Metabolic regulation in normal and leukemic stem cells.

Hematopoietic stem cells (HSCs) and leukemic stem cells (LSCs) are crucial for ensuring hematopoietic homeostasis and driving leukemia progression, respectively. Recent research has revealed that metabolic adaptations significantly regulate the function and survival of these stem cells. In this review, we provide an overview of how metabolic pathways regulate oxidative and proteostatic stresses in HSCs during homeostasis and aging. Furthermore, we highlight targetable metabolic pathways and explore their interactions with epigenetics and the microenvironment in addressing the chemoresistance and immune evasion capacities of LSCs. The metabolic differences between HSCs and LSCs have profound implications for therapeutic strategies.

A coordinated adaptive multiscale enhanced spatio-temporal fusion network for multi-lead electrocardiogram arrhythmia detection.

The multi-lead electrocardiogram (ECG) is widely utilized in clinical diagnosis and monitoring of cardiac conditions. The advancement of deep learning has led to the emergence of automated multi-lead ECG diagnostic networks, which have become essential in the fields of biomedical engineering and clinical cardiac disease diagnosis. Intelligent ECG diagnosis techniques encompass Recurrent Neural Networks (RNN), Transformers, and Convolutional Neural Networks (CNN). While CNN is capable of extracting local spatial information from images, it lacks the ability to learn global spatial features and temporal memory features. Conversely, RNN relies on time and can retain significant sequential features. However, they are not proficient in extracting lengthy dependencies of sequence data in practical scenarios. The self-attention mechanism in the Transformer model has the capability of global feature extraction, but it does not adequately prioritize local features and cannot extract spatial and channel features. This paper proposes STFAC-ECGNet, a model that incorporates CAMV-RNN block, CBMV-CNN block, and TSEF block to enhance the performance of the model by integrating the strengths of CNN, RNN, and Transformer. The CAMV-RNN block incorporates a coordinated adaptive simplified self-attention module that adaptively carries out global sequence feature retention and enhances spatial-temporal information. The CBMV-CNN block integrates spatial and channel attentional mechanism modules in a skip connection, enabling the fusion of spatial and channel information. The TSEF block implements enhanced multi-scale fusion of image spatial and sequence temporal features. In this study, comprehensive experiments were conducted using the PTB-XL large publicly available ECG dataset and the China Physiological Signal Challenge 2018 (CPSC2018) database. The results indicate that STFAC-ECGNet surpasses other cutting-edge techniques in multiple tasks, showcasing robustness and generalization.

Optimization of the convolutional neural network classification model under the background of innovative art teaching models.

To improve students' ability to recognize and appreciate artworks, and further enhance their academic performance and classroom satisfaction, this study explores the application of the Convolutional Neural Network (CNN) model based on optimization in art teaching. Firstly, the importance and challenges of art teaching are analyzed. Secondly, the principle and structure of CNN and its application in the classification field are expounded, and then the CNN classification model is optimized. Finally, the effectiveness of the optimized model is verified by experiments. Experimental results show that the optimized model's accuracy is up to 95.2% in the performance evaluation. The training time of the optimized model is much lower than that of the traditional model, and this model still maintains 95.2% accuracy under the noise of 14.7%. In addition, the accuracy of the optimized model on the unseen test data is 92%. In comparing teaching experiment results, by introducing the CNN classification model, Class B students' average score of art homework has increased by 4.3 points. The score for class satisfaction is 8.1 points. This indicates that the optimized CNN model has significant advantages in art teaching and can effectively improve students' classroom satisfaction and academic performance. Therefore, this study has specific reference significance for the innovation of the art teaching model.

Histological and transcriptomic insights into the interaction between grapevine and Colletotrichum viniferum.

