Advances in biomarker sciences and technology最新文献

{"title":"A mini review: Role of novel biomarker for kidney disease of future study","authors":"Palash Mitra ,&nbsp;Sahadeb Jana ,&nbsp;Suchismita Roy","doi":"10.1016/j.abst.2025.02.002","DOIUrl":"10.1016/j.abst.2025.02.002","url":null,"abstract":"<div><div>In the world, kidney disease is most common cause of death. Primary care physicians must conduct appropriate diagnosis, and management in order to avoid detrimental consequences linked to death as well as end-stage kidney disease. In this scenario biomarkers can detect renal pathology more accurately and early than currently known biomarkers, including serum creatinine, estimated glomerular filtration rate and urine albumin, they hold out hope for bettering the care of individuals with kidney illnesses. Nowadays, nephrology is concentrating extensively on finding novel indicators of acute stage of kidney disease in order to prevent further complications from chronic kidney disease as well as end-stage renal disease. The best treatment targets for a particular patient or illness context may also be determined with the use of proteomic and genomic biomarkers. Therefore, current advancements in the study of important biomarkers including tumor necrosis factor, transforming growth factor, interleukin −1, interleukin-18, nephrin, uromodulin, collagen, osteopontin, NGAL and Dickkopf-3 are linked to different aspects of renal injury. Prognosis and risk classification can be enhanced by a variety of proteome and genome biomarkers that are linked to different pathophysiological processes that follow renal damage.</div></div>","PeriodicalId":72080,"journal":{"name":"Advances in biomarker sciences and technology","volume":"7 ","pages":"Pages 65-75"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143428787","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":"Genomic analysis identifies an incipient signature to forecast imatinib resistance before start of treatment in patients with chronic myeloid leukemia","authors":"Rahul Mojidra ,&nbsp;Nilesh Gardi ,&nbsp;Bhausaheb Bagal ,&nbsp;Navin Khattry ,&nbsp;Anant Gokarn ,&nbsp;Sachin Punatar ,&nbsp;Rukmini Govekar","doi":"10.1016/j.abst.2025.01.004","DOIUrl":"10.1016/j.abst.2025.01.004","url":null,"abstract":"<div><div>The unprecedented success of tyrosine kinase inhibitor (TKI), imatinib, to induce remission in 86 % of chronic phase (CP) patients of chronic myeloid leukemia (CML) is undermined by drug resistance. Few patients have primary resistance and do not respond to imatinib, while majority of them who respond must continue treatment to sustain the remission. This continued treatment increases the possibility of developing secondary resistance and these resistant patients progress to the acute phase of blast crisis (BC) wherein the survival is 7–11 months. However, if the patients who are at risk of developing resistance, can be identified before start of treatment with imatinib, they can be assisted with better treatment strategies. To identify markers to forecast imatinib resistance we chose to study chromosomal aberrations (CAs), as they are associated with causation, progression as well as drug resistance in CML. In this study, genomic DNA from CD34⁺ cells, isolated from healthy controls and CML patients in CP and BC before start of treatment, were subjected to array comparative genomic hybridization (aCGH). The number of CAs on distinct chromosomes identified by genomic analysis in CML-CP and -BC patients, were able to segregate the patients as imatinib-sensitive and -resistant in cluster analysis. The CP patients who misclassified into predominantly imatinib-resistant BC cluster were found to develop resistance during treatment. We thus report an incipient genomic signature which can forecast development of secondary resistance and upon validation in large cohort of patients has the potential for clinical application.</div></div>","PeriodicalId":72080,"journal":{"name":"Advances in biomarker sciences and technology","volume":"7 ","pages":"Pages 59-64"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143378647","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":"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":"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":"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}

