Search

Online marketers make efforts to sell more products to their customers to increase turnover. One way to sell more products is to ensure that products belonging to the same scene are offered together. As such, it is beneficial to categorize products into different groups and tag them to particular, defined scenes. The mechanism of building relationships between products and scenes is called “scene-based knowledge system construction”. The construction of a scene-based knowledge system is usually based on business operators’ expert knowledge and past experiences, which often causes product categorization to be inaccurate. Hence, in this paper, we discuss the importance and necessity of constructing a scene-based knowledge system, analyze it from a business perspective, and discuss its challenges.

Context: COVID-19 is a novel coronavirus pneumonia, which is related to abnormal liver function. Thus, it is important to explore the occurrences and causes of abnormal liver function with COVID-19. Methods: We chose 109 patients with COVID-19 in 2020 and studied the relationship between gender, age, basic diseases, antiviral drug treatment, disease classification, and abnormal liver function, and analyzed the causes of abnormal liver function in patients with COVID-19 Results: Among patients, 46 (42.20%) had abnormal liver function at admission; 37 (80.43%) had mild abnormal liver function; and 9 (19.57%) had severe liver function. Compared with other age groups, the abnormal rate of serum ALP in the group younger than 21 years old were the highest (P < 0.05). The abnormal rates and concentrations of serum ALT, AST and γ-GT in the male groups were higher than in female groups (P < 0.05), basic disease group were higher than those in the non-basic disease group (P < 0.05). Serum γ-GT concentration after 1 week of antiviral treatment was higher than that before treatment (P < 0.05). The abnormal rate of ALT and AST at discharge was lower than that after antiviral treatment for 1 week (P < 0.05). Serum TB and AST concentrations at discharge were lower than those before treatment (P < 0.05). Serum AST and γ-GT concentrations in severe/critical type group were higher than those in mild or ordinary type group (P < 0.05) Conclusions: In this study, we found male sex, basic diseases, antiviral drugs, and severe/critical types are related to the occurrence of abnormal liver function in COVID-19 patients.

Abstract Histone lysine crotonylation, an evolutionarily conserved modification differing from acetylation, exerts pivotal control over diverse biological processes. Among these are gene transcriptional regulation, spermatogenesis, and cell cycle processes. However, the dynamic changes and functions of histone crotonylation in preimplantation embryonic development in mammals remain unclear. Here, we show that the transcription coactivator P300 functions as a writer of histone crotonylation during embryonic development. Depletion of P300 results in significant developmental defects and dysregulation of the transcriptome of embryos. Importantly, we demonstrate that P300 catalyzes the crotonylation of histone, directly stimulating transcription and regulating gene expression, thereby ensuring successful progression of embryo development up to the blastocyst stage. Moreover, the modification of histone H3 lysine 18 crotonylation (H3K18cr) is primarily localized to active promoter regions. This modification serves as a distinctive epigenetic indicator of crucial transcriptional regulators, facilitating the activation of gene transcription. Together, our results propose a model wherein P300-mediated histone crotonylation plays a crucial role in regulating the fate of embryonic development.

Abstract Purpose This study aims to develop an ensemble machine learning-based (EML-based) risk prediction model for radiation dermatitis (RD) in patients with head and neck cancer undergoing proton radiotherapy, with the goal of achieving superior predictive performance compared to traditional models. Materials and methods Data from 57 head and neck cancer patients treated with intensity-modulated proton therapy at Kaohsiung Chang Gung Memorial Hospital were analyzed. The study incorporated 11 clinical and 9 dosimetric parameters. Pearson’s correlation was used to eliminate highly correlated variables, followed by feature selection via LASSO to focus on potential RD predictors. Model training involved traditional logistic regression (LR) and advanced ensemble methods such as Random Forest and XGBoost, which were optimized through hyperparameter tuning. Results Feature selection identified six key predictors, including smoking history and specific dosimetric parameters. Ensemble machine learning models, particularly XGBoost, demonstrated superior performance, achieving the highest AUC of 0.890. Feature importance was assessed using SHAP (SHapley Additive exPlanations) values, which underscored the relevance of various clinical and dosimetric factors in predicting RD. Conclusion The study confirms that EML methods, especially XGBoost with its boosting algorithm, provide superior predictive accuracy, enhanced feature selection, and improved data handling compared to traditional LR. While LR offers greater interpretability, the precision and broader applicability of EML make it more suitable for complex medical prediction tasks, such as predicting radiation dermatitis. Given these advantages, EML is highly recommended for further research and application in clinical settings.

