Identification of key genes increasing susceptibility to atrial fibrillation in nonalcoholic fatty liver disease and the potential mechanisms: mitochondrial dysfunction and systemic inflammation.

Background: Non-alcoholic fatty liver disease (NAFLD) and atrial fibrillation (AF) are major health burdens, with emerging evidence suggesting NAFLD as a significant risk factor for AF, but the mechanism is remain unclear. Methods: In this study, we analyzed gene expression data from NAFLD (GSE89632) and AF (GSE75092) datasets from the Gene Expression Omnibus. We identified co-upregulated and co-downregulated genes between NAFLD and AF, assessed diagnostic potential of specific genes, conducted immune infiltration analysis, and performed molecular docking studies with sodium glucose co-transporter 2 inhibitors (SGLT2i). Results: We identified eight co-upregulated and 31 co-downregulated genes between NAFLD and AF. Genes such as AMOT, PDE11A, TYMS, TMEM98, and PTGS2 demonstrated substantial diagnostic potential for identifying NAFLD patients at risk of AF. Immune infiltration analysis discovered an elevated presence of CD8 T cells, γδ T cells, and M2 macrophages in NAFLD livers, linking systemic inflammation to NAFLD and AF. Additionally, studies have shown that a connection between mitochondrial dysfunction and several hub genes like DGAT1, TYMS, and PTGS2, suggesting that mitochondrial disturbances may underpin the systemic inflammation in NAFLD, which possibly exacerbating AF. Molecular docking studies indicated that empagliflozin's binding affinity with key genes such as DGAT1, TYMS, and PTGS2 presents a novel therapeutic avenue for NAFLD-associated AF. Conclusion: Our study firstly discovered that AMOT, PDE11A, TYMS, TMEM98, and PTGS2 are associated with NAFLD-related AF and hold strong diagnostic values. Our study also indicates that mitochondrial dysfunction and systemic inflammation may be potential mechanisms bridging NAFLD and AF. Additionally, we identified empagliflozin as a potentially effective therapeutic agent for NAFLD-related AF at the molecular structure level. These novel insights contribute to the further understanding, diagnosis, and intervention of NAFLD-related AF.

Molecular mechanisms of HCG18 in the sorafenib resistance of hepatocellular carcinoma.

Sorafenib has been approved for advance hepatocellular carcinoma (HCC), however, drug resistance often occurred. Therefore, it is of great significance to clarify the underlying mechanisms of sorafenib resistance and to find out the effective strategies to overcome sorafenib resistance. The expression of HCG18 was detected by qPCR, MTT, colony formation, flow cytometry and TUNEL assay were used to explore the function of HCG18 on sorafenib resistance in HCC. RNA pull-down, RNA immunoprecipitation, immunofluorescence labeling, luciferase reporter assay, western blot and qPCR were used to investigate the mechanism of HCG18 regulating sorafenib resistance in HCC. Our results showed that HCG18 was significantly increased in HCC, which resulted in shorter 5-year survival for patients with HCC. Sorafenib can induce the expression of HCG18, suggesting HCG18 might be involved in sorafenib resistance in HCC. Further analysis showed that knockdown of HCG18 can reduce viability and increase apoptosis of HCC cells. Mechanistically, HCG18 can bind to USP15, further regulated the protein stability of p65, TAB2 and TAB3, and nuclear location of p65, which finally modulated the NF-κB signaling. Our findings showed that HCG18 played an important role in sorafenib resistance in HCC. And knockdown of HCG18 can promote the sensitivity of HCC cells to sorafenib, inferring that targeting HCG18 might be an effective strategy to overcome sorafenib resistance in HCC.

STEAP4 inhibits cisplatin-induced chemotherapy resistance through suppressing PI3K/AKT in hepatocellular carcinoma.

