SPE coupled to AAS trace determination of Cd(II) and Zn(II) in food samples using amine functionalized GMA-MMA-EGDMA terpolymer: Isotherm and kinetic studies

Simultaneous extraction of five heavy metal ions from root vegetables via dual-frequency ultrasound-assisted enzymatic digestion

The dual-frequency ultrasound-assisted enzymatic digestion (DUED) technique was developed for synchronous green extraction of five heavy metal ions in root vegetables. The combination of α-amylase, cellulase, and papain showed significant advantageous in extracting heavy metal ions. Under optimized dual-frequency ultrasonic conditions, the extraction rates of Cr, As, Cd, Pb, and Hg in carrots reached 99.04%, 105.88%, 104.65%, 104.10%, and 103.13% respectively. And the extraction process is highly efficient, completing in just 15 min. Compared to conventional microwave-assisted acid hydrolysis method, this technique eliminates the need for high-temperature concentrated acid, enhancing its environmental sustainability while maintaining mild reaction conditions, making it ideal for biosensors application. Additionally, simultaneous extraction and detection of four heavy metals in lotus roots were successfully achieved by using DUED and a fluorescent paper-based microfluidic chip. The obtained results are consistent with those obtained using conventional methods.

A portable multi-channel fluorescent paper-based microfluidic chip based on smartphone imaging for simultaneous detection of four heavy metals

Due to the excessive contamination of heavy metals pollution, it is very urgent and necessary to develop a real-time detection method for the heavy metals in food. As a target sensing device, a paper-based microfluidic device (μPAD) has the advantages of simplicity, low-cost, and portability. In this study, a self-driven microfluidic paper-based chip was first developed for the simultaneous detection of four targets. The channels on the microfluidic chip were prepared by using wax printing and automatic screen printing on the filter paper, where liquid flowed by capillary force without pump assistance. Based on the specific binding ability of aptamers to heavy metals, a "turn-on" fluorescence aptasensor for the simultaneous detection of four heavy metal ions was developed on the proposed multi-channel device via smartphone imaging. The obtained fluorescence images were digitized into RGB color values by Image J software, and an M-mode was established to realize the quantitative detection of heavy metal ions. Under optimal conditions, the limits of detection for lead(II), mercury(II), cadmium(II), and arsenic(III) were 4.20 nM, 1.70 nM, 2.04 nM, and 1.65 nM, respectively. Furthermore, the aptasensor was successfully applied to the quantitative detection of four heavy metal ions in apple and lettuce samples with recovery rates of 84.0%-104.1%.

Prediction and visualization of gene modulated ultralow cadmium accumulation in brown rice grains by hyperspectral imaging

Monitoring (including prediction and visualization) the gene modulated cadmium (Cd) accumulation in rice grains is one of the most important steps for identification of key transporter genes responsible for grain Cd accumulation and breeding low grain-Cd-accumulating rice cultivars. A method to predict and visualize the gene modulated ultralow Cd accumulation in brown rice grains based on the hyperspectral image (HSI) technology is proposed in this study. Firstly, the Vis-NIR HSIs of brown rice grain samples with 48Cd content levels induced by gene modulation (ranging from 0.0637 to 0.1845 mg/kg) are collected using HSI system. Then, Kernel-ridge (KRR) and random forest (RFR) regression models based on full spectral data and the data after feature dimension reduction (FDR) with kernel principal component analysis (KPCA) and truncated singular value decomposition (TSVD) algorithms are established to predict the Cd contents. RFR model shows poor performance due to the over-fitting based on the full spectral data, while the KRR model can obtain a good predict accuracy with R_p² of 0.9035, RMSEP of 0.0037 and RPD of 3.278. After the FDR of the full spectral data, the RFR model combined with TSVD reaches the optimum prediction accuracy with R_p² of 0.9056, RMSEP of 0.0074 and RPD of 3.318, and the best prediction precision of KRR model can also be further enhanced by TSVD with R_p² of 0.9224, RMSEP of 0.0067 and RPD of 3.512. Finally, the visualization of the predicted Cd accumulation in brown rice grains are realized based on the best regression model (KRR + TSVD). The results of this work indicate that Vis-NIR HSI has great potential for detection and visualization gene modulation induced ultralow Cd accumulation and transport in rice crops.

Ensuring high selectivity for preconcentration and detection of ultra-trace cadmium using a phage-functionalized metal–organic framework

A phage functionalized metal–organic framework for selective preconcentration and detection of trace cadmium.

Ladder chain Cd-based polymer as a highly effective adsorbent for removal of Congo red

Developing of high effective and fast-rate adsorbent materials has been recently attracted intensive attentions all over the world due to organic dye polluted water treatment. However, few studies have been reported on the ultrahigh-capacity and fast-rate removal of Congo red. In this work, a new stable Cd-based coordination polymer exhibits excellent adsorption performance towards Congo Red. This ladder chain [Cd₄(H₂L)₄(H₂O)₈(NDS)]_n·3n(NDS) (I) (H₂L = N1,N2-bis(pyridin-3-ylmethyl) ethane-1,2-diamine, 1,5-H₂NDS = 1,5-naphthalene disulfonic acid) has been successfully synthesized by the hydrothermal reaction. At room temperature, the experimental adsorption capacity of coordination polymer (I) towards Congo red can reach up to 16,880 mg g^-1 in 20 min (pH = 2.0-3.2), and its higher capacity and faster rate are all better than those in reported inorganic and metal-organic frameworks absorbents. The adsorption process is spontaneous and endothermic reaction, and fits well with the second-order kinetics, Langmuir and Scatchard isotherm adsorption models. The excellent adsorption performance of (I) towards Congo red is related to the strong electrostatic, various hydrogen bonding and π-π stacking interactions under acidic conditions.

Development and treatment procedure of arsenic-contaminated water using a new and green chitosan sorbent: kinetic, isotherm, thermodynamic and dynamic studies

Arsenic is classified as one of the most toxic elements for humans by the World Health Organization (WHO). With the tightening drinking water regulation to 10 μg L−1 by the WHO, it is necessary to find efficient sorbent materials for arsenic. In this work, the removal of arsenic(V) from water is achieved with an insoluble chitosan sorbent in the protonated form obtained by a simple heating process. Kinetic studies show a very fast sorption (less than 10 min). The Langmuir isotherm model is best describing experimental data with a capacity of 42 mg g−1 at pH 8. The sorption process is based on anion exchange (chemisorption) determined from the Dubinin-Radushkevich model. The sorption efficiency of the chitosan sorbent is 97% at low concentrations (e.g. 100 μg L−1). Thermodynamic analysis reveals that the sorption process is exothermic and is controlled by enthalpic factors. Breakthrough curves (BTC) were acquired in real-time by instrumental chromatography and was better described by the Thomas model. BTC from column sorption and desorption with a salt solution suggest that this sorbent is relevant for large scale applications. With this new renewable product, it will be possible to treat arsenic contaminated water at low cost and with little waste (concentration factor of 1500).