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Purpose: Identify the hypoxia genes related to chemotherapy resistance of oral cancer, and construct a chemotherapy response model by machine learning algorithm. Methods: 72 oral cancer patients with complete chemotherapy records and chemotherapy reactions were screened from the Cancer Genome Atlas (TCGA) database. According to the chemotherapy reactions, they were divided into chemotherapy sensitive group and chemotherapy resistant group. The differential genes were screened by Limma package. Then the chemotherapy response gene were screened by univariate analysis. Based on the gene expression profile of chemotherapy response, four machine learning algorithms were used to construct the prediction model of chemotherapy response. The core genes were screened by lasso regression analysis. Finally, the prognosis and immune infiltration of the core genes were analyzed. The results were verified by immunohistochemistry (IHC). Results: We obtained 22 hypoxia related differential genes. Univariate analysis found 6 Chemotherapy response genes. Machine learning algorithms show that XGBoost have the best predictive performance for chemotherapy response. ALDOA is the core gene of chemotherapy resistance. Conclusions: Successfully constructed a chemotherapy prediction model for oral cancer by machine learning algorithm. Under hypoxia, the high expression of ALDOA is associated with chemotherapy resistance in oral cancer.
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Pine wilt disease caused by Bursaphelenchus xylophilus poses a serious threat to the economic and ecological value of forestry. Nematode trapping fungi trap and kill nematodes using specialized trapping devices, which are highly efficient and non-toxic to the environment, and are very promising for use as biological control agents. In this study, we isolated several nematode-trapping fungi from various regions and screened three for their high nematocidal efficiency. However, the effectiveness of these fungi as nematicides is notably influenced by temperature and exhibits different morphologies in response to temperature fluctuations, which are categorized as "NA," "thin," "dense," and "sparse." The trend of trap formation with temperature was consistent with the trend of nematocidal efficiency with temperature. Both of which initially increased and then decreased with increasing temperature. Among them, Arthrobotrys cladodes exhibited the highest level of nematocidal activity and trap formation among the tested species. Transcriptome data were collected from A. cladodes with various trap morphologies. Hydrolase activity was significantly enriched according to GO and KEGG enrichment analyses. Eight genes related to hydrolases were found to be consistent with the trend of trap morphology with temperature. Weighted gene co-expression analysis and the Cytoscape network revealed that these 8 genes are associated with either mitosis or autophagy. This suggests that they contribute to the formation of "dense" structures in nematode-trapping fungi. One of these genes is the serine protein hydrolase gene involved in autophagy. This study reveals a potentially critical role for hydrolases in trap formation and nematocidal efficiency. And presents a model where temperature affects trap formation and nematocidal efficiency by influencing the serine protease prb1 involved in the autophagy process.
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The Micromachines Editorial Office retracts the article "Preparation and analysis of structured color Janus droplets based on microfluidic 3D droplet printing" [...].
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The microfluidic technique for the three-dimensional (3D) printing of Janus droplets offers precise control over their size, orientation, and positioning. The proposed approach investigates the impact of variables such as the volume ratio of the oil phase, droplet size, and the ratio of nonionic surfactants on the dimensions of the structured color apertures of Janus droplets. The findings reveal that structured color apertures modulate accurately. Furthermore, fabricating color patterns facilitates cat, fish, and various other specific shapes using structured color Janus droplets. The color patterns exhibit temperature-sensitive properties, enabling them to transition between display and concealed states. Herein, the adopted microfluidic technique creates Janus droplets with customizable characteristics and uniform size, solving orientation as well as space arrangement problems. This approach holds promising applications for optical devices, sensors, and biomimetic systems.