Electrochromic Sensor Augmented with Machine Learning for Enzyme-Free Analysis of Antioxidants.

Our study presents an electrochromic sensor that operates without the need for enzymes or multiple oxidant reagents. This sensor is augmented with machine learning algorithms, enabling the identification, classification, and prediction of six different antioxidants with high accuracy. We utilized polyaniline (PANI), Prussian blue (PB), and copper-Prussian blue analogues (Cu-PBA) at their respective oxidation states as electrochromic materials (ECMs). By designing three readout channels with these materials, we were able to achieve visual detection of antioxidants without relying on traditional "lock and key" specific interactions. Our sensing approach is based on the direct electrochemical reactions between oxidized electrochromic materials (ECMsox) as electron acceptors and various antioxidants, which act as electron donors. This interaction generates unique fingerprint patterns by switching the ECMsox to reduced electrochromic materials (ECMsred), causing their colors to change. Through the application of density functional theory (DFT), we demonstrated the molecular-level basis for the distinct multicolor patterns. Additionally, machine learning algorithms were employed to correlate the optical patterns with RGB data, enabling complex data analysis and the prediction of unknown samples. To demonstrate the practical applications of our design, we successfully used the EC sensor to diagnose antioxidants in serum samples, indicating its potential for the on-site monitoring of antioxidant-related diseases. This advancement holds promise for various applications, including the real-time monitoring of antioxidant levels in biological samples, the early diagnosis of antioxidant-related diseases, and personalized medicine. Furthermore, the success of our electrochromic sensor design highlights the potential for exploring similar strategies in the development of sensors for diverse analytes, showcasing the versatility and adaptability of this approach.

Quantitative measurement of CA 15-3 cancer biomarker using an electrochemical aptasensor based on the electrodeposition of Au thin film on cauliflower-like rGO-MoS2 nanocomposite.

The present research was conducted to design and construct an electrochemical aptasensor for evaluating carbohydrate antigen 15-3 (CA15-3) as a biomarker for breast cancer. The aptasensor has been fabricated by a gold thin film (AuTF) electrodeposited on a cauliflower-like reduced graphene oxide-molybdenum sulfide nanocomposite (rGO-MoS2). The modified electrode's surface was used to immobilize the thiolated aptamer, which was subsequently treated with CA 15-3 antigen. The aptasensor fabrication process was assessed using electrochemical impedance spectroscopy (EIS) and cyclic voltammetry (CV). This research also applied EIS to the quantitative measurement of CA 15-3 antigen by the proposed aptasensor. The interfacial charge transfer resistance (Rct) alteration before and after incubation of CA 15-3 by the immobilized aptamer was considered a signal for the quantitative measurement of CA 15-3. A linear concentration ranging from 5.0 to 200.0 U mL-1 with a detection limit of 3.0 × 10-1 U mL-1 was obtained for CA 15-3 using the EIS method. This designed aptasensor indicates satisfactory repeatability and stability, good selectivity, and high sensitivity. Moreover, clinical samples were assayed by the prepared aptasensor and compared with the ELISA method, yielding acceptable results. The recovery and relative standard deviation (RSD) of CA 15-3 in human serum samples were in the range 95.0 to 107.0% and 3.5 to 7.5%, respectively.

Fluorescent-tagged water with carbon dots derived from phenylenediamine as an equipment-free nanotracer for enhanced oil recovery.

Chemical enhanced oil recovery (EOR) through waterflooding is the most commonly used method to improve crude oil displacement and extraction however; the impact of environmental side effects may remain ambiguous. Regarding, flooding tagged water with tracers provides a better understanding of the fate of injected water and the reservoir conditions more than oil recovery. This study's main focus is the proposed carbon dots (CDs) to develop fluorescent-tagged with dual functions as a sensing and an enhancing agent for EOR operations. Different physicochemical and optical properties were obtained for CDs by tuning the surface chemistry of phenylenediamine (PD) isomers and tartaric acid (TA) via the solvothermal method which leads to green, and yellow fluorescent emissions. Size distribution and colloidal and thermal stability of the prepared nanofluids carrying CDs were controlled by atomic force microscope (AFM), transmission electron microscopy (TEM), dynamic light scattering (DLS), zeta potential, and thermogravimetric analysis (TGA). Long-time emission stability in high temperature and salinity such as conditions found in the oil reservoirs was precisely detected by fluorescence spectroscopy and a portable UV cabinet as the on-site detection method to confirm the sensing ability of CDs. While, rheological parameters of nanofluids such as viscosity, wettability alteration, and fluid/crude oil interfacial tension were evaluated to support the potential of CDs as an enhancing agent to sweep crude oil on the carbonate rock reservoirs. The oil displacement mechanism was monitored on the micromodel pattern by recording 27.8 % and 20.5 % displacement factors for the prepared nanofluids carrying 200 ppm CDs.

Thriving Under Stress: Pseudomonas aeruginosa Outcompetes the Background Polymicrobial Community Under Treatment Conditions in a Novel Chronic Wound Model.

