Analysis of factors that promote the participation of patients with chronic diseases in shared decision making on medication: a cross-sectional survey in Hubei Province, China.

BACKGROUND: Shared decision making (SDM) improves the health status of patients with chronic diseases, especially in the condition of poly-medicated patients. This study aims to find the factors associated with participation of patients with chronic diseases in SDM on medication. METHODS: A total of 1,196 patients with chronic diseases were selected in Hubei Province of China using cluster sampling methods. The random forest method was applied to rank the importance of independent variables by Mean Decrease Gini and out-of- bag (OOB) curve. Multivariate logistic regression was used to explore the independent variables' effect direction and relative hazard. RESULTS: In this study, 5.18% of patients used patient-directed decision making (PDM, a decision-making model led by patients), 37.79% of patients used SDM (a collaborative decision-making model by patients and doctors), and 57.02% of patients used doctor-directed decision making (DDM, or paternalistic decision making, a decision-making model led by doctors). The random forest analysis demonstrated that the top 5 important factors were age, education, exercise, disease course, and medication knowledge. The OOB curve showed that the error rate reached minimum when top 5 variables in importance ranking composed an optimal variable combination. In multivariate logistic regression, we chose SDM as a reference group, and identified medication knowledge (OR = 2.737, 95%CI = 1.524 ~ 4.916) as the influencing factor between PDM and SDM. Meanwhile, the influencing factors between DDM and SDM were age (OR = 0.636, 95%CI = 0.439 ~ 0.921), education (OR = 1.536, 95%CI = 1.122 ~ 2.103), exercise (OR = 1.443, 95%CI = 1.109 ~ 1.877), disease course (OR = 0.750, 95%CI = 0.584 ~ 0.964), and medication knowledge (OR = 1.446, 95%CI = 1.120 ~ 1.867). CONCLUSION: Most Chinese patients with chronic diseases used DDM during their medication decision-making, and some patients used PDM and SDM. The participation in SDM should be taken seriously among elderly patients with lower education levels. The SDM promotion should focus on transformation of patients' traditional perception and enhance their medication knowledge.

A Rapid Method of the Rock Mass Surface Reconstruction for Surface Deformation Detection at Close Range.

Characterizing the surface deformation during the inter-survey period could assist in understanding rock mass progressive failure processes. Moreover, 3D reconstruction of rock mass surface is a crucial step in surface deformation detection. This study presents a method to reconstruct the rock mass surface at close range in a fast way using the improved structure from motion-multi view stereo (SfM) algorithm for surface deformation detection. To adapt the unique feature of rock mass surface, the AKAZE algorithm with the best performance in rock mass feature detection is introduced to improve SfM. The surface reconstructing procedure mainly consists of image acquisition, feature point detection, sparse reconstruction, and dense reconstruction. Hereafter, the proposed method was verified by three experiments. Experiment 1 showed that this method effectively reconstructed the rock mass model. Experiment 2 proved the advanced accuracy of the improved SfM compared with the traditional one in reconstructing the rock mass surface. Eventually, in Experiment 3, the surface deformation of rock mass was quantified through reconstructing images before and after the disturbance. All results have shown that the proposed method could provide reliable information in rock mass surface reconstruction and deformation detection.

Accuracy Improvement of Binocular Vision Measurement System for Slope Deformation Monitoring.

This paper studies the limitations of binocular vision technology in monitoring accuracy. The factors affecting the surface displacement monitoring of the slope are analyzed mainly from system structure parameters and environment parameters. Based on the error analysis theory, the functional relationship between the structure parameters and the monitoring error is studied. The error distribution curve is obtained through laboratory testing and sensitivity analysis, and parameter selection criteria are proposed. Corresponding image optimization methods are designed according to the error distribution curve of the environment parameters, and a large number of tests proved that the methods effectively improved the measurement accuracy of slope deformation monitoring. Finally, the reliability and accuracy of the proposed system and method are verified by displacement measurement of a slope on site.

Non-Contact Measurement of the Surface Displacement of a Slope Based on a Smart Binocular Vision System.

