ZIKV is a public health threat causing neurological complications such as microcephaly and Guillain-Barre syndrome, with the additional risk of sexual transmission. The absence of FDA-approved drugs or vaccines for ZIKV, highlight the immediate requirement for potential therapeutics. A potential target for antiviral drug development is the NS2B-NS3 protease which is a critical enzyme in the replication and maturation of ZIKV. Here, we report the inhibitory activity of tripeptide compounds for this protease via molecular docking and molecular dynamics (MD) study. The docking studies were further followed by a 200 ns MD simulation to investigate the stability and binding mode of the inhibitor within the active site of protease. The simulation revealed that, the complex remains stable with lower root mean square deviation RMSD and higher root mean square fluctuation (RMSF) values and showed strong ligand-protein interaction. Further investigation of torsion angles in the ligand and secondary structural changes in the protease support to the viability of these tripeptide inhibitors as anti-viral agents. The results obtained in this study suggest that tripeptide-derived inhibitors of ZIKV may be applied as potential leads for developing novel therapies against the ZIKV, indicating a potential direction for future drug discovery and clinical treatments.
{"title":"In silico screening of tripeptide inhibitors reveals potential lead compounds for targeting zika virus NS2B-NS3 protease","authors":"Farhan Ullah , Wajeeha Rahman , Anees Ullah , Shahid Ullah , Sheng Wang","doi":"10.1016/j.abst.2025.11.001","DOIUrl":"10.1016/j.abst.2025.11.001","url":null,"abstract":"<div><div>ZIKV is a public health threat causing neurological complications such as microcephaly and Guillain-Barre syndrome, with the additional risk of sexual transmission. The absence of FDA-approved drugs or vaccines for ZIKV, highlight the immediate requirement for potential therapeutics. A potential target for antiviral drug development is the NS2B-NS3 protease which is a critical enzyme in the replication and maturation of ZIKV. Here, we report the inhibitory activity of tripeptide compounds for this protease via molecular docking and molecular dynamics (MD) study. The docking studies were further followed by a 200 ns MD simulation to investigate the stability and binding mode of the inhibitor within the active site of protease. The simulation revealed that, the complex remains stable with lower root mean square deviation RMSD and higher root mean square fluctuation (RMSF) values and showed strong ligand-protein interaction. Further investigation of torsion angles in the ligand and secondary structural changes in the protease support to the viability of these tripeptide inhibitors as anti-viral agents. The results obtained in this study suggest that tripeptide-derived inhibitors of ZIKV may be applied as potential leads for developing novel therapies against the ZIKV, indicating a potential direction for future drug discovery and clinical treatments.</div></div>","PeriodicalId":72080,"journal":{"name":"Advances in biomarker sciences and technology","volume":"8 ","pages":"Pages 34-43"},"PeriodicalIF":0.0,"publicationDate":"2025-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145737011","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}
Pub Date : 2025-11-17DOI: 10.1016/j.abst.2025.11.007
P. Karthika , M. Premkumar
Cervical cancer has an extreme effect on women's health worldwide, recognized as the 4th most significant contributor to cancer fatalities among female. World Health Organization (WHO) states that there was on 660,000 new reports and 350,000 death occurred. Detecting the disease early can lead to a significant decrease in the death rate up to 80 %. Currently, doctors diagnose cervical cancer by examining cervical biopsies through Pap smears and colposcopy images. However this techniques is time-intensive, taking up to several hours per case and susceptible to misdiagnosis and diagnostic error between 10 and 30 %.Deep learning has illustrated significant potential for addressing biomedical challenges such as analysis of medical images, disease forecasting, and image partitioning. AI-powered diagnostic methods utilizing deep learning models–such as CNNs, DenseNets, and U-Nets—have achieved classification accuracies exceeding 95 % on datasets like Herlev and SIPaKMeD. This paper surveys diverse deep learning strategies that were implemented for the identification and analysis of cervical carcinoma, emphasizing their performance metrics, datasets and clinical applicability.
