Advances in biomarker sciences and technology最新文献

{"title":"Bridging traditional risk factors and genetic insights: A review on polygenic risk scores in cardiovascular diseases","authors":"Abhishek Gupta ,&nbsp;Komal Shah ,&nbsp;Aakansha Shukla","doi":"10.1016/j.abst.2025.09.002","DOIUrl":"10.1016/j.abst.2025.09.002","url":null,"abstract":"<div><div>Cardiovascular diseases (CVDs) remain the leading cause of global morbidity and mortality, with traditional risk models often falling short in predicting individual susceptibility-especially among diverse populations. Recent advances in genomics have led to the development of polygenic risk scores (PRS), which aggregate the effects of multiple single nucleotide polymorphisms (SNPs) to estimate genetic predisposition to CVD. This review explores the scientific evolution, clinical relevance, and limitations of PRS in CVD prediction. Evidence shows that integrating PRS with conventional risk factors significantly improves risk stratification, aiding in early detection and personalized prevention strategies. Notably, ethnicity-specific PRS models are being developed to enhance predictive accuracy for non-European populations, including South Asians. Despite its promise, PRS implementation faces challenges, such as Eurocentric bias in genome-wide association studies (GWAS), limited accessibility in low- and middle-income countries, and ethical concerns regarding equity and data privacy. Future research should emphasize multi-ethnic datasets, integration with clinical and lifestyle data, and development of equitable policies. As PRS continues to be effective in refining cardiovascular risk stratification, its integration into public health frameworks could revolutionize risk assessment and drive the shift toward precision medicine.</div></div>","PeriodicalId":72080,"journal":{"name":"Advances in biomarker sciences and technology","volume":"7 ","pages":"Pages 365-377"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145048295","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bringing lab to the field: Exploring innovations in point-of-care diagnostics for the rapid detection and management of tropical diseases in resource-limited settings","authors":"Abdullahi Tunde Aborode ,&nbsp;Ridwan Olamilekan Adesola ,&nbsp;Godfred Yawson Scott ,&nbsp;Emele Arthur-Hayford ,&nbsp;Oche Joseph Otorkpa ,&nbsp;Somuah Daniel Kwaku ,&nbsp;Emmanuel Ebuka Elebesunu ,&nbsp;Eghaghe Osadebamwen Nibokun ,&nbsp;Ibude Jane Aruorivwooghene ,&nbsp;Adetolase A. Bakre ,&nbsp;Oluwaseun Adeolu Ogundijo ,&nbsp;Olamilekan Gabriel Banwo ,&nbsp;Oluwatobiloba Ige ,&nbsp;Ibrahim O. Adelakun ,&nbsp;Isreal Ayobami Onifade ,&nbsp;Segun E. Ogungbemi ,&nbsp;Boluwatife T. Dosunmu ,&nbsp;Oluwaseunayo Deborah Ayando ,&nbsp;Nike Idowu ,&nbsp;Grace A. Adegoye ,&nbsp;Olusegun Oluwaseun Jimoh","doi":"10.1016/j.abst.2025.01.001","DOIUrl":"10.1016/j.abst.2025.01.001","url":null,"abstract":"<div><div>Tropical diseases present major health challenges in regions with limited resources, where access to advanced laboratory facilities is often scarce. This study explores the innovative techniques emerging in point-of-care (POC) diagnostics that are transforming the detection and treatment of tropical diseases. These advancements aim to provide faster diagnosis, better medical care, and ongoing monitoring in areas where traditional diagnostic methods are not practical, combining the precision of laboratory testing with the accessibility of field-based solutions. The review focuses on rapid diagnostic tests, molecular diagnostic tools, and smartphone-based applications, analyzing their advantages, limitations, and potential impact on healthcare delivery. It also addresses the challenges and opportunities involved in deploying these technologies in resource-constrained environments. Key to their success is the need for interdisciplinary collaboration, sustainable funding models, and strong regulatory frameworks to ensure their effective integration into healthcare systems. The review emphasizes how point-of-care diagnostics can play a crucial role in reducing the burden of tropical diseases and advancing health equity on a global scale.