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Endometriosis is a refractory estrogen-dependent gynecological disease in which ovarian endometriosis(OE) is the most common, and the main cell components are endometrial epithelial cells and stromal cells. However, constructing ectopic endometrial epithelial cell models in basic studies is still challenging. In this study, we explored the feasibility and influencing factors of constructing and validating eutopic and ectopic endometrial organoid models of OE as in-vitro models. Eutopic and ectopic endometrial tissues of OE patients were selected to establish organoids. Morphologically, the organoids showed a three-dimensional glandular structure with vacuoles or cystic irregularities, and the histological features of the epithelial organoids in endometriosis were well preserved. Immunofluorescence showed positive expression of epithelial markers and estrogen/progesterone receptors. Genetic identification revealed a 100% match between endometriosis epithelial organoids and endometrial tissue, indicating a common origin. The effects of estrogen and progesterone on the proliferation and secretion of organoids differed with the change in concentration. The successful construction of ectopic endometrial organoids provides a new in vitro model for drug intervention and mechanism study of ovarian endometriosis.

Objective This study aimed to investigate the effects of the interaction between ROP16 and TAF15 on apoptosis and cell cycle regulation in A549 lung adenocarcinoma cells. Methods Lentivirus-infected A549 cells which could overexpress type I, II, and III ROP16, along with an empty vector control group, were established. Potential interacting proteins with ROP16 were identified by using co-immunoprecipitation (Co-IP) and liquid chromatography-mass spectrometry (LC–MS). High-scoring interacting proteins were selected for verification through Venn diagram analysis, scoring, and intensity evaluation. The interaction between ROP16 and TAF15 was confirmed by using co-immunoprecipitation. Moreover, TAF15-specific siRNA was synthesized and transfected into A549 cells overexpressing ROP16 types I, II, and III. The levels of apoptosis and cell cycle were detected by flow cytometry (FCM), and the expression levels of apoptosis-related proteins and cell cycle-related proteins were detected by real-time fluorescence quantitative PCR (RT-qPCR) and western blotting. Results Three stable A549 cell lines overexpressing type I, II, and III ROP16 were successfully established. IP-LC/MS identified 29 potential ROP16-interacting proteins, among which 13 had a score greater than 100. Subsequent bioinformatic analysis and co-immunoprecipitation confirmed the interaction between ROP16 and TAF15. Flow cytometry analysis revealed that type I and III ROP16 promoted A549 cell apoptosis and induced cell cycle arrest. Furthermore, western blotting and RT-qPCR demonstrated their modulation of the expression of cell cycle regulators (p21, CDK6, Cyclin D1) and apoptosis-related proteins (Bax, BCL-2, p53, Caspase-9). In contrast, type II ROP16 exhibited none of these effects. However, upon TAF15 silencing, the pro-apoptotic effects of type I and III ROP16 were attenuated, no significant cell cycle arrest was observed, and their regulatory effects on the expression of cell cycle- and apoptosis-related proteins were also significantly diminished. Conclusions Our study demonstrates that type I/III ROP16 induce apoptosis and cell cycle arrest in A549 cells through interactions with the host RNA-binding protein TAF15. These findings not only provide compelling evidence for the oncosuppressive potential of Toxoplasma gondii -derived secretory proteins but also uncover a previously unrecognized mechanism by which parasite effectors hijack host transcriptional regulators to subvert cancer cell survival pathways. Graphical Abstract

Garden waste is a solid waste produced by plant littering or pruning. Improper disposal can easily pollute the environment. The addition of bulking agents (BAs) can improve the efficiency of organic waste composting. In this study, garden waste and dairy manure were used as raw materials, and easily available and recyclable branches were used as bulking agents to realize the synergistic resource utilization of the two. Three treatments were set up in the experiment, and 10% crushed branches, 1 cm branches, and 3 cm branches were added to the raw materials, respectively. The results showed that compared with the control group (adding crushed branches), the addition of 1 cm branches and 3 cm branches increased the cellulose degradation rate by 13.16–13.33% and the hemicellulose degradation rate by 18.24–23.86%. The monitoring results of CO[sub.2] release showed that the cumulative CO[sub.2] release of the treatment groups with 1 cm and 3 cm branches was 78.56 L and 102.17 L, respectively, which was significantly higher than that of the crushed branches (67.24 L), indicating that the addition of 1 cm and 3 cm branches increased microbial activity and degradation efficiency. Microbial diversity analysis further showed that in the treatment group with 1 cm branches, the number of nodes in the co-occurrence network increased by 24.11% and 2.84%, respectively, compared with the crushed branches and 3 cm branches, and the number of edges increased by 44.25% and 19.72%, forming the most abundant and complex microbial community, which verified its promotion effect on the composting process from the microbial level. In summary, this study recommends the use of branches with a particle size of 1 cm as BAs for garden waste composting.