{"title":"An in-depth exploration of CNN-based deep learning models in cervical carcinoma analysis","authors":"P. Karthika , M. Premkumar","doi":"10.1016/j.abst.2025.11.007","DOIUrl":"10.1016/j.abst.2025.11.007","url":null,"abstract":"<div><div>Cervical cancer has an extreme effect on women's health worldwide, recognized as the 4th most significant contributor to cancer fatalities among female. World Health Organization (WHO) states that there was on 660,000 new reports and 350,000 death occurred. Detecting the disease early can lead to a significant decrease in the death rate up to 80 %. Currently, doctors diagnose cervical cancer by examining cervical biopsies through Pap smears and colposcopy images. However this techniques is time-intensive, taking up to several hours per case and susceptible to misdiagnosis and diagnostic error between 10 and 30 %.Deep learning has illustrated significant potential for addressing biomedical challenges such as analysis of medical images, disease forecasting, and image partitioning. AI-powered diagnostic methods utilizing deep learning models–such as CNNs, DenseNets, and U-Nets—have achieved classification accuracies exceeding 95 % on datasets like Herlev and SIPaKMeD. This paper surveys diverse deep learning strategies that were implemented for the identification and analysis of cervical carcinoma, emphasizing their performance metrics, datasets and clinical applicability.</div></div>","PeriodicalId":72080,"journal":{"name":"Advances in biomarker sciences and technology","volume":"8 ","pages":"Pages 19-33"},"PeriodicalIF":0.0,"publicationDate":"2025-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145571865","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}
Pub Date : 2025-11-15DOI: 10.1016/j.abst.2025.11.002
Kiptoo K. Cosmas , Silas Kiruki , Olivia A. Njiri , Grace K. Nyambati , John Mokua Mose , Omwenga Isaac , Alfred Orina Isaac , James Nyabuga Nyariki
Amoxicillin and cotrimoxazole are among the most frequently prescribed antibiotics, yet their impact on gut microbiota and systemic physiology, particularly during early life, remains a critical concern. This study investigated the effects of these antibiotics on the gut microbiome and associated physiological and biochemical responses in young male Swiss mice (5 weeks old), serving as a model for infant exposure. Five experimental groups were employed: control, amoxicillin (9.62 mg/kg), cotrimoxazole (15 mg/kg), cotrimoxazole + amoxicillin, and cotrimoxazole + amoxicillin followed by probiotic administration. Parameters assessed included gut microbial composition, hematological indices, organ weights, liver and kidney function, cytokine profiles, oxidative stress markers, and histopathological alterations. Both antibiotics induced marked gut dysbiosis. Cotrimoxazole significantly increased leukocyte, neutrophil, lymphocyte, and monocyte counts, while amoxicillin caused thrombocytosis and cotrimoxazole induced thrombocytopenia; probiotic treatment normalized these effects. Amoxicillin reduced brain glutathione (GSH) levels, whereas cotrimoxazole decreased GSH in both liver and brain. Combined antibiotic exposure exacerbated GSH depletion and elevated nitric oxide (NO) and malondialdehyde (MDA) levels, effects mitigated by probiotics exposure. Co-exposure to cotrimoxazole and amoxicillin upregulated pro-inflammatory cytokines TNF-α and IFN-γ and increased serum markers of hepatic and renal injury (alanine-transaminases, alkaline phosphatases, Aspartate transaminases, creatinine, urea, uric acid). Histopathological analysis confirmed aggravated hepatic and renal damage under combined antibiotic exposure, which was markedly alleviated by probiotics. These findings demonstrate that amoxicillin and cotrimoxazole disrupt gut microbial balance, eliciting systemic oxidative, organ damage and inflammatory responses. Probiotic intervention confers significant protection, underscoring the need for cautious antibiotic use and microbiota-restorative strategies.
