Impact on survival of the number of lymph nodes resected in patients with lymph node-negative gastric cancer

BACKGROUND: Patients with lymph node-negative gastric cancer show a better overall survival rate than those who have a pathological lymph node-positive gastric cancer. But a large number of patients still develop recurrence. We aimed to explore the significant prognostic factors of lymph node-negative gastric cancer and determine how many lymph nodes should be removed. METHODS: A total of 3103 patients who underwent radical operation are identified from the Surveillance, Epidemiology, and End Results database. Standard survival methods and restricted multivariable Cox regression models were applied. RESULTS: The overall survival rate was significantly higher with an increasing number of negative lymph node resected. Among the 843 patients who had the exact T stage, the overall survival rate was significantly better in T3-4 group with more than 15 lymph nodes resected (P \u3c 0.001) but not in T1-2 stage patients (P = 0.44). A further 25 more lymph nodes resection did not show additional survival benefits. Multivariate analysis of patients demonstrated that age, depth of tumor invasion, and the number of lymph nodes resected were the significant and independent prognostic factors. CONCLUSIONS: A lymphadenectomy with more than 15 lymph nodes removal should be performed for T3-4 lymph node-negative gastric cancer. But the survival benefit of a lymphadenectomy with more than 25 lymph nodes removal is disputed. And the further treatment should refer to the prognostic indicators

Exploiting Traffic Balancing and Multicast Efficiency in Distributed Video-on-Demand Architectures

Distributed Video-on-Demand (DVoD) systems are proposed as a solution to the limited streaming capacity and null scalability of centralized systems. In a previous work, we proposed a fully distributed large-scale VoD architecture, called Double P-Tree, which has shown itself to be a good approach to the design of flexible and scalable DVoD systems. In this paper, we present relevant design aspects related to video mapping and traffic balancing in order to improve Double P-Tree architecture performance. Our simulation results demonstrate that these techniques yield a more efficient system and considerably increase its streaming capacity. The results also show the crucial importance of topology connectivity in improving multicasting performance in DVoD systems. Finally, a comparison among several DVoD architectures was performed using simulation, and the results show that the Double P-Tree architecture incorporating mapping and load balancing policies outperforms similar DVoD architectures.This work was supported by the MCyT-Spain under contract TIC 2001-2592 and partially supported by the Generalitat de Catalunya- Grup de Recerca Consolidat 2001SGR-00218

Unified Detoxifying and Debiasing in Language Generation via Inference-time Adaptive Optimization

Warning: this paper contains model outputs exhibiting offensiveness and biases. Recently pre-trained language models (PLMs) have prospered in various natural language generation (NLG) tasks due to their ability to generate fairly fluent text. Nevertheless, these models are observed to capture and reproduce harmful contents in training corpora, typically toxic language and social biases, raising severe moral issues. Prior works on ethical NLG tackle detoxifying and debiasing separately, which is problematic since we find debiased models still exhibit toxicity while detoxified ones even exacerbate biases. To address such a challenge, we propose the first unified framework of detoxifying and debiasing called UDDIA, which jointly formalizes these two problems as rectifying the output space. We theoretically interpret our framework as learning a text distribution mixing weighted attributes. Besides, UDDIA conducts adaptive optimization of only a few parameters during decoding based on a parameter-efficient tuning schema without any training data. This leads to minimal generation quality loss and improved rectification performance with acceptable computational cost. Experimental results demonstrate that compared to several strong baselines, UDDIA achieves debiasing and detoxifying simultaneously and better balances efficiency and effectiveness, taking a further step towards practical ethical NLG.Comment: Work in Progress. Preprin