SPE based soil processing and aptasensor integrated detection system for rapid on site screening of arsenic contamination in soil

Detection of Emerging Pollutants Using Aptamer-Based Biosensors: Recent Advances, Challenges, and Outlook

The synergistic potentialities of innovative materials that include aptamers have opened new paradigms in biosensing platforms for high-throughput monitoring systems. The available nucleobase functional moieties in aptamers offer exclusive features for bioanalytical sensing applications. In this context, compared to various in-practice biological recognition elements, the utilization of aptamers in detection platforms results in an extensive range of advantages in terms of design flexibility, stability, and sensitivity, among other attributes. Thus, the utilization of aptamers-based biosensing platforms is extensively anticipated to meet unaddressed challenges of various in-practice and standard analytical and sensing techniques. Furthermore, the superior characteristics of aptasensors have led to their applicability in the detection of harmful pollutants present in ever-increasing concentrations in different environmental matrices and water bodies, seeking to achieve simple and real-time monitoring. Considering the above-mentioned critiques and notable functional attributes of aptamers, herein, we reviewed aptamers as a fascinating interface to design, develop, and deploy a new generation of monitoring systems to aid modern bioanalytical sensing applications. Moreover, this review aims to summarize the most recent advances in the development and application of aptasensors for the detection of various emerging pollutants (EPs), e.g., pharmaceutical, and personal care products (PPCPs), endocrine-disrupting chemicals (EDCs), pesticides and other agricultural-related compounds, and toxic heavy elements. In addition, the limitations and current challenges are also reviewed, considering the technical constraints and complexity of the environmental samples.

Smartphone based aptasensors as intelligent biodevice for food contamination detection in food and soil samples: Recent advances

Nowadays, the integration of conventional analytical approaches with smartphones has been developed novel, emerging and affordable devices for improving on-site detection platforms in the fields of food safety. Smartphone-based aptasensors as the next generation of portable aptasensing technique has attracted considerable attention as it offers a semi-automated user interface that can be exploited by inexpert characters. Wireless data transferability is an undeniable advantage that home-testing platforms have as well as it can suggest high computational power. In addition, these types of biodevices can provide real-time monitoring in terms of exchanging digital networks in real-time. To elaborate, the ability of smartphones to connect through the Internet is one of the most critical advantages of smartphone-based aptasensor that can be uploaded to Cloud databases and results can be disseminated as spatio-temporal maps across the globe. This review focused on the recent progress and technical breakthroughs of aptasensor on the smartphone as a groundbreaking enterprise in the field of biochemical analysis, importantly in the aspect of the combination of different types of biosensors including electrochemical, optical and colorimetric. In our opinion, this review can broaden our understanding of using smartphones as a portable sensing approach by addressing the current challenges and future perspectives.

Thiourea derivatives acting as functional monomers of As(Ш) molecular imprinted polymers: A theoretical and experimental study on binding mechanisms

Thiourea derivatives are expected to be potential monomers of As(Ш) molecular imprinted polymers (MIPs) which are used to specifically recognize As(Ш). However, the specific recognition and binding mechanisms between template and monomers are unclear, which limits the practical applications of MIPs in As(Ш)detection. In this work, density functional theory (DFT) calculations, molecular dynamics (MD) simulations and experimental methods were jointly applied to explore the binding interactions between H₃AsO₃ and thiourea derivatives and environmental factors influences, aiming to find out the best monomer and optimal preparation conditions for H₃AsO₃ MIPs. Among five monomer candidates, (2, 6-difluorophenyl) thiourea (FT) was calculated to be the most potential one, while allyl thiourea (AT) was the second choice. Configurations of the most stable binding complexes were found out. The optimal solvent was found to be toluene and the bindings were more favorable at pH 7.5 in aqueous solution. Besides, EGDMA was proved as the best cross-linker with the optimal ratio of template: monomer: cross-linker= 2:3:20. Moreover, the binding interactions were identified to be hydrogen bonds, and the non-covalent nature was revealed. These findings provide references for efficient design and preparation of good-performance H₃AsO₃ MIPs, which can be used to detect and remove As(Ш) from environment.

