Several papers report that the colon is one of the tissues regulated by estrogen receptor (ER)β. To better understand the physiological role of ERβ in colonic tissue, we have compared morphology, proliferation, and differentiation of colonic epithelium in ERβ ^−/− mice and WT littermates. BrdUrd labeling revealed that the number of proliferating cells was higher in ERβ ^−/− mice and that the migration of labeled cells toward the luminal surface was faster in ERβ ^−/− mice than in WT littermates. Additionally, in the absence of ERβ, there was a decrease in apoptosis, which was measured by immunohistochemical staining of cleaved caspase-3. The state of differentiation of the colonic epithelial cells was studied by using epithelial markers. In ERβ ^−/− mice, there was a significant decrease in the expression of the differentiation marker cytokeratin (CK)20 and in the cellular adhesion molecules α-catenin (an adherens junction protein) and plectin (a hemidesmosomal protein). These changes were also evident by electron microscopy as abnormalities in tight junctions and in the number and shape of desmosomes in ERβ ^−/− mice. These findings suggest a role for ERβ in the organization and architectural maintenance of the colon. Furthermore, our results indicate that the rapidly proliferating cells of the colonic epithelium in ERβ ^−/− mice are lost by increased shedding and not by increased apoptosis. In this way, hyperproliferative cells that lack ERβ do not form hyperplastic lesions and do not accumulate in the superficial epithelium.

Background: Resveratrol is a natural polyphenolic compound known for its beneficial effects on energy homeostasis, and it also has multiple properties, including anti-oxidant, anti-inflammatory, and anti-tumor activities. Recently, silent information regulator genes (Sirtuins) have been identified as targets of resveratrol. Sirtuin 1 (SIRT1), originally found as an NAD⁺-dependent histone deacetylase, is a principal modulator of pathways downstream of calorie restriction, and the activation of SIRT1 ameliorates glucose homeostasis and insulin sensitivity. To date, the presence and physiological role of SIRT1 in the ovary are not known. Here we found that SIRT1 was localized in granulosa cells of the human ovary. Methods: The physiological roles of resveratrol and SIRT1 in the ovary were analyzed. Immunohistochemistry was performed to localize the SIRT1 expression. SIRT1 protein expression of cultured cells and luteinized human granulosa cells was investigated by Western blot. Rat granulosa cells were obtained from diethylstilbestrol treated rats. The cells were treated with increasing doses of resveratrol, and subsequently harvested to determine mRNA levels and protein levels. Cell viability was tested by MTS assay. Cellular apoptosis was analyzed by caspase 3/7 activity test and Hoechst 33342 staining. Results: SIRT1 protein was expressed in the human ovarian tissues and human luteinized granulosa cells. We demonstrated that resveratrol exhibited a potent concentration-dependent inhibition of rat granulosa cells viability. However, resveratrol-induced inhibition of rat granulosa cells viability is independent of apoptosis signal. Resveratrol increased mRNA levels of SIRT1, LH receptor, StAR, and P450 aromatase, while mRNA levels of FSH receptor remained unchanged. Western blot analysis was consistent with the results of quantitative real-time RT-PCR assay. In addition, progesterone secretion was induced by the treatment of resveratrol. Conclusions: These results suggest a novel mechanism that resveratrol could enhance progesterone secretion and expression of luteinization-related genes in the ovary, and thus provide important implications to understand the mechanism of luteal phase deficiency.

