeutic purposes in IVF; however, further studies are required for choosing the most promising ones due to heterogeneity of results. Widespread adoption of LC-MS and miRNA microarrays can help quantify a representative FF metabolome, and we see great potential for in vitro supplementation (IVS) of some FF biomarkers in improving IVF/ICSI outcomes.PMID:40149979 | DOI:10.3390/biom15030443

Biomolecules. 2025 Mar 6;15(3):385. doi: 10.3390/biom15030385.ABSTRACTStaphylea pinnata L., (S. pinnata), has long been recognized in Europe as both a wild food source and a traditional medicinal. This study aimed to characterize the metabolomic profile of the leaf extract of S. pinnata and assess its cytotoxic, genotoxic, and antigenotoxic effects in vitro for the first time. The methanolic extract of the leaves was analyzed using Ultra-Performance Liquid Chromatography-High-Resolution Mass Spectrometry (UPLC-HRMS). To evaluate its cytotoxic, genotoxic, and antigenotoxic properties, the cytokinesis block micronucleus assay was performed on Chinese hamster ovarian K1 cells. The analysis revealed a wide variety of metabolites in the extract, with B-type procyanidins and prodelphinidins being the most abundant. The genotoxicity of the extract varied depending on its concentration; at the lowest concentration (75 μg/mL), it showed no genotoxic effects and exhibited antigenotoxic properties by reducing the frequency of micronuclei induced by mitomycin C. However, at the highest concentration (300 μg/mL), the extract demonstrated genotoxic effects. In conclusion, the S. pinnata extract displayed both genotoxic and antigenotoxic properties, which may be attributed to its phytochemical composition. These findings highlight the complex nature of the plant's bioactive compounds, suggesting potential therapeutic applications with careful consideration of dosage. Additional research is necessary to understand the mechanisms underlying these properties.PMID:40149921 | DOI:10.3390/biom15030385

Biomolecules. 2025 Mar 5;15(3):377. doi: 10.3390/biom15030377.ABSTRACTCardiovascular diseases (CVDs) remain a leading cause of global morbidity and mortality. Metabolomics allows for the identification of important biomarkers for CVDs, essential for early detection and risk assessment. This cross-sectional study aimed to identify novel metabolic biomarkers associated with CVDs using non-targeted metabolomics. We compared the metabolic profiles of 112 patients with confirmed CVDs diagnosis and 112 gender- and age-matched healthy controls from the Qatar Biobank database. Orthogonal partial least square discriminate analysis and linear models were used to analyze differences in the level of metabolites between the two groups. We report here a significant association between the indoleacetylglutamine pathway and cardiovascular diseases, expanding the repertoire of gut microbiota metabolites linked to CVDs. Our findings suggest that alterations in gut microbiota metabolism, potentially resulting in increased production of indoleacetate, indoleacetylglutamine, and related compounds at the expense of the cardioprotective indolepropionate, may contribute to this association. Our findings may pave the way for novel approaches in CVD risk assessment and potential therapeutic interventions targeting the gut-heart axis.PMID:40149912 | DOI:10.3390/biom15030377