Chemotherapy resistance is the leading cause for hepatocellular carcinoma (HCC)-induced death. Exploring resistance generation mechanism is an urgent need for HCC therapy. Here, we found STEAP4 was significantly downregulated in HCC patients with recurrence. Patients with low STEAP4 had poor outcome, suggesting STEAP4 might inhibit chemotherapy resistance. Cell viability assay, colony formation assay, apoptosis assay, soft agar growth assay, and tumor animal model showed STEAP4 inhibited cisplatin resistance. Mechanism analysis showed STEAP4 inhibited PI3K/AKT pathway through directly interacting with AKT. Double knockdown of STEP4 and AKT significantly inhibited cisplatin resistance. We also found STEAP4 expression was negatively correlated with PI3K/AKT pathway activity in clinic specimens. In summary, our findings suggested STEAP4 inhibited cisplatin resistance through suppressing PI3K/AKT pathway activity, providing a target for HCC therapy.

SePiCo: Semantic-Guided Pixel Contrast for Domain Adaptive Semantic Segmentation.

Domain adaptive semantic segmentation attempts to make satisfactory dense predictions on an unlabeled target domain by utilizing the supervised model trained on a labeled source domain. One popular solution is self-training, which retrains the model with pseudo labels on target instances. Plenty of approaches tend to alleviate noisy pseudo labels, however, they ignore the intrinsic connection of the training data, i.e., intra-class compactness and inter-class dispersion between pixel representations across and within domains. In consequence, they struggle to handle cross-domain semantic variations and fail to build a well-structured embedding space, leading to less discrimination and poor generalization. In this work, we propose emantic-Guided Pixel Contrast (SePiCo), a novel one-stage adaptation framework that highlights the semantic concepts of individual pixels to promote learning of class-discriminative and class-balanced pixel representations across domains, eventually boosting the performance of self-training methods. Specifically, to explore proper semantic concepts, we first investigate a centroid-aware pixel contrast that employs the category centroids of the entire source domain or a single source image to guide the learning of discriminative features. Considering the possible lack of category diversity in semantic concepts, we then blaze a trail of distributional perspective to involve a sufficient quantity of instances, namely distribution-aware pixel contrast, in which we approximate the true distribution of each semantic category from the statistics of labeled source data. Moreover, such an optimization objective can derive a closed-form upper bound by implicitly involving an infinite number of (dis)similar pairs, making it computationally efficient. Extensive experiments show that SePiCo not only helps stabilize training but also yields discriminative representations, making significant progress on both synthetic-to-real and daytime-to-nighttime adaptation scenarios. The code and models are available at https://github.com/BIT-DA/SePiCo.

LncRNA SLC7A11-AS1 promotes the progression of hepatocellular carcinoma by mediating KLF9 ubiquitination.

Hepatocellular carcinoma (HCC) is a malignant tumor, which seriously threatens the life of patients. LncRNA SLC7A11-AS1 was reported to be abnormally expressed in HCC. Here, the functions and relative molecular regulatory mechanism of SLC7A11-AS1 in HCC were investigated. Nude mice and HCC cells were used as the experimental subjects. Knockdown or overexpression of exogenous genes was conducted in HCC cells. RT-qPCR, IHC, and western blot were employed to evaluate the abundance of genes and proteins. The malignant behaviors were evaluated using CCK-8, clone formation, wound-healing, and Transwell. The locations of SLC7A11-AS1 and KLF9 in cells were determined by FISH and IF assays. The total m6A level was evaluated by dot-blot assay. m6A modification of SLC7A11-AS1 was detected using RNA MeRIP. The interactions among molecules were validated by RIP, ChIP, dual luciferase reporter assay, and co-IP. SLC7A11-AS1 was elevated apparently in HCC cells and HCC tissues from mice. SLC7A11-AS1 silencing could suppress HCC progression, which was validated in in vivo and in vitro experiments. Furthermore, METTL3 mediated m6A modification of SLC7A11-AS1 to elevate its expression. In addition, SLC7A11-AS1 downregulated KLF9 expression by affecting STUB1-mediated ubiquitination degradation and KLF9 enhanced PHLPP2 expression to inactivate the AKT pathway. Eventually, rescue experiments revealed that KLF9 knockdown abolished SLC7A11-AS1 silencing-mediated suppression of HCC progression in vivo and in vitro. Our results unveiled that m6A-modified SLC7A11-AS1 promoted HCC progression by regulating the STUB1/KLF9/PHLPP2/AKT axis, indicating that targeting SLC7A11-AS1 might alleviate HCC progression.

