The Immune Regulatory Role of Cytokine-Induced Killer Cells Treatment on Non-Small Cell Lung Cancer Patients

Although a great progress has been made in surgery, radiotherapy and chemotherapy for non-small cell lung cancer (NSCLC), the 5-year overall survival rate (OS) remains unsatisfactory (approximately 15%). Recently, cytokine-induced killer (CIK) cells treatment as an adoptive immunotherapy has great promises in the scenario of potential new approaches for the treatment of lung tumors. Adaptive and innate cellular immunity are all important for inhibiting tumor growth and the clearance of cancer. The abilities to efficiently kill tumor cells and promote immune responses are the ultimate basic ability requested to CIK cells treatment. Therefore, we conducted a systematic review to evaluate the immunoregulation of CIK cells treatment in NSCLC patients to provide an objective reference for clinical decision-making

An inventory control model with interconnected logistic services for vendor inventory management

International audienceThis paper proposes an inventory control model taking advantage of interconnected logistic services in the Physical Internet for fast-moving consumer goods (FMCG) sector. Unlike current hierarchical inventory model where the source of each is pre-assigned, the goods are stored and distributed in an interconnected and open network of PI-hubs which enables storage capacity and transportation sharing among different companies around the network. As a result, theoretically, the suppliers can push their goods all around the network and the retailers can be served by any hub in the network. A non-linear global optimization inventory model to minimize the total logistic costs is proposed and a heuristic using simulated annealing is applied to solve the problem. Numerical experiments are taken to compare the performance of the proposed PI inventory model and classic inventory control model for different settings of a typical supply network. Results suggest that the PI inventory control model can always reduce the total logistic cost while reaching a comparable or improved end customer service level

THE STUDY ON INFLUENCES OF ONLINE REVIEW HELPFULNESS

With the surge in the number of the online review, how to get valuable information from a large number of useless information become a new problem that people face with when they shopping online. So far, many scholars have carried on some researches on this problem, but most of the studies were based on tangible goods\u27 online reviews, and studies about services\u27 online reviews are still very few. This research-in-progress aims to apply the ELM (Elaboration Likelihood Model) analysis framework to develop the model of customer review helpfulness from the perspective of cognitive theory. We plan to carry on empirical research on the review data of service from Dianping.com, and test the model presented in this paper according to the theoretical analysis

Enabling Quality Control for Entity Resolution: A Human and Machine Cooperation Framework

Even though many machine algorithms have been proposed for entity resolution, it remains very challenging to find a solution with quality guarantees. In this paper, we propose a novel HUman and Machine cOoperation (HUMO) framework for entity resolution (ER), which divides an ER workload between the machine and the human. HUMO enables a mechanism for quality control that can flexibly enforce both precision and recall levels. We introduce the optimization problem of HUMO, minimizing human cost given a quality requirement, and then present three optimization approaches: a conservative baseline one purely based on the monotonicity assumption of precision, a more aggressive one based on sampling and a hybrid one that can take advantage of the strengths of both previous approaches. Finally, we demonstrate by extensive experiments on real and synthetic datasets that HUMO can achieve high-quality results with reasonable return on investment (ROI) in terms of human cost, and it performs considerably better than the state-of-the-art alternatives in quality control.Comment: 12 pages, 11 figures. Camera-ready version of the paper submitted to ICDE 2018, In Proceedings of the 34th IEEE International Conference on Data Engineering (ICDE 2018

Probabilistic Energy Optimization in Wireless Sensor Networks with Variable Size Griding

Abstract-Due to limited energy supplies, reducing power consumption is an important goal in wireless sensor networks. Clustering techniques are used to reduce power consumption and prolong network lifetime in many existing research efforts, among which grid-based ones are often used due to their simplicity and scalability. However, most existing work uses average distance as a simplification in calculating distance-related power consumption, which leads to a large underestimation of the actual energy depletion rate. In this paper, we propose an energy optimization model based on probabilistic distance distributions, which captures the distance-induced power consumption with high accuracy. We further analyze the uneven traffic distribution in wireless sensor networks and propose a nonuniform griding scheme to balance the energy depletion in all grids. Through our analysis, we are able to obtain the optimal grid size ratio that minimizes the energy consumption. Analytical results are validated through simulation, which shows the promising potentials of our method and the nonuniform griding technique

Polysaccharides from the Chinese medicinal herb Achyranthes bidentata enhance anti-malarial immunity during Plasmodium yoelii 17XL infection in mice

<p>Abstract</p> <p>Background</p> <p>Clinical immunity to malaria in human populations is developed after repeated exposure to malaria. Regulation and balance of host immune responses may lead to optimal immunity against malaria parasite infection. Polysaccharides (ABPS) derived from the Chinese herb ox knee <it>Achyranthes bidentata </it>possess immuno-modulatory functions. The aim of this study is to use the rodent malaria model <it>Plasmodium yoelii </it>17XL (<it>P. y</it>17XL) to examine whether pretreatment with ABPS will modulate host immunity against malaria infection and improve the outcome of the disease.</p> <p>Methods</p> <p>To determine whether ABPS could modulate immunity against malaria, mice were pretreated with ABPS prior to blood-stage infection by <it>P. y</it>17XL. Host survival and parasitaemia were monitored daily. The effect of pretreatment on host immune responses was studied through the quantitation of cytokines, dendritic cell populations, and natural regulatory T cells (Treg).</p> <p>Results</p> <p>Pretreatment with ABPS prior to infection significantly extended the survival time of mice after <it>P. y</it>17XL infection. At three and five days post-infection, ABPS pretreated mice developed stronger Th1 immune responses against malaria infection with the number of F4/80⁺CD36⁺macrophages and levels of IFN-γ, TNF-α and nitric oxide being significantly higher than in the control group. More importantly, ABPS-treated mice developed more myeloid (CD11c⁺CD11b⁺) and plasmacytoid dendritic cells (CD11c⁺CD45R⁺/B220⁺) than control mice. ABPS pretreatment also resulted in modulated expression of MHC-II, CD86, and especially Toll-like receptor 9 by CD11c⁺dendritic cells. In comparison, pretreatment with ABPS did not alter the number of natural Treg or the production of the anti-inflammatory cytokine IL-10.</p> <p>Conclusion</p> <p>Pretreatment with the immuno-modulatory ABPS selectively enhanced Th1 immune responses to control the proliferation of malaria parasites, and prolonged the survival of mice during subsequent malaria infection.</p