A new constrained mKP hierarchy and the generalized Darboux transformation for the mKP equation with self-consistent sources

The mKP equation with self-consistent sources (mKPESCS) is treated in the framework of the constrained mKP hierarchy. We introduce a new constrained mKP hierarchy which may be viewed as the stationary hierarchy of the mKP hierarchy with self-consistent sources. This offers a natural way to obtain the Lax representation for the mKPESCS. Based on the conjugate Lax pairs, we construct the generalized Darboux transformation with arbitrary functions in time $t$ for the mKPESCS which, in contrast with the Darboux transformation for the mKP equation, provides a non-auto-B\"{a}cklund transformation between two mKPESCSs with different degrees. The formula for $n$-times repeated generalized Darboux transformation is proposed and enables us to find the rational solutions (including the lump solutions), soliton solutions and the solutions of breather type of the mKPESCS.Comment: 23 pages, no figures. to appeare in Physica

DDX5 facilitates HIV-1 replication as a cellular co-factor of Rev.

HIV-1 Rev plays an important role in the late phase of HIV-1 replication, which facilitates export of unspliced viral mRNAs from the nucleus to cytoplasm in infected cells. Recent studies have shown that DDX1 and DDX3 are co-factors of Rev for the export of HIV-1 transcripts. In this report, we have demonstrated that DDX5 (p68), which is a multifunctional DEAD-box RNA helicase, functions as a new cellular co-factor of HIV-1 Rev. We found that DDX5 affects Rev function through the Rev-RRE axis and subsequently enhances HIV-1 replication. Confocal microscopy and co-immunoprecipitation analysis indicated that DDX5 binds to Rev and this interaction is largely dependent on RNA. If the DEAD-box motif of DDX5 is mutated, DDX5 loses almost all of its ability to bind to Rev, indicating that the DEAD-box motif of DDX5 is required for the interaction between DDX5 and Rev. Our data indicate that interference of DDX5-Rev interaction could reduce HIV-1 replication and potentially provide a new molecular target for anti-HIV-1 therapeutics

Rhamnazin Inhibits Malignant Progression of ProstateCancer Cells via DPP4/JAK/STAT Signaling Pathway

Background: Rhamnazin is a natural dimethoxyflavonoid compound and Rhamnazin has been reported to have antitumor activity. This work is performed to study the function of Rhamnazin in prostate cancer (PCa) cells and its mechanism. Methods: Rhamnazin (20 µM) was used to treat 22Rv1 and C4-2B cells, and the cells treated with dimethyl sulfoxide (DMSO) were set as the control group. To investigate the role of dipeptidyl peptidase 4 (DPP4) in mediating the biological effects of Rhamnazin, DPP4 overexpression plasmids were transfected into the PCa cell lines. Cell counting kit-8 method was employed to detect the proliferation; apoptosis and cell cycle were detected by flow cytometry. the target genes of Rhamnazin were predicted in Traditional Chinese Medicine Systems Pharmacology (TCMSP) database. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis of target genes of Rhamnazin was performed using the Database for Annotation, Visualization and Integrated Discovery (DAVID database). Human Protein Atlas database was utilized to identify genes associated with poor PCa prognosis. GEPIA database was used to validate the expression and prognosis of DPP4 in PCa. The LinkedOmics database was used to analyze the signaling pathway related to DPP4 in PCa. Quantitative polymerase chain reaction was performed to detect DPP4 mRNA levels. Western blot assays were performed to detect the expression levels of DPP4, phosphorylated (p-) Janus kinase 1 (JAK1) and p-signal transducer and activator of transcription 3 (STAT3). Results: Functional assays confirmed that Rhamnazin inhibited the proliferation of PCa cells (p < 0.05), and promoted apoptosis (p < 0.05) and blocked the cell cycle progression (p < 0.05). In addition, Rhamnazin significantly inhibited the expression of DPP4 (p < 0.05), and up-regulating DPP4 reversed the effects of Rhamnazin (p < 0.05). It was further found that DPP4 was associated with JAK/STAT signaling and Rhamnazin inhibited the expression of p-JAK1 (p < 0.05) and p-STAT3 (p < 0.05) through DPP4. Conclusion: Rhamnazin has the potential to kill PCa cells via DPP4/JAK/STAT axis

Future organizational identification: Visionary leadership gives me foresight to identify with my organization in the future

This research introduces the concept of future organizational identification (FOI), an extension of organizational identification (OI) that emphasizes its forward-looking aspect. FOI refers to an individual's projection of their self-definition based on the continuity of their organizational membership. Drawing on construal level theory (CLT) and a future-oriented approach, this research investigates how visionary leadership, which offers vision communication and vision of continuity, may enhance followers' FOI through future focus. Study 1, comprising Studies 1a and 1b, validates the measurement of FOI in workplace contexts. With a three-wave, time-lagged investigation, Study 2 demonstrates that leaders' vision communication fosters followers' FOI by promoting future focus, and vision of continuity positively moderates this mediation effect. These findings advance literature on organizational identification, visionary leadership, and CLT. We conclude by discussing the theoretical and practical implications of our findings and proposing directions for future research

Risk prediction of product-harm events using rough sets and multiple classifier fusion:an experimental study of listed companies in China

With the increasing of frequency and destructiveness of product-harm events, study on enterprise crisis management becomes essentially important, but little literature thoroughly explores the risk prediction method of product-harm event. In this study, an initial index system for risk prediction was built based on the analysis of the key drivers of the product-harm event's evolution; ultimately, nine risk-forecasting indexes were obtained using rough set attribute reduction. With the four indexes of cumulative abnormal returns as the input, fuzzy clustering was used to classify the risk level of a product-harm event into four grades. In order to control the uncertainty and instability of single classifiers in risk prediction, multiple classifier fusion was introduced and combined with self-organising data mining (SODM). Further, an SODM-based multiple classifier fusion (SB-MCF) model was presented for the risk prediction related to a product-harm event. The experimental results based on 165 Chinese listed companies indicated that the SB-MCF model improved the average predictive accuracy and reduced variation degree simultaneously. The statistical analysis demonstrated that the SB-MCF model significantly outperformed six widely used single classification models (e.g. neural networks, support vector machine, and case-based reasoning) and other six commonly used multiple classifier fusion methods (e.g. majority voting, Bayesian method, and genetic algorithm)