Elevated FAM134B expression induces radiation-sensitive in hepatocellular carcinoma.

BACKGROUND: Previous studies have shown that Family with sequence similarity 134 member B (FAM134B) was involved in the occurrence and development of malignancy, however, the function and molecular mechanism of FAM134B in Hepatocellular Carcinoma (HCC) radiotherapy resistance remain unclear. Therefore, it may clinical effective to clarify the molecular mechanism and identify novel biomarker to overcome radiotherapy resistance in HCC. METHODS: The protein and mRNA expression of FAM134B were determined using Real-time PCR and Western blot, respectively. IHC assay was performed to investigate the association between FAM134B expression and the clinicopathological characteristics of 132 HCC patients. Functional assays, such as in situ model, colon formation, FACS, and Tunel assay were used to determine the oncogenic role of FAM134B in human HCC progression. Furthermore, western blotting and luciferase assay were used to determine the mechanism of FAM134B promotes radiation-sensitive in HCC cells. RESULTS: We noted that FAM134B was downregulated in HCC, which was correlated with the radiation resistance in patients with HCC. Overexpression of FAM134B contribute to radiation sensitive in HCC; however, inhibition of FAM134B confers HCC cell lines to radiation resistance both in vitro and in vivo. Moreover, we found that FAM134B interacts with FMS related receptor tyrosine kinase 3 (FLT3) and downregulation of FAM134B activated JAK/Stat3 signaling pathway. Importantly, pharmacological inhibition of JAK/Stat3 signaling pathway significantly counteracted downregulation of FAM134B-induced radiation resistance and enhanced radiation therapeutic efficacy in HCC. CONCLUSIONS: Our findings suggest that FAM134B may be a potential therapeutic biomarker for the treatment of HCC patients with radiotherapy tolerance.

Overexpression of tripartite motif-containing 47 (TRIM47) confers sensitivity to PARP inhibition via ubiquitylation of BRCA1 in triple negative breast cancer cells.

Triple-negative breast cancers (TNBC) frequently harbor defects in DNA double-strand break repair through homologous recombination (HR), such as BRCA1 dysfunction. However, less than 15% of TNBC patients were found to carry BRCA1 mutation, indicating that there are other mechanisms regulating BRCA1-deficient in TNBC. In the current study, we shown that overexpression of TRIM47 correlates with progression and poor prognosis in triple-negative breast cancer. Moreover, we demonstrated that TRIM47 directly interacts with BRCA1 and induces ubiquitin-ligase-mediated proteasome turnover of BRCA1, subsequently leads to a decrease of BRCA1 protein levels in TNBC. Moreover, the downstream gene expression of BRCA1, such as p53, p27, p21 was significantly reduced in the overexpression of TRIM47 cell lines but increased in TRIM47-deleted cells. Functionally, we found that overexpression of TRIM47 in TNBC cells confers an exquisite sensitivity to olaparib, an inhibitor of poly-(ADP-ribose)-polymerase (PARP), but TRIM47 inhibition significantly confers TNBC cells resistance to olaparib both in vitro and in vivo. Furthermore, we showed that overexpression of BRCA1 significant increase the olaparib resistance in TRIM47-overexpression-induced PARP inhibitions sensitivity. Taken together, our results uncover a novel mechanism for BRCA1-deficient in TNBC and targeting TRIM47/BRCA1 axis may be a promising prognostic factor and a valuable therapeutic target for TNBC.

SPRR3 Contributes to Aggressiveness of Pancreatic Cancer Cells via NF-κB Signaling Pathway.

