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The influence of resonant magnetic perturbations (RMPs) on the dynamics of turbulence and flows at the edge of the HL-2A tokamak is analyzed utilizing transfer entropy technique. The results have shown that the RMP damps the poloidal flows as well as the E × B shearing rate, whereas enhances the toroidal flows and leads to a broadened particle spectrum with increased small scale turbulence transport. The causality analysis indicates that the regulation impact of poloidal flow on turbulent fluctuations and particle flux is weakened, while that of the toroidal rotation on the latter is strengthened by the RMP field. The impact of the changes in poloidal flow dominates over that of the modified toroidal flow on turbulent transport in the edge. The magnetic perturbation and the flows generally show predator–prey oscillations, where the causal effect between the former and the toroidal flow transits to a synchronization relation in the presence of RMP. In addition, the RMP field will weaken the causal effect on poloidal Reynolds stress while strengthening the parallel-radial component simultaneously. The present findings provide a possible explanation on the effects of external fields on the edge transport, which is suggested to be dominated by the complex interactions among external perturbations, flows, and ambient microturbulence. [ABSTRACT FROM AUTHOR]

OBJECTIVE: Numerous investigations have indicated a correlation between air pollution (AP) and an elevated ischemic stroke (IS) likelihood. The existing literature does not provide a consensus about the possible link between AP and IS. A two-sample Mendelian randomization (MR) analysis was utilized to systematically measure the causal link between AP and ischemic stroke. Furthermore, the mediating impact of inflammatory factors was also performed by a two-step MR. MATERIALS AND METHODS: A two-sample MR analysis was utilized to examine the AP impact on the incidence of IS. Additionally, a twostep MR approach was carried out to account for possible mediating variables. The indirect impact was determined by employing the product approach, which included multiplying the AP impact on inflammatory factors by the inflammatory factors' impacts on IS. The MR effect was identified through inverse variance-weighted (IVW) meta-analysis of each Wald Ratio. Additionally, complementary studies were conducted using the weighted median and MR-egger approaches. RESULTS: The IVW method with random effects showed that the per unit increase in genetically predicted PM2.5 was linked to the 0.362-fold elevated ischemic stroke risk (OR: 1.362, 95% CI: 1.032-1.796, p=0.029). Furthermore, the IVM technique, incorporating random effects, demonstrated that the per unit increase in genetically predicted PM2.5 was related to an elevated Interleukin (IL)-1β risk (OR: 1.529, 95% CI: 1.191-1.963, p=0.001), IL-6 (OR: 1.498, 95% CI: 1.094-2.052, p=0.012) and IL-17 (OR: 1.478, 95% CI: 1.021-2.139, p=0.038). IL-1β, IL-6, and IL-17 modulated the PM2.5 impact on ischemic stroke, while the proportion mediated by them was 59.5%. CONCLUSIONS: A positive correlation between genetically predicted PM2.5 levels and elevated ischemic stroke risk is mediated by IL-1β, IL-6, and IL-17. [ABSTRACT FROM AUTHOR]

The low permeability reservoir perfect an important role of energy replacement in petroleum industry. Aiming at the problem of low prediction accuracy of the deep profile control in low permeability reservoirs and the lack of theoretical basis for the tracking and adjustment of projects, the variation characteristics of relaxation time are determined based on the viscoelastic experiments of movable gels with different concentrations, shear rates and angular velocities. The viscoelastic mobile gel apparent viscosity model considering the relaxation time kinetics is established based on the Maxwell theory and the pressure prediction model for the expanded granular/mobile gel deep profile control in low permeability reservoirs is established. Finally, the real production data of profile control wells in Yushulin oilfield in China is taken as an example, the application effects of the new pressure prediction model considering the viscoelasticity, the pressure model without viscoelasticity and the numerical simulation model are compared and verified. The results show that the gel exhibits viscoelasticity at high shear rate, and when the gel concentration is increased from 500 mg/L to 1500 mg/L, the relaxation time decreases from 1.04 s to 0.08 s and from 6.3 s to 0.8 s before and after gelation, respectively. The application effects of the models show that the new model takes into account the viscoelasticity of the gel, which is 12.3 percentage points higher than that of the traditional pressure model based on the reservoir engineering method and 10.6 percentage points higher than that of the numerical simulation model. [ABSTRACT FROM AUTHOR]

OBJECTIVE: The absence of proper pathogen treatment in the early stages can result in missing out on treatment chances or the overuse of antibiotics, both of which are the primary factors behind fatalities caused by lung infections. In this study, we aimed to investigate the efficacy of metagenomic next-generation sequencing (mNGS) in comparison to conventional detection methods in detecting infectious pathogens. PATIENTS AND METHODS: In this retrospective study, the infection pathogens of 104 patients were examined, and 86 bronchoalveolar lavage fluid (BALF), eight pleural effusions, and ten sputum samples were collected. The conventional detection approaches and mNGS analysis were used to determine the infection pathogen profiles and their detection rates were analyzed. RESULTS: Our study showed that mNGS was more sensitive (89.42%) than the conventional detection methods (56.73%) (p < 0.001), with a 32.69% improvement in sensitivity. The efficacy of mNGS in detecting mixed infections was significantly higher than that of conventional detection methods, with a detection rate of 85.29% compared to 17.65% (p < 0.001). The study demonstrated that mNGS had a higher sensitivity than the conventional detection methods when it came to diagnosing pulmonary infections, making it a potentially useful tool for clinical diagnosis. CONCLUSIONS: Combining mNGS with other pathogenic detection techniques can be an effective way to increase the rate of detecting pulmonary infections, as well as to provide guidance for treatment adjustments. Furthermore, the timing of sample collection and antibiotic administration can influence the effectiveness of mNGS when used on BALF specimens. [ABSTRACT FROM AUTHOR]