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Abstract Chronic liver diseases are worldwide on the rise. Due to the rapidly increasing incidence, in particular in Western countries, metabolic dysfunction-associated steatotic liver disease (MASLD) is gaining importance as the disease can develop into hepatocellular carcinoma. Lipid accumulation in hepatocytes has been identified as the characteristic structural change in MASLD development, but molecular mechanisms responsible for disease progression remained unresolved. Here, we uncover in primary hepatocytes from a preclinical model fed with a Western diet (WD) an increased basal MET phosphorylation and a strong downregulation of the PI3K-AKT pathway. Dynamic pathway modeling of hepatocyte growth factor (HGF) signal transduction combined with global proteomics identifies that an elevated basal MET phosphorylation rate is the main driver of altered signaling leading to increased proliferation of WD-hepatocytes. Model-adaptation to patient-derived hepatocytes reveal patient-specific variability in basal MET phosphorylation, which correlates with patient outcome after liver surgery. Thus, dysregulated basal MET phosphorylation could be an indicator for the health status of the liver and thereby inform on the risk of a patient to suffer from liver failure after surgery.

Some of the important geodetic time series used in various Earth science disciplines are provided without uncertainty estimates. This can affect the validity of conclusions based on such data. However, an efficient uncertainty quantification algorithm to tackle this problem is currently not available. Here we present a methodology to approximate the aleatoric uncertainty in time series, called Bayesian Hamiltonian Monte Carlo Autoencoders (BaHaMAs). BaHaMAs is based on three elements: (1) self-supervised autoencoders that learn the underlying structure of the time series, (2) Bayesian machine learning that accurately quantifies the data uncertainty, and (3) Monte Carlo sampling that follows the Hamiltonian dynamics. The method can be applied in various fields in the Earth sciences. As an example, we focus on Atmospheric and Oceanic Angular Momentum time series (AAM and OAM, respectively), which are typically provided without uncertainty information. We apply our methodology to 3-hourly AAM and OAM time series and quantify the uncertainty in the data from 1976 up to the end of 2022. Furthermore, since Length of Day (LOD) is a geodetic time series that is closely connected to AAM and OAM and its short-term prediction is important for various space-geodetic applications, we show that the use of the derived uncertainties alongside the time series of AAM and OAM improves the prediction performance of LOD on average by 17% for different time spans. Finally, a comparison with alternative uncertainty quantification baseline methods, i.e., variational autoencoders and deep ensembles, reveals that BaHaMAs is more accurate in quantifying uncertainty. [ABSTRACT FROM AUTHOR]

Dye decolorization through biological treatment techniques has been gaining momentum as it is based on suspended and attached growth biomass in both batch and continuous modes. Hence, this review focused on the contribution of moving bed biofilm reactors (MBBR) in dye removal. MBBR have been demonstrated to be an excellent technology for pollution extraction, load shock resistance, and equipment size and energy consumption reduction. The review went further to highlight different biocarrier materials for biofilm development this review identified biochar as an innovative and environmentally friendly material produced through the application of different kinds of reusable or recyclable wastes and biowastes. Biochar as a carbonized waste biomass could be a better competitor and environmentally friendly substitute to activated carbon given its lower mass costs. Biochar can be easily produced particularly in rural locations where there is an abundance of biomass-based trash. Given that circular bioeconomy lowers dependency on natural resources by turning organic wastes into an array of useful products, biochar empowers the creation of competitive goods. Thus, biochar was identified as a novel, cost-effective, and long-term management strategy since it brings about several essential benefits, including food security, climate change mitigation, biodiversity preservation, and sustainability improvement. This review concludes that integrating two treatment methods could greatly lead to better color, organic matter, and nutrients removal than a single biological MBBR treatment process. [ABSTRACT FROM AUTHOR]

Prenatal alcohol-exposed (AE) infants and children often demonstrate disrupted sleep patterns, including more frequent awakenings, reduced total sleep time, and more night-to-night sleep variability. Despite the strong connection between sleep patterns and circadian rhythmicity, relatively little is known about circadian rhythm disruptions in individuals with AE. Recently, several reports demonstrated that evaluating the expression patterns of human clock genes in biological fluids could reveal an individual’s circadian phenotype. Human saliva offers an emerging and easily available physiological sample that can be collected non-invasively for core-clock gene transcript analyses. We compared the expression patterns of core-clock genes and their regulatory genes in salivary samples of children aged 6–10 years-old with and without AE during the light cycle between ZT0-ZT11. We isolated the RNA from the samples and measured the expression patterns of core clock genes and clock regulating genes using the human specific primers with quantitative real-time PCR. Analysis of core clock genes expression levels in saliva samples from AE children indicates significantly altered levels in expression of core-clock BMAL1, CLOCK, PER1-3 and CRY1,2, as compared to those in age-matched control children. We did not find any sex difference in levels of clock genes in AE and control groups. Cosinor analysis was used to evaluate the rhythmic pattern of these clock genes, which identified circadian patterns in the levels of core clock genes in the control group but absent in the AE group. The gene expression profile of a salivary circadian biomarker ARRB1 was rhythmic in saliva of control children but was arhythmic in AE children. Altered expression patterns were also observed in clock regulatory genes: NPAS2, NFL3, NR1D1, DEC1, DEC2, and DBP, as well as chromatin modifiers: MLL1, P300, SIRT1, EZH2, HDAC3, and ZR1D1, known to maintain rhythmic expression of core-clock genes. Overall, these findings provide the first evidence that AE disturbs the circadian patten expression of core clock genes and clock-regulatory chromatin modifiers in saliva. [ABSTRACT FROM AUTHOR]

This study develops the use of ‘blue rings’ (BR), reflecting incomplete cell wall lignification, as a sensitive thermal indicator in bristlecone pine (Pinus longaeva D.K. Bailey). Using double-stained anatomical thin-sections, we explore the climatic and topographical constraints governing BR formation by developing a time-series from 83 cores and comparing BR occurrence with the full temporal span of available climatic data (1895–2008 CE). Lignification is temperature-dependent and continues at a cellular level post-radial growth completion. As BRs reflect incomplete lignification, they can serve as a higher resolution and more sensitive proxy for past cooling than previously established tree-growth indicators. Results indicate that blue ring formation is primarily induced by low September temperatures and responds more sensitively to cooling than the well-established frost-ring record. Additionally, the occurrence and intensity of blue rings decreases gradually below the upper tree line. Bristlecone pine BRs are demonstrated to have significant capacity to enhance the reconstruction of past cooling events in North America connected with both localized and hemispheric scale forcing over multi-millennial timescales. Given its unmatched longevity, the species offers an unparalleled potential for Holocene length climate reconstruction. Findings also highlight the potential for blue rings to provide a more nuanced understanding of past temperature fluctuations across multi-millennial timescales. [ABSTRACT FROM AUTHOR]