{"title":"Amoxicillin and cotrimoxazole-driven dysbiosis disrupted blood cell levels, cytokine balance and induced oxido-nitrosative stress in young mice","authors":"Kiptoo K. Cosmas , Silas Kiruki , Olivia A. Njiri , Grace K. Nyambati , John Mokua Mose , Omwenga Isaac , Alfred Orina Isaac , James Nyabuga Nyariki","doi":"10.1016/j.abst.2025.11.002","DOIUrl":"10.1016/j.abst.2025.11.002","url":null,"abstract":"<div><div>Amoxicillin and cotrimoxazole are among the most frequently prescribed antibiotics, yet their impact on gut microbiota and systemic physiology, particularly during early life, remains a critical concern. This study investigated the effects of these antibiotics on the gut microbiome and associated physiological and biochemical responses in young male Swiss mice (5 weeks old), serving as a model for infant exposure. Five experimental groups were employed: control, amoxicillin (9.62 mg/kg), cotrimoxazole (15 mg/kg), cotrimoxazole + amoxicillin, and cotrimoxazole + amoxicillin followed by probiotic administration. Parameters assessed included gut microbial composition, hematological indices, organ weights, liver and kidney function, cytokine profiles, oxidative stress markers, and histopathological alterations. Both antibiotics induced marked gut dysbiosis. Cotrimoxazole significantly increased leukocyte, neutrophil, lymphocyte, and monocyte counts, while amoxicillin caused thrombocytosis and cotrimoxazole induced thrombocytopenia; probiotic treatment normalized these effects. Amoxicillin reduced brain glutathione (GSH) levels, whereas cotrimoxazole decreased GSH in both liver and brain. Combined antibiotic exposure exacerbated GSH depletion and elevated nitric oxide (NO) and malondialdehyde (MDA) levels, effects mitigated by probiotics exposure. Co-exposure to cotrimoxazole and amoxicillin upregulated pro-inflammatory cytokines TNF-α and IFN-γ and increased serum markers of hepatic and renal injury (alanine-transaminases, alkaline phosphatases, Aspartate transaminases, creatinine, urea, uric acid). Histopathological analysis confirmed aggravated hepatic and renal damage under combined antibiotic exposure, which was markedly alleviated by probiotics. These findings demonstrate that amoxicillin and cotrimoxazole disrupt gut microbial balance, eliciting systemic oxidative, organ damage and inflammatory responses. Probiotic intervention confers significant protection, underscoring the need for cautious antibiotic use and microbiota-restorative strategies.</div></div>","PeriodicalId":72080,"journal":{"name":"Advances in biomarker sciences and technology","volume":"8 ","pages":"Pages 1-18"},"PeriodicalIF":0.0,"publicationDate":"2025-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145571904","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}
Pub Date : 2025-11-14DOI: 10.1016/j.abst.2025.11.005
Pipika Das , Riya Kar , Titli Panchali , Ananya Dutta , Manisha Phoujdar , Kuntal Ghosh , Shrabani Pradhan
Obesity is a condition of energy balance in which nutrient intake consistently exceeds energy expenditure, increasing the risk of various potentially fatal disorders. Docosapentaenoic acid (DPA) is an omega-3 fatty acid that has been reported to provide a number of health benefits. However, the effects of DPA on adipocyte differentiation are poorly understood. Linoelaidic acid (LA) is an isomer of linoleic acid that remains underexplored. The main aim of this investigation is to explore the role of linoelaidic acid and DPA ratio on lipid accumulation and AMPK pathway activation in 3T3-L1 cells. Differentiated adipocyte were treated with different ratio of fatty acids and performed cell viability assay, Oil Red O staining, gene expression and immunoblotting analysis. The fatty acids did not cause cytotoxicity in preadipocytes. Notably, DPA reduced lipid accumulation, suggesting its anti-adipogenic potential. Moreover, LA/DPA ratio also markedly increased the mRNA expression of genes associated with lipolysis, including peroxisome proliferator-activated receptor-α, carnitine palmitoyl transferase-1, adiponectin, and lipoprotein lipase, while inhibiting those involved in lipogenesis, such as leptin, sterol regulatory element binding protein-1c and fatty acid synthase. In addition, LA/DPA mixture strongly suppressed inflammation induced by TNF-α, IL-6, IL-1β. On mechanistic levels, LA/DPA in ratio of 1:1 and 4:1 regulates the AMPK signaling by reducing phosphorylation levels of PPAR-γ, C/EBP-α, acetyl-CoA carboxylase, and stearoyl-CoA desaturase. These findings demonstrated that LA and DPA in combination can prevent 3T3-L1 preadipocytes from differentiating, which implies it may be used therapeutically to prevent obesity.
