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Background As reported by the World Health Organization, a novel coronavirus (2019-nCoV) was identified as the causative virus of Wuhan pneumonia of unknown etiology by Chinese authorities on 7 January, 2020. The virus was named as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by International Committee on Taxonomy of Viruses on 11 February, 2020. This study aimed to develop a mathematical model for calculating the transmissibility of the virus. Methods In this study, we developed a Bats-Hosts-Reservoir-People transmission network model for simulating the potential transmission from the infection source (probably be bats) to the human infection. Since the Bats-Hosts-Reservoir network was hard to explore clearly and public concerns were focusing on the transmission from Huanan Seafood Wholesale Market (reservoir) to people, we simplified the model as Reservoir-People (RP) transmission network model. The next generation matrix approach was adopted to calculate the basic reproduction number ( R 0 ) from the RP model to assess the transmissibility of the SARS-CoV-2. Results The value of R 0 was estimated of 2.30 from reservoir to person and 3.58 from person to person which means that the expected number of secondary infections that result from introducing a single infected individual into an otherwise susceptible population was 3.58. Conclusions Our model showed that the transmissibility of SARS-CoV-2 was higher than the Middle East respiratory syndrome in the Middle East countries, similar to severe acute respiratory syndrome, but lower than MERS in the Republic of Korea.

Natural hazard named entity recognition is a technique used to recognize natural hazard entities from a large number of texts. The method of natural hazard named entity recognition can facilitate acquisition of natural hazards information and provide reference for natural hazard mitigation. The method of named entity recognition has many challenges, such as fast change, multiple types and various forms of named entities. This can introduce difficulties in research of natural hazard named entity recognition. To address the above problem, this paper constructed a natural disaster annotated corpus for training and evaluation model, and selected and compared several deep learning methods based on word vector features. A deep learning method for natural hazard named entity recognition can automatically mine text features and reduce the dependence on manual rules. This paper compares and analyzes the deep learning models from three aspects: pretraining, feature extraction and decoding. A natural hazard named entity recognition method based on deep learning is proposed, namely XLNet-BiLSTM-CRF model. Finally, the research hotspots of natural hazards papers in the past 10 years were obtained through this model. After training, the precision of the XLNet-BilSTM-CRF model is 92.80%, the recall rate is 91.74%, and the F1-score is 92.27%. The results show that this method, which is superior to other methods, can effectively recognize natural hazard named entities.

Background Methanogens are crucial to global methane budget and carbon cycling. Methanogens from the phylum Euryarchaeota are currently classified into one class and seven orders, including two novel methanogen taxa, Methanofastidiosa and Methanomassiliicoccales . The relative importance of the novel methanogens to methane production in the natural environment is poorly understood. Results Here, we used a combined metagenomic and metatranscriptomic approach to investigate the metabolic activity of methanogens in mangrove sediments in Futian Nature Reserve, Shenzhen. We obtained 13 metagenome-assembled genomes (MAGs) representing one class ( Methanofastidiosa ) and five orders ( Methanomassiliicoccales , Methanomicrobiales , Methanobacteriales , Methanocellales , and Methanosarcinales ) of methanogens, including the two novel methanogens. Comprehensive annotation indicated the presence of an H 2 –dependent methylotrophic methanogenesis pathway in Methanofastidiosa and Methanomassiliicoccales . Based on the functional gene analysis, hydrogenotrophic and methylotrophic methanogenesis are the dominant pathways in mangrove sediments. MAG mapping revealed that hydrogenotrophic Methanomicrobiale s were the most abundant methanogens and that methylotrophic Methanomassiliicoccales were the most active methanogens in the analyzed sediment profile, suggesting their important roles in methane production. Conclusions Partial or near-complete genomes of two novel methanogen taxa, Methanofastidiosa and Methanomassiliicoccales , in natural environments were recovered and analyzed here for the first time. The presented findings highlight the ecological importance of the two novel methanogens and complement knowledge of how methane is produced in mangrove ecosystem. This study implies that two novel methanogens play a vital role in carbon cycle. 5YyKCJK4pi2g2ojNbkZqz7 Video Abstract