Earthquakes and tsunamis can trigger acoustic and gravity waves that could reach the ionosphere, generating electron density disturbances, known as traveling ionospheric disturbances. These perturbations can be investigated as variations in ionospheric total electron content (TEC) estimated through global navigation satellite systems (GNSS) receivers. The VARION (Variometric Approach for Real-Time Ionosphere Observation) algorithm is a well-known real-time tool for estimating TEC variations. In this context, the high amount of data allows the exploration of a VARION-based machine learning classification approach for TEC perturbation detection. For this purpose, we analyzed the 2015 Illapel earthquake and tsunami for its strength and high impact. We use the VARION-generated observations (i.e., dsTEC/dt) provided by 115 GNSS stations as input features for the machine learning algorithms, namely, Random Forest and XGBoost. We manually label time frames of TEC perturbations as the target variable. We consider two elevation cut-off time series, namely, 15° and 25°, to which we apply the classifier. XGBoost with a 15° elevation cut-off dsTEC/dt time series reaches the best performance, achieving an F1 score of 0.77, recall of 0.74, and precision of 0.80 on the test data. Furthermore, XGBoost presents an average difference between the labeled and predicted middle epochs of TEC perturbation of 75 s. Finally, the model could be seamlessly integrated into a real-time early warning system, due to its low computational time. This work demonstrates high-probability TEC signature detection by machine learning for earthquakes and tsunamis, that can be used to enhance tsunami early warning systems. [ABSTRACT FROM AUTHOR]

Dense Global Navigation Satellite System (GNSS) observations are beneficial for monitoring the small-scale troposphere turbulence in both spatiotemporal domains. Densification of current geodetic GNSS networks can be achieved by incorporating low-cost GNSS receivers and antennas, benefitting weather monitoring. This study aims to focus on real-time tropospheric delay estimation using real-time GNSS data streams collected by low-cost GNSS receivers and antennas. The results indicate that: (1) Low-cost GNSS devices can offer accuracies of 7.5 mm in winter and 10.8 mm in summer for real-time zenith tropospheric delay (ZTD) estimations; (2) By applying the phase center variation corrections for low-cost GNSS antennas, which are often ignored in previous studies on low-cost GNSS applications, can produce more reliable real-time ZTD estimations; (3) Low-cost GNSS devices can capture the ZTD fluctuations under heavy precipitation events in a real-time mode, showing a great potential as sensors to monitoring severe weather. These results underscore the viability of low-cost GNSS devices as cost-effective sensors that complement geodetic GNSS equipment in real-time troposphere monitoring and forecasting, especially at small scales. Their integration aids in the densification of existing monitoring networks, thereby bolstering GNSS meteorology applications. [ABSTRACT FROM AUTHOR]

Past and present habitability of Mars have been intensely studied in the context of the search for signals of life. Despite the harsh conditions observed today on the planet, some ancient Mars environments could have harbored specific characteristics able to mitigate several challenges for the development of microbial life. In such environments, Fe2+ minerals like siderite (already identified on Mars), and vivianite (proposed, but not confirmed) could sustain a chemolithoautotrophic community. In this study, we investigate the ability of the acidophilic iron-oxidizing chemolithoautotrophic bacterium Acidithiobacillus ferrooxidans to use these minerals as its sole energy source. A. ferrooxidans was grown in media containing siderite or vivianite under different conditions and compared to abiotic controls. Our experiments demonstrated that this microorganism was able to grow, obtaining its energy from the oxidation of Fe2+ that came from the solubilization of these minerals under low pH. Additionally, in sealed flasks without CO2, A. ferrooxidans was able to fix carbon directly from the carbonate ion released from siderite for biomass production, indicating that it could be able to colonize subsurface environments with little or no contact with an atmosphere. These previously unexplored abilities broaden our knowledge on the variety of minerals able to sustain life. In the context of astrobiology, this expands the list of geomicrobiological processes that should be taken into account when considering the habitability of environments beyond Earth, and opens for investigation the possible biological traces left on these substrates as biosignatures. [ABSTRACT FROM AUTHOR]

Radio signals transmitted by Global Navigation Satellite System (GNSS) satellites experience tropospheric delays. While the hydrostatic part, referred to as zenith hydrostatic delay (ZHD) when mapped to the zenith direction, can be analytically modelled with sufficient accuracy, the wet part, referred to as zenith wet delay (ZWD), is much more difficult to determine and needs to be estimated. Thus, there exist several ZWD models which are used for various applications such as positioning and climate research. In this study, we present a data-driven, global model of the spatial ZWD field, based on the Extreme Gradient Boosting (XGBoost). The model takes the geographical location, the time, and a number of meteorological variables (in particular, specific humidity at several pressure levels) as input, and can predict ZWD anywhere on Earth as long as the input features are available. It was trained on ZWDs at 10718 GNSS stations and tested on ZWDs at 2684 GNSS stations for the year 2019. Across all test stations and all observations, the trained model achieved a mean absolute error of 6.1 mm, respectively, a root mean squared error of 8.1 mm. Comparisons of the XGBoost-based ZWD predictions with independently computed ZWDs and baseline models underline the good performance of the proposed model. Moreover, we analysed regional and monthly models, as well as the seasonal behaviour of the ZWD predictions in different climate zones, and found that the global model exhibits a high predictive skill in all regions and across all months of the year. [ABSTRACT FROM AUTHOR]

Purpose: The GALAD score and the BALAD-2 score are biomarker-based scoring systems used to detect hepatocellular carcinoma (HCC). Both incorporate levels of alpha-fetoprotein (AFP), lens culinaris agglutinin-reactive AFP (AFP-L3), and des-gamma-carboxy prothrombin (DCP). Our objective was to examine the relationship between the GALAD score as well as the BALAD-2 score and treatment response to transarterial or systemic treatments in patients with HCC. Methods: A total of 220 patients with HCC treated with either transarterial (n = 121) or systemic treatments (n = 99; mainly Sorafenib) were retrospectively analyzed. The GALAD score and the BALAD-2 score were calculated based on AFP-L3, AFP, and DCP levels measured in serum samples collected before treatment. The results were correlated with 3-month treatment efficacy based on radiologic mRECIST criteria. Results: The GALAD score showed a strong correlation with BCLC stage (p < 0.001) and total tumor diameter before treatment (p < 0.001).The GALAD score at baseline was significantly lower in patients with a 3-month response to transarterial (p > 0.001) than in refractory patients. Among patients receiving systemic treatment, the median BALAD-2 score at baseline showed a strong association with response at month 3 (p < 0.001). In the transarterial treatment group, the GALAD score (AUC = 0.715; p < 0.001) as well as the BALAD score (AUC = 0.696; p < 0.001) were associated with overall survival, hereby outperforming AFP, AFP-L3 and DCP. Conclusion: The GALAD score as well as the BALAD-2 score hold significant promise as a prognostic tool for patients with early or intermediate-stage HCC who are undergoing transarterial or systemic treatments.Highlights: The GALAD score is associated with response of HCC to transarterial treatments. The BALAD-2 score is associated with response of HCC to systemic treatments. The GALAD score is also associated with response in HCC patients with AFP levels ≤ 20 ng/mL. The GALAD score as well as the BALAD-2 score at baseline correlate with overall survival in patients who received transarterial therapy. [ABSTRACT FROM AUTHOR]