In vitro infection models are important for studying the effects of antimicrobials on microbial growth and metabolism. However, many models lack important biological components that resemble the polymicrobial nature of chronic wounds or infections. In this study, we developed a perfused meat model that supports the growth of the human pathogen Pseudomonas aeruginosa in a native meat microbial background to investigate the impact of antibiotics and hydrogen peroxide on polymicrobial community growth and metabolism. P. aeruginosa plays an important role as an etiological agent involved in chronic infections and is a common opportunistic pathogen. Chemical stressors in the form of hydrogen peroxide, carbenicillin, and gentamicin were perfused through the meat with polymicrobial growth on the surface. The relative abundances of P. aeruginosa and the background microbial community were analyzed by cell viability assays, and metabolic changes of the entire community in response to different antimicrobial treatments were characterized by GC-MS analysis of volatile organic compounds. The meat background community was characterized by amplicon sequencing. Relative densities of P. aeruginosa and background microbiota were similar under control conditions. Antimicrobial stressors, even at sub-inhibitory, physiologically relevant concentrations, spurred P. aeruginosa dominance of the meat surface community. Volatile metabolite ion intensity levels showed that antibacterial treatments drive changes in microbial metabolism. The abundance of the P. aeruginosa-derived metabolite, acetophenone, remained stable with treatment, whereas the relative abundances of 2-butanone, 2-nonanone, and 2-aminoacetophenone changed in response to treatment, suggesting these could serve as biomarkers of infection. Our model recapitulates some of the physiological conditions of chronic wounds and facilitates high throughput experiments without the high cost of in vivo models. Expanded use of this perfusion model will contribute to the understanding of polymicrobial growth and metabolism in the context of chronic wounds and infections.

Smart Chip for Visual Detection of Bacteria Using the Electrochromic Properties of Polyaniline.

Finding fast and reliable ways to detect pathogenic bacteria is crucial for addressing serious public health issues in clinical, environmental, and food settings. Here, we present a novel assay based on the conversion of an electrochemical signal into a more convenient optical readout for the visual detection of Escherichia coli. Electropolymerizing polyaniline (PANI) on an indium tin oxide screen-printed electrode (ITO SPE), we achieved not only the desired electrochromic behavior but also a convenient way to modify the electrode surface with antibodies (taking advantage of the many amine groups of PANI). Applying a constant potential to the PANI-modified ITO SPE induces a change in their oxidation state, which in turn generates a color change on the electrode surface. The presence of E. coli on the electrode surface increases the resistance in the circuit affecting the PANI oxidation states, producing a different electrochromic response. Using this electrochromic sensor, we could measure concentrations of E. coli spanning 4 orders of magnitude with a limit of detection of 102 colony forming unit per 1 mL (CFU mL-1) by the naked eye and 101 CFU mL-1 using ImageJ software. In this work we show that merging the sensitivity of electrochemistry with the user-friendliness of an optical readout can generate a new and powerful class of biosensors, with potentially unlimited applications in a variety of fields.

Surface-Enhanced Raman Scattering-Based Odor Compass: Locating Multiple Chemical Sources and Pathogens.

Olfaction is important for identifying and avoiding toxic substances in living systems. Many efforts have been made to realize artificial olfaction systems that reflect the capacity of biological systems. A sophisticated example of an artificial olfaction device is the odor compass which uses chemical sensor data to identify odor source direction. Successful odor compass designs often rely on plume-based detection and mobile robots, where active, mechanical motion of the sensor platform is employed. Passive, diffusion-based odor compasses remain elusive as detection of low analyte concentrations and quantification of small concentration gradients from within the sensor platform are necessary. Further, simultaneously identifying multiple odor sources using an odor compass remains an ongoing challenge, especially for similar analytes. Here, we show that surface-enhanced Raman scattering (SERS) sensors overcome these challenges, and we present the first SERS odor compass. Using a grid array of SERS sensors, machine learning analysis enables reliable identification of multiple odor sources arising from diffusion of analytes from one or two localized sources. Specifically, convolutional neural network and support vector machine classifier models achieve over 90% accuracy for a multiple odor source problem. This system is then used to identify the location of an Escherichia coli biofilm via its complex signature of volatile organic compounds. Thus, the fabricated SERS chemical sensors have the needed limit of detection and quantification for diffusion-based odor compasses. Solving the multiple odor source problem with a passive platform opens a path toward an Internet of things approach to monitor toxic gases and indoor pathogens.

Emerging frontiers in drug release control by core-shell nanofibers: a review.

In recent years, core-shell (CS) nanofiber has widely been used as a carrier for controlled drug release. This outstanding attention toward CS nanofiber is mainly due to its tremendous significance in controllable drug release in specific locations. The major advantage of CS nanofibers is forming a highly porous mesh, boosting its performance for many applications, due to its large surface-to-volume ratio. This inherently high ratio has prompted electrospun fibers to be considered one of the best drug-delivery-systems available, with the capacity to enhance properties such as cell attachment, drug loading, and mass transfer. Using electrospun fibers as CS nanofibers to incorporate different cargos such as antibiotics, anticancer agents, proteins, DNA, RNA, living cells, and diverse growth factors would considerably satisfy the need for a universal carrier in the field of nanotechnology. In addition to their high surface area, other benefit included in these nanofibers is the ability to trap drugs, easily controlled morphology, and their biomimetic characteristics. In this review, by taking the best advantages of the preparation and uses of CS nanofibers, a novel work in the domain of the controlled drug delivery by nanofiber-based scaffolds is presented.

