BERT4ETH: A Pre-trained Transformer for Ethereum Fraud Detection

As various forms of fraud proliferate on Ethereum, it is imperative to safeguard against these malicious activities to protect susceptible users from being victimized. While current studies solely rely on graph-based fraud detection approaches, it is argued that they may not be well-suited for dealing with highly repetitive, skew-distributed and heterogeneous Ethereum transactions. To address these challenges, we propose BERT4ETH, a universal pre-trained Transformer encoder that serves as an account representation extractor for detecting various fraud behaviors on Ethereum. BERT4ETH features the superior modeling capability of Transformer to capture the dynamic sequential patterns inherent in Ethereum transactions, and addresses the challenges of pre-training a BERT model for Ethereum with three practical and effective strategies, namely repetitiveness reduction, skew alleviation and heterogeneity modeling. Our empirical evaluation demonstrates that BERT4ETH outperforms state-of-the-art methods with significant enhancements in terms of the phishing account detection and de-anonymization tasks. The code for BERT4ETH is available at: https://github.com/git-disl/BERT4ETH.Comment: the Web conference (WWW) 202

Attention-Block Deep Learning Based Features Fusion in Wearable Social Sensor for Mental Wellbeing Evaluations

With the progressive increase of stress, anxiety and depression in working and living environment, mental health assessment becomes an important social interaction research topic. Generally, clinicians evaluate the psychology of participants through an effective psychological evaluation and questionnaires. However, these methods suffer from subjectivity and memory effects. In this paper, a new multi- sensing wearable device has been developed and applied in self-designed psychological tests. Speech under different emotions as well as behavior signals are captured and analyzed. The mental state of the participants is objectively assessed through a group of psychological questionnaires. In particular, we propose an attention-based block deep learning architecture within the device for multi-feature classification and fusion analysis. This enables the deep learning architecture to autonomously train to obtain the optimum fusion weights of different domain features. The proposed attention-based architecture has led to improving performance compared with direct connecting fusion method. Experimental studies have been carried out in order to verify the effectiveness and robustness of the proposed architecture. The obtained results have shown that the wearable multi-sensing devices equipped with the attention-based block deep learning architecture can effectively classify mental state with better performance

Stevioside Prevents Wear Particle-Induced Osteolysis by Inhibiting Osteoclastogenesis and Inflammatory Response via the Suppression of TAK1 Activation

Aseptic loosening and periprosthetic osteolysis are the leading causes of total joint arthroplasty failure, which occurs as a result of chronic inflammatory response and enhanced osteoclast activity. Here we showed that stevioside, a natural compound isolated from Stevia rebaudiana, exhibited preventative effects on titanium particle-induced osteolysis in a mouse calvarial model. Further histological assessment and real-time PCR analysis indicated that stevioside prevented titanium particle-induced osteolysis by inhibiting osteoclast formation and inflammatory cytokine expression in vivo. In vitro, we found that stevioside could suppress RANKL-induced osteoclastogenesis and titanium particle-induced inflammatory response in a dose-dependent manner. Mechanistically, stevioside achieved these effects by disrupting the phosphorylation of TAK1 and subsequent activation of NF-κB/MAPKs signaling pathways. Collectively, our data suggest that stevioside effectively suppresses osteoclastogenesis and inflammatory response both in vitro and in vivo, and it might be a potential therapy for particle-induced osteolysis and other osteolytic diseases

A dZnONPs Enhanced Hybrid Injectable Photocrosslinked Hydrogel for Infected Wounds Treatment

Chronic wounds caused by related diseases such as ischemia, diabetes, and venous stasis are often hard to manage, mainly because of their susceptibility to infection and the lack of healing-promoting growth factors. Functional hydrogel is a promising material for wound treatment due to its regulable swelling rate and its ability to absorb wound exudate, which can keep the wound isolated from the outside world to prevent infection. In this study, a photocrosslinked physicochemical double-network hydrogel with injectable, antibacterial, and excellent mechanical properties was prepared. The dZnONPs enhanced hybrid injectable photocrosslinked double-network hydrogel (Ebs@dZnONPs/HGT) was synthetized starting from acylated hyaluronic acid and tannic acid via free radical reaction and hydrogen bonding, following doped with ebselen (Ebs) loaded dendritic zinc oxide nanoparticles (dZnONPs) to prepare the Ebs@dZnONPs/HGT hydrogel. The physicochemical characterization confirmed that the Ebs@dZnONPs/HGT hydrogel had excellent mechanical properties, hydrophilicity, and injectable properties, and could fit irregular wounds well. In vitro experiments revealed that the Ebs@dZnONPs/HGT hydrogel presented credible cytocompatibility and prominent antibacterial activity against Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus). In vivo experiments further demonstrated that the Ebs@dZnONPs/HGT hydrogel had excellent biosafety and could improve re-epithelialization in the wound area, thus significantly accelerating wound healing

