COVID-19 causes record decline in global CO2 emissions

The considerable cessation of human activities during the COVID-19 pandemic has affected global energy use and CO2 emissions. Here we show the unprecedented decrease in global fossil CO2 emissions from January to April 2020 was of 7.8% (938 Mt CO2 with a +6.8% of 2-{\sigma} uncertainty) when compared with the period last year. In addition other emerging estimates of COVID impacts based on monthly energy supply or estimated parameters, this study contributes to another step that constructed the near-real-time daily CO2 emission inventories based on activity from power generation (for 29 countries), industry (for 73 countries), road transportation (for 406 cities), aviation and maritime transportation and commercial and residential sectors emissions (for 206 countries). The estimates distinguished the decline of CO2 due to COVID-19 from the daily, weekly and seasonal variations as well as the holiday events. The COVID-related decreases in CO2 emissions in road transportation (340.4 Mt CO2, -15.5%), power (292.5 Mt CO2, -6.4% compared to 2019), industry (136.2 Mt CO2, -4.4%), aviation (92.8 Mt CO2, -28.9%), residential (43.4 Mt CO2, -2.7%), and international shipping (35.9Mt CO2, -15%). Regionally, decreases in China were the largest and earliest (234.5 Mt CO2,-6.9%), followed by Europe (EU-27 & UK) (138.3 Mt CO2, -12.0%) and the U.S. (162.4 Mt CO2, -9.5%). The declines of CO2 are consistent with regional nitrogen oxides concentrations observed by satellites and ground-based networks, but the calculated signal of emissions decreases (about 1Gt CO2) will have little impacts (less than 0.13ppm by April 30, 2020) on the overserved global CO2 concertation. However, with observed fast CO2 recovery in China and partial re-opening globally, our findings suggest the longer-term effects on CO2 emissions are unknown and should be carefully monitored using multiple measures

A novel MAPT variant (E342K) as a cause of familial progressive supranuclear palsy

BackgroundMAPT variants are a known cause of frontotemporal dementia and Parkinsonian syndrome, of which progressive supranuclear palsy syndrome (PSP) is a rare manifestation.ObjectiveTo report a novel MAPT variant in a PSP pedigree with autosomal dominant inheritance pattern, and to produce a literature review of PSP patients with MAPT variants.MethodsA comprehensive clinical, genetic, and molecular neuroimaging investigation was conducted on a 61 years-old female proband diagnosed with PSP. We also collected the clinical presentation data and history of the patient’s pedigree, and performed further genetic analysis of 4 relatives, from two generations, with and without symptoms.ResultsThe proband exhibited typical clinical manifestation of PSP. A cranial MRI revealed midbrain atrophy, and an FDG-PET scan suggested hypo-metabolic changes in caudate nucleus, left prefrontal lobe, both temporal poles, and midbrain. 18F-florzolo-tau-PET revealed tau-protein deposits in the thalamus and brainstem bilaterally. A gene test by whole-exome sequencing identified a novel MAPT variant [NM_005910.6, exon 11, c.1024G > A (p.E342K)], and the same variant was also identified in one affected relative and one asymptomatic relative, a probable pre-symptomatic carrier.ConclusionThe PSP pedigree caused by the novel MAPT (E342K) variant, expanded the mutational spectrum of MAPT

Streptococcus Mutans Membrane Vesicles Enhance Candida albicans Pathogenicity and Carbohydrate Metabolism

Streptococcus mutans and Candida albicans, as the most common bacterium and fungus in the oral cavity respectively, are considered microbiological risk markers of early childhood caries. S. mutans membrane vesicles (MVs) contain virulence proteins, which play roles in biofilm formation and disease progression. Our previous research found that S. mutans MVs harboring glucosyltransferases augment C. albicans biofilm formation by increasing exopolysaccharide production, but the specific impact of S. mutans MVs on C. albicans virulence and pathogenicity is still unknown. In the present study, we developed C. albicans biofilms on the surface of cover glass, hydroxyapatite discs and bovine dentin specimens. The results showed that C. albicans can better adhere to the tooth surface with the effect of S. mutans MVs. Meanwhile, we employed C. albicans biofilm-bovine dentin model to evaluate the influence of S. mutans MVs on C. albicans biofilm cariogenicity. In the S. mutans MV-treated group, the bovine dentin surface hardness loss was significantly increased and the surface morphology showed more dentin tubule exposure and broken dentin tubules. Subsequently, integrative proteomic and metabolomic approaches were used to identify the differentially expressed proteins and metabolites of C. albicans when cocultured with S. mutans MVs. The combination of proteomics and metabolomics analysis indicated that significantly regulated proteins and metabolites were involved in amino acid and carbohydrate metabolism. In summary, the results of the present study proved that S. mutans MVs increase bovine dentin demineralization provoked by C. albicans biofilms and enhance the protein and metabolite expression of C. albicans related to carbohydrate metabolism

