Epitope-mimicking peptides or “mimotopes” are known for binding the same antibody paratope as their antigen counterparts, eliciting a similar immunological response [1]. Therefore, they can be used as an alternative to conjugated or labelled antigens for developing competitive immunoassays and immunosensors, especially in those situations where the modification of the target molecule is challenging due to its chemical structure or associated toxicity. Our work has focused on the application of the so-called phage display techniques for selecting mimopeptides to target fumonisin B1 (FB1) and zearalenone (ZON) mycotoxins, and on the development of alternative biosensing approaches for the analysis of these target compounds in foods. A phage-displayed peptide library was used to identify the specific clones for both mycotoxins. The performance of the selected phage-borne peptides was evaluated firstly in competitive immunoassays, and those providing the highest sensitivities for FB1 or ZON were subsequently applied to the development of immunosensors based on the synthetic peptides and a magnetic bead-based assay with luminescent detection. In an alternative approach, recombinant fusion proteins were constructed by genetic engineering to produce the peptides tagged with fluorescent or bioluminescent proteins. The latter could be directly applied as tracers in biosensor development, avoiding the need for secondary antibodies or further labelling [2]. A comparative evaluation of the optimized assays confirmed that the use of magnetic bead-based assay with the synthetic peptide gave higher sensitivities for FB1 detection (limit of detection, LOD, 0.03 ng mL–1). However, the use of the recombinant protein constructs also produced a good analytical performance (LOD of 1.1 and 0.3 ng mL–1 for FB1 measurements based on fluorescence quenching or bioluminescence, respectively), with rapid simple assays for the mycotoxins determinations at concentrations below the maximum residue levels established by the European legislation for those mycotoxins in cereal samples. Binding of the FB1-mimicking peptides to their respective antibody was also evaluated by SPR [3]. The novel assays were validated using spiked samples or reference materials, demonstrating that the developed biosensors could be a valuable tool for straightforward detection of mycotoxin-contaminated foods. Acknowledgements: Ministry of Science, Innovation and Universities (RTI2018-096410B-C21/22). R.P. acknowledges UCM for a predoctoral grant.

Epitope-mimicking peptides or “mimotopes” are known for binding the same antibody paratope as their antigen counterparts, eliciting a similar immunological response [1]. Therefore, they can be used as an alternative to conjugated or labelled antigens for developing competitive immunoassays and immunosensors, especially in those situations where the modification of the target molecule is challenging due to its chemical structure or associated toxicity. Our work has focused on the application of the so-called phage display techniques for selecting mimopeptides to target fumonisin B1 (FB1) and zearalenone (ZON) mycotoxins, and on the development of alternative biosensing approaches for the analysis of these target compounds in foods. A phage-displayed peptide library was used to identify the specific clones for both mycotoxins. The performance of the selected phage-borne peptides was evaluated firstly in competitive immunoassays, and those providing the highest sensitivities for FB1 or ZON were subsequently applied to the development of immunosensors based on the synthetic peptides and a magnetic bead-based assay with luminescent detection. In an alternative approach, recombinant fusion proteins were constructed by genetic engineering to produce the peptides tagged with fluorescent or bioluminescent proteins. The latter could be directly applied as tracers in biosensor development, avoiding the need for secondary antibodies or further labelling [2]. A comparative evaluation of the optimized assays confirmed that the use of magnetic bead-based assay with the synthetic peptide gave higher sensitivities for FB1 detection (limit of detection, LOD, 0.03 ng mL–1). However, the use of the recombinant protein constructs also produced a good analytical performance (LOD of 1.1 and 0.3 ng mL–1 for FB1 measurements based on fluorescence quenching or bioluminescence, respectively), with rapid simple assays for the mycotoxins determinations at concentrations below the maximum residue levels established by the European legislation for those mycotoxins in cereal samples. Binding of the FB1-mimicking peptides to their respective antibody was also evaluated by SPR [3]. The novel assays were validated using spiked samples or reference materials, demonstrating that the developed biosensors could be a valuable tool for straightforward detection of mycotoxin-contaminated foods. Acknowledgements: Ministry of Science, Innovation and Universities (RTI2018-096410B-C21/22). R.P. acknowledges UCM for a predoctoral grant.