The widespread clinical adoption of novel magnesium alloy coronary stents, combined with increasing densification of urban power transmission infrastructure, highlighted a significant research gap regarding the effects of power-frequency electromagnetic fields (EMFs) on these implants. This study employed field-circuit coupling numerical methods to simulate electromagnetic field exposure in simulated patients with implanted coronary stent positioned at various locations near a 200kVA three-phase transformer. The analysis focused on the distribution patterns of induced electromagnetic fields within both cardiac tissues and the stent, as well as the resultant Ampere forces acting on the stent. The results showed that the simulated patient directly beneath the three-phase transformer was exposed to the maximum electromagnetic radiation, but the magnetic flux density (Bmax) and the induced electric field intensity (Emax) of the cardiac tissue were lower than the public exposure limits of the International Commission on Non-Ionizing Radiation Protection (ICNIRP). The Bmax and Emax of the stent at the same position were 1.245 μT and 5.086 × 10-4 mV/m, respectively. The maximum Ampere force density of the stent in the Y- axis (perpendicular to the coronal plane) was 3.714 × 10-6 N/m3. The above findings indicate that, under the conditions of this simulation, a 200 kVA power transformer exerts minimal interference on the magnesium alloy stent and cardiac tissues. The magnetic flux density and induced electric field in the heart tissues, as well as the Ampere force acting on the magnesium alloy stent, all remain within established safety limits.

The methanogenic degradation of oil hydrocarbons can proceed through syntrophic partnerships of hydrocarbon-degrading bacteria and methanogenic archaea 1 – 3 . However, recent culture-independent studies have suggested that the archaeon ‘ Candidatus Methanoliparum’ alone can combine the degradation of long-chain alkanes with methanogenesis 4 , 5 . Here we cultured Ca . Methanoliparum from a subsurface oil reservoir. Molecular analyses revealed that Ca . Methanoliparum contains and overexpresses genes encoding alkyl-coenzyme M reductases and methyl-coenzyme M reductases, the marker genes for archaeal multicarbon alkane and methane metabolism. Incubation experiments with different substrates and mass spectrometric detection of coenzyme-M-bound intermediates confirm that Ca . Methanoliparum thrives not only on a variety of long-chain alkanes, but also on n -alkylcyclohexanes and n -alkylbenzenes with long n -alkyl (C ≥13 ) moieties. By contrast, short-chain alkanes (such as ethane to octane) or aromatics with short alkyl chains (C ≤12 ) were not consumed. The wide distribution of Ca . Methanoliparum 4 – 6 in oil-rich environments indicates that this alkylotrophic methanogen may have a crucial role in the transformation of hydrocarbons into methane. ‘Candidatus Methanoliparum’ overexpresses genes encoding alkyl-coenzyme M and methyl-coenzyme M reductases—markers of archaeal multicarbon alkane and methane metabolism—and thrives on a variety of long-chain alkanes and n -alkylcyclohexanes, and n -alkylbenzenes with long n -alkyl (C ≥13 ) moieties.

The archaeal phylum Woesearchaeota, within the DPANN superphylum, includes phylogenetically diverse microorganisms that inhabit various environments. Their biology is poorly understood due to the lack of cultured isolates. Here, we analyze datasets of Woesearchaeota 16S rRNA gene sequences and metagenome-assembled genomes to infer global distribution patterns, ecological preferences and metabolic capabilities. Phylogenomic analyses indicate that the phylum can be classified into ten subgroups, termed A–J. While a symbiotic lifestyle is predicted for most, some members of subgroup J might be host-independent. The genomes of several Woesearchaeota, including subgroup J, encode putative [FeFe] hydrogenases (known to be important for fermentation in other organisms), suggesting that these archaea might be anaerobic fermentative heterotrophs. The biology of the archaeal phylum Woesearchaeota is poorly understood due to the lack of cultured isolates. Here, the authors analyze datasets of Woesearchaeota 16 S rRNA gene sequences and metagenome-assembled genomes to infer global distribution patterns, ecological preferences and metabolic capabilities.

The leading modes of intraseasonal surface air temperature (SAT) over mid-high-latitude Eurasia (MHLE) in boreal winter are captured with the observational 10–60-day SAT anomaly during 1979–2016 by an empirical orthogonal function (EOF) analysis. Each cycle of the southeastward-propagating intraseasonal oscillation (ISO) of SAT is divided into eight phases formed by the first two principal components (PC1 and PC2). Reforecast data from five operational models in the Sub-seasonal to Seasonal (S2S) Project are utilized to assess the prediction skill of the intraseasonal SAT over the MHLE based on the PC index. It is revealed that the upper limit of the useful forecast skill ranges from ~ 10 to ~ 20 days and the models display a better score for target strong cases, although they underestimate the amplitude of the intraseasonal signal. Generally, a higher prediction skill appears in target phase 3, while a lower score exists in target phase 6. The phase-dependent feature of prediction skill is found to be associated with the phase-dependence of amplitude bias and phase angle error, indicating the importance of skillfully predicting ISO amplitude and propagation speed. On the basis of PC index, the ECMWF model can skillfully predict the evolution of an ISO event up to ~ 20 days in advance. Further assessment of potential predictability reveals a 5-day skill gap for ECMWF model, which needs to be overcome by reducing forecast errors for the current prediction scheme. In a nutshell, the real-time PC index can be an efficient method to capture and predict the ISO signal over MHLE, providing possibilities for improving sub-seasonal forecast skill of wintertime intraseasonal SAT anomaly. Meanwhile, more efforts are still needed for the improvements of dynamical prediction systems, to facilitate more accurate and longer-lead predictions of intraseasonal SAT signal over MHLE during boreal winter.

