On dendritic cell-based therapy for cancers

Dendritic cells (DCs), the most prevalent antigen-presenting cell in vivo, had been widely characterized in the last three decades. DCs are present in almost all tissues of the body and play cardinal roles in recognition of microbial agents,autoantigens, allergens and alloantigen. DCs process the microbial agents or their antigens and migrate to lymphoid tissues to present the antigenic peptide to lymphocytes. This leads to activation of antigen-specific lymphocytes. Initially, it was assumed that DCs are principally involved in the induction and maintenance of adaptive immune responses, but now it is evident that DCs also have important roles in innate immunity. These features make DCs very good candidates for therapy against various pathological conditions including malignancies. Initially, DC-based therapy was used in animal models of cancers. Data from these studies inspired considerable optimism and DC-based therapies was started in human cancers 8 years ago. In general,DC-based therapy has been found to be safe in patients with cancers, although few controlled trials have been conducted in this regard. Because the fundamentals principles of human cancers and animal models of cancers are different, the therapeutic efficacy of the ongoing regime of DC-based therapy in cancer patients is not satisfactory. In this review, we covered the various aspects that should be considered for developing better regime of DC-based therapy for human cancers.     

Uniform exponential stability of periodic discrete switched linear system

Let {Π_τ(m, n): m?≥?n?≥?0} be the family of periodic discrete transition matrices generated by bounded valued square matrices Λ_τ(n), where $\tau :[0,1,2,?)\to \Omega$ is an arbitrary switching signal. We prove that the family {Π_τ(m, n): m?≥?n?≥?0} of bounded linear operator is uniformly exponentially stable if and only if the sequence $n?{\sum }_{k=0}^n{e}^{i\alpha k}{\Pi }_{\tau }(n,k)w\left(k\right):{\mathbb{Z}}_{+}\to \mathbb{R}$ is bounded.     

Estimating seismic demand parameters using the endurance time method

The endurance time (ET) method is a time history based dynamic analysis in which structures are subjected to gradually intensifying excitations and their performances are judged based on their responses at various excitation levels. Using this method, the computational effort required for estimating probable seismic demand parameters can be reduced by an order of magnitude. Calculation of the maximum displacement or target displacement is a basic requirement for estimating performance based on structural design. The purpose of this paper is to compare the results of the nonlinear ET method with the nonlinear static pushover (NSP) method of FEMA 356 by evaluating performances and target displacements of steel frames. This study will lead to a deeper insight into the capabilities and limitations of the ET method. The results are further compared with those of the standard nonlinear response history analysis. We conclude that results from the ET analysis are in proper agreement with those from standard procedures.