Recent Trends in Biosensors for Environmental Quality Monitoring

The monitoring of environmental pollution requires fast, reliable, cost-effective and small devices. This need explains the recent trends in the development of biosensing devices for pollutant detection. The present review aims to summarize the newest trends regarding the use of biosensors to detect environmental contaminants. Enzyme, whole cell, antibody, aptamer, and DNA-based biosensors and biomimetic sensors are discussed. We summarize their applicability to the detection of various pollutants and mention their constructive characteristics. Several detection principles are used in biosensor design: amperometry, conductometry, luminescence, etc. They differ in terms of rapidity, sensitivity, profitability, and design. Each one is characterized by specific selectivity and detection limits depending on the sensitive element. Mimetic biosensors are slowly gaining attention from researchers and users due to their advantages compared with classical ones. Further studies are necessary for the development of robust biosensing devices that can successfully be used for the detection of pollutants from complex matrices without prior sample preparation.

AuNPs- Aβ-Ni-HRP sandwich assay: A new sensitive colorimetric method for the detection of Aβ 1-40

Amyloid β-peptide (Aβ) is a key predictor for preclinical diagnosis of Alzheimer's disease (AD) and vascular diseases. In this work, we propose a gold nanoparticle (AuNPs)-Aβ-nickel (Ni)-horseradish peroxidase (HRP) based colorimetric assay for the detection of Aβ_1-40. The consecutive binding of Aβ_1-40 to AuNPs and metal ions is designed and examined for Aβ-specific aggregation of AuNPs and the generation of quantitative colorimetric signals. The affinity of Aβ_1-40 towards various metal ions was studied first, and two metal ions, Cu and Ni, were specifically tested with Metal Ion-Binding Site Prediction (MIB) and High-resolution Electrospray Ionization Mass Spectrometry (HR-ESI-MS). Subsequently, the binding of Aβ_1-40 and AuNPs was examined, and the binding between Aβ-AuNPs and Ni-HRP was finally analyzed by UV-Vis and nano-zetasizer. Based on the characterized dual binding of Aβ_1-40, a colorimetric sandwich assay was developed and the analytical performance of the developed assay has been evaluated with standard solutions and human serum samples. Good linearity within a range from 0 nM to 10 nM was found. The detection limits of 0.22 nM in the standard sample and 0.23 nM in the human serum sample have been demonstrated. The newly developed colorimetric sandwich assay is a short, simple, antibody-free assay and achieves high sensitivity with only 100 μL Aβ_1-40 samples. The assay has immense potential for the detection of Aβ_1-40 in biological or biomedical diagnosis.

Advances in aptamer screening and aptasensors' detection of heavy metal ions

Heavy metal pollution has become more and more serious with industrial development and resource exploitation. Because heavy metal ions are difficult to be biodegraded, they accumulate in the human body and cause serious threat to human health. However, the conventional methods to detect heavy metal ions are more strictly to the requirements by detection equipment, sample pretreatment, experimental environment, etc. Aptasensor has the advantages of strong specificity, high sensitivity and simple preparation to detect small molecules, which provides a new direction platform in the detection of heavy metal ions. This paper reviews the selection of aptamers as target for heavy metal ions since the 21th century and aptasensors application for detection of heavy metal ions that were reported in the past five years. Firstly, the selection methods for aptamers with high specificity and high affinity are introduced. Construction methods and research progress on sensor based aptamers as recognition element are also introduced systematically. Finally, the challenges and future opportunities of aptasensors in detecting heavy metal ions are discussed.

Facile fabrication of magnetic covalent organic frameworks and their application in selective enrichment of polychlorinated naphthalenes from fine particulate matter

Magnetic covalent organic frameworks (Fe₃O₄@TPPCl₄) were synthesized via a one-pot process in which magnetic nanoparticles (Fe₃O₄@MNP) served as a magnetic core and 2,4,6-trihydroxy-1,3,5-benzenetricarbaldehyde (TP) and 2,2',5,5'-tetrachlorobenzidine (PCl₄) as two building blocks to form a shell. The as-prepared Fe₃O₄@TPPCl₄ nanoparticles have superior features, including large surface area (186.5 m² g^-1), high porosity, strong magnetic responsiveness (42.6 emu g^-1), high chlorine content, and outstanding thermal stability, which make them an ideal adsorbent for highly selective enrichment of polychlorinated naphthalenes (PCNs). Combining with atmospheric pressure gas chromatography tandem mass spectrometry (APGC-MS/MS), a simple analytical method of Fe₃O₄@TPPCl₄-based magnetic solid-phase extraction (MSPE)-APGC-MS/MS was developed, which exhibited good linearity (r ≥ 0.9991) for eight PCNs in the concentration range 0.1-100 ng L^-1. Moreover, low detection limits (0.005-0.325 ng L^-1), high enrichment factors (46.62-81.97-fold), and good relative standard deviations (RSDs) of inter-day (n = 3, 1.64 to 7.44%) and day-to-day (n = 3, 2.62 to 8.23%) were achieved. This method was successfully applied to the selective enrichment of PCNs in fine particulate matter (PM)_2.5 samples, and ultra-trace PCNs were found in the range 1.56-3.75 ng kg^-1 with satisfactory recoveries (93.11-105.81%). The successful application demonstrated the great potential of Fe₃O₄@TPPCl₄ nanoparticles as an adsorbent for enrichment of halogenated compounds. Schematic presented one-pot synthesis of magnetic covalent organic framework nanocomposites (Fe₃O₄@TPPCl₄) and their application in the selective enrichment of PCNs from PM_2.5 prior to APGC-MS/MS analysis.