The paper presents an intelligent real-time slope surface deformation monitoring system based on binocular stereo-vision. To adapt the system to field slope monitoring, a design scheme of concentric marking point is proposed. Techniques including Zernike moment edge extraction, the least squares method, and k-means clustering are used to design a sub-pixel precision localization method for marker images. This study is mostly focused on the tracking accuracy of objects in multi-frame images obtained from a binocular camera. For this purpose, the Upsampled Cross Correlation (UCC) sub-pixel template matching technique is employed to improve the spatial-temporal contextual (STC) target-tracking algorithm. As a result, the tracking accuracy is improved to the sub-pixel level while keeping the STC tracking algorithm at high speed. The performance of the proposed vision monitoring system has been well verified through laboratory tests.

Toward industrial production of isoprenoids in Escherichia coli: Lessons learned from CRISPR-Cas9 based optimization of a chromosomally integrated mevalonate pathway.

Escherichia coli has been the organism of choice for the production of different chemicals by engineering native and heterologous pathways. In the present study, we simultaneously address some of the main issues associated with E. coli as an industrial platform for isoprenoids, including an inability to grow on sucrose, a lack of endogenous control over toxic mevalonate (MVA) pathway intermediates, and the limited pathway engineering into the chromosome. As a proof of concept, we generated an E. coli DH1 strain able to produce the isoprenoid bisabolene from sucrose by integrating the cscAKB operon into the chromosome and by expressing a heterologous MVA pathway under stress-responsive control. Production levels dropped dramatically relative to plasmid-mediated expression when the entire pathway was integrated into the chromosome. In order to optimize the chromosomally integrated MVA pathway, we established a CRISPR-Cas9 system to rapidly and systematically replace promoter sequences. This strategy led to higher pathway expression and a fivefold improvement in bisabolene production. More interestingly, we analyzed proteomics data sets to understand and address some of the challenges associated with metabolic engineering of the chromosomally integrated pathway. This report shows that integrating plasmid-optimized operons into the genome and making them work optimally is not a straightforward task and any poor engineering choices on the chromosome may lead to cell death rather than just resulting in low titers. Based on these results, we also propose directions for chromosomal metabolic engineering.

A High-Speed Target-Free Vision-Based Sensor for Bus Rapid Transit Viaduct Vibration Measurements Using CMT and ORB Algorithms.

Bus Rapid Transit (BRT) has become an increasing source of concern for public transportation of modern cities. Traditional contact sensing techniques during the process of health monitoring of BRT viaducts cannot overcome the deficiency that the normal free-flow of traffic would be blocked. Advances in computer vision technology provide a new line of thought for solving this problem. In this study, a high-speed target-free vision-based sensor is proposed to measure the vibration of structures without interrupting traffic. An improved keypoints matching algorithm based on consensus-based matching and tracking (CMT) object tracking algorithm is adopted and further developed together with oriented brief (ORB) keypoints detection algorithm for practicable and effective tracking of objects. Moreover, by synthesizing the existing scaling factor calculation methods, more rational approaches to reducing errors are implemented. The performance of the vision-based sensor is evaluated through a series of laboratory tests. Experimental tests with different target types, frequencies, amplitudes and motion patterns are conducted. The performance of the method is satisfactory, which indicates that the vision sensor can extract accurate structure vibration signals by tracking either artificial or natural targets. Field tests further demonstrate that the vision sensor is both practicable and reliable.

Production of jet fuel precursor monoterpenoids from engineered Escherichia coli.

Monoterpenes (C10 isoprenoids) are the main components of essential oils and are possible precursors for many commodity chemicals and high energy density fuels. Monoterpenes are synthesized from geranyl diphosphate (GPP), which is also the precursor for the biosynthesis of farnesyl diphosphate (FPP). FPP biosynthesis diverts the carbon flux from monoterpene production to C15 products and quinone biosynthesis. In this study, we tested a chromosomal mutation of Escherichia coli's native FPP synthase (IspA) to improve GPP availability for the production of monoterpenes using a heterologous mevalonate pathway. Monoterpene production at high levels required not only optimization of GPP production but also a basal level of FPP to maintain growth. The optimized strains produced two jet fuel precursor monoterpenoids 1,8-cineole and linalool at the titer of 653 mg/L and 505 mg/L, respectively, in batch cultures with 1% glucose. The engineered strains developed in this work provide useful resources for the production of high-value monoterpenes. Biotechnol. Bioeng. 2017;114: 1703-1712. © 2017 Wiley Periodicals, Inc.