Pancreatic cancer remains a deadly solid tumor with worst survival, and a better understanding of the mechanisms of carcinogenesis of pancreatic cancer is critical to promote the survival of patients with pancreatic cancer. qPCR and western blot assay were used to determine the expression of SPRR3 in pancreatic cancer. Anchorage-independent growth ability, BrdU labeling, Transwell assay, and in vivo experiment were used to examine the functions of SPRR3 in aggressiveness of pancreatic cancer. Luciferase reporter assay, nucleoplasmic-separation technique, qPCR, and western blot assay were used to investigate the mechanism of SPRR3 regulating aggressiveness of pancreatic cancer. Our results showed that SPRR3 was significantly increased in pancreatic cancer, which resulted in poor survival for patients with pancreatic cancer. Further analysis showed that overexpression of SPRR3 contributed to anchorage-independent growth ability, growth rate, and invasion ability of pancreatic cancer cells. While, knockdown of SPRR3 showed the reverse results. Mechanistically, overexpression of SPRR3 can promote the transcription of NF-κB pathway, nuclear accumulation of p65, and mRNA levels of NF-κB pathway downstream genes. But, knockdown of SPRR3 induced the reverse results. The above findings clarified the important roles of SPRR3 in the progression of pancreatic cancer through NF-κB pathway. And targeting SPRR3 might be an effective strategy to therapy pancreatic cancer.

BCAT1, as a prognostic factor for HCC, can promote the development of liver cancer through activation of the AKT signaling pathway and EMT.

More and more studies have shown that Branched chain amino acid transaminase 1 (BCAT1) is involved in the occurrence and development of a variety of tumors. However, the mechanism of its occurrence and development in hepatocellular carcinoma (HCC) remains unclear. Here, we demonstrated the relationship between BCAT1 and AKT signaling pathway, as well as EMT, and the clinical significance of BCAT1 by using BCAT1 expression in 5 cell lines and 113 liver cancer and non-liver cancer tissue samples. The results showed that the expression of AKT was positively correlated with BCAT1 in HCC tissues, and BCAT1 could promote the progression of HCC cells through the AKT signaling pathway. Clinical analysis and Bioinformatics technology analysis revealed that BCAT1 was correlated with poor prognosis, and BCAT1 expression in the HCC tissues was evidently correlated with tumor number, vascular invasion, Edmondson grade and TNM stage (P < 0.05). In vitro studies showed that BCAT1 increased the invasion and migration of in MHCC-97H cells a d Huh7 cells. By inhibiting the expression of the BCAT1 gene, we detected the corresponding changes in the expression levels of Twist, E-cadherin and Vimentin, confirming that BCAT1 may promote the invasion and migration of HCC cells through epithelial-mesenchymal transformation (EMT). Overall, BCAT1 can activate AKT signaling pathway and EMT to promote the development and metastasis of HCC cells. this study may provide new ideas and directions for cancer diagnosis and treatment.

Critical Classes and Samples Discovering for Partial Domain Adaptation.

Partial domain adaptation (PDA) attempts to learn transferable models from a large-scale labeled source domain to a small unlabeled target domain with fewer classes, which has attracted a recent surge of interest in transfer learning. Most conventional PDA approaches endeavor to design delicate source weighting schemes by leveraging target predictions to align cross-domain distributions in the shared class space. Accordingly, two crucial issues are overlooked in these methods. First, target prediction is a double-edged sword, and inaccurate predictions will result in negative transfer inevitably. Second, not all target samples have equal transferability during the adaptation; thus, "ambiguous" target data predicted with high uncertainty should be paid more attentions. In this article, we propose a critical classes and samples discovering network (CSDN) to identify the most relevant source classes and critical target samples, such that more precise cross-domain alignment in the shared label space could be enforced by co-training two diverse classifiers. Specifically, during the training process, CSDN introduces an adaptive source class weighting scheme to select the most relevant classes dynamically. Meanwhile, based on the designed target ambiguous score, CSDN emphasizes more on ambiguous target samples with larger inconsistent predictions to enable fine-grained alignment. Taking a step further, the weighting schemes in CSDN can be easily coupled with other PDA and DA methods to further boost their performance, thereby demonstrating its flexibility. Extensive experiments verify that CSDN attains excellent results compared to state of the arts on four highly competitive benchmark datasets.

