Search Results (941)

Background: The integration of multi-omics data, such as genomics and transcriptomics, into artificial intelligence models has advanced precision medicine. However, their clinical applicability remains limited due to model complexity. We integrated DNA mutation, RNA expression, and A>I(G) RNA editing data to develop a predictive model for drug response in breast cancer. Methods: We analyzed 104 patients from the Breast Cancer Genome-Guided Therapy Study (ClinicalTrials.gov: NCT02022202). Clinical variables, gene expression, tumor and germline DNA variants, and RNA editing features were integrated into machine learning models to predict therapy response. Generalized linear models (GLM), random forest (RF), and support vector machines (SVM) were trained and evaluated across multiple random 70/30 train-test splits. Feature selection was performed exclusively within the training set using LASSO regularization. Model performance was assessed using the F1-score on independent test sets. The additive effect of RNA editing was evaluated using paired comparisons across identical train/test splits. Results: We characterized the cohort using clinical, mutational, transcriptomic, and RNA editing profiles in 69 non-responders and 35 responders. Across repeated splits, adding RNA editing frequently maintained or modestly improved predictive performance, particularly in expression-based models, with paired analyses showing a statistically significant increase in F1-score. Conclusions: RNA editing represents a complementary molecular layer that can enhance multi-omic models for therapy response prediction in breast cancer, supporting further investigation of epitranscriptomic features in precision oncology. Full article

Background: HER2-low breast cancer is a biologically heterogeneous subgroup in which hormone receptor (HR) expression critically shapes prognosis and treatment, but the underlying regulatory mechanisms remain unclear. MicroRNAs (miRNAs) are key post-transcriptional regulators of gene expression and may contribute to HR heterogeneity. This study aimed to identify deregulated miRNAs and associated gene networks distinguishing HER2-low/HR-positive from HER2-low/HR-negative tumors, elucidating the molecular mechanisms underlying this divergence. Methods: Differential expression analyses of miRNAs and genes were performed using Wilcoxon tests and DESeq2 (|log₂FC| > 1; FDR-adjusted p-value < 0.05). Survival analyses were conducted using Cox proportional hazards models to evaluate the individual miRNAs and miRNA signature. Functional enrichment analyses, including GO, KEGG and Reactome pathways, were performed. Correlation analysis and the miRNA target prediction were integrated to identify regulatory interactions. Results: Comparisons between HER2-low/HR-positive and HER2-low/HR-negative tumors identified 165 significantly deregulated miRNAs and 170 strongly deregulated genes. Intersection analysis highlighted miR-9-5p, miR-532-5p and miR-576-5p as specifically associated with HR-negative status. Survival analyses showed non-significant trends for the overall survival and progression-free interval. Functional enrichment analysis revealed hormone-related pathways in HR-positive tumors and immune, inflammatory and proliferative pathways in HR-negative tumors. Integrative correlation and target prediction analyses identified two miRNA–mRNA regulatory axes, miR-576-5p/TGFBI and miR-9-5p/POU2F2. Conclusions: Our study demonstrated that HER2-low breast cancer exhibits distinct miRNA and gene expression profiles, which highlight different transcriptomic profiles according to HR status for the first time. Specific miRNA–gene networks may drive transcriptional heterogeneity, serving as potential biomarkers for stratification and as therapeutic targets. These findings provide insight into the molecular basis of HER2-low tumor diversity and support future development of HR-directed therapeutic strategies. Full article

