Efficient production of d-lactate from methane in a lactate-tolerant strain of Methylomonas sp. DH-1 generated by adaptive laboratory evolution

Background Methane, a main component of natural gas and biogas, has gained much attention as an abundant and low-cost carbon source. Methanotrophs, which can use methane as a sole carbon and energy source, are promising hosts to produce value-added chemicals from methane, but their metabolic engineering is still challenging. In previous attempts to produce lactic acid (LA) from methane, LA production levels were limited in part due to LA toxicity. We solved this problem by generating an LA-tolerant strain, which also contributes to understanding novel LA tolerance mechanisms. Results In this study, we engineered a methanotroph strain Methylomonas sp. DH-1 to produce d-lactic acid (d-LA) from methane. LA toxicity is one of the limiting factors for high-level production of LA. Therefore, we first performed adaptive laboratory evolution of Methylomonas sp. DH-1, generating an LA-tolerant strain JHM80. Genome sequencing of JHM80 revealed the causal gene watR, encoding a LysR-type transcription factor, whose overexpression due to a 2-bp (TT) deletion in the promoter region is partly responsible for the LA tolerance of JHM80. Overexpression of the watR gene in wild-type strain also led to an increase in LA tolerance. When d form-specific lactate dehydrogenase gene from Leuconostoc mesenteroides subsp. mesenteroides ATCC 8293 was introduced into the genome while deleting the glgA gene encoding glycogen synthase, JHM80 produced about 7.5-fold higher level of d-LA from methane than wild type, suggesting that LA tolerance is a critical limiting factor for LA production in this host. d-LA production was further enhanced by optimization of the medium, resulting in a titer of 1.19 g/L and a yield of 0.245 g/g CH4. Conclusions JHM80, an LA-tolerant strain of Methylomonas sp. DH-1, generated by adaptive laboratory evolution was effective in LA production from methane. Characterization of the mutated genes in JHM80 revealed that overexpression of the watR gene, encoding a LysR-type transcription factor, is responsible for LA tolerance. By introducing a heterologous lactate dehydrogenase gene into the genome of JHM80 strain while deleting the glgA gene, high d-LA production titer and yield were achieved from methane.This work was supported by C1 Gas Refnery Program through the National Research Foundation of Korean (NRF) funded by the Ministry of Science and ICT (2016M3D3A01913245)

Magnetic Field-Based Vehicle Positioning System in Long Tunnel Environment

Recently, long tunnels are becoming more prevalent in Korea, and exits are added at certain sections of the tunnels. Thus, a navigation system should correctly guide the user toward the exit; however, adequate guidance is not delivered because the global navigation satellite system (GNSS) signal is not received inside a tunnel. Therefore, we present an accurate position estimation system using a magnetic field for vehicles passing through a tunnel. The position can be accurately estimated using the magnetic sensor of a smartphone with an appropriate attitude estimation and magnetic sensor calibration. Position estimation was realized by attaching the smartphone on the dashboard during navigation and calibrating the sensors using position information from the GNSS and magnetic field database before entering the tunnel. This study used magnetic field sequence data to estimate vehicle positions inside a tunnel. Furthermore, subsequence dynamic time warping was applied to compare the magnetic field data stored in the buffer with the magnetic field database, and the feasibility and performance of the proposed system was reviewed through an experiment in an actual tunnel. The analysis of the position estimation results confirmed that the proposed system could appropriately deliver tunnel navigation

Magnetic Field-Based Vehicle Positioning System in Long Tunnel Environment

Recently, long tunnels are becoming more prevalent in Korea, and exits are added at certain sections of the tunnels. Thus, a navigation system should correctly guide the user toward the exit; however, adequate guidance is not delivered because the global navigation satellite system (GNSS) signal is not received inside a tunnel. Therefore, we present an accurate position estimation system using a magnetic field for vehicles passing through a tunnel. The position can be accurately estimated using the magnetic sensor of a smartphone with an appropriate attitude estimation and magnetic sensor calibration. Position estimation was realized by attaching the smartphone on the dashboard during navigation and calibrating the sensors using position information from the GNSS and magnetic field database before entering the tunnel. This study used magnetic field sequence data to estimate vehicle positions inside a tunnel. Furthermore, subsequence dynamic time warping was applied to compare the magnetic field data stored in the buffer with the magnetic field database, and the feasibility and performance of the proposed system was reviewed through an experiment in an actual tunnel. The analysis of the position estimation results confirmed that the proposed system could appropriately deliver tunnel navigation

Monte Carlo simulation of secondary neutron dose for scanning proton therapy using FLUKA.

Proton therapy is a rapidly progressing field for cancer treatment. Globally, many proton therapy facilities are being commissioned or under construction. Secondary neutrons are an important issue during the commissioning process of a proton therapy facility. The purpose of this study is to model and validate scanning nozzles of proton therapy at Samsung Medical Center (SMC) by Monte Carlo simulation for beam commissioning. After the commissioning, a secondary neutron ambient dose from proton scanning nozzle (Gantry 1) was simulated and measured. This simulation was performed to evaluate beam properties such as percent depth dose curve, Bragg peak, and distal fall-off, so that they could be verified with measured data. Using the validated beam nozzle, the secondary neutron ambient dose was simulated and then compared with the measured ambient dose from Gantry 1. We calculated secondary neutron dose at several different points. We demonstrated the validity modeling a proton scanning nozzle system to evaluate various parameters using FLUKA. The measured secondary neutron ambient dose showed a similar tendency with the simulation result. This work will increase the knowledge necessary for the development of radiation safety technology in medical particle accelerators

Optimization of Proton CT Detector System and Image Reconstruction Algorithm for On-Line Proton Therapy.

The purposes of this study were to optimize a proton computed tomography system (pCT) for proton range verification and to confirm the pCT image reconstruction algorithm based on projection images generated with optimized parameters. For this purpose, we developed a new pCT scanner using the Geometry and Tracking (GEANT) 4.9.6 simulation toolkit. GEANT4 simulations were performed to optimize the geometric parameters representing the detector thickness and the distance between the detectors for pCT. The system consisted of four silicon strip detectors for particle tracking and a calorimeter to measure the residual energies of the individual protons. The optimized pCT system design was then adjusted to ensure that the solution to a CS-based convex optimization problem would converge to yield the desired pCT images after a reasonable number of iterative corrections. In particular, we used a total variation-based formulation that has been useful in exploiting prior knowledge about the minimal variations of proton attenuation characteristics in the human body. Examinations performed using our CS algorithm showed that high-quality pCT images could be reconstructed using sets of 72 projections within 20 iterations and without any streaks or noise, which can be caused by under-sampling and proton starvation. Moreover, the images yielded by this CS algorithm were found to be of higher quality than those obtained using other reconstruction algorithms. The optimized pCT scanner system demonstrated the potential to perform high-quality pCT during on-line image-guided proton therapy, without increasing the imaging dose, by applying our CS based proton CT reconstruction algorithm. Further, we make our optimized detector system and CS-based proton CT reconstruction algorithm potentially useful in on-line proton therapy

CNR results.

<p>CNR results.</p

Reconstructed images and profiles obtained using 200 MeV proton beam.

<p>These images were reconstructed by three different techniques. The RSP profiles were obtained using <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0156226#pone.0156226.e003" target="_blank">Eq 3</a> to compare with the ideal RSP profile for 200 MeV protons.</p

Non-scattered proton counts versus detector thickness.

<p>This graph shows the non-scattered proton counts for various detector thicknesses.</p

Number of protons incident on 50^th detector.

<p>Number of protons incident on 50^th detector.</p