Search Results (2,118)

Background/Objectives: Conventional ketogenic diets, although effective for weight loss, often contain high total and saturated fat intake, which leads to increased low-density lipoprotein cholesterol (LDL-C). Thus, the Healthy Ketogenic Diet (HKD) was developed to address these concerns. It emphasizes calorie restriction, limiting net carbohydrate intake to 50 g per day, prioritizing unsaturated fats, and reducing saturated fat intake. However, adherence to the HKD remains a challenge in urban, time-constrained environments. Therefore, this pilot randomized controlled trial aimed to investigate the effects of Healthy Ketogenic Diet Ready-To-Eat (HKD-RTE) meals (provided for the first month only) versus HKD alone on weight loss and metabolic parameters among overweight adults. Methods: Multi-ethnic Asian adults (n = 50) with a body mass index (BMI) ≥ 27.5 kg/m² were randomized into the HKD-RTE group (n = 24) and the HKD group (n = 26). Both groups followed the HKD for six months, with the HKD-RTE group receiving HKD-RTE meals during the first month. Five in-person workshops and mobile health coaching through the Nutritionist Buddy Keto app helped to facilitate dietary adherence. The primary outcome was the change in body weight at 6 months. Linear regression was performed on the change from baseline for each continuous outcome, adjusting for demographics and relevant covariates. Logistic regression was performed on binary weight loss ≥5%, adjusting for demographics and relevant covariates. Results: In the HKD group, participants’ adherence to the 50 g net carbohydrate target was 15 days, while that in the HKD-RTE group was 19 days over a period of 30 days. Participants’ adherence to calorie targets was 21 days in the HKD group and 23 days in the HKD-RTE. The average compliance with the HKD-RTE meals provided in the HKD-RTE group was 55%. The HKD-RTE group experienced a greater percentage weight loss at 1 month (−4.8 ± 3.0% vs. −1.8 ± 6.2%), although this was not statistically significant. This trend continued up to 6 months, with the HKD-RTE group showing a greater percentage weight reduction (−8.6 ± 6.8% vs. −3.9 ± 8.6%; p = 0.092). At 6 months, the HKD-RTE group had a greater reduction in total cholesterol (−0.54 ± 0.76 mmol/L vs. −0.05 ± 0.56 mmol/L; p = 0.283) and LDL-C (−0.43 ± 0.67 mmol/L vs. −0.03 ± 0.52 mmol/L; p = 0.374) compared to the HKD group. Additionally, the HKD-RTE group exhibited greater reductions in systolic blood pressure (−8.3 ± 9.7 mmHg vs. −5.3 ± 11.0 mmHg), diastolic blood pressure (−7.7 ± 8.8 mmHg vs. −2.0 ± 7.0 mmHg), and HbA1c (−0.3 ± 0.5% vs. −0.1 ± 0.4%) than the HKD group (not statistically significant for any). Conclusions: Both HKD-RTE and HKD led to weight loss and improved metabolic profiles. The HKD-RTE group tended to show more favorable outcomes. Short-term HKD-RTE meal provision may enhance initial weight loss, with sustained long-term effects. Full article

Cardiovascular disease (CVD) remains the leading cause of mortality worldwide, with hypercholesterolemia identified as a major, but modifiable risk factor. This review serves as the second part of a comprehensive analysis of dyslipidemia management. The first installment laid the groundwork by detailing the key pathophysiological mechanisms of lipid metabolism, the development of atherosclerosis, major complications of hyperlipidemia, and the importance of cardiovascular risk assessment in therapeutic decision-making. It also examined non-pharmacological interventions and conventional therapies, with a detailed focus on statins and ezetimibe. Building upon that foundation, the present article focuses exclusively on emerging pharmacological therapies designed to overcome limitations of standard treatment. It explores the mechanisms, clinical applications, safety profiles, and pharmacogenetic aspects of novel agents such as proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors (alirocumab, evolocumab), small interfering RNA (siRNA) therapy (inclisiran), adenosine triphosphate–citrate lyase (ACL) inhibitor (bempedoic acid), microsomal triglyceride transfer protein (MTP) inhibitor (lomitapide), and angiopoietin-like protein 3 (ANGPTL3) inhibitor (evinacumab). These agents offer targeted strategies for patients with high residual cardiovascular risk, familial hypercholesterolemia (FH), or statin intolerance. By integrating the latest advances in precision medicine, this review underscores the expanding therapeutic landscape in dyslipidemia management and the evolving potential for individualized care. Full article

