A review on emerging diagnostic assay for viral detection: the case of avian influenza virus.

Biotechnology-based detection systems and sensors are in use for a wide range of applications in biomedicine, including the diagnostics of viral pathogens. In this review, emerging detection systems and their applicability for diagnostics of viruses, exemplified by the case of avian influenza virus, are discussed. In particular, nano-diagnostic assays presently under development or available as prototype and their potentials for sensitive and rapid virus detection are highlighted.

The implementation of artificial neural networks for the multivariable optimization of mesoporous NiO nanocrystalline: biodiesel application.

In the present research, artificial neural network (ANN) modelling was utilized to determine the relative importance of effective variables to achieve optimum specific surface areas of a synthesized catalyst. Initially, carbonaceous nanocrystalline mesoporous NiO core-shell solid sphere composites were produced by applying incomplete carbonized glucose (ICG) as the pore directing agent and polyethylene glycol (PEG; 4000) as the surfactant via a hydrothermal-assisted method. The Brunauer-Emmett-Teller (BET) model was applied to ascertain the textural characteristics of the as-prepared mesoporous NiO catalyst. The effects of several key parameters such as metal ratio, surfactant and template concentrations, and calcination temperature on the prediction of the surface areas of the as-synthesized catalyst were evaluated. In order to verify the optimum hydrothermal fabrication conditions, ANN was trained over five different algorithms (QP, BBP, IBP, LM, and GA). Among five different algorithms, LM-4-7-1 representing 4 nodes in the input layer, 7 nodes in the hidden layer, and 1 node in the output layer was verified as the optimum model due to its optimum numerical properties. According to the modelling study, the calcination temperature demonstrated the most effective parameter, while the ICG concentration indicated the least effect. By verifying the optimum hydrothermal fabrication conditions, the thermal decomposition of ammonium sulphate (TDAS) was applied to the functionalized surface areas and mesoporous walls by -SO3H functional groups. In addition, the catalytic performance and reusability of the produced mesoporous SO3H-NiO catalyst were evaluated via the transesterification of waste cooking palm oil, resulting in a methyl ester content of 97.4% and excellent stability for nine consecutive transesterification reactions without additional treatments.

Detection of Citrus tristeza virus by using fluorescence resonance energy transfer-based biosensor.

Due to the low titer or uneven distribution of Citrus tristeza virus (CTV) in field samples, detection of CTV by using conventional detection techniques may be difficult. Therefore, in the present work, the cadmium-telluride quantum dots (QDs) was conjugated with a specific antibody against coat protein (CP) of CTV, and the CP were immobilized on the surface of gold nanoparticles (AuNPs) to develop a specific and sensitive fluorescence resonance energy transfer (FRET)-based nanobiosensor for detecting CTV. The maximum FRET efficiency for the developed nano-biosensor was observed at 60% in AuNPs-CP/QDs-Ab ratio of 1:8.5. The designed system showed higher sensitivity and specificity over enzyme linked immunosorbent assay (ELISA) with a limit of detection of 0.13µgmL(-1) and 93% and 94% sensitivity and specificity, respectively. As designed sensor is rapid, sensitive, specific and efficient in detecting CTV, this could be envisioned for diagnostic applications, surveillance and plant certification program.

Development of sandwich-form biosensor to detect Mycobacterium tuberculosis complex in clinical sputum specimens.

Mycobacterium tuberculosis, the causing agent of tuberculosis, comes second only after HIV on the list of infectious agents slaughtering many worldwide. Due to the limitations behind the conventional detection methods, it is therefore critical to develop new sensitive sensing systems capable of quick detection of the infectious agent. In the present study, the surface modified cadmium-telluride quantum dots and gold nanoparticles conjunct with two specific oligonucleotides against early secretory antigenic target 6 were used to develop a sandwich-form fluorescence resonance energy transfer-based biosensor to detect M. tuberculosis complex and differentiate M. tuberculosis and M. bovis Bacille Calmette-Guerin simultaneously. The sensitivity and specificity of the newly developed biosensor were 94.2% and 86.6%, respectively, while the sensitivity and specificity of polymerase chain reaction and nested polymerase chain reaction were considerably lower, 74.2%, 73.3% and 82.8%, 80%, respectively. The detection limits of the sandwich-form fluorescence resonance energy transfer-based biosensor were far lower (10 fg) than those of the polymerase chain reaction and nested polymerase chain reaction (100 fg). Although the cost of the developed nanobiosensor was slightly higher than those of the polymerase chain reaction-based techniques, its unique advantages in terms of turnaround time, higher sensitivity and specificity, as well as a 10-fold lower detection limit would clearly recommend this test as a more appropriate and cost-effective tool for large scale operations.

Development of sandwich-form biosensor to detect Mycobacterium tuberculosis complex in clinical sputum specimens

Mycobacterium tuberculosis, the causing agent of tuberculosis, comes second only after HIV on the list of infectious agents slaughtering many worldwide. Due to the limitations behind the conventional detection methods, it is therefore critical to develop new sensitive sensing systems capable of quick detection of the infectious agent. In the present study, the surface modified cadmium-telluride quantum dots and gold nanoparticles conjunct with two specific oligonucleotides against early secretory antigenic target 6 were used to develop a sandwich-form fluorescence resonance energy transfer-based biosensor to detect M. tuberculosis complex and differentiate M. tuberculosis and M. bovis Bacille Calmette–Guerin simultaneously. The sensitivity and specificity of the newly developed biosensor were 94.2% and 86.6%, respectively, while the sensitivity and specificity of polymerase chain reaction and nested polymerase chain reaction were considerably lower, 74.2%, 73.3% and 82.8%, 80%, respectively. The detection limits of the sandwich-form fluorescence resonance energy transfer-based biosensor were far lower (10 fg) than those of the polymerase chain reaction and nested polymerase chain reaction (100 fg). Although the cost of the developed nanobiosensor was slightly higher than those of the polymerase chain reaction-based techniques, its unique advantages in terms of turnaround time, higher sensitivity and specificity, as well as a 10-fold lower detection limit would clearly recommend this test as a more appropriate and cost-effective tool for large scale operations.