The characterisation of engineered nanoparticles (eNP) in an environmental or biological sample is difficult enough, while the characterisation of natural nanoparticles is close to a nightmare. This lecture covers the determination of natural nanoparticles (nNP) in petrochemical products (1) and in biological samples (2) using a multi-method approach. It will give a rationale why environmental chemists are interested in nNPs and why the characterisation can explain processes. The main focus will be on the use of ICP-MS based methods.

The characterisation of engineered nanoparticles (eNP) in an environmental or biological sample is difficult enough, while the characterisation of natural nanoparticles is close to a nightmare. This lecture covers the determination of natural nanoparticles (nNP) in petrochemical products (1) and in biological samples (2) using a multi-method approach. It will give a rationale why environmental chemists are interested in nNPs and why the characterisation can explain processes. The main focus will be on the use of ICP-MS based methods.

The characterisation of engineered nanoparticles (eNP) in an environmental or biological sample is difficult enough, while the characterisation of natural nanoparticles is close to a nightmare. This lecture covers the determination of natural nanoparticles (nNP) in petrochemical products (1) and in biological samples (2) using a multi-method approach. It will give a rationale why environmental chemists are interested in nNPs and why the characterisation can explain processes. The main focus will be on the use of ICP-MS based methods.

The interest on surface enhanced vibrational spectroscopies (SEVS) such as surface enhanced Raman spectroscopy (SERS) and surface enhanced infrared absorption spectroscopy (SEIRAS) has increased in response to the challenges of single molecule analysis. While Raman and infrared spectroscopies are powerful complementary analytical tools providing information on the vibrational fingerprint of molecules, their intrinsically low sensitivity due to the associated molecular absorption/scattering crosssections has limited a wider application in analytical scenarios, SEVS overcoming this limitation. There are two main mechanisms namely, electromagnetic (EM) and chemical (CM) considered to contribute to the signal enhancement observed in SEVS. While the EM increases the electromagnetic field at the surface of the nanostructured surface, the CM gives rise to an increase in sensitivity due to chemical interactions between the analyte and the signal-enhancing nanostructure. To date, most SERS/SEIRA signal-enhancing materials are based on metallic nanostructures, i.e. especially noble metals with different geometries including nanoparticles, nanostars, etc. The materials domain has been gradually extended to transition and semiconductor materials including single-element semiconductors such as graphene. In this communication, different nanomaterials for both SERS and SEIRAS are presented, ranging from gold nanoparticles [1] and multi-branched gold nanostars [2], which provide a high density of so-called “hot spots” at the surface, to hybrid substrates comprising semiconductor materials [3], which provide the substrate with photocatalytic activity, as well as graphene [4], which has more recently emerged as a promising signal-enhancing material.

The interest on surface enhanced vibrational spectroscopies (SEVS) such as surface enhanced Raman spectroscopy (SERS) and surface enhanced infrared absorption spectroscopy (SEIRAS) has increased in response to the challenges of single molecule analysis. While Raman and infrared spectroscopies are powerful complementary analytical tools providing information on the vibrational fingerprint of molecules, their intrinsically low sensitivity due to the associated molecular absorption/scattering crosssections has limited a wider application in analytical scenarios, SEVS overcoming this limitation. There are two main mechanisms namely, electromagnetic (EM) and chemical (CM) considered to contribute to the signal enhancement observed in SEVS. While the EM increases the electromagnetic field at the surface of the nanostructured surface, the CM gives rise to an increase in sensitivity due to chemical interactions between the analyte and the signal-enhancing nanostructure. To date, most SERS/SEIRA signal-enhancing materials are based on metallic nanostructures, i.e. especially noble metals with different geometries including nanoparticles, nanostars, etc. The materials domain has been gradually extended to transition and semiconductor materials including single-element semiconductors such as graphene. In this communication, different nanomaterials for both SERS and SEIRAS are presented, ranging from gold nanoparticles [1] and multi-branched gold nanostars [2], which provide a high density of so-called “hot spots” at the surface, to hybrid substrates comprising semiconductor materials [3], which provide the substrate with photocatalytic activity, as well as graphene [4], which has more recently emerged as a promising signal-enhancing material.

