RESUMO
In this study, gas contents, geochemical features, and origins of coalbed methane (CBM) and their influence factors were investigated on nos. 7 and 8 CBM reservoirs from the Suzhou mining area of the Huaibei coalfield. Results have shown that the selected CBM reservoirs are characterized by various thickness (0.50-9.19 m) and buried depth (619-1226 m), but have relatively better lithology of surrounding rocks. Coal samples have similar maturity (Ro,max = 0.71-1.05%), but show differences in chemical composition and macerals. Gas content of nos. 7 and 8 CBM reservoirs ranges from 6.13-12.25 m3/t, but the value of former is lower than that of later one overall. In addition, CH4 is a predominantly component with a value of 88.23-99.00% (avg. 96.69%), and the heavy hydrocarbon gas (C2+) is 0.00-1.93% (avg. 0.41%). The δ13CCH4 value ranges from -64.54 to -46.36 (avg. -53.92), and the δ13DCH4 value is -224.36 to -211.75 (avg. -219.09). Based on the analysis of components and isotopic values, the CBM samples are thermogenic (20.92-71.30%; avg 50.09%) and secondary biogenic gases (28.70-74.49%; avg. 49.91%). Gas content shows changeable characteristics at a buried depth of 300-1300 m, which is affected by buried depth, reservoir temperature and pressure, Mad and vitrinite. However, the CH4 concentration shows no correlation with buried depth. Moreover, the buried depth is significantly positively correlated to δ13CCH4 and δ13DCH4. Based on the relationship between gas content and isotope values, it suggests that δ13CCH4 or δ13DCH4 may have a relationship with the main controlling factors of gas content.
RESUMO
Derived from camelid heavy-chain antibodies, nanobodies (Nbs) are the smallest natural antibodies and are an ideal tool in biological studies because of their simple structure, high yield, and low cost. Nbs possess significant potential for developing highly specific and user-friendly diagnostic assays. Despite offering considerable advantages in detection applications, knowledge is limited regarding the exclusive use of Nbs in lateral flow immunoassay (LFIA) detection. Herein, we present a novel double "Y" architecture, achieved by using the SpyTag/SpyCatcher and Im7/CL7 systems. The double "Y" assemblies exhibited a significantly higher affinity for their epitopes, as particularly evident in the reduced dissociation rate. An LFIA employing double "Y" assemblies was effectively used to detect the severe acute respiratory syndrome coronavirus-2 N protein, with a detection limit of at least 500 pg/mL. This study helps broaden the array of tools available for the development of Nb-based diagnostic techniques.
Assuntos
SARS-CoV-2 , Anticorpos de Domínio Único , Anticorpos de Domínio Único/química , Anticorpos de Domínio Único/imunologia , Imunoensaio/métodos , SARS-CoV-2/imunologia , SARS-CoV-2/isolamento & purificação , Limite de Detecção , Humanos , COVID-19/diagnóstico , COVID-19/virologia , COVID-19/imunologia , Proteínas do Nucleocapsídeo de Coronavírus/imunologia , Proteínas do Nucleocapsídeo de Coronavírus/análiseRESUMO
Bimetallic oxide is a potential catalyst for oxidative desulfurization of fuel. Thus, an appropriate method is needed to improve its catalytic performance. Manufacturing defect is an effective means. In this contribution, an oxygen vacancies (OVs) regulation strategy for enhancing the catalytic activity of bimetallic oxide is proposed. Density functional theory (DFT) calculations show that the crystal phase has a huge influence on the generation energy of oxygen vacancies, so a series of V-Nb mixed oxide with different crystal phases are synthesized. Detailed characterizations show that the as-prepared tetragonal V-Nb mixed oxide (T-VNbOx) has lower OVs formation energy and larger OVs concentration (compared to orthorhombic V-Nb mixed oxides, O-VNbOx). Owing to the activation of OVs, the catalytic activity of T-VNbOx was significantly enhanced to form ultra-deep oxidative desulfurization. In addition, T-VNbOx can be cycled eight times without significantly degrading the desulfurization performance.