Gibberellins (GAs) play a crucial regulatory role in the growth and development of cotton (Gossypium hirsutum L.). Through bioinformatics analyses, we identified a total of 39 GA2ox genes (encoding gibberellin 2-oxidases) in the cotton genome, designated GhGA2ox1 to GhGA2ox39. Based on phylogenetic analysis, these genes were classified into five groups. We further examined their gene structures, conserved motifs, and chromosomal distributions, revealing that members within the same group shared similar structural and motif organizations. Collinearity and cis-element analyses provided important insights into the evolutionary history and regulatory potential of the GA2ox gene family in cotton. Notably, using nucleotide diversity (π) and population differentiation (F_ST) analyses across the entire family, we screened and identified nine candidate genes that underwent strong artificial selection during cotton domestication and improvement. Further haplotype-phenotype association analysis identified GH_D09G0919 (GhGA2ox31) as a key regulator of Plant Height (PH). To validate their regulatory roles, we analyzed the genotype distribution in accessions with extreme phenotypes. The results revealed divergent selection histories for these two loci: the favorable allele of GH_D01G0720 (GhGA2ox23) was already fixed in the tested population, whereas GH_D09G0919 maintained significant natural variation. Specifically, the Hap2 allele of GH_D09G0919 was significantly enriched in the shortest accessions compared to the tallest ones. Importantly, quantitative real-time polymerase chain reaction (qRT-PCR) analysis confirmed that the Hap2 allele drives significantly higher gene expression in leaves, suggesting that enhanced GA catabolism underlies the compact phenotype. Additionally, transcriptomic profiling revealed the tissue-specific expression patterns of candidate genes, implying their functional roles in development. Furthermore, functional validation using the Arabidopsis mutant of the homologous gene (AtGA2ox8) confirmed its conserved role in regulating plant height, as the mutant exhibited a distinct short-stature phenotype. These results uncover valuable genetic resources for molecular breeding to shape compact cotton architecture. Collectively, this study aims to analyze the evolutionary patterns of the cotton GA2ox gene family and to identify key genes that regulate plant height under artificial selection, providing theoretical support for molecular breeding of compact plant types. Full article

Loss of ovarian hormones following menopause or ovariectomy is associated with increased anxiety, cognitive impairment, and dysregulation of hypothalamic neuroendocrine pathways. MicroRNAs (miRNAs) and tRNA-derived fragments (tRFs) are emerging classes of small non-coding RNAs that act as post-transcriptional regulators of stress, inflammation, and synaptic function; however, their coordinated involvement in estradiol-mediated hypothalamic regulation remains poorly understood. In this study, adult female mice were assigned to control, estradiol-treated, ovariectomized (OVX), or OVX plus estradiol groups. Anxiety- and cognition-related behaviors were assessed using the open field, Y-maze, and elevated plus maze tests. Circulating estradiol levels and hypothalamic gonadotropin-releasing hormone (GnRH) expression were quantified by ELISA. Hypothalamic mRNA, miRNA, and tRF expression profiles were analyzed by RNA sequencing, followed by differential expression analysis, functional enrichment, integrative network construction, and quantitative real-time PCR validation. Ovariectomy induced anxiety-like behaviors, impaired working memory, reduced estradiol levels, and increased hypothalamic GnRH expression, all of which were reversed by estradiol treatment. Transcriptomic analysis identified 376 differentially expressed miRNAs, 182 differentially expressed tRFs, and 439 differentially expressed mRNAs, enriched in pathways related to stress responses, neuroendocrine regulation, synaptic signaling, metabolic homeostasis, and neuroinflammation. Integrated miRNA–mRNA and tRF–mRNA network analyses revealed several estradiol-responsive miRNAs (including miR-200a-5p, miR-182/183-5p, miR-381-3p, miR-148a-3p, and miR-10 family members) predicting key hub genes such as Gcg, Wnt4, Prkacb, Sgk1, Fpr2, and Aldoa, and key tRFs like tRFdb-1003, tRFdb-1013, tRFdb-1026, tRFdb-3001a and tRFdb-5020a, targeting hub genes such as Wnt4, Prkacb, Sh3rf2, Hpse, Cxcr2 and Zbtb16 respectively. Collectively, these findings demonstrate that estradiol ameliorates OVX-induced behavioral and endocrine dysfunction by reorganizing hypothalamic miRNA- and tRF-mediated regulatory networks involved in stress adaptation, synaptic homeostasis, and neuroimmune signaling. Full article

Lymphovascular invasion is an adverse pathologic feature in prostate cancer, but its independent molecular drivers remain unclear due to strong confounding by tumor grade and stage. We performed a confounder-adjusted transcriptomic analysis of 403 TCGA-PRAD samples. Differential expression was adjusted for Gleason score and pathological T stage. A transcriptional profile associated with LVI was derived and tested in multivariable logistic and Cox proportional hazards models for biochemical recurrence-free survival, with bootstrap internal validation. After multivariable adjustment, 129 genes were independently associated with LVI. This gene set was overwhelmingly enriched for interferon-alpha/beta signaling and antiviral response pathways. A continuous composite score derived from this profile predicted a reduced risk of biochemical recurrence independently of standard clinicopathological factors (adjusted HR per unit = 0.911, 95% CI: 0.835–0.993, p = 0.033). Multi-omics integration revealed subtle promoter hypomethylation and strong correlations between methylation and expression for key interferon genes, supporting transcriptional regulation. We identify a robust, interferon-response transcriptional profile that specifically defines LVI in prostate cancer after accounting for major clinical confounders. This transcriptional signature provides independent prognostic information, refines the biological understanding of LVI, and presents a novel targetable pathway for further investigation. Full article

