Application of d-SPE before SPE and HPLC-FLD to Analyze Bisphenols in Human Breast Milk Samples

Determination of Parabens and Phenolic Compounds in Dairy Products through the Use of a Two-Step Continuous SPE System Including an Enhanced Matrix Removal Sorbent in Combination with UHPLC-MS/MS

Dairy products can be contaminated by parabens and phenolic compounds from a vast variety of sources, such as packaging and manufacturing processes, or livestock through feed and environmental water. A two-step continuous solid-phase extraction (SPE) and purification methodology was developed here for the determination of both types of compounds. In the first step, a sample extract is passed in sequence through an EMR-lipid sorbent and an Oasis PRiME HBL sorbent to remove fat and preconcentrate the analytes for subsequent detection and quantification by UHPLC-MS/MS. This method enabled the determination of 28 parabens and phenolic contaminant with excellent recovery (91-105%) thanks to the SPE sorbent combination used. The proposed method was validated through the determination of the target compounds, and was found to provide low detection limits (1-20 ng/kg) with only slight matrix effects (0-10%). It was used to analyse 32 different samples of dairy products with different packaging materials. Bisphenol A and bisphenol Z were the two phenolic compounds quantified in the largest number of samples, at concentrations over the range of 24-580 ng/kg, which did not exceed the limit set by European regulations. On the other hand, ethylparaben was the paraben found at the highest levels (33-470 ng/kg).

A Fast Method for Determination of Seven Bisphenols in Human Breast Milk Samples with the Use of HPLC-FLD

Plastic pollution, where bisphenol A (BPA) is widely used in its production, has gained popularity. BPA omnipresence and toxicity, especially for infants, has led food safety authorities to place restrictions on BPA usage. It has led to the introduction of the marked 'BPA-free'-labelled products, where BPA is often replaced by other bisphenols (BPs) which are suspected of being similar or even more toxic than BPA. Moreover, the free forms of BPs are more dangerous than their conjugated forms and the conjugation of BPs is less effective in infants than in adults. Considering that human breast milk is the main source of nutrition for infants, the constant biomonitoring not only of BPA, but the wider group of BPs in such crucial matrices seems to be vital. In this study, a fast, simple, 'green' and cost-effective DLLME-based extraction technique combined with HPLC-FLD was optimized for the determination of seven selected bisphenols simultaneously. The procedure has satisfactory recovery values of 67-110% with the most RSD% at 17%. The LODs and LOQs ranged from 0.5 ng/mL to 2.1 ng/mL and 1.4 ng/mL to 6.3 ng/mL, respectively. The procedure was successfully applied to the biomonitoring of free forms of BPs in 10 real human breast milk samples.

Application of High-Performance Liquid Chromatography Combined with Fluorescence Detector and Dispersive Liquid-Liquid Microextraction to Quantification of Selected Bisphenols in Human Amniotic Fluid Samples

Bisphenol A (BPA) is a widely produced chemical worldwide found in numerous everyday products. Its endocrine-disrupting properties and omnipresence have aroused concern and led to several restrictions on its use. These restrictions and growing public awareness about the toxicity of BPA have resulted in market products labeled "BPA-free", with BPAs often being replaced by other bisphenols. This is why constant biomonitoring of bisphenol levels in various body fluids and tissues is essential. In this study, we propose the use of simple, cost-effective high-performance liquid chromatography coupled with the fluorescence detector (HPLC-FLD) method for the determination of simultaneously selected bisphenols in amniotic fluid. For the sample preparation, a fast, simple, and "green" dispersive liquid-liquid microextraction (DLLME) method was used, achieving mean recovery values in the range of 80.9-115.9% with relative standard deviations below 12% for all analytes. Limits of quantification (LOQs) determined in the amniotic fluid matrix ranged from 6.17 to 22.72 ng/mL and were obtained from a calibration curve constructed using least-squares linear regression analysis for all cases. The presented sample preparation procedure can be easily adopted for LC-MS analysis.

