Mueller polarimetric imaging for fast macroscopic mapping of microscopic collagen matrix remodeling by smooth muscle cells.

Smooth muscle cells (SMCs) are critical players in cardiovascular disease development and undergo complex phenotype switching during disease progression. However, SMC phenotype is difficult to assess and track in co-culture studies. To determine the contractility of SMCs embedded within collagen hydrogels, we performed polarized light imaging and subsequent analysis based on Mueller matrices. Measurements were made both in the absence and presence of endothelial cells (ECs) in order to establish the impact of EC-SMC communication on SMC contractility. The results demonstrated that Mueller polarimetric imaging is indeed an appropriate tool for assessing SMC activity which significantly modifies the hydrogel retardance in the presence of ECs. These findings are consistent with the idea that EC-SMC communication promotes a more contractile SMC phenotype. More broadly, our findings suggest that Mueller polarimetry can be a useful tool for studies of spatial heterogeneities in hydrogel remodeling by SMCs.

Differences in spatial versus temporal reaction norms for spring and autumn phenological events.

For species to stay temporally tuned to their environment, they use cues such as the accumulation of degree-days. The relationships between the timing of a phenological event in a population and its environmental cue can be described by a population-level reaction norm. Variation in reaction norms along environmental gradients may either intensify the environmental effects on timing (cogradient variation) or attenuate the effects (countergradient variation). To resolve spatial and seasonal variation in species' response, we use a unique dataset of 91 taxa and 178 phenological events observed across a network of 472 monitoring sites, spread across the nations of the former Soviet Union. We show that compared to local rates of advancement of phenological events with the advancement of temperature-related cues (i.e., variation within site over years), spatial variation in reaction norms tend to accentuate responses in spring (cogradient variation) and attenuate them in autumn (countergradient variation). As a result, among-population variation in the timing of events is greater in spring and less in autumn than if all populations followed the same reaction norm regardless of location. Despite such signs of local adaptation, overall phenotypic plasticity was not sufficient for phenological events to keep exact pace with their cues-the earlier the year, the more did the timing of the phenological event lag behind the timing of the cue. Overall, these patterns suggest that differences in the spatial versus temporal reaction norms will affect species' response to climate change in opposite ways in spring and autumn.

Author Correction: Chronicles of nature calendar, a long-term and large-scale multitaxon database on phenology.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Chronicles of nature calendar, a long-term and large-scale multitaxon database on phenology.

We present an extensive, large-scale, long-term and multitaxon database on phenological and climatic variation, involving 506,186 observation dates acquired in 471 localities in Russian Federation, Ukraine, Uzbekistan, Belarus and Kyrgyzstan. The data cover the period 1890-2018, with 96% of the data being from 1960 onwards. The database is rich in plants, birds and climatic events, but also includes insects, amphibians, reptiles and fungi. The database includes multiple events per species, such as the onset days of leaf unfolding and leaf fall for plants, and the days for first spring and last autumn occurrences for birds. The data were acquired using standardized methods by permanent staff of national parks and nature reserves (87% of the data) and members of a phenological observation network (13% of the data). The database is valuable for exploring how species respond in their phenology to climate change. Large-scale analyses of spatial variation in phenological response can help to better predict the consequences of species and community responses to climate change.