</div></div>","PeriodicalId":72080,"journal":{"name":"Advances in biomarker sciences and technology","volume":"7 ","pages":"Pages 28-43"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143098985","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Etiological connections between initial COVID-19 and two rare infectious diseases","authors":"Zhengjun Zhang","doi":"10.1016/j.abst.2024.12.001","DOIUrl":"10.1016/j.abst.2024.12.001","url":null,"abstract":"<div><div>The origin of COVID-19 remains unclear despite extensive research. Theoretical models can simplify complex epigenetic landscapes by reducing vast methylation sites into manageable sets, revealing fundamental pathogen interactions that leap medical advances for the first time in tracing virus origin in the literature and practices. In our study, a max-logistic intelligence classifier analyzed 865,859 Infinium MethylationEPIC sites (CpGs), identifying eight CpGs that achieved 100 % accuracy in distinguishing COVID-19 patients from other respiratory disease patients and healthy controls. One CpG, cg07126281, linked to the SAMM50 gene, shares genetic ties with rare infectious diseases like Sennetsu fever and glanders, suggesting a potential connection between COVID-19 and these diseases, possibly transmitted through contaminated seafood or glanders-infected individuals. Identifying such links among 865,859 CpG sites is challenging, with a random correlation probability of less than one in ten million. However, the likelihood of finding meaningful associations with rare diseases lowers this probability to one in one hundred million, reinforcing the credibility of our findings. These results highlight the importance of investigating seafood markets and global supply chains in tracing COVID-19's origins and emphasize the need for ongoing biosafety and biosecurity measures to prevent future outbreaks.</div></div>","PeriodicalId":72080,"journal":{"name":"Advances in biomarker sciences and technology","volume":"7 ","pages":"Pages 8-20"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143099112","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Review on zebra fish as an alternative animal model for neurological studies","authors":"Khode Aniket Prakash ,&nbsp;Darshana Sunil Nagmoti ,&nbsp;Manali Sanjayswami Borkar ,&nbsp;Hiray Kuldeep Pannalal ,&nbsp;Nagaraju Bandaru","doi":"10.1016/j.abst.2025.08.005","DOIUrl":"10.1016/j.abst.2025.08.005","url":null,"abstract":"<div><div>Zebrafish (<em>Danio rerio</em>) have emerged as a powerful alternative animal model in neurological research due to their unique combination of genetic, anatomical, and physiological characteristics. Their transparent embryonic development, high genetic homology with humans, and well-characterized nervous system make them invaluable for studying neurological diseases and disorders. Zebrafish offer practical advantages such as rapid reproduction, cost-effectiveness, and suitability for high-throughput screening. They have been extensively utilized to investigate neurodevelopmental disorders, neurodegenerative diseases like Parkinson's and Alzheimer's, and epilepsy. Moreover, their amenability to genetic manipulation enables precise modeling of human neurological conditions. Behavioral assays in zebrafish provide insights into cognitive, motor, and emotional functions, which can be quantified to study disease phenotypes and therapeutic interventions. Recent advances in imaging techniques, such as live imaging of neuronal activity using calcium indicators, have further enhanced their utility. This review highlights the advantages of zebrafish as an alternative model system, discusses key findings from zebrafish-based neurological studies, and outlines challenges such as translating findings to mammalian systems. By consolidating current knowledge, this article emphasizes the pivotal role of zebrafish in advancing our understanding of neurological mechanisms and in developing novel treatments for brain disorders.</div></div>","PeriodicalId":72080,"journal":{"name":"Advances in biomarker sciences and technology","volume":"7 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145010287","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Network-based discovery of autophagy-regulating miRNA signatures in ovarian carcinoma","authors":"A. Shriraksha,&nbsp;V.R. Devaraj","doi":"10.1016/j.abst.2025.10.001","DOIUrl":"10.1016/j.abst.2025.10.001","url":null,"abstract":"<div><div>Ovarian cancer (OC) remains a leading cause of gynaecologic mortality due to lack of reliable early detection biomarkers. Given the emerging role of autophagy in tumor progression, this study explored the contribution of autophagy-associated miRNAs in OC using integrative bioinformatic approaches. Differential expression analysis of the E-TABM-975 dataset (3 normal, 125 tumor samples) identified 69 significantly altered miRNAs. Functional enrichment revealed their targets were involved in key pathways such as PI3K–AKT, MAPK, endocytosis, and autophagy