Polyhydroxybutyrate (PHB) is a biodegradable polyester considered a sustainable alternative to petroleum-based plastics. However, its biodegradation in the presence of plasticizers remains poorly defined. This study investigated the impact of phthalate ester- and glycol-based plasticizers on PHB degradation by Ralstonia sp. C1. Real Time -Polymerase Chain Reaction(RT-PCR) analysis showed that expression of the PHB depolymerase gene phaZa1 remained unchanged in all additive-treated cultures, indicating no transcriptional interference. Liquid-medium degradation assays quantified by HPLC revealed rapid PHB utilization, with more than 50% degraded within 24 h and over 98% degraded within 48 h, with no significant differences relative to the control. Growth-inhibition assays further demonstrated that none of the plasticizers impaired bacterial viability, as OD₆₀₀ profiles were comparable to untreated cultures. Soil degradation experiments confirmed that PHB films containing additives decomposed at rates similar to additive-free films, reaching approximately 80% degradation within 10 weeks. Overall, the tested plasticizers did not affect enzyme expression, microbial activity, or PHB biodegradation, highlighting the suitability of plasticized PHB materials for environmentally sustainable applications and supporting their scalable use as biodegradable alternatives to conventional plastics. Full article

PET biodegradation remains limited due to its intrinsic properties—high crystallinity, hydrophobicity, and strong chemical stability. These characteristics lead to extremely slow degradation rates and contribute to PET’s persistence in the environment. Understanding how microorganisms respond at the molecular level when exposed to such a recalcitrant polymer is therefore essential. Living organisms express genes in response to their needs during development. When microbes are under critical conditions, such as when contaminants are present, they express genes encoding specific enzymes that attack the pollutant. In this study, a fungus isolated from the infected fruit of the plant Randia monantha was identified as Aspergillus terreus. It was tested for polyethylene terephthalate (PET) degradation, and the fungus Aspergillus nidulans was evaluated due to its previously reported recombinant cutinases for PET degradation. A microplastic polyethylene terephthalate (PET-MP) particle size of <355 μm for degradation was established, and a PET weight loss of 1.62% for A. nidulans and 1.01% for A. terreus was found. Additionally, the degradation of PET was confirmed by FTIR and SEM. This study also compares the transcriptomic profiles of Aspergillus nidulans and Aspergillus terreus during cultivation with PET-MP residues, which serve as a replacement for the carbon source. We present the first evidence of chitinase overexpression during direct exposure of PET to Aspergillus fungi. Interestingly, chitinase expression was detected in the crude extracts of A. nidulans and A. terreus during culture in the presence of PET residues, which replaced the carbon source. The chitinase produced by each fungus has a similar molecular weight of approximately 44 kDa. Chitinase activity was monitored over a 14-day cultivation period; from day 2, chitinase activity was detected in both cultures and continued to increase until day 14, when the highest values reported in this work were 24.88 ± 4.17 U mg⁻¹ and 10.41 ± 0.47 U mg⁻¹ for A. nidulans and A. terreus, respectively. Finally, we proposed a pathway for PET degradation by Aspergillus fungi that involves mycelial adherence and the secretion of hydrophobins, followed by the production of intermediates and monomers via esterase hydrolysis, and ultimately, the entry of monomers to the ethylene glycol (EG) and terephthalic acid (TPA) pathways, further suggesting these Aspergillus as candidates to produce valuable compounds under these conditions, such as muconic acid, gallic acid, and vanillic acid. Full article

