Alicia Maroto

Nanosensors in environmental analysis.

Nanoscience and nanotechnology deal with the study and application of structures of matter of at least one dimension of the order of less than 100 nm (1 nm=one millionth of a millimetre). However, properties related to low dimensions are more important than size. Nanotechnology is based on the fact that some very small structures usually have new properties and behaviour that are not displayed by the bulk matter with the same composition. This overview introduces and discusses the main concepts behind the development of nanosensors and the most relevant applications in the field of environmental analysis. We focus on the effects (many of which are related to the quantum nature) that distinguish nanosensors and give them their particular behaviour. We will review the main types of nanosensors developed to date and highlight the relationship between the property monitored and the type of nanomaterial used. We discuss several nanostructures that are currently used in the development of nanosensors: nanoparticles, nanotubes, nanorods, embedded nanostructures, porous silicon, and self-assembled materials. In each section, we first describe the type of nanomaterial used and explain the properties related to the nanostructure. We then briefly describe the experimental set up and discuss the main advantages and quality parameters of nanosensing devices. Finally, we describe the applications, many of which are in the environmental field.

Fast detection of Salmonella Infantis with carbon nanotube field effect transistors

In this paper we report a fast, sensitive and label-free biosensor for the selective determination of Salmonella Infantis. It is based on a field effect transistor (FET) in which a network of single-walled carbon nantotubes (SWCNTs) acts as the conductor channel. Anti-Salmonella antibodies were adsorbed onto the SWCNTs and subsequently the SWCNTs were protected with Tween 20 to prevent the non-specific binding of other bacteria or proteins. Our FET devices were exposed to increasing concentrations of S. Infantis and were able to detect at least 100 cfu/mL in 1h. To evaluate the selectivity of our FET devices, Streptococcus pyogenes and Shigella sonnei were tested as potential competing bacteria for Salmonella. At a concentration of 500 cfu/mL, neither Streptococcus nor Shigella interfered with the detection of Salmonella. Therefore, these devices could be used as useful label-free platforms to detect S. Infantis and, by using the suitable antibody, other bacteria or viruses.

Estimating uncertainties of analytical results using information from the validation process

A new approach for calculating uncertainties of analytical results based on the information from the validation process is proposed. This approach complements the existing approaches proposed to date and can be applied to any validated analytical method. The precision estimates generated during the process of assessment of the accuracy take into account the uncertainties of preprocessing steps and analytical measurement steps as long as the different factors that influence these steps are representatively varied in the whole validation process. Since the accuracy of an analytical method should be always assessed before applying it to future working samples, little extra work needs to be done to estimate the final uncertainty. Other sources of uncertainty not previously considered (e.g. uncertainty associated to sampling, to differences between the test-sample and the working sample, etc.) are subsequently included and mathematically combined with the uncertainty arising from the assessment of the accuracy to provide the overall uncertainty. These ideas are illustrated with a case study of the determination of copper in contaminated land.

Measurement uncertainty in analytical methods in which trueness is assessed from recovery assays

We propose a new procedure for estimating the uncertainty in quantitative routine analysis. This procedure uses the information generated when the trueness of the analytical method is assessed from recovery assays. In this paper, we assess trueness by estimating proportional bias (in terms of recovery) and constant bias separately. The advantage of the procedure is that little extra work needs to be done to estimate the measurement uncertainty associated to routine samples. This uncertainty is considered to be correct whenever the samples used in the recovery assays are representative of the future routine samples (in terms of matrix and analyte concentration). Moreover, these samples should be analysed by varying all the factors that can affect the analytical method. If they are analysed in this fashion, the precision estimates generated in the recovery assays take into account the variability of the routine samples and also all the sources of variability of the analytical method. Other terms related to the sample heterogeneity, sample pretreatments or factors not representatively varied in the recovery assays should only be subsequently included when necessary. The ideas presented are applied to calculate the uncertainty of results obtained when analysing sulphides in wine by HS-SPME-GC.

