Abstract: The book provides excellent information on well-established. Biosensors Based on Nanomaterials and Nanodevices links interdisciplinary research from leading experts to provide graduate students. Get this from a library! Biosensors based on nanomaterials and nanodevices. These problems, coupled with the ultrahigh sensitivity to temperature and ambient conditions, prevent this very accurate measurement technique from being popular for portable devices. In a biosensor, the sensing element that responds to the substance being measured is biological in nature.
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It has to be connected to a transducer of some sort, such that a visually observable signal can be recorded. At present, transducers that can be incorporated into the sensors are nanomaterials. The widespread interest in nanomaterials is driven by their many desirable properties; in particular, the ability to tailor the size and structure and hence the properties of nanomaterials offers excellent prospects for designing novel sensing systems and enhancing the performance of the biosensor. Conventional optical sandwich bioaffinity assays have the disadvantage of capturing only a small number of labels per binding event.
Nanoparticles can be custom-made for specific bioassays, and because of their small size, their properties are strongly influenced by the binding of target biomolecules.
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The driving force behind the use of nanoparticle-quantifying tags in optical bioassays has been addressing the limitations of organic fluorophores. Nanowires offer the best chance of creating robust, sensitive, and selective electrical detectors of biological binding events. Current flow in any one-dimensional system is extremely sensitive to minor perturbations, and in nanowires the current flows extremely close to the surface. The combination of the tunable conducting properties of semiconducting nanowires and the ability to bind analytes on their surface yields a direct, label-free electrical readout.
Carbon nanotubes are particularly exciting one-dimensional nanomaterials that have attracted considerable interest owing to their unique structure-dependent electronic and mechanical properties. Because of their high surface-to-volume ratio and novel electron transport properties, the electronic conductance of these nanostructures is strongly influenced by minor surface perturbations, such as those associated with binding of macromolecules.
Such one-dimensional materials thus offer the prospect of rapid real-time and sensitive label-free bioelectronic detection, and massive redundancy in nanosensor arrays.
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Membranes of various pore size, length, morphology, and density have been synthesized from diverse materials for size exclusion-based separation. To achieve this, materials with controllable pore diameter, length, and surface chemistry are needed. Selective capture requires two steps, ie, collection and immobilization. Membranes are well suited for this because of their enhanced surface interactions with the liquid being analyzed.
The overall sensitivity of any sensor depends on signal transduction and the mass transport effect. Miniaturization of a sensor increases the signal-to-noise ratio, an inherent advantage for signal transduction. It has been reported that mass transport of analytical solution through the sensor surface plays an important role in determining sensitivity.
Total flux to the sensor was studied as a function of sensor geometry and volumetric flow. Enhancing mass transport by conventional methods of decreasing height decreased the volumetric flow rate, which in turn decreased the total flux of the sensor. On the other hand, injecting the analyte directly into the sensor rather than merely streaming it past the sensing surface increased the mass transport effect, which in turn increased the total flux of the sensor.
It was found that the flux of the sensor could be increased by using a nanoporous membrane. Thus, the sensitivity of sensors could be enhanced by incorporating nanoporous membranes into microfluidic-based biosensors. Nanomaterial structures enable spatial confinement. In support of this observation, there is a compelling argument in the realm of biophysical understanding of proteins and their structures. A crowded environment exists inside a cell structure, in which the cytoplasm is typically different from the dilute solutions generally used in in vitro studies of proteins, and there is a school of thought which states that this may significantly affect the behavior of proteins.
Figure 3 Illustration of the molecular crowding theory. Even though this volume is empty, it is not possible to add even a single additional ball bearing of the same size. In other words, the volume available for the ball bearing has become zero, ie, total volume minus the excluded volume has effectively become zero A.
These spaces can be filled with smaller particles and this in itself would leave smaller gaps which can be filled with much smaller particles such as water molecules B and C. The binding affinities and rates of self-assembly can change by orders of magnitude as a result of confinement. Crowding is therefore a very important factor when performing an in vitro study. To study cells and their mechanisms in vivo, techniques known as cryoelectron tomography and fluorescent tags are used. Evidence has been presented that the reaction rates in cytoplasm filled with large ensembles of macromolecules are very similar to the ones predicted by the molecular crowding theory.
In short, what this means is that the biochemistry that would take place in a test tube is not exactly the same as that taking place in the body. Thus, it is imperative to use this idea in a device that measures the accurate concentration of proteins and other biomolecules, as it is measured from physiological fluids. Simple theoretical models presented by various groups to study and understand the essence of folding and binding of proteins in confined places was also taken into consideration during the conception of the device.
Protein folding is the process by which the linear information contained in the amino acid sequence of a polypeptide gives rise to the well defined three-dimensional conformation of the functional protein. Because unfolded proteins can reach their native state spontaneously in vitro, it was assumed that folding acquisition of the tertiary structure and assembly formation of protein oligomers of newly synthesized polypeptides in vivo occurs essentially uncatalyzed and without the input of metabolic energy.
This central idea has been revised in recent years after the discovery that correct folding of many proteins inside the cell depends on pre-existing protein machinery, known as molecular chaperones. Crowding prevents self-assembly of partly folded polypeptide chains, which is characterized as aggregation in in vitro studies. From the above discussion, it would seem useful to provide a very small confined area in which the proteins could be detected.
To achieve this purpose, nanobiosensors comprising nanomaterial embedded on the surface of measurement electrodes have been designed for detecting disease biomarkers. During the development of nanobiosensor devices, each of these individual elements must be individually optimized; however, for the device to meet requirements, each of the elements must work in unison. Selectivity refers to the response of the nanobiosensor only to the target biomolecules and not to other similar molecules.
