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Sökning: WFRF:(Xun Wei)

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1.
  • Beal, Jacob, et al. (författare)
  • Robust estimation of bacterial cell count from optical density
  • 2020
  • Ingår i: Communications Biology. - : Springer Science and Business Media LLC. - 2399-3642. ; 3:1
  • Tidskriftsartikel (refereegranskat)abstract
    • Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data.
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2.
  • Fan, Wei, et al. (författare)
  • A Data-Driven Machining Error Analysis Method for Finish Machining of Assembly Interfaces of Large-Scale Components
  • 2021
  • Ingår i: Journal of manufacturing science and engineering. - : ASME International. - 1087-1357 .- 1528-8935. ; 143:4
  • Tidskriftsartikel (refereegranskat)abstract
    • To guarantee the final assembly quality of the large-scale components, the assembly interfaces of large components need to be finish-machined on site. Such assembly interfaces are often in low-stiffness structure and made of difficult-to-cut materials, which makes it hard to fulfill machining tolerance. To solve this issue, a data-driven adaptive machining error analysis and compensation method is proposed based on on-machine measurement. Within this context, an initial definite plane is fitted via an improved robust iterating least-squares plane-fitting method based on the spatial statistical analysis result of machining errors of the key measurement points. Then, the parameters of the definite plane are solved by a simulated annealing-particle swarm optimization (SA-PSO) algorithm to determine the optimal definite plane; it effectively decomposes the machining error into systematic error and process error. To reduce these errors, compensation methods, tool-path adjustment method, and an optimized group of cutting parameters are proposed. The proposed method is validated by a set of cutting tests of an assembly interface of a large-scale aircraft vertical tail. The results indicate that the machining errors are successfully separated, and each type of error has been reduced by the proposed method. A 0.017 mm machining accuracy of the wall-thickness of the assembly interface has been achieved, well fulfilling the requirement of 0.05 mm tolerance.
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3.
  • Fan, Wei, et al. (författare)
  • A machining accuracy informed adaptive positioning method for finish machining of assembly interfaces of large-scale aircraft components
  • 2021
  • Ingår i: Robotics and Computer-Integrated Manufacturing. - : Elsevier BV. - 0736-5845 .- 1879-2537. ; 67
  • Tidskriftsartikel (refereegranskat)abstract
    • An assembly interface of a large-scale aircraft component is a joint surface to connect adjacent large components. To guarantee the final assembly accuracy of the large components, the assembly interface is finish machined on site before the final assembly to cut the observed machining allowance. Thus, aiming at realizing the high efficiency and high quality in the finish machining operation, in this paper we propose an adaptive positioning method that integrates comprehensive engineering constrains (including Positioning Accuracy Constraints (PACs) of the large component and Machining Accuracy Constraints (MACs) of the assembly interface). In this method, the key Measurement Points (MPs) of a component are assigned to obtain its initial pose. Then the measurement data and the initial pose are used as input data to obtain the optimal pose parameters of the component based on an improved Particle Swarm Optimization Simulated Annealing (PSO-SA) algorithm. The optimal pose parameters can provide data support for the adaptive positioning of the large component, the function of which is implemented based on IEC 61499 Function Block (FB) technology. Finally, a positioning experiment of a vertical tail of a large passenger aircraft is used to validate the proposed method. The experimental results illustrate that the proposed method can improve the efficiency and positioning accuracy of the large component, compared to the traditional method.
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4.
  • Leebens-Mack, James H., et al. (författare)
  • One thousand plant transcriptomes and the phylogenomics of green plants
  • 2019
  • Ingår i: Nature. - : Nature Publishing Group. - 0028-0836 .- 1476-4687. ; 574:7780, s. 679-
  • Tidskriftsartikel (refereegranskat)abstract
    • Green plants (Viridiplantae) include around 450,000-500,000 species(1,2) of great diversity and have important roles in terrestrial and aquatic ecosystems. Here, as part of the One Thousand Plant Transcriptomes Initiative, we sequenced the vegetative transcriptomes of 1,124 species that span the diversity of plants in a broad sense (Archaeplastida), including green plants (Viridiplantae), glaucophytes (Glaucophyta) and red algae (Rhodophyta). Our analysis provides a robust phylogenomic framework for examining the evolution of green plants. Most inferred species relationships are well supported across multiple species tree and supermatrix analyses, but discordance among plastid and nuclear gene trees at a few important nodes highlights the complexity of plant genome evolution, including polyploidy, periods of rapid speciation, and extinction. Incomplete sorting of ancestral variation, polyploidization and massive expansions of gene families punctuate the evolutionary history of green plants. Notably, we find that large expansions of gene families preceded the origins of green plants, land plants and vascular plants, whereas whole-genome duplications are inferred to have occurred repeatedly throughout the evolution of flowering plants and ferns. The increasing availability of high-quality plant genome sequences and advances in functional genomics are enabling research on genome evolution across the green tree of life.
