Supramolecular Control in Nanostructured Film Architectures for Detecting Breast Cancer

Multidimensional calibration spaces in Staphylococcus Aureus detection using chitosan-based genosensors and electronic tongue

Mastitis diagnosis can be made by detecting Staphylococcus aureus (S. aureus), which requires high sensitivity and selectivity. Here, we report on microfluidic genosensors and electronic tongues to detect S. aureus DNA using impedance spectroscopy with data analysis employing visual analytics and machine learning techniques. The genosensors were made with layer-by-layer films containing either 10 bilayers of chitosan/chondroitin sulfate or 8 bilayers of chitosan/sericin functionalized with an active layer of cpDNA S. aureus. The specific interactions leading to hybridization in these genosensors allowed for a low limit of detection of 5.90 × 10-19 mol/L. The electronic tongue had four sensing units made with 6-bilayer chitosan/chondroitin sulfate films, 10-bilayer chitosan/chondroitin sulfate, 8-bilayer chitosan/sericin, and 8-bilayer chitosan/gold nanoparticles modified with sericin. Despite the absence of specific interactions, various concentrations of DNA S. aureus could be distinguished when the impedance data were plotted using a dimensionality reduction technique. Selectivity of S. aureus DNA was confirmed using multidimensional calibration spaces, based on machine learning, with accuracy up to 89 % for the genosensors and 66 % for the electronic tongue. Hence, with these computational methods one may opt for the more expensive genosensors or the simpler and cheaper electronic tongue, depending on the sensitivity level required to diagnose mastitis.

Proteomic-based electrochemical non-invasive biosensor for early breast cancer diagnosis

Breast cancer is the second highest cause of cancer-related mortality in women worldwide and in the United States, accounting for around 571,000 deaths per year. Early detection of breast cancer increases treatment results and the possibility of a cure. While existing diagnostic modalities such as mammography, ultrasound, and biopsy exist, some are prohibitively expensive, uncomfortable, time-consuming, and have limited sensitivity, necessitating the development of a cost-effective, rapid, and highly sensitive approach such as an electrochemical biosensor. Our research focuses on detecting breast cancer patients using the ECM1 biomarker, which has higher expression in synthetic urine. Our study has two primary objectives: (i) Diverse ECM1 protein concentrations are measured using electrochemical impedance spectroscopy and ELISA. Establishing a standard curve for the electrochemical biosensor by calibrating ECM-1 protein levels using electrochemical impedance spectroscopy. (ii) Validation of the effectiveness of the electrochemical biosensor. This aim entails testing the unknown concentration of ECM1 in the synthetic urine to ensure the efficiency of the biosensor to detect the biomarker in the early stages. The results show that the synthetic urine solution's ECM-1 detection range ranges from 1 pg/ml to 500 ng/ml. This shows that by detecting changes in ECM-1 protein levels in patient urine, the electrochemical biosensor can consistently diagnose breast cancer in its early stages or during increasing recurrence. Our findings highlight the electrochemical biosensor's efficacy in detecting early-stage breast cancer biomarkers (ECM-1) in patient urine. Further studies will be conducted with patient samples and develop handheld hardware for patient usage.

Nanoarchitectonic E-Tongue of Electrospun Zein/Curcumin Carbon Dots for Detecting Staphylococcus aureusin Milk

We report a nanoarchitectonic electronic tongue made with flexible electrodes coated with curcumin carbon dots and zein electrospun nanofibers, which could detect Staphylococcus aureus(S. aureus) in milk using electrical impedance spectroscopy. Electronic tongues are based on the global selectivity concept in which the electrical responses of distinct sensing units are combined to provide a unique pattern, which in this case allowed the detection of S. aureus through non-specific interactions. The electronic tongue used here comprised 3 sensors with electrodes coated with zein nanofibers, carbon dots, and carbon dots with zein nanofibers. The capacitance data obtained with the three sensors were processed with a multidimensional projection technique referred to as interactive document mapping (IDMAP) and analyzed using the machine learning-based concept of multidimensional calibration space (MCS). The concentration of S. aureus could be determined with the sensing units, especially with the one containing zein as the limit of detection was 0.83 CFU/mL (CFU stands for colony-forming unit). This high sensitivity is attributed to molecular-level interactions between the protein zein and C-H groups in S. aureus according to polarization-modulated infrared reflection-absorption spectroscopy (PM-IRRAS) data. Using machine learning and IDMAP, we demonstrated the selectivity of the electronic tongue in distinguishing milk samples from mastitis-infected cows from milk collected from healthy cows, and from milk spiked with possible interferents. Calibration of the electronic tongue can also be reached with the MCS concept employing decision tree algorithms, with an 80.1% accuracy in the diagnosis of mastitis. The low-cost electronic tongue presented here may be exploited in diagnosing mastitis at early stages, with tests performed in the farms without requiring specialized laboratories or personnel.

