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Modeling Antibiotic Treatment in Hospitals, Inferring Synaptic Plasticity from Spiking, and Synthesizing Developmental Trajectories

Check out our highlights from the PLOS Computational Biology September issue:


Modeling antibiotic treatment in hospitals: A systematic approach shows benefits of combination therapy over cycling, mixing, and mono-drug therapies


For life-threatening infections, antibiotics need to be administered as soon as possible. Because it takes time to acquire data about the disease-causing bacteria, the immediate treatment is often empirical. In particular, three treatment strategies are generally discussed in the field of empirical treatment: cycling, mixing, and combination therapy. Despite a number of clinical and theoretical studies, it still remains unclear which treatment strategy best prevents the emergence of resistance, and why. To address this controversy, Burcu Tepekule and colleagues present a mathematical model capturing both mono- and multi-drug therapies. They sampled and analyzed a large parameter space to assess the effect of parameters on treatment success, and determine which treatment strategy is the best under which circumstances. Using methods such as linear discriminant analysis and particle swarm optimisation, they found that combination therapy outperforms the other strategies by a large margin for most of the biologically relevant parameter space. They also show that the rate of de novo emergence of double resistance and the costs of resistance mutations are the most important parameters determining whether combination therapy succeeds over the others.


Artificial current injection to a layer 2/3 pyramidal neuron. Image Credit: Ghanbari et al.

Estimating short-term synaptic plasticity from pre- and post-synaptic spiking


Information processing in the nervous system critically depends on dynamic changes in the strength of connections between neurons. Short-term synaptic plasticity (STP), involving changes that occur on timescales from milliseconds to a few seconds, is thought to play a role in tasks such as speech recognition, motion detection, and working memory. Although intracellular recordings in slices of neural tissue have identified synaptic mechanisms of STP and have demonstrated its potential role in information processing, studying STP in intact animals, especially during behavior, is experimentally difficult. Unlike intracellular recordings, extracellular spiking of hundreds of neurons simultaneously can be recorded even in behaving animals. Here Abed Ghanbari and colleagues developed two models that allow estimation of STP from extracellular spike recordings. They validate these models using results from in vitro experiments which simulate a realistic synaptic input from a population of presynaptic neurons with defined STP rules. The results show that both new models can accurately recover the synaptic dynamics underlying spiking. These new methods will allow us to study STP using extracellular recordings, and therefore on a much larger scale than previously possible in behaving animals.



Synthesizing developmental trajectories

September Issue Image: Data fusion for synthesis of developmental trajectories. Villoutreix and colleagues report a new approach to data fusion in studies of developmental dynamics and use it to reconstruct multivariable dynamics of a patterning cascade in the early Drosophila embryo. The image shows an optical cross-section of the embryo during the 3rd hour of development. Villoutreix et al.


A wide range of problems in biology require analysis of multivariable dynamics in space and time. As a rule, the multiscale nature and complexity of real systems precludes simultaneous monitoring of all the relevant variables, and multivariable dynamics must be synthesized from partial views provided by different experimental techniques. Paul Villoutreix and colleagues present a formal framework for accomplishing this task in the context of imaging studies of pattern formation in developing tissues.

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