The effects of long-term adjustments in body weight on the lipid balance in patients with severe obesity are not well understood. This study aimed to evaluate a non-invasive lipidomic approach to identifying biomarkers that could help predict which patients may require additional therapies before and after weight loss. Using mass spectrometry, 275 lipid species were analysed in non-obese controls, patients with severe obesity, and patients one year after bariatric surgery. The results showed that severe obesity disrupts lipid pathways, contributing to lipotoxicity, inflammation, mitochondrial stress, and abnormal lipid metabolism. Although weight loss improved these disturbances, surgery did not fully normalise the lipid profiles of all patients. Outcomes varied depending on their baseline liver health and genetic differences. Persistent alterations in cholesterol handling, membrane composition, and mitochondrial function were observed in partial responders. Elevated levels of sterol lipids, glycerophospholipids, and sphingolipids emerged as markers of complete metabolic recovery, identifying candidates for targeted post-surgical interventions. These findings support the use of lipidomics to personalise obesity treatment and follow-up. Full article

Childhood obesity increases chronic disease risk, but no comprehensive synthesis has evaluated the impact of school-based combined nutrition education and physical activity interventions on cardiometabolic biomarkers in children aged 3 to 12 years. This systematic review was conducted in accordance with PRISMA guidelines and registered in PROSPERO (CRD420251085194). Five databases were systematically searched through June 2025. Twelve randomized controlled trials involving 18,231 children were included and assessed using the PEDro scale. Ten trials demonstrated significant improvements in at least one cardiometabolic biomarker. Blood pressure (8 studies) outcomes showed systolic reductions of 1.41–6.0 mmHg in six studies. Glucose metabolism (5 studies) improved in two studies with reductions of 0.20–0.22 mmol/L. Lipid profiles (7 studies) improved in three studies, including total cholesterol (−0.32 mmol/L). Insulin levels (5 studies) decreased significantly in two investigations. Anthropometric improvements included BMI and body fat. Physical activity increased by >45 min/week and dietary habits improved significantly. Programs with daily implementation (90-min sessions 4x/week), longer duration (≥12 months), family involvement (parent education), and curriculum integration (classroom lessons) showed superior effectiveness. Interventions targeting children with overweight/obesity demonstrated higher changes compared to the general population. However, methodological limitations included a lack of assessor blinding, absence of subject/therapist blinding, and inadequate retention rates. School-based interventions combining nutrition and physical activity can produce significant improvements in cardiometabolic biomarkers, supporting comprehensive, sustained multicomponent programs for early chronic disease prevention. Full article

Background: Charcot–Marie–Tooth (CMT) is a group of inherited diseases impairing the peripheral nervous system. CMT originates from genetic variants that affect proteins fundamental for the myelination of peripheral nerves and survival. Moreover, environmental and humoral factors can impact disease development and evolution. Currently, no therapy is available. Metabolomics is an emerging field of biomedical research that enables the development of novel biomarkers for neurodegenerative diseases by targeting metabolic pathways or metabolites. This study aimed to evaluate the metabolomics profile of CMT disease by comparing patients with healthy individuals. Methods: A total of 22 CMT patients (CMT) were included in this study and were demographically matched with 26 healthy individuals (C). Serum samples were analyzed through Nuclear Magnetic Resonance spectroscopy, and multivariate and univariate statistical analyses were subsequently applied. Results: A supervised model showed a clear separation (R²X = 0.3; R²Y = 0.7; Q² = 0.4; p-value = 0.0004) between the two classes of subjects, and nine metabolites were found to be significantly different (2-hydroxybutyrate, 3-hydroxybutyrate, 3-methyl-2-oxovalerate, choline, citrate, glutamate, isoleucine, lysine, and methyl succinate). The combined ROC curve showed an AUC of 0.94 (CI: 0.9–1). Additional altered metabolic pathways were also identified within the disease context. Conclusion: This study represents a promising starting point, demonstrating the efficacy of metabolomics in evaluating CMT patients and identifying novel potential disease biomarkers. Full article