Diagnostics of SARS-CoV-2 infection using electrical impedance spectroscopy with an immunosensor to detect the spike protein

Mass testing for the diagnostics of COVID-19 has been hampered in many countries owing to the high cost of the methodologies to detect genetic material of SARS-CoV-2. In this paper, we report on a low-cost immunosensor capable of detecting the spike protein of SARS-CoV-2, including in samples of inactivated virus. Detection is performed with electrical impedance spectroscopy using an immunosensor that contains a monolayer film of carboxymethyl chitosan as matrix, coated with an active layer of antibodies specific to the spike protein. In addition to a low limit of detection of 0.179 fg/mL within an almost linear behavior from 10⁻²⁰ g/mL to 10⁻¹⁴ g/mL, the immunosensor was highly selective. For the samples with the spike protein could be distinguished in multidimensional projection plots from samples with other biomarkers and analytes that could be interfering species for healthy and infected patients. The excellent analytical performance of the immunosensors was validated with the distinction between control samples and those containing inactivated SARS-CoV-2 at different concentrations. The mechanism behind the immunosensor performance is the specific antibody-protein interaction, as confirmed with the changes induced in C–H stretching and protein bands in polarization-modulated infrared reflection absorption spectra (PM-IRRAS). Because impedance spectroscopy measurements can be made with low-cost portable instruments, the immunosensor proposed here can be applied in point-of-care diagnostics for mass testing even in places with limited resources.

Controlled molecular architectures in microfluidic immunosensors for detecting Staphylococcus aureus

Detection of pathogenic microorganisms is essential for food quality control and diagnosis of various diseases, which is currently performed with high-cost, sophisticated methods. In this paper, we report on a low-cost detection method based on impedance spectroscopy to detect Staphylococcus aureus (S. aureus). The immunosensors were made with microfluidic devices made of interdigitated electrodes coated with layer-by-layer (LbL) films of chitosan and chondroitin sulfate, on which a layer of anti-S. aureus antibodies was adsorbed. The limit of detection was 2.83 CFU mL-1 with a limit of quantification of 9.42 CFU mL-1 for immunosensors with 10-bilayer LbL films. This level of sensitivity is sufficient to detect traces of bacteria that cause mastitis in milk, which we have confirmed by distinguishing milk samples containing various concentrations of S. aureus from pure milk and milk contaminated with Escherichia coli (E. coli) and Salmonella. Distinction of these samples was made possible by projecting the electrical impedance data with the interactive document mapping (IDMAP) technique. The high sensitivity and selectivity are attributed to the highly specific interaction with anti-S. aureus antibodies captured with polarization-modulated reflection absorption spectroscopy (PM-IRRAS), with adsorption on the antibodies explained with the Langmuir-Freundlich model. Since these immunosensors are stable for up to 25 days and detection measurements can be made within minutes, the methodology proposed is promising for monitoring S. aureus contamination in the food industry and hospitals, and in detecting bovine mastitis.