Introduction: Grape is of high economic value. Colletotrichum viniferum, a pathogen causing grape ripe rot and leaf spot, threatens grape production and quality. Methods: This study investigates the interplay between C. viniferum by Cytological study and transcriptome sequencing. Results: Different grapevine germplasms, V. vinifera cv. Thompson Seedless (TS), V. labrusca accession Beaumont (B) and V. piasezkii Liuba-8 (LB-8) were classified as highly sensitive, moderate resistant and resistant to C. viniferum, respectively. Cytological study analysis reveals distinct differences between susceptible and resistant grapes post-inoculation, including faster pathogen development, longer germination tubes, normal appressoria of C. viniferum and absence of white secretions in the susceptible host grapevine. To understand the pathogenic mechanisms of C. viniferum, transcriptome sequencing was performed on the susceptible grapevine "TS" identifying 236 differentially expressed C. viniferum genes. These included 56 effectors, 36 carbohydrate genes, 5 P450 genes, and 10 genes involved in secondary metabolism. Fungal effectors are known as pivotal pathogenic factors that modulate plant immunity and affect disease development. Agrobacterium-mediated transient transformation in Nicotiana benthamiana screened 10 effectors (CvA13877, CvA01508, CvA05621, CvA00229, CvA07043, CvA05569, CvA12648, CvA02698, CvA14071 and CvA10999) that inhibited INF1 (infestans 1, P. infestans PAMP elicitor) induced cell death and 2 effectors (CvA02641 and CvA11478) that induced cell death. Additionally, transcriptome analysis of "TS" in response to C. viniferum identified differentially expressed grape genes related to plant hormone signaling (TGA, PR1, ETR, and ERF1/2), resveratrol biosynthesis genes (STS), phenylpropanoid biosynthesis genes (PAL and COMT), photosynthetic antenna proteins (Lhca and Lhcb), transcription factors (WRKY, NAC, MYB, ERF, GATA, bHLH and SBP), ROS (reactive oxygen species) clearance genes (CAT, GSH, POD and SOD), and disease-related genes (LRR, RPS2 and GST). Discussion: This study highlights the potential functional diversity of C. viniferum effectors. Our findings lay a foundation for further research of infection mechanisms in Colletotrichum and identification of disease response targets in grape.

Hybrid construction of tissue-engineered nerve graft using skin derived precursors induced neurons and Schwann cells to enhance peripheral neuroregeneration.

Peripheral nerve injury is a major challenge in clinical treatment due to the limited intrinsic capacity for nerve regeneration. Tissue engineering approaches offer promising solutions by providing biomimetic scaffolds and cell sources to promote nerve regeneration. In the present work, we investigated the potential role of skin-derived progenitors (SKPs), which are induced into neurons and Schwann cells (SCs), and their extracellular matrix in tissue-engineered nerve grafts (TENGs) to enhance peripheral neuroregeneration. SKPs were induced to differentiate into neurons and SCs in vitro and incorporated into nerve grafts composed of a biocompatible scaffold including chitosan neural conduit and silk fibroin filaments. In vivo experiments using a rat model of peripheral nerve injury showed that TENGs significantly enhanced nerve regeneration compared to the scaffold control group, catching up with the autograft group. Histological analysis showed improved axonal regrowth, myelination and functional recovery in animals treated with these TENGs. In addition, immunohistochemical staining confirmed the presence of induced neurons and SCs within the regenerated nerve tissue. Our results suggest that SKP-induced neurons and SCs in tissue-engineered nerve grafts have great potential for promoting peripheral nerve regeneration and represent a promising approach for clinical translation in the treatment of peripheral nerve injury. Further optimization and characterization of these engineered constructs is warranted to improve their clinical applicability and efficacy.

The role of NF-kappaB in the inflammatory processes related to dental caries, pulpitis, apical periodontitis, and periodontitis-a narrative review.

Tooth-related inflammatory disorders, including caries, pulpitis, apical periodontitis (AP), and periodontitis (PD), are primarily caused by resident oral microorganisms. Although these dental inflammatory conditions are typically not life-threatening, neglecting them can result in significant complications and greatly reduce an individual's quality of life. Nuclear factor κB (NF-κB), a family formed by various combinations of Rel proteins, is extensively involved in inflammatory diseases and even cancer. This study reviews recent data on NF-κB signaling and its role in dental pulp stem cells (DPSCs), dental pulp fibroblasts (DPFs), odontoblasts, human periodontal ligament cells (hPDLCs), and various experimental animal models. The findings indicate that NF-κB signaling is abnormally activated in caries, pulpitis, AP, and PD, leading to changes in related cellular differentiation. Under specific conditions, NF-κB signaling occasionally interacts with other signaling pathways, affecting inflammation, bone metabolism, and tissue regeneration processes. In summary, data collected over recent years confirm the central role of NF-κB in dental inflammatory diseases, potentially providing new insights for drug development targeting NF-κB signaling pathways in the treatment of these conditions. Keywords: NF-κB, dental caries, pulpitis, apical periodontitis, periodontitis.

A hemoadhican-based sponge with anti-heparin interference for treating uncontrollable massive hemorrhage.