Background: The candidate therapeutic peptide TnP demonstrates broad, system-level regulatory capacity, revealed through integrated network analysis from transcriptomic data in zebrafish. Our study primarily identifies TnP as a multifaceted modulator of drug metabolism, wound healing, proteolytic activity, and pigmentation pathways. Results: Transcriptomic profiling of TnP-treated larvae following tail fin amputation revealed 558 differentially expressed genes (DEGs), categorized into four functional networks: (1) drug-metabolizing enzymes (cyp3a65, cyp1a) and transporters (SLC/ABC families), where TnP alters xenobiotic processing through Phase I/II modulation; (2) cellular trafficking and immune regulation, with upregulated myosin genes (myhb/mylz3) enhancing wound repair and tlr5-cdc42 signaling fine-tuning inflammation; (3) proteolytic cascades (c6ast4, prss1) coupled to autophagy (ulk1a, atg2a) and metabolic rewiring (g6pca.1-tg axis); and (4) melanogenesis-circadian networks (pmela/dct-fbxl3l) linked to ubiquitin-mediated protein turnover. Key findings highlight TnP’s unique coordination of rapid (protease activation) and sustained (metabolic adaptation) responses, enabled by short network path lengths (1.6–2.1 edges). Hub genes, such as nr1i2 (pxr), ppara, and bcl6aa/b, mediate crosstalk between these systems, while potential risks—including muscle hypercontractility (myhb overexpression) or cardiovascular effects (ace2-ppp3ccb)—underscore the need for targeted delivery. The zebrafish model validated TnP-conserved mechanisms with human relevance, particularly in drug metabolism and tissue repair. TnP’s ability to synchronize extracellular matrix remodeling, immune resolution, and metabolic homeostasis supports its development for the treatment of fibrosis, metabolic disorders, and inflammatory conditions. Conclusions: Future work should focus on optimizing tissue-specific delivery and assessing genetic variability to advance clinical translation. This system-level analysis positions TnP as a model example for next-generation multi-pathway therapeutics. Full article

Cancer metabolic reprogramming plays a critical role in tumor progression and therapeutic resistance, underscoring the need for advanced analytical strategies. Metabolomics, leveraging mass spectrometry and nuclear magnetic resonance (NMR) spectroscopy, offers a comprehensive and functional readout of tumor biochemistry. By enabling both targeted metabolite quantification and untargeted profiling, metabolomics captures the dynamic metabolic alterations associated with cancer. The integration of metabolomics with machine learning (ML) approaches further enhances the interpretation of these complex, high-dimensional datasets, providing powerful insights into cancer biology from biomarker discovery to therapeutic targeting. This review systematically examines the transformative role of ML in cancer metabolomics. We discuss how various ML methodologies—including supervised algorithms (e.g., Support Vector Machine, Random Forest), unsupervised techniques (e.g., Principal Component Analysis, t-SNE), and deep learning frameworks—are advancing cancer research. Specifically, we highlight three major applications of ML–metabolomics integration: (1) cancer subtyping, exemplified by the use of Similarity Network Fusion (SNF) and LASSO regression to classify triple-negative breast cancer into subtypes with distinct survival outcomes; (2) biomarker discovery, where Random Forest and Partial Least Squares Discriminant Analysis (PLS-DA) models have achieved >90% accuracy in detecting breast and colorectal cancers through biofluid metabolomics; and (3) prognostic modeling, demonstrated by the identification of race-specific metabolic signatures in breast cancer and the prediction of clinical outcomes in lung and ovarian cancers. Beyond these areas, we explore applications across prostate, thyroid, and pancreatic cancers, where ML-driven metabolomics is contributing to earlier detection, improved risk stratification, and personalized treatment planning. We also address critical challenges, including issues of data quality (e.g., batch effects, missing values), model interpretability, and barriers to clinical translation. Emerging solutions, such as explainable artificial intelligence (XAI) approaches and standardized multi-omics integration pipelines, are discussed as pathways to overcome these hurdles. By synthesizing recent advances, this review illustrates how ML-enhanced metabolomics bridges the gap between fundamental cancer metabolism research and clinical application, offering new avenues for precision oncology through improved diagnosis, prognosis, and tailored therapeutic strategies. Full article

