Sensitivity Analysis of Incentive Situations and Personal Attributes to Driving Anger Based on MNL Model: A Naturalistic Experimental Study

Driving anger, called "road rage", has gradually become universal phenomenon nowadays, which has been a concern to traffic management authorities. It is necessary to figure out impacting degree of the influencing factors on driving anger for taking the corresponding intervening measures. Forty drivers were enrolled to conduct naturalistic experiments on a busy route in Wuhan, China, where drivers\u27 anger can be induced by various incentive situations including jaywalking, weaving/cutting in line, traffic congestion and red light with extra paid if completing the experiment ahead of reference time. According to behavioral theory and disaggregation theory, the influencing factors including the incentive situations and personal attributes (i.e. gender, age, temperament) were determined for proposing driving anger prediction model based on MNL (multinomial logit). Then, the sensitivity of each influencing factor on driving anger was analyzed by elasticity theory on the basis of the proposed model. The result indicates that age, temperament and illegal behaviors from surrounding people are decisive influencing factors to driving anger sates with different intensity because their average elasticity values for none anger (neutral), low anger, medium anger, high anger are 1.254, 2.713, 2.914, respectively, which are all bigger than 1. Moreover, the accuracy of the proposed model is 78.30%. The results can provide theoretical support for developing key monitoring or targeted intervention to deal with the decisive influencing factors for traffic management authorities

Impact of Temperament Types and Anger Intensity on Drivers\u27 EEG Power Spectrum and Sample Entropy: An On-road Evaluation Toward Road Rage Warning

"Road rage", also called driving anger, is becoming an increasingly common phenomenon affecting road safety in auto era as most of previous driving anger detection approaches based on physiological indicators are often unreliable due to the less consideration of drivers\u27 individual differences. This study aims to explore the impact of temperament types and anger intensity on drivers\u27 EEG characteristics. Thirty-two drivers with valid license were enrolled to perform on-road experiments on a particularly busy route on which a variety of provoking events like cutting in line of surrounding vehicle, jaywalking, occupying road of non-motor vehicle and traffic congestion frequently happened. Then, muti-factor analysis of variance (ANOVA) and post hoc analysis were utilized to study the impact of temperament types and anger intensity on drivers\u27 power spectrum and sample entropy of θ and β waves extracted from EEG signals. The study results firstly indicated that right frontal region of the brain has close relationship with driving anger. Secondly, there existed significant main effects of temperament types on power spectrum and sample entropy of β wave while significant main effects of anger intensity on power spectrum and sample entropy of θ and β wave were all observed. Thirdly, significant interactions between temperament types and anger intensity for power spectrum and sample entropy of β wave were both noted. Fourthly, with the increase of anger intensity, the power spectrum and sample entropy both decreased sufficiently for θ wave while increased remarkably for β wave. The study results can provide a theoretical support for designing a personalized and hierarchical warning system for road rage

PNMBG: Point Neighborhood Merging with Border Grids

The special clustering algorithm is attractive for the task of grouping arbitrary shaped database into several proper classes. Up to now, a wide variety of clustering algorithms designed for this task have been proposed, the majority of these algorithms is density-based. But the effectivity and efficiency still is the great challenges for these algorithms as far as the clustering quality of such task is concerned. In this paper, we propose an arbitrary shaped clustering method with border grids (PNMBG), PNMBG is a crisp partition method. It groups objects to point neighborhoods firstly, and then iteratively merges these point neighborhoods into clusters via grids, only bordering grids are considered during the merging stage. Experiments show that PNMBG has a good efficiency especially on the database with high dimension. In general, PNMBG outperforms DBSCAN in the term of efficiency and has an almost same effectivity with the later

DNA damage-induced activation of ATM promotes β-TRCP-mediated Mdm2 ubiquitination and destruction