Metastasis to the Pancreas From Ductal Carcinoma In Situ of Breast Cancer: A Case Report and Review of Literature.

Background: The usual locations of metastatic breast neoplasms include the bones, the liver, the lung, and the brain. Breast cancer rarely metastasizes to the pancreas. However, pancreatic metastasis and primary pancreatic cancer are difficult to differentiate because of their similar clinical features and radiological characteristics. Case presentation: We report on a 49-year-old woman initially diagnosed with left breast ductal carcinoma in June 2008. The patient was admitted to the hospital with jaundice after 12 years. Computed tomography (CT) scan and magnetic resonance imaging (MRI) revealed a mass in the pancreas head. Histopathology and immunohistochemistry showed ductal carcinoma originating from breast cancer. She underwent pancreatoduodenectomy to relieve jaundice. The patient is still alive with a favorable prognosis. Conclusions: In this paper, we mainly discuss the clinical characteristics, diagnostic methods, and surgical treatment of pancreatic metastasis. When a pancreatic lesion is detected with a history of breast cancer, the pancreatic metastasis likely originates from breast cancer.

LINC02273 Promotes Hepatocellular Carcinoma Progression via Retaining ß-Catenin in the Nucleus to Augment Wnt Signaling.

Hepatocellular carcinoma (HCC) is a lethal malignancy whereas the molecular mechanisms remain poorly understood. Recently, long noncoding RNAs (lncRNA) have been shown to regulate HCC progression. However, the involved lncRNAs remain to be fully explored. Here, we showed the expression pattern and biological function of a recently identified lncRNA, LINC02273, in HCC. LINC02273 played a critical role in HCC progression via stabilizing ß-catenin. Knockdown of LINC02237 remarkably inhibited the proliferation, stemness, migration, and invasion abilities, whereas it increased the apoptosis of HCC cells. Overall, we characterized the functions of LINC02273 in HCC and its potential as a novel HCC targeting candidate.

Dipeptidyl peptidase-8 induces sorafenib resistance via binding with c-Rel to mediate NF-κB signaling in hepatocellular carcinoma.

Sorafenib is the important first-standard drug for patients with advanced hepatocellular carcinoma (HCC). A major obstacle to successful treatment is sorafenib resistance. However, the mechanism of sorafenib resistance is unclear. The present study aimed to determine the involvement of dipeptidyl peptidase-8 (DPP8) in sorafenib resistance. DPP8 expression was detected using quantitative real-time PCR (qPCR) and western blot analysis. The effect of DPP8 on sorafenib resistance was examined using terminal deoxynulceotidyl transferase nick-end-labeling (TUNEL), colony formation, flow cytometry, luciferase reporter, immunofluorescence, and immunoprecipitation (IP) assays. We found that DPP8 mRNA and protein levels were dramatically upregulated in HCC. Gene set enrichment analysis (GSEA) illustrated that DPP8 might be involved in apoptosis regulation. Downregulation of DPP8 substantially promoted the sensitivity of HCC cells to sorafenib. Further analysis showed that DPP8 might regulate nuclear factor kappa B (NF-κB) signaling, which was confirmed using a luciferase reporter assay. Downregulation of DPP8 decreased the expression levels of downstream genes of the NF-κB pathway. IP showed that DPP8 can interact with NF-κB subunit c-Rel, an important protein of NF-κB signaling. Finally, a drug combination of sorafenib and Val-boroPro induced higher mortality of HCC cells than sorafenib alone in DPP8-upregulated cells. Our findings indicated that using the inhibitor Val-boroPro might be a promising method to enhance sorafenib sensitivity in advanced HCC.

Generalized Domain Conditioned Adaptation Network.

