Preparation and Characterization of Baicalein-Loaded Nanoliposomes for Antitumor Therapy

Baicalein (BAI) is a major constituent of Scutellaria baicalensis Georgi. Previous studies showed that BAI had obvious effects on U14 cervical tumor-bearing mice model and HeLa cells. However, the use of BAI is inconvenient and troublesome, due to its low oral bioavailability. The aim of this study was to develop baicalein-loaded nanoliposomes (BAI-LP) to improve its bioavailability. In this study, BAI-LP was prepared by thin film hydration method. The average size, polydispersity index (PDI), zeta potential and encapsulation efficiency (EE) of the BAI-LP were 194.6±2.08 nm, 0.17±0.025, -30.73±0.41 mV, and 44.3±2.98%, respectively. Drug storage stability study showed no significant changes in these values after 4 weeks of storing at 4°C. Additionally, Sulforhodamine B (SRB) experimental results indicated that the BAI-LP could achieve better anti-tumor effects than free BAI. The results of the experiment demonstrated that BAI-LP had a better antitumor effect with a higher inhibition rate of 66.34±15.33% than free BAI with a inhibition rate of 41.89±10.50% by using U14 cervical tumor-bearing mice model. In conclusion, the study suggested that BAI-LP would serve as a potent delivery vehicle for BAI in future cancer therapy

Actively implementing an evidence-based feeding guideline for critically ill patients (NEED): a multicenter, cluster-randomized, controlled trial

Background: Previous cluster-randomized controlled trials evaluating the impact of implementing evidence-based guidelines for nutrition therapy in critical illness do not consistently demonstrate patient benefits. A large-scale, sufficiently powered study is therefore warranted to ascertain the effects of guideline implementation on patient-centered outcomes. Methods: We conducted a multicenter, cluster-randomized, parallel-controlled trial in intensive care units (ICUs) across China. We developed an evidence-based feeding guideline. ICUs randomly allocated to the guideline group formed a local "intervention team", which actively implemented the guideline using standardized educational materials, a graphical feeding protocol, and live online education outreach meetings conducted by members of the study management committee. ICUs assigned to the control group remained unaware of the guideline content. All ICUs enrolled patients who were expected to stay in the ICU longer than seven days. The primary outcome was all-cause mortality within 28 days of enrollment. Results: Forty-eight ICUs were randomized to the guideline group and 49 to the control group. From March 2018 to July 2019, the guideline ICUs enrolled 1399 patients, and the control ICUs enrolled 1373 patients. Implementation of the guideline resulted in significantly earlier EN initiation (1.20 vs. 1.55 mean days to initiation of EN; difference − 0.40 [95% CI − 0.71 to − 0.09]; P = 0.01) and delayed PN initiation (1.29 vs. 0.80 mean days to start of PN; difference 1.06 [95% CI 0.44 to 1.67]; P = 0.001). There was no significant difference in 28-day mortality (14.2% vs. 15.2%; difference − 1.6% [95% CI − 4.3% to 1.2%]; P = 0.42) between groups. Conclusions: In this large-scale, multicenter trial, active implementation of an evidence-based feeding guideline reduced the time to commencement of EN and overall PN use but did not translate to a reduction in mortality from critical illness. Trial registration: ISRCTN, ISRCTN12233792. Registered November 20th, 2017

Actively implementing an evidence-based feeding guideline for critically ill patients (NEED): a multicenter, cluster-randomized, controlled trial.

BackgroundPrevious cluster-randomized controlled trials evaluating the impact of implementing evidence-based guidelines for nutrition therapy in critical illness do not consistently demonstrate patient benefits. A large-scale, sufficiently powered study is therefore warranted to ascertain the effects of guideline implementation on patient-centered outcomes.MethodsWe conducted a multicenter, cluster-randomized, parallel-controlled trial in intensive care units (ICUs) across China. We developed an evidence-based feeding guideline. ICUs randomly allocated to the guideline group formed a local "intervention team", which actively implemented the guideline using standardized educational materials, a graphical feeding protocol, and live online education outreach meetings conducted by members of the study management committee. ICUs assigned to the control group remained unaware of the guideline content. All ICUs enrolled patients who were expected to stay in the ICU longer than seven days. The primary outcome was all-cause mortality within 28 days of enrollment.ResultsForty-eight ICUs were randomized to the guideline group and 49 to the control group. From March 2018 to July 2019, the guideline ICUs enrolled 1399 patients, and the control ICUs enrolled 1373 patients. Implementation of the guideline resulted in significantly earlier EN initiation (1.20 vs. 1.55 mean days to initiation of EN; difference - 0.40 [95% CI - 0.71 to - 0.09]; P = 0.01) and delayed PN initiation (1.29 vs. 0.80 mean days to start of PN; difference 1.06 [95% CI 0.44 to 1.67]; P = 0.001). There was no significant difference in 28-day mortality (14.2% vs. 15.2%; difference - 1.6% [95% CI - 4.3% to 1.2%]; P = 0.42) between groups.ConclusionsIn this large-scale, multicenter trial, active implementation of an evidence-based feeding guideline reduced the time to commencement of EN and overall PN use but did not translate to a reduction in mortality from critical illness.Trial registrationISRCTN, ISRCTN12233792 . Registered November 20th, 2017