Mitochondria, pivotal organelles in cellular metabolism and energy production, have emerged as critical players in the pathogenesis of cancer. This review outlines the progress in mitochondrial profiling through mass spectrometry-based metabolomics and its applications in cancer research. We provide unprecedented insights into the mitochondrial metabolic rewiring that fuels tumorigenesis, metastasis, and therapeutic resistance. The purpose of this review is to provide a comprehensive guide for the implementation of mitochondrial metabolomics, integrating advanced methodologies—including isolation, detection, and data integration—with insights into cancer-specific metabolic rewiring. We first summarize current methodologies for mitochondrial sample collection and pretreatment. Furthermore, we then discuss the recent advancements in mass spectrometry-based methodologies that facilitate the detailed profiling of mitochondrial metabolites, unveiling significant metabolic reprogramming associated with tumorigenesis. We emphasize how recent technological advancements have addressed longstanding challenges in the field and explore the role of mitochondrial metabolism-driven cancer development and progression for novel drug discovery and translational research applications in cancer. Collectively, this review delineates emerging opportunities for therapeutic discovery and aims to establish a foundation for future investigations into the therapeutic modulation of mitochondrial pathways in cancer, thereby paving the way for innovative diagnostic and therapeutic approaches targeting mitochondrial pathways. Full article

Background: There is growing interest in the potential role of manganese (Mn) in the development of Alzheimer’s Disease and related dementias (ADRD). Methods: In this nested pilot study of a ferroalloy worker cohort, we investigated the impact of chronic occupational Mn exposure on cognitive function through β-amyloid (Aβ) deposition and multi-omics profiling. We evaluated six male Mn-exposed workers (median age 63, exposure duration 31 years) and five historical controls (median age: 60 years), all of whom had undergone brain PET scans. Exposed individuals showed significantly higher Aβ deposition in exposed individuals (p < 0.05). The average annual cumulative respirable Mn was 329.23 ± 516.39 µg/m³ (geometric mean 118.59), and plasma Mn levels were significantly elevated in the exposed group (0.704 ± 0.2 ng/mL) compared to controls (0.397 ± 0.18 in controls). Results: LC-MS/MS-based pathway analyses revealed disruptions in olfactory signaling, mitochondrial fatty acid β-oxidation, biogenic amine synthesis, transmembrane transport, and choline metabolism. Simoa analysis showed notable alterations in ADRD-related plasma biomarkers. Protein microarray revealed significant differences (p < 0.05) in antibodies targeting neuronal and autoimmune proteins, including Aβ (25–35), GFAP, serotonin, NOVA1, and Siglec-1/CD169. Conclusion: These findings suggest Mn exposure is associated with neurodegenerative biomarker alterations and disrupted biological pathways relevant to cognitive decline. Full article

Neurodegenerative diseases, including Alzheimer’s disease, Parkinson’s disease, and amyotrophic lateral sclerosis, are characterized by progressive neuronal loss and share key pathological features such as oxidative stress, mitochondrial dysfunction, and chronic neuroinflammation. Recent research has highlighted the potential of ketogenic metabolism, particularly the use of ketone bodies like β-hydroxybutyrate, as a therapeutic approach targeting these shared mechanisms. This review provides a comprehensive synthesis of current knowledge on the neuroprotective effects of ketogenic interventions, including both dietary strategies and exogenous ketone supplementation. We discuss how ketone bodies improve mitochondrial function, reduce reactive oxygen species, modulate inflammatory pathways, and influence neurotransmission and synaptic plasticity. Additionally, we examine experimental and clinical evidence supporting the application of ketogenic therapies in neurodegenerative diseases, highlighting disease-specific findings, benefits, and limitations. While preclinical data are robust and suggest meaningful therapeutic potential, clinical studies remain limited and heterogeneous, with challenges related to adherence, safety, and patient selection. The review also addresses the translational relevance of ketogenic strategies, considering their feasibility, combination with other therapies, and the need for personalized approaches based on genetic and metabolic profiles. By critically evaluating existing data, this article aims to clarify the mechanisms through which ketogenic metabolism may exert neuroprotective effects and to outline future directions for research and clinical application in the context of neurodegenerative disorders. Full article