Aptamer immobilization on amino-functionalized metal-organic frameworks: an ultrasensitive platform for the electrochemical diagnostic of Escherichia coli O157:H7.

Herein, we report the development of an electrochemical biosensor for Escherichia coli O157:H7 diagnostic based on amino-functionalized metal-organic frameworks (MOFs) as a new generation of organic-inorganic hybrid nanocomposites. The electrical and morphological properties of MOFs were enhanced by interweaving each isolated MOF crystal with polyaniline (PANI). Subsequent attachment of the amine-modified aptamer to the polyanilinated MOFs was accomplished using glutaraldehyde (GA) as a cross-linking agent. The prepared biocompatible platform was carefully characterized by means of field-emission scanning electron microscopy (FESEM), energy-dispersive spectroscopy (EDS), Fourier transform infrared spectroscopy (FT-IR), and X-ray powder diffraction (XRD) techniques. The biosensor fabrication and its electrochemical characterizations were monitored by cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) techniques. Differential pulse voltammetry (DPV) was applied to monitoring and quantitation of the interaction between the aptamer and E. coli O157:H7 using methylene blue (MB) as an electrochemical indicator. Changes in the reduction peak current of MB in the presence of E. coli O157:H7 was recorded as an analytical signal and indicated a relationship with the logarithm of the E. coli O157:H7 concentration in the range of 2.1 × 101 to 2.1 × 107 CFU mL-1 with a LOQ of 21 CFU mL-1 and LOD of 2 CFU mL-1. The electrochemical aptasensor displayed good recovery values for the detection of E. coli O157:H7 in environmental real samples and also could act as a smart device to investigate the effects of antibacterial agents against E. coli O157:H7.

Design and fabrication of an electrochemical aptasensor using Au nanoparticles/carbon nanoparticles/cellulose nanofibers nanocomposite for rapid and sensitive detection of Staphylococcus aureus.

Since that pathogenic bacteria are major threats to human health, this paper describes the fabrication of an effective and durable sensing platform based on gold nanoparticles/carbon nanoparticles/cellulose nanofibers nanocomposite (AuNPs/CNPs/CNFs) at the surface of glassy carbon electrode for sensitive and selective detection of Staphylococcus aureus (S. aureus). The AuNPs/CNPs/CNFs nanocomposite with the high surface area, excellent conductivity, and good biocompatibility was used for self-assembled of the thiolated specific S. aureus aptamer as a sensing element. The surface morphology of AuNPs/CNPs/CNFs nanocomposite was characterized with field emission scanning electron microscopy (FESEM), energy dispersive spectroscopy (EDS), dynamic light scattering (DLS) and ultraviolet-visible (UV-Vis) spectrophotometric methods. Each aptasensor modification step was monitored with cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) techniques. The fabricated aptasensor exhibited a wide linear dynamic range (1.2 × 101 to 1.2 × 108) CFU mL-1 with a LOD of 1 CFU mL-1 and was be capable to accurate detection and determination of Staphylococcus aureus in human blood serum as a clinical sample with a complex matrix.

Longitudinal Monitoring of Biofilm Formation via Robust Surface-Enhanced Raman Scattering Quantification of Pseudomonas aeruginosa-Produced Metabolites.

Detection of bacterial metabolites at low concentrations in fluids with complex background allows for applications ranging from detecting biomarkers of respiratory infections to identifying contaminated medical instruments. Surface-enhanced Raman scattering (SERS) spectroscopy, when utilizing plasmonic nanogaps, has the relatively unique capacity to reach trace molecular detection limits in a label-free format, yet large-area device fabrication incorporating nanogaps with this level of performance has proven difficult. Here, we demonstrate the advantages of using chemical assembly to fabricate SERS surfaces with controlled nanometer gap spacings between plasmonic nanospheres. Control of nanogap spacings via the length of the chemical crosslinker provides uniform SERS signals, exhibiting detection of pyocyanin, a secondary metabolite of Pseudomonas aeruginosa, in aqueous media at concentration of 100 pg·mL-1. When using machine learning algorithms to analyze the SERS data of the conditioned medium from a bacterial culture, having a more complex background, we achieve 1 ng·mL-1 limit of detection of pyocyanin and robust quantification of concentration spanning 5 orders of magnitude. Nanogaps are also incorporated in an in-line microfluidic device, enabling longitudinal monitoring of P. aeruginosa biofilm formation via rapid pyocyanin detection in a medium effluent as early as 3 h after inoculation and quantification in under 9 h. Surface-attached bacteria exposed to a bactericidal antibiotic were differentially less susceptible after 10 h of growth, indicating that these devices may be useful for early intervention of bacterial infections.