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( Yeo Seon Kwon ),( Seul Ki Min ),( Seung Ju Yeon ),( Jin Ha Hwang ),( Jae-sang Hong ),( Hwa Sung Shin ) 한국미생물 · 생명공학회 2017 Journal of microbiology and biotechnology Vol.27 No.4
A heteronemertean, Yininemertes pratensis, was collected in Han River Estuary, South Korea. This estuarine nemertean has been known by the local fishermen for harmful effects to the glass eels, juveniles of Japanese eel Anguilla japonica, migrating to fresh water. The present study confirmed the neurotoxic effects of this heteronemertean ribbon worm at the cellular level. Derivative types of neurotoxic tetrodotoxin (TTX), 5,11-dideoxy TTX (m/z 288) and 11- norTTX-6(S)-01 (m/z 305.97), were identified through HPLC and MALDI-TOF MS. However, significant neurotoxicity was confirmed in the fraction containing an undefined molecule corresponding to the 291.1 (m/z) peak, when tested in rat primary astrocytes and dorsal ganglion cells. This study is the first to report neurotoxins of the estuarine nemertean, fairly abundant in the Han River estuary, and suggests the long-term monitoring of population dynamics and surveillance of the toxicity in this river estuary.
Yeo, Hyeonjung,Lee, Dongkyu,Kim, Jin Soo,Eo, Pil Seon,Kim, Dong Kyu,Lee, Joon Seok,Kwon, Ki Tae,Lee, Jeeyeon,Park, Ho Yong,Yang, Jung Dug Korean Society of Plastic and Reconstructive Surge 2021 Archives of Plastic Surgery Vol.48 No.2
Background In recent years, implant-based breast reconstruction has been performed because of its simplicity, short operation time, and rapid recovery of patients. Several studies have reported treatment methods for implant surgery-related infection, which is a serious complication. The aim of this study was to introduce our strategy for salvaging infected implants and to evaluate its effectiveness. Methods The authors performed a retrospective study of 145 cases from 132 patients who underwent implant-based breast reconstruction from January 2012 to December 2018. Empirical antibiotics were immediately administered to patients with suspected infections. The patients then underwent salvage treatment including appropriate antibiotics, ultrasonography-guided aspiration, debridement, antibiotic lavage, and implant exchange through a multidisciplinary approach. Patient demographics, operative data, duration until drain removal, adjuvant treatment, and complications were analyzed. Results The total infection rate was 5.5% (8/145). A longer indwelling catheter period and adjuvant treatment were significantly associated with infection. The salvage treatment showed a success rate of 87.5% (7/8). Seven patients who received early aggressive salvage treatment recovered from infection. One patient with methicillin-resistant Staphylococcus aureus, who received salvage treatment 11 days after symptom onset, did not respond to drainage and antibiotic treatment. That patient subsequently underwent explantation. Conclusions In implant-based breast reconstruction, prevention of infection is of the utmost importance. However, if an infection is suspected, proactive empirical antibiotic therapy and collaboration with the necessary departments are required. Through a multidisciplinary approach and proactive early management, swift and appropriate salvage should be performed.
수산화라디칼 소모인자를 이용한 자외선, 과산화수소공정의 효율적인 운전 조건도출
김선백(Seon Baek Kim),권민환(Min Hwan Kwon),윤여준(Yeo Joon Yoon),정유미(You Mi Jung),황태문(Tae Mun Hwang),강준원(Joon Wun Kang) 大韓環境工學會 2014 대한환경공학회지 Vol.36 No.8
본 논문은 먹는물 처리공정에 적합한 고도산화공정 중 하나인 자외선/과산화수소공정의 효율적인 운전을 위한 최적운전 조건을 도출하는 방법을 연구하였다. 자외선/과산화수소 공정에서 대상물질의 제거효율을 예측하고 그에 따른 운전조건을 도출하기 위한 핵심 인자인 수산화라디칼 소모인자를 보다 쉽고 빠르게 측정하기 위해 새로운 지표물질인 로다민 비 (Rhodamin B, RhB)를 선정하여 검증하였다. 그 결과, 기존 지표물질인 para-Chlorobenzoic acid (pCBA)와 비교해 약 1.1% 이하의 오차율로 높은 신뢰성을 가진 것을 확인하였다. 검증된 RhB를 이용하여 측정한 수산화라디칼 소모인자 및 모델링을 통해 대상물질(Ibuprofen)의 제거효율 예측 가능성을 평가한 결과, 실제 실험값과 평균 오차율 약 5% 내외로 거의 일치하였다. 약 8개월간의 자외선/과산화수소공정 파일럿 플랜트 유입수의 수산화라디칼 소모인자 모니터링 결과, 최대 두 배 정도의 차이로 크게 변화하였다. 이 차이는 미량오염물질 중 하나인 Caffeine의 목표 제거율을 만족하기 위한 자외선 에너지를 약 1.7배 증가시켜야 할 정도로 큰 값이다. 이상의 결과를 통해 자외선/과산화수소 공정을 안전하고 효율적으로 운전하기 위해서는 수산화라디칼 소모인자의 측정이 매우 중요하며, 측정된 소모인자, 자외선 흡광도(A₂54), 대상물질의 정보만 입력하면 자외선/과산화수소 공정을 쉽게 제어할 수 있음을 확인하였다. This study investigated a method to determine an efficient operating condition for the UV/H₂O₂ process. The OH radical scavenging factor is the most important factor to predict the removal efficiency of the target compound and determine the operating condition of the UV/H₂O₂ process. To rapidly and simply measure the scavenging factor, Rhodamine B (RhB) was selected as a probe compound. Its reliability was verified by comparing it with a typical probe compound (para-chlorobenzoic acid, pCBA); the difference between RhB and pCBA was only 1.1%. In a prediction test for the removal of Ibuprofen, the RhB method also shows a high reliability with an error rate of about 5% between the experimental result and the model prediction using the measured scavenging factor. In the monitoring result, the scavenging factor in the influent water of the UV/H₂O₂ pilot plant was changed up to 200% for about 8 months, suggesting that the required UV dose could be increased about 1.7 times to achieve 90% caffeine removal. These results show the importance of the scavenging factor measurement in the UV/H₂O₂ process, and the operating condition could simply be determined from the scavenging factor, absorbance, and information pertaining to the target compound.
