temporal dynamics
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Electroencephalography (EEG) studies investigating visuo-spatial working memory (vWM) in aging typically adopt an event-related potential (ERP) analysis approach that has shed light on the age-related changes during item retention and retrieval. However, this approach does not fully enable a detailed description of the time course of the neural dynamics related to aging. The most frequent age-related changes in brain activity have been described by two influential models of neurocognitive aging, the Hemispheric Asymmetry Reduction in Older Adults (HAROLD) and the Posterior-Anterior Shift in Aging (PASA). These models posit that older adults tend to recruit additional brain areas (bilateral as predicted by HAROLD and anterior as predicted by PASA) when performing several cognitive tasks. We tested younger (N = 36) and older adults (N = 35) in a typical vWM task (delayed match-to-sample) where participants have to retain items and then compare them to a sample. Through a data-driven whole scalp EEG analysis we aimed at characterizing the temporal dynamics of the age-related activations predicted by the two models, both across and within different stages of stimulus processing. Behaviorally, younger outperformed older adults. The EEG analysis showed that older adults engaged supplementary bilateral posterior and frontal sites when processing different levels of memory load, in line with both HAROLD and PASA-like activations. Interestingly, these age-related supplementary activations dynamically developed over time. Indeed, they varied across different stages of stimulus processing, with HAROLD-like modulations being mainly present during item retention, and PASA-like activity during both retention and retrieval. Overall, the present results suggest that age-related neural changes are not a phenomenon indiscriminately present throughout all levels of cognitive processing.

Within-host spread of pathogens is an important process for the study of plant-pathogen interactions. However, the development of plant-pathogen lesions remains practically difficult to characterize and quantify beyond the common traits such as lesion area. We tackle the spatio-temporal dynamics of interactions by combining image-based phenotyping with mathematical modelling. We consider the spread of Peyronellaea pinodes on pea stipules that were monitored daily with visible imaging. We assume that pathogen propagation on host-tissues can be described by the Fisher-KPP model where lesion spread depends on both a logistic local growth and an homogeneous diffusion. Model parameters are estimated using a variational data assimilation approach on sets of registered images. This modelling framework is used to compare the spread of an aggressive isolate on two pea cultivars with contrasted levels of partial resistance. We show that the expected slower spread on the most resistant cultivar is actually due to a decrease of diffusion and, to a lesser extent, local growth. These results demonstrate that spatial models with imaging allows one to disentangle the processes involved in host-pathogen interactions. Hence, promoting model-based phenotyping of interactions would allow a better identification of quantitative traits thereafter used in genetics and ecological studies.

Background The understanding of longitudinal changes in the urinary microbiota of healthy women and its relation to intestinal microbiota is limited. Methods From a cohort of 15 premenopausal women without known urogenital disease or current symptoms, we collected catheter urine (CU), vaginal and periurethral swabs, and fecal samples on four visits over six months. Additionally, ten participants provided CU and midstream urine (MU) to assess comparability. Urine was subjected to expanded culture. 16S rRNA gene sequencing was performed on all urine, fecal, and selected vaginal and periurethral samples. Sequence reads were processed (DADA2 pipeline) and analyzed using QIIME 2 and R. Results Relative abundances of urinary microbiota were variable over 6–18 months. The degree of intraindividual variability of urinary microbiota was higher than that found in fecal samples. Still, nearly half of the observed beta diversity of all urine samples could be attributed to differences between volunteers (R2 = 0.48, p = 0.001). After stratification by volunteer, time since last sexual intercourse was shown to be a factor significantly contributing to beta diversity (R2 = 0.14, p = 0.001). We observed a close relatedness of urogenital microbial habitats and a clear distinction from intestinal microbiota in the overall betadiversity analysis. Microbiota compositions derived from MU differed only slightly from CU compositions. Within this analysis of low-biomass samples, we identified contaminating sequences potentially stemming from sequencing reagents. Conclusions Results from our longitudinal cohort study confirmed the presence of a rather variable individual urinary microbiota in premenopausal women. These findings from catheter urine complement previous observations on temporal dynamics in voided urine. The higher intraindividual variability of urinary microbiota as compared to fecal microbiota will be a challenge for future studies investigating associations with urogenital diseases and aiming at identifying pathogenic microbiota signatures.