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5.
  • Xun, Wei Wei, et al. (författare)
  • Single-nucleotide polymorphisms (5p15.33, 15q25.1, 6p22.1, 6q27 and 7p15.3) and lung cancer survival in the European Prospective Investigation into Cancer and Nutrition (EPIC).
  • 2011
  • Ingår i: Mutagenesis. - : Oxford University Press (OUP). - 0267-8357 .- 1464-3804. ; 26:5, s. 657-666
  • Tidskriftsartikel (refereegranskat)abstract
    • The single-nucleotide polymorphisms (SNPs) rs402710 (5p15.33), rs16969968 and rs8034191 (15q25.1) have been consistently identified by genome-wide association studies (GWAS) as significant predictors of lung cancer risk, while rs4324798 (6p22.1) was previously found to influence survival time in small-cell lung cancer (SCLC) patients. Using the same population of one of the original GWAS, we investigated whether the selected SNPs and 31 others (also identified in GWAS) influence survival time, assuming an additive model. The effect of each polymorphism on all cause survival was estimated in 1094 lung cancer patients, and lung cancer-specific survival in 763 patients, using Cox regression adjusted for a priori confounders and competing causes of death where appropriate. Overall, after 1558 person-years of post-diagnostic follow-up, 874 deaths occurred from all causes, including 690 from lung cancer. In the lung cancer-specific survival analysis (1102 person-years), only rs7452888 (6q27) and rs2710994 (7p15.3) modified survival, with adjusted hazard ratios of 1.19 (P = 0.009) and 1.32 (P = 0.011) respectively, taking competing risks into account. Some weak associations were identified in subgroup analysis for rs16969968 and rs8034191 (15q25.1) and rs4324798 (6p22.1) and survival in never-smokers, as well as for rs402710 in current smokers and SCLC patients. In conclusion, rs402710 (5p15.33), rs16969968 and rs8034191 (both 15q25.1) and rs4324798 (6p22.1) were found to be unrelated to survival times in this large cohort of lung cancer patients, regardless of whether the cause of death was from lung cancer or not. However, rs7452888 (6q27) was identified as a possible candidate SNP to influence lung cancer survival, while stratified analysis hinted at a possible role for rs8034191, rs16969968 (15q25.1) and rs4324798 (6p22.1) in influencing survival time in lung cancer patients who were never-smokers, based on a small sample.
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6.
  • Baltar, Valéria Troncoso, et al. (författare)
  • A structural equation modelling approach to explore the role of B vitamins and immune markers in lung cancer risk
  • 2013
  • Ingår i: European Journal of Epidemiology. - : Springer Science and Business Media LLC. - 0393-2990 .- 1573-7284. ; 28:8, s. 677-688
  • Tidskriftsartikel (refereegranskat)abstract
    • The one-carbon metabolism (OCM) is considered key in maintaining DNA integrity and regulating gene expression, and may be involved in the process of carcinogenesis. Several B-vitamins and amino acids have been implicated in lung cancer risk, via the OCM directly as well as immune system activation. However it is unclear whether these factors act independently or through complex mechanisms. The current study applies structural equations modelling (SEM) to further disentangle the mechanisms involved in lung carcinogenesis. SEM allows simultaneous estimation of linear relations where a variable can be the outcome in one equation and the predictor in another, as well as allowing estimation using latent variables (factors estimated by correlation matrix). A large number of biomarkers have been analysed from 891 lung cancer cases and 1,747 controls nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Four putative mechanisms in the OCM and immunity were investigated in relation to lung cancer risk: methionine-homocysteine metabolism, folate cycle, transsulfuration, and mechanisms involved in inflammation and immune activation, all adjusted for tobacco exposure. The hypothesized SEM model confirmed a direct and protective effect for factors representing methionine-homocysteine metabolism (p = 0.020) and immune activation (p = 0.021), and an indirect protective effect of folate cycle (p = 0.019), after adjustment for tobacco smoking. In conclusion, our results show that in the investigation of the involvement of the OCM, the folate cycle and immune system in lung carcinogenesis, it is important to consider complex pathways (by applying SEM) rather than the effects of single vitamins or nutrients (e.g. using traditional multiple regression). In our study SEM were able to suggest a greater role of the methionine-homocysteine metabolism and immune activation over other potential mechanisms.