The difference between observed and modelled precession/nutation reveals unmodelled signals commonly referred to as Celestial Pole Offsets (CPO), denoted by dX and dY. CPO are currently observed only by Very Long Baseline Interferometry (VLBI), but there is nearly 4 weeks of latency by which the data centers provide the most accurate, final CPO series. This latency problem necessitates predicting CPO for high-accuracy, real-time applications that require information regarding Earth rotation, such as spacecraft navigation. Even though the International Earth Rotation and Reference Systems Service (IERS) provides so-called rapid CPO, they are usually less accurate and therefore, may not satisfy the requirements of the mentioned applications. To enhance the quality of CPO predictions, we present a new methodology based on Neural Additive Models (NAMs), a class of interpretable machine learning algorithms. We formulate the problem based on long short-term memory neural networks and derive simple analytical relations for the quantification of prediction uncertainty and feature importance, thereby enhancing the intelligibility of predictions made by machine learning. We then focus on the short-term prediction of CPO with a forecasting horizon of 30 days. We develop an operational framework that consistently provides CPO predictions. Using the CPO series of Jet Propulsion Laboratory as the input to the algorithm, we show that NAMs predictions improve the IERS rapid products on average by 57% for dX and 25% for dY under fully operational conditions. Our predictions are both accurate and overcome the latency issue of final CPO series and thus, can be used in real-time applications. [ABSTRACT FROM AUTHOR]

The state-of-the-art paper packaging biorefinery utilizes cellulose fibrous material from paddy straw and papaya latex to produce packaging products. This in turn generate wastewater with high organic matter content that if disposed without treatment will pollute water bodies and affect aquatic life below water. Therefore, to comply with "clean water and sanitation" (SDG 6) and "life below water" (SDG 14), this study assesses the efficacy of an extended aeration activated sludge (EAAS) in the treatment of paper packaging biorefinery wastewater (PPBW) by employing paddy straw-derived activated carbon as a biosorbent. Findings revealed that the system was able to achieve 95–98.2% and 90.62–94.96% biological oxygen demand (BOD5) and chemical oxygen demand (COD) reduction, respectively. The maximum organic matter removals were achieved at 2-day hydraulic retention time (HRT) and 60% PPBW concentration. To evaluate substrate removal rates, the first-order, modified Stover–Kincannon and Grau second-order models were used. In the modified Stover–Kincannon model, high correlation coefficients values R2 of 0.99986 and 0.99991 were obtained for COD and BOD5, respectively. Twenty grams COD/L/day and 50 gBOD5/L/day were obtained as Umsr for COD and BOD5, respectively, and 20.402 g/L/day and 56.295 g/L/day as KV constants for COD and BOD5, respectively. The COD and BOD5 biokinetic constant values for the Grau second-order organic matter removal rate constant kS were 36 day−1 and 0.78 day−1, respectively. Here, 0.9989 and 0.99928 were the obtained R2 values for COD and BOD5, respectively. The EAAS bioreactor system described by modified Stover–Kincannon model was proven to best suit the experimental data. Therefore, the model can be used in designing an EAAS system and consequently predict the bioreactor behaviour. The result of this study provided a benchmark for the actual implementation of PSAC in PPBW treatment for COD and BOD5 removal. It has been proven that PSAC biosorbent sourced from a natural agro-waste material is essential and could be used as an efficient substance for organic matter removal. Operating expenses and associated savings were such that PASC was more attractive in an economic analysis of wastewater treatment demands. It is environmentally benign and offers a green treatment option to the PPBW. It could be an alternative to chemical materials because it is harmless to human health and proffer sustainable solution to potable water production. [ABSTRACT FROM AUTHOR]

Glucose homeostasis is maintained by hormones secreted from different cell types of the pancreatic islets and controlled by manifold input including signals mediated through G protein-coupled receptors (GPCRs). RNA-seq analyses revealed expression of numerous GPCRs in mouse and human pancreatic islets, among them Gpr116/Adgrf5. GPR116 is an adhesion GPCR mainly found in lung and required for surfactant secretion. Here, we demonstrate that GPR116 is involved in the somatostatin release from pancreatic delta cells using a whole-body as well as a cell-specific knock-out mouse model. Interestingly, the whole-body GPR116 deficiency causes further changes such as decreased beta-cell mass, lower number of small islets, and reduced pancreatic insulin content. Glucose homeostasis in global GPR116-deficient mice is maintained by counter-acting mechanisms modulating insulin degradation. Our data highlight an important function of GPR116 in controlling glucose homeostasis. In vitro, ex vivo, and in vivo analysis shows that the Adhesion GPCR ADGRF5/GPR116 regulates islet functionality. Activation of the receptor leads to an increase in somatostatin secretion whereas loss of the receptor results in metabolic changes. [ABSTRACT FROM AUTHOR]

The emergence of low-cost micro-electro-mechanical system inertial measurement units, cameras and global navigation satellite system (GNSS) receivers has promoted the research of multisensor fusion positioning. With the rapid development of chip technology, it has become a trend for low-cost GNSS chips to provide multi-frequency carrier phase observations while supporting multiple constellations. To enhance the positioning performance of multi-frequency and multi-system precise point positioning (PPP) in the difficult urban environment, we propose a tightly coupled system of monocular visual-inertial odometry (MVIO) and uncombined PPP (UC-PPP) based on factor graph optimization. The initialization of MVIO and UC-PPP adopts a coarse-to-fine approach to correct the transformation of local and global frames online. Moreover, the sliding window and marginalization methods are adopted to retain the constraints between adjacent observations and eliminate useless observations in the window. The pedestrian and vehicle tests in urban environments verify the performance of the proposed method. Compared with open-source software GVINS, the positioning accuracy of the proposed method has been further improved by using carrier phase observations with higher measurement accuracy. Compared with PPP alone, the improvement of the proposed method for the low-speed and short-distance pedestrian test in the east, north, and up directions is 73.3, 54.8 and 62.7%, respectively, while the improvement for the high-speed and long-distance vehicle test is 63.0, 59.3 and 70.5%, respectively. Experiment results show that the proposed method has better positioning accuracy and continuity in difficult urban environments. [ABSTRACT FROM AUTHOR]

