Objective: Previously, we showed that neuromodulators are important factors involved in depression, here we aim to further investigate the interactions between neuromodulators and sex hormone involved in menopause related depression in rats.Methods: Menopausal depression was made with bilateral ovariectomies in female SD rats followed by chronic mild unpredictable stress treatment for 21 days. Thirty six rats were randomly divided into four groups: sham surgery group, sham/stress group, surgery group, surgery/stress group. Then open-field locomotor scores and sucrose intake were employed to observe behavior changes. The levels of norepinephrine (NE), dopamine (DA), serotonin (5-HT) in the cerebral spinal fluid and serum adrenocorticotropic hormone (ACTH), cortisone were determined with High-performance liquid chromatography (HPLC). Serum estradiol (E2), follicle-stimulating hormone (FSH), and luteinizing hormone (LH) were measured with radioimmunoassay.Results: The open-field locomotor scores and sucrose intake were significantly decreased after the surgery and stress treatment (p < 0.01). The Serum E2 level decreased significantly after the surgery (p < 0.01), but serum LH, FSH levels increased significantly in the surgery group than the sham surgery group (p < 0.01). The cortisone levels increased significantly in sham/stress group than that in the sham surgery group during the first 2 weeks at stressful treatment, but decrease afterwards. The monoamine levels in the surgery/stress group were much lower than those in the sham surgery group (p < 0.01). The correlation analysis found that LH and FSH are related more to the neurotransmitter release than E2.Conclusion: Ovary removal rats showed depression-like behaviors, with LH and FSH increase and monoamine decrease, and the levels of these monoamines in the stress treated groups changed only after the stressful treatment. The LH, FSH hormone increasing might be the reason for the lower monoamine release, which in turn might be the reason for depressed syndromes in the menopause. The cortisone and ACTH in the serum in the surgery/stress group were much higher than that in the sham surgery group.

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Semantic segmentation is a critical topic in computer vision, and it has numerous practical applications, including mobile devices, autonomous driving, and many other fields. However, in these application scenarios, it is often essential for the segmentation models to achieve a balance between efficiency and performance. A lightweight attention-guided redundancy-reuse network (LARNet) was proposed to address this challenge in this paper. Specifically, the multi-scale asymmetric redundancy reuse (MAR) module was designed as the main component of the encoder for dense encoding of contextual semantic features. Furthermore, the efficient attention fusion (EAF) module was established for multi-scale information fusion via the channel and spatial attention mechanisms in the decoder. A series of experiments were conducted to verify the proposed network. The results of tests on multiple datasets suggest that the network has higher accuracy and faster speed than the existing real-time semantic segmentation methods.