Hemoadhican (HD) is an exopolysaccharide with a branched structure that has been reported for its high hemostatic ability. In this study, a HD-based hemostatic sponge was prepared through ultrasonic dissolution and freeze-drying without using any cross-linking agent. The sponge could spontaneously cross-link using hydrogen bonds to form adhesive mud within 3 s upon contact with blood. This sponge-mud mixture adhered tightly to the wound tissue, forming a pressure-resistant physical barrier that captures and locks in blood cells and platelets. Simultaneously, the hydrophobic methyl groups of HD sponges repel blood inwardly, effectively sealing the wound. The brush-like structure of HD molecules was suspected to penetrate wet tissues through topological entanglement, thereby enhancing wet adhesion. Compared with gauze and gelatin sponges, HD sponges achieved more effective hemostasis in animal models using rat and rabbit femoral arteries. In particular, HD sponges showed excellent hemostasis in heparin-induced hemorrhage models in mice and pigs. The in vivo experiment demonstrated the excellent biosafety of the HD sponge. Conclusively, the HD sponge is a safe and efficient rapid hemostatic material that is expected to become an alternative material for clinical hemostatic procedures.

Association between systemic inflammation markers and blood pressure among children and adolescents: National Health and Nutrition Examination Survey.

BACKGROUND: Few studies have estimated the associations of systemic inflammation markers and high blood pressure (HBP) in the pediatric population. METHODS: Basing on data from the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2018, we assessed the associations between four inflammation-related factors based on blood cell counts: systemic immune inflammation index (SII), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), and risk for pediatric HBP by estimating odds ratios (ORs) using multivariable logistic regression models. RESULTS: A total of 17,936 children aged 8-19 years were included in the analysis, representing about 36.7 million American children. The prevalence rates of elevated blood pressure (EBP) and hypertension (HTN) were 15.79% and 6.77%, respectively. The results showed that the ORs for EBP per standard deviation (SD) increment in SII and NLR were estimated at 1.11 [95% confidence interval (95%CI): 1.04, 1.17] and 1.08 (95%CI: 1.02, 1.15), respectively; and the OR for EBP per SD increment in LMP were estimated at 0.90 (95%CI: 0.83, 0.96). These associations were stronger in boys and younger children. CONCLUSIONS: The study suggested that inflammation-related factors could serve as easily accessible early biomarkers for HBP risk prediction and prevention in children and adolescents. IMPACT: The study suggested that inflammation-related factors could serve as easily accessible early biomarkers for HBP risk prediction and prevention in children and adolescents. This is the first study that demonstrates the close association between systemic inflammation markers and HBP in children and adolescents using nationally representative population data. The findings have more public health implications and support that systemic inflammation markers based on blood cell counts could serve as easily accessible biomarkers of HBP risk and prevention in earlier identification of the diseases.

Temporal trends, in-hospital outcomes, and risk factors of acute myocardial infarction among patients with epilepsy in the United States: a retrospective national database analysis from 2008 to 2017.

Background: The relationship between epilepsy and risk of acute myocardial infarction (AMI) is not fully understood. Evidence from the Stockholm Heart Study indicates that the risk of AMI is increased in people with epilepsy. This study aims to analyze the temporal trends in prevalence, adverse clinical outcomes, and risk factors of AMI in patients with epilepsy (PWE). Methods: Patients aged 18 years or older, diagnosed with epilepsy with or without AMI and hospitalized from January 1, 2008, to December 31, 2017, were identified from the National Inpatient Sample (NIS) database. The Cochran-Armitage trend test and logistic regressions were conducted using SAS 9.4. Odds ratios (ORs) were generated for multiple variables. Results: A total of 8,456,098 inpatients were eligible for our analysis, including 181,826 comorbid with AMI (2.15%). The prevalence of AMI diagnosis in PWE significantly increased from 1,911.7 per 100,000 hospitalizations in 2008 to 2,529.5 per 100,000 hospitalizations in 2017 (Ptrend < 0.001). Inpatient mortality was significantly higher in epilepsy patients with AMI compared to those without AMI (OR = 4.61, 95% CI: 4.54 to 4.69). Factors significantly associated with AMI in PWE included age (≥75 years old vs. 18 ~ 44 years old, OR = 3.54, 95% CI: 3.45 to 3.62), atherosclerosis (OR = 4.44, 95% CI: 4.40 to 4.49), conduction disorders (OR = 2.21, 95% CI: 2.17 to 2.26), cardiomyopathy (OR = 2.11, 95% CI: 2.08 to 2.15), coagulopathy (OR = 1.52, 95% CI: 1.49 to 1.54), dyslipidemia (OR = 1.26, 95% CI: 1.24 to 1.27), peptic ulcer disease (OR = 1.23, 95% CI: 1.13 to 1.33), chronic kidney disease (OR = 1.23, 95% CI: 1.22 to 1.25), smoking (OR = 1.20, 95% CI: 1.18 to 1.21), and weight loss (OR = 1.20, 95% CI: 1.18 to 1.22). Conclusion: The prevalence of AMI in PWE increased during the decade. Mortality rates were high among this population, highlighting the need for comprehensive attention to prophylaxis for risk factors and early diagnosis of AMI in PWE by physicians.

