ABSTRACT: ObjectiveIt has been reported that cell-free Epstein-Barr virus (EBV-DNA) in plasma was useful in diagnosing and monitoring nasopharyngeal
carcinoma (NPC). The current study was designed to evaluate the significance of EBV-DNA in monitoring the prognosis of nasopharyngeal
carcinoma and comparing its significance with that of plasma VCA/lgA and EA/lgA levels.
MethodsE8V -DNA, VCA/lgA, and EA/lgA levels in plasma were determined in NPC patients with different prognosis after radiotherapy,
including 30 distant metastatic patients, 22 local recurrence patients and 24 individuals with remission who had been followed-up
for more than 2 years after treatment. EBV-DNA was determined using a real-time quantitative PCR system, and levels of VCA/lgA
and EA/lgA were measured using standard immunofluorescence. In a cohort study, the indexes were determined after different
radiation periods for the 20 new cases of nasopharyngeal carcinoma.
ResultsThe median plasma EBV-DNA concentration was 135,100 copies/ ml (interquartile range: 5,525-1,003 750) in metastatic group,
20,500 copies/ ml (interquartile range: 0 -58,500) in the local recurrence group and 0 copies/ml (interquartile range: 0-0)
in the continuous remission group (P< 0.05). The levels of VCA/lgA and EA/lgA showed no significant differences among the different groups. The high level of
EBV-DNA concentration in the metastatic group was more than that in the local recurrence group. A level of 1,000,000 copies/ml
of EBV DNA was an indication of distant metastasis of the NPC patients with a sensitivity of 27.3%. However, the sensitivity
was 0 in the local recurrence group. For the 20 new patients, EBV -DNA concentration gradually decreased during the radiation
period. Before radiation there were 32,050 copies/ml (interquartile range: 3,880-317,750), 0 copies/ml (interquartile range:
0-14 375) after a 40 Gy radiation dose and 0 copies/ml (interquartile range: 0-2940) after the radiation was finished (P< 0.05). However, the levels of VCA/lgA and EA/lgA showed no significant difference.
ConclusionDetermination of plasma cell -free EBV -DNA level is more valuable than evaluation of VCA/lgA and EA/lgA for monitoring the
prognosis of NPC patients.
Chinese Journal of Clinical Oncology 04/2012; 1(3):190-195.
ABSTRACT: Survivin and Livin are new members from the family of anti-apoptotic factors. Increased levels of Survivin and Livin have been observed in many malignancies and correlated with poor prognosis. Survivin is expressed almost exclusively in proliferating cells, including various kinds of cancers, but Livin expression is relatively rare in cancer cells. Therefore, the present study examines the expressions of Survivin and Livin in nasopharyngeal carcinoma (NPC) and investigates whether their expression contributes to the prognosis of NPC.
We investigated the expression of Survivin and Livin in 80 NPC samples using immunohistochemistry stain and correlated it with the survival of these patients using log-rank test and Cox multifactor regression analysis.
All the patients were followed up at least for 60 months. During the following period, 21 cases developed distant metastasis, 9 cases developed local-regional recurrence, and 5 developed both distant metastasis and local-regional recurrence. Among them, 30 patients died of recurrence of tumor. In addition, the expression of Survivin was related with distant metastasis. Patients with low Survivin expression had better overall survival, disease-free survival and distant metastasis-free survival rates than the group with high Survivin expression (P = .0086, .0097, and .0318, respectively). Cox regression analysis confirmed that high Survivin expression was related to worse prognosis in NPC patients. However Livin expression level was not related with the survival of patients with NPC.
NPC expresses high levels of Survivin and Livin, which may play an important role in the oncogenesis and tumor development. Over-expression of Survivin was related with poor prognosis. We suggest that the determination of Survivin expression may provide predictive information on NPC patients.
The Laryngoscope 02/2006; 116(1):126-30. · 1.75 Impact Factor
ABSTRACT: The main attack strategy in an intense robotic soccer match is for an attack robot (AR) to avoid the competing side's threat and to avoid the most threatening defensive robot of the opponent to reach the objective and to effectively initiate an attack with the help of the cooperation robot (CR). This paper defines an attacking model and a cooperative model and their algorithms. Two co-evolution computation (CEC) populations of robot are also designed: one is denoted as AR subset, the other CR subset. Based on this definition, the paper proposes a new multiple robots avoidance based on CEC method (or MRACEC for short). A theoretical analysis indicates that the MRACEC method has better robustness and optimizing ability.
Tools with Artificial Intelligence, 2005. ICTAI 05. 17th IEEE International Conference on; 12/2005
ABSTRACT: Because of its accurate and robust performance, association rule-based approach is recently used for image classification. However, the existing algorithms for associative classification suffer from inefficiency. Addressing this problem, a novel algorithm based on atomic association rules is presented and successfully used in image block classification. Mining only the atomic association rules achieves fast image block classification. Using the strong atomic association rules, extracted under a high confidence threshold, can accurately differentiate instances from the image dataset. Furthermore, multi-passes of partial classifications can classify the whole dataset. This algorithm uses a self-adaptive confidence threshold and a dynamic support threshold, both of which are important for good classification performance. The experiments were performed on a standard dataset of image segmentation. The results show the proposed algorithm can classify the image blocks faster, more accurate and robust than the typical associative classification algorithm.
Computer and Information Technology, 2004. CIT '04. The Fourth International Conference on; 10/2004
4th IEEE International Workshop on Source Code Analysis and Manipulation (SCAM 2004), 15-16 September 2004, Chicago, IL, USA; 01/2004
ABSTRACT: In the electricity utilities around the world, a large number of power transformers are operating beyond their design life. The reliability and quality of power transformers is vital to system operation. In order to determine the condition of the insulation in transformers, many methods are developed. The most interesting methods for identifying fault conditions of the insulation for oil-filled transformer are dissolved gas analysis (DGA), acoustic analysis for the partial discharge (PD), liquid chromatography, and transfer function techniques. But people only apply single of them to monitoring transformer, and fail to combine the full of information from different methods. This paper establishes a theory prototype of neural network fuzzy information optimization processing technique. The learning rule and some key properties for the neural network are analyzed. It gives a fuzzy neural network learning rule. The paper integrates different diagnostic methods and information likes DGA, gas rate, acoustic analysis for the PD, temperatures in transformer, electric current, etc. that the data is not very clearly separable. There are different weights associated with each diagnosis decision with DGA, PD, and other technique. And a non-linear penalty function is used.
Dielectric Liquids, 2005. ICDL 2005. 2005 IEEE International Conference on;