Probing the Dynamic Interaction between Damaged DNA and a Cellular Responsive Protein Using a Piezoelectric Mass Biosensor

Single-atom sites on perovskite chips for record-high sensitivity and quantification in SERS

Surface enhanced Raman scattering (SERS) is a rapid and nondestructive technique that is capable of detecting and identifying chemical or biological compounds. Sensitive SERS quantification is vital for practical applications, particularly for portable detection of biomolecules such as amino acids and nucleotides. However, few approaches can achieve sensitive and quantitative Raman detection of these most fundamental components in biology. Herein, a noble-metal-free single-atom site on a chip strategy was applied to modify single tungsten atom oxide on a lead halide perovskite, which provides sensitive SERS quantification for various analytes, including rhodamine, tyrosine and cytosine. The single-atom site on a chip can enable quantitative linear SERS responses of rhodamine (10^-6-1 mmol L^-1), tyrosine (0.06-1 mmol L^-1) and cytosine (0.2-45 mmol L^-1), respectively, which all achieve record-high enhancement factors among plasmonic-free semiconductors. The experimental test and theoretical simulation both reveal that the enhanced mechanism can be ascribed to the controllable single-atom site, which can not only trap photoinduced electrons from the perovskite substrate but also enhance the highly efficient and quantitative charge transfer to analytes. Furthermore, the label-free strategy of single-atom sites on a chip can be applied in a portable Raman platform to obtain a sensitivity similar to that on a benchtop instrument, which can be readily extended to various biomolecules for low-cost, widely demanded and more precise point-of-care testing or in-vitro detection.

ELECTRONIC SUPPLEMENTARY MATERIAL

Supplementary material is available for this article at 10.1007/s40843-022-1968-5 and is accessible for authorized users.

Challenges and Opportunities for Clustered Regularly Interspaced Short Palindromic Repeats Based Molecular Biosensing

Clustered regularly interspaced short palindromic repeats, CRISPR, has recently emerged as a powerful molecular biosensing tool for nucleic acids and other biomarkers due to its unique properties such as collateral cleavage nature, room temperature reaction conditions, and high target-recognition specificity. Numerous platforms have been developed to leverage the CRISPR assay for ultrasensitive biosensing applications. However, to be considered as a new gold standard, several key challenges for CRISPR molecular biosensing must be addressed. In this paper, we briefly review the history of biosensors, followed by the current status of nucleic acid-based detection methods. We then discuss the current challenges pertaining to CRISPR-based nucleic acid detection, followed by the recent breakthroughs addressing these challenges. We focus upon future advancements required to enable rapid, simple, sensitive, specific, multiplexed, amplification-free, and shelf-stable CRISPR-based molecular biosensors.

Advancing Biosensors with Machine Learning

Chemometrics play a critical role in biosensors-based detection, analysis, and diagnosis. Nowadays, as a branch of artificial intelligence (AI), machine learning (ML) have achieved impressive advances. However, novel advanced ML methods, especially deep learning, which is famous for image analysis, facial recognition, and speech recognition, has remained relatively elusive to the biosensor community. Herein, how ML can be beneficial to biosensors is systematically discussed. The advantages and drawbacks of most popular ML algorithms are summarized on the basis of sensing data analysis. Specially, deep learning methods such as convolutional neural network (CNN) and recurrent neural network (RNN) are emphasized. Diverse ML-assisted electrochemical biosensors, wearable electronics, SERS and other spectra-based biosensors, fluorescence biosensors and colorimetric biosensors are comprehensively discussed. Furthermore, biosensor networks and multibiosensor data fusion are introduced. This review will nicely bridge ML with biosensors, and greatly expand chemometrics for detection, analysis, and diagnosis.

Ultrasensitive Poly(boric acid) Hydrogel-Coated Quartz Crystal Microbalance Sensor by Using UV Pressing-Assisted Polymerization for Saliva Glucose Monitoring

Quartz crystal microbalance (QCM) has attracted extensive attention in the field of biological analysis and detection because of its high sensitivity, fast response, real-time measurement, good operability, and low-cost production. However, to detect the trace amounts of small molecules, such as low-concentration saliva glucose under physiological conditions, is still a major challenge. Herein, the surface of a QCM chip was coated with a poly(boric acid)-based hydrogel using UV pressing-assisted polymerization to obtain a simple device for glucose detection. The designed QCM sensor shows a record-low detection limit of glucose (3 mg/L at pH 7.5), which is ∼30 times lower than that of sensors fabricated by conventional surface initiation-spin coating. The outperformance of the poly(boric acid) hydrogel-coated QCM sensor is probably due to the uniform and compact microstructure, as well as the presence of sufficient glucose-binding sites resulting from the hydrogel coating generated by UV pressing-assisted polymerization. This method provides an important solution to detect the trace amounts of small organic molecules or ions and has the potential to push forward the practical applications of QCM sensors.

Materials Nanoarchitectonics for Mechanical Tools in Chemical and Biological Sensing

In this Focus Review, nanoarchitectonic approaches for mechanical-action-based chemical and biological sensors are briefly discussed. In particular, recent examples of piezoelectric devices, such as quartz crystal microbalances (QCM and QCM-D) and a membrane-type surface stress sensor (MSS), are introduced. Sensors need well-designed nanostructured sensing materials for the sensitive and selective detection of specific targets. Nanoarchitectonic approaches for sensing materials, such as mesoporous materials, 2D materials, fullerene assemblies, supported lipid bilayers, and layer-by-layer assemblies, are highlighted. Based on these sensing approaches, examples of bioanalytical applications are presented for toxic gas detection, cell membrane interactions, label-free biomolecular assays, anticancer drug evaluation, complement activation-related multiprotein membrane attack complexes, and daily biodiagnosis, which are partially supported by data analysis, such as machine learning and principal component analysis.

Synthesis of benzo[6]urils and their selective interactions with bipyridines

Benzo[6]urils bearing hydroxymethyl or methyl groups have been synthesized with a facile method, and their supramolecular interactions with bipyridine guests have been investigated.