Background/purpose: Occult HBV infection (OBI) could have serious clinical consequences in patients receiving immunosuppressive therapy. We aimed to investigate the prevalence of OBI in Chinese patients with autoimmune hepatitis (AIH) and to analyze its clinical and virological features.
Methods: 103 AIH cases were enrolled. Hepatitis B virus (HBV) serological markers were screened by chemiluminescence. HBV-DNA were detected by nest-PCR and real-time PCR. HBV genotyping and mutation analysis were performed by Sanger sequencing.
Results: Twenty-four out of 103 (23.30%) AIH patients had OBI as evidenced by positive HBV-DNA and negative hepatitis B surface antigen (HBsAg). HBV genotype C is the predominant genotype (57.89%), which had more amino acid (AA) substitutions in S region than that of B-genotype group (P = 0.001). The distribution of AA substitution in the 'α' determinant region between genotype C and B were significantly different (P = 0.042). In addition to those already reported OBI-associated AA substitutions (e.g., sG145R and sV184A), some new OBI-associated AA substitutions (e.g., sV106A, sC137* and sL176P) were found in AIH patients in our study. Three out of 24 (12.50%) OBI patients were diagnosed as decompensated cirrhosis, one patient with S deletion mutation and two patients with HBV extensive AA substitutions.
Conclusions: There was a higher proportion of AIH patients with OBI than the general population in China, which can be either seropositive or seronegative-OBI in AIH patients is associated with some specific AA substitutions. The presence of deletion mutations and the extent of AA substitutions in the HBV S region may have predictive clinical implications.
Keywords: Amino acid substitution; Autoimmune hepatitis; Occult HBV infection.
There is a dearth of information on the occurrence and risks of antibiotics in the urban rivers from plateau areas. This study investigated 83 antibiotics in water and sediments of an urban river and effluents of sewage treatment plants (E-STPs) in Xining, Qinghai (northeastern Tibetan Plateau). Fifty-three antibiotics were detected, and the concentrations of individual antibiotics varied in the range of undetected (ND)-552 ng/L in water, ND-164 ng/g in sediments, and ND-3821 ng/L in E-STPs. Seasonal differences of antibiotic concentrations were significant for water samples (p<0.05) but insignificant for sediments (p>0.05). In urban area, E-STP is the main source of antibiotics in the river, while runoff from manured cropland contributes partially to antibiotics in the river in the suburban area. The antibiotic compositions in water were different from those in sediments, but were similar to those in E-STPs. Notably, because of strong solar radiation and long sunshine hours in the plateau area, low levels of quinolones, which are sensitive to photolysis, were observed in river water. Moreover, norfloxacin and enrofloxacin, observed in urban river from other regions of China, were not detected in the Huangshui River water. The occurrence of ofloxacin, erythromycin, roxithromycin, clarithromycin, and trimethoprim in E-STPs may induce a possible risk to antibiotic resistance evolution. Trimethoprim, anhydroerythromycin, sulfamethoxazole, sulfapyridine, and clindamycin in river water could pose low to medium risks to aquatic organisms. Further investigation on the occurrence and distribution of antibiotic resistance genes in the Huangshui River is urgently needed.
This paper discusses an accepted emendation to an earlier version of IG X 2.1 137. Early draft copies of the Herennia announcement show that Antoninus Pius was hailed as Σωτήρ by the city of Thessalonike, a rare epithet for this emperor. This reading was later replaced due to an expert's claim that σωτῆρος was σωτηρίας. Since this seems to conform to a well-known salutary formula, the emendation was adopted from then on. This paper wishes to suggest that the reading of σωτῆρος is based on reliable and published reports instead, and ought to be preferred over the expert claim. Empirical evidence is given to support reading σωτῆρος.
