Salmonella는 전 세계적으로 위장관 질환을 일으키는 주 요 식중독 원인균 중 하나이다. 본 연구에서는 국내 유통 닭고기에서 분리된 Salmonella enterica subsp. enterica serovar Enteritidis (S. Enteritidis) IJCS4-13 균주에 대해 WGS를 이용한 유전체 분석을 진행하였다. 해당 균주의 유전체는 4,678,812 bp 크기의 원형 염색체 (G+C 함량 52.17%)와 59,372 bp 크기의 플라스미드 (G+C 함량 51.96%)로 구성되어 있었다. 유전체 분석 결과, 총 147개 의 병원성 관련 유전자를 확인하였다. 이들 유전자는 부 착, 침입, 대식세포 내 생존, 스트레스 적응 등 다양한 병 원성 기전에 관여하는 것으로 알려져있다. 따라서 본 균 주는 다수의 병원성 인자를 보유하고 있어 높은 독력 잠 재력을 지니고 있음을 시사한다. 본 연구에서 보고한 유 전체 정보는 S. Enteritidis의 병원성 메커니즘 규명 및 식 품 매개 감염병 관리에 중요한 기초 자료를 제공할 것이다.

With a view towards reducing traffic accidents on roadways, various methods have been considered to predict accidents. In this study, we analyze traffic accident frequency models that employ fixed- and random-parameter negative binomial approaches. Random parameters enable the inclusion of unobserved heterogeneity in traffic accident data, which current popular methods with fixed parameters such as Poisson or negative binomial models cannot consider in terms of time variation or segment-specific effects. A continuous, unbalanced panel of accident histories for 208 four-way signalized intersections on national highways in Seoul was used to estimate a traffic accident occurrence model that considered traffic volumes and various geometric characteristics at intersections. The results revealed that the left-turn exclusive lanes and traffic volumes on minor roads had random parameters that affected the likelihood of accident frequencies differently; the other variables were found to significantly affect traffic safety at the intersections on the national highways as fixed parameters. Based on these results, it can be concluded that the same traffic safety facilities have different effects on traffic accidents on major and minor roads. The insights from this study suggest the need for a broader analysis of integrated guidelines for facilities that impact intersection accident propensities.

Background: Stroke patients commonly suffer from balance impairments that limit functional activities, such as walking difficulties. Robot-assisted gait training is gaining attention as an effective rehabilitation strategy for balance and gait in stroke rehabilitation. Objects: The purpose of this study was to investigate the effects of progressive velocity robot-assisted gait training (PRG) on balance and gait abilities in stroke patients. Methods: All subjects were randomly divided into three groups: PRG (n = 12); comfortable speed robot-assisted gait training (CRG) (n = 12); and control group (n = 16). Subjects in PRG and CRG underwent robot-assisted gait training for 30 minutes, three times a week for six weeks. And the control group performed overground gait training using a treadmill at the same frequency and for the same amount of time as the experimental group. All Subjects were assessed for muscle strength, balance, gait and motor function pre- and post-intervention. Results: The study results showed that all subjects showed significant differences in all measurements post-intervention (p < 0.05). Additionally, PRG was found to significantly improve in Medical Research Council (MRC) and Fugl-Meyer Assessment (FMA) compared to CRG, and CRG showed significant differences compared to the control group in MRC, Berg Balance Scale (BBS) and Timed Up and Go test (TUG) (p < 0.05). PRG exhibited significant differences in all areas in the between-group comparison with the control group (p < 0.05). Conclusion: These results suggest that PRG may be effective strategy to improve balance and gait ability for with stroke.