Structure-guided enzymology of the lipid A acyltransferase LpxM reveals a dual activity mechanism.

Gram-negative bacteria possess a characteristic outer membrane, of which the lipid A constituent elicits a strong host immune response through the Toll-like receptor 4 complex, and acts as a component of the permeability barrier to prevent uptake of bactericidal compounds. Lipid A species comprise the bulk of the outer leaflet of the outer membrane and are produced through a multistep biosynthetic pathway conserved in most Gram-negative bacteria. The final steps in this pathway involve the secondary acylation of lipid A precursors. These are catalyzed by members of a superfamily of enzymes known as lysophospholipid acyltransferases (LPLATs), which are present in all domains of life and play important roles in diverse biological processes. To date, characterization of this clinically important class of enzymes has been limited by a lack of structural information and the availability of only low-throughput biochemical assays. In this work, we present the structure of the bacterial LPLAT protein LpxM, and we describe a high-throughput, label-free mass spectrometric assay to characterize acyltransferase enzymatic activity. Using our structure and assay, we identify an LPLAT thioesterase activity, and we provide experimental evidence to support an ordered-binding and "reset" mechanistic model for LpxM function. This work enables the interrogation of other bacterial acyltransferases' structure-mechanism relationships, and the assay described herein provides a foundation for quantitatively characterizing the enzymology of any number of clinically relevant LPLAT proteins.

Characterization of an Acinetobacter baumannii lptD Deletion Strain: Permeability Defects and Response to Inhibition of Lipopolysaccharide and Fatty Acid Biosynthesis.

UNLABELLED: Lipid A on the Gram-negative outer membrane (OM) is synthesized in the cytoplasm by the Lpx pathway and translocated to the OM by the Lpt pathway. Some Acinetobacter baumannii strains can tolerate the complete loss of lipopolysaccharide (LPS) resulting from the inactivation of early LPS pathway genes such as lpxC. Here, we characterized a mutant deleted for lptD, which encodes an OM protein that mediates the final translocation of fully synthesized LPS to the OM. Cells lacking lptD had a growth defect comparable to that of an lpxC deletion mutant under the growth conditions tested but were more sensitive to hydrophobic antibiotics, revealing a more significant impact on cell permeability from impaired LPS translocation than from the loss of LPS synthesis. Consistent with this, ATP leakage and N-phenyl-1-naphthylamine (NPN) fluorescence assays indicated a more severe impact of lptD deletion than of lpxC deletion on inner and outer membrane permeability, respectively. Targeted liquid chromatography-mass spectrometry (LCMS) analysis of LPS intermediates from UDP-3-O-R-3-hydroxylauroyl-N-acetyl-α-d-glucosamine through lipid IV(A) showed that the loss of LptD caused an accumulation of lipid IV(A). This suggested that pathway intermediate accumulation or mislocalization caused by the blockage of later LPS pathway steps impacts envelope integrity. Supporting this notion, chemical inhibition of lipid A precursor enzymes, including LpxC and FabB/F, in the lptD deletion strain partially rescued growth and permeability defects. IMPORTANCE: New antibiotics to treat Gram-negative bacterial infections are urgently needed. Inhibition of LPS biosynthesis is attractive because this would impact viability and cell permeability. Therefore, a better understanding of this pathway is important, especially in strains such as A. baumannii ATCC 19606, where LPS biosynthesis is not essential in vitro. We show that ATCC 19606 also survives the loss of the final translocation of LPS into the OM (lptD deletion). Intriguingly, this impaired cell envelope integrity more than the loss of LPS biosynthesis (lpxC deletion), presumably due to the accumulation of toxic intermediates. Supporting this, chemical inhibition of LPS biosynthesis partially reversed this permeability defect. This extends our understanding of the LPS machinery and provides insights into potential interrelationships of the target steps along this important pathway.