Background/Objectives: Extranodal NK/T-cell lymphoma, nasal type (ENKTCL-NT), is a rare and extremely aggressive subtype of non-Hodgkin lymphoma that most frequently involves the nasal cavity and upper aerodigestive tract. Primary isolated oral manifestation is exceptionally uncommon and may mimic odontogenic or infectious diseases, delaying diagnosis. We report a case of ENKTCL-NT presenting initially as a destructive oral lesion without sinonasal involvement at diagnosis. Methods: A 32-year-old man with progressive palatal ulceration underwent clinical and imaging assessment (panoramic radiography and staging ^18F-FDG PET–CT) and repeated biopsies. Diagnosis was established using histopathology (H&E), immunohistochemistry (T-cell markers and cytotoxic profile), EBV detection by EBER in situ hybridization, and T-cell receptor gamma (TCRG) gene rearrangement analysis. Results: The lesion presented as a hemorrhagic, ulcerative palatal destruction covered by pseudomembranous exudate and was complicated by fungal infection, periostitis, and severe dental inflammatory foci, contributing to diagnostic delay. Histopathological examination revealed extensive necrosis with a dense atypical lymphoid infiltrate; angiocentric and angiodestructive growth was identified in one biopsy specimen. Tumor cells expressed T-cell markers (CD2, CD3, CD5, CD7; heterogeneous) and cytotoxic markers (TIA-1) and showed CD30 and CD56 positivity, with EBV positivity confirmed by EBER in situ hybridization. Molecular analysis demonstrated monoclonal TCRG rearrangement, and Ki-67 indicated high proliferative activity. Initial PET–CT demonstrated an intensely FDG-avid, locally invasive lesion without distant organ involvement. The patient was treated with L-asparaginase-based SMILE chemotherapy followed by radiotherapy (50 Gy), achieving marked initial clinical improvement and partial metabolic response; however, systemic relapse subsequently occurred with refractory disease despite salvage therapy and immunotherapy. Conclusions: This case highlights the substantial diagnostic challenge posed by isolated oral extranodal NK/T-cell lymphoma, nasal type, which may closely mimic benign inflammatory or infectious conditions and lead to significant diagnostic delay. Persistent, progressive, or therapy-resistant oral ulcerations should prompt early consideration of hematologic malignancy. Timely biopsy with comprehensive immunophenotyping, EBV testing, and close multidisciplinary collaboration are essential for accurate diagnosis and may contribute to earlier diagnosis and improved patient outcomes in these rare and atypical presentations. Full article

Background/Objectives: The precise classification of non-small-cell lung cancer (NSCLC) into lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) has important role in treatment decisions and in prognosis. Proper subtyping ensures that patients receive the most appropriate therapeutic strategies and allows clinicians to make informed evaluations regarding disease outcomes. This study presents a deep neural-network-based classification approach utilizing genome-wide DNA methylation profiles from the Illumina HumanMethylation450 BeadChip platform. Methods: A total of 5000 of the most discriminative CpG probes are identified through variance-based feature selection in the presented methodology, which are then classified through a five-layer deep neural network with batch normalization and dropout regularization. Training and validation were performed using data from The Cancer Genome Atlas (TCGA), with external validation conducted on two independent Gene Expression Omnibus (GEO) datasets: GSE39279 and GSE56044. Results: The model achieved 96.92% accuracy with an area under the receiver-operating characteristic curve (AUC-ROC) of 0.9981 on the TCGA test set. Robust generalization was obtained in cross-dataset validation experiments, with the GEO-trained model achieving 88.92% accuracy and 0.9724 AUC-ROC when validated on TCGA data. The most influential CpG biomarkers contributing to classification decisions are analysed using SHAP (Shapley Additive Explanations). Conclusions: These findings demonstrate the potential of DNA methylation-based deep learning approaches for reliable NSCLC subtype classification with clinical applicability. Full article

Ischemic stroke triggers hypoxia, inflammation, and oxidative stress. Local oxygen delivery may prevent secondary injuries. Herein, we implanted a catalase-incorporated thiolated gelatin-based oxygen-releasing hydrogel sheet in a rat model of photothrombosis to evaluate early infarct attenuation and feasibility. Male Sprague–Dawley rats were allocated to four groups (n = 6/group): control at 24 h (G1), with hydrogel sheet at 24 h (G2), control at 72 h (G3), and with hydrogel sheet at 72 h (G4). Focal ischemia was induced with Rose Bengal and targeted illumination through a 6.0-mm cranial defect. A hydrogel sheet was applied to the cortex after surgery. The infarct burden was assessed by 2,3,5-triphenyltetrazolium chloride (TTC) staining and magnetic resonance imaging (MRI), while mRNA expression levels of tumor necrosis factor-α (TNF-α), brain-derived neurotrophic factor (BDNF), and superoxide dismutase (SOD) were measured by quantitative reverse transcription PCR. Body weight was monitored as a safety measure. At 24 h, TTC showed a significant infarct reduction in G2 compared with G1. At 72 h, infarct measures did not differ significantly between G4 and G3. MRI and gene expression analyses did not show statistically significant between-group differences and are presented as exploratory outcomes. Weight and perioperative status were similar across groups, indicating short-term tolerability. The hydrogel sheet was associated with reduced TTC-defined infarct burden at 24 h in this model; confirmatory studies will require larger, powered cohorts, longer follow-up with functional testing, and in vivo oxygen release profiling to optimize dose, placement, and exposure time. Full article