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7.
  • Baltar, Valéria Troncoso, et al. (författare)
  • Smoking, secondhand smoke, and cotinine levels in a subset of EPIC cohort
  • 2011
  • Ingår i: Cancer Epidemiology, Biomarkers and Prevention. - : American Association for Cancer Research. - 1055-9965 .- 1538-7755. ; 20:5, s. 869-875
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Several countries are discussing new legislation regarding the ban on smoking in public places, based on the growing evidence of the hazards of secondhand smoke (SHS) exposure. The objective of the present study is to quantitatively assess the relationship between smoking, SHS, and serum cotinine levels in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Methods: From a study on lung cancer in the EPIC cohort, questionnaire information on smoking was collected at enrolment, and cotinine was measured in serum. Three statistical models were applied by using samples available in a cross-section design: (i) cotinine levels by categories combining smoking and SHS (n = 859); (ii) the effect of hours of passive smoking exposure in nonsmokers only (n = 107); (iii) the effect of the number of cigarettes consumed per day in current smokers only (n = 832). All models were adjusted for country, sex, age, and body mass index. Results: Among nonsmokers, passive smokers presented significant differences in cotinine compared with nonexposed, with a marked (but not significant) difference among former-smokers. A one hour per day increment of SHS gave rise to a significant 2.58 nmol/L (0.45 ng/mL) increase in mean serum cotinine (P < 0.001). In current smokers, a one cigarette per day increment gave rise to a significant 22.44 nmol/L (3.95 ng/mL) increase in cotinine mean (P < 0.001). Conclusions: There is clear evidence that not only tobacco smoking but also involuntary exposure increases cotinine levels. Impact: This study strengthens the evidence for the benefits of a smoking ban in public places.
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8.
  • Beelen, Rob, et al. (författare)
  • Effects of long-term exposure to air pollution on natural-cause mortality : an analysis of 22 European cohorts within the multicentre ESCAPE project
  • 2014
  • Ingår i: The Lancet. - : Elsevier. - 0140-6736 .- 1474-547X. ; 383:9919, s. 785-795
  • Tidskriftsartikel (refereegranskat)abstract
    • Background Few studies on long-term exposure to air pollution and mortality have been reported from Europe. Within the multicentre European Study of Cohorts for Air Pollution Effects (ESCAPE), we aimed to investigate the association between natural-cause mortality and long-term exposure to several air pollutants. Methods We used data from 22 European cohort studies, which created a total study population of 367 251 participants. All cohorts were general population samples, although some were restricted to one sex only. With a strictly standardised protocol, we assessed residential exposure to air pollutants as annual average concentrations of particulate matter (PM) with diameters of less than 2.5 mu m (PM2.5), less than 10 mu m (PM10), and between 10 mu m and 2.5 mu m (PMcoarse), PM2.5 absorbance, and annual average concentrations of nitrogen oxides (NO2 and NOx), with land use regression models. We also investigated two traffic intensity variables-traffic intensity on the nearest road (vehicles per day) and total traffic load on all major roads within a 100 m buff er. We did cohort-specific statistical analyses using confounder models with increasing adjustment for confounder variables, and Cox proportional hazards models with a common protocol. We obtained pooled effect estimates through a random-effects meta-analysis. Findings The total study population consisted of 367 251 participants who contributed 5 118 039 person-years at risk (average follow-up 13.9 years), of whom 29 076 died from a natural cause during follow-up. A significantly increased hazard ratio (HR) for PM2.5 of 1.07 (95% CI 1.02-1.13) per 5 mu g/m(3) was recorded. No heterogeneity was noted between individual cohort effect estimates (I-2 p value=0.95). HRs for PM2.5 remained significantly raised even when we included only participants exposed to pollutant concentrations lower than the European annual mean limit value of 25 mu g/m(3) (HR 1.06, 95% CI 1.00-1.12) or below 20 mu g/m(3) (1.07, 1.01-1.13). Interpretation Long-term exposure to fine particulate air pollution was associated with natural-cause mortality, even within concentration ranges well below the present European annual mean limit value.