{"title":"Mechanistic insights on effective ratio of Linoelaidic and Docosapentaenoic acid by modulating adipogenic and inflammatory biomarkers in 3T3-L1 preadipocytes","authors":"Pipika Das , Riya Kar , Titli Panchali , Ananya Dutta , Manisha Phoujdar , Kuntal Ghosh , Shrabani Pradhan","doi":"10.1016/j.abst.2025.11.005","DOIUrl":"10.1016/j.abst.2025.11.005","url":null,"abstract":"<div><div>Obesity is a condition of energy balance in which nutrient intake consistently exceeds energy expenditure, increasing the risk of various potentially fatal disorders. Docosapentaenoic acid (DPA) is an omega-3 fatty acid that has been reported to provide a number of health benefits. However, the effects of DPA on adipocyte differentiation are poorly understood. Linoelaidic acid (LA) is an isomer of linoleic acid that remains underexplored. The main aim of this investigation is to explore the role of linoelaidic acid and DPA ratio on lipid accumulation and AMPK pathway activation in 3T3-L1 cells. Differentiated adipocyte were treated with different ratio of fatty acids and performed cell viability assay, Oil Red O staining, gene expression and immunoblotting analysis. The fatty acids did not cause cytotoxicity in preadipocytes. Notably, DPA reduced lipid accumulation, suggesting its anti-adipogenic potential. Moreover, LA/DPA ratio also markedly increased the mRNA expression of genes associated with lipolysis, including peroxisome proliferator-activated receptor-α, carnitine palmitoyl transferase-1, adiponectin, and lipoprotein lipase, while inhibiting those involved in lipogenesis, such as leptin, sterol regulatory element binding protein-1c and fatty acid synthase. In addition, LA/DPA mixture strongly suppressed inflammation induced by TNF-α, IL-6, IL-1β. On mechanistic levels, LA/DPA in ratio of 1:1 and 4:1 regulates the AMPK signaling by reducing phosphorylation levels of PPAR-γ, C/EBP-α, acetyl-CoA carboxylase, and stearoyl-CoA desaturase. These findings demonstrated that LA and DPA in combination can prevent 3T3-L1 preadipocytes from differentiating, which implies it may be used therapeutically to prevent obesity.</div></div>","PeriodicalId":72080,"journal":{"name":"Advances in biomarker sciences and technology","volume":"8 ","pages":"Pages 102-117"},"PeriodicalIF":0.0,"publicationDate":"2025-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145840275","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}
Epilepsy is one of the most prevalent neurological disorders that negatively impacts patients' quality of life and poses a severe health risk. It is often characterized by recurrent brain seizures. A current method that involves monitoring these seizures is Electroencephalography, which allows for the scientific investigation of electrical impulses within the brain. In this research, we have used Artificial Intelligence and Machine Learning in the management of Epilepsy to evaluate electrical impulses within the brain, emphasizing the potential to significantly improve the quality of life of those who suffer from this disorder. The goal of this study is to propose a Deep Neural Network model that can predict early seizure detection of Epilepsy using Electroencephalography data from a control group in order to anticipate the frequency of episodes of the patient and provide accurate insights into when they might experience their symptoms. Additionally, our research aims to identify particular genes of interest with specific protein targets that are directly responsible for the changes in EEG values in the epileptic patients. After thorough examination of these proteins' therapeutic targets and ligands, a suitable ligand and protein were identified and docked. The purpose of the docking studies in the Machine Learning model gains valuable information about the genetic origin for the change in EEG values in Epileptic patients.