Solid-contact potentiometric aptasensor based on aptamer functionalized carbon nanotubes for the direct determination of proteins.

A facile, solid-contact selective potentiometric aptasensor exploiting a network of single-walled carbon nanotubes (SWCNT) acting as a transducing element is described in this work. The molecular properties of the SWCNT surface have been modified by covalently linking aptamers as biorecognition elements to the carboxylic groups of the SWCNT walls. As a model system to demonstrate the generic application of the approach, a 15-mer thrombin aptamer interacts with thrombin and the affinity interaction gives rise to a direct potentiometric signal that can be easily recorded within 15 s. The dynamic linear range, with a sensitivity of 8.0 mV/log a(Thr) corresponds to the 10(-7)-10(-6) M range of thrombin concentrations, with a limit of detection of 80 nM. The aptasensor displays selectivity against elastase and bovine serum albumin and is easily regenerated by immersion in 2 M NaCl. The aptasensor demonstrates the capacity of direct detection of the recognition event avoiding the use of labels, mediators, or the addition of further reagents or analyte accumulation.

Determination of choline and derivatives with a solid-contact ion-selective electrode based on octaamide cavitand and carbon nanotubes

A new solid-contact ion-selective electrode has been developed for determining choline and derivatives in aqueous solutions. The backbone of this new potentiometric sensor is the conjunction of the cavitand receptor, as the molecular recognition element, and a network of non-carboxylated single-walled carbon nanotubes, acting as a solid transducer material. The octaamide cavitand, a synthetic receptor that is highly selective for biologically important trimethyl alkylammonium cations such as choline, acetylcholine or carnitine, makes the selective determination of these compounds possible for the first time. The guest-host interaction takes place in the acrylate ion-selective membrane of the solid-contact electrode. The sensor was characterized by electrochemical impedance spectroscopy and environmental scanning electron microscopy. The new electrode displays a nearly Nernstian slope (57.3+/-1.0 mV/decade) and very stable behaviour (DeltaE/Deltat=224 muVh(-1)) throughout the dynamic range (10(-5) to 10(-1)M). The limit of detection of 10(-6.4)M and the high selectivities obtained will enable choline and derivatives to be determined in biological samples. Finally, the stability of the electrical potential of the new solid-contact electrode was examined by performing current-reversal chronopotentiometry and the influence of the interfacial water film was evaluated by the potentiometric water layer test.

Estimation of measurement uncertainty by using regression techniques and spiked samples

Abstract In this paper, we describe how to assess the trueness of analytical procedures using spiked samples and regression techniques. We show then how to calculate the uncertainty of future samples using the information generated in this process. Two types of bias are calculated in the assessment of trueness: a proportional bias (normally expressed in terms of recovery) and a constant bias. Since in many cases blank samples are not available, we propose a method for assessing trueness when samples that already contain the native analyte are spiked at several levels of concentration. Only proportional bias can be estimated from spiked samples, while constant bias must be estimated by the Youden method, i.e. by taking different amounts of sample. We propose two ways of assessing trueness. The first expresses results as instrumental responses and the second expresses results as concentration. We then present expressions for calculating uncertainty that cover these two situations. Finally, we use the expressions to calculate uncertainty from validation data of the analysis of esters in wine by SPME-GC.

Effect of non-significant proportional bias in the final measurement uncertainty

The trueness of an analytical method can be assessed by calculating the proportional bias of the method in terms of apparent recovery. If the apparent recovery does not differ significantly from one, the analytical method has not a significant bias. If this is the case, the bias is neglected and the uncertainty associated with this bias is included in the uncertainty budget of results. However, when assessing trueness there is always a probability of incorrectly concluding that the proportional bias is not significant. Therefore, the uncertainty of results may be underestimated. In this paper, we study how non-significant bias affects the uncertainty of analytical results. Moreover, we study how to avoid the underestimation of uncertainty by including the non-significant bias calculated in the uncertainty budget. To answer these questions, we have used the Monte-Carlo method to simulate the process of estimating the apparent recovery of a biased analytical method and, subsequently, the future results this method provides. The results of the simulation show that non-significant bias may underestimate the uncertainty of analytical results when bias contributes in more than 20% to the overall uncertainty. Uncertainty is specially underestimated when bias contributes in more than 50% to the overall uncertainty.

