| 1. |
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| 2. |
- Kristanl, Matej, et al.
(författare)
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The Seventh Visual Object Tracking VOT2019 Challenge Results
- 2019
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Ingår i: 2019 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION WORKSHOPS (ICCVW). - : IEEE COMPUTER SOC. - 9781728150239 ; , s. 2206-2241
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Konferensbidrag (refereegranskat)abstract
- The Visual Object Tracking challenge VOT2019 is the seventh annual tracker benchmarking activity organized by the VOT initiative. Results of 81 trackers are presented; many are state-of-the-art trackers published at major computer vision conferences or in journals in the recent years. The evaluation included the standard VOT and other popular methodologies for short-term tracking analysis as well as the standard VOT methodology for long-term tracking analysis. The VOT2019 challenge was composed of five challenges focusing on different tracking domains: (i) VOT-ST2019 challenge focused on short-term tracking in RGB, (ii) VOT-RT2019 challenge focused on "real-time" short-term tracking in RGB, (iii) VOT-LT2019 focused on long-term tracking namely coping with target disappearance and reappearance. Two new challenges have been introduced: (iv) VOT-RGBT2019 challenge focused on short-term tracking in RGB and thermal imagery and (v) VOT-RGBD2019 challenge focused on long-term tracking in RGB and depth imagery. The VOT-ST2019, VOT-RT2019 and VOT-LT2019 datasets were refreshed while new datasets were introduced for VOT-RGBT2019 and VOT-RGBD2019. The VOT toolkit has been updated to support both standard short-term, long-term tracking and tracking with multi-channel imagery. Performance of the tested trackers typically by far exceeds standard baselines. The source code for most of the trackers is publicly available from the VOT page. The dataset, the evaluation kit and the results are publicly available at the challenge website(1).
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| 7. |
- Chen, Song, et al.
(författare)
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Early osteoimmunomodulation by mucin hydrogels augments the healing and revascularization of rat critical-size calvarial bone defects
- 2023
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Ingår i: BIOACTIVE MATERIALS. - : Elsevier BV. - 2452-199X. ; 25, s. 176-188
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Tidskriftsartikel (refereegranskat)abstract
- The design principle of osteogenic bone grafts has shifted from immunological inertness to limiting foreign body response to combined osteoimmunomodulatory activity to promote high-quality endogenous bone regeneration. Recently developed immunomodulatory mucin hydrogels have been shown to elicit very low complement activation and suppress macrophage release and activation after implantation in vivo. However, their immunoregulatory activity has not yet been studied in the context of tissue repair. Herein, we synthesized mucinmonetite composite materials and investigated their early osteoimmunomodulation using a critical-size rat bone defect model. We demonstrated that the composites can polarize macrophages towards the M2 phenotype at weeks 1 and 2. The early osteoimmunomodulation enhanced early osteogenesis and angiogenesis and ultimately promoted fracture healing and engraftment (revascularization of the host vasculature) at weeks 6 and 12. Overall, we demonstrated the applicability of mucin-based immunomodulatory biomaterials to enhance tissue repair in tissue engineering and regenerative medicine.
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| 8. |
- Cheng, Jie, et al.
(författare)
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Interactions in Composite Film Formation of Mefp-1/graphene on Carbon Steel
- 2021
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Ingår i: Coatings. - : MDPI AG. - 2079-6412. ; 11:10
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Tidskriftsartikel (refereegranskat)abstract
- Mefp-1 adhesive protein derived from marine blue mussels, together with the 2D material graphene, was used to build the green composite film with enhanced anti-corrosion property and mechanical strength. The corrosion inhibition of the composite film, formed by different methods, was evaluated by using electrochemical impedance spectroscopy. The non-degraded adhesion of the composite film to the carbon steel substrate was proved by nano-scratch tests. Infrared spectroscopy was utilized to investigate the film formation process and "three-body interactions " between Mefp-1, graphene and carbon steel surface. The results show that the Mefp-1 adsorbs on the carbon steel surface mainly through the covalent bond between catechols and Fe(III). Meanwhile, Mefp-1 can bond to non-adhesive graphene by forming hydrogen bonds and pi-pi interaction non-covalent bonds, which facilitate the formation of a robust Mefp-1/graphene composite film on the carbon steel surface.