Multipath is the main unmodeled error source hindering high-precision Global Navigation Satellite System data processing. Conventional multipath mitigation methods, such as sidereal filtering (SF) and multipath hemispherical map (MHM), have certain disadvantages: They are either not easy to use or not effective enough for multipath mitigation. In this study, we propose a machine learning (ML)-based multipath mitigation method. Multipath modeling was formulated as a regression task, and the multipath errors were fitted with respect to azimuth and elevation in the spatial domain. We collected 30 days of 1 Hz GPS data to validate the proposed method. In total, five short baselines were formed and multipath errors were extracted from the postfit residuals. ML-based multipath models, as well as observation-domain SF and MHM models, were constructed using 5 days of residuals before the target day and later applied for multipath correction. It was found that the XGBoost (XGB) method outperformed SF and MHM. It achieved the highest residual reduction rates, which were 24.9%, 36.2%, 25.5% and 20.4% for GPS P1, P2, L1 and L2 observations, respectively. After applying the XGB-based multipath corrections, kinematic positioning precisions of 1.6 mm, 1.9 mm and 4.5 mm could be achieved in east, north and up components, respectively, corresponding to 20.0%, 17.4% and 16.7% improvements compared to the original solutions. The effectiveness of the ML-based multipath model was further validated using 30 s sampling data and data from a low-cost device. We conclude that the ML-based multipath mitigation method is effective, easy to use, and can be easily extended by adding auxiliary input features, such as signal-to-noise ratio, during model training. [ABSTRACT FROM AUTHOR]

Thermochemical conversion of garden waste to biochar was carried out to prepare a green adsorbent for the removal of Cs, Cu, Ni, and Pb, which was characterized by XPS, SEM–EDX, and FT-IR analyses. The biocharˊs adsorption capacity was 20.5(Cs), 25.2(Cu), 12.4(Ni), and 45.9(Pb) mg g−1 and demonstrated satisfactory performance for different pH values. The kinetics data evaluation revealed that besides chemisorption, intraparticle diffusion contributes to metal removal. Moreover, the physical and structural properties of biochar play an important role in adsorption. Results indicate the suitability of using GW biochar as an alternative sorbent for both radionuclides and metal extraction. [ABSTRACT FROM AUTHOR]

Very long baseline interferometry (VLBI) is a geodetic technique capable of deriving the complete set of Earth orientation parameters, including the highly variable Earth’s phase of rotation. This observable can be expressed through UT1–UTC, the difference between the Universal Time and the Coordinated Universal Time. The so-called Intensive sessions, or Intensives, are typically 1-h sessions between two to three stations that are observed daily with the primary goal of determining UT1–UTC with a short latency. In this publication, we examine the impact of erroneous a priori information on the UT1–UTC estimation with VLBI Intensive sessions in a systematic way and on a global scale. Our findings are based on a simulation study which is carried out on a regular 10 × 10 degree grid of artificial telescopes. In the simulations, realistic errors are introduced in the station coordinates, polar motion and nutation to get a global picture of the impact of these errors on the estimation of UT1–UTC. Our results reveal that in contrast to errors in the horizontal components of the station coordinates, an error in the station height only slightly affects the UT1–UTC estimate. North–south-oriented baselines are in general strongly affected by errors in the a priori information. In all cases, very short and very long baselines as well as baselines with a midpoint close to the equatorial plane are less robust. On the other hand, east–west-oriented baselines, except equatorial baselines, seem to be rather resistant against errors of these a priori values. [ABSTRACT FROM AUTHOR]

Earth orientation parameters (EOPs) are essential in geodesy, linking the terrestrial and celestial reference frames. Due to the time needed for data processing and combining different space geodetic techniques, EOPs of the highest quality suffer latencies from several days to several weeks. However, real-time EOPs are needed for multiple geodetic and geophysical applications. Predictions of EOPs in the ultra-short term can overcome the latency of EOP products to a certain extent. Traditionally, predictions are performed using statistical methods. With the rapid expansion of computing capacity and data volume, the application of deep learning in geodesy has become increasingly promising in recent years. In particular, the Long Short-Term Memory (LSTM) neural networks, one of the most popular Recurrent Neural Network varieties, are promising for geodetic time series prediction. In this study, we investigate the potential of using LSTM to predict daily length of day (LOD) variations up to ten days in advance, accounting for the contribution of effective angular momentum (EAM). The data are first preprocessed to obtain residuals by combining physical and statistical models. Then, we employ LSTM networks to predict the LOD residuals using both LOD and EAM residuals as input features. Our methods outperform all other state-of-the-art methods in the first eight days with an improvement of up to 43% under the first EOP Prediction Comparison Campaign conditions. In addition, we assess the performance of LOD predictions using more extended time series to consider the improvements of EOP products over the last decade. The results show that extending data volume significantly increases the performance of the methods. [ABSTRACT FROM AUTHOR]

Very Long Baseline Interferometry (VLBI) experiments are organized within the geodetic, astrometric and astronomical communities for different applications, requiring different observation strategies adopted in scheduling. Currently, the next-generation geodetic and astrometric VLBI Global Observing System (VGOS) is being established. Over the last years, evidence was presented that the delays introduced by the angular structure of the geodetic radio sources contribute significantly to the VGOS observable error budget. Consequently, correcting these structure delays through imaging will play an important part in the future, requiring a different scheduling approach. Within this work, a new source-centric VLBI scheduling approach is presented for improved imaging capabilities of geodetic observations. The algorithm is tested for a seven- and nine-station network and compared with classical geodetic schedules. Monte Carlo simulations are utilized to determine the expected geodetic and astrometric parameter precision, and two independent processing pipelines are used to assess the potential for astronomical source imaging. Based on the simulation results, it is revealed that with the new scheduling approach twice as many sources can be properly imaged. Furthermore, the precision of the Earth orientation parameter estimates is improved on average by 15 % , while the source position coordinate estimates are on average improved by 50 % . Tests with two VGOS networks of twelve and 29 antennas further reveal that the scheduling approach is also applicable to future VGOS networks. [ABSTRACT FROM AUTHOR]

In the present study, effect of europium on the structural and thermal properties of iron phosphate glass was studied and compared with that of pristine iron phosphate glass. Europium-loaded iron phosphate glass [composition-3 mass% Eu2O3-97 mass% (40 mol% Fe2O3-60 mol% P2O5)] was synthesized by conventional melt quench technique, and its amorphous nature was ascertained by X-ray diffraction method. The presence of europium in iron phosphate glass lowered the glass stability and glass forming ability of pristine iron phosphate glass. The presence of europium also resulted in lower specific heat capacity and higher thermal expansion. This is due to the depolymerization of glass network connectivity in the presence of europium, which was further confirmed from the Raman spectra. However, the major network linkage is pyrophosphate as that of pure iron phosphate glass. [ABSTRACT FROM AUTHOR]

