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Differential fluorescent staining is an effective tool widely adopted for the visualization, segmentation and quantification of cells and cellular substructures as a part of standard microscopic imaging protocols. Incompatibility of staining agents with viable cells represents major and often inevitable limitations to its applicability in live experiments, requiring extraction of samples at different stages of experiment increasing laboratory costs. Accordingly, development of computerized image analysis methodology capable of segmentation and quantification of cells and cellular substructures from plain monochromatic images obtained by light microscopy without help of any physical markup techniques is of considerable interest. The enclosed set contains human colon adenocarcinoma Caco-2 cells microscopic images obtained under various imaging conditions with different viable vs non-viable cells fractions. Each field of view is provided in a three-fold representation, including phase-contrast microscopy and two differential fluorescent microscopy images with specific markup of viable and non-viable cells, respectively, produced using two different staining schemes, representing a prominent test bed for the validation of image analysis methods.

IntroductionComplex gait disturbances represent one of the prominent manifestations of various neurophysiological conditions, including widespread neurodegenerative disorders such as Alzheimer's and Parkinson's diseases. Therefore, instrumental measurement techniques and automatic computerized analysis appears essential for the differential diagnostics, as well as for the assessment of treatment effectiveness from experimental animal models to clinical settings.MethodsHere we present a marker-free instrumental approach to the analysis of gait disturbances in animal models. Our approach is based on the analysis of video recordings obtained with a camera placed underneath an open field arena with transparent floor using the DeeperCut algorithm capable of online tracking of individual animal body parts, such as the snout, the paws and the tail. The extracted trajectories of animal body parts are next analyzed using an original computerized methodology that relies upon a generalized scalable model based on fractional Brownian motion with parameters identified by detrended partial cross-correlation analysis.ResultsWe have shown that in a mouse model representative movement patterns are characterized by two asymptotic regimes characterized by integrated 1/f noise at small scales and nearly random displacements at large scales separated by a single crossover. More detailed analysis of gait disturbances revealed that the detrended cross-correlations between the movements of the snout, paws and tail relative to the animal body midpoint exhibit statistically significant discrepancies in the Alzheimer's disease mouse model compared to the control group at scales around the location of the crossover.DiscussionWe expect that the proposed approach, due to its universality, robustness and clear physical interpretation, is a promising direction for the design of applied analysis tools for the diagnostics of various gait disturbances and behavioral aspects in animal models. We further believe that the suggested mathematical models could be relevant as a complementary tool in clinical diagnostics of various neurophysiological conditions associated with movement disorders.

In a changing climate, forest ecosystems become increasingly vulnerable to the continuously exacerbating heat and drought stress conditions. Climate stress resilience is governed by a complex interplay of global, regional and local factors, with hydrological conditions among the key roles. Using a modified detrended partial cross-correlation analysis (DPCCA), we analyze the interconnections between long-term tree ring width (TRW) data and regional climate variations at various scales and time lags. By comparing dendrochronological series of Scots pine trees near the southern edge of the boreal ecotone, we investigate how local hydrological conditions affect heat and drought stress resilience of the forest ecosystem. While TRW are negatively correlated with spring and summer temperatures and positively correlated with the Palmer drought severity index (PDSI) in the same year indicating that heat waves and droughts represent the limiting factors, at inter-annual scales remarkable contrasts can be observed between areas with different local hydrological conditions. In particular, for the sphagnum bog area positive TRW trends over several consecutive years tend to follow negative PDSI trends and positive spring and summer temperature trends of the same duration with a time lag between one and three years, indicating that prolonged dry periods, as well as warmer springs and summers appear beneficial for the increased annual growth. In contrast, for the surrounding elevated dry land area a reversed tendency can be observed, with pronounced negative long-term correlations with temperature and positive correlations with PDSI. Moreover, by combining detrending models and partial correlation analysis, we show explicitly that the long-term temperature dependence could be partially attributed to the spurious correlations induced by coinciding trends of the trees ageing and climate warming, while contrasts in correlations between TRW and PDSI become only further highlighted, indicating the major impact of the local hydrological conditions on the drought stress resilience.