( Hye Seon Kang ),( Sang Haak Lee ),( Ah Young Shin ),( Chang Dong Yeo ),( Chan Kwon Park ),( Ju Sang Kim ),( Yong Hyun Kim ),( Jin Woo Kim ),( Seung Joon Kim ) 대한결핵 및 호흡기학회 2020 대한결핵 및 호흡기학회 추계학술대회 초록집 Vol.128 No.-
Backgrounds The Glasgow prognostic score (GPS) reflects the host systemic inflammatory response and is validated prognostic factor in lung cancer. However, little is known about the prognostic role in NSCLC patients with immunotherapy after platinum-based cytotoxic chemotherapy. Methods This study used a lung cancer cohort of the Catholic Medical Center of Korea between January 2018 and June 2020. We included the patients who were diagnosed with unresectable advanced stage non-small cell lung cancer (NSCLC) or recurrent disease after pulmonary resection and had received at least one regimen of platinum-based chemotherapy before being administered immunotherapy. The patients with NSCLC treated with anti-PD1 or anti-PD-L1 (pembrolizumab, nivolumab, or atezolizumab) and assessed the prognostic value of the GPS. The GPS was calculated using C-reactive protein and albumin concentrations within 1 week before starting anti-PD1 or anti-PD-L1 treatment. Results A total of 78 patients with NSCLC treated with immunotherapy as 2nd or 3rd line therapy after platinum-based chemotherapy. Kaplan-Meier analyses revealed that higher GPS was significant predictors of shorter PFS (Log rank < 0.001) and OS (Log rank < 0.001) (Fig 1). In cox-regression multivariate analysis, the hazard ratios for disease progression were 2.146 (95% CI: 0.814-5.656; P = 0.123) for a GPS of 1 and 9.73 (95% CI: 2.931-32.298, P < 0.001) for a GPS of 2 relative to a GPS of 0. Older age (P = 0.033), lower PD-L1 expression (P = 0.036) and higher GPS (P = 0.007) were independently associated with shorter OS. Conclusion Higher GPS were identified as one of poor prognostic factor for OS and PFS in NSCLC patients received immunotherapy as 2nd or 3rd line therapy after platinum-based chemotherapy.
Prediction of Postoperative Lung Function in Lung Cancer Patients Using Machine Learning Models
( Oh Beom Kwon ),( Solji Han ),( Hwa Young Lee ),( Hye Seon Kang ),( Sung Kyoung Kim ),( Ju Sang Kim ),( Chan Kwon Park ),( Sang Haak Lee ),( Seung Joon Kim ),( Jin Woo Kim ),( Chang Dong Yeo ) 대한결핵 및 호흡기학회 2023 Tuberculosis and Respiratory Diseases Vol.86 No.3
Background: Surgical resection is the standard treatment for early-stage lung cancer. Since postoperative lung function is related to mortality, predicted postoperative lung function is used to determine the treatment modality. The aim of this study was to evaluate the predictive performance of linear regression and machine learning models. Methods: We extracted data from the Clinical Data Warehouse and developed three sets: set I, the linear regression model; set II, machine learning models omitting the missing data: and set III, machine learning models imputing the missing data. Six machine learning models, the least absolute shrinkage and selection operator (LASSO), Ridge regression, ElasticNet, Random Forest, eXtreme gradient boosting (XGBoost), and the light gradient boosting machine (LightGBM) were implemented. The forced expiratory volume in 1 second measured 6 months after surgery was defined as the outcome. Five-fold cross-validation was performed for hyperparameter tuning of the machine learning models. The dataset was split into training and test datasets at a 70:30 ratio. Implementation was done after dataset splitting in set III. Predictive performance was evaluated by R<sup>2</sup> and mean squared error (MSE) in the three sets. Results: A total of 1,487 patients were included in sets I and III and 896 patients were included in set II. In set I, the R<sup>2</sup> value was 0.27 and in set II, LightGBM was the best model with the highest R<sup>2</sup> value of 0.5 and the lowest MSE of 154.95. In set III, LightGBM was the best model with the highest R<sup>2</sup> value of 0.56 and the lowest MSE of 174.07. Conclusion: The LightGBM model showed the best performance in predicting postoperative lung function.