Background: Characterization of physical fuel distributions across heterogeneous landscapes is needed to understand fire behavior, account for smoke emissions, and manage for ecosystem resilience. Remote sensing measurements at various scales inform fuel maps for improved fire and smoke models. Airborne lidar that directly senses variation in vegetation height and density has proven to be especially useful for landscape-scale fuel load and consumption mapping. Here we predicted field-observed fuel loads from airborne lidar and Landsat-derived fire history metrics with random forest (RF) modeling. RF models were then applied across multiple lidar acquisitions (years 2012, 2019, 2020) to create fuel maps across our study area on the Kaibab Plateau in northern Arizona, USA. We estimated consumption across the 2019 Castle and Ikes Fires by subtracting 2020 fuel load maps from 2019 fuel load maps and examined the relationship between mapped surface fuels and years since fire, as recorded in the Monitoring Trends in Burn Severity (MTBS) database. Results: R-squared correlations between predicted and ground-observed fuels were 50, 39, 59, and 48% for available canopy fuel, 1- to 1000-h fuels, litter and duff, and total surface fuel (sum of 1- to 1000-h, litter and duff fuels), respectively. Lidar metrics describing overstory distribution and density, understory density, Landsat fire history metrics, and elevation were important predictors. Mapped surface fuel loads were positively and nonlinearly related to time since fire, with asymptotes to stable fuel loads at 10–15 years post fire. Surface fuel consumption averaged 16.1 and 14.0 Mg ha− 1 for the Castle and Ikes Fires, respectively, and was positively correlated with the differenced Normalized Burn Ratio (dNBR). We estimated surface fuel consumption to be 125.3 ± 54.6 Gg for the Castle Fire and 27.6 ± 12.0 Gg for the portion of the Ikes Fire (42%) where pre- and post-fire airborne lidar were available. Conclusions: We demonstrated and reinforced that canopy and surface fuels can be predicted and mapped with moderate accuracy using airborne lidar data. Landsat-derived fire history helped account for spatial and temporal variation in surface fuel loads and allowed us to describe temporal trends in surface fuel loads. Our fuel load and consumption maps and methods have utility for land managers and researchers who need landscape-wide estimates of fuel loads and emissions. Fuel load maps based on active remote sensing can be used to inform fuel management decisions and assess fuel structure goals, thereby promoting ecosystem resilience. Multitemporal lidar-based consumption estimates can inform emissions estimates and provide independent validation of conventional fire emission inventories. Our methods also provide a remote sensing framework that could be applied in other areas where airborne lidar is available for quantifying relationships between fuels and time since fire across landscapes. [ABSTRACT FROM AUTHOR]

A spectrophotometric method, circumventing interference from F− ions, during estimation of Zr in U-Zr alloy fuel, has been developed. F− ions from added HF, for quantitative dissolution of metallic fuels, were converted to a strong ionic liquid complex using a cocktail of masking agents. Zr(IV) complexed with Xylenol Orange, displayed enhanced sensitivity below 1 μg/mL, in acetate buffer medium with masking agents, when F−was ≥ 5 μg/mL. Validation and standardization of the method has been accomplished, using arc melted and injection casted samples of U-Zr alloys, respectively. Prevention of interference from F− by masking agents was elucidated using density functional theory. [ABSTRACT FROM AUTHOR]

One of the core products of VLBI is the rapid determination of the Earth rotation parameter, expressed through dUT1. Multiple so-called Intensive observing programs exist that are observing dUT1 on a regular basis. Within this work, a detailed overview over the last five years of the VLBI Intensive observing programs INT2 and INT3 is provided. INT2 sessions are typically observed with a single baseline using a recording rate of 256 Mbps while INT3 sessions are multi-baseline Intensives with up to five stations and a recording rate of 1 Gbps . The median dUT1 precision estimated from INT2 sessions is 10.5 μ s while it is 5.9 μ s for INT3 sessions. The best performing INT2 baseline is between station MK-VLBA and WETTZELL with a median dUT1 formal error of 6.4 μ s and showing only a small bias of - 2.5 μ s w.r.t. the JPL EOP2 series. Starting in 2019, the scheduling strategy of the INT3 sessions was significantly changed, leading to a reduction in the estimated average dUT1 formal errors by 25 % for 4-station sessions and 45 % for 5-stations sessions. Mid-2020, the same change was performed for INT2 sessions, leading to a reduction in the average dUT1 mean formal error of up to 44 % for the baseline between MK-VLBA and WETTZELL. It is further revealed that the precision of single-baseline INT3 analysis is not significantly better than its INT2 counterpart, although a four-times higher data-rate is used. The reason for this is differences in scheduling optimization. On average, the mean formal error of the best single-baseline INT3 analysis is 50 % higher compared to utilizing the whole network. Besides analyzing dUT1 formal errors, the latency of the dUT1 results is compared for three analysis centers. For INT3 sessions, results are typically available within 24 hours, while it takes two to three days for INT2 sessions, due to observations occurring on weekends. Overall, this work provides detailed insight into the INT2 and INT3 session performances while revealing a strong positive trend in the precision of dUT1 measurements over the last years due to changes in the scheduling strategy. [ABSTRACT FROM AUTHOR]

The study showed novel findings about changes in the fate and bioavailability of conazole fungicides (CFs) after biochar (BC) addition to soil. Two contrasting soils (low- and high-sorbing of CF; L soils, H soils) were amended by three BCs (low-, moderate-, and high-sorbing of CF; L-BC, M-BC, H-BC) at 0.2% and 2% doses. Epoxiconazole (EPC) and tebuconazole (TBC) were then added to the soil–BC mixtures, and their degradation, bioaccumulation in earthworms (Eisenia andrei), and bioconcentration in lettuce (Lactuca sativa) were studied for three months. Also, stir bar sorptive extraction (SBSE) was performed to determine CF (bio)accessibility. The EPC and TBC degradation in the soil–BC mixtures followed usually the first-order decay kinetics. The BC addition prevalently decreased the pesticides degradation in the L soil mixtures but often increased it in the H soil mixtures. In general, EPC degraded less than TBC. BC type and dose roles in the pesticides degradation were unclear. The BC addition significantly reduced pesticide uptake to the earthworms in the L soil mixtures (by 37–96%) and in the H soil mixtures (by 6–89%) with 2% BC. The BC addition reduced pesticide uptake to the lettuce roots and leaves significantly—up to two orders of magnitude, and this reduction was strong in H soil mixtures at 2% of BC. The BC addition reduced the CF (bio)accessibility measured by SBSE in all L soil mixtures and some H soil mixtures with 2% BC. Although not significant, it also seems that the pesticide bioaccumulation, bioconcentration, and (bio)accessibility were decreasing according to the BC type (L-BC > M-BC > H-BC). The pesticide concentrations in the earthworms and lettuce correlated significantly to the SBSE results, which indicates this technique as a possible predictor of biotic uptake. Our results showed that the interactions were hard to predict in the complex soil–BC–pesticide system. [ABSTRACT FROM AUTHOR]

Hemoglobin is one of the most widely studied proteins genetically, biochemically, and structurally. It is an oxygen carrying tetrameric protein that imparts the characteristic red color to blood. Each chain of hemoglobin harbors a heme group embedded in a hydrophobic pocket. Several studies have investigated structural variations present in mammalian hemoglobin and their functional implications. However, camel hemoglobin has not been thoroughly explored, especially from a structural perspective. Importantly, very little is known about how the heme group interacts with hemoglobin under varying conditions of osmolarity and temperature. Several experimental studies have indicated that the tense (T) state is more stable than the relaxed (R) state of hemoglobin under normal physiological conditions. Despite the fact that R state is less stable than the T state, no extensive structural dynamics studies have been performed to investigate global quaternary transitions of R state hemoglobin under normal physiological conditions. To evaluate this, several 500 ns all-atom molecular dynamics simulations were performed to get a deeper understanding of how camel hemoglobin behaves under stress, which it is normally exposed to, when compared to human hemoglobin. Notably, camel hemoglobin was more stable under physiological stress when compared to human hemoglobin. Additionally, when compared to camel hemoglobin, cofactor-binding regions of hemoglobin also exhibited more fluctuations in human hemoglobin under the conditions studied. Several differences were observed between the residues of camel and human hemoglobin that interacted with heme. Importantly, distal residues His58 of α hemoglobin and His63 of β hemoglobin formed more sustained interactions, especially at higher temperatures, in camel hemoglobin. These residues are important for oxygen binding to hemoglobin. Thus, this work provides insights into how camel and human hemoglobin differ in their interactions under stress. [ABSTRACT FROM AUTHOR]