Background As women with low ovarian reserve embark on the challenging journey of in-vitro fertilisation (IVF) treatment, the choice between natural and mildly stimulated cycles becomes a pivotal consideration. It is unclear which of these two regimens is superior for women with low ovarian reserve. Our study aims to assess the impact of natural cycles on embryo quality and pregnancy outcomes in women with low ovarian reserve undergoing IVF treatment compared to mildly stimulated cycles.Methods This retrospective study enrolled consecutive patients with low ovarian reserve who underwent IVF/intracytoplasmic sperm injection (ICSI) at Guangdong Second Provincial General Hospital between January 2017 and April 2021. The primary outcome for pregnancy rate of 478 natural cycles and 448 mild stimulated cycles was compared. Secondary outcomes included embryo quality and oocyte retrieval time of natural cycles.Results The pregnancy rate in the natural cycle group was significantly higher than that in the mildly stimulated cycle group (51.8% vs. 40.1%, p = 0.046). Moreover, natural cycles exhibited higher rates of available embryos (84.1% vs. 78.6%, p = 0.040), high-quality embryos (61.8% vs. 53.2%, p = 0.008), and utilisation of oocytes (73% vs. 65%, p = 0.001) compared to mildly stimulated cycles. Oocyte retrievals in natural cycles were predominantly performed between 7:00 and 19:00, with 94.9% occurring during this time frame. In natural cycles with high-quality embryos, 96.4% of oocyte retrievals were also conducted between 7:00 and 19:00.Conclusion Natural cycles with appropriately timed oocyte retrieval may present a valuable option for patients with low ovarian reserve.

Host-virus interactions can significantly impact the viral life cycle and pathogenesis; however, our understanding of the specific host factors involved in highly pathogenic avian influenza A virus H7N9 (HPAI H7N9) infection is currently restricted. Herein, we designed and synthesized 65 small interfering RNAs targeting host genes potentially associated with various aspects of RNA virus life cycles. Afterward, HPAI H7N9 viruses were isolated and RNA interference was used to screen for host factors likely to be involved in the life cycle of HPAI H7N9. Moreover, the research entailed assessing the associations between host proteins and HPAI H7N9 proteins. Twelve key host proteins were identified: Annexin A (ANXA)2, ANXA5, adaptor related protein complex 2 subunit sigma 1 (AP2S1), adaptor related protein complex 3 subunit sigma 1 (AP3S1), ATP synthase F1 subunit alpha (ATP5A1), COPI coat complex subunit alpha (COP)A, COPG1, heat shock protein family A (Hsp70) member 1A (HSPA)1A, HSPA8, heat shock protein 90 alpha family class A member 1 (HSP90AA1), RAB11B, and RAB18. Co-immunoprecipitation revealed intricate interactions between viral proteins (hemagglutinin, matrix 1 protein, neuraminidase, nucleoprotein, polymerase basic 1, and polymerase basic 2) and these host proteins, presumably playing a crucial role in modulating the life cycle of HPAI H7N9. Notably, ANXA5, AP2S1, AP3S1, ATP5A1, HSP90A1, and RAB18, were identified as novel interactors with HPAI H7N9 proteins rather than other influenza A viruses (IAVs). These findings underscore the significance of host-viral protein interactions in shaping the dynamics of HPAI H7N9 infection, while highlighting subtle variations compared with other IAVs. Deeper understanding of these interactions holds promise to advance disease treatment and prevention strategies.