Exposure of monocytes to heat shock does not increase class II expression but modulates antigen-dependent T cell responses

Expression of heat shock (HS) proteins (HSP) increases after exposure to elevated temperatures or other types of injury, such as oxldative injury. Because of their function as ‘molecular chaperones', HSP are suggested to participate in antigen processing and presentation. We have previously reported that HS modulates antigen presentation in a human EBV-transformed B cell line. Here we investigated the effects of HS on MHC class II expression and on antigen processing and presentation by human monocytes. Monocytes were isolated from peripheral blood of normal human volunteers, purified by adherence, then exposed to temperatures ranging from 37 to 45°C for 20 min, allowed to recover for 2 h at 37°C and used for immunofluorescence or as antigen presenting cells in autologous and heterologous lymphocyte proliferation assays. No increase in class II expression was detected as assessed by flow cytometry. Monocytes (3 × 104) and lymphocytes (1 × 105) were co-cultured for 5 days in the presence of several antigens [diphtheria toxold, tetanus toxold or purified peptlde derivative (PPD)] and labeled with 1 μCI [3H]thymldlne for 16 h. Pre-exposure to HS (44°C) significantly (P < 0.001) increased T cell responses to diphtheria toxold, whereas the effect on the responses to other antigens (tetanus toxold or PPD) were not significant. HS did not increase heterologous T cell responses nor T cell proliferation induced by the non-processed superantigens such as staphylococcal enterotoxln B. The effect of HS was inhibited by actlnomycln B and thus appeared dependent upon HSP synthesis. HSP-mediated increases in antigen processing may potentiate the ongoing immune response at inflammatory site

Design methodology of an electric vehicle hybrid energy storage unit for improved energy efficiency

This work proposes a design methodology that allows designing the energy storage unit of an electric vehicle in order to minimize the required energy and the resulting losses. A simple analytical model of the vehicle losses is derived. Driving conditions and solar production scenarios are obtained from stochastic processes; they are employed to generate a number of vehicle power profiles. Candidate supercapacitor arrangements are classified in terms of losses and energy capacity, leading to the associated Pareto minimum

Active Surge control of electrically driven centrifugal compressors

A novel approach for the active surge control of centrifugal compression systems with actuated recycle valves is presented. This actuator, commonly used in industrial plants, allows the system to recover from surge by increasing the mass flow rate through the compressor. A backstepping control is designed for the recycle valve, and is combined with a nonlinear Model Predictive Control of the drive torque, to track a desired reference state while accounting for system constraints. The optimization problem is solved approximately, to account for the computational limitation of industrial controllers. Simulations based on a real compression system show that the proposed control system tracks a desired reference and is robust to uncertainties in the outlet valve characteristics

Short-term scheduling of make-and-pack production processes: a hybrid method for large-scale instances

We present an overview of recent research at IDIAP on speech & face based biometric authentication. This report covers user-customised passwords, adaptation techniques, confidence measures (for use in fusion of audio & visual scores), face verification in difficult image conditions, as well as other related research issues. We also overview the Torch machine-learning library, which has aided in the implementation of the above mentioned techniques

Predictive control in power electronics and drives: basic concepts, theory, and methods

In this chapter we revise basic principles and methods of model predictive control with a view towards applications in power electronics and drives. The simplest predictive control formulations use horizon-one cost functions, which can be related to well-established dead-beat controllers. Model predictive control using larger horizons has the potential to give significant performance benefits, but requires more computations at each sampling instant to solve the associated optimization problems. For particular classes of system models, we discuss practical algorithms, which make long-horizon predictive control suitable for power electronics applications