The liver is one of the most sexually dimorphic organs. The hepatic metabolic pathways that are subject to sexual dimorphism include xenobiotic, amino acid and lipid metabolism. Non-alcoholic fatty liver disease and hepatocellular carcinoma are among diseases with sex-dependent prevalence, progression and outcome. Although male and female livers differ in their abilities to metabolize foreign compounds, including drugs, sex-dependent treatment and pharmacological dynamics are rarely applied in all relevant cases. Therefore, it is important to consider hepatic sexual dimorphism when developing new treatment strategies and to understand the underlying mechanisms in model systems. We isolated primary hepatocytes from male and female C57BL6/N mice and examined the sex-dependent transcriptome, proteome and extracellular metabolome parameters in the course of culturing them for 96 h. The sex-specific gene expression of the general xenobiotic pathway altered and the female-specific expression of Cyp2b13 and Cyp2b9 was significantly reduced during culture. Sex-dependent differences of several signaling pathways increased, including genes related to serotonin and melatonin degradation. Furthermore, the ratios of male and female gene expression were inversed for other pathways, such as amino acid degradation, beta-oxidation, androgen signaling and hepatic steatosis. Because the primary hepatocytes were cultivated without the influence of known regulators of sexual dimorphism, these results suggest currently unknown modulatory mechanisms of sexual dimorphism in vitro. The large sex-dependent differences in the regulation and dynamics of drug metabolism observed during cultivation can have an immense influence on the evaluation of pharmacodynamic processes when conducting initial preclinical trials to investigate potential new drugs. [ABSTRACT FROM AUTHOR]

One of the main tasks of Very Long Baseline Interferometry (VLBI) is the rapid determination of the highly variable Earth’s rotation expressed through the difference between Universal Time UT1 and Coordinated Universal Time UTC (dUT1). For this reason, dedicated one hour, single baseline sessions, called “Intensives”, are observed on a daily basis. Thus far, the optimal geometry of Intensive sessions was understood to include a long east–west extension of the baseline to ensure a dUT1 estimation with highest accuracy. In this publication, we prove that long east–west baselines are the best choice only for certain lengths and orientations. In this respect, optimal orientations may even require significant inclination of the baseline with respect to the equatorial plane. The basis of these findings is a simulation study with subsequent investigations in the partial derivatives of the observed group delays τ with respect to dUT1 ∂ τ / ∂ d U T 1 . Almost 3000 baselines between artificial stations located on a regular 10 × 10 degree grid are investigated to derive a global and generally valid picture about the best length and orientation of Intensive baselines. Our results reveal that especially equatorial baselines or baselines with a center close to the equatorial plane are not suited for Intensives although they provide a good east–west extension. This is explained by the narrow right ascension band of visible sources and the resulting lack of variety in the partial derivatives. Moreover, it is shown that north–south baselines are also capable of determining dUT1 with reasonable accuracy, given that the baseline orientation is significantly different from the Earth rotation axis. However, great care must be taken to provide accurate polar motion a priori information for these baselines. Finally, we provide a better metric to assess the suitability of Intensive baselines based on the effective spread of ∂ τ / ∂ d U T 1 . [ABSTRACT FROM AUTHOR]

Human rhinoviruses (HRV) are frequent cause of asthma exacerbations, however the influence of airway inflammation on the severity of viral infection is poorly understood. Here, we investigated how cytokine-induced remodeling of airway epithelium modulates antiviral response. We analyzed gene expression response in in vitro differentiated bronchial epithelium exposed to cytokines and next infected with HRV16. IL-13-induced mucous cell metaplasia (MCM) was associated with impaired ciliogenesis and induction of antiviral genes, resulting in lower susceptibility to HRV. Epithelial-mesenchymal transition caused by TGF-β was associated with increased virus replication and boosted innate response. Moreover, HRV infection per se caused transient upregulation of MCM markers and growth factors, followed by low-level virus replication and shedding. Our data suggest that the outcome of HRV infection depends on the type of lower airway inflammation and the extent of epithelial damage. Type-2 inflammation (eosinophilic asthma) may induce antiviral state of epithelium and decrease virus sensitivity, while growth factor exposure during epithelial repair may facilitate virus replication and inflammatory response. Additionally, responses to HRV were similar in cells obtained from asthma patients and control subjects, which implicates that antiviral mechanisms are not intrinsically impaired in asthma, but may develop in the presence of uncontrolled airway inflammation. [ABSTRACT FROM AUTHOR]

Maintaining and supporting complete biodegradation during remediation of petroleum hydrocarbon contaminated groundwater in constructed wetlands is vital for the final destruction and removal of contaminants. We aimed to compare and gain insight into biodegradation and explore possible limitations in different filter materials (sand, sand amended with biochar, expanded clay). These filters were collected from constructed wetlands after two years of operation and batch experiments were conducted using two stable isotope techniques; (i) carbon isotope labelling of hexadecane and (ii) hydrogen isotope fractionation of decane. Both hydrocarbon compounds hexadecane and decane were biodegraded. The mineralization rate of hexadecane was higher in the sandy filter material (3.6 µg CO2 g−1 day−1) than in the expanded clay (1.0 µg CO2 g−1 day−1). The microbial community of the constructed wetland microcosms was dominated by Gram negative bacteria and fungi and was specific for the different filter materials while hexadecane was primarily anabolized by bacteria. Adsorption / desorption of petroleum hydrocarbons in expanded clay was observed, which might not hinder but delay biodegradation. Very few cases of hydrogen isotope fractionation were recorded in expanded clay and sand & biochar filters during decane biodegradation. In sand filters, decane was biodegraded more slowly and hydrogen isotope fractionation was visible. Still, the range of observed apparent kinetic hydrogen isotope effects (AKIEH = 1.072–1.500) and apparent decane biodegradation rates (k = − 0.017 to − 0.067 day−1) of the sand filter were low. To conclude, low biodegradation rates, small hydrogen isotope fractionation, zero order mineralization kinetics and lack of microbial biomass growth indicated that mass transfer controlled biodegradation. [ABSTRACT FROM AUTHOR]

