Extracellular Vesicle Associated miRNAs Regulate Signaling Pathways Involved in COVID-19 Pneumonia and the Progression to Severe Acute Respiratory Corona Virus-2 Syndrome

BackgroundExtracellular vesicles (EVs) are mediators of cell-to-cell communication in inflammatory lung diseases. They function as carriers for miRNAs which regulate mRNA transcripts and signaling pathways after uptake into recipient cells. We investigated whether miRNAs associated with circulating EVs regulate immunologic processes in COVID-19.MethodsWe prospectively studied 20 symptomatic patients with COVID-19 pneumonia, 20 mechanically ventilated patients with severe COVID-19 (severe acute respiratory corona virus-2 syndrome, ARDS) and 20 healthy controls. EVs were isolated by precipitation, total RNA was extracted, profiled by small RNA sequencing and evaluated by differential gene expression analysis (DGE). Differentially regulated miRNAs between groups were bioinformatically analyzed, mRNA target transcripts identified and signaling networks constructed, thereby comparing COVID-19 pneumonia to the healthy state and pneumonia to severe COVID-19 ARDS.ResultsDGE revealed 43 significantly and differentially expressed miRNAs (25 downregulated) in COVID-19 pneumonia when compared to controls, and 20 miRNAs (15 downregulated) in COVID-19 ARDS patients in comparison to those with COVID-19 pneumonia. Network analysis for comparison of COVID-19 pneumonia to healthy controls showed upregulated miR-3168 (log2FC=2.28, padjusted<0.001), among others, targeting interleukin-6 (IL6) (25.1, 15.2 - 88.2 pg/ml in COVID-19 pneumonia) and OR52N2, an olfactory smell receptor in the nasal epithelium. In contrast, miR-3168 was significantly downregulated in COVID-19 ARDS (log2FC=-2.13, padjusted=0.003) and targeted interleukin-8 (CXCL8) in a completely activated network. Toll-like receptor 4 (TLR4) was inhibited in COVID-19 pneumonia by miR-146a-5p and upregulated in ARDS by let-7e-5p.ConclusionEV-derived miRNAs might have important regulative functions in the pathophysiology of COVID-19: CXCL8 regulates neutrophil recruitment into the lung causing epithelial damage whereas activated TLR4, to which SARS-CoV-2 spike protein binds strongly, increases cell surface ACE2 expression and destroys type II alveolar cells that secrete pulmonary surfactants; both resulting in pulmonary-capillary leakage and ARDS. These miRNAs may serve as biomarkers or as possible therapeutic targets.

Documentary-based climate reconstructions in the Czech Lands 1501–2020 CE and their European context

Annual and seasonal temperature, precipitation and drought index (SPI, SPEI, Z-index, PDSI) series covering the Czech Lands territory (now the Czech Republic) over 520 years (1501–2020 CE) reconstructed from documentary data combined with instrumental observations were analysed herein. The temperature series exhibits a statistically significant increasing trend, rising from ~1890 and particularly from the 1970s; 1991–2020 represents the warmest and driest 30-year period since 1501 CE. While the long-term precipitation total fluctuations (and derived SPI fluctuations) remain relatively stable with annual and decadal variabilities, past temperature increases are the key factor affecting recent increasing dryness in the SPEI, Z-index and PDSI series. The seasonal temperature series represent a broad European area, while the seasonal precipitation series show lower spatial correlations. A statistical attribution analysis conducted utilizing regression and wavelet techniques confirmed the influence of covariates related to volcanic activity (prompting temporary temperature decreases, especially during summer) and the North Atlantic Oscillation (influential in all seasons except summer) in the Czech climate reconstructions. Furthermore, components tied to multidecadal variabilities in the northern Atlantic and northern Pacific were identified in the temperature and precipitation series and in the drought indices, revealing notable shared oscillations, particularly at periods of approximately 70–100 years.