Actively implementing an evidence-based feeding guideline for critically ill patients (NEED): a multicenter, cluster-randomized, controlled trial (vol 26, 46, 2022)

BackgroundPrevious cluster-randomized controlled trials evaluating the impact of implementing evidence-based guidelines for nutrition therapy in critical illness do not consistently demonstrate patient benefits. A large-scale, sufficiently powered study is therefore warranted to ascertain the effects of guideline implementation on patient-centered outcomes.MethodsWe conducted a multicenter, cluster-randomized, parallel-controlled trial in intensive care units (ICUs) across China. We developed an evidence-based feeding guideline. ICUs randomly allocated to the guideline group formed a local "intervention team", which actively implemented the guideline using standardized educational materials, a graphical feeding protocol, and live online education outreach meetings conducted by members of the study management committee. ICUs assigned to the control group remained unaware of the guideline content. All ICUs enrolled patients who were expected to stay in the ICU longer than seven days. The primary outcome was all-cause mortality within 28 days of enrollment.ResultsForty-eight ICUs were randomized to the guideline group and 49 to the control group. From March 2018 to July 2019, the guideline ICUs enrolled 1399 patients, and the control ICUs enrolled 1373 patients. Implementation of the guideline resulted in significantly earlier EN initiation (1.20 vs. 1.55 mean days to initiation of EN; difference - 0.40 [95% CI - 0.71 to - 0.09]; P = 0.01) and delayed PN initiation (1.29 vs. 0.80 mean days to start of PN; difference 1.06 [95% CI 0.44 to 1.67]; P = 0.001). There was no significant difference in 28-day mortality (14.2% vs. 15.2%; difference - 1.6% [95% CI - 4.3% to 1.2%]; P = 0.42) between groups.ConclusionsIn this large-scale, multicenter trial, active implementation of an evidence-based feeding guideline reduced the time to commencement of EN and overall PN use but did not translate to a reduction in mortality from critical illness.Trial registrationISRCTN, ISRCTN12233792 . Registered November 20th, 2017

Reinforced education improves the quality of bowel preparation for colonoscopy: An updated meta-analysis of randomized controlled trials.

BACKGROUND AND AIMS:Inadequate bowel preparation (BP) is an unfavorable factor that influence the success of colonoscopy. Although standard education (SE) given to patients are proved useful to avoid inadequate BP. Studies concerning the effects of reinforced education (RE) on the quality of BP were inconsistent. The aim of this updated meta-analysis of randomized controlled trial was to compare the quality of BP between patients receiving RE in addition to SE and those receiving SE alone. METHODS:MEDLINE, EMBASE, Web of Science and the Cochrane Library were systemically searched to identify the relevant studies published through April 2019. The primary outcome was the rate of adequate BP. Subgroup analyses were conducted. Secondary outcomes included BP score, adenoma detection rate (ADR), polyp detection rate (PDR), insertion time, withdrawal time, adverse events, >80% purgative intake and diet compliance. Dichotomous variables were reported as odds ratio (OR) with 95% confidence interval (CI). Continuous data were reported as mean difference (MD) with 95%CI. Pooled estimates of OR or MD were calculated using a random-effects model. Statistical heterogeneity was accessed by calculating the I2 value. A P value less than 0.05 was considered significant. RESULTS:A total of 18 randomized controlled trails (N = 6536) were included in this meta-analysis. Patients who received RE had a better BP quality than those only receiving SE (OR 2.59, 95%CI: 2.09-3.19; P80% purgative intake (OR 2.17; 95%CI, 1.09-4.32; P = 0.030) and were compliant with diet restriction (OR 2.38; 95%CI: 1.79-3.17; P<0.001) in the RE group. CONCLUSION:RE significantly improved BP quality, increased ADR and PDR, decreased insertion and withdrawal time and adverse events

Clogging Risk Early Warning for Slurry Shield Tunneling in Mixed Mudstone–Gravel Ground: A Real-Time Self-Updating Machine Learning Approach

Clogging constitutes a significant obstacle to shield tunneling in mudstone soils. Previous research has focused on investigating the influence of soils and slurry properties on clogging, although little attention has been paid to the impact of tunneling parameters on clogging, and particularly early clogging warning during tunneling. This paper contributes to developing a real-time clogging early-warning approach, based on a self-updating machine learning method. The clogging judgment criteria are based on the statistical characteristics of whole-ring tunneling parameters. The paper proposes the use of random forest (RF) for a real-time self-updating early warning strategy for clogging. The performance of this approach is illustrated through its application to a slurry-pressure-balanced shield tunneling construction of Nanning metro line 1. Results show that the RF-based approach can predict clogging during a ring construction with only four minutes of tunneling data, with an accuracy of 95%. The RF model provided the best performance compared with the other machine learning methods. Furthermore, the RF model can realize an accurate clogging prediction in one ring, using less tunneling data with the self-updating mechanism