Bovine serum albumin encapsulation of near infrared fluorescent nano-probe with low nonspecificity and cytotoxicity for imaging of HER2-positive breast cancer cells

Breast cancer with HER2 overexpressing type links to malignant tumor growth and poor clinical outcome. Successful development of sensitive and selective nano-probe for identification of HER2-positive breast cancer cells is of great importance for breast cancer early diagnosis, subtype classification, and treatment planning. Herein, we report a HER2 antibody conjugated near infrared (NIR) emitted MnCuInS/ZnS qumtun dots (QDs) encapsulated bovine serum albumin (BSA) nano-probe for accurately targeted imaging of HER2-positive breast cancer cells. This NIR nano-probe shows good biocompatibility, low nonspecificity and cytotoxicity, high colloidal stability, and allows HER2-positive breast cancer cell identification with good selectivity. The practicality of this targeted NIR fluorescent nano-probe was proved by successful identifying HER2-positive breast cancer cells from HER2-negative breast cancer cells, which indicates that it can be efficiently applied in selective screening of HER2 overexpressing cancer cells, and provide a platform for the strategy design on the distinction of different breast cancer subtypes.

Microfluidic-Based Genosensor To Detect Human Papillomavirus (HPV16) for Head and Neck Cancer

High-risk human papillomavirus (HPV) infection, mainly with HPV16 type, has been increasingly considered as an important etiologic factor in head and neck cancers. Detection of HPV16 is therefore crucial for these types of cancer, but clinical tests are not performed routinely in public health systems owing to the high cost and limitations of the existing tests. In this article, we report on a potentially low-cost genosensor capable of detecting low concentrations of HPV16 in buffer samples and distinguishing, with high accuracy, head and neck cancer cell lines according to their HPV16 status. The genosensor consisted of a microfluidic device that had an active layer of a HPV16 capture DNA probe (cpHPV16) deposited onto a layer-by-layer film of chitosan and chondroitin sulfate. Impedance spectroscopy was the principle of detection utilized, leading to a limit of detection of 10.5 pM for complementary ssDNA HPV16 oligos (ssHPV16). The genosensor was also able to distinguish among HPV16⁺ and HPV16^- cell lines, using the multidimensional projection technique interactive document mapping. Hybridization between the ssHPV16 oligos and cpHPV16 probe was confirmed with polarization-modulated infrared reflection-absorption spectroscopy, where PO₂ and amide I and amide II bands from adenine and thymine were monitored. The electrical response could be modeled as resulting from an adsorption process represented in a Freundlich model. Because the fabrication procedures of the microfluidic devices and genosensors and the data collection and analysis can be implemented at low cost, the results presented here amount to a demonstration of possible routine screening for HPV infections.

A simple architecture with self-assembled monolayers to build immunosensors for detecting the pancreatic cancer biomarker CA19-9

Film architecture for the immunosensor.

Surface-engineered quantum dots/electrospun nanofibers as a networked fluorescence aptasensing platform toward biomarkers

A membrane-based fluorescent sensing platform is a facile, point-of-care and promising technique in chemo/bio-analytical fields. However, the existing fluorescence sensing films for cancer biomarkers have several problems, with dissatisfactory sensitivity and selectivity, low utilization of probes encapsulated in films as well as the tedious design of membrane structures. In this work, a novel fluorescence sensing platform is fabricated by bio-grafting quantum dots (QDs) onto the surface of electrospun nanofibers (NFs). The aptamer integrated into the QDs/NFs can result in high specificity for recognizing and capturing biomarkers. Partially complementary DNA-attached gold nanoparticles (AuNPs) are employed to efficiently hybridize with the remaining aptamer to quench the fluorescence of QDs by nanometal surface energy transfer (NSET) between them both, which are constructed for prostate specific antigen (PSA) assay. Taking advantage of the networked nanostructure of aptamer-QDs/NFs, the fluorescent film can detect PSA with high sensitivity and a detection limit of 0.46 pg mL^-1, which was further applied in real clinical serum samples. Coupling the surface grafted techniques to the advanced network nanostructure of electrospun NFs, the proposed aptasensing platform can be easily extended to achieve sensitive and selective assays for other biomarkers.

