Bioremediation of aniline aerofloat wastewater at extreme conditions using a novel isolate Burkholderia sp. WX-6 immobilized on biochar.

Aniline aerofloat (AAF) is a refractory organic pollutant in floatation wastewater. Little information is currently available on its biodegradation. In this study, a novel AAF-degrading strain named Burkholderia sp. WX-6 was isolated from mining sludge. The strain could degrade more than 80% of AAF at different initial concentrations (100-1000 mg/L) within 72 h. AAF degrading curves were fitted well with the four-parameter logistic model (R2 >0.97), with the degrading half-life ranging from 16.39 to 35.55 h. This strain harbors metabolic pathway for complete degradation of AAF and is resistant to salt, alkali, and heavy metals. Immobilization of the strain on biochar enhanced both tolerance to extreme conditions and AAF removal, with up to 88% of AAF removal rate in simulated wastewater under alkaline (pH 9.5) or heavy metal pollution condition. In addition, the biochar-immobilized bacteria removed 59.4% of COD in the wastewater containing AAF and mixed metal ions within 144 h, significantly (P < 0.05) higher than those by free bacteria (42.6%) and biochar (48.2%) only. This work is helpful to understand AAF biodegradation mechanism and provides viable references for developing practical biotreatment technique of mining wastewater.

Prevalence and Predictors of Chronic Postsurgical Pain After Video-Assisted Thoracoscopic Surgery: A Systematic Review and Meta-analysis.

INTRODUCTION: Determining the prevalence of chronic postsurgical pain (CPSP) after video-assisted thoracoscopic surgery (VATS) and identifying CPSP predictors should improve the prognosis of patients undergoing VATS. Although several studies have investigated predictors of CPSP after VATS, there were significant dissimilarities in the findings due to the confounding of predictors. METHODS: PubMed, Cochrane, MEDLINE, Web of Science, Chinese Biomedical Literature, and China National Knowledge Infrastructure databases were comprehensively searched using the Medical Subject Headings terms "pain, postoperative," "thoracic surgery, video-assisted," and all related free terms from inception until March 27, 2022. The Stata metaprop package was used to comprehensively analyze the incidence of CPSP following VATS. Furthermore, the pooled odds ratios (OR) or the standardized mean differences (SMD) and their corresponding 95% confidence intervals (95% CI) were calculated, and qualitative analyses were performed for predictors that could not be assessed quantitatively to evaluate the effects of the included risk factors on the occurrence of CPSP. Unadjusted odds ratios were utilized to consider the impact of non-significant estimates if the original study did not report them. RESULTS: Of the 4302 studies, 183 were considered eligible, and 17 were finally included in this study. The overall incidence of CPSP after VATS was 35.3% (95% CI 27.1-43.5%). The qualitative synthesis results revealed that female sex, age, and acute postoperative pain were definite predictors of CPSP after VATS. The number of ports, operation time, duration of drainage, and insufficient analgesia were also considered predictors. Consistent, quantitative synthesis results also showed that the aforementioned predictors were closely related to the occurrence of CPSP after VATS. Only by quantitative analysis, postoperative chemotherapy and an educational level less than junior school were also risk factors for CPSP. Other predictors displayed no evidence or unclear evidence of association with CPSP after VATS. CONCLUSION: This study preliminarily determined the incidence of CPSP after VATS based on the existing literature. Female sex, age, and acute pain were identified as risk factors for CPSP after VATS, and other potential risk factors were also identified and analyzed. However, as a result of the inclusion of retrospective studies and inevitable limitations in this systematic review and meta-analysis, the results of this study still need to be verified by large-scale prospective clinical studies. TRIAL REGISTRATION: CRD42022323179.

Nomogram prediction of chronic postsurgical pain in patients with lung adenocarcinoma after video-assisted thoracoscopic surgery: A prospective study.

Chronic postsurgery pain (CPSP) refers to persistent or repeated pain around the incision after surgery. Different from acute postoperative pain, the persistence of CPSP seriously affects the quality of life of patients. CPSP has a considerable global impact due to large surgical volumes. Although the development of video-assisted thoracoscopy (VATS) has reduced the risk of CPSP, it still seriously affects patients' quality of life. Clinical recognition of CPSP at an early stage is limited; therefore, we aimed to develop and validate a nomogram to identify the significant predictive factors associated with CPSP after VATS in patients with lung adenocarcinoma. We screened 137 patients with invasive adenocarcinoma of the lung from among 312 patients undergoing VATS. In this prospective study, patients were divided into the CPSP (n = 52) and non-CPSP (n = 85) groups according to the occurrence of CPSP. Relevant information was collected 1 day before surgery and 1-3 days after surgery, and the occurrence of CPSP was followed up by telephone at 3 months after surgery. Data on clinical characteristics and peripheral blood leukocyte miRNAs were used to establish a nomogram for predicting CPSP using least absolute shrinkage and selection operator (LASSO) regression methods. The area under curve (AUC) was used to determine the recognition ability of the nomograms. The model was subjected to correction and decision curve analyses. Four variables-body mass index (BMI), history of chronic pain, miR 550a-3p, and visual analog scale (VAS) score on postoperative day 2 (VAS2d)-were selected according to LASSO regression to build the nomogram. The nomogram demonstrated adequate calibration and discrimination in the prediction model, with an AUC of 0.767 (95% confidence interval: 0.679-0.856). The calibration plot showed the best fit between model predictions and practical observations, suggesting that the use of the proposed nomogram to predict CPSP is beneficial. A nomogram consisting of BMI, history of chronic pain, miR 550a-3p, and VAS2d predicted the risk of CPSP after VATS in patients with lung adenocarcinoma.

Active pneumatic vibration control by using pressure and velocity measurements and adaptive fuzzy sliding-mode controller.

This paper presents an intelligent control strategy to overcome nonlinear and time-varying characteristics of a diaphragm-type pneumatic vibration isolator (PVI) system. By combining an adaptive rule with fuzzy and sliding-mode control, the method has online learning ability when it faces the system's nonlinear and time-varying behaviors during an active vibration control process. Since the proposed scheme has a simple structure, it is easy to implement. To validate the proposed scheme, a composite control which adopts both chamber pressure and payload velocity as feedback signal is implemented. During experimental investigations, sinusoidal excitation at resonance and random-like signal are input on a floor base to simulate ground vibration. Performances obtained from the proposed scheme are compared with those obtained from passive system and PID scheme to illustrate the effectiveness of the proposed intelligent control.

Model-free adaptive sensing and control for a piezoelectrically actuated system.

Since the piezoelectrically actuated system has nonlinear and time-varying behavior, it is difficult to establish an accurate dynamic model for a model-based sensing and control design. Here, a model-free adaptive sliding controller is proposed to improve the small travel and hysteresis defects of piezoelectrically actuated systems. This sensing and control strategy employs the functional approximation technique (FAT) to establish the unknown function for eliminating the model-based requirement of the sliding-mode control. The piezoelectrically actuated system's nonlinear functions can be approximated by using the combination of a finite number of weighted Fourier series basis functions. The unknown weighted vector can be estimated by an updating rule. The important advantage of this approach is to achieve the sliding-mode controller design without the system dynamic model requirement. The update laws for the coefficients of the Fourier series functions are derived from a Lyapunov function to guarantee the control system stability. This proposed controller is implemented on a piezoelectrically actuated X-Y table. The dynamic experimental result of this proposed FAT controller is compared with that of a traditional model-based sliding-mode controller to show the performance improvement for the motion tracking performance.