BackgroundThe comet assay is a sensitive and widely used technique for assessing DNA damage at the single-cell level. Despite its advantages, traditional manual scoring methods remain time-consuming, subjective and limited in scalability, posing challenges for high-throughput and standardized analysis.ObjectiveThis study aims to develop and evaluate a deep learning-based system for automated comet assay image classification, addressing limitations of manual and semi-automated approaches while enhancing accuracy, reproducibility and processing efficiency.MethodA YOLOv5-based object detection model was trained on a dataset of 875 annotated comet assay images, curated through a three-step expert-reviewed process. Various hyperparameters and data augmentation techniques were optimized to improve performance. The dataset was split into training, validation and test sets, and model performance was evaluated using mAP, precision, recall and confusion matrix analysis.ResultsThe model achieved strong performance, with mAP@0.5 reaching 0.98 and recall exceeding 0.8. Detailed analyses revealed robust learning behavior and generalization capacity. Visual outputs, including precision-recall curves and class-wise confusion matrices, confirmed high classification accuracy, although overlapping comet structures and class imbalance posed challenges. The model demonstrated improved scalability and processing speed compared to traditional tools, supporting its integration into web-based applications.ConclusionThe proposed YOLOv5-based system offers a scalable and accurate solution for automating comet assay analysis. It significantly enhances throughput and reduces human error, supporting its application in genotoxicity testing, biomonitoring and molecular epidemiology. Future work will focus on handling overlapping structures, benchmarking against existing tools and optimizing deployment in real-world laboratory settings.

Benzoxazoles possess a wide range of therapeutic activities, including antimicrobial, antitumor, anti‐inflammatory, and other. Using in silico and in vitro approaches, we determined the potential antitumor activity of benzoxazoles synthesized from thymoquinone in diffuse large B‐cell lymphoma (DLBCL) cells. Molecular docking analysis showed strong binding affinities of benzoxazoles toward Akt and nuclear factor kappa B (NF‐κB) protein targets that promote cancer cell proliferation and survival and whose expression is linked to tumorigenesis of activated B‐cell (ABC) and germinal center B‐cell (GCB) DLBCL subtypes. WST‐8 assay showed the highest inhibitory activity of benzoxazole derivative bearing thiophene substituent in both DLBCL models. Western blot analysis indicated the inhibitory activity of selected compounds in HBL‐1 cells, with decreased p‐NF‐κB and p‐Akt protein expression, whereas treatment of DHL‐4 cells stimulated the expression of p‐Akt and p‐NF‐κB protein levels. These data suggest distinct, cell line‐dependent activities of the substances that potentially act through diverse oncogenic signaling pathways in DLBCL cells and activation of compensatory cell mechanisms that could be an important step for combinatorial treatment approaches.

The complex link between COVID‐19 and immunometabolic diseases demonstrates the important interaction between metabolic dysfunction and immunological response during viral infections. Severe COVID‐19, defined by a hyperinflammatory state, is greatly impacted by underlying chronic illnesses aggravating the cytokine storm caused by increased levels of Pro‐inflammatory cytokines. Metabolic reprogramming, including increased glycolysis and altered mitochondrial function, promotes viral replication and stimulates inflammatory cytokine production, contributing to illness severity. Mitochondrial metabolism abnormalities, strongly linked to various systemic illnesses, worsen metabolic dysfunction during and after the pandemic, increasing cardiovascular consequences. Long COVID‐19, defined by chronic inflammation and immune dysregulation, poses continuous problems, highlighting the need for comprehensive therapy solutions that address both immunological and metabolic aspects. Understanding these relationships shows promise for effectively managing COVID‐19 and its long‐term repercussions, which is the focus of this review paper.

Diffuse large B cell lymphoma (DLBCL) is classified into Germinal Center B‐cell (GCB) and activated B‐cell (ABC) subgroups originating from different stages of lymphoid differentiation. Cell of origin dictates the behavior and therapeutic response of DLBCL. This study aimed to evaluate single and combinatorial effects of metformin and thymoquinone (TQ) in two DLBCL cell lines belonging to GCB and ABC subtypes. Metformin and TQ caused dose‐dependent responses in both ABC and GCB DLBCL subtypes. Metformin had a greater impact on the ABC subtype while TQ demonstrated more pronounced effects on the GCB subtype. Synergistic effects were observed in the DHL4 (GCB subtype) but not in the HBL1 (ABC subtype) cell line. This is the first study to compare the effects of metformin and TQ in ABC versus GCB subtype of DLBCL. It brings valuable results that could be utilized in further research aimed at reshaping treatments for subtype‐specific lymphomas.