RESUMO
The coronavirus disease 2019 has been ravaging throughout the world for three years and has severely impaired both human health and the economy. The causative agent, severe acute respiratory syndrome coronavirus 2 employs the viral RNA dependent RNA polymerase (RdRp) complex for genome replication and transcription, making RdRp an appealing target for antiviral drug development. Systematic characterization of RdRp will undoubtedly aid in the development of antiviral drugs targeting RdRp. Here, our research reveals that RdRp can recognize and utilize nucleoside diphosphates as a substrate to synthesize RNA with an efficiency of about two thirds of using nucleoside triphosphates as a substrate. Nucleoside diphosphates incorporation is also template-specific and has high fidelity. Moreover, RdRp can incorporate ß-d-N4-hydroxycytidine into RNA while using diphosphate form molnupiravir as a substrate. This incorporation results in genome mutation and virus death. It is also observed that diphosphate form molnupiravir is a better substrate for RdRp than the triphosphate form molnupiravir, presenting a new strategy for drug design.
Assuntos
COVID-19 , SARS-CoV-2 , Humanos , SARS-CoV-2/metabolismo , RNA , Difosfatos , Nucleosídeos , RNA Polimerase Dependente de RNA/metabolismo , Antivirais/química , Nucleotídeos , RNA Viral/genética , Proteínas do Olho , Proteínas do Tecido NervosoRESUMO
To investigate the geochemical characteristic, genetic types, and accumulation model of coalbed methane (CBM), 16 samples from a burial depth of 621-1494 m were collected in the Panxie Coal Mining Area of Huainan Coalfield. The results indicate that the samples are dominated by methane, and the concentrations are distributed in the range of 73.11-95.42%. The dryness coefficient is 0.77-1.00 (average, 0.93), and the ratio of methane to the sum of ethane and propane (C1/(C2 + C3)) is 3.18-242.64 (average, 36.15). The δ13CCH4 values are distributed in the range of -65.44 to -32.38 (average, -45.22), the δDCH4 values are in the range of -226.84 to -156.82 (average, -182.93), and the δ13CCO2 values are in the range of -19.7 to -10.1 (average, -15.51). CBM samples in the study area are dominated by thermogenic gases, followed by secondary biogenic gases with CO2 reduction. For the percentages of different genetic gases, the distribution range of thermogenic gas is 70.11-97.86%, whereas that of biogenic gas is 58.65-77.86% for five samples from Zhangji, Panyi, Pansan, and Panbei Coalmines. Moreover, desorption-diffusion fractionation and the effect of groundwater dissolution occurred in the Panxie Coal Mining Area, and higher δ13CCH4 values mostly existed in the deeper coal seams. Furthermore, the biogenic gases are more likely to be secondary biogenic gases generated by CO2 reduction on the basis of data comparison, which is related to the flowing water underground. Accumulation models of different genetic types of CBM are correlated with the burial depth of coal seams, location, and type of faults and aquifers.
RESUMO
To understand the content, pollution, distribution and source and to establish a geochemical baseline of heavy metal elements in soil under the influence of high-density population, the concentrations of heavy metal elements Cr, Mn, Co, Ni, Cu, Zn, As, Cd, Hg, Pb and Fe were determined in 23 soil samples in Suzhou University, and geo-accumulation index, enrichment factor, principal component analysis, spatial analysis and regression analysis were completed. The results showed the following: The elements Cu and As were slightly polluted, while the other heavy metal elements were not. The elements Cd, Cu, Ni and As in soils were mainly caused by agricultural activities of chemical fertilizer, whereas the elements Zn and Hg were impacted by the chemicals and batteries. The heavy metal elements in the north were lower than in the south of the campus, as a whole. The enrichment of elements Cu, As and Cd was caused by the east-west river on the campus, and the enrichment of the elements Mn, Ni and Zn was induced by the reservoir. Biochemical experiments and vehicle parking influenced the spatial enrichment of Cr, Co and Pb, while domestic waste led to the spatial differentiation of Hg concentrations. The regression curve between heavy metal elements and Fe was established, and the background values of the heavy metals Cr, Mn, Co, Ni, Cu, Zn, As, Cd, Hg and Pb are 50.90, 489.37, 11.76, 37.74, 55.70, 58.22, 20.07, 0.09, 0.08 and 24.13 mg/kg, respectively.