Objective: Impaired cerebral blood flow (CBF) regulation, such as reduced reactivity to hypercapnia, contributes to the pathophysiology after aneurysmal subarachnoid hemorrhage (SAH), but temporal dynamics in the acute phase are unknown. Featuring comparable molecular regulation mechanisms, the retinal vessels participate in chronic and subacute stroke- and SAH-associated vessel alterations in patients and can be studied non-invasively. This study is aimed to characterize the temporal course of the cerebral and retinal vascular reactivity to hypercapnia in the acute phase after experimental SAH and compare the potential degree of impairment.Methods: Subarachnoid hemorrhage was induced by injecting 0.5 ml of heparinized autologous blood into the cisterna magna of male Wistar rats using two anesthesia protocols [isoflurane/fentanyl n = 25 (Sham + SAH): Iso—Group, ketamine/xylazine n = 32 (Sham + SAH): K/X—Group]. CBF (laser speckle contrast analysis) and physiological parameters were measured continuously for 6 h. At six predefined time points, hypercapnia was induced by hypoventilation controlled via blood gas analysis, and retinal vessel diameter (RVD) was determined non-invasively.Results: Cerebral reactivity and retinal reactivity in Sham groups were stable with only a slight attenuation after 2 h in RVD of the K/X—Group. In the SAH Iso—Group, cerebral and retinal CO2 reactivity compared to baseline was immediately impaired starting at 30 min after SAH (CBF p = 0.0090, RVD p = 0.0135) and lasting up to 4 h (p = 0.0136, resp. p = 0.0263). Similarly, in the K/X—Group, cerebral CO2 reactivity was disturbed early after SAH (30 min, p = 0.003) albeit showing a recovery to baseline after 2 h while retinal CO2 reactivity was impaired over the whole observation period (360 min, p = 0.0001) in the K/X—Group. After normalization to baseline, both vascular beds showed a parallel behavior regarding the temporal course and extent of impairment.Conclusion: This study provides a detailed temporal analysis of impaired cerebral vascular CO2 reactivity starting immediately after SAH and lasting up to 6 h. Importantly, the retinal vessels participate in these acute changes underscoring the promising role of the retina as a potential non-invasive screening tool after SAH. Further studies will be required to determine the correlation with functional outcomes.

Wheat is an important cereal crop species consumed globally. The growing global population demands a rapid and sustainable growth of agricultural systems. The development of genetically efficient wheat varieties has solved the global demand for wheat to a greater extent. The use of chemical substances for pathogen control and chemical fertilizers for enhanced agronomic traits also proved advantageous but at the cost of environmental health. An efficient alternative environment-friendly strategy would be the use of beneficial microorganisms growing on plants, which have the potential of controlling plant pathogens as well as enhancing the host plant’s water and mineral availability and absorption along with conferring tolerance to different stresses. Therefore, a thorough understanding of plant-microbe interaction, identification of beneficial microbes and their roles, and finally harnessing their beneficial functions to enhance sustainable agriculture without altering the environmental quality is appealing. The wheat microbiome shows prominent variations with the developmental stage, tissue type, environmental conditions, genotype, and age of the plant. A diverse array of bacterial and fungal classes, genera, and species was found to be associated with stems, leaves, roots, seeds, spikes, and rhizospheres, etc., which play a beneficial role in wheat. Harnessing the beneficial aspect of these microbes is a promising method for enhancing the performance of wheat under different environmental stresses. This review focuses on the microbiomes associated with wheat, their spatio-temporal dynamics, and their involvement in mitigating biotic and abiotic stresses.

Abstract. The prediction of species geographic redistribution under climate change (i.e. range shifts) has been addressed by both experimental and modelling approaches and can be used to inform efficient policy measures on the functioning and services of future ecosystems. Dynamic Global Vegetation Models (DGVMs) are considered state-of-the art tools to understand and quantify the spatio-temporal dynamics of ecosystems at large scales and their response to changing environments. They can explicitly include local vegetation dynamics relevant to migration (establishment, growth, seed production), species-specific dispersal abilities and the competitive interactions with other species in the new environment. However, the inclusion of more detailed mechanistic formulations of range shift processes may also widen the overall uncertainty of the model. Thus, a quantification of these uncertainties is needed to evaluate and improve our confidence in the model predictions. In this study, we present an efficient assessment of parameter and model uncertainties combining low-cost analyses in successive steps: local sensitivity analysis, exploration of the performance landscape at extreme parameter values, and inclusion of relevant ecological processes in the model structure. This approach was tested on the newly-implemented migration module of the state-of-the-art DGVM, LPJ-GM 1.0. Estimates of post-glacial migration rates obtained from pollen and macrofossil records of dominant European tree taxa were used to test the model performance. The results indicate higher sensitivity of migration rates to parameters associated with the dispersal kernel (dispersal distances and kernel shape) compared to plant traits (germination rate and maximum fecundity) and highlight the importance of representing rare long-distance dispersal events via fat-tailed kernels. Overall, the successful parametrization and model selection of LPJ-GM will allow simulating plant migration with a more mechanistic approach at larger spatial and temporal scales, thus improving our efforts to understand past vegetation dynamics and predict future range shifts in a context of global change.