Baseline sensitivity and toxicity mechanisms of prochloraz to Alternaria alternata strains associated with maize leaf blight in Heilongjiang province in China.

Alternaria species are fungal pathogens that can infect maize, causing leaf blight disease and significant economic losses. This study aimed to determine the baseline sensitivity to prochloraz of A. alternata isolates obtained from diseased maize leaves collected from Heilongjiang province by assessing the half-maximal effective concentration (EC50) values. The EC50 values of prochloraz ranged from 0.0550 µg/mL to 2.3258 µg/mL, with an average of 0.9995 ± 0.5192 µg/mL. At EC50 (1.2495 µg/mL) and 2EC50 (2.4990 µg/mL), prochloraz increased the number of mycelial offshoots, disrupted the cell membrane integrity of conidia and mycelia, and resulted in a reduced ergosterol content in the mycelia. Prochloraz significantly affected the mycelial cell membrane permeability and increased the malondialdehyde (MDA) content and superoxide dismutase (SOD) activity. No cross-resistance was detected between prochloraz and other fungicides. These data demonstrate that prochloraz is a promising fungicide for managing maize leaf blight caused by A. alternata and provide novel insights into understanding the mechanism of prochloraz toxicity against A. alternata isolates.

Surprising Effects of Ti and Al2O3 Coatings on Tribocatalytic Degradation of Organic Dyes by GaN Nanoparticles.

GaN is more stable than most metal oxide semiconductors for the photocatalytic degradation of organic pollutants in harsh conditions, while its catalytic efficiency has been difficult to be substantially improved. In this study, the tribocatalytic degradation of organic dyes by GaN nanoparticles has been investigated. Stimulated through magnetic stirring using homemade Teflon magnetic rotary disks in glass beakers, the GaN nanoparticles were found to induce negligible degradation in rhodamine B (RhB) and methyl orange (MO) solutions. Surprisingly, the degradation was greatly enhanced in beakers with Ti and Al2O3 coatings on their bottoms: 99.2% and 99.8% of the 20 mg/L RhB solutions were degraded in 3 h for the Ti and Al2O3 coatings, respectively, and 56% and 60.2% of the 20 mg/L MO solutions were degraded in 24 h for the Ti and Al2O3 coatings, respectively. Moreover, the MO molecules were only broken into smaller organic molecules for the Ti coating, while they were completely degraded for the Al2O3 coating. These findings are important for the catalytic degradation of organic pollutants by GaN in harsh environments and for achieving a better understanding of tribocatalysis as well.

Comparative Anti-Cancer and Anti-Inflammatory Activities of Essential Oils from the Bark and Flower of Magnolia officinalis Rehd. et Wils.

This study was designed to compare the antioxidant, antitumor and anti-inflammatory effects of essential oils from the bark and flower of Magnolia officinalis Rehd. et Wils. Distillation extraction and steam distillation were used to extract EOs from the bark and flower. The results showed that the contents of EOs of SDE-F and SDE-B were much higher than that of SD-F and SD-B. EOs from the bark were rich in eudesmol (especially α-eudesmol) and exhibited a stronger antioxidant effect than the flower. The anti-tumor effects of SD-B and SD-F on HepG2 and MDA-MB-231 cells were better than that of SDE-B and SDE-F. The inhibitory rates of SD-B and SD-F on MDA-MB-231 cells were 59.21% and 48.27%, exceeding that of positive control 5-fluorouracil (47.04%) at 50 µg/mL. All four EOs exhibited excellent anti-inflammatory activities through the regulation of nitric oxide production and pro-inflammation cytokines in LPS-induced RAW 264.7 cells and they also remarkably suppressed the mRNA expressions of nitric oxide synthase, IL-6 and TNF-α at the concentration higher than that of positive control dexamethasone. These results indicated significant differences in the composition, and anti-inflammatory and anti-tumor activities of EOs extracted by different methods and provided a theoretical basis for their development and utilization.

