Beyond rest and quiescence (endodormancy and ecodormancy) : A novel model for quantifying plant-environment interaction in bud dormancy release

Bud dormancy of plants has traditionally been explained either by physiological growth arresting conditions in the bud or by unfavourable environmental conditions, such as non-growth-promoting low air temperatures. This conceptual dichotomy has provided the framework also for developing process-based plant phenology models. Here, we propose a novel model that in addition to covering the classical dichotomy as a special case also allows the quantification of an interaction of physiological and environmental factors. According to this plant-environment interaction suggested conceptually decades ago, rather than being unambiguous, the concept of "non-growth-promoting low air temperature" depends on the dormancy status of the plant. We parameterized the model with experimental results of growth onset for seven boreal plant species and found that based on the strength of the interaction, the species can be classified into three dormancy types, only one of which represents the traditional dichotomy. We also tested the model with four species in an independent experiment. Our study suggests that interaction of environmental and physiological factors may be involved in many such phenomena that have until now been considered simply as plant traits without any considerations of effects of the environmental factors.Peer reviewe

Antibodies to decorin-binding protein B (DbpB) in the diagnosis of Lyme neuroborreliosis in children

Peer reviewe

The Unique Determination of Neuronal Currents in the Brain via Magnetoencephalography

The problem of determining the neuronal current inside the brain from measurements of the induced magnetic field outside the head is discussed under the assumption that the space occupied by the brain is approximately spherical. By inverting the Geselowitz equation, the part of the current which can be reconstructed from the measurements is precisely determined. This actually consists of only certain moments of one of the two functions specifying the tangential part of the current. The other function specifying the tangential part of the current as well as the radial part of the current are completely arbitrary. However, it is also shown that with the assumption of energy minimization, the current can be reconstructed uniquely. A numerical implementation of this unique reconstruction is also presented

Closed-loop optimization of transcranial magnetic stimulation with electroencephalography feedback

Background: Transcranial magnetic stimulation (TMS) is widely used in brain research and treatment of various brain dysfunctions. However, the optimal way to target stimulation and administer TMS therapies, for example, where and in which electric field direction the stimuli should be given, is yet to be determined. Objective: To develop an automated closed-loop system for adjusting TMS parameters (in this work, the stimulus orientation) online based on TMS-evoked brain activity measured with electroencephalography (EEG). Methods: We developed an automated closed-loop TMS-EEG set-up. In this set-up, the stimulus parameters are electronically adjusted with multi-locus TMS. As a proof of concept, we developed an algorithm that automatically optimizes the stimulation orientation based on single-trial EEG responses. We applied the algorithm to determine the electric field orientation that maximizes the amplitude of the TMS-EEG responses. The validation of the algorithm was performed with six healthy volunteers, repeating the search twenty times for each subject. Results: The validation demonstrated that the closed-loop control worked as desired despite the large variation in the single-trial EEG responses. We were often able to get close to the orientation that maximizes the EEG amplitude with only a few tens of pulses. Conclusion: Optimizing stimulation with EEG feedback in a closed-loop manner is feasible and enables effective coupling to brain activity. (C) 2022 The Author(s). Published by Elsevier Inc.Peer reviewe

Olive phenology as a sensitive indicator of future climatic warming in the Mediterranean

Experimental and modelling work suggests a strong dependence of olive flowering date on spring temperatures. Since airborne pollen concentrations reflect the flowering phenology of olive populations within a radius of 50 km, they may be a sensitive regional indicator of climatic warming. We assessed this potential sensitivity with phenology models fitted to flowering dates inferred from maximum airborne pollen data. Of four models tested, a thermal time model gave the best fit for Montpellier, France, and was the most effective at the regional scale, providing reasonable predictions for 10 sites in the western Mediterranean. This model was forced with replicated future temperature simulations for the western Mediterranean from a coupled ocean-atmosphere general circulation model (GCM). The GCM temperatures rose by 4·5 °C between 1990 and 2099 with a 1% per year increase in greenhouse gases, and modelled flowering date advanced at a rate of 6·2 d per °C. The results indicated that this long-term regional trend in phenology might be statistically significant as early as 2030, but with marked spatial variation in magnitude, with the calculated flowering date between the 1990s and 2030s advancing by 3–23 d. Future monitoring of airborne olive pollen may therefore provide an early biological indicator of climatic warming in the Mediterranean