Effect of mature spruce forest on canopy interception in subalpine conditions during three growing seasons

The interception process in subalpine Norway spruce stands plays an important role in the distribution of throughfall. The natural mountain spruce forest where our measurements of throughfall and gross precipitation were carried out, is located on the tree line at an elevation of 1,420 m a.s.l. in the Western Tatra Mountains (Slovakia, Central Europe). This paper presents an evaluation of the interception process in a natural mature spruce stand during the growing season from May to October in 2018–2020. We also analyzed the daily precipitation events within each growing season and assigned to them individual synoptic types. The amount and distribution of precipitation during the growing season plays an important role in the precipitation-interception process, which confirming the evaluation of individual synoptic situations. During the monitored growing seasons, precipitation was normal (2018), sub-normal (2019) and above-normal (2020) in comparison with long-term precipitation (1988–2017). We recorded the highest precipitation in the normal and above-normal precipitation years during the north-eastern cyclonic synoptic situation (NEc). During these two periods, interception showed the lowest values in the dripping zone at the crown periphery, while in the precipitation sub-normal period (2019), the lowest interception was reached by the canopy gap. In the central crown zone near the stem, interception reached the highest value in each growing season. In the evaluated vegetation periods, interception reached values in the range of 19.6–24.1% of gross precipitation total in the canopy gap, 8.3–22.2% in the dripping zone at the crown periphery and 45.7–51.6% in the central crown zone near the stem. These regimes are expected to change in the Western Tatra Mts., as they have been affected by windstorms and insect outbreaks in recent decades. Under disturbance regimes, changes in interception as well as vegetation, at least for some period of time, are unavoidable.

Reversibility of Historical and Future Climate Change with a Complex Earth System Model

The reversibility of a wide range of components of the earth system was investigated by comparing forward and time-reversed historical and future simulations of a coupled earth system model known as the Beijing Normal University earth system model. Many characteristics of the climate system, including the surface temperature, ocean heat content (OHC), convective precipitation, total runoff, ground evaporation, soil moisture, sea ice extent and Atlantic Meridional Overturning Circulation, did not fully return to their initial values when the historical or future natural and anthropogenic forcing agents were reversed. The surface temperature and OHC declines lagged behind the decline in greenhouse gases (GHGs). Reverses in other variables occurred in direct response to the decline in GHGs. The sea level increased, even after all of the forces returned to the original values. Furthermore, most of the climate variables did not return to their original values because of thermal inertial. The end states of variables, other than those related to thermal storage, mainly depended on the original state of the natural and anthropogenic forces, and were unaffected by the future growth rate of the GHGs. The climate policy implication of this study is that climate change cannot be completely reversed even if all the external forces are returned to their initial values.

Agroclimatic atlas - prototype

<p><span>Our contribution presents a prototype of Agroclimatic atlas - a web map application, presenting agroclimatic factors: </span><span>Frost-free period, </span>Water balance, Total precipitation, Total solar radiation, Last date with soil temperature above 10 °C for nitrogen application, Number of days with growing temperatures for a crop, Number of days with optimal growing temperatures for a crop HSU - Heat stress units for a crop, <span>The factors are calculated based on algorithms described in </span><em><span>Calculation of Agro-Climatic Factors from Global Climatic Data</span></em><span> (Jedlička et al. 2021, doi:  </span><span>10.3390/app11031245</span><span>).</span></p><p><span>The agroclimatic atlas application aims to provide a comprehensive overview of agriculture-related climatic characteristics of an area of interest in a time retrospective.  The application can be used by both an individual farmer or a precision farming expert exploring a wider area.</span></p><p><span>The principal source of climatic variables (such as temperature, rainfall, evaporation, runoff, and solar radiation) used in the atlas is the </span><span>ERA5-Land dataset</span><span> (available as the </span><span>Copernicus Climate Change Service (C3S) at its Climate Date Store</span><span>). </span></p><p><span>The contemporary version of the Agroclimatic Atlas application is accessible from here https://www.mdpi.com/2076-3417/11/3/1245#</span><span>. This version is in Czech only and portrays data from Czechia 10 years backward. However, the application is under ongoing development driven by the H2020 projects </span><span>Stargate</span><span>, </span><span>Sieusoil</span><span>, and </span><span>Smartagrihubs</span><span>. Therefore a newer version will be presented at the conference. The first design concepts can be seen in the figure below.</span></p><p><img src="https://contentmanager.copernicus.org/fileStorageProxy.php?f=gnp.475eafd0808065334309161/sdaolpUECMynit/1202SME&app=m&a=0&c=31dbfa2ddfd3719b82491d259ccc4117&ct=x&pn=gnp.elif&d=1" alt=""></p><p>Figure 1. - Mockup of Agroclimatic atlas application, accessible from https://xd.adobe.com/view/65199b72-db2f-420a-aee2-bc90dc83aaea-304a/</p>

