The MYC2 and MYB43 transcription factors cooperate to repress HMA2 and HMA4 expression, altering cadmium tolerance in Arabidopsis thaliana.

Cadmium (Cd) represents a hazardous heavy metal, prevalent in agricultural soil due to industrial and agricultural expansion. Its propensity for being absorbed by edible plants, even at minimal concentrations, and subsequently transferred along the food chain poses significant risks to human health. Accordingly, it is imperative to investigate novel genes and mechanisms that govern Cd tolerance and detoxification in plants. Here, we discovered that the transcription factor MYC2 directly binds to the promoters of HMA2 and HMA4 to repress their expression, thereby altering the distribution of Cd in plant tissues and negatively regulating Cd stress tolerance. Additionally, molecular, biochemical, and genetic analyses revealed that MYC2 interacts and cooperates with MYB43 to negatively regulate the expression of HMA2 and HMA4 and Cd stress tolerance. Notably, under Cd stress conditions, MYC2 undergoes degradation, thereby alleviating its inhibitory effect on HMA2 and HMA4 expression and plant tolerance to Cd stress. Thus, our study highlights the dynamic regulatory role of MYC2, in concert with MYB43, in regulating the expression of HMA2 and HMA4 under both normal and Cd stress conditions. These findings present MYC2 as a promising target for directed breeding efforts aimed at mitigating Cd accumulation in edible plant roots.

CDR1, a DUF946 domain containing protein, positively regulates cadmium tolerance in Arabidopsis thaliana by maintaining the stability of OPT3 protein.

Industrial and agricultural production processes lead to the accumulation of cadmium (Cd) in soil, resulting in crops absorb Cd from contaminated soil and then transfer it to human body through the food chain, posing a serious threat to human health. Thus, it is necessary to explore novel genes and mechanisms involved in regulating Cd tolerance and detoxification in plants. Here, we found that CDR1, a DUF946 domain containing protein, localizes to the plasma membrane and positively regulates Cd stress tolerance. The cdr1 mutants exhibited Cd sensitivity, accumulated excessive Cd in the seeds and roots, but decreased in leaves. However, CDR1-OE transgenic plants not only showed Cd tolerance but also significantly reduced Cd in seeds and roots. Additionally, both in vitro and in vivo assays demonstrated an interaction between CDR1 and OPT3. Cell free protein degradation and OPT3 protein level determination assays indicated that CDR1 could maintain the stability of OPT3 protein. Moreover, genetic phenotype analysis and Cd content determination showed that CDR1 regulates Cd stress tolerance and affect the distribution of Cd in plants by maintaining the stability of OPT3 protein. Our discoveries provide a key candidate gene for directional breeding to reduce Cd accumulation in edible seeds of crops.

Wounding induces suberin deposition, relevant gene expressions and changes of endogenous phytohormones in Chinese yam (Dioscorea opposita) tubers.

Wounds on Chinese yam (Dioscorea opposita ) tubers can ocurr during harvest and handling, and rapid suberisation of the wound is required to prevent pathogenic infection and desiccation. However, little is known about the causal relationship among suberin deposition, relevant gene expressions and endogenous phytohormones levels in response to wounding. In this study, the effect of wounding on phytohormones levels and the expression profiles of specific genes involved in wound-induced suberisation were determined. Wounding rapidly increased the expression levels of genes, including PAL , C4H , 4CL , POD , KCSs , FARs , CYP86A1 , CYP86B1 , GPATs , ABCGs and GELPs , which likely involved in the biosynthesis, transport and polymerisation of suberin monomers, ultimately leading to suberin deposition. Wounding induced phenolics biosynthesis and being polymerised into suberin poly(phenolics) (SPP) in advance of suberin poly(aliphatics) (SPA) accumulation. Specifically, rapid expression of genes (e.g. PAL , C4H , 4CL , POD ) associated with the biosynthesis and polymerisation of phenolics, in consistent with SPP accumulation 3days after wounding, followed by the massive accumulation of SPA and relevant gene expressions (e.g. KCSs , FARs , CYP86A1 /B1 , GPATs , ABCGs , GELPs ). Additionally, wound-induced abscisic acid (ABA) and jasmonic acid (JA) consistently correlated with suberin deposition and relevant gene expressions indicating that they might play a central role in regulating wound suberisation in yam tubers.

A Hybrid Deep Learning Model for Recognizing Actions of Distracted Drivers.

With the rapid spreading of in-vehicle information systems such as smartphones, navigation systems, and radios, the number of traffic accidents caused by driver distractions shows an increasing trend. Timely identification and warning are deemed to be crucial for distracted driving and the establishment of driver assistance systems is of great value. However, almost all research on the recognition of the driver's distracted actions using computer vision methods neglected the importance of temporal information for action recognition. This paper proposes a hybrid deep learning model for recognizing the actions of distracted drivers. Specifically, we used OpenPose to obtain skeleton information of the human body and then constructed the vector angle and modulus ratio of the human body structure as features to describe the driver's actions, thereby realizing the fusion of deep network features and artificial features, which improve the information density of spatial features. The K-means clustering algorithm was used to preselect the original frames, and the method of inter-frame comparison was used to obtain the final keyframe sequence by comparing the Euclidean distance between manually constructed vectors representing frames and the vector representing the cluster center. Finally, we constructed a two-layer long short-term memory neural network to obtain more effective spatiotemporal features, and one softmax layer to identify the distracted driver's action. The experimental results based on the collected dataset prove the effectiveness of this framework, and it can provide a theoretical basis for the establishment of vehicle distraction warning systems.