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Glioma is characterized by high heterogeneity and poor prognosis. Attempts have been made to understand its diversity in both genetic expressions and radiomic characteristics, while few integrated the two omics in predicting survival of glioma. This study was intended to investigate the connection between glioma imaging and genome, and examine its predictive value in glioma mortality risk and tumor immune microenvironment (TIME). Clinical, transcriptomics and radiomics data were obtained from public datasets and patients in our center. Correlation analysis between gene expression and radiomic feature (RF) was performed, followed by survival analysis to select RF-related genes (RFRGs) and gene expression-related RFs (GRRFs). After that, RFRGs and GRRFs were used to construct mortality risk prediction model of all glioma and isocitrate dehydrogenase (IDH) wild type (WT) glioma. The association between RFRGs and TIME was explored. Six cohorts composed of 1,754 glioma patients were included. Thirty-five genes and eighty-two RFs demonstrated high correlation with each other. Gene score based on RFRGs was independent predictor of both glioma ( P < 0.05) and IDH-WT glioma ( P < 0.05). Same score based on GRRFs was also able to stratify risk of both glioma ( P < 0.0001) and IDH-WT glioma ( P < 0.0001), with nomograms constructed separately. The TIME of gliomas predicted with RFRGs’ score found mismatched risk of death with immune response. RFRGs and GRRFs were able to predict glioma mortality risk and TIME. Further studies could validate our results and explore this genome-imaging interactions.

SG-III laser facility is now the largest laser driver for inertial confinement fusion research in China. The whole laser facility can deliver 180 kJ energy and 60 TW power ultraviolet laser onto target, with power balance better than 10%. We review the laser system and introduce the SG-III laser performance here.

Ovarian cancer (OC) remains the most lethal gynecologic malignancy. Our previous work showed that WNK lysine-deficient protein kinase 2 (WNK2) promotes OC cell proliferation and migration. To clarify the molecular basis of WNK2-driven OC progression, here, we performed transcriptome sequencing to identify WNK2-regulated mRNAs and noncoding RNAs. We validated candidate targets using qRT-PCR and Western blot analyses. Functional assays, including CCK-8, colony formation, and Transwell assays, evaluated the role of POU5F1B and its capacity to rescue the effects of WNK2 knockdown. POU5F1B is a promising OC therapeutic target, mediating WNK2-driven oncogenesis in xenograft models (n = 10). Because AKT acts downstream of POU5F1B, we examined AKT phosphorylation and found that POU5F1B displayed clear oncogenic activity in OC cells. WNK2 upregulated POU5F1B mRNA and protein levels, while POU5F1B overexpression reversed the tumor-suppressive effects caused by WNK2 depletion. Mechanistically, WNK2 silencing decreased AKT phosphorylation, which POU5F1B overexpression restored. Together, these results demonstrate that WNK2 promotes OC progression by upregulating the validated oncogene POU5F1B and activating AKT signaling. These findings establish WNK2 as an oncogenic driver and a promising therapeutic target in OC.

Background Aerobic glycolysis is a hallmark of cancers including liver hepatocellular carcinoma (LIHC). RNA m5C methylation is involved in LIHC progression. However, the effect of a m5C writer, NSUN5, on glycolysis in LIHC remains not known. The present study aimed to investigate the effect of NSUN5 on glycolysis in LIHC and the molecular mechanism. Methods NSUN5 and EFNA3 expression data were acquired from The Cancer Genome Atlas database. Cell viability and glycolysis were evaluated. Tumor growth was evaluated using the xenograft tumor model. The effect of NSUN5 on EFNA3 m5C methylation was evaluated using methylated RNA immunoprecipitation and dual-luciferase reporter assay. Results We found that NSUN5 and EFNA3 expression was increased in LIHC and related to poor survival. Knocking down NSUN5 inhibited LIHC cell viability and glycolysis in vitro, and inhibited tumor growth and glycolysis in vivo. Moreover, the expression of NSUN5 was positively correlated with that of EFNA3. NSUN5 stabilized EFNA3 by promoting m5C modification of EFNA3. Additionally, overexpression of EFNA3 reversed the inhibition of cell viability and glycolysis induced by NSUN5 silence. Conclusion Silencing of NSUN5 decelerates LIHC progression by inhibiting glycolysis mediated by EFNA3 with m5C modification, highlighting the potential of NSUN5 as a therapeutic target for LIHC.

The non‐POU domain‐containing octamer‐binding protein NONO/p54nrb, which belongs to the Drosophila behaviour/human splicing (DBHS) family, is a multifunctional nuclear protein rarely functioning alone. Emerging solid evidences showed that NONO engages in almost every step of gene regulation, including but not limited to mRNA splicing, DNA unwinding, transcriptional regulation, nuclear retention of defective RNA and DNA repair. NONO is involved in many biological processes including cell proliferation, apoptosis, migration and DNA damage repair. Dysregulation of NONO has been found in many types of cancer. In this review, we summarize the current and fast‐growing knowledge about the regulation of NONO, its biological function and implications in tumorigenesis and cancer progression. Overall, significant findings about the roles of NONO have been made, which might make NONO to be a new biomarker or/and a possible therapeutic target for cancers.

