ZYZ-168 alleviates cardiac fibrosis after myocardial infarction through inhibition of ERK1/2-dependent ROCK1 activation

Selective treatments for myocardial infarction (MI) induced cardiac fibrosis are lacking. In this study, we focus on the therapeutic potential of a synthetic cardio-protective agent named ZYZ-168 towards MI-induced cardiac fibrosis and try to reveal the underlying mechanism. ZYZ-168 was administered to rats with coronary artery ligation over a period of six weeks. Ecocardiography and Masson staining showed that ZYZ-168 substantially improved cardiac function and reduced interstitial fibrosis. The expression of α–smooth muscle actin (α-SMA) and Collagen I were reduced as was the activity of matrix metalloproteinase 9 (MMP-9). These were related with decreased phosphorylation of ERK1/2 and expression of Rho-associated coiled-coil containing protein kinase 1 (ROCK1). In cardiac fibroblasts stimulated with TGF-β1, phenotypic switches of cardiac fibroblasts to myofibroblasts were observed. Inhibition of ERK1/2 phosphorylation or knockdown of ROCK1 expectedly reduced TGF-β1 induced fibrotic responses. ZYZ-168 appeared to inhibit the fibrotic responses in a concentration dependent manner, in part via a decrease in ROCK 1 expression through inhibition of the phosphorylation status of ERK1/2. For inhibition of ERK1/2 phosphorylation with a specific inhibitor reduced the activation of ROCK1. Considering its anti-apoptosis activity in MI, ZYZ-168 may be a potential drug candidate for treatment of MI-induced cardiac fibrosis

Temporal and spatial variations in the parasitoid complex of the horse chestnut leafminer during its invasion of Europe

The enemy release hypothesis posits that the initial success of invasive species depends on the scarcity and poor adaptation of native natural enemies such as predators and parasitoids. As for parasitoids, invading hosts are first attacked at low rates by a species-poor complex of mainly generalist species. Over the years, however, parasitoid richness may increase either because the invading host continuously encounters new parasitoid species during its spread (geographic spread-hypothesis) or because local parasitoids need different periods of time to adapt to the novel host (adjustment-hypothesis). Both scenarios should result in a continuous increase of parasitoid richness over time. In this study, we reconstructed the development of the hymenopteran parasitoid complex of the invasive leafminer Cameraria ohridella (Lepidoptera, Gracillariidae). Our results show that the overall parasitism rate increases as a function of host residence time as well as geographic and climatic factors, altogether reflecting the historic spread of C. ohridella. The same variables also explain the individual parasitism rates of several species in the parasitoid complex, but fail to explain the abundance of others. Evidence supporting the “geographic spread-hypothesis” was found in the parasitism pattern of Cirrospilus talitzkii (Hymenoptera, Eulophidae), while that of Pediobius saulius, another eulophid, indicated an increase of parasitism rates by behavioral, phenological or biological adjustments. Compared to fully integrated host-parasitoid associations, however, parasitism rates of C. ohridella are still very low. In addition, the parasitoid complex lacks specialists, provided that the species determined are valid and not complexes of cryptic (and presumably more specialized) species. Probably, the adjustment of specialist parasitoids requires more than a few decades, particularly to invaders which establish in ecological niches free of native hosts, thus eliminating any possibility of recruitment of pre-adapted parasitoids

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

2-DE proteomics analysis of drought treated seedlings of Quercus ilex supports a root active strategy for metabolic adaptation in response to water shortage

Holm oak is a dominant tree in the western Mediterranean region. Despite being well adapted to dry hot climate, drought is the main cause of mortality post-transplanting in reforestation programs. An active response to drought is critical for tree establishment and survival. Applying a gel-based proteomic approach, dynamic changes in root proteins of drought treated Quercus ilex subsp. Ballota [Desf.] Samp. seedlings were followed. Water stress was applied on 20 day-old holm oak plantlets by water limitation for a period of 10 and 20 days, each followed by 10 days of recovery. Stress was monitored by changes in water status, plant growth, and electrolyte leakage. Contrary to leaves, holm oak roots responded readily to water shortage at physiological level by growth inhibition, changes in water status and membrane stability. Root proteins were extracted using trichloroacetate/acetone/phenol protocol and separated by two-dimensional electrophoresis. Coomassie colloidal stained gel images were analyzed and spot intensity data subjected to multivariate statistical analysis. Selected consistent spots in three biological replicas, presenting significant changes under stress, were subjected to MALDI-TOF mass spectrometry (peptide mass fingerprinting and MS/MS). For protein identification, combined search was performed with MASCOT search engine over NCBInr Viridiplantae and Uniprot databases. Data are available via ProteomeXchange with identifier PXD002484. Identified proteins were classified into functional groups: metabolism, protein biosynthesis and proteolysis, defense against biotic stress, cellular protection against abiotic stress, intracellular transport. Several enzymes of the carbohydrate metabolism decreased in abundance in roots under drought stress while some related to ATP synthesis and secondary metabolism increased. Results point at active metabolic adjustment and mobilization of the defense system in roots to actively counteract drought stress

The relationship between spectral and plant diversity: Disentangling the influence of metrics and habitat types at the landscape scale

Biodiversity monitoring is crucial for ecosystem conservation, but ground data collection is limited by cost, time, and scale. Remote sensing is a convenient approach providing frequent, near-real-time information with fine resolution over wide areas. According to the Spectral Variation Hypothesis (SVH), spectral diversity (SD) is an effective proxy of environmental heterogeneity, which ultimately relates to plant diversity. So far, studies testing the relationship between SD and biodiversity have reported contradictory findings, calling for a thorough investigation of the key factors (i.e., metrics applied, habitat type, scale, and temporal effects) and conditions under which such a relationship exists. This study investigates the applicability of the SVH for monitoring plant diversity at the landscape scale by comparing the performance of three types of SD metrics. Species richness and functional diversity were calculated for >2000 grid cells of 5 ' x 3 ' covering the Czech Republic. Within each cell, we quantified SD using a Landsat-8 "greenest pixel" composite by applying (i) the standard deviation of NDVI, (ii) Rao's Q entropy index and (iii) the richness of "spectral communities". Habitat type (i.e., land cover) was included in the models of the relationship between SD and ground biodiversity. Both species richness and functional diversity showed positive and significant relationships with each SD metric tested. However, SD alone accounted for a small fraction of the deviance explained by the models. Furthermore, the strength of the relationship depended significantly on habitat type and was highest in natural areas with transitional bushy and herbaceous vegetation. Our results underline that despite the stability of the significance of the relationship between SD and plant diversity at this scale, the applicability of SD for biodiversity monitoring is contextdependent and the factors mediating such a relationship must be carefully considered to avoid misleading conclusions

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

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