Broad-specificity amino acid racemase, a novel non-antibiotic selectable marker for transgenic plants

Yi‑Chia Kuan,Venkatesan Thiruvengadam,Jia‑Shin Lin,Jia‑Hsin Liu,Tsan‑Jan Chen,Hsin‑Mao Wu,Wen‑Ching Wang,Liang‑Jwu Chen 한국식물생명공학회 2018 Plant biotechnology reports Vol.12 No.1

The broad-specificity amino acid racemase (Bsar) from Pseudomonas putida catalyzes the racemization of various amino acids, offering a flexible and feasible platform to develop a new non-antibiotic selectable marker system for plant transformation. In the present study, we demonstrated that a Bsar variant, Bsar-R174K, that is useful as a selectable marker gene in Arabidopsis and rice that were susceptible to l-lysine and D-alanine. The introduction of wild-type Bsar, Bsar-R174K or Bsar-R174A into E. coli lysine or asparagine auxotrophs was able to rescue the growth of these microorganisms in minimal media supplemented with selectable amino acid enantiomers. The transformation of Arabidopsis with Bsar or Bsar variants based on d-alanine selection revealed that Bsar-R174K had the greatest efficiency (2.40%), superior to kanamycin selectionbased transformation (1.10%). Whereas, l-lysine-based selection exhibited lower efficiency for Bsar-R174K (0.17%). The progenies of selected Bsar-R174K transgenic Arabidopsis revealed normal growth properties. In addition, Bsar-R174K transgenic rice was obtained on l-lysine medium with an efficiency of 0.9%, and the progenies of the transgenic rice revealed morphologically normal phenotypes comparable with their wild-type counterparts. This study presents the first report of broad range amino acid racemase Bsar-R174K as a non-antibiotic selectable marker system applied in transgenic plants.

Slide Session : OS-CAD-06 ; Cardiology : Erythrocytosis Increased One-Year Mortality in Patients with St-Segment Elevation Myocardial Infarction Un-dergoing Primary Percutaneous Coronary Intervention

( Cheng Wei Liu ),( Yi Ching Lin ),( Chung Ming Tu ),( Pen Chih Liao ),( Kuan Change Chen ),( Yen Wen Wu ) 대한내과학회 2014 대한내과학회 추계학술발표논문집 Vol.2014 No.1

Background: Anemia is associated with poor prognosis in patients with ST-segment elevation myocardial infarction(STEMI). However, it is unclear that erythrocytosis has protective effect in these populations. Hence, we conducted a retrospective cohort study to examine the relationship between erythrocytosis and mortality in patients with STEMI undergoing primary percutaneous coronary intervention (PCI ). Materials and Methods: We screened 1,156 consecutive patients with STEMI undergoing primary PCI in a single center during Feb 2007 and January 2012. There were 201 missing data for door-to-balloon time and 4 missing data for hemoglobin. Of 951 analyzable patients, they were divided into anemia (Hemoglobin<13.0mg/dl in men or <12.0mg/dl in women), normal hemoglobin, and erythrocytosis (hemoglobin =16.0mg/dl in men or =15.0mg/dl in women) groups. The study end point was one-year mortality. Results: There were 148, 535, and 268 patients in anemia, normal hemoglobin, and erythrocytosis groups, respectively. Patients in the anemia group were older and had lower body mass index than other two groups. There was more female, smokers, hypertension, and diabetes in the anemia group. One-year mortality rates were 16.2%, 6.5%, 2.6% (P<0.001) respectively. In univariate proportional hazards regression analysis, age, hemoglobin, total cholesterol, statin use, glycoprotein llb/llla inhibitor use, and TIMI risk score were associated with 1-year mortality in three groups. After adjustment for potential confounders, hemoglobin levels remained an independent predictor of one-year mortality in both anemia (hazard ratio 0.697, 95% CI 0.528-0.960) and erythrocytosis group (hazard ratio 3.129, 95% CI 1.1.474-6.642). Conclusions: Patients with STEMI and anemia had the worst outcomes than normal hemoglobin and erythrocytosis groups. Expectedly, hemoglobin had the protective effect on prognosis in anemia group. However, a hemoglobin level was an independent risk factor of one-year mortality in those with erythrocytosis.

