Thin-film solid-phase microextraction of pesticides from cereal samples using electrospun polyvinyl alcohol/modified chitosan/porous organic framework nanofibers.

In this study, a coating of electrospun polyvinyl alcohol/modified chitosan/hydroxy-containing porous organic framework (PVA/MCS/HC-POF) was fabricated and applied as a novel sorbent for thin-film solid-phase microextraction of pesticides from cereal samples, followed by HPLC-UV. The successful fabrication of PVA/MCS/HC-POF was confirmed through characterization tests. The functional group of MCS and a large number of hydroxyl groups on the HC-POF structure contributed to the co-extraction of pesticides. Under the optimum conditions, the calibration plots were linear within the range of 5.0-800 ng mL-1 (r2 ≥ 0.978), and the limits of detection were obtained below 4.0 ng mL-1. The method's precision was investigated through intra-day, inter-day, and film-to-film RSD (%) measurements, all of which were less than 6.5 %, 8.2 %, and 10.0 %, respectively. Furthermore, satisfactory recoveries ranging from 63.3 % to 79.0 % were obtained. Accordingly, the proposed method can be considered a suitable alternative for measuring trace amounts of pesticides in cereal samples.

Preparation of electrospun polyacrylonitrile/ϒ-cyclodextrin metal-organic framework nanofibers for extraction of multi-classes herbicides from cereal samples before HPLC-UV analysis.

This study employed thin-film solid-phase microextraction procedure as a simple, sensitive, green, and solvent-free method for the co-extraction of multi-classes herbicides from cereal samples before HPLC-UV analysis. To provide an efficient sorbent, electrospun nanofibers of the crosslinked polyacrilonitril/ϒ-cyclodextrin-metal-organic framework (PAN/ϒ-CD-MOF) were successfully fabricated and assessed as a new thin-film adsorbent. Under the optimal conditions (desorption solvent: acetonitrile, desorption time: 5 min, sample solution pH: 7.0, salt concentration: 15% (w/w), and extraction time: 15 min), good linearity in the range of 2.5-1250.0 ng/mL (r2 ≥ 0.992) was obtained. The detection limits were 0.75-2.50 ng/mL. The extraction recoveries and relative recoveries were 64.9-75.7% and 92.9-106.1%, respectively. The method showed good precision as the relative standard deviations were ≤ 6.3%. Finally, the developed method was applied efficiently for trace analysis of the herbicides in wheat, rice, and barley samples. Generally, the proposed method provided a simple, sensitive, environmentally friendly, and relatively fast approach.

Magnetic dispersive solid-phase extraction of triazole and triazine pesticides from vegetable samples using a hydrophilic-lipophilic sorbent based on maltodextrin- and ß-cyclodextrin-functionalized graphene oxide.

Maltodextrin- and ß-cyclodextrin-functionalized magnetic graphene oxide (mGO/ß-CD/MD), a novel hydrophilic-lipophilic composite, was successfully fabricated and used for the co-extraction of triazines and triazoles from vegetable samples before HPLC-UV analysis. mGO/ß-CD/MD was synthesized by chemical bonding of ß-CD and MD to the surface of mGO, using epichlorohydrin (ECH) as a linker. The successful synthesis of mGO/ß-CD/MD was confirmed by characterization tests, including attenuated total reflection-Fourier transform infrared spectroscopy (ATR-FTIR), X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), vibrating sample magnetometry (VSM), thermogravimetric analysis (TGA), energy-dispersive X-ray spectroscopy (EDX), Brunauer-Emmett-Teller (BET), and Barrett-Joyner-Halenda (BJH) analyses. The hydrophobic cavity of ß-CD and a large number of hydroxyl groups on the MD structure contributed to the co-extraction of mentioned pesticides with a wide range of polarity. Under the optimized condition (sorbent amount, 30 mg; desorption time, 10 min; desorption solvent volume, 300 µL; desorption solvent, methanol/acetonitrile (1:1) containing 5% (v/v) acetic acid; extraction time, 20 min; and pH of sample solution, 7.0), good linearity within the range 1.0-1000 µg L-1 (r2 ≥ 0.992) was achieved. Extraction efficiencies were in the range 66.4-95.3%, and the limits of detection were 0.01-0.08 µg L-1. Relative recoveries for spiked samples were obtained in the range 88.4-112.0%, indicating that the matrix effect was insignificant, and good precisions (intra- and inter-day) were also achieved (RSDs < 9.0%, n = 3). The results confirmed that the developed method was efficient for the determination  of trace amounts of pesticides in potato, tomato, and corn samples.