Pentacoordinated pyramidal structures and bonding properties of WN10-/0: anion photoelectron spectroscopy and theoretical calculations.

Anion photoelectron spectroscopy and theoretical calculations were used to investigate the structural and bonding properties of WN10-/0. The electron affinity of WN10 is measured to be 1.582 ± 0.030 eV. The frequency of the NN stretch in WN10 is measured to be 2170 ± 80 cm-1, which is red-shifted with respect to that of the dinitrogen molecule indicating that the NN bonds are weakened in WN10. The theoretical adiabatic detachment energy (ADE) and vertical detachment energy (VDE) of WN10- obtained by calculations at the CCSD(T)/CBS level agree well with experimental results. The structures of WN10-/0 are C4v symmetric pentacoordinated pyramidal structures with five end-on dinitrogen ligands. Our experiments show that the peak of WN10- is dominant in the mass spectrum of anionic WNn, whereas the mass peak of WN12+ is dominant in the mass spectrum of cationic WNn, implying that the stabilities of WNn clusters are strongly related to their charge states.

Machine Learning in Hypertrophic Cardiomyopathy: Nonlinear Model From Clinical and CMR Features Predicting Cardiovascular Events.

BACKGROUND: The cumulative burden of hypertrophic cardiomyopathy (HCM) is significant, with a noteworthy percentage (10%-15%) of patients with HCM per year experiencing major adverse cardiovascular events (MACEs). A current risk stratification scheme for HCM had only limited accuracy in predicting sudden cardiac death (SCD) and failed to account for a broader spectrum of adverse cardiovascular events and cardiac magnetic resonance (CMR) parameters. OBJECTIVES: This study sought to develop and evaluate a machine learning (ML) framework that integrates CMR imaging and clinical characteristics to predict MACEs in patients with HCM. METHODS: A total of 758 patients with HCM (67% male; age 49 ± 14 years) who were admitted between 2010 and 2017 from 4 medical centers were included. The ML model was built on the internal discovery cohort (533 patients with HCM, admitted to Fuwai Hospital, Beijing, China) by using the light gradient-boosting machine and internally evaluated using cross-validation. The external test cohort consisted of 225 patients with HCM from 3 medical centers. A total of 14 CMR imaging features (strain and late gadolinium enhancement [LGE]) and 23 clinical variables were evaluated and used to inform the ML model. MACEs included a composite of arrhythmic events, SCD, heart failure, and atrial fibrillation-related stroke. RESULTS: MACEs occurred in 191 (25%) patients over a median follow-up period of 109.0 months (Q1-Q3: 73.0-118.8 months). Our ML model achieved areas under the curve (AUCs) of 0.830 and 0.812 (internally and externally, respectively). The model outperformed the classic HCM Risk-SCD model, with significant improvement (P < 0.001) of 22.7% in the AUC. Using the cubic spline analysis, the study showed that the extent of LGE and the impairment of global radial strain (GRS) and global circumferential strain (GCS) were nonlinearly correlated with MACEs: an elevated risk of adverse cardiovascular events was observed when these parameters reached the high enough second tertiles (11.6% for LGE, 25.8% for GRS, -17.3% for GCS). CONCLUSIONS: ML-empowered risk stratification using CMR and clinical features enabled accurate MACE prediction beyond the classic HCM Risk-SCD model. In addition, the nonlinear correlation between CMR features (LGE and left ventricular pressure gradient) and MACEs uncovered in this study provides valuable insights for the clinical assessment and management of HCM.

HIF-2α inhibition disrupts leukemia stem cell metabolism and impairs vascular microenvironment to enhance chronic myeloid leukemia treatment.

Leukemic stem cells (LSCs) in chronic myeloid leukemia (CML) contribute to treatment resistance and disease recurrence. Metabolism regulates LSCs, but the mechanisms remain elusive. Here, we show that hypoxia-inducible factor 2α (HIF-2α) is highly expressed in LSCs in mouse and human CML and increases after tyrosine kinase inhibitor (TKI) treatment. Deletion of HIF-2α suppresses disease progression, reduces LSC numbers, and enhances the efficacy of TKI treatment in BCL-ABL-induced CML mice. Mechanistically, HIF-2α deletion reshapes the metabolic profile of LSCs, leading to increased production of reactive oxygen species (ROS) and apoptosis in CML. Moreover, HIF-2α deletion decreases vascular endothelial growth factor (VEGF) expression, thereby suppressing neovascularization in the bone marrow of CML mice. Furthermore, pharmaceutical inhibition of HIF-2α by PT2399 attenuates disease progression and improves the efficacy of TKI treatment in both mouse and human CML. Overall, our findings highlight the role of HIF-2α in controlling the metabolic state and vascular niche remodeling in CML, suggesting it is a potential therapeutic target to enhance TKI therapy.