Epitope-mimicking peptides or “mimotopes” are known for binding the same antibody paratope as their antigen counterparts, eliciting a similar immunological response [1]. Therefore, they can be used as an alternative to conjugated or labelled antigens for developing competitive immunoassays and immunosensors, especially in those situations where the modification of the target molecule is challenging due to its chemical structure or associated toxicity. Our work has focused on the application of the so-called phage display techniques for selecting mimopeptides to target fumonisin B1 (FB1) and zearalenone (ZON) mycotoxins, and on the development of alternative biosensing approaches for the analysis of these target compounds in foods. A phage-displayed peptide library was used to identify the specific clones for both mycotoxins. The performance of the selected phage-borne peptides was evaluated firstly in competitive immunoassays, and those providing the highest sensitivities for FB1 or ZON were subsequently applied to the development of immunosensors based on the synthetic peptides and a magnetic bead-based assay with luminescent detection. In an alternative approach, recombinant fusion proteins were constructed by genetic engineering to produce the peptides tagged with fluorescent or bioluminescent proteins. The latter could be directly applied as tracers in biosensor development, avoiding the need for secondary antibodies or further labelling [2]. A comparative evaluation of the optimized assays confirmed that the use of magnetic bead-based assay with the synthetic peptide gave higher sensitivities for FB1 detection (limit of detection, LOD, 0.03 ng mL–1). However, the use of the recombinant protein constructs also produced a good analytical performance (LOD of 1.1 and 0.3 ng mL–1 for FB1 measurements based on fluorescence quenching or bioluminescence, respectively), with rapid simple assays for the mycotoxins determinations at concentrations below the maximum residue levels established by the European legislation for those mycotoxins in cereal samples. Binding of the FB1-mimicking peptides to their respective antibody was also evaluated by SPR [3]. The novel assays were validated using spiked samples or reference materials, demonstrating that the developed biosensors could be a valuable tool for straightforward detection of mycotoxin-contaminated foods. Acknowledgements: Ministry of Science, Innovation and Universities (RTI2018-096410B-C21/22). R.P. acknowledges UCM for a predoctoral grant.

Infectious diseases are a major cause of morbidity and mortality in low and middle income countries (LMICs). Patients present with fever and non-specific symptoms, which are difficult to distinguish without tests, which are too expensive or unavailable. This results in presumptive diagnosis and treatment, which may be incorrect. Without tools to identify the infection, antibiotic administration is an attractive generic treatment, so now antibiotic resistance in some regions of Africa means half the patients with pneumonia do not respond to first-line antibiotics. Chronic non-communicable disease is also under monitored in LMICs. For example, in Mozambique only 6% of facilities could carry out a blood glucose analysis and personal monitoring is not available in general. A barrier to low-cost diagnostics in LMICs, arises through purchases from the west, without Purchasing Power Parity. There have been numerous attempts to propose low cost diagnostics for LMICs, but they remain high cost when taken in a local affordability context. The required biological reagents for a point of care diagnostic is often be the largest proportion of the total cost (eg >80% in the Philippines for a polymerase in a nucleic acid test, at nearly the same price as in US and Europe, despite the average household income being 80-90% lower). We will report on a ‘gene to diagnostic’ approach: a rational design will be discussed for a multifunctional fusion enzyme as the central reagent in point-of-care diagnostics. The components are a central functional assay protein, a visualising unit and an in-built immobilisation peptide. This reduces downstream isolation steps and eliminates expensive coupling chemicals for integration in a diagnostic. In built production monitoring and QA for the analytical reagent product is demonstrated with the visualizing protein. Applications will be presented for sarcosine determination in urine (a marker of earlystage prostate cancer) with an hourglass-like configuration, and data from a clinical trial of a nucleic acid amplification test, designed for malaria screening in Africa and Malaysian Borneo. The latter nucleic acid test is just beginning trials in Ghana for Covid-19.

