OBJECTIVE: To compare the hatching rates of the vitrified and the fresh mouse blastocysts co-cultured with decidualized or non decdualized human endometrial cells and to confirm the necessity of assisted hatching in the vitrified mouse blastocyst. METHODS: Stromal and epitherial cells isolated from human endometrial tissue were co-cultured and decidualized with TGF-beta 1 and progesterone. The vitrified and the fresh mouse blastocysts were co-cultured with human decidualized or non-decidualized endometrial cells, respectively and the hatching rates were investigated. RESULTS: Epithelial and stromal cells isolated from endometrial tissue were cultured seperately for 24 hours and stained by immunohistochemical staining for cytokeratin (epithelial cells) or vimentin (stromal cells). The immunohistochemical study was positive for cytokeratin or vimentin and confirmed that epithelial and stromal cells were isolated from endometrial tissue successfully. The co-cultured human stromal and epitherial cells were decidualized by administration of TGF-beta 1 and progesterone. The hatching rates of the fresh and the vitrified mouse blastocysts co-cultured with decidualized human endometrial cells were 89% and 31%, respectively. The hatching rates of the fresh and the vitrified mouse blastocysts co-cultured with non-decidualized human endometrial cells were 82% and 27%, respectively. The hatching rates were significantly higher in fresh mouse blastocysts than in vitrified mouse blastocysts regardless of decidualization of human endometrial cells (P<0.05). CONCLUSION: The hatching rate was significantly higher in fresh mouse blastocysts than in vitrified mouse blastocysts. This results showed that the cryopreservation procedure caused the zona hardening of mouse blastocyst and the decidualization of endometrial cells did not affect to hatching rate of the vitrified mouse blastocysts. We confirmed that assisted hatching was necessary for improving the hatching rate of cryopreserved mouse blastocysts.
Animals ; Blastocyst ; Coculture Techniques ; Cryopreservation ; Herpes Zoster ; Humans ; Keratins ; Mice ; Progesterone ; Stromal Cells ; Transforming Growth Factor beta ; Vimentin

Background/Aims: Despite the high efficacy of direct-acting antivirals (DAAs), approximately 1–3% of hepatitis C virus (HCV) patients fail to achieve a sustained virological response. We conducted a nationwide study to investigate risk factors associated with DAA treatment failure. Machine-learning algorithms have been applied to discriminate subjects who may fail to respond to DAA therapy. Methods: We analyzed the Taiwan HCV Registry Program database to explore predictors of DAA failure in HCV patients. Fifty-five host and virological features were assessed using multivariate logistic regression, decision tree, random forest, eXtreme Gradient Boosting (XGBoost), and artificial neural network. The primary outcome was undetectable HCV RNA at 12 weeks after the end of treatment. Results: The training (n=23,955) and validation (n=10,346) datasets had similar baseline demographics, with an overall DAA failure rate of 1.6% (n=538). Multivariate logistic regression analysis revealed that liver cirrhosis, hepatocellular carcinoma, poor DAA adherence, and higher hemoglobin A1c were significantly associated with virological failure. XGBoost outperformed the other algorithms and logistic regression models, with an area under the receiver operating characteristic curve of 1.000 in the training dataset and 0.803 in the validation dataset. The top five predictors of treatment failure were HCV RNA, body mass index, α-fetoprotein, platelets, and FIB-4 index. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the XGBoost model (cutoff value=0.5) were 99.5%, 69.7%, 99.9%, 97.4%, and 99.5%, respectively, for the entire dataset. Conclusions Machine learning algorithms effectively provide risk stratification for DAA failure and additional information on the factors associated with DAA failure.