Recent advances and applications of cyclodextrins in magnetic solid phase extraction.

Cyclodextrins (CDs) as a family of cyclic oligosaccharides are toroidal with a hydrophobic interior and a hydrophilic exterior. They are well-known for their ability to form host-guest inclusion complexes with different compounds. They are used as chiral stationary phases in high performance liquid chromatography (HPLC) and gas chromatography (GC) or as chiral reagents in the background electrolyte of capillary electrophoresis (CE). In recent years, they have been used for modification of sorbents or as sorbents in solid phase extraction (SPE) procedures. Magnetic solid-phase extraction (MSPE), as a new type of SPE procedure, has received considerable attention due to its rapid phase separation process as compared to traditional extraction mode. This review covers the synthesis of CD-based magnetic sorbents (such as immobilization of CDs onto the different supports, production of nanosponges, and making hybrid substances with nanomaterials) and the use of these compounds in MSPE of different analytes from biological, environmental, and food samples. Also, prospects of CD-based sorbents for sample pre-treatment are also proposed.

Blood Lactate Concentration Prediction in Critical Care.

Blood lactate concentration is a reliable risk indicator of deterioration in critical care requiring frequent blood sampling. However, lactate measurement is an invasive procedure that can increase risk of infections. Yet there is no clinical consensus on the frequency of measurements. In response we investigate whether machine learning algorithms can be used to predict blood lactate concentration from ICU health records. We evaluate the performance of different prediction algorithms using a multi-centre critical care dataset containing 13,464 patients. Furthermore, we analyse impact of missing value handling methods in prediction performance for each algorithm. Our experimental analysis show promising results, establishing a baseline for further investigation into this problem.

Monitoring and detecting faults in wastewater treatment plants using deep learning.

Wastewater treatment plants use many sensors to control energy consumption and discharge quality. These sensors produce a vast amount of data which can be efficiently monitored by automatic systems. Consequently, several different statistical and learning methods are proposed in the literature which can automatically detect faults. While these methods have shown promising results, the nonlinear dynamics and complex interactions of the variables in wastewater data necessitate more powerful methods with higher learning capacities. In response, this study focusses on modelling faults in the oxidation and nitrification process. Specifically, this study investigates a method based on deep neural networks (specifically, long short-term memory) compared with statistical and traditional machine-learning methods. The network is specifically designed to capture temporal behaviour of sensor data. The proposed method is evaluated on a real-life dataset containing over 5.1 million sensor data points. The method achieved a fault detection rate (recall) of over 92%, thus outperforming traditional methods and enabling timely detection of collective faults.

Magnetic nanocomposite of chitosan-Schiff base grafted graphene oxide for lead analysis in whole blood.

A new Schiff base grafted graphene oxide-magnetic chitosan was utilized as a novel sorbent for extraction and quantification of lead ion in blood samples via dispersive magnetic solid phase extraction. The prepared nanocomposite sorbent was characterized by SEM, TEM, FT-IR, XRD, VSM and EDX and the quantification analysis was performed by microsampling flame atomic absorption spectrometry. The important parameters on the extraction efficiency were thoroughly optimized by means of experimental design. Under the optimized conditions, an aliquot of 50 mL of sample (pH 6.3) was extracted utilizing 60 mg of magnetic nanoparticles during 30 min. The sorbent was afterward desorbed using 1.0 mL of 0.8 mol L-1 HNO3 under fierce vortex for 6 min. A preconcentration factor of 20 and an absolute recovery of 40% were provided by the proposed method. The limits of detection (3S/N) and quantification (10 S/N) were 0.06 ng mL-1 and 2.0 ng mL-1, respectively. An excellent linearity was achieved within the range of (10-800) ng mL-1 and the regression coefficient was 0.9903. The intra- and inter-day RSDs% were found to be 1.8% and 7.0%, respectively. Furthermore, the method was applied for analysis of blood samples and good accuracies within the range of 97%-108% were obtained.