It is extremely unlikely that a readout method would be able to distinguish between various specific and nonspecific interactions. In real-world blood samples, the target biomolecules are present in lower concentrations than those of nonspecific biomolecules. Certain trade-offs exist between selectivity and preparation of real-world samples to be made suitable for detection. The most daunting challenge in the field of biosensors is meeting the selectivity requirements when tested with complex real-world samples. The concept of nonspecific binding further complicates the task at hand.
This refers to the nonspecific, nontarget biomolecules that attach themselves to the biological probes located on the transducer probe layer. These nonspecific molecules reduce the number of binding locations for the corresponding target biomolecules, not only preventing the binding event but also creating the possibility of a false-positive signal. To overcome this problem, blocking agents such as bovine serum albumin which nonspecifically adsorbs, is readsorbed onto the surface of the immobilized biomolecule and this prevents any further nonspecific binding reactions during the exposure to the complex real-world samples.
The limit of detection is the smallest or lowest amount of target biomolecule concentration that can be reliably detected by the nanobiosensor. This is the figure of merit of the sensor. The dose-response curve is the graph from which the limit of detection and range of concentrations that can be measured using the nanobiosensor are plotted. The dose-response curve is also known as the calibration curve of the device. Reproducibility is another important parameter associated with the device which can be seen from the error bars on a graph.
Dynamic range is the ratio of the largest measurable target concentration and the limit of detection. Nanobiosensors can also be used to quantify the presence of the target biomolecule rather than just detect it. The resolution of the nanobiosensor is the smallest detectable change in target biomolecule concentration that can be detected. Dynamic range and limit of detection are interrelated, and the design of binding agents could be used to alter one parameter while reducing other parameters.
Multiplexing refers to detection of multiple target biomolecules from a single biological sample. This is one of the most important requirements of a nanobiosensor, and could be achieved by localization of different biological probes at different regions of the nanobiosensor. The biggest issue with multiplex detection is the problem of cross-reactivity. A certain biological probe may react with more than one of the target molecules, or certain target molecules might foul the probes.
Using creative design techniques and highly specific probe molecules, these reactions could be reduced, and improved multiplexed detection could be achieved. From the above description of the performance parameters, it appears that the limitations of the nanobiosensor lie in the biological affinity probes rather than in the actual electrical detection mechanism. With improved understanding of the immobilization chemistry and minimizing nonspecific binding issues, the limits of detection using biological probes could be enhanced further.
Nanotechnology on a chip is the new paradigm for designing diagnostic assays for diagnosis of disease. Some examples of devices that incorporate nanotechnology-based biochips and microarrays are nanofluidic arrays and protein nanobiochips.
These devices can be adapted for point-of-care use. One of the more promising uses of nanofluidic devices is isolation and analysis of individual biomolecules that have diagnostic relevance, such as DNA and protein detection. This capability could lead to new detection schemes for a number of chronic diseases. Nanofluidic technology is expected to have broad applications in systems biology, personalized medicine, detection of pathogens, drug development, and clinical research. Protein microarrays for the study of protein function are not widely used, in part because of the challenges in producing proteins to spot on the arrays.
Protein microarrays can be generated by printing complementary DNAs onto glass slides and then translating target proteins with mammalian reticulocyte lysate. This procedure obviates the need to purify proteins, avoids protein stability problems during storage, and captures sufficient protein for functional studies. Within the next decade, diagnostic devices based on nanotechnology will become available, and be able to perform thousands of measurements very rapidly and inexpensively. Future trends in diagnostics will continue in miniaturization of biochip technology to the nanoscale range.
The most common clinical diagnostic application will be analysis of blood proteins. Blood in the systemic circulation reflects the state of health or disease of most organs. Therefore, detection of blood molecular fingerprints will provide a sensitive assessment of health and disease. Molecular electronics and nanoscale chemical sensors will enable construction of microscopic sensors capable of detecting patterns of chemicals in a fluid. Information from a large number of such devices flowing passively in the bloodstream allows estimation of the properties of tiny chemical sources in a macroscopic tissue volume.
Estimates of plausible device capabilities have been used to evaluate their performance for typical chemicals released into the blood by tissues in response to localized injury or infection. With the methods currently used for blood analysis, such a chemical source would be difficult to distinguish from background when diluted throughout the blood volume and withdrawn as a blood sample. The trend will be to build diagnostic devices from the bottom up, starting with the most fundamental building blocks.
Unless there are early successes that translate into large-volume sales and early adoption, the long range forecast for nanobiosensors in disease diagnosis is promising. A factor that may support the implementation of nanobiosensors is the trend of moving away from fluorescent labeling as miniaturization reduces the signal intensity, but there have been some improvements making fluorescent labeling methods viable with nanoparticles.
Nanobiosensors will also facilitate the development of non-polymerase chain reaction diagnostic technologies. As a further refinement, nanotechnology can potentially be used for analysis of a single cell to enable a genetic diagnosis. In the near future, use of nanodiagnostics could reduce waiting times for test results. For example, patients with contagious diseases could provide urine samples when they first arrive at the clinic, and the results could be ready by the time they see the physician.
Patients could then be given a prescription immediately, reducing the length of time that the patient has to wait for results, thereby decreasing anxiety, improving compliance, and making the whole process less costly. In the next decade, nanobiotechnology-based biosensors will play an important role not only in diagnosis but also in linking diagnosis with treatment and development of personalized medicine.
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