A prospective randomised trial to study the role of levamisole and interferon alfa in an adjuvant therapy with 5-FU for stage III colon cancer

The purpose of this trial was to examine the efficacy of the addition of levamisole (LEV) or interferon alfa (IFN) to an adjuvant chemotherapy with 5-fluorouracil (5-FU) in patients with stage III colon cancer. According to a 2 × 2 factorial study design, 598 patients were randomly assigned to one of four adjuvant treatment arms. Patients in arm one received 5-FU weekly for 1 year, patients in arm two 5-FU plus LEV, in arm three 5-FU plus IFN and patients in arm four 5-FU, LEV and IFN. The relative risk of relapse and the relative risk of death were significantly higher for patients treated with LEV compared with those without LEV treatment (HR 1.452, 95% CI 1.135–1.856, P=0.0028; HR 1.506, 95% CI 1.150–1.973, P=0.0027, respectively). No significant impact on survival was observed for therapy with IFN in the univariate analysis. The addition of LEV to adjuvant 5-FU significantly worsened the prognosis of patients with stage III colon cancer. Interferon alfa had no significant influence on survival when combined with adjuvant 5-FU, but increased the toxicity of therapy substantially

An Imperfect Dopaminergic Error Signal Can Drive Temporal-Difference Learning

An open problem in the field of computational neuroscience is how to link synaptic plasticity to system-level learning. A promising framework in this context is temporal-difference (TD) learning. Experimental evidence that supports the hypothesis that the mammalian brain performs temporal-difference learning includes the resemblance of the phasic activity of the midbrain dopaminergic neurons to the TD error and the discovery that cortico-striatal synaptic plasticity is modulated by dopamine. However, as the phasic dopaminergic signal does not reproduce all the properties of the theoretical TD error, it is unclear whether it is capable of driving behavior adaptation in complex tasks. Here, we present a spiking temporal-difference learning model based on the actor-critic architecture. The model dynamically generates a dopaminergic signal with realistic firing rates and exploits this signal to modulate the plasticity of synapses as a third factor. The predictions of our proposed plasticity dynamics are in good agreement with experimental results with respect to dopamine, pre- and post-synaptic activity. An analytical mapping from the parameters of our proposed plasticity dynamics to those of the classical discrete-time TD algorithm reveals that the biological constraints of the dopaminergic signal entail a modified TD algorithm with self-adapting learning parameters and an adapting offset. We show that the neuronal network is able to learn a task with sparse positive rewards as fast as the corresponding classical discrete-time TD algorithm. However, the performance of the neuronal network is impaired with respect to the traditional algorithm on a task with both positive and negative rewards and breaks down entirely on a task with purely negative rewards. Our model demonstrates that the asymmetry of a realistic dopaminergic signal enables TD learning when learning is driven by positive rewards but not when driven by negative rewards

Bacteria-inducing legume nodules involved in the improvement of plant growth, health and nutrition

Bacteria-inducing legume nodules are known as rhizobia and belong to the class Alphaproteobacteria and Betaproteobacteria. They promote the growth and nutrition of their respective legume hosts through atmospheric nitrogen fixation which takes place in the nodules induced in their roots or stems. In addition, rhizobia have other plant growth-promoting mechanisms, mainly solubilization of phosphate and production of indoleacetic acid, ACC deaminase and siderophores. Some of these mechanisms have been reported for strains of rhizobia which are also able to promote the growth of several nonlegumes, such as cereals, oilseeds and vegetables. Less studied are the mechanisms that have the rhizobia to promote the plant health; however, these bacteria are able to exert biocontrol of some phytopathogens and to induce the plant resistance. In this chapter, we revised the available data about the ability of the legume nodule-inducing bacteria for improving the plant growth, health and nutrition of both legumes and nonlegumes. These data showed that rhizobia meet all the requirements of sustainable agriculture to be used as bio-inoculants allowing the total or partial replacement of chemicals used for fertilization or protection of crops