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Introduction: In metabolic engineering and synthetic biology applications, promoters with appropriate strengths are critical. However, it is time-consuming and laborious to annotate promoter strength by experiments. Nowadays, constructing mutation-based synthetic promoter libraries that span multiple orders of magnitude of promoter strength is receiving increasing attention. A number of machine learning (ML) methods are applied to synthetic promoter strength prediction, but existing models are limited by the excessive proximity between synthetic promoters. Methods: In order to enhance ML models to better predict the synthetic promoter strength, we propose EVMP(Extended Vision Mutant Priority), a universal framework which utilize mutation information more effectively. In EVMP, synthetic promoters are equivalently transformed into base promoter and corresponding k-mer mutations, which are input into BaseEncoder and VarEncoder, respectively. EVMP also provides optional data augmentation, which generates multiple copies of the data by selecting different base promoters for the same synthetic promoter. Results: In Trc synthetic promoter library, EVMP was applied to multiple ML models and the model effect was enhanced to varying extents, up to 61.30% (MAE), while the SOTA(state-of-the-art) record was improved by 15.25% (MAE) and 4.03% (R2). Data augmentation based on multiple base promoters further improved the model performance by 17.95% (MAE) and 7.25% (R2) compared with non-EVMP SOTA record. Discussion: In further study, extended vision (or k-mer) is shown to be essential for EVMP. We also found that EVMP can alleviate the over-smoothing phenomenon, which may contributes to its effectiveness. Our work suggests that EVMP can highlight the mutation information of synthetic promoters and significantly improve the prediction accuracy of strength. The source code is publicly available on GitHub: https://github.com/Tiny-Snow/EVMP.
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INTRODUCTION: The aim of this study was to describe the most recent trends and epidemiologic patterns of fatal injuries resulting from explosions in Iraq, one of the countries most affected by violence from explosive devices. METHODS: Iraqi Ministry of Health (MoH) routine prospective injury surveillance collects information on all fatal injuries recorded by coroners from physical examinations, police reports, and family members in eight governorates of Iraq: Baghdad, Al-Anbar, Basrah, Erbil, Kerbala, Maysan, Ninevah, and Al-Sulaimaniya. This study analyzed explosive-related fatal injuries that occurred from January 1, 2010 through December 31, 2013. RESULTS: Analysis included 2,803 fatal injuries. The number of fatal injuries declined from 2010 through 2012, followed by an increase in 2013. One-thousand one-hundred and one explosion-related fatalities were documented in 2013, more than twice as many as in 2012 or in 2011. Most fatalities were among men aged 20-39 years. Of all causalities, 194 (6.9%) were among females and 302 (10.8%) were among children aged less than 18 years. The majority of fatalities were caused by improvised explosive devices (IEDs): car bombs (15.3%), suicide bombs (4.0%), and other IEDs (29.6%). The highest number of fatalities occurred in streets and roads. Of all deaths, 95.6% occurred in three governorates: Baghdad, Ninevah, and Al-Anbar. CONCLUSIONS: Explosives continue to result in a high number of fatal injuries in Iraq. Following a period of declining violence from explosives, in 2013, fatalities increased. Most explosion-related injuries resulted from IEDs; males aged 20-39 years were at greatest risk.