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| 9. |
- Gu, Qiang, et al.
(författare)
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VKORC1-1639G>A, CYP2C9, EPHX1691A>G genotype, body weight, and age are important predictors for warfarin maintenance doses in patients with mechanical heart valve prostheses in southwest China
- 2010
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Ingår i: European Journal of Clinical Pharmacology. - : Springer Science and Business Media LLC. - 0031-6970 .- 1432-1041. ; 66:12, s. 1217-1227
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Tidskriftsartikel (refereegranskat)abstract
- There were great interindividual differences in warfarin maintenance dosage (ranging from 0.6 to 8.4 mg/day) among the 127 patients with mechanical heart valve prostheses. VKORC1-1639G>A, CYP2C9, EPHX1691A>G polymorphism, body weight, and age were found to affect the dose demands. Multiple linear regression models incorporating genetic polymorphisms of VKORC1, CYP2C9, EPHX1691A>G, and the nongenetic factors of age and body weight were developed, and explained up to 76.8% of the total variation (adjusted R (2) of 0.743) in warfarin maintenance doses in southwest Chinese patients with mechanical heart valve prostheses.
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| 10. |
- Huang, He, et al.
(författare)
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Material informatics for uranium-bearing equiatomic disordered solid solution alloys
- 2021
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Ingår i: Materials Today Communications. - : Elsevier BV. - 2352-4928. ; 29
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Tidskriftsartikel (refereegranskat)abstract
- Near-equiatomic, multi-component alloys with disordered solid solution phase (DSSP) are associated with outstanding performance in phase stability, mechanical properties and irradiation resistance, and may provide a feasible solution for developing novel uranium-based alloys with better fuel capacity. In this work, we build a machine learning (ML) model of disordered solid solution alloys (DSSAs) based on about 6000 known multicomponent alloys and several materials descriptors to efficiently predict the DSSAs formation ability. To fully optimize the ML model, we develop a multi-algorithm cross-verification approach in combination with the SHapley Additive exPlanations value (SHAP value). We find that the Delta S-C, Lambda, Phi(s), gamma and 1/Omega, corresponding to the former two Hume - Rothery (H - R) rules, are the most important materials descriptors affecting DSSAs formation ability. When the ML model is applied to the 375 uranium-bearing DSSAs, 190 of them are predicted to be the DSSAs never known before. 20 of these alloys were randomly synthesized and characterized. Our predictions are in-line with experiments with 3 inconsistent cases, suggesting that our strategy offers a fast and accurate way to predict novel multi-component alloys with high DSSAs formation ability. These findings shed considerable light on the mapping between the material descriptors and DSSAs formation ability.
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| 11. |
- Huang, Tony, et al.
(författare)
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What has digital transformation changed? : A Chinese case study of hidden costs using a socio-economic approach to management
- 2023
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Ingår i: Revue Française de Gestion Industrielle. - France. - 0242-9780 .- 2804-9284. ; 37:1, s. 41-54
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Digital transformation is regarded as a way to solve business problems in an organisation. However, the impact on the company’s hidden costs should also be more precisely analysed. This research relies on the socio-economic approach to management to describe the impact of digital transformation maturity growth on hidden costs in a Chinese manufacturing company. This paper combines the case study research method with some quantitative techniques by conducting correlation analyses of staff turnover, low-quality work and occupational injuries and diseases. The results indicate that digital transformation maturity growth is correlated with the financial consequences of staff’s excess salary in terms of turnover and with non-production in terms of occupational injuries and diseases. Moreover, this study suggests that future studies should consider the impact of digital transformation maturity growth on these three factors in light of the corresponding contextual factors regarding organisational contexts and cultures.