The integration of predictive modeling with in-silico drug discovery enhances both the diagnostic and therapeutic dimensions of epilepsy care. This dual-layered approach not only supports early warning systems but also opens avenues for personalized treatment strategies. Our study thus represents a step toward a more holistic, computationally driven framework for neurological disorder management. By bridging data-driven seizure prediction with molecular-level therapeutic exploration, this research contributes to precision medicine and highlights the potential of interdisciplinary computational approaches in tackling complex, treatment-resistant forms of epilepsy.
{"title":"Implementation of a disease trigger prediction model using AIML for early diagnosis of epilepsy","authors":"Aarohi Deshpande , Aarohi Gherkar , Avni Bhambure , Girish Shivhare , Shreyash Kolhe , Bhupendra Prajapati , Shama Mujawar","doi":"10.1016/j.abst.2025.07.001","DOIUrl":"10.1016/j.abst.2025.07.001","url":null,"abstract":"<div><div>Epilepsy is one of the most prevalent neurological disorders that negatively impacts patients' quality of life and poses a severe health risk. It is often characterized by recurrent brain seizures. A current method that involves monitoring these seizures is Electroencephalography, which allows for the scientific investigation of electrical impulses within the brain. In this research, we have used Artificial Intelligence and Machine Learning in the management of Epilepsy to evaluate electrical impulses within the brain, emphasizing the potential to significantly improve the quality of life of those who suffer from this disorder. The goal of this study is to propose a Deep Neural Network model that can predict early seizure detection of Epilepsy using Electroencephalography data from a control group in order to anticipate the frequency of episodes of the patient and provide accurate insights into when they might experience their symptoms. Additionally, our research aims to identify particular genes of interest with specific protein targets that are directly responsible for the changes in EEG values in the epileptic patients. After thorough examination of these proteins' therapeutic targets and ligands, a suitable ligand and protein were identified and docked. The purpose of the docking studies in the Machine Learning model gains valuable information about the genetic origin for the change in EEG values in Epileptic patients.</div><div>The integration of predictive modeling with in-silico drug discovery enhances both the diagnostic and therapeutic dimensions of epilepsy care. This dual-layered approach not only supports early warning systems but also opens avenues for personalized treatment strategies. Our study thus represents a step toward a more holistic, computationally driven framework for neurological disorder management. By bridging data-driven seizure prediction with molecular-level therapeutic exploration, this research contributes to precision medicine and highlights the potential of interdisciplinary computational approaches in tackling complex, treatment-resistant forms of epilepsy.</div></div>","PeriodicalId":72080,"journal":{"name":"Advances in biomarker sciences and technology","volume":"7 ","pages":"Pages 189-203"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144757957","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}
Pub Date : 2025-01-01DOI: 10.1016/j.abst.2025.05.001
Qianyun Ge , Peng Wang , Shang-jui Wang , Akshay Sood , Lingbin Meng , Cheryl Lee , Anil V. Parwani , Jenny Li , Xuefeng Liu
Bladder cancer (BCa) is a common urological malignancy with a high recurrence rate, often within 2 years of initial diagnosis and treatment. Due to this high recurrence, near all patients require cystoscopic surveillance, which is invasive, uncomfortable, and costly. The cost of surveillance makes this cancer the most expensive cancer per case among all cancer types in the US. Therefore, early detection of recurrence or assessment of patients’ response to treatment, particularly through non-invasive methods, is urgently needed. Since immune checkpoint inhibitors (ICIs) are widely used in many clinical trials for BCa treatment, having non-invasive and reliable biomarkers to select appropriate patients for ICI therapies or predict their treatment responses would be invaluable. Here we summarized the potential applications of programmed death-ligand 1 (PD-L1) from urine or urine BCa cell samples in BCa clinical settings. We discuss the use of both the free form of PD-L1 in urine samples and the expression levels of PD-L1 on the BCa cells shed in urine samples. Free PD-L1 can be measured with flow cytometry or ELISA-based approaches, while detecting PD-L1 on BCa cell surface requires isolating the urine-derived cancer cells and analyzing them via flow cytometry. Furthermore, we discuss the promising future research areas of urinary PD-L1 (uPD-L1) in bladder cancer, with a particular focus on the combination of conditional reprogramming cells (CRCs) technology and uPD-L1 studies, followed by an overview of several ongoing research topics. Based on current findings, uPD-L1 shows great potential as a versatile biomarker; however, further research is urgently needed to facilitate its translation into clinical applications.