Infectious diseases are a major cause of morbidity and mortality in low and middle income countries (LMICs). Patients present with fever and non-specific symptoms, which are difficult to distinguish without tests, which are too expensive or unavailable. This results in presumptive diagnosis and treatment, which may be incorrect. Without tools to identify the infection, antibiotic administration is an attractive generic treatment, so now antibiotic resistance in some regions of Africa means half the patients with pneumonia do not respond to first-line antibiotics. Chronic non-communicable disease is also under monitored in LMICs. For example, in Mozambique only 6% of facilities could carry out a blood glucose analysis and personal monitoring is not available in general. A barrier to low-cost diagnostics in LMICs, arises through purchases from the west, without Purchasing Power Parity. There have been numerous attempts to propose low cost diagnostics for LMICs, but they remain high cost when taken in a local affordability context. The required biological reagents for a point of care diagnostic is often be the largest proportion of the total cost (eg >80% in the Philippines for a polymerase in a nucleic acid test, at nearly the same price as in US and Europe, despite the average household income being 80-90% lower). We will report on a ‘gene to diagnostic’ approach: a rational design will be discussed for a multifunctional fusion enzyme as the central reagent in point-of-care diagnostics. The components are a central functional assay protein, a visualising unit and an in-built immobilisation peptide. This reduces downstream isolation steps and eliminates expensive coupling chemicals for integration in a diagnostic. In built production monitoring and QA for the analytical reagent product is demonstrated with the visualizing protein. Applications will be presented for sarcosine determination in urine (a marker of earlystage prostate cancer) with an hourglass-like configuration, and data from a clinical trial of a nucleic acid amplification test, designed for malaria screening in Africa and Malaysian Borneo. The latter nucleic acid test is just beginning trials in Ghana for Covid-19.

Infectious diseases are a major cause of morbidity and mortality in low and middle income countries (LMICs). Patients present with fever and non-specific symptoms, which are difficult to distinguish without tests, which are too expensive or unavailable. This results in presumptive diagnosis and treatment, which may be incorrect. Without tools to identify the infection, antibiotic administration is an attractive generic treatment, so now antibiotic resistance in some regions of Africa means half the patients with pneumonia do not respond to first-line antibiotics. Chronic non-communicable disease is also under monitored in LMICs. For example, in Mozambique only 6% of facilities could carry out a blood glucose analysis and personal monitoring is not available in general. A barrier to low-cost diagnostics in LMICs, arises through purchases from the west, without Purchasing Power Parity. There have been numerous attempts to propose low cost diagnostics for LMICs, but they remain high cost when taken in a local affordability context. The required biological reagents for a point of care diagnostic is often be the largest proportion of the total cost (eg >80% in the Philippines for a polymerase in a nucleic acid test, at nearly the same price as in US and Europe, despite the average household income being 80-90% lower). We will report on a ‘gene to diagnostic’ approach: a rational design will be discussed for a multifunctional fusion enzyme as the central reagent in point-of-care diagnostics. The components are a central functional assay protein, a visualising unit and an in-built immobilisation peptide. This reduces downstream isolation steps and eliminates expensive coupling chemicals for integration in a diagnostic. In built production monitoring and QA for the analytical reagent product is demonstrated with the visualizing protein. Applications will be presented for sarcosine determination in urine (a marker of earlystage prostate cancer) with an hourglass-like configuration, and data from a clinical trial of a nucleic acid amplification test, designed for malaria screening in Africa and Malaysian Borneo. The latter nucleic acid test is just beginning trials in Ghana for Covid-19.

Dipsticks are versatile sensing tools as they enable easy identification and quantitation of an analyte at any place with little to no instrumental effort, even for the layman. Their readout is mostly optical and reflectance and luminescence are most frequently used. Innovative probes and new polymeric materials can therefore help to increase the selectivity of dipsticks and make various analyte accessible. Therefore, this lecture will demonstrate how the appropriate selection of optical probes can provide new detection schemes that are supported by the choice of new materials and sensor designs. In food analysis, we recently introduced a chromogenic dye on dipsticks that can be used to quantitate biogenic amines (BAs) by imaging the fluorescence response with an inexpensive digital camera. [1] For reflectance readout, we now present a new chromogenic luminescent near-infrared dye embedded into electrospun nanofibers. Those are new nanomaterials that can promote the optical response of dipsticks. Embedding of the NIR-dye into cellulose acetate electrospun nanofibers provides a sensor layer with three different readouts. Either a change of color (green to blue), of reflectance or of fluorescence can indicate the content of BAs in real food samples. In dipsticks, the reflectance responds very similarly to all BAs, no matter if those are aliphatic, aromatic or diamines. Moreover, the dipsticks are selective only for primary amines but do not respond to secondary or tertiary amines. No interference of thiols is found. The evolution of BAs in real samples upon food ageing can be monitored. A useful feature for ion analysis in water is the combination of a classical ion indicator with a luminescent dye. Cuprizone is an optical probe that responds to complexation of copper with a color change. Immobilization of cuprizone and sulforhodamine 101 inside a polyurethane polymer on a dipstick yields a response to the presence of copper ions in two ways. First, Cu2+ is indicated visually by a color change from pink over blue to green. Additionally, the enhanced absorbance of the Cu2+-cuprizone complex quenches the emission of sulforhodamine 101 via an inner-filter effect. [2] This permits the quantitation of copper ions over more than 3 orders of magnitude down to 1 nmol/L. No interference on the fluorescence readout is found, if copper and various heavy metal ions are present, simultaneously. The dipsticks allow an easy control of the threshold concentrations of copper permitted for drinking water by the WHO or the EU. The concentrations found by dipsticks were validated by ICP-OES spectrometry.