SPP1 is associated with adverse prognosis and predicts immunotherapy efficacy in penile cancer

Abstract Background The effect of SPP1 in squamous cell carcinoma of the penis (PSCC) remained unknown. We attempted to clarify the function of the SPP1 gene in PSCC. Method Eight paired penile cancer specimens (including penile cancer tissue, paracancerous tissue, and positive lymph node tissue) subjected to whole transcriptome sequencing were analysed to identify differentially expressed genes. We used immunohistochemistry to detect the expression of SPP1 protein and immune cell related proteins in penile cancer tissue. Then, we performed weighted gene coexpression network analysis (WGCNA) to identify the genes related to SPP1 in penile cancer tissue and positive lymph node tissue. Based on the GSE57955 dataset, the CIBERSORT and ssGSEA algorithms were carried out to investigate the immune environment of PSCC. GSVA analysis was conducted to identify the signaling pathways related to SPP1 subgroups. Enzyme-linked immunosorbent assay (ELISA) method was adopted to detect SPP1 level in the serum of 60 patients with penile cancer. Results Differential analysis indicated that SPP1 was the most differentially upregulated gene in both penile cancer tissues and positive lymph node tissues. Survival analysis suggested that the prognosis of the low-SPP1 group was significantly poorer than that of the high-SPP1 group. Subsequently, immune-related bioinformatics showed that SPP1 was significantly associated with B cells, CD8 + T cells, CD4 + T cells, macrophages, helper T cells, neutrophils and dendritic cells. The immunohistochemical results showed that the high-SPP1 group was characterized by relatively high expression of CD16 and relatively low expression of CD4. GSVA analysis indicated that high-SPP1 group was significantly associated with immune-related pathways such as PD-L1 expression and the PD-1 checkpoint pathway in cancer and the TNF signaling pathway. ELISA demonstrated that the serum level of SPP1 in patients with positive lymph node metastasis of penile cancer was significantly higher than that in patients with negative lymph node metastasis of penile cancer. Conclusion Our study shows that the SPP1 gene might be an effective biomarker for predicting the prognosis and the efficacy of immunotherapy in PSCC patients

RAB20 Promotes Proliferation via G2/M Phase through the Chk1/cdc25c/cdc2-cyclinB1 Pathway in Penile Squamous Cell Carcinoma

RAB20, a member of the RAS GTPase oncogene family, is overexpressed in several cancers with poor outcomes, promoting tumorigenesis and inducing genomic instability. Here, we performed comprehensive genomic sequencing on eight penile squamous cell carcinoma (PSCC) and normal tissue pairs and found that RAB20 was upregulated in tumors, especially in metastatic lymph nodes. RAB20 overexpression in tumors was further verified by qPCR, Western blotting, and immunohistochemistry of our newly established PSCC cell lines and paired tissues. The clinical significance of RAB20 was validated in 259 PSCC patients, the largest cohort to date, and high RAB20 expression positively correlated with the T, N, M status, extranodal extension, and clinical stage (all p p = 0.011, HR = 2.090; 95% Cl: 1.183–4.692), and PSCC patients with high RAB20 expression experienced shorter 5-year cancer-specific survival times (p < 0.001). Furthermore, tumorigenesis assays demonstrated that RAB20 knockdown inhibited cell proliferation, migration, and colony formation in vitro and tumor growth in vivo. RAB20 depletion also induced PSCC cell cycle arrest at G2/M by increasing Chk1 expression and promoting cdc25c phosphorylation to reduce cdc2-cyclinB1 complex formation. Our study revealed an oncogenic role for RAB20 in promoting PSCC cell proliferation at the G2/M phase via the Chk1/cdc25c/cdc2-cyclinB1 pathway. Thus, RAB20 could be a promising prognostic biomarker of advanced PSCC with poor patient survival outcomes and could be a potential therapeutic target