Acute Limonene Toxicity in Escherichia coli Is Caused by Limonene Hydroperoxide and Alleviated by a Point Mutation in Alkyl Hydroperoxidase AhpC.

Limonene, a major component of citrus peel oil, has a number of applications related to microbiology. The antimicrobial properties of limonene make it a popular disinfectant and food preservative, while its potential as a biofuel component has made it the target of renewable production efforts through microbial metabolic engineering. For both applications, an understanding of microbial sensitivity or tolerance to limonene is crucial, but the mechanism of limonene toxicity remains enigmatic. In this study, we characterized a limonene-tolerant strain of Escherichia coli and found a mutation in ahpC, encoding alkyl hydroperoxidase, which alleviated limonene toxicity. We show that the acute toxicity previously attributed to limonene is largely due to the common oxidation product limonene hydroperoxide, which forms spontaneously in aerobic environments. The mutant AhpC protein with an L-to-Q change at position 177 (AhpC(L177Q)) was able to alleviate this toxicity by reducing the hydroperoxide to a more benign compound. We show that the degree of limonene toxicity is a function of its oxidation level and that nonoxidized limonene has relatively little toxicity to wild-type E. coli cells. Our results have implications for both the renewable production of limonene and the applications of limonene as an antimicrobial.

Principal component analysis of proteomics (PCAP) as a tool to direct metabolic engineering.

Targeted proteomics is a convenient method determining enzyme expression levels, but a quantitative analysis of these proteomic data has not been fully explored yet. Here, we present and demonstrate a computational tool (principal component analysis of proteomics, PCAP) that uses quantitative targeted proteomics data to guide metabolic engineering and achieve higher production of target molecules from heterologous pathways. The method is based on the application of principal component analysis to a collection of proteomics and target molecule production data to pinpoint specific enzymes that need to have their expression level adjusted to maximize production. We illustrated the method on the heterologous mevalonate pathway in Escherichia coli that produces a wide range of isoprenoids and requires balanced pathway gene expression for high yields and titers. PCAP-guided engineering resulted in over a 40% improvement in the production of two valuable terpenes. PCAP could potentially be productively applied to other heterologous pathways as well.

[Research on high-order Windkessel model for assessing vascular compliance].

In this paper, we propose the construction of a fifth-order Windkessel model, and give complete mathematical solutions for this model. Utilizing the diastolic pulse wave analytical methods, we derived the parameters of the mathematical model. The parameters were further applied to estimate arterial compliance, blood flow inertia, peripheral resistance and other indices. With simulation tools we assess the validity of the model, and built a simulation circuit with the model parameters R, C and L. The model parameters were obtained from the high-order Windkessel model. The stroke volume of left ventricle is employed as the input of the simulation circuit. At the end of the circuit, the responding signal was gained. And it in turn was compared with the measured pulse waveform. The results show that the fifth-order Windkessel model is superior to the third-order Windkessel model in the pulse wave fitting and stability, and thus better reflects the role of microvessles in the circulatory system.

Enhancing the deceleration capacity index of heart rate by modified-phase-rectified signal averaging.

Deceleration capacity (DC) of heart rate is a novel indicator of autonomic nervous system (ANS) activity. In this paper, we proposed a modified DC index based on improved phase-rectified signal averaging (PRSA) algorithm. Sinusoidal analysis is applied to elucidate the rationality of the improved PRSA. Then the validity of the modified DC is verified by the databases of chronic heart failure (CHF) patients and control group. Both the conventional and modified DCs are significantly lower in CHF patients than that in the control group (2.12 +/- 2.98 vs. 6.34 +/- 1.92 ms, P < 0.0001 and 5.45 +/- 2.48 vs. 10.64 +/- 1.76 ms, P < 0.0001, respectively). And the modified DC provides higher accuracy in distinguishing CHF than the conventional one (87.4 vs. 82.1%). The results indicate that the suggested technique enhances the performance of PRSA and improves the efficiency of DC in assessing ANS activity in CHF patients.