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These findings demonstrate the feasibility of using WBE to monitor COVID-19 at the zip code level. Highly localized disease surveillance methods can improve public health prevention and mitigation measures at the community level.Edible seaweeds are rich in essential vitamins and minerals, which made them a popular food worldwide. Porphyra haitanensis is one of the most commonly consumed seaweeds with the known ability to accumulate a high level of total arsenic (As). A large number of articles have shown arsenic and phosphorus (P) interactions in microalgae due to the plant's inability to differentiate arsenate from phosphate. However, very limited information is available for edible seaweed at environmentally relevant concentrations. In this study, P. haitanensis was treated with arsenic as AsV (As1 0.06 μM, As2 0.4 μM, As3 1.2 μM) and phosphorous (P1 3.2 μM, P2 13 μM) in a filtered seawater matrix under laboratory condition for six days. A better growth rate was found in seaweeds grown in P2 treatments. Moreover, superoxide dismutase (SOD) activity and malondialdehyde (MDA) content measurements revealed that a higher P concentration prevent seaweeds from lipid peroxidation and oxidative stress. Transcriptome studies indicated the As replacement to P has the ability to target seaweed cell membrane composition, transmembrane transport, DNA and ATP binding. The inorganic As (iAs) had a concentration of 0.54 to 4.45 mg/kg in P. haitanensis on Day 6 with As1, As2, and As3 treatments under low P regime (P1), which exceeds the limits of iAs concentration (0.1-0.5 mg/kg) in National Food Safety Standard-Limits of Pollutants in Food (GB 2762-2017). High P regime (P2) not only reduced the total As but also iAs effectively, even in the highest As treatment (As3), the iAs concentration was less than 0.5 mg/kg on Day 6. These findings provide a good insight for seafood safety guarantees and are important for the management of coastal artificial seaweed farming.The pollen of Betula pendula Roth (silver birch) is considered to be the main cause of allergy-related rhinitis in Europe and its protein-based allergens such as Bet v 1 are well characterized. However, little is known about non-protein components of birch pollen, e.g., small RNAs and their proinflammatory activity. In the present study, next-generation sequencing (NGS) and bioinformatic approaches were used for silver birch pollen (SBP)-derived microRNA profiling and evaluation of microRNA target genes and pathways in human. Human lung cells, namely WI-38 fibroblasts and A549 alveolar epithelial cells were then stimulated with SBP microRNA in vitro and imaging cytometry-based analysis of the levels of proinflammatory cytokines, autophagy parameters and small RNA processing regulators was conducted. Bioinformatic analysis revealed that SBP microRNA may interfere with autophagy, inflammation and allergy pathways in human. SBP and SBP-derived microRNA induced NF-κB-mediated proinflammatory response in human lung cells as judged by increased levels of NF-κB p65, IL-8 and TNFα. NSUN2 and NSUN5 were involved in pollen-derived microRNA processing. Pollen-derived microRNA also modulated autophagic pathway by changes in the pools of LC3B and p62 that may affect autophagy-based adaptive responses during allergic lung inflammation. We postulate that SBP-derived microRNAs can be considered as novel proinflammatory environmental agents.Concentrated Animal Feeding Operations (CAFOs) have arisen and expanded in the U.S. and globally to address efficiencies in livestock production. CAFOs tend to cluster in space for logistical purposes. Efficient distribution of concentrated manures produced by these operations is often not economically feasible, which may lead to accumulation on land near CAFOs, potentially resulting in local environmental changes. Moreover, as CAFOs are established or expand, they may need more lands to apply their manures, likely driving land use changes even after their establishment. Studies have yet to investigate these spatiotemporal impacts of CAFOs. We investigated whether the presence of regulated liquid waste CAFOs is associated with land use change over time and space as well as degraded environmental conditions surrounding those facilities. We used MODIS (Moderate Resolution Imaging Spectrometer) images from 2000 to 2018 to examine these questions in Michigan and North Carolina- states with varied CAFO establishment histories. We found that cropland extent increased while savanna and forest decreased near CAFOs. Similar observations did not occur outside of areas influenced by CAFOs. We also found evidence of environmental degradation, including decreased evapotranspiration and increased day and nighttime land surface temperatures in North Carolina. This study advances our understanding of environmental impacts surrounding CAFOs. Our findings can support policy changes and highlight the need to better understand these globally increasing entities.Fine particulate matter (PM2.5) samples collected in 2018 in Taiyuan, a typical industrial and mining city in North China Plain (NCP), were characterized based on ultrahigh-performance liquid chromatography (UHPLC) coupled with orbitrap mass spectrometry. Potential molecular identifications based on precise molecular weight were conducted to obtain the compositional and source information of organic aerosols (OAs) in this city. Evident variation trends were observed during the sampling period in the composition, degree of oxidation and saturation of the obtained molecules. The proportion of CHOS- and CHO+ were increased from winter to summer and then decreased, conversely the proportion of CHN+ was decreased