Backgrounds/Aims: Ovarian cancer is the most lethal gynaecologic malignancy and is difficult to detect early. The inefficient early diagnosis of ovarian cancer is the main contributor to its high mortality rate. Aptamers, as chemical antibodies, are single-stranded DNA or RNA oligonucleotides that target cells or molecules with high affinity. Methods: Binding ability of R13 was measured by flow cytometry analysis. Stability of R13 was tested in blood serum of an ovarian cancer patient. Internalization of R13 was verified by confocal microscope imaging. 80 cases ovarian cancer tissues, 10 cases normal ovary tissues in a microarray and 6 fallopian tube tissues were prepared for this study. R13’s target ability was further confirmed in vivo tumor models in NOD/SCID mice. Results: In this study, we found aptamer R13 bound to ovarian cancer cells with dissociation constants in the nanomolar range. Moreover, these results were further confirmed by tissue imaging. Next we demonstrated that the targets of R13 are membrane proteins and that its internalization occurs in a caveolae-mediated and clathrin-mediated manner. The target function of R13 was determined by imaging A2780 tumours in mouse models. Conclusion: These findings suggest that R13 is a promising novel tool to diagnose and deliver drugs to treat ovarian cancer.

Hepatocellular carcinoma (HCC) remains one of the most prevalent malignant tumors globally, characterized by high incidence and mortality rates. Despite ongoing research, the underlying molecular mechanisms of HCC development are not yet fully understood. Utilizing bioinformatic analysis, real-time quantitative reverse transcription polymerase chain reaction (RT-qPCR), and Western blot assays, we identified that the expression of specificity protein 1 (Sp1) was significantly elevated in HCC cells compared to normal cells. Knockdown of the Sp1 gene led to a marked reduction in the viability and clonogenic potential of HCC cells. Further investigation revealed that the succinylation level of Sp1 was also increased in HCC cells. The upregulation of Sp1 expression was attributed to its succinylation, mediated by KAT2A, with lysine (K)562 identified as the succinylation site. Additionally, KAT2A and Sp1 were found to influence the upregulation of mTOR phosphorylation. Collectively, these findings suggest that KAT2A-promoted succinylation of Sp1 enhances the proliferative capacity of HCC cells by activating the mTOR pathway, providing a theoretical foundation for potential therapeutic strategies against HCC.

Background/aimsThe aim of this study was to develop and evaluate digital ray, based on preoperative and postoperative image pairs using style transfer generative adversarial networks (GANs), to enhance cataractous fundus images for improved retinopathy detection.MethodsFor eligible cataract patients, preoperative and postoperative colour fundus photographs (CFP) and ultra-wide field (UWF) images were captured. Then, both the original CycleGAN and a modified CycleGAN (C2ycleGAN) framework were adopted for image generation and quantitatively compared using Frechet Inception Distance (FID) and Kernel Inception Distance (KID). Additionally, CFP and UWF images from another cataract cohort were used to test model performances. Different panels of ophthalmologists evaluated the quality, authenticity and diagnostic efficacy of the generated images.ResultsA total of 959 CFP and 1009 UWF image pairs were included in model development. FID and KID indicated that images generated by C2ycleGAN presented significantly improved quality. Based on ophthalmologists’ average ratings, the percentages of inadequate-quality images decreased from 32% to 18.8% for CFP, and from 18.7% to 14.7% for UWF. Only 24.8% and 13.8% of generated CFP and UWF images could be recognised as synthetic. The accuracy of retinopathy detection significantly increased from 78% to 91% for CFP and from 91% to 93% for UWF. For retinopathy subtype diagnosis, the accuracies also increased from 87%–94% to 91%–100% for CFP and from 87%–95% to 93%–97% for UWF.ConclusionDigital ray could generate realistic postoperative CFP and UWF images with enhanced quality and accuracy for overall detection and subtype diagnosis of retinopathies, especially for CFP.\\Trial registration numberThis study was registered with ClinicalTrials.gov (NCT05491798).

Image quality variation is a prominent cause of performance degradation for intelligent disease diagnostic models in clinical applications. Image quality issues are particularly prominent in infantile fundus photography due to poor patient cooperation, which poses a high risk of misdiagnosis. Here, we developed a deep learning-based image quality assessment and enhancement system (DeepQuality) for infantile fundus images to improve infant retinopathy screening. DeepQuality can accurately detect various quality defects concerning integrity, illumination, and clarity with area under the curve (AUC) values ranging from 0.933 to 0.995. It can also comprehensively score the overall quality of each fundus photograph. By analyzing 2,015,758 infantile fundus photographs from real-world settings using DeepQuality, we found that 58.3% of them had varying degrees of quality defects, and large variations were observed among different regions and categories of hospitals. Additionally, DeepQuality provides quality enhancement based on the results of quality assessment. After quality enhancement, the performance of retinopathy of prematurity (ROP) diagnosis of clinicians was significantly improved. Moreover, the integration of DeepQuality and AI diagnostic models can effectively improve the model performance for detecting ROP. This study may be an important reference for the future development of other image-based intelligent disease screening systems.

Breast cancer ranks as the most frequently diagnosed cancer among women worldwide. Elevated cytoplasmic p21 levels are often found in breast cancer tissues and related to a poor prognosis. However, the underlying mechanisms that lead to the stabilization of cytoplasmic p21 protein, which normally has a very short half-life, remain obscure. In this study, we found that there was a strong correlation between p21 and USP11 in the cytoplasm of breast cancer tissues and cells. Furthermore, we revealed that ERK1/2 phosphorylated USP11 at the Ser905 site, which promoted the cytoplasmic localization of USP11. In the cytoplasm, USP11 colocalized and interacted with p21. As a result, USP11 catalyzed the removal of polyubiquitin chains bound to cytoplasmic p21 and resulted in its stabilization. Functionally, USP11-mediated stabilization of cytoplasmic p21 induced breast cancer cell proliferation and . Our findings provide the first evidence that ubiquitinated p21 in the cytoplasm can be recycled through USP11-mediated deubiquitination, and we identified the USP11-p21 axis in the cytoplasm as a potential therapeutic target for breast cancer control.