Gene specific DNA based sensors have potential applications for rapid and real time monitoring of hybridization signal with the target nucleic acid of pathogens. Different types of DNA based sensors and their applications have been studied for rapid and accurate detection of pathogens causing human diseases. These sensors are based on surface plasmon resonance, quantum-dots, molecular beacons, piezoelectric and electrochemical etc. Curbing epidemics at an early stage is one of the massive challenges in healthcare systems. Timely detection of the causative organism may provide a solution to restrain mortality caused by the disease. With the advent of interdisciplinary sciences, bioelectronics has emerged as an effective alternative for disease diagnostics. Gene specific DNA sensors present themselves as cost-effective, sensitive and specific platforms for detection of disease causing pathogens. The mini review explores different transducer based sensors and their potential in diagnosis of acute and chronic diseases.
: Epithelial ovarian cancer (EOC) is a chronic and degenerative disease propelled by mutation in BRCA1/2 genes, familial history, smoking and polycystic ovary syndrome. Although lifetime risk of ovarian cancer is low, yet it is the fifth leading cause of cancer related deaths. Surprisingly, EOC represents 90% of all ovarian cancers, out of which 70% women are diagnosed with the malignancy at its advanced III-IV stages. Early detection may increase the life expectancy up to 5 years. Thus, it has become need of the hour to attain improvement of clinical outcomes of EOC and improve life expectancy of patients. Plethora of proteins in different biological fluids may serve as prospective identifiers for the disease. Over the years, accurate identification of proteins secreted by EOC cells has been perfected by in vitro and in silico state of art technologies. Multivariate test, consisting of histo-pathological data in combination with protein biomarker panel has paved way for enhanced and accurate assessment for EOC, still there is a chance of further improvement. This review encompasses the inputs made in ovarian cancer biomarker discovery and demonstrates their potential usefulness for design of early diagnostics of EOC.
Objective: Chronic kidney disease (CKD) is usually diagnosed by measuring the glomerular filtration rate (GFR), and diagnostics are still inadequate at the clinical level. Most of the diagnostic kits available estimate GFR rate by determining clearance of serum creatinine using various instrumentation generally available at hospitals. Serum creatinine is considered the major marker for renal deficiency disorders. In addition, it is also an indicator of muscle mass and dietary intake. Hence, the need for a more reliable marker for CKD arises. A low molecular weight protein cystatin C has been found to be a reliable biomarker for the detection of kidney function as it is solely filtered by the glomerulus and not secreted by renal tubules. Methods:The basic setup of the kit was designed using a syringe containing multiwalled carbon nanotube (MWCNT) conjugated protease. Casein beads were immersed in phosphate-buffered saline in the syringe. The glass/MWCNT/papain solid support was subsequently inserted into the syringe in such a way that the beads came in contact with the immobilized enzyme conjugate. The inhibitory action of cystatin C against protease forms the basis for the functioning of the kit. Results:Results indicated that papain while immobilization needs to be in dynamic conformation. At 37°C, papain gave better activity as compared to protein immobilized at 4°C. Fourier transformation infrared spectroscopy observations confirmed the physical adsorption on the MWCNTs. The experimentation confirmed the feasibility of using prototype for detection of cystatin C. Conclusion:The proposed alternate method may offer a cost effective solution to detection of CKD and its progression. Papain conjugated with MWCNT indicated its temperature and pH stability. The initial design of the diagnostic kit for the detection of CKD has shown to be successful with a good detection range corresponding to Stages I and II of CKD. Further testing needs to be done for the prototype using patient samples
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