A method for estimating particulate organic carbon at the sea surface based on geodetector and machine learning

Particulate organic carbon (POC) is an essential component of the carbon pump within marine organisms. Exploring estimation methods for POC holds substantial significance for understanding the marine carbon cycle. In this study, we investigated the spatial heterogeneity of 30 factors and POC concentrations using geodetector to account for nonlinearity, diversity, and complexity. Ultimately, 20 factors including sea surface temperature, sea surface salinity, and chlorophyll-a were selected as modeling variables. Six machine learning models—backpropagation neural network, convolutional neural network, attention-based neural network, random forest (RF), adaptive boosting, and extreme gradient boosting were used to compare their performance. The results indicate that among the six machine learning algorithms, RF exhibits the strongest performance, with a root mean square error of 0.11 [log(mg/m3)] and an average percentage deviation of 2.73%. Global annual average sea surface POC concentrations were estimated for 2007 and compared to NASA’s POC product. The outcomes indicate that the RF model-based estimation method displays enhanced accuracy in estimating POC concentrations within intricate coastal environments, while the backpropagation neural network performed better in estimating POC concentrations in open ocean areas. Leveraging the RF model, global sea surface POC concentrations were estimated for the years 2007 through 2016, enabling a spatiotemporal analysis. The analysis unveils heightened POC concentrations in coastal regions and lower levels in open ocean areas. Furthermore, POC concentrations were greater in high-latitude regions compared to mid and low latitude counterparts. In conclusion, the global sea surface POC product in this study exhibits heightened spatial resolution and improved data completeness in contrast to other products. It enhances the accuracy of conventional POC estimation methods, particularly within coastal regions

Radiotherapy Exposure in Cancer Patients and Subsequent Risk of Stroke: A Systematic Review and Meta-Analysis

Background: Cancer patients who have undergone radiotherapy may have an increased risk of subsequent stroke. A clear and detailed understanding of this risk has not been established.Methods: A search for research articles published from January 1990 to November 2017 in the English language was conducted. Subsequent stroke risk in cancer survivors was compared using relative risk (RR) and 95% confidence intervals (CI) according to whether or not radiotherapy was given.Results: A total of 12 eligible studies were identified including 57,881 total patients. All studies were retrospective, as no prospective studies were identified. The meta-analysis revealed a higher overall risk of subsequent stroke in cancer survivors/patients given radiotherapy compared to those not given radiotherapy (RR: 2.09, 95% CI: 1.45, 3.16). In addition, compared to patients not given radiotherapy, there was an increased risk of subsequent stroke for radiotherapy treated patients with Hodgkin's lymphoma (RR: 2.81, 95% CI: 0.69, 4.93) or head/neck/brain/nasopharyngeal cancer (RR: 2.16, 95% CI: 1.16, 3.16), for patients younger than 40 years (RR: 3.53, 95% CI: 2.51, 4.97) or aged 40–49 years (RR: 1.23, 95% CI: 1.09, 1.45) and for patients treated in Asia (RR: 1.88, 95% CI: 1.48, 2.29), the United States (RR: 1.62, 95% CI: 1.01, 2.23), or in Europe (RR: 4.11, 95% CI 2.62, 6.45).Conclusions: The available literature indicates an approximate overall doubling of the subsequent stroke risk in cancer patients given radiotherapy. The elevated risk was generally statistically significant according to cancer type, baseline patient age and region or country where treatment was given. Caution is required in interpreting these findings due to the heterogeneity of populations represented and lack of standardization and completeness across published studies. Further, if real, we cannot conclude the extent to which patient, treatment and/or investigational factors are responsible for this apparent elevated risk. An objective and more detailed understanding of the risks of radiotherapy, and how to prevent them, is urgently required. It is the responsibility of all who provide cancer services to ensure that the experience of all their patients is documented and analyzed using quality registries