Domain adaptation (DA) attempts to transfer knowledge learned in the labeled source domain to the unlabeled but related target domain without requiring large amounts of target supervision. Recent advances in DA mainly proceed by aligning the source and target distributions. Despite the significant success, the adaptation performance still degrades accordingly when the source and target domains encounter a large distribution discrepancy. We consider this limitation may attribute to the insufficient exploration of domain-specialized features because most studies merely concentrate on domain-general feature learning in task-specific layers and integrate totally-shared convolutional networks (convnets) to generate common features for both domains. In this paper, we relax the completely-shared convnets assumption adopted by previous DA methods and propose Domain Conditioned Adaptation Network (DCAN), which introduces domain conditioned channel attention module with a multi-path structure to separately excite channel activation for each domain. Such a partially-shared convnets module allows domain-specialized features in low-level to be explored appropriately. Further, given the knowledge transferability varying along with convolutional layers, we develop Generalized Domain Conditioned Adaptation Network (GDCAN) to automatically determine whether domain channel activations should be separately modeled in each attention module. Afterward, the critical domain-specialized knowledge could be adaptively extracted according to the domain statistic gaps. As far as we know, this is the first work to explore the domain-wise convolutional channel activations separately for deep DA networks. Additionally, to effectively match high-level feature distributions across domains, we consider deploying feature adaptation blocks after task-specific layers, which can explicitly mitigate the domain discrepancy. Extensive experiments on four cross-domain benchmarks, including DomainNet, Office-Home, Office-31, and ImageCLEF, demonstrate the proposed approaches outperform the existing methods by a large margin, especially on the large-scale challenging dataset. The code and models are available at https://github.com/BIT-DA/GDCAN.

Amplification of DDR2 mediates sorafenib resistance through NF-κB/c-Rel signaling in hepatocellular carcinoma.

Sorafenib was the first systemic therapy approved by the Food and Drug Administration to treat advanced hepatocellular carcinoma (HCC). However, sorafenib therapy is frequently accompanied by drug resistance. We aimed to explore the mechanisms of sorafenib resistance and provide feasible solutions to increase the response to sorafenib in patients with advanced HCC. The expression profile of discoidin domain receptor 2 (DDR2) in HCC tissues and cells was detected using quantitative real-time PCR (qPCR) and western blotting assays. The effects of DDR2 on sorafenib resistance were examined using 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide, colony formation, TdT-mediated dUTP nick end labeling, and flow cytometry assays. The effect of DDR2 on the nuclear factor kappa B (NF-κB) signaling pathway was evaluated by luciferase reporter, immunofluorescence, qPCR and flow cytometry assays. We demonstrated that DDR2 expression was dramatically upregulated in sorafenib-resistant HCC tissues relative to sensitive tissues. Downregulation of DDR2 sensitized HCC cell lines to sorafenib cytotoxicity. Further analysis showed that DDR2 could increase the nuclear location of REL proto-oncogene, a NF-κB subunit, to mediate NF-κB signaling. Blocking NF-κB signaling using the NF-κB signaling inhibitor, bardoxolone methyl, increased the response of HCC cells to sorafenib. Further analysis showed that DNA amplification of DDR2 is an important mechanism leading to DDR2 overexpression in HCC. Our results demonstrated that DDR2 is a potential therapeutic target in patients with HCC, and targeting DDR2 represents a promising approach to increase sorafenib sensitivity in patients with HCC.

TRIM37 overexpression is associated with chemoresistance in hepatocellular carcinoma via activating the AKT signaling pathway.

BACKGROUND: Hepatocellular carcinoma (HCC) is the most common primary liver cancer in the worldwide. Sorafenib is approved for first-line therapy against advanced HCC, but chemo-resistance is still a leading cause of tumor relapse and treatment failure in HCC. Thus, there is a significant clinical need to identify effective strategies to overcome drug resistance on the disease. METHODS: The protein and mRNA expression of TRIM37 in HCC cell lines and patient tissues were determined using Real-time PCR and Western blot, respectively. HCC tissue samples were analyzed by IHC to investigate the association between TRIM37expression and the clinicopathological characteristics of HCC patients. Functional assays, such as MTT, FACS, and Tunel assay, are used to determine the oncogenic role of TRIM37 in human HCC progression. Furthermore, western blotting and luciferase assay were used to determine the mechanism of TRIM37promotes chemoresistance in HCC. RESULTS: We found that both the mRNA and protein expression of TRIM37 was markedly upregulated in HCC cell lines and tissues, especially in Sorafenib-resistance HCC tissues. Moreover, high TRIM37 expression was associated with poor prognosis with HCC patients. TRIM37 overexpression confers Sorafenib resistance on HCC cells; however, inhibition of TRIM37 sensitized HCC cell lines to Sorafenib cytotoxicity. Additionally, TRIM37 upregulated the levels of AKT activity and phosphorylated AKT, thereby activating canonical AKT signaling. CONCLUSION: Our findings suggest that targeting TRIM37 signaling may represent a promising strategy to enhance Sorafenib response in HCC patients with chemoresistant.