Uncertainties in ERA-5 and UERRA reanalyses detected by adjusted radar precipitation - a regional study for the Czech Republic

<p>Regional reanalysis constitute of potentially attractive new data source for many applications. They can offer added value benefiting from their higher spatial and temporal resolution. On the other hand, similarly as other data sources in regular network, reanalysis comes with uncertainties especially in the case of extremes.</p><p>The monitoring capability of reanalysis is essential for their usage as the reference datasets for climate model validation as well as for hydrological models. In this contribution, we evaluate the agreement of precipitation between modern reanalysis products (Era5, Era5 Land, Harmonie and Mescan-Surfex; with resolution between 5.5 and 32 km) and observed data at different time scales, from annual to subdaily. Studied characteristics of precipitation are for instance annual cycle of precipitation amount and the number of wet days, diurnal cycle of precipitation, and extremes. The common period for all datasets is 2002 – 2018.</p><p>Observed data used in this study are represented by adjusted radar-derived precipitation totals in 1km raster over the Czech Republic. The adjusted radar-derived precipitation totals are gained as follows. First, the radar-derived rain field is spatially adjusted to measurements from the rain gauges as a whole. For each day, the ratio between the mean 1-day precipitation total calculated from all rain gauges and the mean 1-day precipitation total estimated from the corresponding radar pixels is determined and used for a multiplication of radar-derived precipitation in every pixel of the radar domain. Second, the spatially adjusted radar-derived rain rates are locally adjusted in individual pixels based on the distance from the closest rain gauge, whereas the weight of the observed precipitation is decreasing with increasing distance to the given pixel. Adjusted daily precipitation total is then divided according to 10 min radar-derived estimates, from which the precipitation accumulations of longer duration are calculated.</p>

Modeling of the Geological Probability Procedure for the Prediction of High Flows in Small Streams, Case Study of Medvednica Mt., Croatia

Floods are defined by maximum water levels or flow of high-water waves. Here, we defined the deterministic method for the calculation of the probability of a high discharge event, named as the Probability Of Success (POS). The POS method previously developed for petroleum subsurface systems has been modified for the surface hydrological system with the purpose of flood prediction. The case study of this research is the small basin of Kašina Stream on Medvednica Mt. (NW Croatia). The data are obtained upstream from the hydrological station Gornja Kašina. The POS model is defined by four categories. Each geological category is described with accompanied events and probabilities. Floods are defined by four categories: total precipitation, total water flow, basement, and maximal water capacity in soil. The categories total precipitation and basement were divided into two sub-categories each: quantity and duration; porosity and soil depth. Data are collected for a hydrometeorological event, namely an intensive convective storm on 24–25 July 2020, when Zagreb was locally hit by heavy urban floods. The presented probability method yielded a probability of 1.76% that such an event could happen to the station. However, the flooding was not recorded. A comparison of the real event and the predicted probability supported the adequacy and applicability of the method, showing it has high reliability. The presented probability model could be easily applied, with small modifications, to the entire area of Northern Croatia for the prediction of small basin flooding events.