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| 12. |
- Liu, Dachuan, et al.
(författare)
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Amorphous iron-calcium phosphate-mediated biomineralized scaffolds for vascularized bone regeneration
- 2023
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Ingår i: Materials & design. - : Elsevier BV. - 0264-1275 .- 1873-4197. ; 235
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Tidskriftsartikel (refereegranskat)abstract
- Construction of organic–inorganic composites similar to natural bone in terms of structure and composition has attracted extensive attention. However, the clinical applications of these composites are limited due to the insufficient osteogenic and mechanical properties. In nature, the presence of amorphous iron-calcium phosphate (Fe-ACP) strengthens the mechanical properties of some biominerals, and our previous study has revealed its synthetic route and in vitro osteogenic properties. However, the potential role of Fe-ACP on biomineralization and constructing biomimetic scaffolds for bone regeneration has not been studied. Herein, a biomimetic scaffold with good osteogenic property was fabricated based on the mineralization of Fe-ACP, with the assistance of ice-templated freeze-casting. The in vitro study showed that the mineralized scaffolds possessed favorable biocompatibility and osteogenic property. Moreover, the scaffolds promoted cell chemotaxis and angiogenic property by upregulating the hypoxia inducible factor-1α (HIF-1α). In vivo experiment demonstrated potent early osteogenesis along with angiogenesis and ultimately promoted bone regeneration. Overall, the mineralized scaffold mediated by Fe-ACP precursors provide a unique platform to enhance bone tissue repair.
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| 13. |
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| 15. |
- Pecunia, Vincenzo, et al.
(författare)
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Roadmap on energy harvesting materials
- 2023
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Ingår i: Journal of Physics. - : IOP Publishing. - 2515-7639. ; 6:4
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Tidskriftsartikel (refereegranskat)abstract
- Ambient energy harvesting has great potential to contribute to sustainable development and address growing environmental challenges. Converting waste energy from energy-intensive processes and systems (e.g. combustion engines and furnaces) is crucial to reducing their environmental impact and achieving net-zero emissions. Compact energy harvesters will also be key to powering the exponentially growing smart devices ecosystem that is part of the Internet of Things, thus enabling futuristic applications that can improve our quality of life (e.g. smart homes, smart cities, smart manufacturing, and smart healthcare). To achieve these goals, innovative materials are needed to efficiently convert ambient energy into electricity through various physical mechanisms, such as the photovoltaic effect, thermoelectricity, piezoelectricity, triboelectricity, and radiofrequency wireless power transfer. By bringing together the perspectives of experts in various types of energy harvesting materials, this Roadmap provides extensive insights into recent advances and present challenges in the field. Additionally, the Roadmap analyses the key performance metrics of these technologies in relation to their ultimate energy conversion limits. Building on these insights, the Roadmap outlines promising directions for future research to fully harness the potential of energy harvesting materials for green energy anytime, anywhere.
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| 16. |
- Qie, Zhiwei, et al.
(författare)
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Sensitive detection of atrazine in tap water using TELISA
- 2015
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Ingår i: Analyst. - : Royal Society of Chemistry (RSC). - 1364-5528. ; 140:15, s. 5220-5226
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Tidskriftsartikel (refereegranskat)abstract
- A highly sensitive flow injection analysis (FIA)-based thermal enzyme-linked immunoassay, TELISA, was developed for the rapid detection of atrazine (ATZ) in tap water. ATZ and beta-lactamase-labeled ATZ were employed in a competitive immunoassay using a monoclonal antibody (mAb). After the off-column liquid-phase competition, the mAb was captured on the Protein G Sepharose (TM) 4 Fast Flow (PGSFF) column support material. Injected beta-lactamase substrate ampicillin was degraded by the column-bound ATZ-beta-lactamase, generating a detectable heat signal. Several assay parameters were optimized, including substrate concentration, flow rates and regeneration conditions, as well as the mAb and ATZ-beta dilution ratios and concentrations. The assay linear range was 0.73-4.83 ng mL(-1) with a detection limit of 0.66 ng mL(-1). An entire heat signal requires 10 min for generation, and the cycle time is less than 40 min. The results were reproducible and stable. ATZ-spiked tap water samples exhibited a recovery rate of 103%-116%, which correlated with the UHPLC-MS/MS measurements. We attributed this significant increase in sensitivity over our previously published work to the following factors: (i) the capture of already-formed immune complexes on the column via immobilized Protein G, which eliminated chemical immobilization of the antibody; (ii) off-column preincubation allows the formation of immune complexes under nearly ideal conditions; and (iii) multiple buffers can be used to, in one case, enhance immune-complex formation and in the other to maximize enzymatic activity. Furthermore, the scheme creates a universal assay platform in which sensing is performed in the off-column incubation and detection after capture in the enzyme thermistor (ET) detector, which opens up the possibility of detecting any antigen for which antibodies were available.
