NSUN2/YBX1 promotes the progression of breast cancer by enhancing HGH1 mRNA stability through m5C methylation.

BACKGROUND: RNA m5C methylation has been extensively implicated in the occurrence and development of tumors. As the main methyltransferase, NSUN2 plays a crucial regulatory role across diverse tumor types. However, the precise impact of NSUN2-mediated m5C modification on breast cancer (BC) remains unclear. Our study aims to elucidate the molecular mechanism underlying how NSUN2 regulates the target gene HGH1 (also known as FAM203) through m5C modification, thereby promoting BC progression. Additionally, this study targets at preliminarily clarifying the biological roles of NSUN2 and HGH1 in BC. METHODS: Tumor and adjacent tissues from 5 BC patients were collected, and the m5C modification target HGH1 in BC was screened through RNA sequencing (RNA-seq) and single-base resolution m5C methylation sequencing (RNA-BisSeq). Methylation RNA immunoprecipitation-qPCR (MeRIP-qPCR) and RNA-binding protein immunoprecipitation-qPCR (RIP-qPCR) confirmed that the methylation molecules NSUN2 and YBX1 specifically recognized and bound to HGH1 through m5C modification. In addition, proteomics, co-immunoprecipitation (co-IP), and Ribosome sequencing (Ribo-Seq) were used to explore the biological role of HGH1 in BC. RESULTS: As the main m5C methylation molecule, NSUN2 is abnormally overexpressed in BC and increases the overall level of RNA m5C. Knocking down NSUN2 can inhibit BC progression in vitro or in vivo. Combined RNA-seq and RNA-BisSeq analysis identified HGH1 as a potential target of abnormal m5C modifications. We clarified the mechanism by which NSUN2 regulates HGH1 expression through m5C modification, a process that involves interactions with the YBX1 protein, which collectively impacts mRNA stability and protein synthesis. Furthermore, this study is the first to reveal the binding interaction between HGH1 and the translation elongation factor EEF2, providing a comprehensive understanding of its ability to regulate transcript translation efficiency and protein synthesis in BC cells. CONCLUSIONS: This study preliminarily clarifies the regulatory role of the NSUN2-YBX1-m5C-HGH1 axis from post-transcriptional modification to protein translation, revealing the key role of abnormal RNA m5C modification in BC and suggesting that HGH1 may be a new epigenetic biomarker and potential therapeutic target for BC.

An efficient hybrid differential evolution-golden jackal optimization algorithm for multilevel thresholding image segmentation.

Image segmentation is a crucial process in the field of image processing. Multilevel threshold segmentation is an effective image segmentation method, where an image is segmented into different regions based on multilevel thresholds for information analysis. However, the complexity of multilevel thresholding increases dramatically as the number of thresholds increases. To address this challenge, this article proposes a novel hybrid algorithm, termed differential evolution-golden jackal optimizer (DEGJO), for multilevel thresholding image segmentation using the minimum cross-entropy (MCE) as a fitness function. The DE algorithm is combined with the GJO algorithm for iterative updating of position, which enhances the search capacity of the GJO algorithm. The performance of the DEGJO algorithm is assessed on the CEC2021 benchmark function and compared with state-of-the-art optimization algorithms. Additionally, the efficacy of the proposed algorithm is evaluated by performing multilevel segmentation experiments on benchmark images. The experimental results demonstrate that the DEGJO algorithm achieves superior performance in terms of fitness values compared to other metaheuristic algorithms. Moreover, it also yields good results in quantitative performance metrics such as peak signal-to-noise ratio (PSNR), structural similarity index (SSIM), and feature similarity index (FSIM) measurements.

Age-stage, two-sex life table, and population projection of Ostrinia furnacalis (Lepidoptera: Crambidae) at different temperatures.

Ostrinia furnacalis (Guenée) (Lepidoptera: Crambidae), a highly destructive pest in Asia, poses a significant threat to maize production by causing substantial yield losses. However, there is a lack of information regarding the impact of temperature variations on its population dynamics and the age-stage and two-sex life table. This study aimed to investigate the impact of 4 temperatures (20 °C, 24 °C, 28 °C, 32 °C) on the development, reproduction, and survival of O. furnacalis under controlled laboratory conditions. Our results revealed that O. furnacalis successfully developed, survived, and laid eggs across the tested temperatures (20-32 °C). The shortest developmental duration for all immature stages was observed at 32 °C. Conversely, increasing temperatures led to decreased longevity. Among the temperatures tested, 28 °C proved to be optimal for O. furnacalis, exhibiting the highest intrinsic rate of increase, finite rate of increase, and net reproductive rate. Our findings indicate that O. furnacalis thrives within a wide temperature range of 20-32 °C, with 28 °C being the most favorable for reproduction. These insights are crucial for predicting population dynamics under diverse climatic conditions and developing effective control strategies against O. furnacalis. This study enhances our understanding of O. furnacalis' life-history traits and provides valuable information for targeted pest management approaches.