Background: Oxidative stress is a critical factor contributing to male infertility, impairing spermatogonial stem cells (SSCs) and disrupting normal spermatogenesis. This study aimed to isolate and characterize human SSCs and to investigate oxidative stress-related gene expression, protein interaction networks, and developmental trajectories involved in SSC function. Methods: SSCs were enriched from human orchiectomy samples using CD49f-based magnetic-activated cell sorting (MACS) and laminin-binding matrix selection. Enriched cultures were assessed through morphological criteria and immunocytochemistry using VASA and SSEA4. Transcriptomic profiling was performed using microarray and single-cell RNA sequencing (scRNA-seq) to identify oxidative stress-related genes. Bioinformatic analyses included STRING-based protein–protein interaction (PPI) networks, FunRich enrichment, weighted gene co-expression network analysis (WGCNA), and predictive modeling using machine learning algorithms. Results: The enriched SSC populations displayed characteristic morphology, positive germline marker expression, and minimal fibroblast contamination. Microarray analysis revealed six significantly upregulated oxidative stress-related genes in SSCs—including CYB5R3 and NDUFA10—and three downregulated genes, such as TXN and SQLE, compared to fibroblasts. PPI and functional enrichment analyses highlighted tightly clustered gene networks involved in mitochondrial function, redox balance, and spermatogenesis. scRNA-seq data further confirmed stage-specific expression of antioxidant genes during spermatogenic differentiation, particularly in late germ cell stages. Among the machine learning models tested, logistic regression demonstrated the highest predictive accuracy for antioxidant gene expression, with an area under the curve (AUC) of 0.741. Protein oxidation was implicated as a major mechanism of oxidative damage, affecting sperm motility, metabolism, and acrosome integrity. Conclusion: This study identifies key oxidative stress-related genes and pathways in human SSCs that may regulate spermatogenesis and impact sperm function. These findings offer potential targets for future functional validation and therapeutic interventions, including antioxidant-based strategies to improve male fertility outcomes. Full article

The Pelargonium genus, encompassing over 280 species, remains markedly underexplored despite extensive traditional use for respiratory, gastrointestinal, and dermatological disorders. This review of aqueous, alcoholic, and hydroalcoholic extracts reveals critical research gaps: only 10 species have undergone chemical characterization, while 17 have been evaluated for biological activities. Phytochemical analysis identified 252 unique molecules across all studies, with flavonoids emerging as the predominant class (n = 108). Glycosylated derivatives demonstrated superior bioactivity profiles compared to non-glycosylated analogs. Phenolic acids (n = 43) and coumarins (n = 31) represented additional major classes. Experimental studies primarily documented antioxidant, antibacterial, and anti-inflammatory effects, with emerging evidence for antidiabetic, anticancer, and hepatoprotective activities. However, methodological heterogeneity across studies limits comparative analysis and comprehensive understanding. In silico target prediction analysis was performed on 197 high-confidence molecular structures. Glycosylated flavonols, anthocyanidins, flavones, and coumarins showed strong predicted interactions with key inflammatory targets (ALOX15, ALOX5, PTGER4, and NOS2) and metabolic regulators (GSK3A and PI4KB), providing mechanistic support for observed therapeutic effects and suggesting potential applications in chronic inflammatory and metabolic diseases. These findings underscore the substantial therapeutic potential of underexplored Pelargonium species and advocate for systematic research employing untargeted metabolomics, standardized bioassays, and compound-specific mechanistic validation to fully unlock the pharmacological potential of this diverse genus. Full article

