Search

The objective of this experimental study was to examine the effects of the Chinese herbal medicines Patchouli and Elsholtzia on the follicular granulosa cells of hens undergoing heat stress conditions. In the current investigation, hen follicular granulosa cells were isolated from the prehierarchical follicles of layer hens and then cultured in-vitro. The cells were randomly divided into the 6 groups. Following the completion of this study's experiments using different heat stress and medicinal treatments, the cell activities of each group were measured using an MTT method. The levels of the heat shock protein 70 (HSP70) were detected using ELISA. The expressions of the steroidogenic acute regulatory protein (StAR) mRNA; cytochrome P450 family 11, subfamily A, member 1 (CYP11A1) mRNA; proliferating cell nuclear antigen (PCNA) mRNA; and the follicle stimulating hormone receptor (FSHR) were detected using the real-time quantitative polymerase chain reactions. The concentration levels of estrogen and progesterone in the cell supernatant of each group were measured using ELISA. The results showed that cell activity had significantly decreased following the heat stress treatments at 43℃, 44℃, and 45℃ (P < 0.01), respectively. Meanwhile, cell activities observed in Patchouli and Elsholtzia were found to be much better than those of heat stress group (P < 0.05). In addition, the expression levels of HSP70 in the follicular granulosa cells of Patchouli and Elsholtzia groups were lower than those of heat stress group. Patchouli and Elsholtzia can maintain expressions of the receptor at 43℃. This study determined that the estrogen and progesterone in the supernatant fluid of Patchouli and Elsholtzia were higher than those observed in heat stress. Therefore, the results obtained in this study indicated that the Patchouli and Elsholtzia treatments administered prior the heat stress experiments had successfully protected the follicular granulosa cells from heat damages while maintaining the normal secretory functions of the granulosa cells. [ABSTRACT FROM AUTHOR]

To uncover the relationship between neural activity and behavior, it is essential to reconstruct neural circuits. However, methods typically used for neuron reconstruction from volumetric electron microscopy (EM) dataset are often time-consuming and require extensive manual proofreading, making it difficult to reproduce in a typical laboratory setting. To address this challenge, we have developed a set of acceleration techniques that build upon the Flood Filling Network (FFN), significantly reducing the time required for this task. These techniques can be easily adapted to other similar datasets and laboratory settings. To validate our approach, we tested our pipeline on a dataset of Drosophila larval brain serial section EM images at synaptic-resolution level. Our results demonstrate that our pipeline significantly reduces the inference time compared to the FFN baseline method and greatly reduces the time required for reconstructing the 3D morphology of neurons.