Immunosensor for Pancreatic Cancer Based on Electrospun Nanofibers Coated with Carbon Nanotubes or Gold Nanoparticles

We report the fabrication of immunosensors based on nanostructured mats of electrospun nanofibers of polyamide 6 and poly(allylamine hydrochloride) coated either with multiwalled carbon nanotubes (MWCNTs) or gold nanoparticles (AuNPs), whose three-dimensional structure was suitable for the immobilization of anti-CA19-9 antibodies to detect the pancreatic cancer biomarker CA19-9. Using impedance spectroscopy, the sensing platform was able to detect CA19-9 with a detection limit of 1.84 and 1.57 U mL-1 for the nanostructured architectures containing MWCNTs and AuNPs, respectively. The high sensitivity achieved can be attributed to the irreversible adsorption between antibodies and antigens, as confirmed with polarization-modulated infrared reflection absorption spectroscopy. The adsorption mechanism was typical Langmuir-Freundlich processes. The high sensitivity and selectivity of the immunosensors were also explored in tests with blood serum from patients with distinct concentrations of CA19-9, for which the impedance spectra data were processed with a multidimensional projection technique. The robustness of the immunosensors in dealing with patient samples without suffering interference from analytes present in biological fluids is promising for a simple, effective diagnosis of pancreatic cancer at early stages.

Carbon Nanotube Matrix for Highly Sensitive Biosensors To Detect Pancreatic Cancer Biomarker CA19-9

Biosensors fabricated with nanomaterials promise faster, cheaper, and more efficient alternatives to traditional, often bulky devices for early cancer diagnosis. In this study, we fabricated a thin film sensing unit on interdigitated gold electrodes combining polyethyleneimine and carbon nanotubes in a layer by layer fashion, onto which antibodies anti-CA19-9 were adsorbed with a supporting layer of N-hydroxysuccinimide and 1-ethyl-3-(3-dimethylaminopropyl)carbodiimide solution. By use of impedance spectroscopy, the pancreatic cancer biomarker CA19-9 was detected in a buffer with limit of detection of 0.35 U/mL. This high sensitivity allowed for distinction between samples of blood serum from patients with distinct probabilities to develop pancreatic cancer. The selectivity of the biosensor was confirmed in subsidiary experiments with HT-29 and SW-620 cell lines and possible interferents, e.g., p53 protein, ascorbic acid, and glucose, where significant changes in capacitance could only be measured with HT-29 that contained the CA19-9 biomarker. Chemisorption of CA19-9 molecules onto the layer of anti-CA19-9 antibodies was the mechanism responsible for sensing while electrostatic interactions drove the adsorption of carbon nanotubes, according to polarization-modulated infrared reflection absorption spectroscopy (PM-IRRAS). The adsorption behavior was successfully described by the Langmuir-Freundlich isotherm.

Functionalization-Free Microfluidic Electronic Tongue Based on a Single Response

Electronic tongues (e-tongues) are promising analytical devices for a variety of applications to address the challenges of quality control in water monitoring and industries of foods, beverages, and pharmaceuticals. A crucial drawback in the current e-tongues is the need to recalibrate the device when one or more sensing units (usually with modified surface) are replaced. Another downside is the necessity to perform subsequent surface modifications and analyses to each of the diverse sensing units, undermining the simplicity and velocity of the method. These features have prevented widespread commercial use of the e-tongues. In this paper, we introduce a microfluidic e-tongue that overcomes all such limitations. The key principle of global selectivity of the e-tongue was achieved by recording only a single response, namely, the equivalent admittance spectrum of an association of resistors in parallel. Such resistors consisted of five nonfunctionalized stainless steel microwires (sensing units), which were short-circuited and coated with gold, platinum, nickel, iron, and aluminum oxide films. The microwires were inserted in a chip composed of a single piece of polydimethylsiloxane (PDMS). Using impedance spectroscopy, the e-tongue was successfully applied in classification of basic tastes at a concentration below the threshold for the human tongue. In addition, our chip allowed the distinction of various chemicals used in oil industry. Finally, our cleanroom-free prototyping allows the mass production of chips with easily replaceable and reproducible sensing units. Hence, one can now envisage the widespread dissemination of e-tongues with fast and reproducible data.

