Search algorithms as a framework for the optimization of drug combinations

Combination therapies are often needed for effective clinical outcomes in the management of complex diseases, but presently they are generally based on empirical clinical experience. Here we suggest a novel application of search algorithms, originally developed for digital communication, modified to optimize combinations of therapeutic interventions. In biological experiments measuring the restoration of the decline with age in heart function and exercise capacity in Drosophila melanogaster, we found that search algorithms correctly identified optimal combinations of four drugs with only one third of the tests performed in a fully factorial search. In experiments identifying combinations of three doses of up to six drugs for selective killing of human cancer cells, search algorithms resulted in a highly significant enrichment of selective combinations compared with random searches. In simulations using a network model of cell death, we found that the search algorithms identified the optimal combinations of 6-9 interventions in 80-90% of tests, compared with 15-30% for an equivalent random search. These findings suggest that modified search algorithms from information theory have the potential to enhance the discovery of novel therapeutic drug combinations. This report also helps to frame a biomedical problem that will benefit from an interdisciplinary effort and suggests a general strategy for its solution.Comment: 36 pages, 10 figures, revised versio

Testing timed systems modeled by stream X-machines

Stream X-machines have been used to specify real systems where complex data structures. They are a variety of extended finite state machine where a shared memory is used to represent communications between the components of systems. In this paper we introduce an extension of the Stream X-machines formalism in order to specify systems that present temporal requirements. We add time in two different ways. First, we consider that (output) actions take time to be performed. Second, our formalism allows to specify timeouts. Timeouts represent the time a system can wait for the environment to react without changing its internal state. Since timeous affect the set of available actions of the system, a relation focusing on the functional behavior of systems, that is, the actions that they can perform, must explicitly take into account the possible timeouts. In this paper we also propose a formal testing methodology allowing to systematically test a system with respect to a specification. Finally, we introduce a test derivation algorithm. Given a specification, the derived test suite is sound and complete, that is, a system under test successfully passes the test suite if and only if this system conforms to the specification

Application of remote sensing to state and regional problems

The methods and procedures used, accomplishments, current status, and future plans are discussed for each of the following applications of LANDSAT in Mississippi: (1) land use planning in Lowndes County; (2) strip mine inventory and reclamation; (3) white-tailed deer habitat evaluation; (4) remote sensing data analysis support systems; (5) discrimination of unique forest habitats in potential lignite areas; (6) changes in gravel operations; and (7) determining freshwater wetlands for inventory and monitoring. The documentation of all existing software and the integration of the image analysis and data base software into a single package are now considered very high priority items

On design of quantized fault detection filters with randomly occurring nonlinearities and mixed time-delays

This paper is concerned with the fault detection problem for a class of discrete-time systems with randomly occurring nonlinearities, mixed stochastic time-delays as well as measurement quantizations. The nonlinearities are assumed to occur in a random way. The mixed time-delays comprise both the multiple discrete time-delays and the infinite distributed delays that occur in a random way as well. A sequence of stochastic variables is introduced to govern the random occurrences of the nonlinearities, discrete time-delays and distributed time-delays, where all the stochastic variables are mutually independent but obey the Bernoulli distribution. The main purpose of this paper is to design a fault detection filter such that, in the presence of measurement quantization, the overall fault detection dynamics is exponentially stable in the mean square and, at the same time, the error between the residual signal and the fault signal is made as small as possible. Sufficient conditions are first established via intensive stochastic analysis for the existence of the desired fault detection filters, and then the explicit expression of the desired filter gains is derived by means of the feasibility of certain matrix inequalities. Also, the optimal performance index for the addressed fault detection problem can be obtained by solving an auxiliary convex optimization problem. A practical example is provided to show the usefulness and effectiveness of the proposed design method

Eligibility Traces and Plasticity on Behavioral Time Scales: Experimental Support of neoHebbian Three-Factor Learning Rules

Most elementary behaviors such as moving the arm to grasp an object or walking into the next room to explore a museum evolve on the time scale of seconds; in contrast, neuronal action potentials occur on the time scale of a few milliseconds. Learning rules of the brain must therefore bridge the gap between these two different time scales. Modern theories of synaptic plasticity have postulated that the co-activation of pre- and postsynaptic neurons sets a flag at the synapse, called an eligibility trace, that leads to a weight change only if an additional factor is present while the flag is set. This third factor, signaling reward, punishment, surprise, or novelty, could be implemented by the phasic activity of neuromodulators or specific neuronal inputs signaling special events. While the theoretical framework has been developed over the last decades, experimental evidence in support of eligibility traces on the time scale of seconds has been collected only during the last few years. Here we review, in the context of three-factor rules of synaptic plasticity, four key experiments that support the role of synaptic eligibility traces in combination with a third factor as a biological implementation of neoHebbian three-factor learning rules

From Dataflow Specification to Multiprocessor Partitioned Time-triggered Real-time Implementation *

International audienceOur objective is to facilitate the development of complex time-triggered systems by automating the allocation and scheduling steps. We show that full automation is possible while taking into account the elements of complexity needed by a complex embedded control system. More precisely, we consider deterministic functional specifications provided (as often in an industrial setting) by means of synchronous data-flow models with multiple modes and multiple relative periods. We first extend this functional model with an original real-time characterization that takes advantage of our time-triggered framework to provide a simpler representation of complex end-to-end flow requirements. We also extend our specifications with additional non-functional properties specifying partitioning, allocation , and preemptability constraints. Then, weprovide novel algorithms for the off-line scheduling of these extended specifications onto partitioned time-triggered architectures à la ARINC 653. The main originality of our work is that it takes into account at the same time multiple complexity elements: various types of non-functional properties (real-time, partitioning, allocation, preemptability) and functional specifications with conditional execution and multiple modes. Allocation of time slots/windows to partitions can be fullyor partially provided, or synthesized by our tool. Our algorithms allow the automatic allocation and scheduling onto multi-processor (distributed) sys-tems with a global time base, taking into account communication costs. We demonstrate our technique on a model of space flight software systemwith strong real-time determinism requirements