Low-amplitude, high-frequency electromagnetic field exposure causes delayed and reduced growth in Rosa hybrida

It is now accepted that plants perceive high-frequency electromagnetic field (HF-EMF). We wondered if the HF-EMF signal is integrated further in planta as a chain of reactions leading to a modification of plant growth. We exposed whole small ligneous plants (rose bush) whose growth could be studied for several weeks. We performed exposures at two different development stages (rooted cuttings bearing an axillary bud and 5-leaf stage plants), using two high frequency (900MHz) field amplitudes (5 and 200Vm(-1)). We achieved a tight control on the experimental conditions using a state-of-the-art stimulation device (Mode Stirred Reverberation Chamber) and specialized culture-chambers. After the exposure, we followed the shoot growth for over a one-month period. We observed no growth modification whatsoever exposure was performed on the 5-leaf stage plants. When the exposure was performed on the rooted cuttings, no growth modification was observed on Axis I (produced from the elongation of the axillary bud). Likewise, no significant modification was noted on Axis II produced at the base of Axis I, that came from pre-formed secondary axillary buds. In contrast, Axis II produced at the top of Axis I, that came from post-formed secondary buds consistently displayed a delayed and significant reduced growth (45%). The measurements of plant energy uptake from HF-EMF in this exposure condition (SAR of 7.2 10(-4)Wkg(-1)) indicated that this biological response is likely not due to thermal effect. These results suggest that exposure to electromagnetic field only affected development of post-formed organs.

Heterogeneity and convergence of olfactory first-order neurons account for the high speed and sensitivity of second-order neurons

In the olfactory system of male moths, a specialized subset of neurons detects and processes the main component of the sex pheromone emitted by females. It is composed of several thousand first-order olfactory receptor neurons (ORNs), all expressing the same pheromone receptor, that contact synaptically a few tens of second-order projection neurons (PNs) within a single restricted brain area. The functional simplicity of this system makes it a favorable model for studying the factors that contribute to its exquisite sensitivity and speed. Sensory information—primarily the identity and intensity of the stimulus—is encoded as the firing rate of the action potentials, and possibly as the latency of the neuron response. We found that over all their dynamic range, PNs respond with a shorter latency and a higher firing rate than most ORNs. Modelling showed that the increased sensitivity of PNs can be explained by the ORN-to-PN convergent architecture alone, whereas their faster response also requires cell-to-cell heterogeneity of the ORN population. So, far from being detrimental to signal detection, the ORN heterogeneity is exploited by PNs, and results in two different schemes of population coding based either on the response of a few extreme neurons (latency) or on the average response of many (firing rate). Moreover, ORN-to-PN transformations are linear for latency and nonlinear for firing rate, suggesting that latency could be involved in concentration-invariant coding of the pheromone blend and that sensitivity at low concentrations is achieved at the expense of precise encoding at high concentrations.

Understanding how sensory signals are optimally encoded by nervous systems is of strong interest to neuroscientists, and also to engineers as it may lead to more efficient artificial detection systems. This is particularly relevant to olfaction, because the current electronic noses are far outperformed by their biological counterparts in terms of speed and sensitivity. We here use the moth sex pheromone processing system as a relatively simple model to understand early olfactory coding. We found that performance increases when olfactory information passes from first- to second-order neurons. Second-order neurons respond on average with shorter latency and higher sensitivity than first-order neurons. We show that two critical factors, convergent architecture and neuronal heterogeneity, are needed to account for increased performance.

Plant anesthesia supports similarities between animals and plants: Claude Bernard's forgotten studies

The French scientist Claude Bernard (1813-1878) is famous for his discoveries in physiology and for introducing rigorous experimental methods to medicine and biology. One of his major technical innovations was the use of chemicals in order to disrupt normal physiological function to test hypotheses. But less known is his conviction that the physiological functions of all living organisms rely on the same underlying principles. He hypothesized that similarly to animals, plants are also able to sense changes in their environment. He called this ability "sensitivity." In order to test his ideas, he performed anesthesia on plants and the results of these experiments were presented in 1878 in "Leçonssur les phénomènes de la vie communs aux animaux et aux végétaux." The phenomena described by Claude Bernard more than a century ago are not fully understood yet. Here, we present a short overview of anesthetic effects in animals and we discuss how anesthesia affects plant movements, seed germination, and photosynthesis. Surprisingly, these phenomena may have ecological relevance, since stressed plants generate anesthetics such as ethylene and ether. Finally, we discuss Claude Bernard's interpretations and conclusions in the perspective of modern plant sciences.

Modelling the signal delivered by a population of first-order neurons in a moth olfactory system

A statistical model of the population of first-order olfactory receptor neurons (ORNs) is proposed and analysed. It describes the relationship between stimulus intensity (odour concentration) and coding variables such as rate and latency of the population of several thousand sex-pheromone sensitive ORNs in male moths. Although these neurons likely express the same olfactory receptor, they exhibit, at any concentration, a relatively large heterogeneity of responses in both peak firing frequency and latency of the first action potential fired after stimulus onset. The stochastic model is defined by a multivariate distribution of six model parameters that describe the dependence of the peak firing rate and the latency on the stimulus dose. These six parameters and their mutual linear correlations were estimated from experiments in single ORNs and included in the multidimensional model distribution. The model is utilized to reconstruct the peak firing rate and latency of the message sent to the brain by the whole ORN population at different stimulus intensities and to establish their main qualitative and quantitative properties. Finally, these properties are shown to be in agreement with those found previously in a vertebrate ORN population. This article is part of a Special Issue entitled: Neural Coding.

Odour transduction in olfactory receptor neurons

The molecular mechanisms that control the binding of odorant to olfactory receptors and transduce this signal into membrane depolarization are reviewed. They are compared in vertebrates and insects for interspecific (allelochemicals) and intraspecific (pheromones) olfactory signals. Attempts to develop quantitative models of these multistage signalling networks are presented. Computational analysis of olfactory transduction is still in its infancy and appears as a promising area for future developments.