Background: The occurrence of cotton pests and diseases has always been an important factor affecting the total cotton production. Cotton has a great dependence on environmental factors during its growth, especially climate change. In recent years, machine learning and especially deep learning methods have been widely used in many fields and have achieved good results. Methods: First, this papaer used the common Aprioro algorithm to find the association rules between weather factors and the occurrence of cotton pests. Then, in this paper, the problem of predicting the occurrence of pests and diseases is formulated as time series prediction, and an LSTM-based method was developed to solve the problem. Results: The association analysis reveals that moderate temperature, humid air, low wind spreed and rain fall in autumn and winter are more likely to occur cotton pests and diseases. The discovery was then used to predict the occurrence of pests and diseases. Experimental results showed that LSTM performs well on the prediction of occurrence of pests and diseases in cotton fields, and yields the Area Under the Curve (AUC) of 0.97. Conclusion: Suitable temperature, humidity, low rainfall, low wind speed, suitable sunshine time and low evaporation are more likely to cause cotton pests and diseases. Based on these associations as well as historical weather and pest records, LSTM network is a good predictor for future pest and disease occurrences. Moreover, compared to the traditional machine learning models (i.e., SVM and Random Forest), the LSTM network performs the best.

Prolonged or excessive exposure to noise can lead to hearing loss, tinnitus and hypersensitivity to sound. The effects of noise exposure on main excitatory and inhibitory neurotransmitter systems in auditory pathway have been extensively investigated. However, little is known about aberrant changes in neuromodulator systems caused by noise exposure. In the current study, we exposed 2-month-old mice to a narrow band noise at 116 dB SPL for 6 h or sham exposure, assessed auditory brainstem responses as well as examined the expression of serotonin reuptake transporter (SERT) in the cochlear nucleus (CN), inferior colliculus (IC), and primary auditory cortex (Au1) using immunohistochemistry. We found that noise exposure resulted in a significant increase in hearing thresholds at 4, 8, 16, 24, and 32 kHz, as well as led to a significant reduction of SERT in dorsal cochlear nucleus (DCN), dorsal IC (ICd), external IC (ICe), and Au1 layers I-IV. This reduction of SERT in these subregions of central auditory system was partially recovered 15 or 30 days after noise exposure. Furthermore, we examined efficacy of resveratrol (RSV) on hearing loss and loss of SERT induced by noise exposure. The results demonstrated that RSV treatment significantly attenuated threshold shifts of auditory brainstem responses and loss of SERT in DCN, ICd, ICe, and Au1 layers I-IV. These findings show that noise exposure can cause hearing loss and subregion-specific loss of SERT in the central auditory system, and RSV treatment could attenuate noise exposure-induced hearing loss and loss of SERT in central auditory system.

Increasing evidence suggests that all-trans retinoic acid (ATRA) contributes to the pathogenesis of depression. Although numerous studies have emphasized the role of hippocampal glutamatergic transmission and dendritic spine abnormalities in ATRA-induced depression, it remains unclear whether changes in hypothalamic glutamatergic transmission and dendritic spine density also contribute to its development. This study investigates the effects of ATRA treatment on glutamate receptor expression and dendritic spine density in the hypothalamus of rats. We found that prolonged ATRA exposure induced depression-like behaviors, as evidenced by altered behavior in standard tests. These behavioral changes were accompanied by significant upregulation of retinoic acid receptor α (RARα) and corticotropin-releasing hormone (CRH) expression in the hypothalamus, suggesting a potential involvement of retinoic acid signaling in the regulation of stress-related pathways. Furthermore, rats exhibiting depression-like behaviors after ATRA treatment showed abnormal expression patterns of AMPA receptor subunits. ATRA treatment significantly increases dendritic spine density in hypothalamic neurons, particularly in secondary and tertiary dendrites. Most importantly, significant increases were observed in the GluR1, GluR2, and GluR4 subunits of the AMPA receptor, along with a slight increase in primary dendrite numbers. Additionally, there were significant increases in spine density on secondary and tertiary dendrites, which are critical for synaptic plasticity and neurotransmission. These findings point to a potential disruption in glutamatergic signaling in response to chronic ATRA exposure. In parallel, we observed a significant increase in dendritic spine density in cultured hypothalamic neurons following ATRA treatment. This effect was most pronounced in secondary and tertiary dendrites, indicating a selective enhancement of dendritic complexity. These results suggest that ATRA may alter both synaptic structure and glutamatergic function in the hypothalamus, providing new insights into its potential role in stress-related disorders. Our study highlights the importance of retinoic acid signaling in modulating neural plasticity and provides a novel perspective on the molecular mechanisms underlying ATRA-induced mood disturbances.