Context: Endometriosis is an estrogen-dependent, chronic inflammatory disease. Recent studies have shown that vitamin D (VD) is an effective modulator of the immune system and plays an important role in controlling many inflammatory diseases.Objective: The objective of the study was to clarify the in vitro effects of 1,25-dihydroxy vitamin D3 (1,25[OH]2D3) on human endometriotic stromal cells (ESCs) and to determine the serum levels of VD in endometriosis patients.Design, Patients, and Main Outcome Measures: ESCs were isolated from ovarian endometrioma and cultured with 1,25(OH)2D3. Gene expression of IL-8, cyclooxygenase-2, microsomal prostaglandin E synthase-1, microsomal prostaglandin E synthase-2, cytosolic prostaglandin E synthase, 15-hydroxyprostaglandin dehydrogenase, matrix metalloproteinase (MMP)-2, and MMP-9 was examined using quantitative RT-PCR. The production of IL-8 and prostaglandin E2 was measured using an ELISA and an enzyme immunoassay. Viable cell number was assessed using a cell-counting assay, and DNA synthesis was assessed using the bromodeoxyuridine incorporation assay. Apoptosis was assessed using flow cytometry. The expression of inhibitory-κBα protein was detected using Western blotting. The serum levels of 25-hydroxyvitamin D3 and 1,25(OH)2D3 were measured by a RIA.Results: In vitro studies showed that 1,25(OH)2D3 significantly reduced IL-1β- or TNF-α-induced inflammatory responses, such as IL-8 expression and prostaglandin activity. 1,25(OH)2D3 also reduced viable ESC numbers and DNA synthesis but did not affect apoptosis. MMP-2 and MMP-9 expressions were reduced by 1,25(OH)2D3. 1,25(OH)2D3 inhibited nuclear factor-κB activation. The serum 25-hydroxyvitamin D3 levels were significantly lower in women with severe endometriosis than in the controls and women with mild endometriosis. Serum 1,25(OH)2D3 levels were not different between groups.Conclusions: VD modulates inflammation and proliferation in endometriotic cells, and a lower VD status is associated with endometriosis. Taken together, VD supplementation could be a novel therapeutic strategy for managing endometriosis.

In this study, we compared the uterine tissue of estrogen receptor (ER)β ^−/− mice and their WT littermates for differences in morphology, proliferation [the percentage of labeled cells 2 h after BrdUrd injection and EGF receptor (EGFR) expression], and differentiation (expression of progesterone receptor, E-cadherin, and cytokeratins). In ovariectomized mice, progesterone receptor expression in the uterine epithelium was similar in WT and ERβ ^−/− mice, but E-cadherin and cytokeratin 18 expression was lower in ERβ ^−/− mice. The percentage of cells in S phase was 1.5% in WT mice and 8% in ERβ ^−/− mice. Sixteen hours after injection of 17β-estradiol (E ₂ ), the number of BrdUrd-labeled cells increased 20-fold in WT mice and 80-fold in ERβ ^−/− mice. Although ERα was abundant in intact mice, after ovariectomy, ERα could not be detected in the luminal epithelium of either WT or ERβ ^−/− mice. In both untreated and E ₂ -treated mice, ERα and ERβ were colocalized in the nuclei of many stromal and glandular epithelial cells. However, upon E ₂ + progesterone treatment, ERα and ERβ were not coexpressed in any cells. In WT mice, EGFR was located on the membranes and in the cytoplasm of luminal epithelium, but not in the stroma. In ERβ ^−/− mice, there was a marked expression of EGFR in the nuclei of epithelial and stromal cells. Upon E ₂ treatment, EGFR on cell membranes was down-regulated in WT but not in ERβ ^−/− mice. These findings reveal an important role for ERβ in response to E ₂ and in the organization, growth, and differentiation of the uterine epithelium.

Endometrial cancer is a ubiquitous gynecological disease with increasing global incidence. Therefore, despite the lack of an established screening technique to date, early diagnosis of endometrial cancer assumes critical importance. This paper presents an artificial-intelligence-based system to detect the regions affected by endometrial cancer automatically from hysteroscopic images. In this study, 177 patients (60 with normal endometrium, 21 with uterine myoma, 60 with endometrial polyp, 15 with atypical endometrial hyperplasia, and 21 with endometrial cancer) with a history of hysteroscopy were recruited. Machine-learning techniques based on three popular deep neural network models were employed, and a continuity-analysis method was developed to enhance the accuracy of cancer diagnosis. Finally, we investigated if the accuracy could be improved by combining all the trained models. The results reveal that the diagnosis accuracy was approximately 80% (78.91–80.93%) when using the standard method, and it increased to 89% (83.94–89.13%) and exceeded 90% (i.e., 90.29%) when employing the proposed continuity analysis and combining the three neural networks, respectively. The corresponding sensitivity and specificity equaled 91.66% and 89.36%, respectively. These findings demonstrate the proposed method to be sufficient to facilitate timely diagnosis of endometrial cancer in the near future.