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| 17. |
- Ringsberg, Jonas, 1971, et al.
(författare)
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MARSTRUCT benchmark study on nonlinear FE simulation of an experiment of an indenter impact with a ship side-shell structure
- 2018
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Ingår i: Marine Structures. - : Elsevier BV. - 0951-8339. ; 59:1, s. 142-157
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Tidskriftsartikel (refereegranskat)abstract
- This paper presents a benchmark study on collision simulations that was initiated by the MARSTRUCT Virtual Institute. The objective was to compare assumptions, finite element models, modelling techniques and experiences between established researchers within the field. Fifteen research groups world-wide participated in the study. An experiment involving a rigid indenter penetrating a ship-like side structure was used as the case study. A description of how the experiment was performed, the geometry model of it, and material properties were distributed to the participants prior to their simulations. The paper presents the results obtained from the fifteen FE simulations and the experiment. It presents a comparison of, among other factors, the reaction force versus the indenter displacement, internal energy absorbed by the structure versus the indenter displacement, and analyses of the participants’ ability to predict failure modes and events that were observed in the experiment. The outcome of the study is a discussion and recommendations regarding mesh size, failure criteria and damage models, interpretation of material data and how they are used in a constitutive material model, and finally, uncertainties in general.
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| 18. |
- Shen, Tangyao, et al.
(författare)
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Giant magneto field effect in up-conversion amplified spontaneous emission via spatially extended states in organic-inorganic hybrid perovskites
- 2022
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Ingår i: Opto-Electronic Advances. - : Editorial Office of Opto-Electronic Advances. - 2096-4579. ; 5:2
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Tidskriftsartikel (refereegranskat)abstract
- Up-conversion lasing actions are normally difficult to realize in light-emitting materials due to small multi-photon absorption cross section and fast dephasing of excited states during multi-photon excitation. This paper reports an easily accessible up-conversion amplified spontaneous emission (ASE) in organic-inorganic hybrid perovskites (MAPbBr(3)) films by optically exciting broad gap states with sub-bandgap laser excitation. The broad absorption was optimized by adjusting the grain sizes in the MAPbBr3 films. At low sub-bandgap pumping intensities, directly exciting the gap states leads to 2-photon, 3-photon, and 4-photon up-conversion spontaneous emission, revealing a large optical cross section of multiphoton excitation occurring in such hybrid perovskite films. At moderate pumping intensity (1.19 mJ/cm(2)) of 700 nm laser excitation, a significant spectral narrowing phenomenon was observed with the full width at half maximum (FWHM) decreasing from 18 nm to 4 nm at the peak wavelength of 550 nm, simultaneously with a nonlinear increase on spectral peak intensity, showing an up-conversion ASE realized at low threshold pumping fluence. More interestingly, the up-conversion ASE demonstrated a giant magnetic field effect, leading to a magneto-ASE reaching 120%. In contrast, the upconversion photoluminescence (PL) showed a negligible magnetic field effect (< 1%). This observation provides an evidence to indicate that the light-emitting states responsible for up-conversion ASE are essentially formed as spatially extended states. The angular dependent spectrum results further verify the existence of spatially extended states which are polarized to develop coherent in-phase interaction. Clearly, using broad gap states with spatially extended light-emitting states presents a new approach to develop up-conversion ASE in organic-inorganic hybrid perovskites.