Simulating the carbon balance of a temperate larch forest under various meteorological conditions

<p>Abstract</p> <p>Background</p> <p>Changes in the timing of phenological events may cause the annual carbon budget of deciduous forests to change. Therefore, one should take such events into account when evaluating the effects of global warming on deciduous forests. In this article, we report on the results of numerical experiments done with a model that includes a phenological module simulating the timing of bud burst and other phenological events and estimating maximum leaf area index.</p> <p>Results</p> <p>This study suggests that the negative effects of warming on tree productivity (net primary production) outweigh the positive effects of a prolonged growing season. An increase in air temperature by 3°C (5°C) reduces cumulative net primary production by 21.3% (34.2%). Similarly, cumulative net ecosystem production (the difference between cumulative net primary production and heterotrophic respiration) decreases by 43.5% (64.5%) when temperatures are increased by 3°C (5°C). However, the positive effects of CO₂enrichment (2 × CO₂) outweigh the negative effects of warming (<5°C).</p> <p>Conclusion</p> <p>Although the model was calibrated and validated for a specific forest ecosystem, the implications of the study may be extrapolated to deciduous forests in cool-temperate zones. These forests share common features, and it can be conjectured that carbon stocks would increase in such forests in the face of doubled CO₂and increased temperatures as long as the increase in temperature does not exceed 5°C.</p

Lateral Orbitofrontal Cortex Involvement in Initial Negative Aesthetic Impression Formation

It is well established that aesthetic appreciation is related with activity in several different brain regions. The identification of the neural correlates of beauty or liking ratings has been the focus of most prior studies. Not much attention has been directed towards the fact that humans are surrounded by objects that lead them to experience aesthetic indifference or leave them with a negative aesthetic impression. Here we explore the neural substrate of such experiences. Given the neuroimaging techniques that have been used, little is known about the temporal features of such brain activity. By means of magnetoencephalography we registered the moment at which brain activity differed while participants viewed images they considered to be beautiful or not. Results show that the first differential activity appears between 300 and 400 ms after stimulus onset. During this period activity in right lateral orbitofrontal cortex (lOFC) was greater while participants rated visual stimuli as not beautiful than when they rated them as beautiful. We argue that this activity is associated with an initial negative aesthetic impression formation, driven by the relative hedonic value of stimuli regarded as not beautiful. Additionally, our results contribute to the understanding of the nature of the functional roles of the lOFC

Identification and characterisation of novel SNP markers in Atlantic cod: Evidence for directional selection

<p>Abstract</p> <p>Background</p> <p>The Atlantic cod (<it>Gadus morhua</it>) is a groundfish of great economic value in fisheries and an emerging species in aquaculture. Genetic markers are needed to identify wild stocks in order to ensure sustainable management, and for marker-assisted selection and pedigree determination in aquaculture. Here, we report on the development and evaluation of a large number of Single Nucleotide Polymorphism (SNP) markers from the alignment of Expressed Sequence Tag (EST) sequences in Atlantic cod. We also present basic population parameters of the SNPs in samples of North-East Arctic cod and Norwegian coastal cod obtained from three different localities, and test for SNPs that may have been targeted by natural selection.</p> <p>Results</p> <p>A total of 17,056 EST sequences were used to find 724 putative SNPs, from which 318 segregating SNPs were isolated. The SNPs were tested on Atlantic cod from four different sites, comprising both North-East Arctic cod (NEAC) and Norwegian coastal cod (NCC). The average heterozygosity of the SNPs was 0.25 and the average minor allele frequency was 0.18. <it>F</it>_{<it>ST </it>}values were highly variable, with the majority of SNPs displaying very little differentiation while others had <it>F</it>_{<it>ST </it>}values as high as 0.83. The <it>F</it>_{<it>ST </it>}values of 29 SNPs were found to be larger than expected under a strictly neutral model, suggesting that these loci are, or have been, influenced by natural selection. For the majority of these outlier SNPs, allele frequencies in a northern sample of NCC were intermediate between allele frequencies in a southern sample of NCC and a sample of NEAC, indicating a cline in allele frequencies similar to that found at the Pantophysin I locus.</p> <p>Conclusion</p> <p>The SNP markers presented here are powerful tools for future genetics work related to management and aquaculture. In particular, some SNPs exhibiting high levels of population divergence have potential to significantly enhance studies on the population structure of Atlantic cod.</p

