Changes in the allocation of endogenous strigolactone improve plant biomass production on phosphate-poor soils.

Strigolactones (SLs) are carotenoid-derived phytohormones shaping plant architecture and inducing the symbiosis with endomycorrhizal fungi. In Petunia hybrida, SL transport within the plant and towards the rhizosphere is driven by the ABCG-class protein PDR1. PDR1 expression is regulated by phytohormones and by the soil phosphate abundance, and thus SL transport integrates plant development with nutrient conditions. We overexpressed PDR1 (PDR1 OE) to investigate whether increased endogenous SL transport is sufficient to improve plant nutrition and productivity. Phosphorus quantification and nondestructive X-ray computed tomography were applied. Morphological and gene expression changes were quantified at cellular and whole tissue levels via time-lapse microscopy and quantitative PCR. PDR1 OE significantly enhanced phosphate uptake and plant biomass production on phosphate-poor soils. PDR1 OE plants showed increased lateral root formation, extended root hair elongation, faster mycorrhization and reduced leaf senescence. PDR1 overexpression allowed considerable SL biosynthesis by releasing SL biosynthetic genes from an SL-dependent negative feedback. The increased endogenous SL transport/biosynthesis in PDR1 OE plants is a powerful tool to improve plant growth on phosphate-poor soils. We propose PDR1 as an as yet unexplored trait to be investigated for crop production. The overexpression of PDR1 is a valuable strategy to investigate SL functions and transport routes.

Non-destructive measurement of soybean leaf thickness via X-ray computed tomography allows the study of diel leaf growth rhythms in the third dimension.

Present-day high-resolution leaf growth measurements provide exciting insights into diel (24-h) leaf growth rhythms and their control by the circadian clock, which match photosynthesis with oscillating environmental conditions. However, these methods are based on measurements of leaf area or elongation and neglect diel changes of leaf thickness. In contrast, the influence of various environmental stress factors to which leaves are exposed to during growth on the final leaf thickness has been studied extensively. Yet, these studies cannot elucidate how variation in leaf area and thickness are simultaneously regulated and influenced on smaller time scales. Only few methods are available to measure the thickness of young, growing leaves non-destructively. Therefore, we evaluated X-ray computed tomography to simultaneously and non-invasively record diel changes and growth of leaf thickness and area. Using conventional imaging and X-ray computed tomography leaf area, thickness and volume growth of young soybean leaves were simultaneously and non-destructively monitored at three cardinal time points during night and day for a period of 80 h under non-stressful growth conditions. Reference thickness measurements on paperboards were in good agreement to CT measurements. Comparison of CT with leaf mass data further proved the consistency of our method. Exploratory analysis showed that measurements were accurate enough for recording and analyzing relative diel changes of leaf thickness, which were considerably different to those of leaf area. Relative growth rates of leaf area were consistently positive and highest during 'nights', while diel changes in thickness fluctuated more and were temporarily negative, particularly during 'evenings'. The method is suitable for non-invasive, accurate monitoring of diel variation in leaf volume. Moreover, our results indicate that diel rhythms of leaf area and thickness show some similarity but are not tightly coupled. These differences could be due to both intrinsic control mechanisms and different sensitivities to environmental factors.

Assessing potato tuber diel growth by means of X-ray computed tomography.

The formation and development of belowground organs is difficult to study. X-ray computed tomography (CT) provides the possibility to analyse and interpret subtle volumetric changes of belowground organs such as tubers, storage roots and nodules. Here, we report on the establishment of a method based on a voxel dimension of 240 µm and precision (standard deviation) of 30 µL that allows interpreting growth differences among potato tubers happening within 3 h. Plants were not stressed by the application of X-ray radiation, which was shown both by morphological comparison with control plants and by analysis of lipid peroxidation as a measure of oxidative stress. Diel (24 h) tuber growth fluctuations of three potato genotypes were monitored in soil-filled pots of 10 L. In contrast to the results from previous reports, most tubers grew at similar rates during day and night. Tuber growth was not related to the developmental stage of plants and tubers. Pronounced differences were observed between average growth rates in different tubers within a plant. These results are discussed in the context of restrictions of past methods to study tuber growth and in the context of their potential for the characterization of the formation and development of other belowground plant organs.

Subthalamic stimulation modulates self-estimation of patients with Parkinson's disease and induces risk-seeking behaviour.