{"title":"Urine PD-L1 as a non-invasive biomarker for immune checkpoint inhibitor (ICI) therapy in bladder cancer","authors":"Qianyun Ge , Peng Wang , Shang-jui Wang , Akshay Sood , Lingbin Meng , Cheryl Lee , Anil V. Parwani , Jenny Li , Xuefeng Liu","doi":"10.1016/j.abst.2025.05.001","DOIUrl":"10.1016/j.abst.2025.05.001","url":null,"abstract":"<div><div>Bladder cancer (BCa) is a common urological malignancy with a high recurrence rate, often within 2 years of initial diagnosis and treatment. Due to this high recurrence, near all patients require cystoscopic surveillance, which is invasive, uncomfortable, and costly. The cost of surveillance makes this cancer the most expensive cancer per case among all cancer types in the US. Therefore, early detection of recurrence or assessment of patients’ response to treatment, particularly through non-invasive methods, is urgently needed. Since immune checkpoint inhibitors (ICIs) are widely used in many clinical trials for BCa treatment, having non-invasive and reliable biomarkers to select appropriate patients for ICI therapies or predict their treatment responses would be invaluable. Here we summarized the potential applications of programmed death-ligand 1 (PD-L1) from urine or urine BCa cell samples in BCa clinical settings. We discuss the use of both the free form of PD-L1 in urine samples and the expression levels of PD-L1 on the BCa cells shed in urine samples. Free PD-L1 can be measured with flow cytometry or ELISA-based approaches, while detecting PD-L1 on BCa cell surface requires isolating the urine-derived cancer cells and analyzing them via flow cytometry. Furthermore, we discuss the promising future research areas of urinary PD-L1 (uPD-L1) in bladder cancer, with a particular focus on the combination of conditional reprogramming cells (CRCs) technology and uPD-L1 studies, followed by an overview of several ongoing research topics. Based on current findings, uPD-L1 shows great potential as a versatile biomarker; however, further research is urgently needed to facilitate its translation into clinical applications.</div></div>","PeriodicalId":72080,"journal":{"name":"Advances in biomarker sciences and technology","volume":"7 ","pages":"Pages 172-179"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144178498","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":"Corrigendum to “Paper based molecularly imprinted SERS substrate for early detection of lysophosphatidic acid in ovarian cancer” [Advan Biomarker Sci Technol. 6 (2024) 46–58 https://doi.org/10.1016/j.abst.2024.03.001]","authors":"Nazia Tarannum , Deepak Kumar , Akanksha Yadav , Anil K. Yadav","doi":"10.1016/j.abst.2025.09.003","DOIUrl":"10.1016/j.abst.2025.09.003","url":null,"abstract":"","PeriodicalId":72080,"journal":{"name":"Advances in biomarker sciences and technology","volume":"7 ","pages":"Page 394"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145361989","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}
Pub Date : 2025-01-01DOI: 10.1016/j.abst.2025.02.002
Palash Mitra , Sahadeb Jana , Suchismita Roy
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.