Should non-significant bias be included in the uncertainty budget?

Abstract The bias of an analytical procedure is calculated in the assessment of trueness. If this experimental bias is not significant, we assume that the procedure is unbiased and, consequently, the results obtained with this procedure are not corrected for this bias. However, when assessing trueness there is always a probability of incorrectly concluding that the experimental bias is not significant. Therefore, non-significant experimental bias should be included as a component of uncertainty. In this paper, we have studied if it is always necessary to include this term and which is the best approach to include this bias in the uncertainty budget. To answer these questions, we have used the Monte-Carlo method to simulate the assessment of trueness of biased procedures and the future results these procedures provide. The results show that non-significant experimental bias should be included as a component of uncertainty when the uncertainty of this bias represents at least a 30% of the overall uncertainty.

Detection of Human Immunoglobulin G at Physiological Conditions with Chemically Functionalizated Carbon Nanotube Field Effect Transistors

Abstract: In this paper we report a label-free biosensor able to detect 10 mg/L of human immunoglobulin G (HIgG) at physiological conditions. It is based on a field effect transistor in which a network of carbon nanotubes (CNTs) acts as the conductor channe l. HIgG an-tibodies are linked to the CNTs in three steps. First, the polymer polyethyleneimine (PEI) covers the CNTs’ surface preventing the non-specific binding of proteins. Second, the HIgG antibodies are linked to the CNTs using glutaraldehyde as a cross-linker. Finally, glycine is used to block the unreacted aldehyde groups and minimize unspecific adsorption effects. The selectivity of the sensor has been tested against 10 mg/L of serum albumin, the most abundant protein in plasma. Keywords: Carbon nanotube field effect transistor, human immunoglobulin G, CNT functionalization, immunosensor, antigen–antibody interaction, physiological conditions. INTRODUCTION Immunoanalytical techniques, such as enzyme-linked immu-nosorbent assay (ELISA), immunoelectrophoresis or fluoroimmu-noassays, based on the interaction between an antigen and the cor-responding antibody, have been used for many years due to their proven usefulness. However, the need to use labels and to add spe-cific reagents makes them frequently costly and time consuming. These techniques are not direct in the sense that they need a secon-dary mechanism to be able to detect the recognition event. There-fore, the development of new improved methods for the rapid de-tection of antigens or antibodies is important and applicable to sev-eral fields such as medical diagnosis, environmental analysis or forensic medicine. Immunoglobulin G is usually used as a model antigen when doing immunoassays [1]. Human Immunoglobulin G (HIgG) is one of the most important proteins found in human body fluids. Its primary function is related to defence mechanisms, when foreign agents have entered the human body. HIgG concentration changes are related to several diseases and, therefore, the protein is a relevant diagnosis indicator. CNTs were first seen by S. Iijima in 1991 [2]. Among other in-teresting characteristics, semiconducting CNTs modify their electri-cal conductivity when their nearest chemical environment changes [3]. In an attempt to take advantage of this property, CNTs have been integrated into field effect transistors (FETs) [4] as the semi-conducting channel of carbon nanotube field effect transistors (CNTFETs). CNTFETs have recently been used as biosensors and, nowadays, several kinds of biomolecules have been immobilized on CNTs: proteins [5-7], aptamers [8, 9], antibodies [5, 9], and DNA [10]. CNTFET based biosensors show several potential advantages such as needing a low volume of the sample, responding quickly, being sensitive, being label free and allowing miniaturization. Among the numerous studies on CNTs applied to biosensing, there are few reports which use a CNTFET and an antigen-antibody in-teraction to obtain an immunosensor. Takeda