Background: Breast cancers are heterogeneous in nature, including many molecular subtypes, each displaying varying characteristics in clinical outcomes as well as in responses to treatments. Subtyping requires absolute precision for the application of precision medicine; however, this is not an easy task, given the dimensionality as well as noise in miRNA expression profiles. Even though miRNAs display potential as a biological marker for subtyping breast cancers, feature selection and optimizing learning algorithms would help harness their potential as a diagnostic tool. Methods: We propose the Adaptive Hill Climbing Artificial Lemming Algorithm (AHALA), a hybrid optimization framework that integrates the global search capability of the Artificial Lemming Algorithm with an adaptive hill-climbing local search strategy. Low-variance filtering and differential gene expression analysis were first applied to reduce dimensionality and enhance biological relevance. AHALA was then used to optimize deep neural network hyperparameters for miRNA-based multi-class breast cancer subtype classification. The method was validated using TCGA breast cancer miRNA expression data and benchmarked against state-of-the-art optimization algorithms using the CEC2021 test suite. Results: AHALA had a high classification performance measure for each type of breast cancer with a mean accuracy of 95.74%, precision of 95.98%, recall of 95.74%, F1 measure of 95.74%, and AUC value of 0.9682. The new algorithm had superior convergence and significance compared with other optimization algorithms. Feature selection revealed miRNAs that belong to each subtype, such as hsa-miR-190b, hsa-miR-429, hsa-miR-505-3p, hsa-miR-3614-5p, and hsa-miR-935. Conclusions: The AHALA framework offers a potent and efficient method of performing miRNA-based subtyping of breast cancer that integrates global exploration and local search to its advantage. Its high level of classification, stability, and ability to identify biologically important biomarkers mark this method as promising. Full article

Pancreatic cancer is a highly intractable malignancy that necessitates personalized treatment strategies. Conventional patient-derived models, such as three-dimensional organoids, are often limited by intellectual property constraints and high costs. In this study, we developed an affordable adherent culture system for patient-derived pancreatic cancer cells using a proprietary medium and laminin-coated dishes. Primary cultures were successfully established from 28 patients with pancreatic ductal adenocarcinoma, exceeding a 90% success rate. Validation of eight samples confirmed maintenance of epithelial cell adhesion molecule expression and preservation of oncogenic KRAS mutations. Transcriptomic profiling revealed consistent upregulation of a six-gene signature (FAP, IGFBP5, PRRX1, SPARC, WNT5A, and ADAMTS12), which is associated with malignancy. In vitro drug sensitivity assays revealed interpatient heterogeneity with preliminary clinical associations. In conclusion, this simplified platform provides high-purity cancer cells and serves as a functional precision medicine tool. Beyond conventional chemotherapy, this platform has the potential to support applications ranging from biomarker validation and exploratory preclinical testing of novel therapeutics, including immune checkpoint inhibitors and antibody–drug conjugates. This optimization can lead to personalized therapeutic strategies for pancreatic cancer. Full article

The increasing complexity of disease mechanisms challenges accurate diagnosis, prevention, and early risk stratification. Beyond genetic predisposition, epigenetic regulation—particularly DNA methylation—represents a dynamic molecular interface linking environmental exposures, metabolic imbalance, inflammation, and disease development. DNA methylation is the most extensively studied epigenetic mechanism and plays a central role in controlling gene expression across physiological and pathological conditions. In this review, we provide an integrated overview of DNA methylation biology and its involvement in inflammatory, metabolic, and oncological diseases, with a specific focus on pathways related to chronic inflammation and oxidative stress. We summarize evidence demonstrating how aberrant methylation patterns contribute to disease initiation and progression, highlighting recurrent epigenetic signatures affecting key regulatory genes. In parallel, we discuss current and emerging technologies for DNA methylation analysis, ranging from targeted methylation-specific assays to next-generation sequencing-based approaches, including nanopore adaptive sampling. Finally, we explore the translational potential of DNA methylation-based tests as predictive and preventive tools, emphasizing their ability to identify disease-associated molecular alterations before clinical onset. Overall, this evidence supports the integration of epigenetic profiling into future precision medicine strategies aimed at early risk assessment, prognosis refinement, and personalized prevention. Full article

