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| 2. |
- Beal, Jacob, et al.
(författare)
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Robust estimation of bacterial cell count from optical density
- 2020
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Ingår i: Communications Biology. - : Springer Science and Business Media LLC. - 2399-3642. ; 3:1
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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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| 3. |
- Dai, Helong, et al.
(författare)
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Blockade of CD27/CD70 pathway to reduce the generation of memory T cells and markedly prolong the survival of heart allografts in presensitized mice
- 2011
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Ingår i: Transplant Immunology. - : Elsevier BV. - 1878-5492 .- 0966-3274. ; 24:4, s. 195-202
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Tidskriftsartikel (refereegranskat)abstract
- Background: Alloreactive memory T cells are a major obstacle to transplantation acceptance due to their capacity for accelerated rejection. Methods: C57BL/6 mice that had rejected BALB/c skin grafts 4 weeks earlier were used as recipients. The recipient mice were treated with anti-CD154/LFA-1 with or without anti-CD70 during the primary skin transplantation and anti-CD154/LFA-1 or not during the secondary transplantation of BALB/c heart. We evaluated the impact of combinations of antibody-mediated blockade on the generation of memory T cells and graft survival after fully MHC-mismatched transplantations. Results: One month after the primary skin transplantation, the proportions of CD4(+) memory T cells/CD4(+) T cells and CD8(+)memory T cells/CD8(+) T cells in the anti-CD154/LFA-1 combination group were 47.32 +/- 428% and 23.18 +/- 2.77%, respectively. In the group that included anti-CD70 treatment, the proportions were reduced to 34.10 +/- 2.71% and 12.19 +/- 3.52% (P<0.05 when comparing the proportion of memory T cells between the two groups). The addition of anti-CD70 to the treatment regimen prolonged the mean survival time following secondary heart transplantation from 10 days to more than 90 days (P<0.001). Furthermore, allogenic proliferation of recipient splenic T cells and graft-infiltrating lymphocytes were significantly decreased. Meanwhile, the proportion of regulatory T cells was increased to 9.46 +/- 1.48% on day 100 post-transplantation (P<0.05). Conclusions: The addition of anti-CD70 to the anti-CD154/LFA-1 combination given during the primary transplantation reduced the generation of memory T cells. This therapy regimen provided a potential means to alleviate the accelerated rejection mediated by memory T cells during secondary heart transplantation and markedly prolong the survival of heart allografts. (C) 2011 Elsevier B.V. All rights reserved.
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| 4. |
- Doherty, Brett T, et al.
(författare)
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Maternal, cord, and three-year-old child serum thyroid hormone concentrations in the Health Outcomes and Measures of the Environment study
- 2020
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Ingår i: Clinical Endocrinology. - : Blackwell Science Ltd.. - 0300-0664 .- 1365-2265. ; 92:4, s. 366-372
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Tidskriftsartikel (refereegranskat)abstract
- PURPOSE: Maternal thyroid function during pregnancy may influence offspring thyroid function, though relations between maternal and child thyroid function are incompletely understood. We sought to characterize relations between maternal, cord and child thyroid hormone concentrations in a population of mother-child pairs with largely normal thyroid function.METHODS: In a prospective birth cohort, we measured thyroid hormone concentrations in 203 mothers at 16 gestational weeks, 273 newborns and 159 children at 3 years among participants in the Health Outcomes and Measures of the Environment (HOME) Study. We used multivariable linear regression to estimate associations of maternal thyroid hormones during pregnancy with cord serum thyroid hormones and also estimated associations of maternal and cord thyroid hormones with child thyroid-stimulating hormone (TSH).RESULTS: Each doubling of maternal TSH was associated with a 16.4% increase of newborn TSH (95% CI: 3.9%, 30.5%), and each doubling of newborn TSH concentrations was associated with a 10.4% increase in child TSH concentrations at 3 years (95% CI: 0.1%, 21.7%). An interquartile range increase in cord FT4 concentrations was associated with an 11.7% decrease in child TSH concentrations at 3 years (95% CI: -20.2%, -2.3%).CONCLUSIONS: We observed relationships between maternal, newborn and child thyroid hormone concentrations in the HOME Study. Our study contributes to understandings of interindividual variability in thyroid function among mother-child pairs, which may inform future efforts to identify risk factors for thyroid disorders or thyroid-related health outcomes.
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| 5. |
- Liu, Yongkui, et al.