Emerging risks of toxic metal(loid)s in soil-vegetables influenced by steel-making activities and isotopic source apportionment

Industrial activities tend to deteriorate adjacent agricultural lands due to accumulation of potentially toxic elements in soils and crops. However, better understanding of their distinctive source partitions and transfer process remains insufficient in steel-making area. The paper focuses on the pollution levels, health risks, and provenance identification of Tl, As, Pb, Cu, Ni, Co, Sb, Cd, Zn, Be, Cr, Fe, Mn, Mo, Sn, and V in common vegetables from different farmlands near a steel-making plant. The results showed that the Tl, As, Pb, Cd, Cr, Cu and Mn were of high-level contamination in soils and generally above the maximum permissible level (MPL). Calculation using hazard quotients (HQ) exhibited that consumption of the studied vegetables may entail significant health risks to residents, especially for children, resulting from the elevated contents of Tl, As and associated toxic elements. Calculation by binary mixing model using Pb isotopic compositions suggested that steel-making activities contributed to 35-80% of the contamination of Pb and As in vegetables. It is necessary to adopt appropriate remediation measures to mitigate the farmland contamination and ensure the food safety of the agricultural products.

Estimation of Soil Arsenic Content with Hyperspectral Remote Sensing

With the continuous application of arsenic-containing chemicals, arsenic pollution in soil has become a serious problem worldwide. The detection of arsenic pollution in soil is of great significance to the protection and restoration of soil. Hyperspectral remote sensing is able to effectively monitor heavy metal pollution in soil. However, due to the possible complex nonlinear relationship between soil arsenic (As) content and the spectrum and data redundancy, an estimation model with high efficiency and accuracy is urgently needed. In response to this situation, 62 samples and 27 samples were collected in Daye and Honghu, Hubei Province, respectively. Spectral measurement and physical and chemical analysis were performed in the laboratory to obtain the As content and spectral reflectance. After the continuum removal (CR) was performed, the stable competitive adaptive reweighting sampling algorithm coupled the successive projections algorithm (sCARS-SPA) was used for characteristic band selection, which effectively solves the problem of data redundancy and collinearity. Partial least squares regression (PLSR), radial basis function neural network (RBFNN), and shuffled frog leaping algorithm optimization of the RBFNN (SFLA-RBFNN) were established in the characteristic wavelengths to predict soil As content. These results show that the sCARS-SPA-SFLA-RBFNN model has the best universality and high prediction accuracy in different land-use types, which is a scientific and effective method for estimating the soil As content.

Label-Free Electrochemical Microfluidic Chip for the Antimicrobial Susceptibility Testing

The emergence and spread of antibiotic-resistant bacteria is a global threat to human health. An accurate antibiotic susceptibility test (AST) before initiating the treatment is paramount in the treatment and bacterial resistance control. However, the current AST methods either are complex, use chemical and biological labels, lack multiplexing, are expensive, or are too slow to be used for routine screening. The primary objective of the current study is to develop an automated electrochemical microfluidic chip (EMC) for simple and rapid AST. The microfluidic channels and gold microelectrodes were designed for the automation of antibiotic mixing and distribution in multiple test chambers and for electrical signal measurements. The designed chip was tested for AST with E. coli samples, and the results were compared with conventional broth microdilution. The presented EMC provided rapid bacterial count and AST in 170 and 150 min, respectively, while the conventional broth microdilution evaluates in 450 and 240 min, respectively. The rapid AST capability of the EMC was further demonstrated with the artificial urine samples, and the results were obtained in 270 min, which was 90 min faster than the broth microdilution method. Additionally, the minimum inhibitory concentration (MIC) was evaluated on the EMC and compared with the results from an AlamarBlue assay. The experimental results indicate the sensitivity of the chip, minimum loss of antibiotics, and eventually, reduction in the evolution of antibiotic resistance. Cumulatively, we have developed an automated, label-free, economical, rapid, robust, and user-friendly EMC for the evaluation of AST in urine samples.