A crucial role of adenosine deaminase in regulating gluconeogenesis in mice.

Adenosine deaminase (ADA) catalyzes the irreversible deamination of adenosine (ADO) to inosine and regulates ADO concentration. ADA ubiquitously expresses in various tissues to mediate ADO-receptor signaling. A significant increase in plasma ADA activity has been shown to be associated with the pathogenesis of type 2 diabetes mellitus. Here, we show that elevated plasma ADA activity is a compensated response to high level of ADO in type 2 diabetes mellitus and plays an essential role in the regulation of glucose homeostasis. Supplementing with more ADA, instead of inhibiting ADA, can reduce ADO levels and decrease hepatic gluconeogenesis. ADA restores a euglycemic state and recovers functional islets in db/db and high-fat streptozotocin diabetic mice. Mechanistically, ADA catabolizes ADO and increases Akt and FoxO1 phosphorylation independent of insulin action. ADA lowers blood glucose at a slower rate and longer duration compared to insulin, delaying or blocking the incidence of insulinogenic hypoglycemia shock. Finally, ADA suppresses gluconeogenesis in fasted mice and insulin-deficient diabetic mice, indicating the ADA regulating gluconeogenesis is a universal biological mechanism. Overall, these results suggest that ADA is expected to be a new therapeutic target for diabetes.

OMGMed: Advanced System for Ocular Myasthenia Gravis Diagnosis via Eye Image Segmentation.

This paper presents an eye image segmentation-based computer-aided system for automatic diagnosis of ocular myasthenia gravis (OMG), called OMGMed. It provides great potential to effectively liberate the diagnostic efficiency of expert doctors (the scarce resources) and reduces the cost of healthcare treatment for diagnosed patients, making it possible to disseminate high-quality myasthenia gravis healthcare to under-developed areas. The system is composed of data pre-processing, indicator calculation, and automatic OMG scoring. Building upon this framework, an empirical study on the eye segmentation algorithm is conducted. It further optimizes the algorithm from the perspectives of "network structure" and "loss function", and experimentally verifies the effectiveness of the hybrid loss function. The results show that the combination of "nnUNet" network structure and "Cross-Entropy + Iou + Boundary" hybrid loss function can achieve the best segmentation performance, and its MIOU on the public and private myasthenia gravis datasets reaches 82.1% and 83.7%, respectively. The research has been used in expert centers. The pilot study demonstrates that our research on eye image segmentation for OMG diagnosis is very helpful in improving the healthcare quality of expert doctors. We believe that this work can serve as an important reference for the development of a similar auxiliary diagnosis system and contribute to the healthy development of proactive healthcare services.

Ethyl pyruvate attenuates cellular adhesion and proliferation of diffuse large B-cell lymphoma by targeting c-Jun.

Diffuse large B-cell lymphoma (DLBCL) stands out as the most common type of malignant cancer, representing the majority of cases of non-Hodgkin's lymphoma. Ethyl pyruvate (EP) is a derivative of pyruvic acid and found to have potent anti-tumor properties. Despite its potential benefits, the impact of EP on DLBCL remains ambiguous. Our objective is to elucidate the role of EP in modulating the development of DLBCL. Analysis of cholecystokinin-8 (CCK-8) revealed that treatment with EP significantly diminished the viability of DLBCL cells. Furthermore, EP administration suppressed colony formation and hindered cell adhesion and invasion in DLBCL cells. Examination of cell cycle progression showed that EP treatment induced arrest at the G1 phase and subsequently reduced the S phase population in DLBCL cells. EP treatment consistently exhibited apoptosis-inducing properties in Annexin-V assays, and notably downregulated the expression of Bcl-2 while increasing levels of proapoptotic cleaved caspase 3 and BAX in DLBCL cells. Additionally, EP treatment decreased the overexpression of c-Jun in c-Jun-transfected DLBCL cells. Further, EP demonstrated DNA-damaging effects in TUNEL assays. In vivo, xenograft animal models revealed that EP treatment significantly mitigated DLBCL tumor growth and suppressed DLBCL cell adhesion to bone marrow stromal cells. In summary, these findings suggest that EP mitigates DLBCL progression by inducing apoptosis, inducing cell cycle arrest, and promoting DNA damage.