regulation. Network analysis highlighted hub miRNAs (miR-340-5p, miR-106b-5p, miR-144-5p) interacting with autophagy-related genes (PTEN, MAP1B). A Random Forest model trained on E-TABM-975 achieved 99.22 % accuracy, and independent validation using E-TABM-343 (15 normal, 69 tumor) confirmed strong generalization (100 % accuracy). While most miRNAs exhibited consistent expression trends across datasets, a few discordant cases likely reflect dataset-specific variation. Limited availability of large cohorts with matched normal tissues remains a major constraint. The study provides a computational framework for identifying autophagy-related miRNAs with diagnostic relevance and outlines a phased experimental validation strategy to advance these findings toward translational applicability.</div></div>","PeriodicalId":72080,"journal":{"name":"Advances in biomarker sciences and technology","volume":"7 ","pages":"Pages 380-393"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145319636","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"CAR-T and nanotechnology: A comparative Perspective on autoimmune disease and cancer","authors":"A. Pavithra ,&nbsp;C. Ragavendran","doi":"10.1016/j.abst.2025.03.002","DOIUrl":"10.1016/j.abst.2025.03.002","url":null,"abstract":"<div><div>Nanotechnology has emerged as a key transformative force in upgrading Chimeric Antigen Receptor T-cell (CAR-T) from generation to generation in cancer and autoimmune treatment. Nanotechnology-aided CAR-T therapy has shown its ability to overcome various challenges in contemporary CAR-T therapy. The comparative analysis of CAR-T and its applications in cancer and autoimmune diseases focuses on target specificity, with immune cells being used as “chaperones” for nanoparticles, Immunosuppressibility by modifying microarchitecture, prolonged cell viability, and other nanotechnological modifications has been briefly discussed. The latest and smartest innovations, such as nano-enzymes linked CAR, stimuli-responsive nanoparticles, nano-based dual-targeting CAR structures, and nano-cargos, have upgraded CAR-T therapy to its latest advancements. Despite regulatory compliance, and cost of production and utility of Nano-CAR-T can be overcome by the use of green nanotechnology. The aid of advancements in AIs, software, MLs etc offers promising solutions to hurdles in scalability. A number of clinical and preclinical trials in the last few years have been explained to highlight the current status of Nano-CAR-T in present-day treatment and for a promising future. This review emphasizes the novel role of nanotechnology in shaping the future of advanced CAR-T therapy, paving the way for milestones in medical research.</div></div>","PeriodicalId":72080,"journal":{"name":"Advances in biomarker sciences and technology","volume":"7 ","pages":"Pages 124-137"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143790815","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification of bipolar disorder related biomarkers, signaling pathways and potential therapeutic compounds based on bioinformatics methods and molecular docking technology","authors":"Basavaraj Vastrad ,&nbsp;Shivaling Pattanashetti ,&nbsp;Chanabasayya Vastrad","doi":"10.1016/j.abst.2025.08.004","DOIUrl":"10.1016/j.abst.2025.08.004","url":null,"abstract":"<div><div>Bipolar disorder (BD), also known as psychiatric disorder, affects millions of people all over the world. The aim of this investigation was to screen and verify hub genes involved in BD as well as to explore potential molecular mechanisms. The next generation sequencing (NGS) dataset GSE124326 was downloaded from the Gene Expression Omnibus (GEO) database, which contained 480 samples, including 240 BD and 240 normal controls. Differentially expressed genes (DEGs) were filtered and subjected to gene ontology (GO) and pathway enrichment analyses. A Protein-Protein Interaction (PPI) network and modules were constructed and analyzed. We predicted regulatory miRNAs and TFs of hub-genes through miRNet and NetworkAnalyst online database. Drug predicted for BD treatment was screened out from the DrugBank through NetworkAnalyst. Molecular docking studies were carried out for predicting novel drug molecules. Receiver operating characteristic curve (ROC) curves was drawn to elucidate the diagnostic value of hub genes. In this investigation, total of 957 DEGs, including 477 up regulated and 480 down regulated genes. The GO and pathway enrichment analyses of the DEGs showed that the up regulated genes were enriched in the neutrophil degranulation, immune system, transport, cytoplasm