(författare)
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A framework for scheduling in cloud manufacturing with deep reinforcement learning
- 2019
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Ingår i: 2019 IEEE 17th International Conference on Industrial Informatics Aalto University (INDIN). - : Institute of Electrical and Electronics Engineers (IEEE). ; , s. 1775-1780
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Konferensbidrag (refereegranskat)abstract
- Cloud manufacturing is a novel service-oriented networked manufacturing paradigm that aims to provide on-demand manufacturing cloud services to consumers. Scheduling is a critical means for achieving that aim. Currently, research on scheduling in cloud manufacturing is still in its infancy, and current frequently adopted meta-heuristic algorithm-based approaches have some shortcomings, e.g. they require complex design processes and lack adaptability to dynamic environments. Deep reinforcement learning (DRL) that combines advantages of reinforcement learning and deep learning provides an efficient, adaptive and intelligent approach for solving scheduling problems in cloud manufacturing. However, to the best of our knowledge, there has been no application of DRL to scheduling in cloud manufacturing. This work conducts a preliminary exploration over this issue. First, a DRL-based framework for scheduling in cloud manufacturing is proposed. Then a DRL model for online single-task scheduling in cloud manufacturing is presented to demonstrate the effectiveness of the framework. DRL as a promising technique will find wide applications in cloud manufacturing, and this work can provide some reference for future research on this.
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| 6. |
- Stanaway, Jeffrey D., et al.
(författare)
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Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories, 1990-2017: A systematic analysis for the Global Burden of Disease Study 2017
- 2018
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Ingår i: The Lancet. - 1474-547X .- 0140-6736. ; 392:10159, s. 1923-1994
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Tidskriftsartikel (refereegranskat)abstract
- Background The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 comparative risk assessment (CRA) is a comprehensive approach to risk factor quantification that offers a useful tool for synthesising evidence on risks and risk-outcome associations. With each annual GBD study, we update the GBD CRA to incorporate improved methods, new risks and risk-outcome pairs, and new data on risk exposure levels and risk- outcome associations. Methods We used the CRA framework developed for previous iterations of GBD to estimate levels and trends in exposure, attributable deaths, and attributable disability-adjusted life-years (DALYs), by age group, sex, year, and location for 84 behavioural, environmental and occupational, and metabolic risks or groups of risks from 1990 to 2017. This study included 476 risk-outcome pairs that met the GBD study criteria for convincing or probable evidence of causation. We extracted relative risk and exposure estimates from 46 749 randomised controlled trials, cohort studies, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. Using the counterfactual scenario of theoretical minimum risk exposure level (TMREL), we estimated the portion of deaths and DALYs that could be attributed to a given risk. We explored the relationship between development and risk exposure by modelling the relationship between the Socio-demographic Index (SDI) and risk-weighted exposure prevalence and estimated expected levels of exposure and risk-attributable burden by SDI. Finally, we explored temporal changes in risk-attributable DALYs by decomposing those changes into six main component drivers of change as follows: (1) population growth; (2) changes in population age structures; (3) changes in exposure to environmental and occupational risks; (4) changes in exposure to behavioural risks; (5) changes in exposure to metabolic risks; and (6) changes due to all other factors, approximated as the risk-deleted death and DALY rates, where the risk-deleted rate is the rate that would be observed had we reduced the exposure levels to the TMREL for all risk factors included in GBD 2017.
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| 7. |
- Wang, Yan, et al.