To clarify the aerosol optical properties under different pollution levels and their impacting factors, hourly organic carbon (OC), elemental carbon (EC), and water-soluble ion (WSI) concentrations in PM2.5 were observed by using monitoring for aerosols and gases (MARGA) and a semicontinuous OC/EC analyzer (Model RT-4) in Wuhan from 9 to 26 January 2018. The aerosol extinction coefficient (b(ext)) was reconstructed using the original Interagency Monitoring of Protected Visual Environment (IMPROVE) formula with a modification to include sea salt aerosols. A good correlation was obtained between the reconstructed b(ext) and measured b(ext) converted from visibility. b(ext) presented a unimodal distribution on polluted days (PM2.5 mass concentrations > 75 mu g.m(-3)), peaking at 19:00. b(ext) on clean days (PM2.5 mass concentrations < 75 mu g.m(-3)) did not change much during the day, while on polluted days, it increased rapidly starting at 12:00 due to the decrease of wind speed and increase of relative humidity (RH). PM2.5 mass concentrations, the aerosol scattering coefficient (b(scat)), and the aerosol extinction coefficient increased with pollution levels. The value of b(ext) was 854.72 Mm(-1) on bad days, which was 4.86, 3.1, 2.29, and 1.28 times of that obtained on excellent, good, acceptable, and poor days, respectively. When RH < 95%, b(ext) exhibited an increasing trend with RH under all pollution levels, and the higher the pollution level, the bigger the growth rate was. However, when RH > 95%, b(ext) on acceptable, poor and bad days decreased, while b(ext) on excellent and good days still increased. The overall b(ext) in Wuhan in January was mainly contributed by NH4NO3 (25.2%) and organic matter (20.1%). The contributions of NH4NO3 and (NH4)(2)SO4 to b(ext) increased significantly with pollution levels. On bad days, NH4NO3 and (NH4)(2)SO4 contributed the most to b(ext), accounting for 38.2% and 27.0%, respectively.
Nonuniform subsampling methods are effective to reduce computational burden and maintain estimation efficiency for massive data. Existing methods mostly focus on subsampling with replacement due to its high computational efficiency. If the data volume is so large that nonuniform subsampling probabilities cannot be calculated all at once, then subsampling with replacement is infeasible to implement. This paper solves this problem using Poisson subsampling. We first derive optimal Poisson subsampling probabilities in the context of quasi-likelihood estimation under the A- and L-optimality criteria. For a practically implementable algorithm with approximated optimal subsampling probabilities, we establish the consistency and asymptotic normality of the resultant estimators. To deal with the situation that the full data are stored in different blocks or at multiple locations, we develop a distributed subsampling framework, in which statistics are computed simultaneously on smaller partitions of the full data. Asymptotic properties of the resultant aggregated estimator are investigated. We illustrate and evaluate the proposed strategies through numerical experiments on simulated and real data sets.
To deal with massive data sets, subsampling is known as an effective method which can significantly reduce computational costs in estimating model parameters. In this article, an efficient subsampling method is developed for large-scale quantile regression via Poisson sampling framework, which can solve the memory constraint problem imposed by big data. Under some mild conditions, large sample properties for the estimator involving the weak and strong consistencies, and asymptotic normality are established. Furthermore, the optimal subsampling probabilities are derived according to the A-optimality criterion. It is shown that the estimator based on the optimal subsampling asymptotically achieves a smaller variance than that by the uniform random subsampling. The proposed method is illustrated and evaluated through numerical analyses on both simulated and real data sets.
In this paper, foam-assisted CO2 EOR and anti-gas channelling technology are investigated and optimized to enhance tight oil recovery. A series of laboratory experiments, including pressure−volume−temperature, foam generation and evaluation, and coreflood tests, and phase behaviour theoretical mathematical models are performed to evaluate foam agent, analyze anti-gas channelling mechanisms and influential factors, and optimize foam-assisted CO2 EOR technique. The specific CO2 bulk fluid behaviour and phase behaviour in wellbore are determined through experimental and theoretical models. Two distinct stages are found to be divided prior to and after the CO2 gas breakthrough. Most oil productions, which is in the range of 28–40%, occur prior to the gas breakthrough, whereas only additional 5–8% oil is produced after the gas breakthrough. A higher injection rate and/or permeability ratio result in an earlier gas breakthrough and causes less oil to be produced before gas breakthrough while the oil recovery factor slightly increases after the breakthrough by increasing injection rate. Gas diffusion in water-saturated core reach equilibrium faster than that in the oil-saturated core. An overall evaluation parameter is developed to select foam agent. The optimized static condition for the selected foam agent here is approximately 9 MPa at low temperatures while dynamic performance is improved at a higher gas but lower liquid injection rate. The simultaneous water-alternating-gas injection scheme in subsequent of an initial gas injection with liquid−gas ratio of 1:1 performs better than the water-alternating-gas scheme, which is proven to be effective for the core samples with fracture width of 82.67 μm. Finally, the oilfield surface foaming operational system is designed to upscale laboratory research to practical applications with specific operating setup and procedures, which has been applied in the target oil reservoir and performs well as expected.