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Background: Bile duct leaks (BDLs) are serious complications that occurs after hepatobiliary surgery and trauma, leading to rapid clinical deterioration. Endoscopic retrograde cholangiopancreatography (ERCP) is the first-line treatment for BDLs, but it is not clear which patients will respond to this therapy and which patients will require additional surgical intervention. The aim of our study was to explore the predictors of successful ERCP for BDLs. Methods: A retrospective analysis was conducted using data from six centers' databases. All consecutive patients who were clinically confirmed as BDLs were included in the study. Collected data were demographics, disease severity, and ERCP procedure characteristics. Univariate and multivariate analysis were used to select independent predictive factors that affect the outcome of ERCP for BDLs, and a nomogram was established. Calibration and ROC curves were used to evaluate the models. Results: Four hundred and forty-eight consecutive patients were clinically confirmed as BDLs and 347 were excluded. In the 101 patients included patients, clinical success was achieved in 78 patients (77.2%). In logistic multivariable regression, two independent factors were negatively associated with the success of ERCP: SIRS (OR, 0.183; 95% CI 0.039–0.864; P = 0.032) and high-grade leak (OR 0.073; 95% CI 0.010–0.539; P = 0.010). Two independent factors were positively associated with the success of ERCP: leak-bridging drainage (OR 4.792; 95% CI 1.08–21.21; P = 0.039) and cystic duct leak (OR 6.193; 95% CI 1.03–37.17; P = 0.046). The prediction model with these four factors was evaluated using a receiver-operating characteristic (ROC) curve, which demonstrated an area under the curve of 0.9351. The calibration curve showed that the model had good predictive accuracy. Conclusion: Leak-bridging drainage and cystic duct leak are positive predictors for the success of ERCP, while SIRS and high-grade leak are negative predictors. This prediction model with nomogram has good predictive ability and practical clinical value, and may be helpful in clinical decision-making and prognostication. [ABSTRACT FROM AUTHOR]

Bemisia tabaci is a pest that poses a significant threat to the survival of Nicotiana tabacum and leads to decreased production and economic losses. However, it is still unknown whether proteomic changes occur in resistant N. tabacum in response to B. tabaci stresses. In the present study, iTRAQ was performed to unmask the regulating networks mediated by candidate proteins involved in resistance against B. tabaci. A total of 357 differentially accumulated proteins (DAPs) responsible for B. tabaci infestation were identified, including 178 upregulated and 179 downregulated proteins. The majority of DAPs were involved in the regulation of ROS production, cell expansion, citrate cycle (TCA cycle), photosynthesis, carbon fixation, and metabolic pathways. Moreover, the expression patterns of several genes encoding DAPs were validated by qRT-PCR. Our results indicate these proteins play a significant role in the resistance of N. tabacum against B. tabaci infestation. These findings also provide a valuable proteomic resource for the elucidation of the mechanism of resistance against B. tabaci. [ABSTRACT FROM AUTHOR]

Sybil attack can counterfeit traffic scenario by sending false messages with multiple identities, which often causes traffic jams and even leads to vehicular accidents in vehicular ad hoc network (VANET). It is very difficult to be defended and detected, especially when it is launched by some conspired attackers using their legitimate identities. In this paper, we propose an event based reputation system (EBRS), in which dynamic reputation and trusted value for each event are employed to suppress the spread of false messages. EBRS can detect Sybil attack with fabricated identities and stolen identities in the process of communication, it also defends against the conspired Sybil attack since each event has a unique reputation value and trusted value. Meanwhile, we keep the vehicle identity in privacy. Simulation results show that EBRS is able to defend and detect multi-source Sybil attacks with high performances. [ABSTRACT FROM AUTHOR]