Growth mechanism of carbon nanotubes from Co-W-C alloy catalyst revealed by atmospheric environmental transmission electron microscopy

High???melting point alloy catalysts have been reported to be effective for the structure-controlled growth of single-wall carbon nanotubes (SWCNTs). However, some fundamental issues remain unclear because of the complex catalytic growth environment. Here, we directly investigated the active catalytic phase of Co-W-C alloy catalyst, the growth kinetics of CNTs, and their interfacial dynamics using closed-cell environmental transmission electron microscopy at atmospheric pressure. The alloy catalyst was precisely identified as a cubic ??-carbide phase that remained unchanged during the whole CNT growth process. Rotations of the catalyst nanoparticles during CNT growth were observed, implying a weak interfacial interaction and undefined orientation dependence for the solid catalyst. Theoretical calculations suggested that the growth kinetics are determined by the diffusion of carbon atoms on the surface of the ??-carbide catalyst and through the interface of the catalyst-CNT wall

Highly Selective Production of Ethylene by the Electroreduction of Carbon Monoxide.

Conversion of carbon monoxide to high value-added ethylene with high selectivity by traditional syngas conversion process is challenging because of the limitation of Anderson-Schulz-Flory distribution. Herein we report a direct electrocatalytic process for highly selective ethylene production from CO reduction with water over Cu catalysts at room temperature and ambient pressure. An unprecedented 52.7 % Faradaic efficiency of ethylene formation is achieved through optimization of cathode structure to facilitate CO diffusion at the surface of the electrode and Cu catalysts to enhance the C-C bond coupling. The highly selective ethylene production is almost without other carbon-based byproducts (e.g. C1 -C4 hydrocarbons and CO2 ) and avoids the drawbacks of the traditional Fischer-Tropsch process that always delivers undesired products. This study provides a new and promising strategy for highly selective production of ethylene from the abundant industrial CO

Next-Generation Sequencing of Cerebrospinal Fluid for the Diagnosis of Neurocysticercosis

Background: Neurocysticercosis (NCC) is the most common helminthic infection of the central nervous system (CNS). The diagnosis of NCC is sometimes challenging due to its heterogenous clinical manifestations and the variable sensitivity and specificity of neuroimaging and serological tests.Methods: Next-generation sequencing (NGS) of cerebrospinal fluid (CSF) was used to detect pathogens in patients with clinically suspected CNS infections. A series of patients diagnosed with NCC is reviewed here.Results: Using NGS of CSF, four patients were diagnosed with NCC. The reads corresponding to Taenia solium ranged from 478 to 117,362, with genomic coverage of 0.0564–11.15%. Reads corresponding to T. solium were not found in non-template controls and far exceeded those of the background microorganisms in patients with NCC, facilitating the interpretation of the NGS results.Conclusions: This case series demonstrates that NGS of CSF is promising in the diagnosis of NCC in difficult to diagnose cases. Larger studies are needed in the future

Near-real-time monitoring of global CO2 emissions reveals the effects of the COVID-19 pandemic

The COVID-19 pandemic is impacting human activities, and in turn energy use and carbon dioxide (CO2) emissions. Here we present daily estimates of country-level CO2 emissions for different sectors based on near-real-time activity data. The key result is an abrupt 8.8% decrease in global CO2 emissions (−1551 Mt CO2) in the first half of 2020 compared to the same period in 2019. The magnitude of this decrease is larger than during previous economic downturns or World War II. The timing of emissions decreases corresponds to lockdown measures in each country. By July 1st, the pandemic’s effects on global emissions diminished as lockdown restrictions relaxed and some economic activities restarted, especially in China and several European countries, but substantial differences persist between countries, with continuing emission declines in the U.S. where coronavirus cases are still increasing substantially