The Mdm2 oncoprotein promotes p53 ubiquitination and destruction. Yet, exact molecular mechanisms of Mdm2 destruction itself, under DNA damaging conditions, remain unclear. Recently, we identified SCFβ-TRCP as a novel E3 ligase that targets Mdm2 for ubiquitination and destruction in a Casein Kinase Iδ (CKIδ)-dependent manner. However, it remains elusive how the β-TRCP/CKIδ/Mdm2 signaling axis is regulated by DNA damage signals to govern p53 activity. Consistent with previous studies, we found that inactivation of the Ataxia Telangiectasia Mutated (ATM) kinase, in turn, impaired DNA damage-induced Mdm2 destruction. Although phosphorylation of Mdm2 at Ser395 (an ATM phosphorylation site) facilitated Mdm2 interaction with β-TRCP, Ser395A-Mdm2 was degraded non-distinguishably from WT-Mdm2 by SCFβ-TRCP upon DNA damaging treatments. This indicates that in addition to phosphorylating Mdm2 at Ser395, ATM may govern Mdm2 stability through other unknown mechanisms. We further demonstrated that DNA damage-induced activation of ATM directly phosphorylated CKIδ at two well-conserved S/TQ sites, which promotes CKIδ nuclear localization to increase CKIδ-mediated phosphorylation of Mdm2, thereby facilitating subsequent Mdm2 ubiquitination by SCFβ-TRCP. Our studies provide a molecular mechanism of how ATM could govern DNA damage-induced destruction of Mdm2 in part by phosphorylating both Mdm2 and CKIδ to modulate SCFβ-TRCP–mediated Mdm2 ubiquitination. Given the pivotal role of Mdm2 in the negative regulation of p53, this work will also provide a rationale for developing CKIδ or ATM agonists as anti-cancer agents

SCFβ-TRCP-mediated degradation of NEDD4 inhibits tumorigenesis through modulating the PTEN/Akt signaling pathway

The HECT domain-containing ubiquitin E3 ligase NEDD4 is widely expressed in mammalian tissues and plays a crucial role in governing a wide spectrum of cellular processes including cell growth, tissue development and homeostasis. Recent reports have indicated that NEDD4 might facilitate tumorigenesis through targeted degradation of multiple tumor suppressor proteins including PTEN. However, the molecular mechanism by which NEDD4 stability is regulated has not been fully elucidated. Here we report that SCFβ-TRCP governs NEDD4 protein stability by targeting it for ubiquitination and subsequent degradation in a Casein Kinase-I (CKI) phosphorylation-dependent manner. Specifically, depletion of β-TRCP, or inactivation of CKI, stabilized NEDD4, leading to down-regulation of its ubiquitin target PTEN and subsequent activation of the mTOR/Akt oncogenic pathway. Furthermore, we found that CKIδ-mediated phosphorylation of Ser347 and Ser348 on NEDD4 promoted its interaction with SCFβ-TRCP for subsequent ubiquitination and degradation. As a result, compared to ectopic expression of wild-type NEDD4, introducing a non-degradable NEDD4 (S347A/S348A-NEDD4) promoted cancer cell growth and migration. Hence, our findings revealed the CKI/SCFβ-TRCP signaling axis as the upstream negative regulator of NEDD4, and further suggested that enhancing NEDD4 degradation, presumably with CKI or SCFβ-TRCP agonists, could be a promising strategy for treating human cancers

PNMBG: Point Neighborhood Merging with Border Grids

The special clustering algorithm is attractive for the task of grouping arbitrary shaped database into several proper classes. Up to now, a wide variety of clustering algorithms designed for this task have been proposed, the majority of these algorithms is density-based. But the effectivity and efficiency still is the great challenges for these algorithms as far as the clustering quality of such task is concerned. In this paper, we propose an arbitrary shaped clustering method with border grids (PNMBG), PNMBG is a crisp partition method. It groups objects to point neighborhoods firstly, and then iteratively merges these point neighborhoods into clusters via grids, only bordering grids are considered during the merging stage. Experiments show that PNMBG has a good efficiency especially on the database with high dimension. In general, PNMBG outperforms DBSCAN in the term of efficiency and has an almost same effectivity with the later

SCFβ-TRCP targets MTSS1 for ubiquitination-mediated destruction to regulate cancer cell proliferation and migration