Patients with Parkinson's disease with deep brain stimulation in the subthalamic nucleus postoperatively often display higher impulsivity and therefore may experience difficulties in social interactions. Here, we examined social interactions of patients with Parkinson's disease with and without deep brain stimulation in the subthalamic nucleus in competitive situations. We hypothesized altered self-estimation and risk-seeking behaviour in this patient group induced by deep brain stimulation in the subthalamic nucleus. To test the hypothesis, an experimental setting was used in which participants performed a calculation task and chose their preferred compensation. Based on their actual calculation performance, more patients with Parkinson's disease with deep brain stimulation chose a competitive tournament compensation. Assuming rational behaviour, this self-selection pattern reflects increased risk tolerance. Since patients who performed in the lowest quartile chose the tournament option, the data suggest that deep brain stimulation in the subthalamic nucleus results in a loss of the correct reference frame against which patients with Parkinson's disease evaluate their performance. The stimulation-induced combination of overestimation of their own performance, increased risk-taking, and preference for competitive environments despite poor performance is likely to impact considerably on the patients' social and work life.

The importance of effect sizes when comparing cycle threshold values of SARS-CoV-2 variants.

PURPOSE: We aimed to elaborate whether cycle threshold (Ct) values differ significantly between wild type SARS-CoV-2 (wtV) and certain viral variants and how strong or weak a potential significant effect might be. METHODS: In a retrospective study, we investigated 1873 SARS-CoV-2 positive samples for the occurrence of viral marker mutations. Age, gender, clinical setting, days after onset of symptoms, and Ct values were recorded. Statistical analysis was carried out with special consideration of effect sizes. RESULTS: During the study period wtV was detected in 1013 samples (54%), while 845 (45%) patients carried the Alpha variant of concern (VOC), and 15 (1%) the Beta VOC. For further analysis, only wtV and the Alpha VOC were included. In a multi-factor ANOVA and post-hoc test with Bonferroni-correction for the age groups we found significant main-effects for Ct values of the viral variant (wtV mean 26.4 (SD 4.27); Alpha VOC mean 25.0 (SD 3.84); F (1,1850) = 55.841; p < .001) and the clinical setting (outpatients: mean 25.7 (SD 4.1); inpatients: mean 27.0 (SD 4.2); F (1,1850) = 8.520, p = .004). However, since the effect sizes were very small (eta squared for the Alpha VOC = .029 and the clinical setting = .004), there was only a slight trend towards higher viral loads of the Alpha VOC compared to wtV. CONCLUSIONS: In order to compare different variants of SARS-CoV-2 the calculation of effect sizes seems to be necessary. A combination of p-values as estimates of the existance of an effect and effect sizes as estimates of the magnitude of a potential effect may allow a better insight into transmission mechanisms of SARS-CoV-2.

The effect of filtering on Granger causality based multivariate causality measures.

In the past, causality measures based on Granger causality have been suggested for assessing directionality in neural signals. In frequency domain analyses (power or coherence) of neural data, it is common to preprocess the time series by filtering or decimating. However, in other fields, it has been shown theoretically that filtering in combination with Granger causality may lead to spurious or missed causalities. We investigated whether this result translates to multivariate causality methods derived from Granger causality with (a) a simulation study and (b) an application to magnetoencephalographic data. To this end, we performed extensive simulations of the effect of applying different filtering techniques and evaluated the performance of five different multivariate causality measures in combination with two numerical significance measures (random permutation and leave one out method). The analysis included three of the most widely used filters (high-pass, low-pass, notch filter), four different filter types (Butterworth, Chebyshev I and II, elliptic filter), variation of filter order, decimating and interpolation. The simulation results suggest that preprocessing without a strong prior about the artifact to be removed disturbs the information content and time ordering of the data and leads to spurious and missed causalities. Only if apparent artifacts like a current or movement artifact are present, filtering out the respective disturbance seems advisable. While oversampling poses no problem, decimation by a factor greater than the minimum time shift between the time series may lead to wrong inferences. In general, the multivariate causality measures are very sensitive to data preprocessing.

Parkinson subtype-specific Granger-causal coupling and coherence frequency in the subthalamic area.

Previous work on Parkinson's disease (PD) has indicated a predominantly afferent coupling between affected arm muscle activity and electrophysiological activity within the subthalamic nucleus (STN). So far, no information is available indicating which frequency components drive the afferent information flow in PD patients. Non-directional coupling e.g. by measuring coherence is primarily established in the beta band as well as at tremor frequency. Based on previous evidence it is likely that different subtypes of the disease are associated with different connectivity patterns. Therefore, we determined coherence and causality between local field potentials (LFPs) in the STN and surface electromyograms (EMGs) from the contralateral arm in 18 akinetic-rigid (AR) PD patients and 8 tremor-dominant (TD) PD patients. During the intraoperative recording, patients were asked to lift their forearm contralateral to the recording side. Significantly more afferent connections were detected for the TD patients for tremor-periods and non-tremor-periods combined as well as for only tremor periods. Within the STN 74% and 63% of the afferent connections are associated with coherence from 4-8Hz and 8-12Hz, respectively. However, when considering only tremor-periods significantly more afferent than efferent connections were associated with coherence from 12 to 20Hz across all recording heights. No difference between efferent and afferent connections is seen in the frequency range from 4 to 12Hz for all recording heights. For the AR patients, no significant difference in afferent and efferent connections within the STN was found for the different frequency bands. Still, for the AR patients dorsal of the STN significantly more afferent than efferent connections were associated with coherence in the frequency range from 12 to 16Hz. These results provide further evidence for the differential pathological oscillations and pathways present in AR and TD Parkinson patients.