Dipsticks are versatile sensing tools as they enable easy identification and quantitation of an analyte at any place with little to no instrumental effort, even for the layman. Their readout is mostly optical and reflectance and luminescence are most frequently used. Innovative probes and new polymeric materials can therefore help to increase the selectivity of dipsticks and make various analyte accessible. Therefore, this lecture will demonstrate how the appropriate selection of optical probes can provide new detection schemes that are supported by the choice of new materials and sensor designs. In food analysis, we recently introduced a chromogenic dye on dipsticks that can be used to quantitate biogenic amines (BAs) by imaging the fluorescence response with an inexpensive digital camera. [1] For reflectance readout, we now present a new chromogenic luminescent near-infrared dye embedded into electrospun nanofibers. Those are new nanomaterials that can promote the optical response of dipsticks. Embedding of the NIR-dye into cellulose acetate electrospun nanofibers provides a sensor layer with three different readouts. Either a change of color (green to blue), of reflectance or of fluorescence can indicate the content of BAs in real food samples. In dipsticks, the reflectance responds very similarly to all BAs, no matter if those are aliphatic, aromatic or diamines. Moreover, the dipsticks are selective only for primary amines but do not respond to secondary or tertiary amines. No interference of thiols is found. The evolution of BAs in real samples upon food ageing can be monitored. A useful feature for ion analysis in water is the combination of a classical ion indicator with a luminescent dye. Cuprizone is an optical probe that responds to complexation of copper with a color change. Immobilization of cuprizone and sulforhodamine 101 inside a polyurethane polymer on a dipstick yields a response to the presence of copper ions in two ways. First, Cu2+ is indicated visually by a color change from pink over blue to green. Additionally, the enhanced absorbance of the Cu2+-cuprizone complex quenches the emission of sulforhodamine 101 via an inner-filter effect. [2] This permits the quantitation of copper ions over more than 3 orders of magnitude down to 1 nmol/L. No interference on the fluorescence readout is found, if copper and various heavy metal ions are present, simultaneously. The dipsticks allow an easy control of the threshold concentrations of copper permitted for drinking water by the WHO or the EU. The concentrations found by dipsticks were validated by ICP-OES spectrometry.

Dipsticks are versatile sensing tools as they enable easy identification and quantitation of an analyte at any place with little to no instrumental effort, even for the layman. Their readout is mostly optical and reflectance and luminescence are most frequently used. Innovative probes and new polymeric materials can therefore help to increase the selectivity of dipsticks and make various analyte accessible. Therefore, this lecture will demonstrate how the appropriate selection of optical probes can provide new detection schemes that are supported by the choice of new materials and sensor designs. In food analysis, we recently introduced a chromogenic dye on dipsticks that can be used to quantitate biogenic amines (BAs) by imaging the fluorescence response with an inexpensive digital camera. [1] For reflectance readout, we now present a new chromogenic luminescent near-infrared dye embedded into electrospun nanofibers. Those are new nanomaterials that can promote the optical response of dipsticks. Embedding of the NIR-dye into cellulose acetate electrospun nanofibers provides a sensor layer with three different readouts. Either a change of color (green to blue), of reflectance or of fluorescence can indicate the content of BAs in real food samples. In dipsticks, the reflectance responds very similarly to all BAs, no matter if those are aliphatic, aromatic or diamines. Moreover, the dipsticks are selective only for primary amines but do not respond to secondary or tertiary amines. No interference of thiols is found. The evolution of BAs in real samples upon food ageing can be monitored. A useful feature for ion analysis in water is the combination of a classical ion indicator with a luminescent dye. Cuprizone is an optical probe that responds to complexation of copper with a color change. Immobilization of cuprizone and sulforhodamine 101 inside a polyurethane polymer on a dipstick yields a response to the presence of copper ions in two ways. First, Cu2+ is indicated visually by a color change from pink over blue to green. Additionally, the enhanced absorbance of the Cu2+-cuprizone complex quenches the emission of sulforhodamine 101 via an inner-filter effect. [2] This permits the quantitation of copper ions over more than 3 orders of magnitude down to 1 nmol/L. No interference on the fluorescence readout is found, if copper and various heavy metal ions are present, simultaneously. The dipsticks allow an easy control of the threshold concentrations of copper permitted for drinking water by the WHO or the EU. The concentrations found by dipsticks were validated by ICP-OES spectrometry.