{"title":"Unraveling ankylosing spondylitis: Exploring the genetic and immunological factors and latest treatment innovations","authors":"Nilasree Hazra ,&nbsp;Sudeshna Sengupta ,&nbsp;Dipannita Burman ,&nbsp;Jyoti Sekhar Banerjee ,&nbsp;Malavika Bhattacharya","doi":"10.1016/j.abst.2024.12.002","DOIUrl":"10.1016/j.abst.2024.12.002","url":null,"abstract":"<div><div>Ankylosing spondylitis (AS) is a chronic inflammatory arthritis primarily affecting the spine and sacroiliac joints. Gut microbiota significantly affects ankylosing spondylitis (AS) pathophysiology. Environmental factors, like smoking, and genetic predispositions can worsen AS. Patients often have altered fecal microbiota, decreased Bacteroides and Lachnospiraceae, and increased Proteobacteria and Enterobacteriaceae. <em>Bacteroides coprophilus</em> and <em>Prevotella copri</em> are particularly enriched in AS. This condition is associated with the HLA-B27 genetic marker and involves various immunological cells and inflammatory cytokines. To develop more effective treatments, research is ongoing to identify specific signaling pathways and genetic markers associated with AS.Gender prevalence of AS is now more evenly distributed, with women experiencing longer diagnostic delays and increased disease activity. Treatment regimens and responses to medication may vary between genders. Some case studies suggest that an Ayurvedic approach, including Panchakarma treatments and specific Ayurvedic medications, may be beneficial in managing AS. HLA-B27 and non-HLA genes such as IL23R, ERAP1, and RUNX3 are linked to AS susceptibility. The Th17 lymphocyte system, associated with IL23R, plays a role in AS pathogenesis, highlighting potential treatment targets. Over 100 genes related to AS were identified in genome-wide association studies, many connected to IL-23-driven inflammation and antigen processing. AS is regulated by various immunological cells, and changes in bone structure are caused by the interaction of immune cells with bone cells. Ankylosing spondylitis (AS) involves inflammatory cytokines like IL-1β IL-17 and IL-23. The immune system plays a crucial role in the disease, with certain proteins linked to AS risk. However, further research is needed to determine the effectiveness of this approach.</div></div>","PeriodicalId":72080,"journal":{"name":"Advances in biomarker sciences and technology","volume":"7 ","pages":"Pages 21-27"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143099100","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":"“MiRNA based target identification of TNFα gene in nephrotic syndrome”","authors":"Praveenkumar Kochuthakidiyel Suresh ,&nbsp;Yogalakshmi Venkatachalapathy ,&nbsp;Sarenya Anandaraj ,&nbsp;Nandita Ganesh ,&nbsp;Dharshini Sanker ,&nbsp;Mohana Priya C.D.","doi":"10.1016/j.abst.2025.01.003","DOIUrl":"10.1016/j.abst.2025.01.003","url":null,"abstract":"<div><h3>Background</h3><div>Nephrotic syndrome (NS) can be caused by various underlying kidney conditions. In most cases, the exact cause of NS is unknown, although it may be related to the body's immune system malfunctioning. Recent studies suggested that <em>TNFα</em> gene contributes significantly to the progression of nephrotic syndrome patients. This study investigates the role of <em>TNFα</em> gene in nephrotic syndrome by studying gene interactions, co-expressions and network biological approaches to predict the miRNA associated with <em>TNFα</em> gene as a biomarker in nephrotic syndrome patients. We conduct a detailed study and identify the <em>TNFα</em> associated genes involved in nephrotic syndrome using Genecard, NCBI GEO, Enrichr and String database. Based on the co-expression and network-based studies we identified a list of gene along with <em>TNFα</em> gene and predict the miRNA pattern associated with each gene. Hub miRNA is predicted as a biomarker for NS. We predict a panel of Mirna by network-based approach, hsa-miR-130a-3p,hsa-miR-130b-3p,hsa-miR-181a-2-3p,hsa-miR-301a-3p,miR-301b-3p,hsa-miR-3666,hsa-miR-4295,hsa-miR-4310,hsa-miR-6835–5p,hsa-miR-7157–5p.There is a growing body of evidence suggesting the utility of miRNAs as biomarkers for nephrotic syndrome (NS). The enrichment and co expression analysis suggest involved in the progression of various cancers especially <em>BRACA1 AND BRACA2</em>. MiRNA-based target prediction is an emerging tool to forecast progressive markers for identifying steroid-resistant nephrotic syndrome (SRNS) patients and evaluating the efficacy of drugs used in treatment. Based on our analysis, cancer associated genes and miRNAs expressed more. Nevertheless, further analysis is imperative to uncover unknown factors causing NS and its association with cancer progression and development.</div></div>","PeriodicalId":72080,"journal":{"name":"Advances in biomarker sciences and technology","volume":"7 ","pages":"Pages 76-85"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143445912","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":"Faecal microbial transplant","authors":"Onifade Isreal Ayobami, Oluwatomiwa Jubilee Sunbare-Funto, Chinedu Endurance Mbah, O. Ajibade, O. Oyawoye, A. Aborode, S. C. Ogunleye, A. Jamiu, Basit Bolarinwa, Mosope F. Abanikannda, Zainab Tiamiyu, A. R. Idowu, O. Ige, Opara Julia Kelechi, Jeremiah I. Abok, Eniola A. Lawal, Ibude Jane Aruorivwooghene, Adekunle Fatai Adeoye, Olowo Roqeebah, Emmanuel Akinloye Ojewole, R. Adesola","doi":"10.1016/j.abst.2024.02.001","DOIUrl":"https://doi.org/10.1016/j.abst.2024.02.001","url":null,"abstract":"","PeriodicalId":72080,"journal":{"name":"Advances in biomarker sciences and technology","volume":"38 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139817822","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}