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| 19. |
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| 20. |
- Sun, Bin, et al.
(författare)
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An Improved k-Nearest Neighbours Method for Traffic Time Series Imputation
- 2017
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Konferensbidrag (refereegranskat)abstract
- Intelligent transportation systems (ITS) are becoming more and more effective, benefiting from big data. Despite this, missing data is a problem that prevents many prediction algorithms in ITS from working effectively. Much work has been done to impute those missing data. Among different imputation methods, k-nearest neighbours (kNN) has shown excellent accuracy and efficiency. However, the general kNN is designed for matrix instead of time series so it lacks the usage of time series characteristics such as windows and weights that are gap-sensitive. This work introduces gap-sensitive windowed kNN (GSW-kNN) imputation for time series. The results show that GSW-kNN is 34% more accurate than benchmarking methods, and it is still robust even if the missing ratio increases to 90%.
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| 21. |
- Sun, Bin, et al.
(författare)
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An Overview of Parameter and Data Strategies for K-Nearest Neighbours Based Short-Term Traffic Prediction
- 2017
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Ingår i: ACM International Conference Proceeding Series Volume Part F133326. - New York, NY, USA : Association for Computing Machinery (ACM). - 9781450353762 ; , s. 68-74
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Konferensbidrag (refereegranskat)abstract
- Modern intelligent transportation systems (ITS) requires reliable and accurate short-term traffic prediction. One widely used method to predict traffic is k-nearest neighbours (kNN). Though many studies have tried to improve kNN with parameter strategies and data strategies, there is no comprehensive analysis of those strategies. This paper aims to analyse kNN strategies and guide future work to select the right strategy to improve prediction accuracy. Firstly, we examine the relations among three kNN parameters, which are: number of nearest neighbours (k), search step length (d) and window size (v). We also analysed predict step ahead (m) which is not a parameter but a user requirement and configuration. The analyses indicate that the relations among parameters are compound especially when traffic flow states are considered. The results show that strategy of using v leads to outstanding accuracy improvement. Later, we compare different data strategies such as flow-aware and time-aware ones together with ensemble strategies. The experiments show that the flowaware strategy performs better than the time-aware one. Thus, we suggest considering all parameter strategies simultaneously as ensemble strategies especially by including v in flow-aware strategies.
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| 22. |
- Sun, Bin, 1988-
(författare)
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Automated Traffic Time Series Prediction
- 2018
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Intelligent transportation systems (ITS) are becoming more and more effective. Robust and accurate short-term traffic prediction plays a key role in modern ITS and demands continuous improvement. Benefiting from better data collection and storage strategies, a huge amount of traffic data is archived which can be used for this purpose especially by using machine learning.For the data preprocessing stage, despite the amount of data available, missing data records and their messy labels are two problems that prevent many prediction algorithms in ITS from working effectively and smoothly. For the prediction stage, though there are many prediction algorithms, higher accuracy and more automated procedures are needed.Considering both preprocessing and prediction studies, one widely used algorithm is k-nearest neighbours (kNN) which has shown high accuracy and efficiency. However, the general kNN is designed for matrix instead of time series which lacks the use of time series characteristics. Choosing the right parameter values for kNN is problematic due to dynamic traffic characteristics. This thesis analyses kNN based algorithms and improves the prediction accuracy with better parameter handling using time series characteristics.Specifically, for the data preprocessing stage, this work introduces gap-sensitive windowed kNN (GSW-kNN) imputation. Besides, a Mahalanobis distance-based algorithm is improved to support correcting and complementing label information. Later, several automated and dynamic procedures are proposed and different strategies for making use of data and parameters are also compared.Two real-world datasets are used to conduct experiments in different papers. The results show that GSW-kNN imputation is 34% on average more accurate than benchmarking methods, and it is still robust even if the missing ratio increases to 90%. The Mahalanobis distance-based models efficiently correct and complement label information which is then used to fairly compare performance of algorithms. The proposed dynamic procedure (DP) performs better than manually adjusted kNN and other benchmarking methods in terms of accuracy on average. What is better, weighted parameter tuples (WPT) gives more accurate results than any human tuned parameters which cannot be achieved manually in practice. The experiments indicate that the relations among parameters are compound and the flow-aware strategy performs better than the time-aware one. Thus, it is suggested to consider all parameter strategies simultaneously as ensemble strategies especially by including window in flow-aware strategies.In summary, this thesis improves the accuracy and automation level of short-term traffic prediction with proposed high-speed algorithms.