Information Visualization and Feature Selection Methods Applied to Detect Gliadin in Gluten-Containing Foodstuff with a Microfluidic Electronic Tongue

The fast growth of celiac disease diagnosis has sparked the production of gluten-free food and the search for reliable methods to detect gluten in foodstuff. In this paper, we report on a microfluidic electronic tongue (e-tongue) capable of detecting trace amounts of gliadin, a protein of gluten, down to 0.005 mg kg^-1 in ethanol solutions, and distinguishing between gluten-free and gluten-containing foodstuff. In some cases, it is even possible to determine whether gluten-free foodstuff has been contaminated with gliadin. That was made possible with an e-tongue comprising four sensing units, three of which made of layer-by-layer (LbL) films of semiconducting polymers deposited onto gold interdigitated electrodes placed inside microchannels. Impedance spectroscopy was employed as the principle of detection, and the electrical capacitance data collected with the e-tongue were treated with information visualization techniques with feature selection for optimizing performance. The sensing units are disposable to avoid cross-contamination as gliadin adsorbs irreversibly onto the LbL films according to polarization-modulated infrared reflection absorption spectroscopy (PM-IRRAS) analysis. Small amounts of material are required to produce the nanostructured films, however, and the e-tongue methodology is promising for low-cost, reliable detection of gliadin and other gluten constituents in foodstuff.

Analysis of Scanning Electron Microscopy Images To Investigate Adsorption Processes Responsible for Detection of Cancer Biomarkers

Adsorption processes are responsible for detection of cancer biomarkers in biosensors (and immunosensors), which can be captured with various principles of detection. In this study, we used a biosensor made with nanostructured films of polypyrrole and p53 antibodies, and image analysis of scanning electron microscopy data made it possible to correlate morphological changes of the biosensor with the concentration of cells containing the cancer biomarker p53. The selectivity of the biosensor was proven by distinguishing images obtained with exposure of the biosensor to cells containing the biomarker from those acquired with cells that did not contain it. Detection was confirmed with cyclic voltammetry measurements, while the adsorption of the p53 biomarker was probed with polarization-modulated infrared reflection absorption (PM-IRRAS) and a quartz crystal microbalance (QCM). Adsorption is described using the Langmuir-Freundlich model, with saturation taking place at a concentration of 100 Ucells/mL. Taken together, our results point to novel ways to detect biomarkers or any type of analyte for which detection is based on adsorption as is the case of the majority of biosensors.

On the convergence of nanotechnology and Big Data analysis for computer-aided diagnosis

An overview is provided of the challenges involved in building computer-aided diagnosis systems capable of precise medical diagnostics based on integration and interpretation of data from different sources and formats. The availability of massive amounts of data and computational methods associated with the Big Data paradigm has brought hope that such systems may soon be available in routine clinical practices, which is not the case today. We focus on visual and machine learning analysis of medical data acquired with varied nanotech-based techniques and on methods for Big Data infrastructure. Because diagnosis is essentially a classification task, we address the machine learning techniques with supervised and unsupervised classification, making a critical assessment of the progress already made in the medical field and the prospects for the near future. We also advocate that successful computer-aided diagnosis requires a merge of methods and concepts from nanotechnology and Big Data analysis.

Adsorption according to the Langmuir-Freundlich model is the detection mechanism of the antigen p53 for early diagnosis of cancer

Biosensors for early detection of cancer biomarkers normally depend on specific interactions between such biomarkers and immobilized biomolecules in the sensing units. Though these interactions are expected to yield specific, irreversible adsorption, the underlying mechanism appears not to have been studied in detail. In this paper, we show that adsorption explained with the Langmuir-Freundlich model is responsible for detection of the antigen p53 associated with various types of cancers. Irreversible adsorption was proven between anti-p53 antibodies immobilized on the biosensors and the antigen p53, with the adequacy of the Langmuir-Freundlich model being confirmed with three independent experimental methods, viz. polarization-modulated infrared reflection absorption spectroscopy (PM-IRRAS), nanogravimetry using a quartz crystal microbalance and electrochemical impedance spectroscopy. The method based on this irreversible adsorption was sufficiently sensitive (limit of detection of 1.4 pg mL(-1)) for early diagnosis of Hodgkin lymphoma, pancreatic and colon carcinomas, and bladder, ovarian and lung cancers, and could distinguish between MCF7 cells containing the antigen p53 from Saos-2 cells that do not contain it.