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Prostate cancer (PCa) risk-associated SNPs are enriched in noncoding cis-regulatory elements (rCREs), yet their modi operandi and clinical impact remain elusive. Here, we perform CRISPRi screens of 260 rCREs in PCa cell lines. We find that rCREs harboring high risk SNPs are more essential for cell proliferation and H3K27ac occupancy is a strong indicator of essentiality. We also show that cell-line-specific essential rCREs are enriched in the 8q24.21 region, with the rs11986220-containing rCRE regulating MYC and PVT1 expression, cell proliferation and tumorigenesis in a cell-line-specific manner, depending on DNA methylation-orchestrated occupancy of a CTCF binding site in between this rCRE and the MYC promoter. We demonstrate that CTCF deposition at this site as measured by DNA methylation level is highly variable in prostate specimens, and observe the MYC eQTL in the 8q24.21 locus in individuals with low CTCF binding. Together our findings highlight a causal mechanism synergistically driven by a risk SNP and DNA methylation-mediated 3D genome architecture, advocating for the integration of genetics and epigenetics in assessing risks conferred by genetic predispositions.

Neuroendocrine prostate cancer (NEPC), a lethal form of the disease, is characterized by loss of androgen receptor (AR) signaling during neuroendocrine transdifferentiation, which results in resistance to AR-targeted therapy. Clinically, genomically and epigenetically, NEPC resembles other types of poorly differentiated neuroendocrine tumors (NETs). Through pan-NET analyses, we identified ONECUT2 as a candidate master transcriptional regulator of poorly differentiated NETs. ONECUT2 ectopic expression in prostate adenocarcinoma synergizes with hypoxia to suppress androgen signaling and induce neuroendocrine plasticity. ONEUCT2 drives tumor aggressiveness in NEPC, partially through regulating hypoxia signaling and tumor hypoxia. Specifically, ONECUT2 activates SMAD3, which regulates hypoxia signaling through modulating HIF1α chromatin-binding, leading NEPC to exhibit higher degrees of hypoxia compared to prostate adenocarcinomas. Treatment with hypoxia-activated prodrug TH-302 potently reduces NEPC tumor growth. Collectively, these results highlight the synergy between ONECUT2 and hypoxia in driving NEPC, and emphasize the potential of hypoxia-directed therapy for NEPC patients.

In this paper, a progressive image transmission and recovery algorithm based on hybrid attention mechanism and feature fusion is proposed, aiming to solve the challenge of monitoring the signal-less region of transmission lines. The method combines wavelet transform, Swin Transformer, and hybrid attention module with the Pixel Shuffle upsampling mechanism to achieve a balance between quality and efficiency of image transmission in a low bandwidth environment. Initial preview is achieved by prioritizing the transmission of low-frequency subbands through wavelet transform, followed by dynamic optimization of the weight allocation of key features using a hybrid attention and local window multi-scale self-attention mechanism, and further enhancement of the resolution of the decoded image through Pixel Shuffle upsampling. Experimental results show that the algorithm significantly outperforms existing methods in terms of image quality (PSNR, SSIM), transmission efficiency, and bandwidth utilization, proving its superior adaptability and effectiveness in surveillance scenarios in signal-free regions. [ABSTRACT FROM AUTHOR]

Arc droop presents significant challenges in power system management due to its inherent complexity and dynamic nature. To address these challenges in predicting arc sag for transmission lines, this paper proposes an innovative time–series prediction model, AROA-CNN-LSTM-Attention(AROA-CLA). The model aims to enhance arc sag prediction by integrating a convolutional neural network (CNN), a long short-term memory network (LSTM), and an attention mechanism, while also utilizing, for the first time, the adaptive rabbit optimization algorithm (AROA) for CLA parameter tuning. This combination improves both the prediction performance and the generalization capability of the model. By effectively leveraging historical data and exhibiting superior time–series processing capabilities, the AROA-CLA model demonstrates excellent prediction accuracy and stability across different time scales. Experimental results show that, compared to traditional and other modern optimization models, AROA-CLA achieves significant improvements in RMSE, MAE, MedAE, and R2 metrics, particularly in reducing errors, accelerating convergence, and enhancing robustness. These findings confirm the effectiveness and applicability of the AROA-CLA model in arc droop prediction, offering novel approaches for transmission line monitoring and intelligent power system management. [ABSTRACT FROM AUTHOR]

In order to obtain a new type of fiber-based luminescent solar concentrators (FLSCs) which can meet the requirements of textile processing by melt spinning method. FLSCs were prepared by melt spinning using biology base polyamide and high temperature fluorescent dyes. The effects of the type, concentration and drafting ratio of fluorescent dyes on their structure and properties were investigated. The results show that the FLSCs show a smooth surface and a uniform evenness. The absorbance of the FLSCs increases with the increase of fluorescent dye concentration. The excitation fluorescence intensity of FLSCs increases initially and then decreases. When the dye concentration is 0.2 wt%, the short-circuit current generated by the FLSCs coupling with polycrystalline solar panels reaches saturation, The current of introducing yellow fluorescent dye FLSCs can reach 10.2 µ A. The absorbance and short-circuit current of 3 X drawn FLSCs are lower than those of as-spun FLSCs, while no significant change on the excitation fluorescence intensity of FLSCs. The tenacity values are all greater than 1.1 cN/dtex, which means the prepared FLSCs can meet the mechanical properties requirements of textile processing. [ABSTRACT FROM AUTHOR]

The Hippo pathway is generally understood to inhibit tumor growth by phosphorylating the transcriptional cofactor YAP to sequester it to the cytoplasm and reduce the formation of YAP-TEAD transcriptional complexes. Aberrant activation of YAP occurs in various cancers. However, we found a tumor-suppressive function of YAP in clear cell renal cell carcinoma (ccRCC). Using cell cultures, xenografts, and patient-derived explant models, we found that the inhibition of upstream Hippo-pathway kinases MST1 and MST2 or expression of a constitutively active YAP mutant impeded ccRCC proliferation and decreased gene expression mediated by the transcription factor NF-κB. Mechanistically, the NF-κB subunit p65 bound to the transcriptional cofactor TEAD to facilitate NF-κB–target gene expression that promoted cell proliferation. However, by competing for TEAD, YAP disrupted its interaction with NF-κB and prompted the dissociation of p65 from target gene promoters, thereby inhibiting NF-κB transcriptional programs. This cross-talk between the Hippo and NF-κB pathways in ccRCC suggests that targeting the Hippo-YAP axis in an atypical manner—that is, by activating YAP—may be a strategy for slowing tumor growth in patients. Editor's summary: The transcriptional cofactor YAP is usually associated with tumor progression. However, Li et al. found that YAP has a tumor-suppressive role in clear cell renal cell carcinoma (ccRCC) by outcompeting another transcription factor for a binding partner. The proliferation of ccRCC cells was driven by the NF-κB subunit p65 in complex with the cofactor TEAD. YAP competed for TEAD binding, displacing p65 and preventing its transcriptional activity. Activating YAP repressed tumor growth in mice, suggesting the potential of this counterintuitive approach to stall primary ccRCC growth in patients. —Leslie K. Ferrarelli [ABSTRACT FROM AUTHOR]