and enzyme regulator activity, and the down regulated genes were enriched in extracellular matrix organization, diseases of metabolism, multicellular organismal process, cell periphery and metal ion binding. We screened hub genes include UBB, UBE2D1, TUBA1A, RPL11, RPS24, NOTCH3, CAV1, CNBD2, CCNA1 and MYH11. We also predicted miRNAs, TFs and drugs include hsa-mir-8085, hsa-mir-4514, HMG20B, STAT3, phenserine and roflumilast. Molecular docking technology screened out three small molecule compounds, including Kakkalide, Divaricatol and Brucine small molecule compounds. The current investigation illustrates a characteristic NGS data in BD, which might contribute to the interpretation of the progression of BD and provide novel biomarkers and therapeutic targets for BD.</div></div>","PeriodicalId":72080,"journal":{"name":"Advances in biomarker sciences and technology","volume":"7 ","pages":"Pages 261-319"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144925605","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Application of Generative Adversarial Networks on RNASeq data to uncover COVID-19 severity biomarkers","authors":"Yvette K. Kalimumbalo ,&nbsp;Rosaline W. Macharia ,&nbsp;Peter W. Wagacha","doi":"10.1016/j.abst.2025.01.002","DOIUrl":"10.1016/j.abst.2025.01.002","url":null,"abstract":"<div><h3>Background</h3><div>The COVID-19 pandemic has highlighted the need for reliable biomarkers to predict disease severity and guide treatment strategies. However, the analysis of RNASeq data for biomarker discovery using machine learning is constrained by limited sample sizes, primarily due to cost and privacy considerations. In this study, we applied Generative Adversarial Networks (GANs) to RNASeq data in the process of identifying biomarkers associated with COVID-19 severity.</div></div><div><h3>Methods</h3><div>RNASeq data from COVID-19 patients, along with severity metadata, were collected from the GEO database. Differential expression analysis was conducted and GAN models were trained to augment the original dataset. This enhanced subsequent machine learning models’ robustness and accuracy for biomarker discovery. Feature selection using Recursive Feature Elimination with Cross-Validation (RFECV) identified key biomarkers on cGAN- and cWGAN-augmented datasets.</div></div><div><h3>Results</h3><div>Several key biomarkers significantly associated with disease severity were identified. Gene Ontology Enrichment analysis revealed upregulation of neutrophil degranulation and downregulation of T-cell activity, consistent with previous findings. The ROC analysis using a Random Forest machine learning model and the five most important biomarkers (CCDC65, ZNF239, OTUD7A, CEP126, and TCTN2) achieved high accuracy (AUC: 0.98, Acc: 0.94) in predicting disease severity. These genes are associated with processes such as cilium assembly, IFN activation, and NF-kB pathway suppression.</div></div><div><h3>Conclusions</h3><div>Our results demonstrate that GANs can effectively augment RNASeq data, leading to consistent findings that align with known mechanisms and providing new insights into severe COVID-19 transcriptional responses. Further experimental validation is needed to confirm the applicability of these biomarkers in diverse populations.</div></div>","PeriodicalId":72080,"journal":{"name":"Advances in biomarker sciences and technology","volume":"7 ","pages":"Pages 44-58"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143098984","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Clinical features and predictive model for invasive pulmonary fungal infections in hematologic disorders","authors":"Jun Wang ,&nbsp;Xuefeng He ,&nbsp;Feng Chen ,&nbsp;Xiao Ma ,&nbsp;Daxiong Zeng ,&nbsp;Junhong Jiang","doi":"10.1016/j.abst.2025.02.001","DOIUrl":"10.1016/j.abst.2025.02.001","url":null,"abstract":"<div><h3>Objective</h3><div>This study was to investigate the clinical features of hematological disorders complicated by invasive pulmonary fungal infections and identify factors affecting treatment outcomes, with the aim of developing a predictive model.</div></div><div><h3>Methods</h3><div>Clinical data were collected from patients with hematological disorders and invasive pulmonary fungal infections between January 2020 and June 2023. Based on metagenomics next generation sequencing (mNGS) of bronchoalveolar lavage fluid (BALF), patients were categorized into three groups: <em>Candida</em>, <em>Mucor</em>, <em>and Aspergillus</em>. General conditions, clinical features, treatments, and outcomes were compared. Treatment outcomes were assessed two months after therapy and classified as either improved or not improved. Factors influencing outcomes were analyzed, and a risk prediction model for treatment failure was developed.