RADIX: rhizoslide platform allowing high throughput digital image analysis of root system expansion.

BACKGROUND: Phenotyping of genotype-by-environment interactions in the root-zone is of major importance for crop improvement as the spatial distribution of a plant's root system is crucial for a plant to access water and nutrient resources of the soil. However, so far it is unclear to what extent genetic variations in root system responses to spatially varying soil resources can be utilized for breeding applications. Among others, one limiting factor is the absence of phenotyping platforms allowing the analysis of such interactions. RESULTS: We developed a system that is able to (a) monitor root and shoot growth synchronously, (b) investigate their dynamic responses and (c) analyse the effect of heterogeneous N distribution to parts of the root system in a split-nutrient setup with a throughput (200 individual maize plants at once) sufficient for mapping of quantitative trait loci or for screens of multiple environmental factors. In a test trial, 24 maize genotypes were grown under split nitrogen conditions and the response of shoot and root growth was investigated. An almost double elongation rate of crown and lateral roots was observed under high N for all genotypes. The intensity of genotype-specific responses varied strongly. For example, elongation of crown roots differed almost two times between the fastest and slowest growing genotype. A stronger selective root placement in the high-N compartment was related to an increased shoot development indicating that early vigour might be related to a more intense foraging behaviour. CONCLUSION: To our knowledge, RADIX is the only system currently existing which allows studying the differential response of crown roots to split-nutrient application to quantify foraging behaviour in genome mapping or selection experiments. In doing so, changes in root and shoot development and the connection to plant performance can be investigated.

The ETH field phenotyping platform FIP: a cable-suspended multi-sensor system.

Crop phenotyping is a major bottleneck in current plant research. Field-based high-throughput phenotyping platforms are an important prerequisite to advance crop breeding. We developed a cable-suspended field phenotyping platform covering an area of ~1ha. The system operates from 2 to 5m above the canopy, enabling a high image resolution. It can carry payloads of up to 12kg and can be operated under adverse weather conditions. This ensures regular measurements throughout the growing period even during cold, windy and moist conditions. Multiple sensors capture the reflectance spectrum, temperature, height or architecture of the canopy. Monitoring from early development to maturity at high temporal resolution allows the determination of dynamic traits and their correlation to environmental conditions throughout the entire season. We demonstrate the capabilities of the system with respect to monitoring canopy cover, canopy height and traits related to thermal and multi-spectral imaging by selected examples from winter wheat, maize and soybean. The system is discussed in the context of other, recently established field phenotyping approaches; such as ground-operating or aerial vehicles, which impose traffic on the field or require a higher distance to the canopy.

Rapid phenotyping of crop root systems in undisturbed field soils using X-ray computed tomography.

BACKGROUND: X-ray computed tomography (CT) has become a powerful tool for root phenotyping. Compared to rather classical, destructive methods, CT encompasses various advantages. In pot experiments the growth and development of the same individual root can be followed over time and in addition the unaltered configuration of the 3D root system architecture (RSA) interacting with a real field soil matrix can be studied. Yet, the throughput, which is essential for a more widespread application of CT for basic research or breeding programs, suffers from the bottleneck of rapid and standardized segmentation methods to extract root structures. Using available methods, root segmentation is done to a large extent manually, as it requires a lot of interactive parameter optimization and interpretation and therefore needs a lot of time. RESULTS: Based on commercially available software, this paper presents a protocol that is faster, more standardized and more versatile compared to existing segmentation methods, particularly if used to analyse field samples collected in situ. To the knowledge of the authors this is the first study approaching to develop a comprehensive segmentation method suitable for comparatively large columns sampled in situ which contain complex, not necessarily connected root systems from multiple plants grown in undisturbed field soil. Root systems from several crops were sampled in situ and CT-volumes determined with the presented method were compared to root dry matter of washed root samples. A highly significant (P < 0.01) and strong correlation (R(2) = 0.84) was found, demonstrating the value of the presented method in the context of field research. Subsequent to segmentation, a method for the measurement of root thickness distribution has been used. Root thickness is a central RSA trait for various physiological research questions such as root growth in compacted soil or under oxygen deficient soil conditions, but hardly assessable in high throughput until today, due to a lack of available protocols. CONCLUSIONS: Application of the presented protocol helps to overcome the segmentation bottleneck and can be considered a step forward to high throughput root phenotyping facilitating appropriate sample sizes desired by science and breeding.