Design of Fast Acquisition System and Analysis of Geometric Feature for Highway Tunnel Lining Cracks Based on Machine Vision

Under the dual effects of the rapid growth of tunnel mileage and operating years, the application and research of tunnel crack identification based on machine vision are increasing with the vigorous development of machine vision. However, due to the complex environment in tunnels, it is difficult to quickly obtain tunnel lining cracks via computer visions in the tunnel. Therefore, this paper presents the design of a fast acquisition system with the geometric feature analysis for tunnel lining cracks, which has been integrated into a tunnel fast inspection vehicle with a machine vision module. Through the research on the image acquisition system of the tunnel lining, the parameter selection of the crack shooting hardware system is determined, and the fast calculation method of shooting parameters is proposed. The geometric characteristic analysis of the tunnel lining crack image is employed to calculate crack width and determine the optimal gray value of crack extraction. Field tests have been conducted in the highway tunnels in Zhejiang and Yunnan provinces in China and the result indicates that the proposed approach yields much better performance in the detection efficiency, whose time of detection is only 1%, and the number of personnel required is only 40% of the traditional pure manual method. Compared with similar systems, it also has significant advantages in crack resolution and detection speed. This research provides a means of rapid acquisition of tunnel cracks and laying a foundation for the evaluation of the service performance of the tunnel

Design of Fast Acquisition System and Analysis of Geometric Feature for Highway Tunnel Lining Cracks Based on Machine Vision

Under the dual effects of the rapid growth of tunnel mileage and operating years, the application and research of tunnel crack identification based on machine vision are increasing with the vigorous development of machine vision. However, due to the complex environment in tunnels, it is difficult to quickly obtain tunnel lining cracks via computer visions in the tunnel. Therefore, this paper presents the design of a fast acquisition system with the geometric feature analysis for tunnel lining cracks, which has been integrated into a tunnel fast inspection vehicle with a machine vision module. Through the research on the image acquisition system of the tunnel lining, the parameter selection of the crack shooting hardware system is determined, and the fast calculation method of shooting parameters is proposed. The geometric characteristic analysis of the tunnel lining crack image is employed to calculate crack width and determine the optimal gray value of crack extraction. Field tests have been conducted in the highway tunnels in Zhejiang and Yunnan provinces in China and the result indicates that the proposed approach yields much better performance in the detection efficiency, whose time of detection is only 1%, and the number of personnel required is only 40% of the traditional pure manual method. Compared with similar systems, it also has significant advantages in crack resolution and detection speed. This research provides a means of rapid acquisition of tunnel cracks and laying a foundation for the evaluation of the service performance of the tunnel

High-sensitivity computational miniaturized terahertz spectrometer using a plasmonic filter array and a modified multilayer residual CNN

Spectrometer miniaturization is desired for handheld and portable applications, yet nearly no miniaturized spectrometer is reported operating within terahertz (THz) waveband. Computational strategy, which can acquire incident spectral information through encoding and decoding it using optical devices and reconstruction algorithms, respectively, is widely employed in spectrometer miniaturization as artificial intelligence emerges. We demonstrate a computational miniaturized THz spectrometer, where a plasmonic filter array tailors the spectral response of a blocked-impurity-band detector. Besides, an adaptive deep-learning algorithm is proposed for spectral reconstructions with curbing the negative impact from the optical property of the filter array. Our spectrometer achieves modest spectral resolution (2.3 cm−1) compared with visible and infrared miniaturized spectrometers, outstanding sensitivity (e.g., signal-to-noise ratio, 6.4E6: 1) superior to common benchtop THz spectrometers. The combination of THz optical devices and reconstruction algorithms provides a route toward THz spectrometer miniaturization, and further extends the applicable sphere of the THz spectroscopy technique

Achieving molecular-level selective detection of volatile organic compounds through a strong coupling effect of ultrathin nanosheets and Au nanoparticles

The high density of surface active sites, high efficiency of interfacial carrier transport, and molecular diffusion path determine the efficiency of the electrochemical sensors. The ultrathin structures have atomic-level thickness, carrier migration and heat diffusion are limited in the two-dimensional plane, resulting in excellent conductivity and high carrier concentration. A one-step chemical method is applied to synthesize defect-rich Au-SnO2 in an ultrathin nanosheet form (thickness of 2–3 nm). The strong interaction between Au and SnO2 via the Au–O–Sn bonding and the catalytic effect of Au can prolong the service life via decreasing the optimal operating temperature (55 °C) and promote the Au-SnO2 sensor to exclusively detect formaldehyde at the ppb level (300 ppb). The experimental findings along with theoretical study reveal that Au nanoparticles have a different effect on the competitive adsorption and chemical reaction over the surface of the Au–SnO2 with formaldehyde and other interfering VOC gases, such as methanol, ethanol, and acetone. This study provides mechanistic insights into the correlation between operating temperature and the performance of the Au–SnO2 chemiresistive sensor. This work allows the development of highly efficient and stable electrochemical sensors to detect VOC gases at room temperature in the future