The interest on surface enhanced vibrational spectroscopies (SEVS) such as surface enhanced Raman spectroscopy (SERS) and surface enhanced infrared absorption spectroscopy (SEIRAS) has increased in response to the challenges of single molecule analysis. While Raman and infrared spectroscopies are powerful complementary analytical tools providing information on the vibrational fingerprint of molecules, their intrinsically low sensitivity due to the associated molecular absorption/scattering crosssections has limited a wider application in analytical scenarios, SEVS overcoming this limitation. There are two main mechanisms namely, electromagnetic (EM) and chemical (CM) considered to contribute to the signal enhancement observed in SEVS. While the EM increases the electromagnetic field at the surface of the nanostructured surface, the CM gives rise to an increase in sensitivity due to chemical interactions between the analyte and the signal-enhancing nanostructure. To date, most SERS/SEIRA signal-enhancing materials are based on metallic nanostructures, i.e. especially noble metals with different geometries including nanoparticles, nanostars, etc. The materials domain has been gradually extended to transition and semiconductor materials including single-element semiconductors such as graphene. In this communication, different nanomaterials for both SERS and SEIRAS are presented, ranging from gold nanoparticles [1] and multi-branched gold nanostars [2], which provide a high density of so-called “hot spots” at the surface, to hybrid substrates comprising semiconductor materials [3], which provide the substrate with photocatalytic activity, as well as graphene [4], which has more recently emerged as a promising signal-enhancing material.

Breast cancer is one of the main mortality-causing diseases in women, and the search for biomarkers for early detection, prognosis and drug response prediction is an important field of research. Iron uptake, as transferrin-bound iron, is controlled through the modulation of the expression of the transferrin receptor 1 (TfR1). The overexpression of this receptor has been related to poorer outcome for the patients[1], due to the higher iron requirements of the more malignant cancer phenotypes. Therefore, the measurement of TfR1 in breast cancer tissues and cells is expected to serve as a prognosis biomarker. Bulk studies for the analysis of cells or tissues have been most commonly applied for many years. Such techniques have provided extremely valuable information in fields like biomarker detection or metallodrug studies. However, they require the digestion of over several millions of cells and, therefore, they provide averaged values within the entire population of cells. Elemental analysis by ICP-MS is a highly sensitive MS-based approach that allows for the analysis of single cells (SC-ICP-MS) when using adequate sample introduction systems and integration times. Therefore, SC-ICP-MS has recently permitted the access to information on small cell populations that are otherwise hidden behind the big majority of cells in bulk analysis but may have tremendous biological importance. In this presentation, the capabilities of triple quadrupole ICP-MS in combination with high-efficiency sample introduction systems will be highlighted for the quantification of TfR1 in single breast cancer cells. By using a properly characterized metal-labelled antibody, TfR1 on the surface of the cells will be tagged and quantified in relation to the concentration of the labelling metal. The results obtained by SC-ICP-MS for the breast cancer cell lines MCF7 and the more malignant MDA-MB-231 will be compared with those obtained by traditional bulk ELISA methods. In all cases, the expression of TfR1 resulted to be higher in the more malignant cancer phenotype, which confirms the expected alteration of the iron homeostasis in this type of cells.

Breast cancer is one of the main mortality-causing diseases in women, and the search for biomarkers for early detection, prognosis and drug response prediction is an important field of research. Iron uptake, as transferrin-bound iron, is controlled through the modulation of the expression of the transferrin receptor 1 (TfR1). The overexpression of this receptor has been related to poorer outcome for the patients[1], due to the higher iron requirements of the more malignant cancer phenotypes. Therefore, the measurement of TfR1 in breast cancer tissues and cells is expected to serve as a prognosis biomarker. Bulk studies for the analysis of cells or tissues have been most commonly applied for many years. Such techniques have provided extremely valuable information in fields like biomarker detection or metallodrug studies. However, they require the digestion of over several millions of cells and, therefore, they provide averaged values within the entire population of cells. Elemental analysis by ICP-MS is a highly sensitive MS-based approach that allows for the analysis of single cells (SC-ICP-MS) when using adequate sample introduction systems and integration times. Therefore, SC-ICP-MS has recently permitted the access to information on small cell populations that are otherwise hidden behind the big majority of cells in bulk analysis but may have tremendous biological importance. In this presentation, the capabilities of triple quadrupole ICP-MS in combination with high-efficiency sample introduction systems will be highlighted for the quantification of TfR1 in single breast cancer cells. By using a properly characterized metal-labelled antibody, TfR1 on the surface of the cells will be tagged and quantified in relation to the concentration of the labelling metal. The results obtained by SC-ICP-MS for the breast cancer cell lines MCF7 and the more malignant MDA-MB-231 will be compared with those obtained by traditional bulk ELISA methods. In all cases, the expression of TfR1 resulted to be higher in the more malignant cancer phenotype, which confirms the expected alteration of the iron homeostasis in this type of cells.