MYB Proto-oncogene-like 1-TWIST1 Axis Promotes Growth and Metastasis of Hepatocellular Carcinoma Cells.

MYB proto-oncogene-like 1 (MYBL1) has been reported to be a strong activator of transcription and plays an important role in the development of cancer. However, the precise biological function and molecular mechanism of MYBL1 in hepatocellular carcinoma (HCC) cells remain unclear. In the present study, we found that the expression of MYBL1 was markedly overexpressed in HCC cell lines and HCC samples, respectively. Moreover, MYBL1 expression positively correlated with tumor progression and inversely correlated with patient survival in 368 human HCC tissue samples. Overexpression of MYBL1 induced, whereas knockdown of MYBL1 reduced, HCC proliferation and metastasis both in vitro and in vivo. Furthermore, we demonstrated that HCC patients with high MYBL1 expression had significantly shorter overall and poorer disease-free survival than those with low MYBL1 expression. MYBL1 transcriptionally upregulated TWIST1 expression by directly targeting the TWIST1 promoter. More importantly, the in vitro analysis was consistent with the significant correlation between MYBL1 and TWIST1 expression observed in a large cohort of human HCC specimens. Taken together, our results demonstrate that MYBL1 plays an important role in HCC growth and metastasis and reveal a plausible mechanism for upregulation of TWIST1 in HCC.

Discriminative Transfer Feature and Label Consistency for Cross-Domain Image Classification.

Visual domain adaptation aims to seek an effective transferable model for unlabeled target images by benefiting from the well-labeled source images following different distributions. Many recent efforts focus on extracting domain-invariant image representations via exploring target pseudo labels, predicted by the source classifier, to further mitigate the conditional distribution shift across domains. However, two essential factors are overlooked by most existing methods: 1) the learned transferable features should be not only domain invariant but also category discriminative; and 2) the target pseudo label is a two-edged sword to cross-domain alignment. In other words, the wrongly predicted target labels may hinder the class-wise domain matching. In this article, to address these two issues simultaneously, we propose a discriminative transfer feature and label consistency (DTLC) approach for visual domain adaptation problems, which can naturally unify cross-domain alignment with discriminative information preserved and label consistency of source and target data into one framework. To be specific, DTLC first incorporates class discriminative information by penalizing the maximum distance of data pair in the same class and the minimum distance of data pair sharing the different labels for each data into the distribution alignment of both domains. The target pseudo labels are then refined based on the label consistency within the domains. Thus, the transfer feature learning and coarse-to-fine target labels would be coupled to benefit each other in an iterative way. Comprehensive experiments on several visual cross-domain benchmarks verify that DTLC can gain remarkable margins over state-of-the-art (SOTA) nondeep visual domain adaptation methods and even be comparable to competitive deep domain adaptation ones.

Correction to: Minichromosome maintenance 3 promotes hepatocellular carcinoma radioresistance by activating the NF-κB pathway.

In the original publication of this article [1], the Fig. 7 is wrong, but does not affect discussions and conclusions drawn in the article.

Correction to: Minichromosome maintenance 3 promotes hepatocellular carcinoma radioresistance by activating the NF-κB pathway.

In the original publication of this article [1], the authors reported the order of the authors was incorrect and needs to be revised. The original article has been updated to rectify this error.