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| 23. |
- Sun, Bin, 1988-, et al.
(författare)
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Correcting and complementing freeway traffic accident data using mahalanobis distance based outlier detection
- 2017
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Ingår i: Technical Gazette. - : Strojarski Facultet. - 1330-3651 .- 1848-6339. ; 24:5, s. 1597-1607
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Tidskriftsartikel (refereegranskat)abstract
- A huge amount of traffic data is archived which can be used in data mining especially supervised learning. However, it is not being fully used due to lack of accurate accident information (labels). In this study, we improve a Mahalanobis distance based algorithm to be able to handle differential data to estimate flow fluctuations and detect accidents and use it to support correcting and complementing accident information. The outlier detection algorithm provides accurate suggestions for accident occurring time, duration and direction. We also develop a system with interactive user interface to realize this procedure. There are three contributions for data handling. Firstly, we propose to use multi-metric traffic data instead of single metric for traffic outlier detection. Secondly, we present a practical method to organise traffic data and to evaluate the organisation for Mahalanobis distance. Thirdly, we describe a general method to modify Mahalanobis distance algorithms to be updatable. © 2017, Strojarski Facultet. All rights reserved.
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| 24. |
- Sun, Bin, et al.
(författare)
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Flow-Aware WPT k-Nearest Neighbours Regression for Short-Term Traffic Prediction
- 2017
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Ingår i: Proceedings - IEEE Symposium on Computers and Communications. - : Institute of Electrical and Electronics Engineers (IEEE). - 9781538616291 ; , s. 48-53
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Konferensbidrag (refereegranskat)abstract
- Robust and accurate traffic prediction is critical in modern intelligent transportation systems (ITS). One widely used method for short-term traffic prediction is k-nearest neighbours (kNN). However, choosing the right parameter values for kNN is problematic. Although many studies have investigated this problem, they did not consider all parameters of kNN at the same time. This paper aims to improve kNN prediction accuracy by tuning all parameters simultaneously concerning dynamic traffic characteristics. We propose weighted parameter tuples (WPT) to calculate weighted average dynamically according to flow rate. Comprehensive experiments are conducted on one-year real-world data. The results show that flow-aware WPT kNN performs better than manually tuned kNN as well as benchmark methods such as extreme gradient boosting (XGB) and seasonal autoregressive integrated moving average (SARIMA). Thus, it is recommended to use dynamic parameters regarding traffic flow and to consider all parameters at the same time.
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| 25. |
- Sun, Bin, 1988-, et al.
(författare)
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Short-Term Traffic Forecasting Using Self-Adjusting k-Nearest Neighbours
- 2018
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Ingår i: IET Intelligent Transport Systems. - : Institution of Engineering and Technology. - 1751-956X .- 1751-9578. ; 12:1, s. 41-48
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Tidskriftsartikel (refereegranskat)abstract
- Short-term traffic forecasting is becoming more important in intelligent transportation systems. The k-nearest neighbours (kNN) method is widely used for short-term traffic forecasting.However, kNN parameters self-adjustment has been a problem due to dynamic traffic characteristics. This paper proposes a fully automatic dynamic procedure kNN (DP-kNN) that makes the kNN parameters self-adjustable and robust without predefined models or training. We used realworld data with more than one-year traffic records to conduct experiments. The results show that DP-kNN can perform better than manually adjusted kNN and other benchmarking methods with regards to accuracy on average. This study also discusses the difference between holiday and workday traffic prediction as well as the usage of neighbour distance measurement.