Traumatic brain injury (TBI) is a leading cause of death and disability worldwide. (-)-Epigallocatechin-3-gallate (EGCG) has shown robust neuroprotective effects on various brain injury models in rodents. Herein, we aimed to investigate if EGCG protects against TBI and unravel the underlying mechanisms. A total of 102 mice were used for this study. TBI was induced by controlled cortical impact (CCI). EGCG was given immediately after TBI injury. Neurological functions were accessed by corner test, paw placement, modified neurological severity score, rotarod test, and Morris water maze test. AMPK inhibitor and AMPKα1-knockout mice were used to further study the signaling pathways involved in the observed effects. Our results show that EGCG significantly ameliorated CCI-induced neurological impairment, including spatial learning and memory. EGCG suppressed CCI-induced inflammation and oxidative stress. Furthermore, EGCG downregulated the phosphorylation of IKKα/β, IκBα, and nuclear translocation of NF-κB p65; upregulated AMPK phosphorylation; and altered corresponding changes in the phosphorylation of the downstream target’s ribosomal protein S6, AS160, and CaMKKß. Our data demonstrate that EGCG protects against CCI-induced TBI through the activation of the AMPK pathway in mice, suggesting that EGCG might be a promising therapeutic intervention preventing locomotor and cognitive impairments after TBI.

Uric acid (UA) is mainly synthesized in the liver, intestine, and vascular endothelium and excreted by the kidney (70 %) and intestine (30 %). Hyperuricemia (HUA) occurs when UA production exceeds excretion. Many studies have found that elevated UA is associated with diabetic microvascular complications (DMC), including diabetic retinopathy (DR), diabetic nephropathy (DN), and diabetic peripheral neuropathy (DPN). In addition, too high or too low UA levels will promote the occurrence and development of chronic diseases, but the relationship between UA and diabetic microvascular complications (DMC) is not clear. Therefore, the rational treatment of UA in patients with diabetes is essential. In this review, we summarize and discuss the mechanism and treatment of UA and DMC and may provide potential advice for rational drug selection. •SUA was closely related to diabetes and its complications.•Sodium-glucose cotransporter 2 (SGLT-2) could reduce the levels of SUA.•Dotinurad is a newer urate-lowering agent that suppresses UA reabsorption through the selective inhibition of URAT1 in the proximal renal tubules.

“Psychrodesulfovibrio”, a proposed genus within the family Desulfovibrionaceae, is a group of sulfate-reducing bacteria with biogeochemical significance but restricted child taxa availability. In this study, a strictly anaerobic bacterium, designed strain FT415T, was isolated from mangrove sediments in Futian Mangrove Nature Reserve in Shenzhen, China. The strain was Gram-stain-negative, motile, and vibrio-shaped with a single polar flagellum, which grew at the temperature range of 15–42 °C (optimum 37 °C), pH range of 6.0–7.5 (optimum 6.8), and in the presence of 0–36 g l−1 NaCl (optimum 6 g l−1 NaCl). In the presence of sulfate, electron donors including lactate, ethanol, pyruvate, malate, fumarate, succinate, cysteine, and glycerol were incompletely oxidized to acetate, and H2 and formate were used as electron donors with acetate as the carbon source by strain FT415T. Sulfate, thiosulfate, sulfide, and anthraquinone-2,6-disulfonate were reduced in the presence of lactate. Fe(III) oxide was reduced without cell growth. Fermentative growth was observed with pyruvate and cysteine. Vitamins were not required for growth. The major cellular fatty acids (> 10%) were C16:0, summed feature 10 (C18:1c11/t9/t6 and/or unknown ECL 17.834), C16:1cis 9, and C18:0. The major polar lipids were phosphatidylethanolamine, phospholipids, and aminolipids. The predominant menaquinone was MK-6(H2). The genomic DNA G+C content was 56.7%. Phylogenetic analysis showed that strain FT415T shared a 98.1% similarity in 16S rRNA gene sequence, an average nucleotide identity value of 84.0%, an average amino-acid identity value of 85.4%, and a digital DNA-DNA hybridization value of 25.7% with its closest relative Desulfovibrio subterraneus HN2T, which has been proposed to be transferred to the genus “Psychrodesulfovibrio”. Based on phenotypic, phylogenetic, and genotypic evidence, a new species of the family Desulfovibrionaceae, Desulfovibrio mangrovi sp. nov. was proposed with the type strain FT415T (=GDMCC 1.3410T=KCTC 25525T).