Background/Objectives: Thymomas are the most common tumors of the anterior mediastinum. While early-stage disease often has a favorable prognosis, therapeutic options in advanced stages remain limited. Moreover, the molecular profile of thymomas is still poorly characterized. In the present study, we explored the presence of targetable mutations and programmed death-ligand 1 (PD-L1) expression in a cohort of surgically resected thymomas. Furthermore, we investigated the correlation between PD-L1 expression, histological subtype, and risk of recurrence in patients who underwent curative-intent thymectomy. Methods: Mutational profiling was performed using a DNA-based NGS Cancer Panel of 16 genes. PD-L1 expression was evaluated via Tumor Proportion Score (TPS), and thymomas with TPS ≥ 50% were identified as high expressors. The associations with histological subtype and disease-free survival (DFS) were analyzed using logistic regression, Cox proportional hazards models, and Kaplan–Meier survival curves. Results: In our study, 2/37 (5.4%) of tested neoplasms (type AB and B2 thymoma) reported as a PIK3CA mutation; no other targetable mutations were observed. Moreover, high PD-L1 expression (≥50%) was reported in (15/37) 40.5% of patients and was significantly associated with aggressive histological subtypes (B2 and B3) (p < 0.001). Logistic regression analysis showed that high PD-L1 expression was a significant predictor of aggressive histology (McFadden’s R² = 0.268, p < 0.001), with an odds ratio of 15.5 (95% CI: 2.9–83.4; p = 0.001). During follow-up, 5/37 (13.5%) of patients experienced disease recurrence; however, no significant difference in DFS was found between high and low PD-L1 expression groups. Conclusions: Our data confirm the presence of PIK3CA mutations in thymomas and encourage the exploration the potential role of molecular target therapy in this setting. Moreover, we underlined that high PD-L1 expression level is associated with more aggressive thymoma subtypes and may have a role as a prognostic biomarker. These findings support the need for further studies on the potential role of molecular and predictive pathology in thymic epithelial tumors. Full article

Background: Caloric restriction (CR) is a dietary intervention based on limiting calories relative to the basic energy needs of the organism, which changes the intensity of metabolism, causes changes in the functioning of the endocrine and sympathetic systems, and influences the expression of genes in muscle, heart, and brain cells. During the use of CR, there is a transition from carbohydrate supply to increased fat metabolism. Fatty acids are more or less susceptible to free radicals, depending on their molecular structure. Oxidation (peroxidation) contributes to the production of metabolites (including hydroxyeicosatetraenoic acid and hydroxyoctadecadienoic acid), some of which are involved in inflammation. Methods: The aim of this study was to evaluate the effects of long-term caloric restriction on the tissue levels of selected fatty acids and fatty acid-derived lipid mediators with pro-inflammatory or anti-inflammatory properties in skeletal muscle and intestinal tissues. The study was carried out on C57BL/6 mice. During the 8-month experiment, the mice in the study group were fed a 30% calorie restricted diet—according to the Every-Other-Day Diet concept. Analyses were performed on intestinal and muscle tissues collected from animals. Fatty acid derivatives were isolated using solid-phase extraction (C-18 columns) columns, and isolation of fatty acids was performed using a modified Folch method. The compounds were analyzed by liquid and gas chromatography. Results: CR induced detectable alterations in both fatty acid profiles and lipid mediator concentrations in a tissue-specific manner. However, most of these changes did not remain statistically significant after multiple testing correction. Conclusions: These findings suggest potential effects of long-term CR on lipid signaling pathways, although the current dataset lacks the statistical power required to draw definitive conclusions. This study highlights the need for further research using larger sample sizes and integrated multiomic approaches to elucidate the molecular mechanisms underlying lipidomic adaptations to prolonged caloric restriction. Full article