Catchpoole, DR & Stewart, BW 1993, 'Etoposide-induced Cytotoxicity in Two Human T-Cell Leukemic Lines: Delayed Loss of Membrane Permeability rather than DNA Fragmentation as an Indicator of Programmed Cell Death', Cancer Research, vol. 53, no. 18, pp. 4287-4296.
Features of the apoptotic response evident in glucocorticoid-treated thymocytes are not uniformly observed in cell lines exposed to anticancer drugs. The significance of such variation has been assessed by monitoring molecular and cellular processes induced by etoposide (VP-16) in the human lymphoblastoid T-cell lines CCRF-CEM (CEM) and MOLT-4 contrasted, where appropriate, with those induced by necrotizing injury. Cytotoxic concentrations of the drug were determined to be 5-100 μm on the basis of tetrazolium reduction assay. The two lines were equally sensitive to VP-16; no difference in concentration of drug which inhibited cell growth by 50% with respect to control (i.e., drug free) cultures was apparent irrespective of exposure times from 3-72 h. DNA strand breaks were evident in both populations within 3 h of exposure to VP-16. Morphological change, assessed microscopically, involving nuclear condensation and cell shrinkage was qualitatively and quantitatively similar in VP-16-treated CEM and MOLT-4 cells. Flow cytometric analysis indicated that the G2/M fraction of the randomly dividing MOLT-4 population was approximately one-third that of CEM cells, but each line exhibited a decrease in this fraction 3-6 h after treatment Despite these similarities, marked differences in the response to VP-16 were evident in the two populations. Internucleosomal fragmentation, detected electrophoretically 3 h after treatment in DNA isolated from CEM cells, was not detected under any condition in MOLT-4 DNA Apoptotic bodies, also evident within 3 h of VP-16 treatment of CEM cells, were not readily apparent in MOLT-4 cells under the same conditions. Treatment causing necrosis resulted in trypan blue uptake within 1 h in a similar high proportion of cells from both lines. Exposure to VP-16 resulted in such a loss of membrane integrity by 6 h in CEM cells, while change in this parameter occurred only after 24 h in the case of MOLT-4 cells. The findings indicate a wide scope of...
ZHANG, GQ 1993, 'CONVERGENCE OF A SEQUENCE OF FUZZY NUMBER-VALUED FUZZY MEASURABLE FUNCTIONS ON THE FUZZY NUMBER-VALUED FUZZY MEASURE SPACE', FUZZY SETS AND SYSTEMS, vol. 57, no. 1, pp. 75-84.
ZHANG, GQ 1993, 'THE CONVERGENCE FOR A SEQUENCE OF FUZZY INTEGRALS OF FUZZY NUMBER-VALUED FUNCTIONS ON THE FUZZY SET', FUZZY SETS AND SYSTEMS, vol. 59, no. 1, pp. 43-57.
Lin, CT & Lee, CSG 1993, 'Reinforcement structure/parameter learning for neural-network-based fuzzy logic control systems', 1993 IEEE International Conference on Fuzzy Systems, pp. 88-93.
This paper proposes a Reinforcement Neural-Network-Based Fuzzy Logic Control System (RNN-FLCS) for solving various reinforcement learning problems. The proposed RNN-FLCS is best applied to learning environments where obtaining exact training data is expensive. It is constructed by integrating two Neural-Network-Based Fuzzy Logic Controllers (NN-FLCs), each of which is a connectionist model with a feedforward multi-layered network developed for the realization of a fuzzy logic controller. One NN-FLC functions as a fuzzy predictor and the other as a fuzzy controller. Using the temporal difference prediction method, the fuzzy predictor can predict the external reinforcement signal and provide a more informative internal reinforcement signal to the fuzzy controller. The fuzzy controller performs a stochastic exploratory algorithm to adapt itself according to the internal reinforcement signal. During the learning process, the proposed RNN-FLCS can construct a fuzzy logic control system automatically and dynamically through a reward-penalty signal or through very simple fuzzy information feedback; both structure learning and parameter learning are performed simultaneously in the two NN-FLCs using the fuzzy similarity measure. Simulation results are presented to illustrate the performance and applicability of the proposed RNN-FLCS.