Transcript profiling of serine- and cysteine protease inhibitors in Triticum aestivum varieties with different drought tolerance

A high number of protease inhibitors (PI) have been identified in diverse plant species but information about their role in plant stress responses is still fragmentary. Transcript profiling of six published serine and cysteine protease inhibitor sequences in water-deprived plants from four winter wheat (Triticum aestivum) varieties with varying tolerance was performed in order to outline PIs predominantly accumulating under drought. Expression was analyzed by real time RT-qPCR. Considerable transcript accumulation of Bowman-Birk type PI WALI3 (BBPI) was detected in drought stressed leaves suggesting an important regulatory role of BBPI in adjustment of protein metabolism in leaves under dehydration. Serpin transcripts were less represented in water-deprived plants. Transient accumulation of cystatin transcripts revealed organ-specificity. Under drought cystatin and serpin expression in the leaves of the most drought tolerant variety “Katya” tended to preserve relatively stable levels close to the controls. This preliminary data will serve for future detailed study of regulation of proteolysis in winter wheat subjected to unfavorable environmental factors for development of molecular-based strategies for selection of tolerant varieties

Characterization of Moment of Inertia Variations by Holographic Interferometry

Holographic interferometry (HI) is a powerful tool for mapping of surface defects. In conjunction with various stressing techniques [l–4], it offers an NDT tool for the detection of flaws within the volume of materials. The method is advantageous for integrity characterization of components to serve under mechanical stress, where the detailed shape, size and depth of the flaw within the material are of no interest. For most applications, where integrity is tested, the moment of inertia may be used as a measure for classification of the product and for the estimation of its reliability. The presence of volumetric flaws, when the sample is under loading, is expressed in the holographic interferogram. The exterma of the fringe pattern are used for determination of the displacement distribution. The second derivative of the displacement distribution is related to the bending moment and the moment of inertia. The moment of inertia may be further processed to obtain a function free from degrading influence of the specific measuring system employed [5]

Quality control of B-lines analysis in stress Echo 2020

Background The effectiveness trial “Stress echo (SE) 2020” evaluates novel applications of SE in and beyond coronary artery disease. The core protocol also includes 4-site simplified scan of B-lines by lung ultrasound, useful to assess pulmonary congestion. Purpose To provide web-based upstream quality control and harmonization of B-lines reading criteria. Methods 60 readers (all previously accredited for regional wall motion, 53 B-lines naive) from 52 centers of 16 countries of SE 2020 network read a set of 20 lung ultrasound video-clips selected by the Pisa lab serving as reference standard, after taking an obligatory web-based learning 2-h module ( http://se2020.altervista.org ). Each test clip was scored for B-lines from 0 (black lung, A-lines, no B-lines) to 10 (white lung, coalescing B-lines). The diagnostic gold standard was the concordant assessment of two experienced readers of the Pisa lab. The answer of the reader was considered correct if concordant with reference standard reading ±1 (for instance, reference standard reading of 5 B-lines; correct answer 4, 5, or 6). The a priori determined pass threshold was 18/20 (≥ 90%) with R value (intra-class correlation coefficient) between reference standard and recruiting center) > 0.90. Inter-observer agreement was assessed with intra-class correlation coefficient statistics. Results All 60 readers were successfully accredited: 26 (43%) on first, 24 (40%) on second, and 10 (17%) on third attempt. The average diagnostic accuracy of the 60 accredited readers was 95%, with R value of 0.95 compared to reference standard reading. The 53 B-lines naive scored similarly to the 7 B-lines expert on first attempt (90 versus 95%, p = NS). Compared to the step-1 of quality control for regional wall motion abnormalities, the mean reading time per attempt was shorter (17 ± 3 vs 29 ± 12 min, p < .01), the first attempt success rate was higher (43 vs 28%, p < 0.01), and the drop-out of readers smaller (0 vs 28%, p < .01). Conclusions Web-based learning is highly effective for teaching and harmonizing B-lines reading. Echocardiographers without previous experience with B-lines learn quickly.info:eu-repo/semantics/publishedVersio

Double down on remote sensing for biodiversity estimation. A biological mindset

In the light of unprecedented planetary changes in biodiversity, real-time and accurate ecosystem and biodiversity assessments are becoming increasingly essential for informing policy and sustainable development. Biodiversity monitoring is a challenge, especially for large areas such as entire continents. Nowadays, spaceborne and airborne sensors provide information that incorporate wavelengths that cannot be seen nor imagined with the human eye. This is also now accomplished at unprecedented spatial resolutions, defined by the pixel size of images, achieving less than a meter for some satellite images and just millimeters for airborne imagery. Thanks to different modeling techniques, it is now possible to study functional diversity changes over different spatial and temporal scales. At the heart of this unifying framework are the “spectral species”—sets of pixels with a similar spectral signal—and their variability over space. The aim of this paper is to summarize the power of remote sensing for directly estimating plant species diversity, particularly focusing on the spectral species concept

Under the mantra: ‘Make use of colorblind friendly graphs’