The individual role of biochar, compost and PGPR has been widely studied in increasing the productivity of plants by inducing resistance against phyto-pathogens. However, the knowledge on combined effect of biochar and PGPR on plant health and management of foliar pathogens is still at juvenile stage. The effect of green waste biochar (GWB) and wood biochar (WB), together with compost (Comp) and plant growth promoting rhizobacteria (PGPR; Bacillus subtilis) was examined on tomato (Solanum lycopersicum L.) physiology and Alternaria solani development both in vivo and in vitro. Tomato plants were raised in potting mixture modified with only compost (Comp) at application rate of 20% (v/v), and along with WB and GWB at application rate of 3 and 6% (v/v), each separately, in combination with or without B. subtilis. In comparison with WB amended soil substrate, percentage disease index was significantly reduced in GWB amended treatments (Comp + 6%GWB and Comp + 3%GWB; 48.21 and 35.6%, respectively). Whereas, in the presence of B. subtilis disease suppression was also maximum (up to 80%) in the substrate containing GWB. Tomato plant growth and physiological parameters were significantly higher in treatment containing GWB (6%) alone as well as in combination with PGPR. Alternaria solani mycelial growth inhibition was less than 50% in comp, WB and GWB amended growth media, whereas B. subtilis induced maximum inhibition (55.75%). Conclusively, the variable impact of WB, GWB and subsequently their concentrations in the soil substrate was evident on early blight development and plant physiology. To our knowledge, this is the first report implying biochar in synergism with PGPR to hinder the early blight development in tomatoes. [ABSTRACT FROM AUTHOR]

Bacterial adhesion is considered as an important property that enables probiotic bacteria to colonise the gastrointestinal tract and confer a health benefit to the host. In the present study, a shrimp gut isolate Bacillus subtilis subsp. inaquosorum V1, an efficient producer of bacteriocin was used. Autoaggregation, co-aggregation and cell surface hydrophobicity assays were performed to confirm the aggregating phenotype of the strain. The results of the assays showed that the strain belonged to a strong aggregating phenotype, autoaggregation (45.7%) and co-aggregation with the pathogens like E. coli (33.17%) and S. aureus (35.7%). It also aggregates with the hydrocarbons such as xylene (44.8%) and toluene (52.67%). The effect of LiCl2 on bacterial cells indicated the role of S-layer proteins on the bacterial adhesion in which LiCl2-treated cells showed minimal adhesion (16.47%), when compared with untreated cells (45.3%). The candidate strain was supplemented in a commercial fish feed and fed to the ornamental fish Carassius auratus. After 30 days, the experimental group of fishes showed an increase in weight gain (34.56%) with the SGR of 0.99% than the control group. The enzymes to toxify the respiratory oxidative stress, namely SOD, catalase and the digestive enzyme activity were found to be more in the experimental fishes. Similarly, the total protein content of the experimental fishes showed a marked increase than the control diet–fed fish. The above results inferred that the experimental strain has the better adhesive property and can be used as an effective probiotic to improve the production in aquaculture. [ABSTRACT FROM AUTHOR]

Biochar, a carbonaceous material, is increasingly used in the remediation of the anthropogenically polluted soils and the restoration of their ecological functions. However, the interaction mechanisms among biochar, inorganic and organic soil properties and soil biota are still not very clear. The effect of biochar on soil microorganisms is very diverse. Several mechanisms of these interactions were suggested. However, a well acceptable mechanism of biochar effect on soil microorganisms is still missing. Therefore, efforts were made to examine and proposed a mechanism of the interactions between biochar and microorganisms, as well as existing problems of biochar impacts on main groups of soil enzymes, the composition of the microbiota and the detoxification (heavy metals) and degradation (polycyclic aromatic hydrocarbons) of soil pollutants. The data on the process of biochar colonization by microorganisms and the effect of volatile pyrolysis products released by biochar on the soil microbiota were analysed in detail. The effects of biochar on the physico-chemical properties of soils, the content of mineral nutrients and the response of microbial communities to these changes are also discussed. The information provided here may contribute to the solution of the feasibility, effectiveness and safety of the biochar questions to enhance the soil fertility and to detoxify pollutants in soils. [ABSTRACT FROM AUTHOR]

The application of pyrogenic materials in immobilization processes of metalloids represents a burning issue in environmental and waste applications and management. The main objective of this study was to characterize the effect of biomass pretreatment by Cu, Fe and Mg blending and pyrolysis temperature on As sorption efficiency as a model of anionic metalloids from model solutions and As immobilization in old mine soil by pyrogenic materials. The physico-chemical characterization of engineered materials produced in slow pyrolysis process at 400 and 700°C from metal-blended hard wood chips (30% w/w) showed increasing of surface areas (1.4–1.8-fold), changes in pH, and more than 50% decrease in total C content. The batch sorption processes of As ions by Cu-modified pyrogenic materials (CuPM), Fe-modified pyrogenic materials (FePM), and Mg-modified pyrogenic materials (MgPM) showed increasing uptake in order CuPM700 (Qmax 2.56 mg g−1) < CuPM400 (Qmax 3.88 mg g−1) < FePM700 (Qmax 5.90 mg g−1) < MgPM700 (Qmax 7.42 mg g−1) < MgPM400 (Qmax 9.59 mg g−1) < FePM400 (Qmax 10.55 mg g−1). Engineered pyrogenic materials produced at 400°C showed higher immobilization effect on soluble As in soil pore water of old mine site soil from Mediterranean area. FePM400 reduced mobility of arsenic > 3.2 times and MgPM400 > 5 times compared to control. Promising pyrogenic material MgPM400 showed immobilization effect also on additional heavy metals (Cd, Cu, Fe, Mn, Pb, Sr, Zn) present in studied soil. [ABSTRACT FROM AUTHOR]

Copper-based fungicides have been used for a long time in viticulture and have accumulated in many vineyard soils. In this study, incrementing Cu(OH)2-based fungicide application from 0.05 to 5 g Cu kg−1 on two agricultural soils (an acidic sandy loam (L, pH 4.95) and an alkaline silt loam (D, pH 7.45)) resulted in 5 times more mobile Cu in the acidic soil. The most sensitive parameters of alfalfa (Medicago sativa) growing in these soils were the root nodule number, decreasing to 34% and 15% of the control at 0.1 g Cu kg−1 in soil L and at 1.5 g Cu kg−1 in soil D, respectively, as well as the nodule biomass, decreasing to 25% and 27% at 0.5 g Cu kg−1 in soil L and at 1.5 g Cu kg−1 in soil D, respectively. However, the enzymatic N2-fixation was not directly affected by Cu in spite of the presence of Cu in the meristem and the zone of effective N2-fixation, as illustrated by chemical imaging. The strongly different responses observed in the two tested soils reflect the higher buffering capacity of the alkaline silt loam and showed that Cu mitigation and remediation strategies should especially target vineyards with acidic, sandy soils. [ABSTRACT FROM AUTHOR]