Metastasis suppressor 1 (MTSS1) is an important tumor suppressor protein, and loss of MTSS1 expression has been observed in several types of human cancers. Importantly, decreased MTSS1 expression is associated with more aggressive forms of breast and prostate cancers, and with poor survival rate. Currently, it remains unclear how MTSS1 is regulated in cancer cells, and whether reduced MTSS1 expression contributes to elevated cancer cell proliferation and migration. Here we report that the SCFβ-TRCP regulates MTSS1 protein stability by targeting it for ubiquitination and subsequent destruction via the 26S proteasome. Notably, depletion of either Cullin 1 or β-TRCP1 led to increased levels of MTSS1. We further demonstrated a crucial role for Ser322 in the DSGXXS degron of MTSS1 in governing SCFβ-TRCP-mediated MTSS1 degradation. Mechanistically, we defined that Casein Kinase Iδ (CKIδ) phosphorylates Ser322 to trigger MTSS1's interaction with β-TRCP for subsequent ubiquitination and degradation. Importantly, introducing wild-type MTSS1 or a non-degradable MTSS1 (S322A) into breast or prostate cancer cells with low MTSS1 expression significantly inhibited cellular proliferation and migration. Moreover, S322A-MTSS1 exhibited stronger effects in inhibiting cell proliferation and migration when compared to ectopic expression of wild-type MTSS1. Therefore, our study provides a novel molecular mechanism for the negative regulation of MTSS1 by β-TRCP in cancer cells. It further suggests that preventing MTSS1 degradation could be a possible novel strategy for clinical treatment of more aggressive breast and prostate cancers

Skp2 is a Promising Therapeutic Target in Breast Cancer

Breast cancer is the most common type of cancer among American women, and remains the second leading cause of cancer-related death for female in the United States. It has been known that several signaling pathways and various factors play critical roles in the development and progression of breast cancer, such as estrogen receptor, Notch, PTEN, human epidermal growth factor receptor 2, PI3K/Akt, BRCA1, and BRCA2. Emerging evidence has shown that the F-box protein S-phase kinase associated protein 2 (Skp2) also plays an important role in the pathogenesis of breast cancer. Therefore, in this brief review, we summarize the novel functions of Skp2 in the pathogenesis of breast cancer. Moreover, we provide further evidence regarding the state of our knowledge toward the development of novel Skp2 inhibitors especially natural “chemopreventive agents” as targeted approach for the prevention and/or treatment of breast cancer

Bibliometric and visual analysis of neutrophil extracellular traps from 2004 to 2022

BackgroundNeutrophil extracellular traps (NETs) are specialized structures formed by neutrophils that were initially found to be important in killing pathogenic bacteria during infection. With the development of related research, the relationship between NETs and diseases such as sepsis, cancer, and systemic lupus erythematosus has received close attention. However, there is a lack of reports that comprehensively and objectively present the current status of NETs-related studies. Therefore, this study aims to visually analyze the current status and trends of NETs-related research by means of bibliometrics and knowledge mapping.MethodsNETs-related articles and reviews were retrieved using the Web of Science core collection subject search, and bibliometric analysis was performed in Excel 365, CiteSpace, VOSviewer, and Bibliometrix (R-Tool of R-Studio).ResultsA total of 4866 publications from 2004 to 2022 were included in the bibliometric analysis. The number of publications shows an increasing trend from year to year. Collaborative network analysis shows that the United States and Germany are the most influential countries in this field, with the highest number of publications and citations. The journal with the most publications is Frontiers in Immunology. Brinkmann Volker is an authoritative author in this field, and his publication “Neutrophil extracellular traps kill bacteria” is the most frequently cited. The literature and keyword analysis shows that the relationship between NETs and diseases (hematological diseases, sepsis, cancer, etc.) and cell death (apoptosis, necroptosis, pyroptosis, etc.) is a popular research topic. Currently, NETs and SARS-CoV-2-related studies are at the forefront of the field.ConclusionThis study is the first to visualize the research in NETs-related fields using bibliometric methods, revealing the trends and frontiers of NETs research. This study will provide valuable references for scholars to find research focus questions and partners