Immunoglobulin GM 3 23 5,13,14 phenotype is strongly associated with IgG1 antibody responses to Plasmodium vivax vaccine candidate antigens PvMSP1-19 and PvAMA-1

<p>Abstract</p> <p>Background</p> <p>Humoral immune responses play a key role in the development of immunity to malaria, but the host genetic factors that contribute to the naturally occurring immune responses to malarial antigens are not completely understood. The aim of the present investigation was to determine whether, in subjects exposed to malaria, GM and KM allotypes--genetic markers of immunoglobulin γ and κ-type light chains, respectively--contribute to the magnitude of natural antibody responses to target antigens that are leading vaccine candidates for protection against <it>Plasmodium vivax</it>.</p> <p>Methods</p> <p>Sera from 210 adults, who had been exposed to malaria transmission in the Brazilian Amazon endemic area, were allotyped for several GM and KM determinants by a standard hemagglutination-inhibition method. IgG subclass antibodies to <it>P. vivax </it>apical membrane antigen 1 (PvAMA-1) and merozoite surface protein 1 (PvMSP1-19) were determined by an enzyme-linked immunosorbent assay. Multiple linear regression models and the non-parametric Mann-Whitney test were used for data analyses.</p> <p>Results</p> <p>IgG1 antibody levels to both PvMSP1-19 and PvAMA-1 antigens were significantly higher (<it>P </it>= 0.004, <it>P </it>= 0.002, respectively) in subjects with the GM 3 23 5,13,14 phenotype than in those who lacked this phenotype.</p> <p>Conclusions</p> <p>Results presented here show that immunoglobulin GM allotypes contribute to the natural antibody responses to <it>P. vivax </it>malaria antigens. These findings have important implications for the effectiveness of vaccines containing PvAMA-1 or PvMSP1-19 antigens. They also shed light on the possible role of malaria as one of the evolutionary selective forces that may have contributed to the maintenance of the extensive polymorphism at the GM loci.</p

A mean field model for movement induced changes in the beta rhythm

In electrophysiological recordings of the brain, the transition from high amplitude to low amplitude signals are most likely caused by a change in the synchrony of underlying neuronal population firing patterns. Classic examples of such modulations are the strong stimulus-related oscillatory phenomena known as the movement related beta decrease (MRBD) and post-movement beta rebound (PMBR). A sharp decrease in neural oscillatory power is observed during movement (MRBD) followed by an increase above baseline on movement cessation (PMBR). MRBD and PMBR represent important neuroscientific phenomena which have been shown to have clinical relevance. Here, we present a parsimonious model for the dynamics of synchrony within a synaptically coupled spiking network that is able to replicate a human MEG power spectrogram showing the evolution from MRBD to PMBR. Importantly, the high-dimensional spiking model has an exact mean field description in terms of four ordinary differential equations that allows considerable insight to be obtained into the cause of the experimentally observed time-lag from movement termination to the onset of PMBR (~ 0.5 s), as well as the subsequent long duration of PMBR (~ 1-10 s). Our model represents the first to predict these commonly observed and robust phenomena and represents a key step in their understanding, in health and disease