Petroleum contamination and its remediation via plant-based solutions have got increasing attention by environmental scientists and engineers. In the current study, the physiological and growth responses of two diesel-tolerant plant species (tolerance limit: 1500–2000 mg/kg), Italian ryegrass (Lolium multiflorum) and Birdsfoot trefoil (Lotus corniculatus), have been investigated in vegetable oil– and diesel oil–amended soils. A long-term (147-day) greenhouse pot experiment was conducted to differentiate the main focus of the study: physical and chemical effects of oil (vegetable and diesel) in freshly spiked soils via evaluating the plant performance and hydrocarbon degradation. Moreover, plant performance was evaluated in terms of seed germination, plant shoot biomass, physiological parameters, and root biomass. Addition of both diesel oil and vegetable oil in freshly spiked soils showed deleterious effects on seedling emergence, root/shoot biomass, and chlorophyll content of grass and legume plants. Italian ryegrass showed more sensitivity in terms of germination rate to both vegetable and diesel oil as compared to non-contaminated soils while Birdsfoot trefoil reduced the germination rate only in diesel oil–impacted soils. The results of the current study suggest that both physical and chemical effects of oil pose negative effects of plant growth and root development. This observation may explain the phenomenon of reduced plant growth in aged/weathered contaminated soils during rhizoremediation experiments. [ABSTRACT FROM AUTHOR]

In the paper we solve the limit problem for partial maxima of m-dependent stationary random fields and we extend the obtained solution to fields satisfying some local mixing conditions. New methods for describing the limitting distribution of maxima are proposed. A notion of a phantom distribution function for a random field is investigated. As an application, several original formulas for calculation of the extremal index are provided. Moving maxima and moving averages as well as Gaussian fields satisfying the Berman condition are considered. [ABSTRACT FROM AUTHOR]

A deeper epigenomic understanding of spatial organization of cells in human tissues is an important challenge. Here we report the first combined positional analysis of transcriptomes and methylomes across three micro-dissected zones (pericentral, intermediate and periportal) of human liver. We identify pronounced anti-correlated transcriptional and methylation gradients including a core of 271 genes controlling zonated metabolic and morphogen networks and observe a prominent porto-central gradient of DNA methylation at binding sites of 46 transcription factors. The gradient includes an epigenetic and transcriptional Wnt signature supporting the concept of a pericentral hepatocyte regeneration pathway under steady-state conditions. While donors with non-alcoholic fatty liver disease show consistent gene expression differences corresponding to the severity of the disease across all zones, the relative zonated gene expression and DNA methylation patterns remain unchanged. Overall our data provide a wealth of new positional insights into zonal networks controlled by epigenetic and transcriptional gradients in human liver. [ABSTRACT FROM AUTHOR]

The Global Geodetic Observing System requirement for the long-term stability of the International Terrestrial Reference Frame is 0.1 mm/year, motivated by rigorous sea level studies. Furthermore, high-quality station velocities are of great importance for the prediction of future station coordinates, which are fundamental for several geodetic applications. In this study, we investigate the performance of predictions from very long baseline interferometry (VLBI) terrestrial reference frames (TRFs) based on Kalman filtering. The predictions are computed by extrapolating the deterministic part of the coordinate model. As observational data, we used over 4000 VLBI sessions between 1980 and the middle of 2016. In order to study the predictions, we computed VLBI TRF solutions only from the data until the end of 2013. The period of 2014 until 2016.5 was used to validate the predictions of the TRF solutions against the measured VLBI station coordinates. To assess the quality, we computed average WRMS values from the coordinate differences as well as from estimated Helmert transformation parameters, in particular, the scale. We found that the results significantly depend on the level of process noise used in the filter. While larger values of process noise allow the TRF station coordinates to more closely follow the input data (decrease in WRMS of about 45%), the TRF predictions exhibit larger deviations from the VLBI station coordinates after 2014 (WRMS increase of about 15%). On the other hand, lower levels of process noise improve the predictions, making them more similar to those of solutions without process noise. Furthermore, our investigations show that additionally estimating annual signals in the coordinates does not significantly impact the results. Finally, we computed TRF solutions mimicking a potential real-time TRF and found significant improvements over the other investigated solutions, all of which rely on extrapolating the coordinate model for their predictions, with WRMS reductions of almost 50%. [ABSTRACT FROM AUTHOR]

Copper (Cu)-based fungicides have been used in viticulture to prevent downy mildew since the end of the 19th century, and are still used today to reduce fungal diseases. Consequently, Cu has built up in many vineyard soils, and it is still unclear how this affects soil functioning. The present study aimed to assess the short and medium-term effects of Cu contamination on the soil fungal community. Two contrasting agricultural soils, an acidic sandy loam and an alkaline silt loam, were used for an eco-toxicological greenhouse pot experiment. The soils were spiked with a Cu-based fungicide in seven concentrations (0–5000 mg Cu kg−1 soil) and alfalfa was grown in the pots for 3 months. Sampling was conducted at the beginning and at the end of the study period to test Cu toxicity effects on total microbial biomass, basal respiration and enzyme activities. Fungal abundance was analysed by ergosterol at both samplings, and for the second sampling, fungal community structure was evaluated via ITS amplicon sequences. Soil microbial biomass C as well as microbial respiration rate decreased with increasing Cu concentrations, with EC50 ranging from 76 to 187 mg EDTA-extractable Cu kg−1 soil. Oxidative enzymes showed a trend of increasing activity at the first sampling, but a decline in peroxidase activity was observed for the second sampling. We found remarkable Cu-induced changes in fungal community abundance (EC50 ranging from 9.2 to 94 mg EDTA-extractable Cu kg−1 soil) and composition, but not in diversity. A large number of diverse fungi were able to thrive under elevated Cu concentrations, though within the order of Hypocreales several species declined. A remarkable Cu-induced change in the community composition was found, which depended on the soil properties and, hence, on Cu availability. [ABSTRACT FROM AUTHOR]

Besides carbon sequestration and improvement of soil properties, biochar (BC) has increasingly been studied as an amendment to immobilise heavy metals in contaminated soils. In a 2-year experiment, we analysed the effects of poplar BC (P-BC, mixed with compost) and gravel sludge with siderite-bearing material (GSFe) on a Cd-, Pb- and Zn-contaminated soil and on metal concentration in Miscanthus × giganteus shoots under greenhouse and field conditions. In the greenhouse, 1% (m/m) P-BC addition reduced NHNO-extractable Cd, Pb and Zn concentrations by 75, 86 and 92%, respectively, at the end of the study. In the leachates, P-BC (1%) could significantly reduce Cd and Zn in both years. In the field, P-BC (3%) induced a reduction of extractable Cd by 87% whereas a combination of P-BC + GSFe reduced Pb by 82% and Zn by 98% in the first year and by 83 and 96% in the second year. In contrast, the metal immobilisation in the soil was hardly reflected in the shoots of Miscanthus × giganteus which generally showed metal concentrations close to control . While Cd was not influenced in both years, Pb and Zn were slightly reduced. Our study confirmed that Miscanthus is an efficient metal excluder, corroborating its suitability for the production of renewable biomass on metal-contaminated soils. [ABSTRACT FROM AUTHOR]