Mostly Process Analytical Technologies (PAT) applications provide several outputs that can come from different process sensors or from different model outputs (soft sensors) generated from a multivariate sensor used for process monitoring and control. This communication presents data fusion strategies to combine sensor and/or model outputs in the development of multivariate statistical process control (MSPC) models. Data fusion is explored through three real process examples: i) MSPC end-point detection of a two-stage polyester production process combining soft sensors output from NIR-based multivariate models. ii) MSPC end-point detection of a fluidised bed drying of pharmaceutical granules process combining of NIR-based soft sensors output and process temperature measurements. iii) On-line MSPC of a benchtop batch gasoline distillation process combining concentration profiles of distilled fractions obtained through multivariate curve resolution – alternating least squares (MCR-ALS) [1] decomposition of NIR process measurements with vapour temperature measurements [2]. The examples studied demonstrate the flexibility in the choice of different inputs (e.g., key properties prediction by multivariate calibration, process profiles issued from a multivariate resolution method, etc.) used to build the data fusion MSPC models and its advantage in relation to MSPC models based uniquely on NIR sensor output. The proposed strategies are of general applicability for any analytical or bioanalytical process that produces several sensor and/or model outputs [3].

Mostly Process Analytical Technologies (PAT) applications provide several outputs that can come from different process sensors or from different model outputs (soft sensors) generated from a multivariate sensor used for process monitoring and control. This communication presents data fusion strategies to combine sensor and/or model outputs in the development of multivariate statistical process control (MSPC) models. Data fusion is explored through three real process examples: i) MSPC end-point detection of a two-stage polyester production process combining soft sensors output from NIR-based multivariate models. ii) MSPC end-point detection of a fluidised bed drying of pharmaceutical granules process combining of NIR-based soft sensors output and process temperature measurements. iii) On-line MSPC of a benchtop batch gasoline distillation process combining concentration profiles of distilled fractions obtained through multivariate curve resolution – alternating least squares (MCR-ALS) [1] decomposition of NIR process measurements with vapour temperature measurements [2]. The examples studied demonstrate the flexibility in the choice of different inputs (e.g., key properties prediction by multivariate calibration, process profiles issued from a multivariate resolution method, etc.) used to build the data fusion MSPC models and its advantage in relation to MSPC models based uniquely on NIR sensor output. The proposed strategies are of general applicability for any analytical or bioanalytical process that produces several sensor and/or model outputs [3].

Mostly Process Analytical Technologies (PAT) applications provide several outputs that can come from different process sensors or from different model outputs (soft sensors) generated from a multivariate sensor used for process monitoring and control. This communication presents data fusion strategies to combine sensor and/or model outputs in the development of multivariate statistical process control (MSPC) models. Data fusion is explored through three real process examples: i) MSPC end-point detection of a two-stage polyester production process combining soft sensors output from NIR-based multivariate models. ii) MSPC end-point detection of a fluidised bed drying of pharmaceutical granules process combining of NIR-based soft sensors output and process temperature measurements. iii) On-line MSPC of a benchtop batch gasoline distillation process combining concentration profiles of distilled fractions obtained through multivariate curve resolution – alternating least squares (MCR-ALS) [1] decomposition of NIR process measurements with vapour temperature measurements [2]. The examples studied demonstrate the flexibility in the choice of different inputs (e.g., key properties prediction by multivariate calibration, process profiles issued from a multivariate resolution method, etc.) used to build the data fusion MSPC models and its advantage in relation to MSPC models based uniquely on NIR sensor output. The proposed strategies are of general applicability for any analytical or bioanalytical process that produces several sensor and/or model outputs [3].