Polyphenols are abundant natural plant micronutrients that commonly contribute to human health due to their anti-inflammatory, antioxidant, antiviral, anti-carcinogenic, anti-aging, anti-allergic, and other biological activities. Their therapeutic benefits mainly depend on the structure, stability, chemical interactions, and absorption, which ultimately affect the bioavailability of these compounds. The bioactivity of polyphenols is evaluated by in vitro and in vivo studies, sometimes yielding inconsistent results due to numerous differences between used models. Among the main differences is the production of reactive oxygen species (ROS) in cultured cell models, potentially leading to misinterpretation of the effects of polyphenolic compounds. Little attention is paid to the polyphenol stability in cell culture medium and the potential generation of artifacts due to their chemical instability. Stability tests of polyphenols are strongly advised to be performed in parallel with cell culture, to help avoid misleading conclusions. This review highlights the existing challenges with cell-based research, focusing on polyphenols' stability in the cell culture media. We also emphasize that new methods analyzing the molecular interactions of compounds with cell culture media supplements are essential to provide a comprehensive understanding of the polyphenols in in vitro models.

Long COVID-19 affects a significant percentage of patients and is characterized by a wide range of symptoms, including weariness and mental fog as well as emotional symptoms like worry and sadness. COVID-19 is closely linked to the autoimmune disorders that are becoming more prevalent worldwide and are linked to immune system hyperactivation, neutrophil extracellular trap (NET) development, and molecular mimicry pathways. Long-term COVID-related autoimmune responses include a watchful immune system referring to the ability of immune system to constantly monitor the body for signs of infection, disease, or abnormal cells; altered innate and adaptive immune cells, autoantigens secreted by living or dead neutrophils, and high concentrations of autoantibodies directed against different proteins. The microbiome, which consists of billions of bacteria living in the human body, is essential for controlling immune responses and supporting overall health. The microbiome can affect the course of long COVID-associated autoimmunity, including the degree of illness, the rate of recovery, and the onset of autoimmune reactions. Although the precise role of the microbiome in long COVID autoimmunity is still being investigated, new studies indicate that probiotics, prebiotics, and dietary changes-interventions that target the microbiome-may be able to reduce autoimmune reactions and enhance long-term outcomes for COVID-19 survivors. More research is required to precisely understand how the microbiome affects COVID-19-related autoimmunity and to create tailored treatment plans.

BACKGROUND: Preclinical drug testing requires in vitro and in vivo assessments that are vital for studying drug pharmacokinetics and toxicity. Distinct factors that play an important role in drug screening, such as hydrophobicity, solubility of the substance and serum protein binding can be challenging by inducing result inconsistencies. Hence, establishing accurate methods to quantify drug concentrations in cell cultures becomes pivotal for reliable and reproducible results important for in vivo dosing predictions. OBJECTIVE: This research focuses on developing an optimized analytical approach via high-pressure liquid chromatography (HPLC) to determine thymoquinone (TQ) levels in monolayer cell cultures. METHODS: The method’s validation adheres to the International Council for Harmonisation (ICH) guideline M10, ensuring its acceptance and applicability. Using an HPLC system with a Diode Array Detector (DAD), the study fine-tuned various parameters to achieve an efficient separation of TQ. Validation covered specificity, sensitivity, matrix effects, linearity, precision, and accuracy, alongside assessing TQ stability in RPMI-1640 medium. RESULTS: The HPLC method exhibited remarkable TQ specificity, free from interfering peaks at the analyte retention. Sensitivity analysis at the lower limit of quantification (LLOQ) revealed 5.68% %CV and 98.37% % mean accuracy. Matrix effect evaluation showcased accuracy within 85–115%. Linearity spanned in the concentration range of 2–10 μ M with a correlation coefficient ( r 2 ) of 0.9993. Precision and accuracy were aligned with acceptance criteria. The proposed method was found to be greener in terms of usage of persistent, bioaccumulative, and toxic chemicals and solvents, corrosive samples, and waste production. CONCLUSION: The developed HPLC-DAD method emerges as specific, accurate, sensitive, and reliable for TQ determination in cell cultures. It ensures robust TQ quantification, enhancing precise in vitro assessments and dependable dosing predictions for in vivo studies. Further research is advocated to investigate TQ’s stability across diverse environmental conditions.