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Paclobutrazol (PBZ) is a plant growth inhibitor and fungicide, but it is also carcinogenic and teratogenic, and has potential harm to human health. In this study, two PBZ haptens (PBZ-1, PBZ-2) were synthesized and conjugated with carrier proteins to get artificial antigens. A highly specific monoclonal antibody (mAb) against PBZ was prepared. The antibody subtype was IgG1 and the concentration was 11.03 mg/mL. A sensitive and rapid time-resolved fluorescence microsphere lateral flow immunoassay (TRFMs-LFIA) was established based on the mAb. The activated pH, the mAbs diluents, the mAb reacting concentration and the probe amount were optimized. The visual limit of detection (vLOD) and quantitative limit of detection (qLOD) of the TRFMs-LFIA for PBZ were 50 and 1.72 ng/mL respectively, and the 50% inhibiting concentration (IC50) was 9.38 ng/mL. The pretreatment procedures are simple and rapid, and the detection time of TRFMs-LFIA strip is 6 min. Qualitative and quantitative analysis of PBZ could be achieved under a UV light or with a portable fluorescence immunoassay analyzer. The average recovery rates ranged from 96.2% to 111.9% and the corresponding coefficients of variation (CV) were 4.0%–11.2% in spiked wheat and rice samples. Twenty real wheat and rice samples were measured by the TRFMs-LFIA and compared with Ultra-performance liquid chromatography/tandem mass spectrometry (UPLC-MS/MS). The measured values showed a good accordance. These results indicated that the proposed assay will provide a novel effective strategy for on-site detection of PBZ.

Negative emotions of drivers may lead to some dangerous driving behaviors, which in turn lead to serious traffic accidents. However, most of the current studies on driver emotions use a single modality, such as EEG, eye trackers, and driving data. In complex situations, a single modality may not be able to fully consider a driver’s complete emotional characteristics and provides poor robustness. In recent years, some studies have used multimodal thinking to monitor single emotions such as driver fatigue and anger, but in actual driving environments, negative emotions such as sadness, anger, fear, and fatigue all have a significant impact on driving safety. However, there are very few research cases using multimodal data to accurately predict drivers’ comprehensive emotions. Therefore, based on the multi-modal idea, this paper aims to improve drivers’ comprehensive emotion recognition. By combining the three modalities of a driver’s voice, facial image, and video sequence, the six classification tasks of drivers’ emotions are performed as follows: sadness, anger, fear, fatigue, happiness, and emotional neutrality. In order to accurately identify drivers’ negative emotions to improve driving safety, this paper proposes a multi-modal fusion framework based on the CNN + Bi-LSTM + HAM to identify driver emotions. The framework fuses feature vectors of driver audio, facial expressions, and video sequences for comprehensive driver emotion recognition. Experiments have proved the effectiveness of the multi-modal data proposed in this paper for driver emotion recognition, and its recognition accuracy has reached 85.52%. At the same time, the validity of this method is verified by comparing experiments and evaluation indicators such as accuracy and F1 score.

A novel and efficient immunoaffinity column (IAC) based on bispecific monoclonal antibody (BsMAb) recognizing aflatoxin B1 (AFB1) and ochratoxin A (OTA) was prepared and applied in simultaneous extraction of AFB1 and OTA from food samples and detection of AFB1/OTA combined with ic-ELISA (indirect competitive ELISA). Two deficient cell lines, hypoxanthine guanine phosphoribosyl-transferase (HGPRT) deficient anti-AFB1 hybridoma cell line and thymidine kinase (TK) deficient anti-OTA hybridoma cell line, were fused to generate a hybrid-hybridoma producing BsMAb against AFB1 and OTA. The subtype of the BsMAb was IgG1 via mouse antibody isotyping kit test. The purity and molecular weight of BsMAb were confirmed by SDS-PAGE method. The cross-reaction rate with AFB2 was 37%, with AFG1 15%, with AFM1 48%, with AFM2 10%, and with OTB 36%. Negligible cross-reaction was observed with other tested compounds. The affinity constant (Ka) was determined by ELISA. The Ka (AFB1) and Ka (OTA) was 2.43 × 108 L/mol and 1.57 × 108 L/mol, respectively. Then the anti-AFB1/OTA BsMAb was coupled with CNBr-Sepharose, and an AFB1/OTA IAC was prepared. The coupling time and elution conditions of IAC were optimized. The coupling time was 1 h with 90% coupling rate, the eluent was methanol–water (60:40, v:v, pH 2.3) containing 1 mol/L NaCl, and the eluent volume was 4 mL. The column capacities of AFB1 and OTA were 165.0 ng and 171.3 ng, respectively. After seven times of repeated use, the preservation rates of column capacity for AFB1 and OTA were 69.3% and 68.0%, respectively. The ic-ELISA for AFB1 and OTA were applied combined with IAC. The IC50 (50% inhibiting concentration) of AFB1 was 0.027 ng/mL, the limit of detection (LOD) was 0.004 ng/mL (0.032 µg/kg), and the linear range was 0.006 ng/mL~0.119 ng/mL. The IC50 of OTA was 0.878 ng/mL, the LOD was 0.126 ng/mL (1.008 µg/kg), and the linear range was 0.259 ng/mL~6.178 ng/mL. Under optimum conditions, corn and wheat samples were pretreated with AFB1-OTA IAC. The recovery rates of AFB1 and OTA were 95.4%~105.0% with ic-ELISA, and the correlations between the detection results and LC-MS were above 0.9. The developed IAC combined with ic-ELISA is reliable and could be applied to the detection of AFB1 and OTA in grains.

In this study, forchlorfenuron (CPPU) was coupled with succinic anhydride to yield a CPPU hapten (CPPU-COOH), and a high-affinity monoclonal antibody (mAb) that can specifically recognize CPPU was produced. Using this mAb as a recognition reagent, a sensitive indirect competitive enzyme-linked immunosorbent assay (icELISA) for CPPU was optimized, which exhibits an IC50 of 1.04 ng/mL, a limit of detection of 0.16 ng/mL, and a linear range of 0.31–3.43 ng/mL for CPPU. Cross-reactivity percentages with six analogues were all below 6%. The average recovery rates for cucumber and orange samples were from 85.23% to 119.14%. The analysis results of this icELISA showed good consistency with those from liquid chromatography mass spectrometry. These results suggest that the proposed icELISA provides a sensitive, specific, and reliable strategy for CPPU detection in food samples.