Blockade of epidermal growth factor receptor function by bivalent and monovalent fragments of 225 anti-epidermal growth factor receptor monoclonal antibodies

We have previously described anti-epidermal growth factor (EGF) receptor monoclonal antibodies (MAbs) which can block binding of transforming growth factor alpha (TGF-alpha) and EGF to receptors and inhibit activation of receptor tyrosine kinase. Studies with these MAbs involving cell cultures and nude mouse xenografts demonstrated their capacity to inhibit the growth of a variety of tumor cell lines, which express EGF receptors and TGF-alpha and appear to depend upon receptor activation for cell proliferation. To explore the mechanism(s) by which anti-EGF receptor 225 MAb inhibits cell proliferation, we have compared the activity of native 225 MAb with the response to bivalent 225 F(ab')2 and monovalent 225 Fab' fragments. Both native 225 MAb and its fragments could inhibit the binding of 125I-EGF to EGF receptors. Scatchard analysis revealed that the Kd of 225 F(ab')2 is comparable to that of 225 MAb (1 nM), whereas the Kd of 225 Fab' is 5 nM. Both bivalent 225 MAb and 225 F(ab')2 and monovalent 225 Fab' were able to completely inhibit TGF-alpha-induced EGF receptor tyrosine kinase activation, as assayed by autophosphorylation of tyrosine residues of EGF receptors on MCF10A nonmalignant human mammary cells, MDA468 human breast adenocarcinoma cells, and A431 human vulvar squamous carcinoma cells. The bivalent forms of MAb could inhibit proliferation stimulated by endogenous (autocrine) TGF-alpha in cultures of these three cell lines. They also blocked growth stimulation by added exogenous TGF-alpha in cultures of MCF10A cells and the growth-inhibitory effect of exogenous TGF-alpha upon MDA468 and A431 cell cultures. Monovalent 225 Fab' had weaker inhibitory effects upon the proliferation of these cell lines. To determine whether the in vivo antiproliferative activity of anti-EGF receptor MAb can occur without the participation of the Fc portion of MAb, the capacities of 225 F(ab')2 and native 225 MAb to inhibit growth of s.c. A431 cell xenografts were compared. Equimolar amounts of either 225 MAb or 225 F(ab')2 were administered at intervals equivalent to the half-lives of the molecules, to attempt to maintain comparable plasma levels. Both 225 MAb and 225 F(ab')2 inhibited A431 cell xenograft growth in a dose-dependent manner, with a more sustained response in the case of the intact antibody.(ABSTRACT TRUNCATED AT 400 WORDS)     

A novel maximum power fuzzy logic controller for photovoltaic solar energy systems

The maximum power tracking problem and efficient energy utilization of a stand-alone photovoltaic array (PVA) feeding voltage controlled linear and nonlinear loads is studied. A novel and simple on-line fuzzy logic-based dynamic search, detection and tracking controller is developed to ensure maximum power point (MPP) operation under excursions in solar insolation, ambient temperature and electric load variations. A computer simulation model of the PVA renewable utilization scheme including the effects of temperature and solar irradiation changes was developed and fully simulated. The load voltage is controlled by a DC chopper and kept constant at the required rated voltage. A permanent magnet DC motor (PMDC) driving a fan-type load was connected in parallel to an RL passive load. A speed control scheme is also used for the PMDC motor drive so that the drive can be operated at specified speeds. Different controllers have been employed in the unified PVA scheme to control three separate loads at MPP tracking condition namely voltage at load bus and speed of the PMDC motor. The main objective of the paper is to present a novel enhanced, cost-effective MPP detector (MPPD) and dynamic MPP tracking (MPPT) controller for a hybrid mix of electric loads.     

A fuzzy logic sliding mode controlled electronic differential for a direct wheel drive EV

In this study, a direct wheel drive electric vehicle based on an electronic differential system with a fuzzy logic sliding mode controller (FLSMC) is studied. The conventional sliding surface is modified using a fuzzy rule base to obtain fuzzy dynamic sliding surfaces by changing its slopes using the global error and its derivative in a fuzzy logic inference system. The controller is compared with proportional–integral–derivative (PID) and sliding mode controllers (SMCs), which are usually preferred to be used in industry. The proposed controller provides robustness and flexibility to direct wheel drive electric vehicles. The fuzzy logic sliding mode controller, electronic differential system and the overall electrical vehicle mechanism are modelled and digitally simulated by using the Matlab software. Simulation results show that the system with FLSMC has better efficiency and performance compared to those of PID and SMCs.     

A novel MPPT algorithm based on optimized artificial neural network by using FPSOGSA for standalone photovoltaic energy systems

Maximum power point tracking (MPPT) algorithms are used to maximize the output power of the photovoltaic (PV) panel under different temperature and irradiance conditions in photovoltaic energy sources (PVES). In this paper, a novel MPPT method based on optimized artificial neural network by using hybrid particle swarm optimization and gravitational search algorithm based on fuzzy logic (FPSOGSA) is proposed to track the operation of the PV panel in maximum power point (MPP). The performance of the proposed MPPT approach is tested by doing the simulation and experimental studies under different environmental conditions. The proposed method is compared with the conventional perturb and observation (P&O) method for standalone PVES. The results of the comparison the obtained from the simulation and experimental studies demonstrate that the proposed MPPT method provides the reduction oscillations around the MPP and the increased maximum power yield of the PV system in the steady state.

     

A variational approach to the radiometric enhancement of digitalimagery

In this correspondence, we present a variational approach to the problem of finding suitable radiometric image transformations that optimize desirable characteristics of the output image histogram. This variational approach can be interpreted as the minimization of the cumulative spacing between histogram bars in the least squares sense subject to some weight function. Most of the common histogram transformation procedures used in remote sensing applications can be deduced from this general variational approach with an appropriate choice of the weight function.     

A novel on-line MPP search algorithm for PV arrays

A novel maximum power point (MPP) search algorithm for photovoltaic (PV) array power systems is introduced. The proposed algorithm determines the maximum power point of a PV array for any temperature and solar irradiation level using an online procedure. The method needs only the online values of the PV array output voltage and current, which can be obtained easily by using just current and voltage transducers. The algorithm requires neither the measurement of temperature and solar irradiation level nor a PV array model that is mostly used in look-up table based algorithms. Satisfactory results were obtained with the proposed algorithm in a laboratory prototype implementation scheme consisting of a PV array computer emulation model, a chopper controlled permanent magnet DC motor, and a DT2827 data acquisition board with the ATLAB software drivers for interfacing