Breast cancer is one of the main mortality-causing diseases in women, and the search for biomarkers for early detection, prognosis and drug response prediction is an important field of research. Iron uptake, as transferrin-bound iron, is controlled through the modulation of the expression of the transferrin receptor 1 (TfR1). The overexpression of this receptor has been related to poorer outcome for the patients[1], due to the higher iron requirements of the more malignant cancer phenotypes. Therefore, the measurement of TfR1 in breast cancer tissues and cells is expected to serve as a prognosis biomarker. Bulk studies for the analysis of cells or tissues have been most commonly applied for many years. Such techniques have provided extremely valuable information in fields like biomarker detection or metallodrug studies. However, they require the digestion of over several millions of cells and, therefore, they provide averaged values within the entire population of cells. Elemental analysis by ICP-MS is a highly sensitive MS-based approach that allows for the analysis of single cells (SC-ICP-MS) when using adequate sample introduction systems and integration times. Therefore, SC-ICP-MS has recently permitted the access to information on small cell populations that are otherwise hidden behind the big majority of cells in bulk analysis but may have tremendous biological importance. In this presentation, the capabilities of triple quadrupole ICP-MS in combination with high-efficiency sample introduction systems will be highlighted for the quantification of TfR1 in single breast cancer cells. By using a properly characterized metal-labelled antibody, TfR1 on the surface of the cells will be tagged and quantified in relation to the concentration of the labelling metal. The results obtained by SC-ICP-MS for the breast cancer cell lines MCF7 and the more malignant MDA-MB-231 will be compared with those obtained by traditional bulk ELISA methods. In all cases, the expression of TfR1 resulted to be higher in the more malignant cancer phenotype, which confirms the expected alteration of the iron homeostasis in this type of cells.

Diatoms are located at the bottom of the food chain. Thus, toxicological relevant metals taken up by diatoms can possibly accumulate within the food web and cause harmful effects. Diatoms are a common test system in ecotoxicology. Toxicological effects weaken the growth of algae which is by default investigated by means of fluorescence detection - diminished fluorescence compared to a non-exposed control group indicates an effect. On basis of the expose concentration as well as obtained fluorescence data potential threshold exceedance in e.g. surface waters is assessed. However, this approach does not allow for the determination of “real” accumulated metal concentration in diatoms. Common approaches are based on microwave assisted digestion and elemental analysis. But, with regard to low absolute metal-content in algae this strategy is only feasible in case of availability of a high biomass. To tackle this problem, alternative, complementary approaches are highly needed. Within the last years, sp-ICP-MS for nanoparticle as well as single cell analysis turned out as a powerful technique to analyze metal contents as well as size distributions on broad size range (nano- to low micrometer scale) [1]. But, common ICP-MS systems do not allow for multi-element detection within single particle/cell events [2, 3]. Thus, simultaneous MS detection devices are needed - just recently, ICP-ToF-MS experienced a revival [4]. We developed an automated sample introduction system based on a HPLC system on-line with single particle-ICP-MS, which allowed for ionic background separation and single algae analysis [5]. For unambiguous tracing several fingerprint elements and multielement analysis in single algae (diatoms) is needed. Thus, we coupled our previous setup on-line to ICP-ToF-MS [6]. Test diatom species were exposed to test substances (Zn) as well as nanoparticles (FeNPs). The developed setup allowed for a fast, automated and multielement analysis in single diatoms. Furthermore, we combined our approach with multivariate data assessment - multielement detection of characteristic fingerprint elements allowed for an unambiguous diatom tracing. Clustering of diatoms according to metal exposure concentration levels was enabled. Our approach is a new potential tool in ecotoxicological testing.