The treatment of ovarian cancer is hindered by its insidious onset and rapid progression. Exosomes (EXOs) present a promising therapeutic strategy for ovarian cancer by modulating the tumor microenvironment. However, concerns regarding the biosafety of animal-derived EXOs pose significant challenges to the development of innovative formulations. In this study, we propose a universal strategy to engineer plant-derived EXOs as microenvironment nanoregulators for targeted ovarian cancer therapy. EXOs derived from ginger were purified, loaded with the natural bioactive compound curcumin (Cur) with high encapsulation efficiency, and functionalized with a tumor-targeting aptamer. Upon intravenous administration, the resulting multifaceted microenvironment nanoregulator, termed A GE@Cur, effectively accumulates at the tumor site and exerts a tumor-suppressive effect through remodeling the tumor microenvironment. This novel therapeutic platform not only addresses the limitations of animal-derived EXOs but also paves the way for the development of innovative microenvironment regulators in clinical applications.

Background This study aimed to develop a novel nomogram that can accurately estimate platinum resistance to enhance precision medicine in epithelial ovarian cancer(EOC). Methods EOC patients who received primary therapy at the General Hospital of Ningxia Medical University between January 31, 2019, and June 30, 2021 were included. The LASSO analysis was utilized to screen the variables which contained clinical features and platinum-resistance gene immunohistochemistry scores. A nomogram was created after the logistic regression analysis to develop the prediction model. The consistency index (C-index), calibration curve, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA) were used to assess the nomogram’s performance. Results The logistic regression analysis created a prediction model based on 11 factors filtered down by LASSO regression. As predictors, the immunohistochemical scores of CXLC1, CXCL2, IL6, ABCC1, LRP, BCL2, vascular tumor thrombus, ascites cancer cells, maximum tumor diameter, neoadjuvant chemotherapy, and HE4 were employed. The C-index of the nomogram was found to be 0.975. The nomogram’s specificity is 95.35% and its sensitivity, with a cut-off value of 165.6, is 92.59%, as seen by the ROC curve. After the nomogram was externally validated in the test cohort, the coincidence rate was determined to be 84%, and the ROC curve indicated that the nomogram’s AUC was 0.949. Conclusion A nomogram containing clinical characteristics and platinum gene IHC scores was developed and validated to predict the risk of EOC platinum resistance.

In this paper, we propose an efficient parallel algorithm for generatingk (k≥1) spanning trees of a connected, weighted and undirected graphG(V,E,W) in the order of increasing weight. It runs inO(Tmat(n)+k logn) time withO(n2/logn) processors on a CREW PRAM, wheren=|V|, m=|E| andTmat (n),O(logn)≤Tmat (n)≤O(log2n) is the run time of the fastest parallel allel algorithm for finding a minimum spanning tree (MST) of G on a CREW PRAM. SinceTmat (n)=O(log2n) for the time being, our algorithm is of the same time bound withTmat (n) whenk≤O(logn).

Maximum satisfiability (MAX SAT) problem is an optimization version of the satisfiability (SAT) problem. This problem arises in certain applications in expert systems and knowledge base revision. MAX SAT problem is NP-hard. Some algorithms can solve this problem, but they are not adapted to the special cases where the number of variables is larger than the number of clauses. Usually, the number of variables has great impact on the efficiency of these algorithms. Thus, a polynomial-time algorithm is proposed to reduce the number of variables. LetT be any instance of the MAX SAT problem. The algorithm transformsT into another instanceP of which the number of variables is smaller than the number of clauses ofT. Using other algorithms, the optimal solution toP can be found, and it can be used to construct the optimal solution ofT. Therefore, this algorithm is an efficient preprocessing step.

A fast and efficient parallel algorithm for finding a maximal edge matching in an undirected graphG(V,E) is proposed. It runs inO(logn) time with (M/logn+n) processors on an EREW PRAM for a class of graph set II, wheren=|V|, m=|E| and II includes at least (i) planar graphs; (ii) graphs of bounded genus; and (iii) graphs of bounded maximum degree and so on. Our algorithm improves the previously known best algorithms by a factor of logn in the time complexity with linear number of processors on EREW PRAMs when the input is limited to II.

The paper briefly reviews NP-hard optimization problems and their inapproximability. The hardness of solving CLIQUE problem is specifically discussed. A dynamic-programming algorithm and its improved version for CLIQUE are reviewed and some additional analysis is presented. The analysis implies that the improved algorithm, HEWN (hierarchical edge-weighted network), only provides a heuristic or useful method, but cannot be called a polynomial algorithm.

AnO(n2) time approximation algorithm for the minimum rectilinear Steiner tree is proposed. The approximation ratio of the algorithm is strictly less than 1.5. The computing performances show the costs of the spanning trees produced by the algorithm are only 0.8% away from the optimal ones.