Spring barley shows dynamic compensatory root and shoot growth responses when exposed to localised soil compaction and fertilisation.

The impact of heterogeneous soil compaction in combination with nutrient availability on root system architecture and root growth dynamics has scarcely been investigated. We quantified changes of barley (Hordeum vulgare L.) root and shoot growth during the first 3 weeks of growth in a controlled-environment chamber. Vertically divided split-root rhizotrons were filled either uniformly with loose or compacted peat, or heterogeneously with loose peat in one compartment and compacted peat in the other. We investigated the following questions. (a) Can growth processes affected by soil compaction be mimicked in our system? (b) Do plants show compensatory growth effects when exposed to heterogeneous soil compaction? (c) Does localised fertiliser application affect root systems' responses to compaction? We observed compensatory effects regarding root system architecture and root growth dynamics due to vertically heterogeneous soil compaction. Roots grew deeper and lateral roots emerged earlier in the loose compartment of the split-root treatment compared with uniform treatments. When fertiliser was applied only via the compacted compartment in the split-root treatment, more lateral roots were initiated in the compacted compartment and lateral root formation started a few days earlier than in the uniform treatments. Consequently, the first days after exposure to heterogeneous soil conditions are critical for the analysis of underlying physiological responses.

Statistical pitfalls in the comparison of multivariate causality measures for effective causality.

The study of Wu et al. (2011) compared the performance of six different causality measures when the autoregressive process was estimated with the Dynamic Autoregressive Neuromagnetic Causal Imaging (DANCI) algorithm to help applied researchers in choosing the best method to estimate effective connectivity. This letter to the editor argues that four methodological restrictions limit the applicability of the results to actual applied research. First, there is no formal test for the significance of a connection between two channels. Second, the simulation results are affected by sizeable sampling variability. Third, only overestimation of the true model order is considered. Fourth, the comparison between methods always involves a joint hypothesis test. The letter discusses the limitations for applied researchers resulting from those restrictions and points to future research directions to overcome them.

GROWSCREEN-Rhizo is a novel phenotyping robot enabling simultaneous measurements of root and shoot growth for plants grown in soil-filled rhizotrons.

Root systems play an essential role in ensuring plant productivity. Experiments conducted in controlled environments and simulation models suggest that root geometry and responses of root architecture to environmental factors should be studied as a priority. However, compared with aboveground plant organs, roots are not easily accessible by non-invasive analyses and field research is still based almost completely on manual, destructive methods. Contributing to reducing the gap between laboratory and field experiments, we present a novel phenotyping system (GROWSCREEN-Rhizo), which is capable of automatically imaging roots and shoots of plants grown in soil-filled rhizotrons (up to a volume of ~18L) with a throughput of 60 rhizotrons per hour. Analysis of plants grown in this setup is restricted to a certain plant size (up to a shoot height of 80cm and root-system depth of 90cm). We performed validation experiments using six different species and for barley and maize, we studied the effect of moderate soil compaction, which is a relevant factor in the field. First, we found that the portion of root systems that is visible through the rhizotrons' transparent plate is representative of the total root system. The percentage of visible roots decreases with increasing average root diameter of the plant species studied and depends, to some extent, on environmental conditions. Second, we could measure relatively minor changes in root-system architecture induced by a moderate increase in soil compaction. Taken together, these findings demonstrate the good potential of this methodology to characterise root geometry and temporal growth responses with relatively high spatial accuracy and resolution for both monocotyledonous and dicotyledonous species. Our prototype will allow the design of high-throughput screening methodologies simulating environmental scenarios that are relevant in the field and will support breeding efforts towards improved resource use efficiency and stability of crop yields.

Reliability of multivariate causality measures for neural data.

In the past decade several multivariate causality measures based on Granger causality have been suggested to assess directionality of neural signals. To date, however, a detailed evaluation of the reliability of these measures is largely missing. We systematically evaluated the performance of five different causality measures (squared partial directed coherence (sPDC), partial directed coherence (PDC), directed transfer function (DTF), direct directed transfer function (dDTF) and transfer function) depending upon data length, noise level, coupling strength, and model order and performed simulations based on four different neural data recording procedures (magnetoencephalography, electroencephalography, electromyography, intraoperative local field potentials). Moreover, we analyzed the effect of two common numerical methods to determine the significance of the particular causality measure (random permutation and the leave one out method (LOOM)). The simulations showed the sPDC combined with the LOOM to be the most reliable and robust choice for assessing directionality in neural data. While DTF and H by construction were unable to distinguish between direct and indirect connections, the dDTF also failed this test. Finally, we applied the causality measures to a real data set. This showed the usefulness of our simulation results for practical applications in order to draw correct inferences and distinguish between conflicting evidence obtained with different causality measures.