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Endometrial cancer screening is crucial for clinical treatment. Currently, cytopathologists analyze cytopathology images is considered a popular screening method, but manual diagnosis is time-consuming and laborious. Deep learning can provide objective guidance efficiency. But endometrial cytopathology images often come from different medical centers with different staining styles. It decreases the generalization ability of deep learning models in cytopathology images analysis, leading to poor performance. This study presents a robust automated screening framework for endometrial cancer that can be applied to cytopathology images with different staining styles, and provide an objective diagnostic reference for cytopathologists, thus contributing to clinical treatment. We collected and built the XJTU-EC dataset, the first cytopathology dataset that includes segmentation and classification labels. And we propose an efficient two-stage framework for adapting different staining style images, and screening endometrial cancer at the cellular level. Specifically, in the first stage, a novel CM-UNet is utilized to segment cell clumps, with a channel attention (CA) module and a multi-level semantic supervision (MSS) module. It can ignore staining variance and focus on extracting semantic information for segmentation. In the second stage, we propose a robust and effective classification algorithm based on contrastive learning, ECRNet. By momentum-based updating and adding labeled memory banks, it can reduce most of the false negative results. On the XJTU-EC dataset, CM-UNet achieves an excellent segmentation performance, and ECRNet obtains an accuracy of 98.50%, a precision of 99.32% and a sensitivity of 97.67% on the test set, which outperforms other competitive classical models. Our method robustly predicts endometrial cancer on cytopathologic images with different staining styles, which will further advance research in endometrial cancer screening and provide early diagnosis for patients. The code will be available on GitHub. [ABSTRACT FROM AUTHOR]

Background: In the study, we aimed to evaluate the ability of micro‐histology combined with cytology to improve the quality of slides and diagnose endometrial lesions. Methods: Endometrial specimens were collected from Li Brushes. Every specimen was prepared for micro‐histological and cytological slides, using cell block (CB) and liquid‐based cytology (LBC) technologies. Semi‐quantitative scoring system was used to evaluate the qualities of slides. CB slides were assessed by 5‐category scoring system. Diagnostic accuracy was calculated in LBC, CB, and LBC + CB groups based on the histological gold standard. Endometrial atypical hyperplasia, and endometrial cancer were considered positive, whereas others were considered negative. Results: A total of 167 patients were enrolled. CB slides were inferior to LBC slides only in cellularity (p < 0.001), but superior in the other six parameters (all p < 0.001). The satisfaction rate of micro‐histology accounted for 92.3%. The accuracy index in the CB group was higher than in the LBC group in terms of sensitivity (85.5% vs. 82.7%) and specificity (98.9% vs. 95.7%). The sensitivity and specificity in the LBC + CB group were increased to 94.2% and 99.0%, respectively. Conclusions: The quality of micro‐histological slides was higher than that of cytological slides. By combining micro‐histology with cytology, higher accuracy was achieved for endometrial lesions diagnosis. [ABSTRACT FROM AUTHOR]

Intratumor heterogeneity (ITH) is a barrier to effective therapy. However, it is largely unknown how ITH is established at the onset of tumor progression, such as in colorectal cancer (CRC). Here, we integrate single‐cell RNA‐seq and functional validation to show that asymmetric division of CRC stem‐like cells (CCSC) is critical for early ITH establishment. We find that CCSC‐derived xenografts contain seven cell subtypes, including CCSCs, that dynamically change during CRC xenograft progression. Furthermore, three of the subtypes are generated by asymmetric division of CCSCs. They are functionally distinct and appear at the early stage of xenografts. In particular, we identify a chemoresistant and an invasive subtype, and investigate the regulators that control their generation. Finally, we show that targeting the regulators influences cell subtype composition and CRC progression. Our findings demonstrate that asymmetric division of CCSCs contributes to the early establishment of ITH. Targeting asymmetric division may alter ITH and benefit CRC therapy. Synopsis: Asymmetric division of colorectal cancer stem‐like cells contributes to the early establishment of intratumor heterogeneity. Targeting asymmetric division may alter intratumor heterogeneity and benefit colorectal cancer therapy. CCSC‐derived xenografts contain seven cell subtypes, which dynamically change during CRC xenograft progression.Three functionally distinct subtypes are generated by asymmetric division of CCSCs at an early xenograft stage.One subtype derived from CCSCs by asymmetric division is chemoresistant and highly invasive.Targeting regulators that control the generation of these subtypes affects xenograft composition and CRC progression. [ABSTRACT FROM AUTHOR]

Abstract Background Suicide and major depressive disorders (MDD) are strongly associated, and genetic factors are responsible for at least part of the variability in suicide risk. We investigated whether variation at the tryptophan hydroxylase-2 (TPH2) gene rs7305115 SNP may predispose to suicide attempts in MDD. Methods We genotyped TPH2 gene rs7305115 SNP in 215 MDD patients with suicide and matched MDD patients without suicide. Differences in behavioral and personality traits according to genotypic variation were investigated by logistic regression analysis. Results There were no significant differences between MDD patients with suicide and controls in genotypic (AG and GG) frequencies for rs7305115 SNP, but the distribution of AA genotype differed significantly (14.4% vs. 29.3%, p < 0.001). The G-allele frequency was significantly higher in cases than control group (58.1% vs.45.6%, p < 0.001), but the A-allele carrier indicated a decreased trend in MDD with suicide behaviors than control group (41.9% vs.54.4%, p < 0.001). The multivariate logistic regression analysis indicated that TPH2 rs7305115 AA (OR 0.33, 95% CI 0.22-0.99), family history of suicide (OR 2.98, 95% CI 1.17-5.04), negative life events half year ago (OR 6.64, 95% CI 2.48-11.04) and hopelessness (OR 7.68, 95% CI 5.79-13.74) were significantly associated with the suicide behaviors in MDD patients. Conclusions The study suggested that hopelessness, negative life events and family history of suicide were risk factors of attempted suicide in MDD while the TPH2 rs7305115A remained a significant protective predictor of suicide attempts.

Overexpression of HMGA2 is common in uterine leiomyomas (ULM). The expression of HMGA2 in its malignant counterpart - uterine leiomyosarcomas (ULMS) remains undetermined. Recently it has been shown that repression of HMGA2 by microRNA let-7s is a critical molecular regulatory mechanism associated with tumour growth in many tumours and cell types, including leiomyomas. To test whether HMGA2 and let-7s play a role in ULMS, we examined the levels of endogenous HMGA2 and let-7 expression and found a significant correlation between these two molecules in a case-matched cohort of human ULMS. We found that overexpression of HMGA2 and let-7-mediated HMGA2 repression is a relevant molecular alteration in ULMS. Disrupting the control of HMGA2 and let-7 pairs promotes ULMS cell growth in vitro.