Huanglongbing (HLB), caused by Candidatus Liberibacter asiaticus (CLas), is the most devastating disease threatening global citrus production. Although no commercial citrus varieties exhibit complete HLB resistance, genotype-specific tolerance variations remain underexplored. This study conducted a comparative transcriptomic profiling of six commercially citrus cultivars in South China, four susceptible cultivars (C. reticulata cv. Tankan, Gongkan, Shatangju, and C. sinensis Osbeck cv. Newhall), and two tolerant cultivars (C. limon cv. Eureka; C. maxima cv Guanxi Yu) to dissect molecular mechanisms underlying HLB responses. Comparative transcriptomic analyses revealed extensive transcriptional reprogramming, with tolerant cultivars exhibiting fewer differentially expressed genes (DEGs) and targeted defense activation compared to susceptible genotypes. The key findings highlighted the genotype-specific regulation of starch metabolism, where β-amylase 3 (BAM3) was uniquely upregulated in tolerant varieties, potentially mitigating starch accumulation. Immune signaling diverged significantly: tolerant cultivars activated pattern-triggered immunity (PTI) via receptor-like kinases (FLS2) and suppressed ROS-associated RBOH genes, while susceptible genotypes showed the hyperactivation of ethylene signaling and oxidative stress pathways. Cell wall remodeling in susceptible cultivars involved upregulated xyloglucan endotransglucosylases (XTH), contrasting with pectin methylesterase induction in tolerant Eureka lemon for structural reinforcement. Phytohormonal dynamics revealed SA-mediated defense and NPR3/4 suppression in Eureka lemon, whereas susceptible cultivars prioritized ethylene/JA pathways. These findings delineate genotype-specific strategies in citrus–CLas interactions, identifying BAM3, FLS2, and cell wall modifiers as critical targets for breeding HLB-resistant cultivars through molecular-assisted selection. This study provides a foundational framework for understanding host–pathogen dynamics and advancing citrus immunity engineering. Full article

Background: Melanoma metastasis, driven by tumor microenvironment (TME)-mediated crosstalk facilitated by extracellular vesicles (EVs), remains a major therapeutic challenge. A critical barrier to clinical translation is the overlap in protein cargo between tumor-derived and healthy cell EVs. Objective: To address this, we developed Scaffold-free Functional Deconvolution (SFD), a novel computational approach that leverages a comprehensive healthy cell EV protein database to deconvolute non-oncogenic background signals. Methods: Beginning with 1915 proteins (identified by MS/MS analysis on an Orbitrap Fusion Lumos Mass Spectrometer using the IonStar workflow) from melanoma EVs isolated using REIUS, SFD applies four sequential filters: exclusion of normal melanocyte EV proteins, prioritization of metastasis-linked entries (HCMDB), refinement via melanocyte-specific databases, and validation against TCGA survival data. Results: This workflow identified 21 high-confidence targets implicated in metabolic-associated acidification, immune modulation, and oncogenesis, and were analyzed for reduced disease-free and overall survival. SFD’s versatility was further demonstrated by surfaceome profiling, confirming enrichment of H7-B3 (CD276), ICAM1, and MIC-1 (GDF-15) in metastatic melanoma EV via Western blot and flow cytometry. Meta-analysis using Vesiclepedia and STRING categorized these targets into metabolic, immune, and oncogenic drivers, revealing a dense interaction network. Conclusions: Our results highlight SFD as a powerful tool for identifying clinically relevant biomarkers and therapeutic targets within melanoma EVs, with potential applications in drug development and personalized medicine. Full article

Background/Objectives: Prioritizing diet- or exercise-related self-efficacy and social support with their interactions may improve the effectiveness of interventions aimed at increasing daily fruit/vegetable intake and exercise, thereby reducing the risk of metabolic disorders in abdominally obese women. This study aimed to identify the profiles of diet- or exercise-related self-efficacy and social support among women with abdominal obesity, examine profiles related to insufficient fruit/vegetable intake and exercise, and explore associating factors of these profiles. Methods: A cross-sectional investigation in central south mainland China collected sociodemographic, anthropometric, and health-related variables, diet-related self-efficacy (Diet-SE) and social support (Diet-SS), exercise-related self-efficacy (Exercise-SE) and social support (Exercise-SS), and daily fruit/vegetable intake and exercise. We used latent profile analysis to identify distinct profiles, and binary logistic regression to examine the profiles’ behaviors and associating factors. Results: A total of 327 abdominally obese women were categorized into four profiles of Diet-SE and Diet-SS, and five profiles of Exercise-SE and Exercise-SS. Women in the Diet Dual-Low Group were associated with insufficient daily fruits/vegetables intake. Women in the Exercise Dual-Low Group or Exercise-SS Medium–Low Group were more likely to engage in insufficient daily exercise. Conclusions: Our findings align with previous evidence that women with low diet- or exercise-related self-efficacy and social support are at increased risk for insufficient daily fruit/vegetable intake or exercise. Additionally, medium Exercise-SS is associated with insufficient exercise behaviors, suggesting that interventions targeting healthy exercise should be initiated earlier among women with medium Exercise-SS, rather than waiting for it to decline to low level. Full article