Diatoms are located at the bottom of the food chain. Thus, toxicological relevant metals taken up by diatoms can possibly accumulate within the food web and cause harmful effects. Diatoms are a common test system in ecotoxicology. Toxicological effects weaken the growth of algae which is by default investigated by means of fluorescence detection - diminished fluorescence compared to a non-exposed control group indicates an effect. On basis of the expose concentration as well as obtained fluorescence data potential threshold exceedance in e.g. surface waters is assessed. However, this approach does not allow for the determination of “real” accumulated metal concentration in diatoms. Common approaches are based on microwave assisted digestion and elemental analysis. But, with regard to low absolute metal-content in algae this strategy is only feasible in case of availability of a high biomass. To tackle this problem, alternative, complementary approaches are highly needed. Within the last years, sp-ICP-MS for nanoparticle as well as single cell analysis turned out as a powerful technique to analyze metal contents as well as size distributions on broad size range (nano- to low micrometer scale) [1]. But, common ICP-MS systems do not allow for multi-element detection within single particle/cell events [2, 3]. Thus, simultaneous MS detection devices are needed - just recently, ICP-ToF-MS experienced a revival [4]. We developed an automated sample introduction system based on a HPLC system on-line with single particle-ICP-MS, which allowed for ionic background separation and single algae analysis [5]. For unambiguous tracing several fingerprint elements and multielement analysis in single algae (diatoms) is needed. Thus, we coupled our previous setup on-line to ICP-ToF-MS [6]. Test diatom species were exposed to test substances (Zn) as well as nanoparticles (FeNPs). The developed setup allowed for a fast, automated and multielement analysis in single diatoms. Furthermore, we combined our approach with multivariate data assessment - multielement detection of characteristic fingerprint elements allowed for an unambiguous diatom tracing. Clustering of diatoms according to metal exposure concentration levels was enabled. Our approach is a new potential tool in ecotoxicological testing.

Diatoms are located at the bottom of the food chain. Thus, toxicological relevant metals taken up by diatoms can possibly accumulate within the food web and cause harmful effects. Diatoms are a common test system in ecotoxicology. Toxicological effects weaken the growth of algae which is by default investigated by means of fluorescence detection - diminished fluorescence compared to a non-exposed control group indicates an effect. On basis of the expose concentration as well as obtained fluorescence data potential threshold exceedance in e.g. surface waters is assessed. However, this approach does not allow for the determination of “real” accumulated metal concentration in diatoms. Common approaches are based on microwave assisted digestion and elemental analysis. But, with regard to low absolute metal-content in algae this strategy is only feasible in case of availability of a high biomass. To tackle this problem, alternative, complementary approaches are highly needed. Within the last years, sp-ICP-MS for nanoparticle as well as single cell analysis turned out as a powerful technique to analyze metal contents as well as size distributions on broad size range (nano- to low micrometer scale) [1]. But, common ICP-MS systems do not allow for multi-element detection within single particle/cell events [2, 3]. Thus, simultaneous MS detection devices are needed - just recently, ICP-ToF-MS experienced a revival [4]. We developed an automated sample introduction system based on a HPLC system on-line with single particle-ICP-MS, which allowed for ionic background separation and single algae analysis [5]. For unambiguous tracing several fingerprint elements and multielement analysis in single algae (diatoms) is needed. Thus, we coupled our previous setup on-line to ICP-ToF-MS [6]. Test diatom species were exposed to test substances (Zn) as well as nanoparticles (FeNPs). The developed setup allowed for a fast, automated and multielement analysis in single diatoms. Furthermore, we combined our approach with multivariate data assessment - multielement detection of characteristic fingerprint elements allowed for an unambiguous diatom tracing. Clustering of diatoms according to metal exposure concentration levels was enabled. Our approach is a new potential tool in ecotoxicological testing.