Image2_Immune-related gene risk score predicting the effect of immunotherapy and prognosis in bladder cancer patients.TIF

Background: Immune checkpoint inhibitor therapy has changed the treatment model of metastatic bladder cancer. However, only approximately 20% of patients benefit from this therapy, and robust biomarkers to predict the effect of immunotherapy are still lacking. In this study, we aimed to investigate whether immune-related genes could be indicators for the prognosis of bladder cancer patients and the effect of immunotherapy.Methods: Based on bladder cancer dataset from the Cancer Genome Atlas (TCGA) and GSE48075, 22 immune microenvironment-related cells were identified by CIBERSORT. After performing a series of bioinformatic and machine learning approaches, we identified distinct tumor microenvironment clusters and three bladder cancer specific immune-related genes (EGFR, OAS1 and MST1R). Then, we constructed immune-related gene risk score (IRGRS) by using the Cox regression method and validated it with the IMvigor210 dataset.Results: IRGRS-high patients had a worse overall survival than IRGRS-low patients, which was consistent with the result in the IMvigor210 dataset. Comprehensive analysis shows that patients with high IRGRS scores are mainly enriched in basal/squamous type (Ba/Sq), and tumor metabolism-related pathways are more Active, with higher TP53 and RB1 gene mutation rates, lower CD4+/CD8+ T cell infiltration, higher M0 macrophage infiltration, and lower immunotherapy efficacy. In contrast, Patients with low IRGRS scores are mainly enriched in the luminal papillary type (LumP), which is associated with the activation of IL-17 and TNF signaling pathways, higher mutation rates of FGFR3 and CDKN1A genes, higher CD4+/CD8+ T cell infiltration content, and The level of M0 macrophage infiltration was relatively low, and the immunotherapy was more probably effective.Conclusion: Our study constructed an IRGRS for bladder cancer and clarified the immune and molecular characteristics of IRGRS-defined subgroups of bladder cancer to investigate the association between IRGRS and its potential implications for prognosis and immunotherapy.</p

Table1_Immune-related gene risk score predicting the effect of immunotherapy and prognosis in bladder cancer patients.XLS

Background: Immune checkpoint inhibitor therapy has changed the treatment model of metastatic bladder cancer. However, only approximately 20% of patients benefit from this therapy, and robust biomarkers to predict the effect of immunotherapy are still lacking. In this study, we aimed to investigate whether immune-related genes could be indicators for the prognosis of bladder cancer patients and the effect of immunotherapy.Methods: Based on bladder cancer dataset from the Cancer Genome Atlas (TCGA) and GSE48075, 22 immune microenvironment-related cells were identified by CIBERSORT. After performing a series of bioinformatic and machine learning approaches, we identified distinct tumor microenvironment clusters and three bladder cancer specific immune-related genes (EGFR, OAS1 and MST1R). Then, we constructed immune-related gene risk score (IRGRS) by using the Cox regression method and validated it with the IMvigor210 dataset.Results: IRGRS-high patients had a worse overall survival than IRGRS-low patients, which was consistent with the result in the IMvigor210 dataset. Comprehensive analysis shows that patients with high IRGRS scores are mainly enriched in basal/squamous type (Ba/Sq), and tumor metabolism-related pathways are more Active, with higher TP53 and RB1 gene mutation rates, lower CD4+/CD8+ T cell infiltration, higher M0 macrophage infiltration, and lower immunotherapy efficacy. In contrast, Patients with low IRGRS scores are mainly enriched in the luminal papillary type (LumP), which is associated with the activation of IL-17 and TNF signaling pathways, higher mutation rates of FGFR3 and CDKN1A genes, higher CD4+/CD8+ T cell infiltration content, and The level of M0 macrophage infiltration was relatively low, and the immunotherapy was more probably effective.Conclusion: Our study constructed an IRGRS for bladder cancer and clarified the immune and molecular characteristics of IRGRS-defined subgroups of bladder cancer to investigate the association between IRGRS and its potential implications for prognosis and immunotherapy.</p