(författare)
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Synergy of orographic drag parameterization and high resolution greatly reduces biases of WRF-simulated precipitation in central Himalaya
- 2020
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Ingår i: Climate Dynamics. - : Springer Science and Business Media LLC. - 0930-7575 .- 1432-0894. ; 54:3-4, s. 1729-40
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Tidskriftsartikel (refereegranskat)abstract
- Current climate models often have significant wet biases in the Tibetan Plateau and encounter particular difficulties in representing the climatic effect of the Central Himalaya Mountain (CHM), where the gradient of elevation is extremely steep and the terrain is complex. Yet, there were few studies dealing with the issue in the high altitudes of this region. In order to improve climate modeling in this region, a network consisting of 14 rain gauges was set up at elevations >2800 m above sea level along a CHM valley. Numerical experiments with Weather Research and Forecasting model were conducted to investigate the effects of meso- and micro-scale terrain on water vapor transport and precipitation. The control case uses a high horizontal resolution (0.03°) and a Turbulent Orographic Form Drag (TOFD) scheme to resolve the mesoscale terrain and to represent sub-grid microscale terrain effect. The effects of the horizontal resolution and the TOFD scheme were then analyzed through comparisons with sensitivity cases that either use a low horizontal resolution (0.09°) or switch off the TOFD scheme. The results show that the simulations with high horizontal resolution, even without the TOFD scheme, can not only increase the spatial consistency (correlation coefficient 0.84–0.92) between the observed and simulated precipitation, but also considerably reduce the wet bias by more than 250%. Adding the TOFD scheme further reduces the precipitation bias by 50% or so at almost all stations in the CHM. The TOFD scheme reduces precipitation intensity, especially heavy precipitation (>10 mm h−1) over high altitudes of the CHM. Both high horizontal resolution and TOFD enhance the orographic drag to slow down wind; as a result, less water vapor is transported from lowland to the high altitudes of CHM, causing more precipitation at lowland area of the CHM and less at high altitudes of CHM. Therefore, in this highly terrain-complex region, it is crucial to use a high horizontal resolution to depict mesoscale complex terrain and a TOFD scheme to parameterize the drag caused by microscale complex terrain.
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| 8. |
- Xu, Kangjun, et al.
(författare)
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Association between serum vitamin B12 and risk of all-cause mortality in elderly adults : a prospective cohort study
- 2021
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Ingår i: BMC Geriatrics. - : BioMed Central. - 1471-2318. ; 21:1
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND AND PURPOSE: Results from previous studies that linking vitamin B12 to risk of chronic diseases or mortality are inconsistent. We hereby explore the association between serum concentration of vitamin B12 and all-cause mortality risk in elderly adults.METHODS: Participants aged over 65 years in the Chinese Longitudinal Healthy Longevity Survey were included in present prospective cohort study. Serum vitamin B12 was assessed at the 2011-2012 and 2014 wave, respectively. Participants were divided into three groups based on two cut-off points - 10th and 90th percentiles of vitamin B12 concentrations - in the whole population. Cox regression model was used to calculate the hazard ratio (HR) and 95 % confidence intervals (95 % CIs), and restricted cubic spline function was further modelled to investigate their dose-response associations.RESULTS: Among 2,086 participants [mean ± SD: 87.74 ± 11.24 years, 908 (43.53 %) males], 943 (45.21 %) died during an average follow-up of 3.34 (SD: 1.63) years. Comparing with participants with middle concentration of serum vitamin B12, participants with high concentration had an increased risk of all-cause mortality [HR (95 %CIs): 1.30 (1.03-1.64)], whereas participants with low concentration had an insignificantly decreased risk of all-cause mortality (0.96, 0.76-1.20). The positive association between high concentration of serum vitamin B12 and all-cause mortality was also observed among the male and in a series of sensitivity analyses. In the dose-response analysis, a J-shape pattern was observed, but the non-linear association was only significant in males (Pnon-linearity = 0.0351).CONCLUSIONS: High concentration of serum vitamin B12 was associated with an increased risk of all-cause mortality in a J-shaped pattern. The precise mechanisms underlying the association remain to be explored.
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| 9. |
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| 10. |
- Yao, Junying, et al.
(författare)
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Robotic grasping training using deep reinforcement learning with policy guidance mechanism
- 2021
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Ingår i: Proceedings of the ASME 2021 16th International Manufacturing Science and Engineering Conference, MSEC 2021. - : ASME International.
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Konferensbidrag (refereegranskat)abstract
- For the past few years, training robots to enable them to learn various manipulative skills using deep reinforcement learning (DRL) has arisen wide attention. However, large search space, low sample quality, and difficulties in network convergence pose great challenges to robot training. This paper deals with assembly-oriented robot grasping training and proposes a DRL algorithm with a new mechanism, namely, policy guidance mechanism (PGM). PGM can effectively transform useless or low-quality samples to useful or high-quality ones. Based on the improved Deep Q Network algorithm, an end-to-end policy model that takes images as input and outputs actions is established. Through continuous interactions with the environment, robots are able to learn how to optimally grasp objects according to the location of maximum Q value. A number of experiments for different scenarios using simulations and physical robots are conducted. Results indicate that the proposed DRL algorithm with PGM is effective in increasing the success rate of robot grasping, and moreover, is robust to changes of environment and objects. Copyright
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