from winter to summer and then increased. By reclassifying the molecules, OA molecules were observed to be more saturated and oxidized in summer. It was caused by the high abundance of organosulfates (OSs) in summer, and aromatic amines/N-heterocycle aromatic hydrocarbons (PANHs) in winter. Molecular identification indicated that the OSs were basically originated from biogenic source isoprene or monoterpene, while the aromatic amines and PANHs were related to anthropogenic emissions of fossil fuel combustion, like other cities in the NCP area. The prevailing northwesterlies in winter may bring coal-burning pollutants from other cities, while the high abundance of organosulfates in summer may be related to the PM2.5 transportation from Shijiazhuang. This study firstly demonstrates the molecular composition characteristics, potential sources, and geographical origins of PM2.5 in Taiyuan, which gives a comprehensive understanding of PM2.5 in a typical industrial and mining city.The prediction of soil organic carbon (SOC) changes in response to environmental change is often limited by a scarcity of revisited temporal data, which constrains scientific understanding and realistic predictions of soil carbon change. The present study improved the potential of nonrevisited temporal data in the prediction of SOC stocks (SOCS) variations. We proposed a method to develop predictions of SOCS change using two independent temporal data sets (pertaining to the 1980s and 2010s) in China based on the digital soil mapping technique. Changes in SOCS over time at the site level were analyzed via the interpolation of missing SOCS values in each data set. Quantitative SOCS change predictions were generated by modeling the relationship between SOCS change and variables that represent changes in climate, vegetation indices, and land cover. The scale-dependent response of SOCS change to these environmental dynamics was assessed. On average, a slight increase was observed from 3.70 kg m-2 in the 1980s to 4.53 kg m-2 in the 2010s. The proposed approach attained moderate accuracy with an R2 value of 0.32 and a root mean squared error (RMSE) of 1.73 kg m-2. We found that changes in climate factors were dominant controls of SOCS change over time at the country scale. At the regional scale, the controlling factors of SOCS change were distinct and variable. Our case study may be of value in the application of independent temporal data sets to analyze soil carbon change on multiple scales. The method may be used to resolve questions of soil carbon change projections and provide an alternative solution to predict likely changes in soil carbon in response to future environmental change when no temporal data are available.Pyrene is a model contaminant of high molecular weight polycyclic aromatic hydrocarbons (HMW-PAHs), which are compounds that have potential carcinogenic effects and pose a serious threat to human health. Finding effective pyrene-degrading bacteria is crucial for removing PAHs from soil. In this study, DNA-based stable isotope probing (DNA-SIP) technology was used to investigate pyrene degraders in PAH-contaminated oilfield soil during natural attenuation (NA), bioaugmentation (BA) and biostimulation (BS). The results show that BA played an important role in pyrene degradation with the highest pyrene removal rate (~95%) after 12 days incubation, followed by removal rates of ~90% for NA and ~30% for BS. In addition, 6 novel pyrene degraders were identified, while 12 well-known PAH degraders were demonstrated to participate in the biodegradation of pyrene. Additionally, the external homologous strains introduced during BA promoted the degradation of pyrene, but not by directly participating in the metabolism of the target compound. Rhamnolipid supplementation during BS promoted the involvement of more microorganisms in the degradation of pyrene, which was beneficial to identifying more pyrene degraders via DNA-SIP. These findings provide new insight into the effects of external homologous strains and supplementary rhamnolipids on pyrene degradation.Accurate simulation of gross primary productivity (GPP) is essential for estimating the global carbon budget. However, GPP modeling is subject to various sources of uncertainties, among which the impacts of biases in climate forcing data have not been well quantified. Here, using a well-validated vegetation model, we compare site-level simulations using either ground-based meteorology or assimilated reanalyses to identify climate-driven uncertainties in the predicted GPP at 91 FLUXNET sites. Simulations yield the lowest root mean square errors (RMSE) in GPP relative to observations when all site-level meteorology and CO2 concentrations are used. Sensitivity tests conducted with Modern-Era Retrospective Analysis (MERRA) reanalyses increase GPP RMSE by 30%. Replacement of site-level CO2 with global annual average values provides limited contributions to these changes. Selleck Epigenetic inhibitor In contrast, GPP uncertainties increase almost linearly with the biases in meteorology. Among all factors, photosynthetically active radiation (PAR), especially diffuse PAR, plays dominant roles in modulating GPP uncertainties. Simulations using all MERRA forcings but with site-level diffuse PAR help reduce over 50% of the climate-driven biases in GPP. Our study reveals that biases in meteorological forcings, especially the variabilities at diurnal to seasonal time scales, can induce significant uncertainties in the simulated GPP at FLUXET sites. We suggest cautions in simulating global GPP using climate reanalyses for dynamic global vegetation models and urgent improvements in climatic variability in reanalyses data, especially for diffuse radiation.