{"title":"A mini review: Role of novel biomarker for kidney disease of future study","authors":"Palash Mitra , Sahadeb Jana , 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}
Pub Date : 2025-01-01DOI: 10.1016/j.abst.2025.11.004
Sarah Esmaeilpour , Farshad Sheikhesmaili , Mohammad Moradzad , Bijan Noori , Mohammad Abdi , Zakaria Vahabzadeh
Background and objectives
Non-alcoholic fatty liver disease (NAFLD) encompasses a spectrum of liver disorders ranging from simple steatosis to steatohepatitis. The development of non-invasive diagnostic tools is crucial for management of liver diseases. MicroRNAs (miRNAs) have emerged as potential biomarkers for NAFLD diagnostic. This case–control pilot study included 30 patients with NAFLD and 30 healthy controls. Our findings indicate promising potential of miR-34a, miR-192, and miR-122 as non-invasive biomarkers for NAFLD.
Materials and methods
We enrolled 30 confirmed NAFLD patients (grade 3) and 30 healthy individuals as controls. General laboratory tests were assessed in both groups. MicroRNA expression levels were quantified using RT-qPCR, and data were analyzed using R software. Diagnostic table was assessed using the area under the ROC curve and 95 % confidence intervals.
Results
Significantly elevated serum levels of miR-34a and miR-192 were observed in NAFLD patients compared to controls (P = 0.002 and P < 0.0001, respectively), whereas miR-122 was downregulated (P < 0.001). The combination of miR-34a, miR-192, and miR-122 showed a high apparent diagnostic performance, which should be interpreted with caution given the limited sample size.
Conclusion
This pilot study suggests that serum miR-34a, miR-192, and miR-122 may serve as promising indicator for NAFLD patients.
{"title":"The diagnostic value of miRNAs combination for Kurdish NAFLD patients","authors":"Sarah Esmaeilpour , Farshad Sheikhesmaili , Mohammad Moradzad , Bijan Noori , Mohammad Abdi , Zakaria Vahabzadeh","doi":"10.1016/j.abst.2025.11.004","DOIUrl":"10.1016/j.abst.2025.11.004","url":null,"abstract":"<div><h3>Background and objectives</h3><div>Non-alcoholic fatty liver disease (NAFLD) encompasses a spectrum of liver disorders ranging from simple steatosis to steatohepatitis. The development of non-invasive diagnostic tools is crucial for management of liver diseases. MicroRNAs (miRNAs) have emerged as potential biomarkers for NAFLD diagnostic. This case–control pilot study included 30 patients with NAFLD and 30 healthy controls. Our findings indicate promising potential of miR-34a, miR-192, and miR-122 as non-invasive biomarkers for NAFLD.</div></div><div><h3>Materials and methods</h3><div>We enrolled 30 confirmed NAFLD patients (grade 3) and 30 healthy individuals as controls. General laboratory tests were assessed in both groups. MicroRNA expression levels were quantified using RT-qPCR, and data were analyzed using R software. Diagnostic table was assessed using the area under the ROC curve and 95 % confidence intervals.</div></div><div><h3>Results</h3><div>Significantly elevated serum levels of miR-34a and miR-192 were observed in NAFLD patients compared to controls (<em>P</em> = 0.002 and <em>P</em> < 0.0001, respectively), whereas miR-122 was downregulated (<em>P</em> < 0.001). The combination of miR-34a, miR-192, and miR-122 showed a high apparent diagnostic performance, which should be interpreted with caution given the limited sample size.</div></div><div><h3>Conclusion</h3><div>This pilot study suggests that serum miR-34a, miR-192, and miR-122 may serve as promising indicator for NAFLD patients.</div></div>","PeriodicalId":72080,"journal":{"name":"Advances in biomarker sciences and technology","volume":"7 ","pages":"Pages 405-413"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145571220","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}
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.
{"title":"Genomic analysis identifies an incipient signature to forecast imatinib resistance before start of treatment in patients with chronic myeloid leukemia","authors":"Rahul Mojidra , Nilesh Gardi , Bhausaheb Bagal , Navin Khattry , Anant Gokarn , Sachin Punatar , 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<sup>+</sup> 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}
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