Establishment of the Model Widely Valid for the Melting and Vaporization Zones in Selective Laser Melting Printings Via Experimental Verifications

Chang-Shuo Chang,Kuan-Ta Wu,Chang-Fu Han,Tsung-Wen Tsai,Sung-Ho Liu,Jen-Fin Lin 한국정밀공학회 2022 International Journal of Precision Engineering and Vol.9 No.1

The thermally affected material properties operating in the three phases and porosity variations in the SS316L steel powder have been introduced to the numerical analyses for the transient volumetric heat source (Q) models developed for the solid powder, melting, and vaporization regions in the selective laser melting (SLM). The bulk Q is thus a function of these heat sources and their ratio defined for the liquid and vapor phases. The heat conduction developed for the solid powders with porosity strings the heat convection with Q as the moving heat source to solve two-dimensional temperature distributions efficiently without the confinement of operating conditions and phase presumption. The specimens with single- and multiple-track printings are prepared to investigate the effects of incident energy density (E) and power intensity (I o) on the geometries of single-track printings and the areal surface roughness (Sa) values of the multiple-track printings with 0 and 50% overlap ratios. Laser power and scanning velocity are the controlling factors for the melting pool depth D and width W . D and W become the governing factors for the keyhole with evaporations, which affects the height H of single track after solidification. The W and D results predicted by the theoretical models developed in this study have an error range, 5–20%, compared to the experimental ones, which is much lower than those reported in the literatures (Gusarov et al. in J Heat Transf 131(7):072101, 2009. https ://doi.org/10.1115/1.31092 45 ; Hussein et al. in Mater Des 52:638–647, 2013. https ://doi.org/10.1016/j.matde s.2013.05.070 ; Yin et al. Int J Adv Manuf Technol 83(9–12): 1847–1859, 2016. https ://doi.org/10.1007/s0017 0-015-7609-x ; Andreotta et al. in Finite Elem Anal Des 135: 36–43, 2017. https ://doi.org/10.1016/j.finel .2017.07.002 ). The contact angle ( ϕ * ) is defined as a function of single-track width ( W ) and solidification height ( H ). ϕ * and Sa are significantly reduced as an E is applied beyond its critical value (47.62–57.14 J/mm 3 ). Significant change in Sa is ascribed to the big difference in the morphology and its surface pattern when E or I o reaches its critical value.

Smart Self-Checkout Carts Based on Deep Learning for Shopping Activity Recognition

Hong-Chuan Chi,Muhammad Atif Sarwar,Yousef-Awwad Daraghmi,Kuan-Wen Liu,Tsi-Ui ?k,Yih-Lang Li 한국통신학회 2020 한국통신학회 APNOMS Vol.2020 No.09

Fast and reliable communication plays a major role in the success of smart shopping applications. In a ”Just Walk Out” shopping scenario, a video camera is installed on the cart to monitor shopping activities and transmit images to the cloud for processing so that items in the cart can be tracked and checked out. This paper proposes a prototype of a smart shopping cart based on image-based action recognition. Firstly, deep learning networks such as Faster R-CNN, YOLOv2, and YOLOv2-Tiny are utilized to analyze the content of each video frame. Frames are classified into three classes: No Hand, Empty Hand, and Holding Items. The classification accuracy based on Faster RCNN, YOLOv2, or YOLOv2-Tiny is between 93.0% and 90.3%, and the processing speed of the three networks can be up to 5 fps, 39 fps, and 50 fps, respectively. Secondly, based on the sequence of frame classes, the timeline is divided into No Hand intervals, Empty Hand intervals, and Holding Items intervals. The accuracy of action recognition is 96%, and the time error is 0.119s on average. Finally, we categorize the events into four cases: No Change, placing, Removing, and Swapping. Even including the correctness of the item recognition, the accuracy of shopping event detection is 97.9%, which is higher than the minimal requirement to deploy such a system in a smart shopping environment. A demo of the system and a link to download the data set used in the paper are in Smart Shopping Cart Prototype or found at this URL: https://hackmd.io/abEiC83rQoqxz7zpL4Kh2w.