A Dual Immunological Raman-Enabled Crosschecking Test (DIRECT) for Detection of Bacteria in Low Moisture Food

Recent Progress in Nanotechnology-Based Approaches for Food Monitoring

Throughout the food supply chain, including production, storage, and distribution, food can be contaminated by harmful chemicals and microorganisms, resulting in a severe threat to human health. In recent years, the rapid advancement and development of nanotechnology proposed revolutionary solutions to solve several problems in scientific and industrial areas, including food monitoring. Nanotechnology can be incorporated into chemical and biological sensors to improve analytical performance, such as response time, sensitivity, selectivity, reliability, and accuracy. Based on the characteristics of the contaminants and the detection methods, nanotechnology can be applied in different ways in order to improve conventional techniques. Nanomaterials such as nanoparticles, nanorods, nanosheets, nanocomposites, nanotubes, and nanowires provide various functions for the immobilization and labeling of contaminants in electrochemical and optical detection. This review summarizes the recent advances in nanotechnology for detecting chemical and biological contaminations in the food supply chain.

An Improved Automated High-Throughput Efficient Microplate Reader for Rapid Colorimetric Biosensing

A high-throughput instrument to measure the full spectral properties of biochemical agents is necessary for fast screening in fields such as medical tests, environmental monitoring, and food analysis. However, this need has currently not been fully met by the commercial microplate reader (CMR). In this study, we have developed an automated high-throughput efficient microplate reader (AHTEMR) platform by combining a spectrometer and high-precision ball screw two-dimensional motion slide together, for high-throughput and full-spectrum-required biochemical assays. A two-dimensional slide working on a ball screw was driven by a stepper motor with a custom-designed master control circuit and used as a motion system of the AHTEMR platform to achieve precise positioning and fast movement of the microplate during measurements. A compact spectrometer was coupled with an in-house designed optical pathway system and used to achieve rapid capture of the full spectral properties of biochemical agents. In a performance test, the AHTEMR platform successfully measured the full spectral absorbance of bovine serum albumin (BSA) and glucose solution in multiple wells of the microplate within several minutes and presented the real-time full spectral absorbance of BSA and glucose solution. Compared with the CMR, the AHTEMR is 79 times faster in full-spectrum measurements and 2.38 times more sensitive at the optimal wavelength of 562 nm. The rapid measurement also demonstrated the great capacity of the AHTEMR platform for screening out the best colorimetric wavelengths for tests of BSA and glucose development, which will provide a promising approach to achieving high-throughput and full-spectrum-required biochemical assays.

Label-Free Differentiation of Cancer and Non-Cancer Cells Based on Machine-Learning-Algorithm-Assisted Fast Raman Imaging

This paper proposes a rapid, label-free, and non-invasive approach for identifying murine cancer cells (B16F10 melanoma cancer cells) from non-cancer cells (C2C12 muscle cells) using machine-learning-assisted Raman spectroscopic imaging. Through quick Raman spectroscopic imaging, a hyperspectral data processing approach based on machine learning methods proved capable of presenting the cell structure and distinguishing cancer cells from non-cancer muscle cells without compromising full-spectrum information. This study discovered that biomolecular information-nucleic acids, proteins, and lipids-from cells could be retrieved efficiently from low-quality hyperspectral Raman datasets and then employed for cell line differentiation.

Applications of surface-enhanced Raman spectroscopy in environmental detection

As the human population grows, the anthropogenic impacts from various agricultural and industrial processes produce unwanted contaminants in the environment. The accurate, sensitive and rapid detection of such contaminants is vital for human health and safety. Surface-enhanced Raman spectroscopy (SERS) is a valuable analytical tool with wide applications in environmental contaminant monitoring. The aim of this review is to summarize recent advancements within SERS research as it applies to environmental detection, with a focus on research published or accessible from January 2021 through December 2021 including early-access publications. Our goal is to provide a wide breadth of information that can be used to provide background knowledge of the field, as well as inform and encourage further development of SERS techniques in protecting environmental quality and safety. Specifically, we highlight the characteristics of effective SERS nanosubstrates, and explore methods for the SERS detection of inorganic, organic, and biological contaminants including heavy metals, pharmaceuticals, plastic particles, synthetic dyes, pesticides, viruses, bacteria and mycotoxins. We also discuss the current limitations of SERS technologies in environmental detection and propose several avenues for future investigation. We encourage researchers to fill in the identified gaps so that SERS can be implemented in a real-world environment more effectively and efficiently, ultimately providing reliable and timely data to help and make science-based strategies and policies to protect environmental safety and public health.

Nanotechnology in food and water security: on-site detection of agricultural pollutants through surface-enhanced Raman spectroscopy

Agricultural pollutants are harmful components threatening human health, wildlife, the environment, and the ecosystem. To avoid their exposure, developing prevention and detection systems with high sensitivity and selectivity is required. Most conventional methods, including molecular and chromatographic techniques, cannot be adopted for outdoor on-site detection even though they can provide sensitive and selective detection. Thus, detection platforms that can provide on-site detection via miniaturized and high throughput systems should be developed. As an alternative method, surface-enhanced Raman scattering (SERS) provides unique information about the substances in the presence of plasmonic nanostructures, and it can be portable with the use of portable detection systems and spectrometers. In this study, on-site detection of agricultural pollutants through SERS is reviewed. Three different types of agricultural pollutants were pointed out. On-site detection of biological pollutants, including bacteria and viruses, is reviewed as the first type of pollutant. As a second type, the detection of pesticides, antibiotics, and additives are focused on as chemical pollutants. The third group includes the detection of microplastics and also nanoparticles from the environment.