Colorblindness is a genetic condition that affects a person's ability to accurately perceive colors. Several papers still exist making use of rainbow colors palette to show output. In such cases, for colorblind people such graphs are meaningless. In this paper, we propose good practices and coding solutions developed in the R Free and Open Source Software to (i) simulate colorblindness, (ii) develop colorblind friendly color palettes and (iii) provide the tools for converting a noncolorblind friendly graph into a new image with improved colors

Scale mismatches between predictor and response variables in species distribution modelling: A review of practices for appropriate grain selection

There is a lack of guidance on the choice of the spatial grain of predictor and response variables in species distribution models (SDM). This review summarizes the current state of the art with regard to the following points: (i) the effects of changing the resolution of predictor and response variables on model performance; (ii) the effect of conducting multi-grain versus single-grain analysis on model performance; and (iii) the role of land cover type and spatial autocorrelation in selecting the appropriate grain size. In the reviewed literature, we found that coarsening the resolution of the response variable typically leads to declining model performance. Therefore, we recommend aiming for finer resolutions unless there is a reason to do otherwise (e.g. expert knowledge of the ecological scale). We also found that so far, the improvements in model performance reported for multi-grain models have been relatively low and that useful predictions can be generated even from single-scale models. In addition, the use of high-resolution predictors improves model performance; however, there is only limited evidence on whether this applies to models with coarser-resolution response variables (e.g. 100 km2 and coarser). Low-resolution predictors are usually sufficient for species associated with fairly common environmental conditions but not for species associated with less common ones (e.g. common vs rare land cover category). This is because coarsening the resolution reduces variability within heterogeneous predictors and leads to underrepresentation of rare environments, which can lead to a decrease in model performance. Thus, assessing the spatial autocorrelation of the predictors at multiple grains can provide insights into the impacts of coarsening their resolution on model performance. Overall, we observed a lack of studies examining the simultaneous manipulation of the resolution of predictor and response variables. We stress the need to explicitly report the resolution of all predictor and response variables

Scientific maps should reach everyone: The cblindplot R package to let colour blind people visualise spatial patterns

Maps represent powerful tools to show the spatial variation of a variable in a straightforward manner. A crucial aspect in map rendering for its interpretation by users is the gamut of colours used for displaying data. One part of this problem is linked to the proportion of the human population that is colour blind and, therefore, highly sensitive to colour palette selection. The aim of this paper is to present the cblindplot R package and its founding function - cblind.plot() - which enables colour blind people to just enter an image in a coding workflow, simply set their colour blind deficiency type, and immediately get as output a colour blind friendly plot. We will first describe in detail colour blind problems, and then show a step by step example of the function being proposed. While examples exist to provide colour blind people with proper colour palettes, in such cases (i) the workflow include a separate import of the image and the application of a set of colour ramp palettes and (ii) albeit being well documented, there are many steps to be done before plotting an image with a colour blind friendly ramp palette. The function described in this paper, on the contrary, allows to (i) automatically call the image inside the function without any initial import step and (ii) explicitly refer to the colour blind deficiency type being experienced, to further automatically apply the proper colour ramp palette

rasterdiv ‐ an Information Theory tailored R package for measuring ecosystem heterogeneity from space: to the origin and back

Ecosystem heterogeneity has been widely recognized as a key ecological indicator of several ecological functions, diversity patterns and change, metapopulation dynamics, population connectivity or gene flow. In this paper, we present a new R package—rasterdiv—to calculate heterogeneity indices based on remotely sensed data. We also provide an ecological application at the landscape scale and demonstrate its power in revealing potentially hidden heterogeneity patterns. The rasterdiv package allows calculating multiple indices, robustly rooted in Information Theory, and based on reproducible open-source algorithms

Transcriptomic and epigenomic profiling reveals altered responses to diesel emissions in Alzheimer's disease both in vitro and in population-based data

INTRODUCTION: Studies have correlated living close to major roads with Alzheimer's disease (AD) risk. However, the mechanisms responsible for this link remain unclear. METHODS: We exposed olfactory mucosa (OM) cells of healthy individuals and AD patients to diesel emissions (DE). Cytotoxicity of exposure was assessed, mRNA, miRNA expression, and DNA methylation analyses were performed. The discovered altered pathways were validated using data from the human population-based Rotterdam Study. RESULTS: DE exposure resulted in an almost four-fold higher response in AD OM cells, indicating increased susceptibility to DE effects. Methylation analysis detected different DNA methylation patterns, revealing new exposure targets. Findings were validated by analyzing data from the Rotterdam Study cohort and demonstrated a key role of nuclear factor erythroid 2–related factor 2 signaling in responses to air pollutants. DISCUSSION: This study identifies air pollution exposure biomarkers and pinpoints key pathways activated by exposure. The data suggest that AD individuals may face heightened risks due to impaired cellular defenses. Highlights: Healthy and AD olfactory cells respond differently to DE exposure. AD cells are highly susceptible to DE exposure. The NRF2 oxidative stress response is highly activated upon air pollution exposure. DE-exposed AD cells activate the unfolded protein response pathway. Key findings are also confirmed in a population-based study.</p