Emotion Recognition of Online Education Learners by Convolutional Neural Networks

At present, the facial expression recognition model in video communication has problems such as weak network generalization ability and complex model structure, which leads to a large amount of computation. Firstly, the Inception architecture is adopted as a design philosophy. The Visual Geometry Group Network (VGGNet) model is improved. Multiscale kernel convolutional layers are constructed to obtain more expressive features. Secondly, the attention mechanism is integrated into a multiscale feature fusion network to form a multiattention mechanism Convolutional Neural Network (CNN) model. Novel spatial and multichannel attention models are designed. The effects of redundant information and noise are reduced. Finally, experiments are carried out on the Fer2013 dataset and the Extended Cohn-Kanade Dataset (CK+) to verify the detection accuracy of the model. The results show that the Delivered Duty Unpaid (DDU) loss can be used for facial expression recognition in complex environments. After the attention module is added, the overall recognition accuracy of the network on Fer2013 and CK+ has been improved to varying degrees. The addition of the channel attention module has a more obvious effect on the recognition accuracy compared with the spatial attention module. The addition of the attention module enables the network to increase the attention to error-prone samples. The improved network model can better extract the key features of facial expressions, enhance the feature discrimination ability, and improve the recognition accuracy of error-prone expressions. The accuracy rate of facial expression recognition with larger movements is over 98%. Facial expressions are an important way of communication between people, and online video has greatly limited this communication method. The proposed CNN model based on multiscale feature fusion will effectively solve these network limitations and have an important and positive impact on future network information exchange.

Application of Solid-Phase Extraction and High-Performance Liquid Chromatography with Fluorescence Detection to Analyze Eleven Bisphenols in Amniotic Fluid Samples Collected during Amniocentesis

Amniocentesis involves taking a sample of the amniotic fluid in order to perform a karyotype test and diagnose any genetic defects that may affect the fetus. Amniotic fluid has been collected from patients with an indication for amniocentesis in the 15–26th week of pregnancy. A simple and sensitive high-performance liquid chromatography with fluorescence detection (HPLC-FLD) method for identification and quantification of eleven selected bisphenols in amniotic fluid samples is proposed. The proposed method involved protein precipitation using acetonitrile, and next the extraction and concentration of analytes by solid-phase extraction (SPE). The solid-phase extraction (SPE) procedure with application of Oasis HLB SPE columns performed well for the majority of the analytes, with recoveries in the range of 67–121% and relative standard deviations (RSD%) less than 16%. The limits of detection (LODs) and quantification (LOQs) of all the investigated analytes were in the range of 0.8–2.5 ng mL⁻¹ and 2.4–7.5 ng mL⁻¹ (curves constructed in methanol) and 1.1–5.2 ng mL⁻¹ and 3.2–15.6 ng mL⁻¹ (curves constructed in the amniotic fluid), respectively. The method was validated at the following two concentration levels: 10 ng mL⁻¹ (2 × LOQ) and 20 ng mL⁻¹ (4 LOQ). The results confirm the validity of the SPE procedure and HPLC-FLD method for identification and quantification of bisphenols in amniotic fluid samples collected during an amniocentesis. The result obtained show that HPLC-FLD is a useful method for determination of bisphenol residues at nanogram per milliliter concentrations in amniotic fluid samples. Residues of five analytes (BADGE·2H₂O, BPAF, BADGE, BADGE·H₂O·HCl and BADGE·2HCl) were detected in amniotic fluid samples. Additionally, the harmfulness of bisphenols as potential pathogens that may cause karyotype disorders and contribute to preterm birth was estimated.

Application of Solid Phase Extraction and High-Performance Liquid Chromatography with Fluorescence Detection to Analyze Bisphenol A Bis (2,3-Dihydroxypropyl) Ether (BADGE 2H2O), Bisphenol F (BPF), and Bisphenol E (BPE) in Human Urine Samples

In this study, we propose a simple, cost-effective, and sensitive high-performance liquid chromatography method with fluorescence detection (HPLC-FLD) for the simultaneous determination of the three bisphenols (BPs): bisphenol A bis (2,3-dihydroxypropyl) ether (BADGE 2H2O), bisphenol F (BPF), and bisphenol E (BPE) in human urine samples. The dispersive solid phase extraction (d-SPE) coupled with solid phase extraction (SPE) procedure performed well for the analytes with recoveries in the range of 74.3-86.5% and relative standard deviations (RSD%) less than 10%. The limits of quantification (LOQs) for all investigated analytes were in the range of 11.42-22.35 ng mL-1. The method was validated at three concentration levels (1 × LOQ, 1.5 × LOQ, and 3 LOQ). During the bisphenols HPLC-FLD analysis, from 6 min a reinforcement (10 or 12) was used, therefore analytes might be identified in the small volume human urine samples. The results demonstrated clearly that the approach developed provides reliable, simple, and rapid quantification and identification of three bisphenols in a urine matrix and could be used for monitoring these analytes.