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9.
  • Beelen, Rob, et al. (författare)
  • Long-term Exposure to Air Pollution and Cardiovascular Mortality An Analysis of 22 European Cohorts
  • 2014
  • Ingår i: Epidemiology. - : Lippincott Williams & Wilkins. - 1044-3983 .- 1531-5487. ; 25:3, s. 368-378
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Air pollution has been associated with cardiovascular mortality, but it remains unclear as to whether specific pollutants are related to specific cardiovascular causes of death. Within the multicenter European Study of Cohorts for Air Pollution Effects (ESCAPE), we investigated the associations of long-term exposure to several air pollutants with all cardiovascular disease (CVD) mortality, as well as with specific cardiovascular causes of death. Methods: Data from 22 European cohort studies were used. Using a standardized protocol, study area-specific air pollution exposure at the residential address was characterized as annual average concentrations of the following: nitrogen oxides (NO2 and NOx); particles with diameters of less than 2.5 mu m (PM2.5), less than 10 mu m (PM10), and 10 mu m to 2.5 mu m (PMcoarse); PM2.5 absorbance estimated by land-use regression models; and traffic indicators. We applied cohort-specific Cox proportional hazards models using a standardized protocol. Random-effects meta-analysis was used to obtain pooled effect estimates. Results: The total study population consisted of 367,383 participants, with 9994 deaths from CVD (including 4,992 from ischemic heart disease, 2264 from myocardial infarction, and 2484 from cerebrovascular disease). All hazard ratios were approximately 1.0, except for particle mass and cerebrovascular disease mortality; for PM2.5, the hazard ratio was 1.21 (95% confidence interval = 0.87-1.69) per 5 mu g/m(3) and for PM10, 1.22 (0.91-1.63) per 10 mu g/m(3). Conclusion: In a joint analysis of data from 22 European cohorts, most hazard ratios for the association of air pollutants with mortality from overall CVD and with specific CVDs were approximately 1.0, with the exception of particulate mass and cerebrovascular disease mortality for which there was suggestive evidence for an association.
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10.
  • Beelen, Rob, et al. (författare)
  • Natural-Cause Mortality and Long-Term Exposure to Particle Components : An Analysis of 19 European Cohorts within the Multi-Center ESCAPE Project
  • 2015
  • Ingår i: Journal of Environmental Health Perspectives. - : Environmental Health Perspectives. - 0091-6765 .- 1552-9924. ; 123:6, s. 525-533
  • Forskningsöversikt (refereegranskat)abstract
    • Background: Studies have shown associations between mortality and long-term exposure to particulate matter air pollution. Few cohort studies have estimated the effects of the elemental composition of particulate matter on mortality. Objectives: Our aim was to study the association between natural-cause mortality and long-term exposure to elemental components of particulate matter. Methods: Mortality and confounder data from 19 European cohort studies were used. Residential exposure to eight a priori-selected components of particulate matter ( PM) was characterized following a strictly standardized protocol. Annual average concentrations of copper, iron, potassium, nickel, sulfur, silicon, vanadium, and zinc within PM size fractions <= 2.5 mu m (PM2.5) and <= 10 mu m (PM10) were estimated using land-use regression models. Cohort-specific statistical analyses of the associations between mortality and air pollution were conducted using Cox proportional hazards models using a common protocol followed by meta-analysis. Results: The total study population consisted of 291,816 participants, of whom 25,466 died from a natural cause during follow-up (average time of follow-up, 14.3 years). Hazard ratios were positive for almost all elements and statistically significant for PM2.5 sulfur (1.14; 95% CI: 1.06, 1.23 per 200ng/m(3)). In a two-pollutant model, the association with PM2.5 sulfur was robust to adjustment for PM2.5 mass, whereas the association with PM2.5 mass was reduced. Conclusions: Long-term exposure to PM2.5 sulfur was associated with natural-cause mortality. This association was robust to adjustment for other pollutants and PM2.5.
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