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Pelvic inflammatory disease (PID) is a common inflammation in the upper reproductive tract in women and may cause serious and costly consequences without effective treatment. Engeletin is a flavanonol glycoside and a naturally derived aldose reductase (AR) inhibitor that is widely distributed in vegetables, fruits, and plant-based foods. The present study investigated the anti-PID activity of engeletin in a mucilage-induced rat model of PID and LPS-stimulated RAW 264.7 macrophages. Engeletin significantly reduced inflammation and ameliorated the typical uterine pathological changes in PID rats. Engeletin also inhibited AR-dependent PLC/PKC/NF-κB and MAPK inflammatory pathways, as indicated by the suppression of the phosphorylation levels of PLC, PKC, p38, ERK, and JNK and the nuclear translocation of NF-κB p65. In vitro studies demonstrated that engeletin significantly inhibited inflammatory mediator expression and enhanced the phagocytic ability of LPS-induced RAW 264.7 macrophages. RNA interference of AR prevented the engeletin-induced inhibition of inflammatory mediators. Engeletin also inhibited AR-dependent PLC/PKC/NF-κB and MAPK inflammatory pathways, which was consistent with the in vivo results. These findings support engeletin as a potential agent for prevention or treatment of PID.

In magnetic resonance imaging (MRI) studies of fetal brain development, structural brain atlases usually serve as essential references for the fetal population. Individual images are usually normalized into a common or standard space for analysis. However, the existing fetal brain atlases are mostly based on MR images obtained from Caucasian populations and thus are not ideal for the characterization of the fetal Chinese population due to neuroanatomical differences related to genetic factors. In this paper, we use an unbiased template construction algorithm to create a set of age-specific Chinese fetal atlases between 21-35 weeks of gestation from 115 normal fetal brains. Based on the 4D spatiotemporal atlas, the morphological development patterns, e.g., cortical thickness, cortical surface area, sulcal and gyral patterns, were quantified. The fetal brain abnormalities were detected when referencing the age-specific template. Additionally, a direct comparison of the Chinese fetal atlases and Caucasian fetal atlases reveals dramatic anatomical differences, mainly in the medial frontal and temporal regions. After applying the Chinese and Caucasian fetal atlases separately to an independent Chinese fetal brain dataset, we find that the Chinese fetal atlases result in significantly higher accuracy than the Caucasian fetal atlases in guiding brain tissue segmentation. These results suggest that the Chinese fetal brain atlases are necessary for quantitative analysis of the typical and atypical development of the Chinese fetal population in the future. The atlases with their parcellations are now publicly available at https://github.com/DeepBMI/FBA-Chinese.