</div></div><div><h3>Results</h3><div>A total of 89 patients with hematological diseases and invasive pulmonary fungal infections were included: 26 with <em>Candida</em>, 25 with <em>Mucor, and</em> 38 with <em>Aspergillus</em>. Significant differences were observed between groups in long-term corticosteroid use, hematological disease outcomes, neutropenia duration, treatment duration, central venous catheter placement, galactomannan (GM) test results, CD4⁺ T-cell count, and clinical manifestations. After two months of antifungal therapy, improvement rates were 96.15 % for <em>Candida</em>, 76.00 % for <em>Mucor</em>, and 63.16 % for <em>Aspergillus</em>. Logistic regression analysis identified elevated platelet count (OR = 0.9823, 95%CI: 0.9663–0.9945), D-dimer (OR = 1.2130, 95%CI: 1.0544–1.4934), C-reactive protein (OR = 1.0066, 95%CI: 1.0026–1.0111) and medication adjustments based on mNGS results (OR = 0.0495, 95%CI: 0.0108–0.1624) as significant prognostic factors. A nomogram prediction model based on these factors demonstrated good discrimination with a C-index of 0.86.</div></div><div><h3>Conclusion</h3><div>The clinical features and treatment outcomes differ among fungal types in patients with hematological disorders and invasive pulmonary fungal infections. The nomogram prediction model, incorporating platelet count, D-dimer, C-reactive protein and mNGS-guided therapy adjustments, offers robust predictive performance for two-month treatment outcomes.</div></div>","PeriodicalId":72080,"journal":{"name":"Advances in biomarker sciences and technology","volume":"7 ","pages":"Pages 86-94"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143471421","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of toxicity and antioxidant activities of various crude extracts of leaves and stems of Zygophyllum simplex","authors":"Noha Maher Galal ,&nbsp;Salem Said Al Touby ,&nbsp;Yahya Bin Abdullah Alrashdi ,&nbsp;Mohammad Amzad Hossain","doi":"10.1016/j.abst.2024.11.003","DOIUrl":"10.1016/j.abst.2024.11.003","url":null,"abstract":"<div><div><em>Zygophyllum simplex</em> (<em>Z</em>. <em>simplex</em>) is a plant that has been used for a long time for the treatment of human diseases. Therefore, this present research study aims to prepare various plant extracts and screen their antioxidant and cytotoxic activities. To attain the present objectives, different crude extracts were prepared from the leaves and stems of <em>Z. simplex</em> by using a maceration method. The activities of antioxidant and cytotoxic were prepared from aerial crude extracts of <em>Z. simplex</em> which were determined by 2,2-diphenyl-1-1-picrylhydrazyl (DPPH) and brine shrimp lethality (BSL) methods, respectively. All the prepared leaves and stems extracts of the selected plant at six different concentrations showed significant antioxidant activity against the DPPH method. The ethyl acetate crude extract showed the highest antioxidant activity and the lowest activity was in butanol extract. However, all the leaves and stems crude extracts of <em>Z. simplex</em> were prepared at different concentrations also showed promising cytotoxic activity against the BSL method. However, based on the antioxidant activity results, the ethyl acetate extract was selected for the isolation of bioactive compounds by using the column chromatographic method. The ethyl acetate was purified by using column chromatography in which different ratios of mobile phase (dichlorometane: methanol) were used. A series of test tubes were collected with a volume of 3 mL and depending on the similar retention mobility (Rf) behavior a total of twelve fractions were prepared. Similarly, the antioxidant activity of the obtained twelve fractions from column chromatography was determined by the same DPPH method. All the fractions showed significant antioxidant activity. Among the fractions from the column, fraction 6 give the highest antioxidant activity and the lowest was fraction 1. In conclusion, all the leaves and stems showed encouraging activities against DPPH and the fraction with the highest antioxidant activity could be used as a natural antioxidant to prevent cell damage.</div></div>","PeriodicalId":72080,"journal":{"name":"Advances in biomarker sciences and technology","volume":"7 ","pages":"Pages 1-7"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143099099","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}