Projection of the Precipitation Extremes in Thailand Under Climate Change Scenario RCP8.5

This study explores the predicted extreme precipitation during 2020–2029 in Thailand, using the output of the nested regional climate model (NRCM) with the Representative Concentration Pathway (RCP) 8.5 emission scenario. The research used five different extreme precipitation indices, i.e., annual precipitation total (PRCPTOT), the annual number of rainy days (RD), simple daily intensity index (SDII), consecutive dry days (CDDs), and consecutive wet days (CWD). The PRCTOT was generally located in eastern Thailand, with significant declining trends, while the increasing trend was found in northern Thailand. The quantity of the PRCPTOT varies marginally from 100 to 200 mm per decade. The annual RD was influenced mostly by the negative trends in Thailand. A remarkable trend is a rising of annual SDII, with major statistical increases ranging from 5 to 20%. A widespread decline in CWD was found in most regions. The statistically significant pattern of CWD has been geographically concentrated in the northern, southern, and eastern regions of Thailand. Southern Thailand continues to decline by −10 to −30%. A drastic decline has been observed in the south of Thailand. Projected interannual precipitation variability shows that December–January–February (DJF) variability will be greater than either annual or June–July–August (JJA) variability in most years, with the exception of 2022, 2025, and 2026, in which the JJA variability will be greater than both the annual variability and the DJF variability.

Moisture Variation with Cloud Effects during a BSISO over the Eastern Maritime Continent in a Cloud-Permitting-Scale Simulation

Despite the great importance of interactions between moisture, clouds, radiation, and convection in the Madden-Julian Oscillation, their role in the boreal summer intraseasonal oscillation (BSISO) has not been well established. This study investigates the moisture variation of a BSISO during its rapid redevelopment over the eastern Maritime Continent through a cloud-permitting-scale numerical simulation. It is found that moisture variation depends closely on the evolution of clouds and precipitation. Total moisture budget analysis reveals that the deepening and strengthening (lessening) of humidity before (after) the BSISO deep convection are attributed largely to zonal advection. In addition, the column moistening/drying is mostly in phase with the humidity and is related to the maintenance of BSISO.An objective cloud-type classification method and a weak temperature gradient approximation are used to further understand the column moistening/drying. Results indicate that elevated stratiform clouds play a significant role in moistening the lower troposphere through cloud water evaporation. Decreases in deep convection condensation and re-evaporation of deep stratiform precipitation induce moistening during the development and after the decay of BSISO deep convection, respectively. Meanwhile, anomalous longwave radiative heating appears first in the lower troposphere during the developing stage of BSISO, further strengthens via the increase of deep stratiform clouds, and eventually deepens with elevated stratiform clouds. Accordingly, anomalous moistening largely in phase with the humidity of BSISO toward its suppressed stage is induced via compensated ascent. Owing to the anomalous decrease in the ratio of vertical moisture and potential temperature gradients, the cloud-radiation effect is further enhanced in the convective phase of BSISO.

Trends and possible causes of cloudiness variability in Montenegro in the period 1961-2017

Cloudiness is an important climate parameter, and it is closely related to insolation, temperature, and precipitation. Total cloud cover (TCC) data along with the number of cloudless (CL) and overcast (OC) days from 18 stations in Montenegro during the period 1961-2017 were used to determine the seasonal trends and possible causes of cloudiness variability. The Mann-Kendall test and Sen’s slope were used for trend detection. We found statistically significant (p < 0.05 and p < 0.10) decreasing (increasing) trends in TCC (the number of CL days) in winter, spring and summer. The exception was in autumn, when an increase (decrease) in the TCC (CL days) was shown, but in most cases, these changes were insignificant. The number of OC days declined in coastal and central regions, while a positive trend was found in the northern region for all seasons. The increase in the number of CL days during the summer and winter was more pronounced compared to the decreasing trend in the number of OC days. Pearson’s correlation (r) was used to access the relationship between cloudiness and principal modes of atmospheric variability such as North Atlantic Oscillation (NAO), Summer North Atlantic Oscillation (SNAO), Arctic Oscillation (AO), East Atlantic Oscillation (EA), East Atlantic-West Russian Oscillation (EAWR), Scandinavian Pattern (SCAND), Polar-Eurasian Oscillation (POLEUR), North Sea-Caspian Pattern (NCP), and South Oscillation (SOI) as well as regional patterns of climate variability—the Mediterranean Oscillation (MOI) and Western Mediterranean Oscillation (WeMO). A significant consistency (r > 0.60, p < 0.05) was found between time series of certain atmospheric circulation patterns and cloud parameters (NAO, AO, EAWR, SCAND, NCP, and MOI-1), especially in the colder half of the year.