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| 26. |
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| 27. |
- Zhu, Bin, et al.
(författare)
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Fundamental study on biomass-fuelled ceramic fuel cell
- 2002
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Ingår i: International Journal of Energy Research. - : Hindawi Limited. - 0363-907X .- 1099-114X. ; 26:1, s. 57-66
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Tidskriftsartikel (refereegranskat)abstract
- Recent development in the advanced intermediate temperature (400 to 700degreesC) ceramic fuel cell (CFC) research brings up feasibility and new opportunity to develop innovative biomass-fuelled CFC technology. This work focuses on fundamentals of the biomass-fuelled CFCs based on available biofuel resources through thermochemical conversion technologies. Both real producer gas from biomass gasification and imitative compounded gas were used as the fuel to operate the CFCs in the biomass CFC testing station. The composition of the fuel gas was varied in a wide range of practices of the present conversion technology both in KTH and Shandong Institute of Technology (SDIT), CFC performances were achieved between 100 and 700 mW cm(-2) at 600-800degreesC corresponding to various gas compositions. A high performance close to 400 mW cm(-2) was obtained at 600degreesC for the gas with the composition of H-2 (50 per cent) + CO (15 per cent) + CO2 (15 per cent) + N-2 (20 per cent) and more than 600 mW cm(-2) for the H-2 (55 per cent) + CO (28 per cent) + CO2 (17 per cent) at 700degreesC. This paper presents the experimental results and discusses the fundamentals and future potentiality on the biomass fuelled CFCs.
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| 28. |
- Zhu, Ying, et al.
(författare)
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Elevated Platelet Count Appears to Be Causally Associated with Increased Risk of Lung Cancer : A Mendelian Randomization Analysis
- 2019
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Ingår i: Cancer Epidemiology, Biomarkers and Prevention. - : American Association for Cancer Research (AACR). - 1055-9965 .- 1538-7755. ; 28:5, s. 935-942
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Tidskriftsartikel (refereegranskat)abstract
- Background: Platelets are a critical element in coagulation and inflammation, and activated platelets are linked to cancer risk through diverse mechanisms. However, a causal relationship between platelets and risk of lung cancer remains unclear. Methods: We performed single and combined multiple instrumental variable Mendelian randomization analysis by an inverse-weighted method, in addition to a series of sensitivity analyses. Summary data for associations between SNPs and platelet count are from a recent publication that included 48,666 Caucasian Europeans, and the International Lung Cancer Consortium and Transdisciplinary Research in Cancer of the Lung data consisting of 29,266 cases and 56,450 controls to analyze associations between candidate SNPs and lung cancer risk. Results: Multiple instrumental variable analysis incorporating six SNPs showed a 62% increased risk of overall nonsmall cell lung cancer [NSCLC; OR, 1.62; 95% confidence interval (CI), 1.15-2.27; P = 0.005] and a 200% increased risk for small-cell lung cancer (OR, 3.00; 95% CI, 1.27-7.06; P = 0.01). Results showed only a trending association with NSCLC histologic subtypes, which may be due to insufficient sample size and/or weak effect size. A series of sensitivity analysis retained these findings. Conclusions: Our findings suggest a causal relationship between elevated platelet count and increased risk of lung cancer and provide evidence of possible antiplatelet interventions for lung cancer prevention. Impact: These findings provide a better understanding of lung cancer etiology and potential evidence for antiplatelet interventions for lung cancer prevention.
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| 29. |
- Aad, G., et al.
(författare)
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- 2015
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Tidskriftsartikel (refereegranskat)
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| 30. |
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- 2019
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Tidskriftsartikel (refereegranskat)
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